Assessing Business Models Arising from the Integration of
Distributed Energy Systems in the Chilean Electric Power System
by
Jorge I. Le Dantec
Master in Finance, Universidad de los Andes, Chile (2011)
Bachelor of Science in Industrial Engineering, Universidad de los Andes, Chile (2005)
SUBMITTED TO THE SYSTEM DESIGN AND MANAGEMENT PROGRAM IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF
Master of Science in Engineering and Management
A____
at the
Massachusetts Institute of Technology
January 2014
JUN 2 6 2014
LIBRARIES
@ 2014 Massachusetts Institute of Technqjogy. All rights reserve d.
Signature redacted
Signature of Author
y (emYesign and Management Program
January 16, 2014
Certified by
S
ignature redacted
Professor Jose Ignhcio Perez Arriaga
Thesis Supervisor
ivir
Vising Professor
Engineering Sys
Accepted by
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MASSACHUSETTr WNS IUTE.
OF TECHNOLOGY
Sign~3ture redacted,
Patrick Hale
Director
System Design and Management Program
Assessing Business Models Arising from the Integration of
Distributed Energy Systems in the Chilean Electric Power System
by
Jorge 1. Le Dantec
Abstract
Electric power systems are more than just networks of generation,
transmission and distribution assets. They are socio-technical systems, involving
regulation, markets and technology availability. Presently, the dynamic relation
among these aspects is creating new consumer needs in many power systems
around the world, which incumbent electricity utilities do not seem well suited to
meet at the required pace. In this context, the integration of Distributed Energy
Systems (DESs) and their related business models appears as a flexible and often
more affordable option to deliver value, by fulfilling the unmet needs of both
consumers and utilities.
To advice Chilean electric power system's stakeholders about the adequacy
of a set of DES-related business models to Chilean needs, this document presents a
systematic analysis, which focuses on the interrelation between business model
attributes, involved DES technologies, and stakeholder needs. Specifically, an
analytic framework is developed and applied to some business models currently
operative in other markets, measuring their adequacy to meet stakeholders' needs
in a set of envisioned scenarios of Chile's power system.
This work provides a systematic tool for decision-making processes in
selecting business models, when the decision must be made with qualitative data.
Moreover, the evaluation in the Chilean system of actual business models shows
results that should be valuable for consumers, utilities, and regulators.
Thesis Supervisor: Professor Jose Ignacio P6rez Arriaga
Title: Visiting Professor, Engineering Systems Division
3
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4
Acknowledgments
As this thesis marks the end of an incredibly enriching experience at MIT, I would
like to show my gratitude to some of the people that made this possible.
I want to deeply thank Professor Pat Hale and the SDM staff, for their trust and
support in academic guidance, extracurricular activities and personal matters.
This support network was also formed by my SDM fellows, an amazing group of
people that were always willing to help. Special thanks to Jorge Moreno, who was
always willing to share his knowledge in Systems and Energy, the main focus of my
studies at MIT.
I am also greatly indebted to my advisor, Professor Ignacio P6rez Arriaga, and the
working team of the "Utility of the Future" project at the MIT Energy Initiative: Dr.
Richard Tabors, Professor Carlos Batlle, and my teammates Ashwini Bharatkumar
and Jesse Jenkins. The great experience that I had at the "Utility of the Future"
project, which gave context to this thesis, was forged by the discussions and
learning acquired by working with this astounding team of professionals and
academics.
My heartfelt gratitude to my parents, for their generous support whenever it was
needed. This endeavor would not have been possible without their help.
Finally, I want to express my deepest gratitude to my wife, Maria Isabel. It is not
easy to find words to thank such an unconditional commitment, shown everyday by
taking care of our children and myself, becoming the cornerstone of our family
during these years at MIT.
5
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6
Table of Contents
LIST OF FIGURES
9
LIST OF TABLES
10
CHAPTER 1- INTRODUCTION
11
1.1 Context & Motivations
11
The role of energy challengesforChilean development
11
Real concerns of utilities
13
The "Utility of the Future" project
14
1.2 Research Approach and Thesis Scope
15
1.3 Objectives and Thesis Roadmap
16
1.4 Acronyms and Definitions
19
CHAPTER 2 - SYSTEMIC APPROACH TO DISTRIBUTED ENERGY SYSTEMS
20
2.1 Distributed Energy Systems (DESs)
What is a DistributedEnergy System?
DistributedEnergy Systems' Components
DistributedEnergy Systems in the Grid
20
20
21
22
2.2 The Expected Role of DESs in Electric Power Systems' Dynamics
23
2.3 DES Business Models Analytic Framework [BMAF]
"Matrix1 ": Business Model Attributes vs. DES Technology Components
"Matrix2": Business Model Attributes vs. Consumer and Utility Needs
25
26
27
CHAPTER 3 - DESS IN THE CHILEAN ELECTRIC POWER SECTOR
28
3.1 Chile: Geography and Economics
The Northern Region
The Centraland Southern Regions
Patagonia& Austral Regions
28
28
29
30
3.2 Chilean Electric Power Sector
ElectricPower Systems in Chile
Structure of the Electric Power Sector
Regulatory Entities and System Operators
31
31
33
34
7
3.3 Distribution-End of the Chilean Electric Power Sector
36
3.4 Integration of DESs under the Current Scenario
Effects Involving Technology-Related Factors
Effects Involving Regulatoiy Factors
Effects Involving Socio-Economic Factors
37
39
40
42
3.5 Integration of DESs under Foreseeable Scenarios
Change Drivers and FutureScenario Projection
Future Scenariosfor DES In teg ration
43
43
44
CHAPTER 4 - BUSINESS MODELS FOR DISTRIBUTED ENERGY SYSTEMS
45
4.1 Business Model Analysis
Energy Suppliers
Energy Demand Managers
DES Enablers
45
46
50
52
4.2 Overall Analysis
57
CHAPTER 5 - BUSINESS MODELS EVALUATION
61
5.1 Quantitative Evaluation of Qualitative Data
Relative Need's Weights and Business Model's Need Fulfillment Scores
Feasibilityand Challenges of the Business Models in the Chilean Context
61
62
67
5.2 Pugh's Method Output
70
CHAPTER 6 - CONCLUSIONS AND RECOMMENDATIONS
73
6.1 Conclusions
73
6.2 Recommendations
Recommendations To Consumers, DES Administrators,or DES Entrepreneurs
Recommendations To Incumbent Utilities
Reconnendations To Regulators
76
76
77
80
6.3 Further Work
82
REFERENCES
83
APPENDICES
85
Appendix A: DNV KEMA's Microgrid Optimizer Tool for Valuation of DESs' Impact 85
87
Appendix B: Calculation Tablesfor Business Model's Need FulfillmentScores
8
List of Figures
Figure
Figure
Figure
Figure
Figure
Figure
Figure
2-1:
2-2:
3-1:
3-2:
3-3:
4-1:
5-1:
Different DES Topologies........................................................................................
20
Layers of DES Technologies..................................................................................
21
Map of Chilean Electric Power Systems ............................................................
32
Current Chilean Electric Power System's Stakeholders Diagram.........35
Distribution Value Added (Rudnick, 2009) ...................................................
37
Aggregation of Business Models Over a "Matrix 1" Table ........................ 57
Factors that affect DER/DES Consumer Adoption.......................................67
9
List of Tables
T able 1-1: A cronym s..............................................................................................................................19
Table 2-1: B M A F's "M atrix 1".............................................................................................................
26
Table 2-2: BMAF's "Matrix 2".............................................................................................................
27
Table 3-1: Eight Scenarios for the Chilean Electric Power Sector ................................
44
T able 4-1: T IL's "M atrix 1"..................................................................................................................
46
T able 4-2: T IL's "M atrix 2"..................................................................................................................
46
Table 4-3: Solar City's "Matrix 1" ...............................................................................................
48
Table 4-4: Solar City's "Matrix 2" ...............................................................................................
48
Table 4-5: Konterra's "Matrix 1"..................................................................................................
49
Table 4-6: Konterra's "Matrix 2" ............................................
49
Table 4-7: EnerNOC's "Matrix 1"..................................................................................................50
Table 4-8: EnerNOC's "Matrix 2"..................................................................................................
51
Table 4-9: Opower's "Matrix 1"...................................................................................................
51
52
Table 4-10: Opower's "Matrix 2" ................................................................................................
53
Table 4-11:WeatherBug's "Matrix 1"........................................................................................
Table 4-12: WeatherBug's "Matrix 2"........................................................................................
53
Table 4-13: Energy Aware's "Matrix 1" ....................................................................................
54
Table 4-14: Energy Aware's "Matrix 2" ....................................................................................
54
Table 4-15: Sequentric's "Matrix 1" ..........................................................................................
56
Table 4-16: Sequentric's "Matrix 2" ..........................................................................................
56
Table 4-17: 8 Business Models' Aggregated "Matrix 2"....................................................
59
Table 5-1: Base Scenario's Ranking of Needs' Relevance.................................................
63
Table 5-2: Base Scenario Needs' Weights................................................................................
63
Table 5-3: 8 Scenarios' Consumer Needs' Weights ...........................................................
64
Table 5-4: Consumer Needs' Fulfillment Scores of the 8 Business Models .............. 65
Table 5-5: Utilities Needs' Fulfillment Scores of the 8 Business Models ................... 65
Table 5-6: Rationale of Consumer Needs' Fulfillment Scores.........................................
66
Table 5-7: Rationale of Utilities Needs' Fulfillment Scores..............................................
66
Table 5-8: Feasibility Scores of the 8 Business Models......................................................69
Table 5-9: Scenario 1 Consumers Needs' Weighting Table ..............................................
70
Table 5-10: Scenario 1 Needs' Weighted Fulfillment Scores ...........................................
70
Table 5-11: Need Fulfillment Scores for the 8 Business Models in the 8 Scenarios.. 71
Table 5-12: Need Fulfillment Scores Considered "Good" (>= 1.50 points)............... 71
Table 5-13: Feasible Business Models that Fulfill Stakeholder's Needs .................... 72
Table 6-1: Regulated Distribution Utility's Opportunities and Challenges in DESs'
B u sin ess M od els ............................................................................................................................
79
10
Chapter 1 - Introduction
1.1 Context & Motivations
The role of energy challengesfor Chilean development
Throughout my life -and particularly during my working years- I have experienced
the crucial role of electricity in nearly all of the activities required for the
development of Chile, my country. I witnessed the blackouts due to droughts in the
late 90's, I realized the relevance of electric power in the cold chain of Chilean
exports (like fruits or salmon that are a relevant part of them) while working in the
Port of Valparaiso, and I observed the fleeing of foreign investment due to its
uncompetitive costs when analyzing new manufacturing plant locations while
working in finance for a consumer goods company.
Nowadays, the scenario has become even more complicated. Though there has been
some progress in regulation, penetration of renewables and short-term security of
supply', there are still many issues related to long-term security of supply 2 and
transmission lines' deployment. These issues have primarily a socio-technical
nature, as they derive from the constant increase of electricity demand in Chile (5%
aggregate rate according to Comisi6n Nacional de Energia [CNE] (2013), requiring
doubling the supply every fourteen years), and from the enhanced environmental
consciousness that has many generation projects -hydroelectric, thermoelectric,
eolic, etc.- stuck in environmental impact evaluations and in the judicial system.
The effect of the scenario described above is highly harmful to Chile's development.
The lack of new hydro buffers increases the risks of energy scarcity due to droughts.
As Chile imports practically all its gas, coal, and oil supplies for power generation,
1 "[S]hort-term energy security focuses on the ability of the energy system to react promptly to
sudden changes in the supply-demand balance(IEA, 2014).
2 "[L]ong-term energy security is mainly linked to timely investments to supply energy in line with
economic developments and environmental needs" (lEA, 2014).
11
fossil fueled alternative to hydropower is much more expensive (not even
mentioning its environmental effects). This combination has a direct effect on the
cost at which electricity is traded, and on its retail price.
This high cost of electricity has a strong impact on the Chilean economy's
competitiveness. Its immediate effect can be seen in the present competitiveness of
the manufacturing industry, whose expensive outputs affect not only exports but
also import-substitution activities. The effects of this competitive issue could range
from the discouragement of investment in electric machinery that could increase
productivity in small businesses, to a lack of development of added-value
manufacturing industry. An additional effect produced by high costs of electricity is
the reduction of the Net Present Value of electricity-based projects in diverse
industrial sectors like Transport, Agriculture, Manufacturing, or Services. This
means that alternative solutions, which may not be as adequate, could be chosen
just because of electricity's high price.
What is interesting about the Chilean case is that it has a huge potential for hydro
and solar power, as well as great opportunities for wind and geothermal power too.
This shows that Chile faces a problem much more complex than sitting supply and
demand on the same table and making them talk. The solution requires a systemic
approach considering all involved stakeholders in a holistic view, which generates a
comprehensive value proposition based on needs, motivations, and capabilities.
The interest to develop that systemic view -applied to complex socio-technical
problems- as well as the possibility of having access MIT's experience in Energy,
were my main motivations to apply to MIT's Systems Design and Management
Program3 for my Master's studies. My goal is to apply the combined knowledge of
Energy and Systems to address some of the challenges of the Chilean power system.
3 http://sdm.mit.edu
12
Real concerns of utilities
The changes currently taking place in the electric power sector are unprecedented
and might be the most disruptive changes in the last 50 years or so. New
developments in Distributed Energy Resources [DERs] and in Information and
Communication Technologies [ICT], have led to the proliferation of Distributed
Energy Systems [DESs] mixing the best of both technological fields. These new DESs
are being utilized by innovative businesses, which articulate a series of value
propositions addressing previously unmet needs.
So, change is here, and traditional utilities acknowledge that they are standing on
the "wrong side of the road" when talking about value creation and new profit
opportunities. Even further, utilities understand that sticking to their upstream-ofthe-meter business model, might cause a value migration to innovative business
models, and that sales volume reduction might affect their revenues to a point
where they may not be able to pay for their stranded assets' loans.
Faced with this unfavorable scenario, utilities -as ROI-maximizing companies 4 have been focused on three tasks: increasing incomes, decreasing expenses, and
reducing risk. To increase incomes, they have been lobbying with regulators to get a
fair (or sometimes "more than fair") regulation and remuneration, which is more
suitable for new trends like penetration of residential distributed generation [DG].
To decrease expenses, they have been looking for cheaper energy sources. Finally, to
reduce risk, some of them have been evaluating portfolio diversification by getting
involved in new businesses emerging as result of the changing environment.
This thesis aims to understand the changing system's environment and to advise
stakeholders of electric power systems [EPSs] on potential business models that
might arise in the scenario of a large penetration of DESs in Chile.
4 ROI: Return on Investment
13
The "Utility of the Future" project
A relevant factor for this thesis, which was vital for its development, was my
appointment as Research Assistant for the "Utility of the Future" project. Between
the months of May of 2013 and January of 2014, I worked for this project of MIT
Energy Initiative, in partnership with the Institute for Research in Technology (1IT)
of Pontifical University of Comillas, and sponsored by ENEL 5 . This research gave me
the opportunity to share knowledge, points of view and resources with a select team
of professors, researchers and professionals from the United States, Spain, and Italy.
The outcome of this experience was not only interesting insights into the specifics of
my thesis research. It also provided me a broad view of different approaches used to
address power systems' issues in different countries. This helped me comprehend
the complexity of the electric power sector as a sociotechnical system whose longterm evolution is strongly driven, not only by technologies, regulation and business
models, but also by consumers' needs and their not-always rational behavior.
The variety of ways in which the previously mentioned drivers can be combined in a
particular power system, results in having optimal system's structures that are
unique for each one of them. This means that technological solutions, innovative
business models or regulatory best practices should not be exported from one
geography to another without a sound analysis, as any singularity of a system might
change drastically the objective function to be optimized.
Based on that last premise, I decided to analyze electric power systems from a scope
broader than the usual technical approach, aiming to understand the social and
technical systems involved in EPSs, their interaction and evolution. Then, after
identifying the factors to be considered when introducing DESs into other systems
or countries, I performed an assessment of the suitability of 8 businesses in the
context of the Chilean EPSs' future envisioned needs.
5 ENEL: largest Italian
electric utility (www.enel.com).
14
1.2 Research Approach and Thesis Scope
This thesis' research is based and inspired on what might be the most distinctive
characteristics of the System Design and Management (SDM) program: holistic
approach and systems thinking. Consequently, the applied research approach
highlights the relevance of understanding the salient factors and stakeholders on
the analyzed system as well as their interaction and dynamics. This also means
going beyond the usual fields of engineering, acknowledging that the most
challenging systems usually are not just technical systems, but socio-technical ones.
In practical terms, this approach tells us that, even when EPSs might have been
historically analyzed through the lens of electrical engineers, they are in fact sociotechnical systems. It can be seen that much of the complexity in electric power
systems is not an effect of advanced technical or technological structures, but a
result of the interaction with social systems, which involve users, regulators and
markets. In such context, the relation with individuals, organizations and technical
systems has to be addressed in the solution search process, no matter whether this
interaction takes place inside the system boundaries or across them.
The paragraph above presents what should be the main drivers for the scope of this
thesis, in order to be aligned with the research approach: focus on the Chilean
electric distribution system's consumers and utilities, as its most salient
stakeholders upstream and downstream the meter, to whom DESs' integration may
add more or less value by fulfilling their unmet needs.
Most of the theoretical background of the different parts of this research was
acquired by the author during his graduate studies at MIT. Maybe the most relevant
ones come form the "Utility of the Future" project, and from the following courses of
the Engineering Systems Division: "Systems Architecture", "Systems Dynamics", and
"Engineering, Economics and Regulation of the Electric Power Sector".
15
1.3 Objectives and Thesis Roadmap
As stated in the previous pages, the general objective of this thesis is to develop a
systematic analysis of the socio-technical dimensions of electric power systems.
This in order to assess Chilean EPS' stakeholders on the adequacy of different DESrelated business models in a set of envisioned future scenarios.
The following paragraphs present each of this document's chapters and their
particular objectives, serving as a roadmap of the thesis work.
Chapter1 - Introduction
The objective of Chapter 1 -as it could be expected from an introductory
chapter- is to present the author's motivations to develop this thesis, plus
the basic information about the work's scope, research approach, structure
and objectives. This chapter also aims to introduce some key concepts that
are recurrently used in the electric distribution sector and in DESs.
Chapter2 - Systems Approach to DistributedEnergy Systems
Being EPSs complex socio-technical systems, System Thinking theories and
tools must be part of the analysis, in order to generate a holistic
understanding of EPSs. Chapter 2 approaches this complexity presenting
DESs, their different parts, the interactions between these parts, and
potential effects of DESs' introduction in the change dynamics of the EPSs as
a whole. The objective pursued is to present a clear idea of the challenges and
opportunities of DESs in the evolutionary process of EPSs. Besides presenting
DESs, this chapter aims to state their relevance in future power systems as
entities that create value (and generate value migration) by addressing
unmet need of consumers and other power systems' stakeholders. In that
same direction, this chapter will present a framework to analyze DES-related
business models and their value propositions.
16
Chapter3 - DistributedEnergy Systems in the Chilean Electric Power Sector
Chapter 3's objective is to present an overview of Chile, its electric power
sector, and in particular, the distribution-end of Chilean EPS. This
information will set the context for the theoretical analysis of the
introduction dynamics of DESs in the Chilean context. Based on a CausalLoop diagram 6 presenting the Chilean context of the DER/DES Consumer
Adoption dynamics, the goal will be centered in identifying the factors and
particularities that could affect the implementation and adoption of DESs,
given the current trends in consumer needs, technology development, and
regulatory innovation, etc. Once the factors that more likely affect DES
implementation are identified, a set of foreseeable scenarios will be
generated in order to evaluate the different DES-related business models,
which will be presented in Chapter 4 and evaluated in Chapter 5.
Chapter4 - Business Modelsfor DistributedEnergy Systems
As a combined outcome of Chapter 2 and Chapter 3, this chapter identifies
those systemic characteristics that should be drivers of change in the future
Chilean context. Then it envisions how different evolutions of those drivers
could generate different scenarios and needs. The goal then for Chapter 4, is
to present and analyze 8 DES-related business models, trying to assess their
suitability to fulfill the needs of the envisioned scenarios presented in
Chapter 3. The analyses will be based in the framework introduced at the end
of Chapter 2. Chapter 4 will also present the trends and commonalities that
could be identified among the 8 business models, as well as an overview of
the challenges or constraints that they must overcome in order to be
successful.
6 System Dynamics theory.
17
Chapter5 - Business Models Evaluation
Based on the scenarios derived from Chapter 3, this chapter will perform a
qualitative/quantitative analysis of the business models' list presented in
Chapter 4. This analysis will be based on the Pugh Method, a decision-making
method commonly used in Systems Architecture and Systems Engineering as
concept selection tool to manage qualitative data. The objective is to assess
their viability and adequacy to the Chilean context, ranking their comparative
performance in each of the needs required by the envisioned scenarios. The
outcome of the analysis would be the identification of the business models
that seem more likely to succeed in the envisioned future of the Chilean
electricity distribution system.
Chapter 6 - Conclusions and Recommendations
The final task of this thesis is to generate a set of conclusions and
recommendations regarding the integration of DESs, which could be helpful
to maximize the value added by DESs' integration to the system as a whole.
The conclusions may not be limited to the context of the Chilean EPS, as they
should refer to the interaction between technology, business models,
regulation and customers needs in dynamic socio-technical systems like
electric power distribution systems. Recommendations will be centered in
advising consumers, DES administrators, DES entrepreneurs, utilities and
regulators regarding best practices in DES and DES-related business models'
implementation in the Chilean EPS.
18
1.4 Acronyms and Definitions
Throughout this document a list of acronyms and concepts will be recurrently
utilized. As these may be related to electric power systems, distributed energy
systems, Chilean entities, etc. that the reader might not be familiar with, this section
presents most of them. Table 1-1 below present this list of concepts, along with their
acronyms and either examples or very short definitions.
Table 1-1: Acronyms
19
Chapter 2 - Systemic Approach to Distributed Energy Systems
2.1 Distributed Energy Systems (DESs)
What is a Distributed Energy System?
A necessary definition for developing a systemic approach to DESs, is to deeply
understand what a DES is, how it is configured, and how it interacts with its
stakeholders and neighboring systems.
A DES, as defined in "The MIT Utility of the Future - Phase I Report" (Bharatkumar et
al., 2014), is a system "combining one or more distributed energy resources (DERs),
including distributed generation, distributed storage, and/or demand response,
with information and communication technologies (ICTs) to enable a business
model that provides valuable services to energy end users or upstream electricity
market actors." Figure 2-1 presents 4 different topologies for DESs.
Figure 2-1: Different DES Topologies
Depending on the function to be performed, the design of the DES should define not
only the topology, but also what combination of technologies will be present in that
configuration. The next subsection presents the different layers of DES technologies
and their function in the DES.
20
Distributed Energy Systems' Components
Depending on their function in the system's output, DES technology components can
be grouped in three layers. A graphical representation of this organizing scheme,
from the UoF research (Bharatkumar et al., 2014), can be seen in the Figure 2-2.
Input delflned by Business Model B !
Systems Environment inssewaft
Layer 3:
D~ii~~k,,
)I
Intelligence0
Layer 2:
Communications
L..ow
nioigad
aign.'n
Dt
I
oet-U
10,(M .W
Layer 1:
Physical
Parts of Distributed Energy Systems (DES)
Parts of Traditional Power and Telecom Systems
Figure 2-2: Layers of DES Technologies
Layer 1 involves most of the physical components and the infrastructure of
incumbent electricity and telecommunications networks, plus DERs. This layer is an
aggregation of loads, wires7 and DERs, and doesn't require other layers to deliver
value. However, its value is significantly increased when adding layers 2 and 3.
Layer 2 and layer 3 include all the ICTs added up to DERs in order to enable DESs.
Layer 2, Communications layer, considers sensing, collecting and managing data, as
well as the capability to remotely control DERs. Layer 3, the Intelligence layer, adds
the brain to the system, analyzing internal and external (to the system) data in order
to generate control decisions to be sent to DERs.
As it can be inferred from Figure 2-2, most of the value creation of DESs -above that
of DERs- is based on the synergy achieved by involving ICT capabilities of remote
sensing, data management and remote control. These new capabilities will show an
even higher relevance in the future, as they provide tools to address the new needs
and requirements imposed by the system's environment.
7 Including power grids, power electronics, Internet and telecommunication networks
21
Distributed Energy Systems in the Grid
Now that DESs and its components have been defined and identified, a good
question to make should be "Why do we need DESs?" or, in other words, "What
value do DESs add in the electric power system?"
The answer to this question is strongly related with the concept of value, as value is
delivered or created when an unmet need is fulfilled 8. As would be explained in the
following section, electricity end-users needs' evolution is affected by the EPS's
dynamics and system's environment. This dynamic relation has been creating new
consumer needs that EPS's current structure does not seem well suited to meet at
the required pace. In this context, DESs present a flexible and often more affordable
way to fulfill those needs. To clarify which are those needs, Figure 2-3 shows a
scheme for these basic needs, some of which are shared by consumers and utilities.
ELECTRICITY RELATED NEEDS
* Consumy's Needs
a
Figure 2-3: Electricity Related Needs
Different configuration of DESs can certainly add value to consumers and utilities by
addressing the needs listed in the previous images. For instance, DG could provide
energy availability to consumers and (in some cases) frequency balance to utilities.
DR could also help utilities to provide availability to consumers. Finally, DS and EVs
could provide variable cost stability, resilience and recovery.
8 Systems Architecture theory
22
2.2 The Expected Role of DESs in Electric Power Systems' Dynamics
The 3-Layers' diagram of Section 2.1 showed a relevant feature that was not
commented in that section. This is the input of business models and other factors
that determine the systems' environment -like regulation, market structure, etc. on the decision making process of the Intelligence Layer. This input, and particularly
its dynamic nature, should be a crucial consideration when trying to determine the
evolution of the system and the future context of DESs when integrating to the grid.
To better understand this interrelation, a Causal-Loop diagram -based on the
concepts of Systems Dynamics theory- is presented in Figure 2-4. The analysis of
such diagram tells us -as it was stated in the introductory chapter- that change is
already here. As social systems evolve, incumbent firms in the power sector -for
many years ignorant of disruptive changes- find themselves in an uncomfortable
position where they seem forced to change in order to survive in the new
environment. Sociotechnical systems -like power systems- have always been
dynamic, but new change drivers have increased their evolution rate to a point
where simple adaptations of the existing business models and regulation are not
enough to keep the pace.
One might argue that the nature of the relationship between technologies,
regulations, business models, etc. has always been dynamic. However, today the
main change driver is the "social" part of this sociotechnical system. Factors
historically considered exogenous to the system, like environmental awareness or
connectivity, are rapidly transforming end-user needs, and as an effect, increasing
the change rates at which the system evolves.
A takeaway from the previous paragraphs is that different rates of change or
adaption to change present in this dynamic system should be addressed differently,
as the traditional business models and regulatory frameworks might not be able to
change at a rate adequate enough to keep the pace of consumer needs' evolution.
23
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The goal then might be add agility to the Regulatory Innovation Loop, so that an adequate regulatory
framework levels the field for innovative business models to add value by meeting needs that the current
business models are not being able to fulfill.
If the business opportunities were tacIded through business model innovation, it will require an
adequate regulatory framework to be able to be executed. Its execution will also fulfill some needs and
develop technology, which will also create some more needs. The difference is that the rate in which
innovative business models meet unfulfilled needs is much faster than that of traditional business models.
More unfulfilled needs create more business opportunities, which can be executed in the traditional
way or through business model innovation. The traditional execution might fulfill some needs, and develop
new technology. When people get used to technology, it creates even more unfulfilled needs.
Businen
2.3 DES Business Models Analytic Framework [BMAF]
The previous section presented the importance of the role of business model
innovation on the fulfillment of new stakeholders' needs. In order to have an idea of
what do DES-related business models look like, this section will introduce a
framework to analyze these business models, characterizing them by the need they
aim to fulfill, the technology mix they apply, and their "business model attributes" (a
concept that will be explained in Figure 2-5).
Business Model Attributes
Definition from the MIT Utility of the Future Phase I Report (Bharatkumar et al., 2014)
"... based on the economic activities that exist in electric power systems, we have defined five core
"attributes" of business models that represent, at the highest level, the principal configuration of
business models within this industry.
An attribute represents a combination of characteristics of the business models incorporating both
the level of financial commitment and the future focus of the stakeholder..."
"At the highest level, attributes of the business model are that a stakeholder may:
*
*
*
*
Own assets;
Operate assets and/or systems of assets;
Fund the acquisition or the operation of assets;
Provide Information to asset owners or operators; or
*
Build or manufacture assets."
Figure 2-5: Business Model Attributes
The Causal Loop diagram of Section 2.2 (Figure 2-4) -and particularly the three
loops at the left- depict the strong and direct relation between needs, technology
and business models. The BMAF is based on that relation, and characterizes
business models based on their representation in two matrices: a first one relating
business model attributes and DES technology components, and a second one
relating business model attributes and the needs that the business model aims to
address.
25
"Matrix 1": Business Model Attributes vs. DES Technology Components
The first matrix -relating business model attributes and DES technology
components- indicates the suitability of each of the DES technologies to be used by
each of the business model attributes. In greenfield projects, this matrix can be used
to decide what DES technologies to develop given the business model attributes that
best fit the organization, or to decide what segments of the value chain should be
developed if developing a given DES technology. In the case of brownfield projects,
the matrix is mostly used to assess the positioning of the project, and look for
synergies that can generate expansion opportunities for the project or its
competitors. A version of this "Matrix 1" can be seen in Table 2-1 below.
Table 2-1: BMAF's "Matrix 1"
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In the main section of the matrix, a checkmark means that the technology is a good
fit for that business model attribute; a cross means that it is not a good fit; and a
question mark states that the fit is unclear. For instance, owning electric vehicle
infrastructure seems to be a good opportunity, owning demand response equipment
doesn't, and the opportunity of business models based on owning ITC is not clear.
The triangle at the right of the matrix shows the potential synergy that attributes
might have when being combined. It uses a check mark on synergy options, a dash
on no-synergy options, and a cross if there is contradiction between the business
model attributes. In this case, there are synergies between owning and operating, no
synergies between funding and providing information, and contradiction between
funding and owning (as it is not logic to profit from funding your own acquisitions).
26
"Matrix 2": Business Model Attributes vs. Consumer and Utility Needs
The second matrix used in the BMAF relates business model attributes to the basic
electricity-related needs (presented in Section 2.1) that they aim to fulfill. Working
with this representation can help to understand where, if somewhere, a business
model can add value by fulfilling the potential unmet needs of a stakeholder. The
example of this "Matrix 2" shown in Table 2-2 below could be showing the value of a
business model where a company builds ICT devices like Home Energy Management
Systems, enhanced with information services to utilities. The ICT devices save
energy and money, but they also handle data that could be used to provide utilities
with information to optimize their hourly generation mix, allowing a better use of
renewables. Consumers might be willing to share this information as they could
receive a payment, while knowing it helps the penetration of large-scale renewables.
Table 2-2: BMAF's "Matrix 2"
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These two matrices, when aggregating on it all industry competitors, could be used
too to visualize, among others, what technologies is the market using to provide
services, and how different services can fulfill different or similar needs.
Having presented the basics of the systemic approach used in this assessment and a
framework to analyze business models on DESs, the next step is to understand the
particularities of the Chilean context, in which the DESs performance will be
evaluated. This will allow us to generate scenarios that will determine how to
measure the performance of each business model.
27
Chapter 3 - DESs in the Chilean Electric Power Sector
3.1 Chile: Geography and Economics
Chile is a 17-million-people country located in South America's south cone. Its
particular long and narrow shape going 2650 miles from north to south between the
Andes Mountains and the Pacific Ocean provides the country many different
landscapes that are both a blessing and a challenge for Chilean people. Besides
having an exceptional potential for tourism, the variety of climates and the natural
configuration that are present in Chile provide a rich source of mineral, hydro and
forestry resources. However, its extreme geography, its high levels of seismicity and
its lack of hydrocarbons, bring considerable economic challenges that are a burden
in Chile's path to economic development.
Regarding its economic policies, Chile has a market-oriented economy characterized
by a high level of foreign trade and a reputation for strong financial institutions and
sound policy that have given it the strongest sovereign bond rating in South America
(Central Intelligence Agency, 2013). The government's role in the economy is mostly
limited to regulation (U.S Department of State, 2013).
Having Chile such diverse landscapes, it is really difficult to describe it
geographically and economically as a whole. Consequently, the paragraphs below
will analyze it using the following discretional subdivisions: northern region, central
and southern regions and Patagonia & austral regions.
The Northern Region
The 500 northern miles of the country is a zone known as the location of one of the
world's driest deserts: Atacama. This region, which limits north with Peru and East
with Bolivia and northern Argentina, hosts most of the mining operations in the
country. The Chilean copper industry controls more than one third of the world's
28
market (Comisi6n Chilena del Cobre [Cochilco], 2013), having reserves of 190
million tons (USGS, 2013), which is 28 percent of known copper reserves in
existence. Chile also shows similar figures in lithium mining, generating 30 percent
of the profits on lithium sales, while having 23 percent of the world reserves
(2nd
place worldwide, after Bolivia). But not only mineral resources can be found in the
north, as it is also known to have one of the best settings for solar energy, with daily
solar global horizontal irradiance [GHI] of 7 kWh/m2 in the Antofagasta Region
(OECD, 2013).
The challenges for northern Chile and its mining-related economy are mostly
related with water and energy management. Mining industry is a large consumer of
power, accounting approximately for 90% (CNE, 2013b) of the total consumption
from northern Chile (over 17 TWh). Despite the huge potential for solar energy, and
due to the low costs of thermal, nearly 99% of the demand is being supplied by
thermal units (CDEC-SING, 2013).
Water management is also a relevant issue, as water is also needed for mining
processes and cooling of thermal units. Then, two water related processes increase
energy demand: energy required for desalination, and energy required for pumping
water to the mountain areas were most of the mines are located.
The Central and Southern Regions
The next 1300 miles of the Chilean territory are the central and southern regions.
With a temperate climate having sharp regional contrasts, it is the home of about
15.5 of the 17 million habitants of the country (about 6 million of them in Santiago,
Chile's capital city) (INE, 2013). Consequently, this region concentrates most of
Chile's commerce, agriculture, forestry, fishery, livestock and services activities.
These regions also have most of the operating hydroelectric plants and some
relevant geothermal resources (especially in the southern region).
29
From an economic standpoint, the challenges for the central and southern regions
are the ones that represent the Chilean society as a whole, and are mostly related to
growth management. In the last thirty years the Chilean economy has grown
significantly and its benefits have started to reach common people. With an
enhanced access to education, credit, goods and services, people have began to
increase their consumption and productivity, reinforcing the economy growth loop.
The flip side of this accelerated growth is that it may lead -as it did in Chile- to high
rates of social inequality, where people started demanding their stake on the profits:
free access to higher education, improved healthcare, higher salaries, etc.
Additionally, higher consumption -combined with an at least sub-optimal capacity
expansion process- led to increased energy prices, which are among the highest in
Latin America. In this context -where government increases public expending,
workforce gets more expensive, and electricity price for industry is extremely
high 9 - the country's competitiveness is harmed, as most other countries in the
markets where Chile competes have lower operational costs.
Patagonia & Austral Regions
The southern 850 miles of the country is a particularly beautiful and cold land,
known to host the western section of Patagonia. Due to the harsh climate and
extreme geography present in these regions, its aggregated population does not
exceed 0.3 million people, some of whom are widely dispersed in areas with a
difficult access. These regions' economy is based on tourism, livestock farming and
forestry. They are also rich in energy related natural resources, like coal, biomass,
some oil & gas and large hydro resources. This scenario provides what are
sometimes conflicting opportunities -like tourism and forestry- and defines the
challenges for this zone, mainly in keeping an adequate balance between economic
development and respect for the ecosystem.
9 The electricity marginal cost for the period Dec 2012 - Nov 2013 in Chilean main power system
(Alto Jahuel 110 kV) had an average and a median of 163 US$/MWh, having 34% of the daily
averages above 200 US$/MWh (Source: www.cdecsic.cl)
30
3.2 Chilean Electric Power Sector
Electric Power Systems in Chile
The subdivisions of the Chilean territory utilized in the previous section were not
randomly chosen. They correspond to the four main power systems of the country,
called "Interconnected Systems" as they are formed by the interconnection of a
group of smaller grids, but these "Interconnected Systems" are not actually
connected among them (see Figure 3-1 on next page).
The power system that serves northern Chile is the SING, which is an acronym for
Sistema Interconectado del Norte Grande, Spanish translation for Northern
Interconnected System. The Chilean National Energy Commission informed that by
the end of 2012 the SING had over 4.1 GW of installed capacity and over 4,000 miles
of transmission lines (>23kV) to serve yearly electricity sales of nearly 14.8 TWh,
with generation production peaks of up to 2.1 GW.
The central and southern zones of Chile are served by the SIC, acronym for Sistema
Interconectado Central, Spanish translation for Central Interconnected System. This
is the largest power system in Chile and by the end of 2012 it had over 13.3 GW of
installed capacity and nearly 12,000 miles of transmission lines (>23kV). In 2012
the SIC served yearly electricity sales of about 46.2 TWh, with generation peaks of
up to 7 GW.
The Patagonia region is served by the Aysen Interconnected System that, by the end
of 2012, had 46.7 MW of installed capacity to serve yearly electricity sales of 148.3
GWh, with generation peaks of 25,5 MW. The austral region is served by the
Magallanes Power System -composed by 3 medium size non-connected grids:
Puerto Natales, Punta Arenas and Porvenir- that, by the end of 2012, had 103.4 MW
of installed capacity to serve yearly electricity sales of 277.8 GWh, and generation
peaks of 50,6 MW (CNE, 2013b).
31
Dx 277 8 G
of sales
Magallanes Systerr
Gx: 103.4 MW of installed capacity.
n mpca ofs 5. 6 MW
rp
Ox: 143 GWh of sales
Gx: 46.7 MW of installed capacity.
productonpeaks of 25 5 MW
Ayskn System
Tx: nearly 12,0 miles of transmission
lines (>23kVj
Ox:about 46 2 TWhof soles
capacit y,
of soles
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produciun peaKs of 7 GW
SIC (Cer tra Sys tem
2>23kV)
Ox: nearly 14 8 TWh
SING tNrchern System)
Gx: >4.1 GW of installed capacity,
producton ceqksof 2 1GW
Tx: > 4,0 miles of transmission lines
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Four Main Chilean Electric Pow Systems and
Geographic Distribution of Generation, Consumption and Population
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Structure of the Electric Power Sector
Chile is known for being, after the reforms that took place in 1982, a pioneer in
electricity market's deregulation. The current structure of the Chilean electric
power sector is primarily defined by the regulatory changes performed in 1982,
plus some additional regulatory changes that took place starting in 2005 ("Ley
Corta" or Short Law and other decrees). In general terms, the Chilean electric power
sector is characterized by its 100% private, vertically and horizontally unbundled
players, who take part in three 0 segments of the value chain: Generation,
Transmission and Distribution.
The Generation segment is characterized for being a competitive market -with no
central planning for capacity expansion- that has clear scale economies on its
operational costs and where prices tend to reflect the marginal production cost.
Generators are remunerated by their energy output (MWh) and by the capacity (MW)
they provide for the systems adequacy. Energy can be sold to distributors (regulated
price), to large consumers (unregulated wholesale price), and to other generators (spot
price set by marginal cost of transfer).
The Transmission segment in Chile involves every line and substation having a voltage
over 23 kV. Transmission is open to access by generators, meaning that they can impose
their right to use the available capacity of a line through the payment of tolls.
Generators and consumers share the toll payments for Transmission.
The Distribution segment operates under a public service concession regime, with an
obligation to provide service on geographic concessions. Distributors buy energy from
generators though public bidding processes and get remunerated by consumers' VAD
(Distribution Added Value) (CNE, 2013b).
10 Sub-Transmission will be considered as a special case of Transmission. These systems are formed
by substations and lines that are connected to the grid and their sole purpose is to supply exclusively
identifiable consumers, or groups of them, that are in the concession area of a distribution company.
33
Regulatory Entities and System Operators
The three previously mentioned segments interact following the market rules
indicated in the Law of Electric Services (DFL1). In order to keep this system
relatively free of market frictions and complying with Chilean laws, the Chilean
government developed a framework involving different entities like the Ministry of
Energy, the National Energy Commission (both governmental agencies), and the
Economic Load Dispatch Centers (independent entities, one for the SING and one for
the SIC).
The role of the Ministry of Energy is to elaborate, coordinate and enforce the plans,
policies and norms for the correct operation and development of the electric power
sector. It is also the role of this Ministry to advise the government in all those
subjects related to energy (Ministerio de Energia, 2013).
The National Commission of Energy (CNE) is a technical entity whose role is to
analyze prices, tariffs and technical norms to whom the electric utilities should stick
in order to assure a sufficient, safe and high quality service, compatible with the
most economic operation (CNE, 2013).
The main function of the Economic Load Dispatch Centers -known as CDECs, from
the Spanish term Centro de Despacho Econ6mico de Carga- is to dispatch
generators minimizing operational costs in pursue of the highest economic
efficiency for the system (AES, 2008). As previously mentioned, both the SIC and the
SING -who added represent more than the 99% of the system's generation-,
dispatch their generators through their own CDECs.
CDECs also provide valuable information for the financial transactions in three
cases: between generators for energy balances (those that had to honor power
supply contracts but were not dispatched have to pay at spot price to those who
actually were dispatched), between generators for capacity balances (related to
34
capacity payments for contributing to the systems sufficiency), and between line
owners and toll payers (for the use of the lines).
A representation of the structure of the Chilean electric power sector, displaying its
main direct stakeholders and the way they interact, can be seen in the diagram
below.
Current Chilean Electric Power System
Customers
Utilities
T9
P11r'te
f
Regulators and System
Operators
r1r:c/IPA
su-pansmaMo wad deizewatetv ound from the e",rar as for thpupo5 uc m1 etde
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Figure 3-2: current Chilean Electric Power System's Stakeholders Diagram
35
3.3 Distribution-End of the Chilean Electric Power Sector
Power distribution grids are formed by a network of lines and substations that
transport electricity from the primary substations that act as coupling points with
the transmission grid, to consumers. In these primary substations voltage is reduced
to 23, 13.2, or 12 kV depending if the end user is industrial or residential. In this
latter case, a secondary substation will again lower the voltage, now to low-tension
standards, which in Chile are 220 V and 380 V, monophasic and triphasic
respectively (CNE, 2013c).
The infrastructure related investments for power distribution shows a certain level
of indivisibility and density economies, particularly when referring to the capacity
of electric equipment like wires and transformers, the supporting structures, and
the rights-of-way that have to be obtained in order to access demand. With that in
mind, optimal design implies considering an adequate level of slack when investing
in equipment, particularly in those assets having long service life (CNE, 2013c).
In this context, where a standard distribution utility has a very long position on
long-life fixed assets, usually financed by long-term debt, the sufficiency of the
remuneration is vital for the company financial survival. This remuneration to the
distributor is paid by consumers in the VAD (acronym of Valor Agregado de
Distribuci6n) or Distribution Added Value. As was indirectly mentioned along the
text, regulated clients pay the VAD in their monthly bill, along with their energy
consumption (kWh), their share of the Transmission Toll, and other distribution
services like metering, reconnections, etc.
The funds provided by the VAD have to be enough to cover the expenses related to
the system operation (follow up and control, damage correction, and incidents),
system maintenance (of lines, substations and protection equipment), and business
management (measurement, meter reading, billing, contracts, etc.). A broader vision
36
of the uses of the VAD can be seen in Figure 3-3 taken from a presentation by
Professor Hugh Rudnick (2009).
Distribution Value Added
Fixed costs
I
Catal
costs
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Figure 3-3: Distribution Value Added (Rudnick, 2009)
3.4 Integration of DESs under the Current Scenario
Now that the current scenario that Chile presents for the integration of DESs has
been described, the purpose of this section is to identify the factors that might
positively or negatively affect this integration process. In order to do that, we must
understand the dynamics of this integration process, particularly the causality
interrelation between the involved factors.
Probably the simpler way to develop a systemic view of the DES integration in Chile
is through a Causal-Loop diagram, taken from System Dynamics' theory, like the one
presented on Figure 3-4.
37
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Figure 3-4: DER/DES Consumer Adoption Dynamics for the Chilean Context
38
The diagram of Figure 3-4 represents the dynamic effects in the system through 7
loops and 4 non-loop variables, which affect DES consumer adoption. In order to
characterize these dynamic effects, they were grouped depending whether they
involve technology-related factors, regulatory factors or socio-economical factors.
Effects Involving Technology-Related Factors
Technology Improvement Loop:
The increase of DER-DES adoption will produce a maturation process in
technologies (learning by doing). It will also encourage R&D investments, as
its costs will be shared by a larger number of units. Maturation and R&D will
lead to Performance Improvements, which will make products more valuable
for end-users. The more valuable to end-users the products become, the
more their adoption increases, generating then a reinforcing loop.
Technology Cost Loop:
Similar to the previous Loop, the technology cost loop increases consumer
adoption by increasing DER-DES valuation. The difference here is that the
valuation is increased because of the scale economies' lower costs achieved
by larger DER-DES consumer adoption. This is also a reinforcing loop.
Valuation of Unfulfilled Needs Met by DERs-DESs:
This factor brings to the system a relevant issue: In a scenario of higher
penetration of intermittent generation at a grid level, which also has more
frequent outages due to imbalances or climate/weather causes, DES could
provide islanding capabilities, power supply reliability or even ancillary
services. Then the consumer adoption of DER-DES will increase if the value of
the provided services is considered by the end user higher than its required
investment and operational costs.
39
Effects Involving Regulatory Factors
Distribution Utility Revenue Effect on Tariffs Loop:
As DER-DES Consumer Adoption increases -all other variables remaining
constant-, the total power purchased from the grid decreases. Then the
collection of the volumetric toll for distribution will be lower, harming the
Distribution Utility Revenues. This is more relevant in those tariffs where
most of the charges are volumetric (as the low tension BT1 tariff for
residential customers in Chile). Sooner or later, if there are no modifications
to the tariff structure, the lower revenues for distribution utilities will make
the per-unit Cost of Grid Electricity to Consumers to increase, incentivizing
DER-DES Consumer Adoption, as their relative cost will be lower than before.
This is a reinforcing loop.
Transmission Utility Revenue Effect on Tariffs Loop:
This is also a reinforcing loop, which follows the same logic of the
Distribution Utility Revenue Effect on Tariffs Loop, but in this case the effect
is related to the collection of volumetric tolls by Transmission instead of
Distribution utilities. Then, the less power is bought from the grid, the lower
the collection and revenue for transmission companies and the higher the
tolls will turn (to recover the investment). Then, as the final cost of grid
electricity will be higher, consumers will have more incentives to adopt
DER/DES technologies.
Wholesale Electricity Prices Loop:
The fall in Power Purchased from the Grid due to DER-DES Consumer
Adoption increases will cause a fall in Wholesale Generation Volume,
meaning lower revenues. These lower revenues will translate into a negative
financial outlook for the generator (from the standpoint of banks and
creditors), which will increase the generator's cost of capital. This higher cost
40
of capital will be reflected, with some delay, in Wholesale Electricity Prices.
Higher wholesale prices imply that sooner or later (depending on the
contracts or if referring to regulated consumers that face prices set on 5 year
period bids) there will be higher Cost of Grid Electricity to Consumers, which
will then mean higher DER-DES Consumer Adoption. This is also a
reinforcing Loop.
Marginal GenerationCost Loop:
Highly related with the Wholesale Electricity Prices Loop, this is a balancing
loop that reflects the fact that a lower Wholesale Generation Volume will
mean a lower Marginal Generator's Production Cost, and lower Wholesale
Electricity Prices. Lower wholesale prices imply (with the same delay
explained in the Wholesale Electricity Prices Loop) lower Cost of Grid
Electricity to Consumers. A lower cost of electricity to consumers connected
to the grid will discourage the adoption of DER-DES. This is the only relevant
balancing loop present in the system.
RegulatoryAdequacy for DES-DER:
As explained in Chapter 2 of this thesis, in order for Innovative Business
Models (like the ones involving DES-DER technologies) to be able to fulfill
unmet stakeholders' needs, it is imperative to have an adequate regulatory
framework. This variable reflects the fact that inadequate regulatory
frameworks can slow down or completely stop DER-DES adoption, if it
doesn't react in time to allow the technology, or constrains the connection to
the system.
41
Effects Involving Socio-Economic Factors
Distribution Utility Costs Effect on Tariffs Loop:
One direct effect of DER-DES Adoption is the Change in Grid Usage Profile.
Whether that change is positive, negative or a mix of both is unknown as it
will depend on the mix of DER-DES technologies that are adopted, but for
sure adoption will increase change. This uncertainty about behavior of the
grid usage profile is then transferred to the Distribution Grid Costs.
Distribution costs may increase, but there is no reason to assume that they
won't decrease. In this context it is unclear if this is a reinforcing or a
balancing loop, but what is clear is that this uncertainty presents an
opportunity and a challenge for new regulatory structures that work in both
cases.
FinancialIncentivesfrom Government, Utilities orAggregators:
This variable reflects the inputs of stakeholders that might be benefited by
DER-DES adoption, and that may give financial incentives to promote that
trend. Obviously, the larger the financial incentives, the higher the DER-DES
consumer adoption rate.
Socio-Economic Adequacy of Business Models:
DESs' rate of adoption will also depend on the existence on competitive
business models that add value to the system and that are suitable for the
socio-economic or cultural context. For instance, DES-related business
models that require sharing consumers' load profiles, might not be adequate
for societies that give an extreme value to any kind of private information. In
that context, inadequate business models could produce low, or even null,
rates of adoption. The more adequate the business model is to the socioeconomic context, the higher the DESs' rate of adoption.
42
3.5 Integration of DESs under Foreseeable Scenarios
Change Drivers and Future Scenario Projection
When analyzing the future of technology related factors, it could be assumed that,
being Chile a country that imports most of its technology, both technology loops
should behave in Chile as they do in any other country having open markets.
However, the variable Valuation of Unfulfilled Needs Met by DERs-DESs will be highly
relevant especially in the SIC, which has transmission capacity issues and weather
exposure as it relies on rainfall for its hydro power plants. How the consumers value
the availability, affordability, reliability, recoverability and low environmental
impact that DESs provide, will define future scenarios.
Regulation is usually an area that shows differences in every country, and the
Chilean case is not the exception. As previously mentioned in this chapter, even
when Chile was a pioneer in electric power market deregulation, not many major
changes have been introduced since then (besides maybe the "short laws", around
2005). Even when this does not imply that there won't be major changes soon; it
might mean that the stakeholders (or at least the ones that can be heard) are
somewhat satisfied with the current scheme.
In that context, the only foreseeable regulatory factor that might generate relevant
changes in consumer behavior regarding DESs is a potential elimination of 100%
volumetric tariff (BT1), forcing customers to choose among the other available
tariffs, which are combinations between volumetric and capacity charges. This
option seems likely in the context of high DES integration, as it could be a fair way to
charge "free-riders" 1 for the "option to be connected to the grid" even when there is
no consumption or net consumption.
11 End-users that fulfill their own electricity needs through DERs tend to use the distribution grid less
than normal end-users. Taken to an extreme, end-user not consuming grid-supplied energy will not
pay for grid costs (investment, operation and maintenance) while having the free option to consume
from the grid if they want to. Those end-users are considered "Free-riders", as they make other endusers pay for a grid they can use.
43
Regarding socio-economical factors, the Chilean government does not usually give
financial incentives, and that doesn't seem that will change in a foreseeable future.
An opportunity for DESs to receive financial incentives from the government might
be in social projects that provide energy reliability or even energy access to remote
villages. Other financial incentives may come from Utilities or Aggregators trying to
develop a particular business model. In this case, is more probable the participation
of new entrants in the sector as incumbent utilities in Chile usually do not take those
kinds of risks. Anyways, it doesn't seem like financial incentives might be a change
driver for future development of DESs in Chile.
Future Scenarios for DES Integration
The identification of potential change drivers for DES integration developed in this
section will allow us to generate eight future scenarios for the Chilean Electric
Power Sector. These scenarios will be utilized in Chapter 4 to evaluate the business
models presented at the end of Chapter 2. They are numbered 1 to 8 and from the
most to the least likely, as shown in the following table:
Table 3-1: Eight Scenarios for the Chilean Electric Power Sector
Smeados
_
__
_
_
_
_
_
_
_
44
Chapter 4 - Business Models for Distributed Energy Systems
4.1 Business Model Analysis
Coherently with the Chilean context presented in Chapter 3, and the needs of its
foreseeable scenarios, this chapter lists and describes eight different DES-related
business models that could be successful in the Chilean context. The cases presented
come from actual companies, and are good examples of the different combinations
of business model attributes and DES technologies that can be found in the market.
The business models' list -which groups them into those that supply energy, those
that manage energy demand, and those that enable DESs- presents business models
from the following companies:
Energy Suppliers
1. Toshiba International Europe (TIL) & German Pension Funds
2. Solar City
3. Standard Solar & Solar Grid Storage (Konterra project)
Energy Demand Managers
4. EnerNOC
5. Opower
Energy Enablers
6. WeatherBug
7. Energy Aware
8. Sequentric
Each one of these business models will be described and analyzed using the BMAF's
matrices presented in Section 2-3. The goal is to extract and present the information
that individualizes each business model, with a particular focus on the value it
provides to different stakeholders as this information will be used in Chapter 5 to
evaluate their performance.
45
Energy Suppliers
1. Toshiba International Europe (TIL) and a group of German pension funds
made a deal 12 with a German real state company that owns and rents apartment
buildings. In this deal, the real state company rents the apartment buildings'
roofs to the pension funds. In these roofs, TIL installs and operates the pension
funds' solar panels and energy storage systems. Pension funds get paid by TIL
who uses the systems' power output to enter in a PPA with the real state
company. In this PPA, TIL agrees to provide electricity to buildings' consumers at
a PV-generated energy locked-in price. The PPA states that in those cases when
the distributed system is not able to meet the energy demand of the apartment
buildings, TIL should buy that power in the wholesale market and sell it at the
same PV locked-in price. This business model mostly bypasses retailers and the
distribution utility.
Table 4-1: TIL's "Matrix I"
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Table 4-2: TIL's "Matrix 2"
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46
Table 4-1 and Table 4-2 present this business model's matrices, which can be
helpful to understand its structure. "Matrix 1" tells that as the pension funds only
own the Distributed Generation [DG] and Distributed Storage [DS] assets, there
are no synergies with other attributes. On the other hand, "Matrix 2" provides
the rationale of involving the pension funds in the deal: lower the upfront
payment for the real state company that otherwise might not be interested in
this deal. "Matrix 1" also states that TIL has synergies when operating and
maintaining the panels that they build. In the case of TIL, "Matrix 2" lists the
benefits for the consumers: resiliency, low & stable variable cost, environmental
affordability (they are mostly supplied by solar power) and time consumption
affordability (TIL takes care of the operation and users have nothing else to do).
2. Solar City 1 3 is providing residential rooftop solar PV systems to consumers
(through lease), installed, operated and maintained by Solar City. End-users pay
a fixed monthly amount for the electricity, plus the -also fixed- solar lease
payments. Solar City guarantees the system's performance. Therefore an
advanced monitoring system connected to Internet is required in order to
remotely sense the solar system.
As seen in Table 4-3, Solar City's "Matrix 1" shows that Solar City takes
advantage of the synergy between owning and operating solar panels. This
synergy is very strong and -as will be discussed later- it makes that nearly all
DG DES developers only operate panels owned by them, affecting the viability of
DG funding business models, which find few consumers willing to bare the risks
of operation and maintenance.
13
http://www.solarcity.com/residential/
47
Table 4-3: Solar City's "Matrix 1"
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"Matrix 2" in Table 4-4 below, presents the needs that can be fulfilled with this
business model. These needs are mainly the same ones as in TIL's business
model (resiliency, low & stable variable cost, environmental affordability and
time consumption affordability), plus access and capacity, because this solution
can also be used by off-grid or grid-connected consumers aiming to increase
capacity.
Table 4-4: Solar City's "Matrix 2"
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3. Standard Solar & Solar Grid Storage developed the Konterra project, a
"sustainable mixed-use community"14 in Maryland, which is an interesting
example of microgrids' 5 incorporating a relevant DG and DS capacity, as well as
Electric Vehicle Infrastructure [EVI]. It can produce 20% of its power demand,
can island itself from the grid, can benefit from electricity storage, and -maybe
14
http://www.energyefficiencymarkets.com/2013/10/17/solar-project-like-others-marylands-
microgrid-play/
15 A microgrid is one of the configurations of DESs, in which resources and loads are collocated.
48
the most interesting part- can sell regulation services to PJM, the Transmission
System Operator.
Table 4-5: Konterra's "Matrix 1"
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In this business model "Matrix 1" and "Matrix 2" -in Table 4-5 and Table 4-6,
respectively-present this build & own project that involves many different types
of DES technologies, where most of the benefit is captured by Konterra's
consumers, who will see increased levels of fulfillment for their reliability and
energy affordability needs.
In order to be financially viable, apart from setting relatively high real estate
prices in the community, the project obtains funds from selling regulation
services in the ancillary services market. These are used to provide reliability to
utilities, required especially for those integrating a large volume of grid-scale
renewable generation resources.
Table 4-6: Konterra's "Matrix 2"
1131M" MT.]
49
Energy Demand Managers
4. EnerNOC is a provider of energy intelligence software, which is mostly known
by DemandSMART' solution1 6 that enables their Demand Response [DR]
business. They focus on aggregating17 large consumers (commercial and
institutional clients) advising them and providing them with the equipment to
implement primarily capacity DR, which is a temporary curtailment of power
usage in case of peak demand events.
In this business model consumers get paid a fixed amount for their willingness
to participate in the program, plus a variable amount depending on how they are
able to meet the load curtailment goal defined in case of a demand response
request. EnerNOC will be paid -at the marginal electricity price- by the System
Operator for the capacity they were able to reduce.
Table 4-7: EnerNOC's "Matrix 1"
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EnerNOC's "Matrix 1" -in Table 4-7- shows its business model's operational
focus, executing demand response through ICT platforms. "Matrix 2" -in Table 48- states that it provides benefit to both utilities and consumers. Utilities (or the
Transmission System Operator [TSO]) benefit from a reduction of the nonserved energy gap, while consumers save energy, save money, and get paid.
16 http://www.enernoc.com/for-businesses/demandsmart
17 The concept of "Aggregation" is essential to understand business models
like EnerNOC's. This
concept implies aggregating the demand or supply from multiple consumers or providers to generate
scale economies, take advantage of a strategic position in the value chain, etc.
50
Table 4-8: EnerNOC's "Matrix 2"
I~~l
-ffiffi
I
5. Opower provides energy intelligence software and costumer engagement
solutions for energy industry. Famous for its energy efficiency solutions, Opower
has leveraged their strategic connection with consumer locations to enable
utilities develop residential consumer DR programs. What they call Behavioral
DR18 makes use of Advanced Metering Infrastructure to motivate consumers in
order to reduce their demand through personalized insights. In this business
model Opower gets paid by the utility that is being benefited with the DR
program.
Error! Reference source not found. corresponds to Opower's "Matrix 1", which
shows that they took advantage of the synergy between building ICT devices and
providing information (DR messages) through them.
Table 4-9: Opower's "Matrix 1"
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http://opower.com/solutions/behavioral-demand-response
51
This strategy, though, could have been easily followed by potential competitors.
The fact of being the first ones to successfully widely deploy with quality devices
made the difference for Opower. This early deployment became a strategic
advantage for Behavioral Demand Response, as Opower was already positioned
close to consumers.
Table 4-10: Opower's "Matrix 2"
__AW_
"Matrix 2" -on Table 4-10- reflects that by enabling Behavioral DR, Opower
provides capacity to utilities, while meeting consumers' financial and
environmental needs.
DES Enablers
6. WeatherBug is an information company that monitors and analyzes
atmospheric conditions. With their SmartHome Plus 19 solution -energy
management device that connects to smart meter data and a local thermostatthey took advantage of their expertise in information management and weather
forecasting to improve energy supply and load management.
The analysis of WeatherBug's business model through "Matrix 1" -in Table 4-11reflects that they are taking advantage of the synergy between information
provision and ICT devices' development.
19 http://earthnetworks.com/Products/SmartHome.aspx
52
Table 4-11:WeatherBug's "Matrix 1"
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Even though in WeatherBug they might not be experts in manufacturing, they
could buy (or outsource) this skill. By doing that, they will be able to generate
products whose differentiating factor is the capability to process their most
valuable output: quality weather forecast information that enhances the
scheduled operation of DG and DS.
Table 4-12: WeatherBug's "Matrix 2"
I FAamw*
Own
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Aftionw
"Matrix 2" in Table 4-12 tells us that, beyond helping consumers to save money
and energy (which meets their financial and environmental affordability needs),
WeatherBug enables a better use of distributed generation and distributed
storage, providing capacity and resiliency to consumers.
53
7. Energy Aware is a technology company that provides products and services
ranging from energy engagement devices for consumers to advanced data
analytics to utilities. With the commercialization of their Neurio" platform 20 which is one of the many home energy management devices in the market- they
created a differentiating feature, as they were able to add solar PV energy
generation monitoring to the energy management system. The analysis of this
additional information is essential to shift the loads in order to optimize demand
management.
Table 4-13: Energy Aware's "Matrix 1"
-
Omand
x
Pv fw
g
/
yr
yr~d
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y
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pr"
_________
Table 4-14: Energy Aware's "Matrix 2"
As Energy Aware's "Matrix 1" and "Matrix 2" show -in Table 4-13 and Table 414-, from an analytical perspective Energy Aware business model is quite
simple: they build an ICT-related device that enables efficient management of
loads and distributed generation, allowing the consumer to meet financial and
environmental needs.
20 https://neur.io/pr/
54
Energy Aware model does not take advantage of attribute synergies, but relies
on the technological innovation of their products, which allows them to process
solar panels information in their home energy management device.
8. Sequentric is a provider of smart grid technologies for consumers and utilities.
With the commercialization of their Communication Gateway they enabled the
connection between meter readers and thermostats (for data collection), load
control modules (for load management or demand response) and smart vehicle
charging transponders that can optimize the use of energy in Electric Vehicles
[EV] charging.
In this business modelz" Sequentric builds the load management devices, and the
ICT devices to communicate with loads and sensors. One load that is particularly
relevant for DESs -because of its growth potential and its relatively high
consumption- is the EV charger.
In addition to the commercialization of Sequentric-built devices, their business
model considers managing device-based load profile information. Utilities are
willing to pay for information that makes them understand what happens
behind the meter, in order to optimize their demand forecasts or offer win-win
deals to consumers. One of these deals relate to when and how they charge the
electric vehicles. Using Sequentric's devices, they can offer special tariffs for
those who charge EVs in they way the Utility needs (for instance, slow charging
from 1AM to 4 AM).
"Matrix 1" in Table 4-15 shows Sequentric's business model, highlighting the
synergy of providing information, while being the ones that build the deployed
devices.
21 https://appanet.cms-plus.com/files/PDFs/201ONationalConfSethHulkowerSmartGridPresentation.pdf
55
Table 4-IS: Sequentric's "Matrix 1"
Imtg"?
Table 4-16: Sequentric's "Matrix 2"
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"Matrix 2" in Table 4-16 shows that with the "Build" attribute of the business
model, Sequentric is meeting the financial and environmental needs of
consumers, which want a better energy management to lower their bills while
helping to preserve the environment. It also shows that the information
provision enables utilities to manage the adequacy of their energy supply.
56
4.2 Overall Analysis
Aggregated Matrices
As it was introduced in Section 2.3, valuable information can be obtained when
aggregating the data from the 8 business models in each of the matrices.
OIVIN~ed
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Figure 4-1: Aggregation of Business Models Over a "Matrix 1" Table
Figure 4-1 presents the aggregation of the 8 business models over a modified
"Matrix 1" (rows "Build" and "Fund" were switched to allow a clearer graphic
representation). After a simple analysis of the data that shows us what technologies
and approaches are these companies taking, the following conclusions can be
drawn:
If Operating,Owning beats Funding: The business models that "Operate"
involving relatively high upfront investments (DG, DS, EVI, not DR, not
ICT devices), bundle that attribute with the "Own" attribute. Operating
and maintaining their own devices is less risky and complex -legally
speaking- than funding and then operating and maintaining their
consumers' devices. Therefore, as consumers usually don't want to bear
the operation and maintenance risks, there is no much market for the
"Fund" attribute.
57
*
Forconsumers, eitheryou Operate oryou Provide Information: The
information provided by the business models that "Provide Information"
to consumers, usually aims to enable the DES to "Operate" (like Opower's
Behavioral DR) or aims to optimize the DES' operation (for instance,
WeatherBug's Home Energy Management System). This means that the
benefit of the information is not part of a business model (it is not being
sold), but an input or enabler of the DES. "Operate" and "Provide
Information" could coexist when the information is sent to utilities or
system operators instead of consumers (like Sequentric's model, if they
also operated their devices.)
-
Companies take advantageof synergies: After populating the data in the
aggregated matrix it was clear that the synergy/contradiction right
triangle of "Matrix 1", presented in the "Utility of the Future" Phase I
Report (Bharatkumar et al., 2014) was correct, or at least aligned with
this market sample. From the 4 business models that have more than one
attribute, every one of them and their attributes has synergies with the
others chosen in the business model.
Most companies in ICT leverage other assets or skills, but ones are more
protectedthan others: Opower, famous for selling ICT devices for energy
management, leverages its closeness to consumers in order to sell DR
services to utilities. Sequentric, manufacturer of ICT devices and EVI, sells
load profile data to utilities. WeatherBug leverages their expertise in
weather and data management. Energy Aware relies on their technology,
capable of including DR in the Home Energy Management System. In this
scenario, companies like WeatherBug have an advantage, as their skill
looks more difficult to replicate than a technology like Energy Aware's.
58
In the case of "Matrix 2", Table 4-17 shows the needs fulfilled by the different
business model attributes and by the DES technologies themselves.
Table 4-17: 8 Business Models' Aggregated "Matrix 2"
From this aggregated matrix, the following conclusions can be drawn:
*
"Adequacy and/or capacity": Consumers get capacity from DES's DG and
DS, while utilities get capacity from Demand Response. Both consumers
and utilities can enhance their capacity's adequacy through information.
*"Resiliency" is different for consumers and utilities: Consumers get
resiliency through a smart use of DG and DS, usually enhanced by the
provision of information (like WeatherBug's) that enhances the energy
management. Utilities can improve their resiliency by buying ancillary
services from utilities (like Konterra's project)
*No "Recovery" services provided by DESs yet: T he common size and high
cost of largest operative DESs (like microgrids) are still not enough to
provide black-start or other recovery services to utilities.
* "Low Upfront Costs" are obtained by leases: As it was mentioned in the
context of aggregated "Matrix 1", the "Fund" attribute is not a preferred
option in this market, and the "Own" attribute prevails. Most of this
ownership models are executed through leases and, in some cases, PPAs.
Leases and PPAs also provide "Stable Variable Costs".
59
e
"Low Variable Costs": These can be obtained by consumers as a lower rate
from the DES administrator that shares savings due to efficiency
(expertise), due to scale economies (central operation) or due to the
benefits of vertical integration (maintenance by the manufacturer).
Payments or discounts made by the utility to the consumer could also be
considered as netting outflows, and then as a lower cost (payments for
DR, Ancillary Services, or consumption data sharing).
" Three main ways to provide "EnvironmentalAffordability": The most
common way in which Consumers fulfill their environmental awareness
needs is through renewable distributed generation, that ensures them
that they are consuming from a "green" source. Utilities can also meet this
need by getting frequency regulation ancillary services from DESs.
Finally, DESs can provide environmental affordability to both consumers
and utilities through Demand Response programs.
"
The "Operate"attributeprovides "Time ConsumptionAffordability": In the
8 analyzed business models, operating was the only way that Time
Consumption was tackled. Even when it seems obvious that ICT solutions
can save time through automation, most of the devices focus on investing
time to save energy and money, or to increase system's convenience.
*
"Build"does not provide value by itself the DES Technology does: Building
or Installation is a one-time process that is necessary for the existence of
the DES, but that by itself does not add any value. A DES system requires
operation as it involves sensing and actuating. It can be argued that
"Build" is the base of the DES Technology, but in these cases, like the
provision of Access, the adopted convention was to assign the delivered
value to the DES Technology.
60
Chapter 5 - Business Models Evaluation
5.1 Quantitative Evaluation of Qualitative Data
Chapter 3 described the current characteristics and needs of stakeholders in the
Chilean electric power system. It also presented 8 future state scenarios, depending
on the evolution of three key variables: penetration of renewables, tariff structure
changes and grid reliability. In each of those 8 scenarios stakeholders will prioritize
needs differently, assigning a particular weight to each of them. Over that base, the
selection process will evaluate how well are DES-related business models able to
fulfill stakeholders' needs.
There are a couple of characteristics that make this evaluation process particularly
challenging. First of all, electricity related needs are very diverse and have different
relevance for each stakeholder. Secondly, there is no standardized quantitative scale
to measure need fulfillment levels. Thirdly, in most regions, like in Chile, there is no
available quantitative data to rank the relevance of a "Need A" over a "Need B" for a
particular stakeholder.
In this scenario, the evaluation process is performed from the standpoint of a
developer making a "go/no-go" decision for the eight business models, using Pugh's
method or decision matrix method. Pugh's method is very useful as a quantitative
technique to support judgments about qualitative information. As stated by Ullman
(2000) in this method "[s]election among itemized alternatives is accomplished by
relative comparison to a set of criteria defined by the issue. Each alternative is
weighed by its ability to meet each criterion. It results in an abstract satisfaction
calculation for each alternative".
In this evaluation, each of the 8 foreseen scenarios (presented at the end of Chapter
3) will be reflected on its own Pugh matrix, which will have its own needs' relative
weights, which will determine the quantitative score of each business model in that
61
scenario. Therefore, for each matrix, and consequently for each scenario, a given
business model will have a score that -as seen in the equation below- is the sum of
the score obtained on fulfilling each need, multiplied by the relevance (weight) of
that need in the current scenario.
Score of Need" i" x Weight of Need" i"
Relative Need's Weights and Business Model's Need Fulfillment Scores
The first logical step, then, to perform Pugh matrix evaluation processes is to specify
each scenario's weighting mix among the needs. This computation of the relative
importance of the needs for end-users and utilities in the 8 scenarios was performed
in two steps.
The first step was assigning the relative needs' weights for the current Chilean
scenario, which is very similar to the base case for the 8 envisioned scenarios (10%
renewable generation, 100% volumetric tariff option available and reliable grid).
The second step involves adding or subtracting points on specific needs' valuation
based on the changes in each of the three variables that define the scenarios
(changes in renewable penetration, tariffs and/or grid reliability).
In the first step, the ranking of needs' relevance for consumers and utilities in the
current Chilean scenario is the following:
0
=
Not important for the average stakeholder
1
=
Important for the average stakeholder
2
=
Very important for the average stakeholder
This methodology to valuate consumers and utilities needs' generates the scores
presented in Table 5-1, which are the base for the weights in Table 5-2.
62
Table 5-1: Base Scenario's Ranking of Needs' Relevance
Table 5-2: Base Scenario Needs' Weights
P-8-'
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s
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, f i&
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f
A similar logic is applied in the second step, to assign weight to the needs' in each of
the 8 scenarios. Here, scores of -1, 0 or 1 points will be added to the base case
depending on how the key variables differ between the new scenario and the base
case. This means the added score points will be assigned as follows:
-1
=
if in the new scenario the need decreases its relevance
0
=
if in the new scenario the need keeps it relevance
1
=
if in the new scenario the need increases its relevance
In our 8 generated scenarios this will imply that in those that have higher
unreliability of the grid, consumers and utilities will add 1 point to the 2 points that
each of them already assigned to the "Resiliency" need on the base case. Then, both
will end up having 3 points for the relevance score of "Resiliency", and consequently
the weight (percentages) will vary. Similarly, consumers will also take 1 point away
from "Low & Stable Variable Cost" base score if the 100% percent volumetric (BT1)
tariff option is eliminated. Finally, utilities will add 1 point to "Adequacy" relevance
base scores in those scenarios having 20% of non-hydro renewable generation
penetration in the grid.
63
Table 5-3 below presents the input data and the results of the computation of needs'
weights for the 8 scenarios. Starting from the base case relevance scores (black
row), the relevance points that should be added are presented in the gray rows, to
then calculate each scenario's total relevance scores in the green rows. Finally the
needs' weights are presented in the yellow rows. The same calculations were made
for utilities needs, whose table can be found in Appendix B.
Table
5-3: 8 Scenarios' Consumer Needs' Weights
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The needs' weights that are presented in the 8 yellow rows at the bottom of Table 53 will become the base to measure the total score of a given business model in each
of the 8 scenarios.
64
Once that the evaluation field is clear in each of the 8 scenarios, quantitative scores
should be assigned to reflect how each DES-related business model is able to fulfill
each specific need. Following the Pugh method, these scores will be assigned based
on how qualitative data fits in a discrete axis 2 2 . In this case the alternatives for need
fulfillment scores would be: 3 points if the DES-related business model fully meets
the need, 2 if it meets most of the need, 1 if it meets a little of the need, 0 if it doesn't
meet the need at all. Table 5-4 and Table 5-5 below show the resulting assigned
scores for the need fulfillment of each of the 8 DES-related business models for
consumers and utilities respectively.
Table 5-4: Consumer Needs' Fulfillment Scores of the 8 Business Models
Access
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0
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1
1
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0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
0
0
0
0
0
0
0
0
1
0
0
1
0
0
1
0
0
1
Table 5-5: Utilities Needs' Fulfillment Scores of the 8 Business Models
U
UTiLIiE
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0
0
0
0
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A quantitative approach was tried by the author in the context of the investigation in the UoF
Project, to achieve a numeric valuation of profitability, reliability and environmental affordability of
the different DES configurations, using DNV KEMA's MicroGrid Optimizer (MGO) tool. This effort,
however, could not be completed as -during the analysis of the software- some relevant
modifications and expansions were required, which were not possible to be finished in the time
scope of this thesis. More information about the MGO tool can be found in Appendix A.
22
65
The rationale behind these scores is presented on Table 5-6 and Table 5-7.
Table 5-6: Rationale of Consumer Needs' Fulfillment Scores
CONSUMM
MAuancr(C
Acess
o
o
o
Solar City's model that could be used to provide access to off
grid consumers that have Internet access. The operation of the
service as a DES requires internet or cellular avalablity, which
Isavailable in most of the country.
0
I
~-
0
0
Both DESs including distributed storage are able to provide
some resiency to consumers.t can't provide resriency 24/4
and Konterra can't provide r ougiency for Its funrgY
enables a better use of G and Sto enhance
Weather
Resiliency meeting a
of the need.
0
kh
None of these business model provides ful Adequacy or
Capacity. Ti1's provides fuN capacity, but not full adequacy, as It
still requires to buy from the grid. Solar City and Konterra
provide a little capacity to be added to the grd's main power
kinflow. Weatherfug enables a better use of0G and DS to
enhance Adequacy, meeting alttle of the need.
0
0
0
l
r
e
m ettle
n
The lease contract of Solar City and the PPA signed with theMu
pensiron fuyns Inthe
thse
0hat
th es as b us
th s I different:
a0
r
0
model
ful
. nme
the nae
trase
weomen
n I th a n
, a y mev
t
I
of lowtra
low and stable variable cost. Some of them don't as Konterra's
fromte
focuses more on sustainabtity and resiency. TIL's
s
model
Respoentnwhich
ed in th e PPA o r lease, b ut
m
Aodo ehl h as a stable varta e cost, fbie
not necessaryiow than the grid provided power.
f0ro m
MrUME
kalN dWM
Ma lOnmsyptn AeM rdabliy
Just like with Variable cost, most of the DES-related business
models provide environmental affordabity
for consumers.
Models that avoid consuming power (like DR) or that makte
consumption more
lient (though home energy
0 management systems) funlly meet that need. Models that
provide renewable generation capacity partly meet the need.
Table
5-7:
enetio
Ra
lities
0
0
0
6
6
0
0 The only DEq-elated business model from the list that is able to
1 provide some00level of resiliency to utilities Isthe Konterra
Amneservices market to allow utilities
0"""""
model, which can sell anciary
0 regulate the grdwhen incudng m Intermittent renewable
0 generation.
ULn
B
but th~tsPagn11t
requiresmath. avaelabilitynesf
tu pfronti
LEW
renewablep
genesration torenter thershvystemD.ma0
0
0 10
0 10
-0 10
M0
0
0
0
0
0
0
--
me
nvieWtEV
0g
00
LOa Stable Varilea cont
0
0
0
0
Affetdablilty
UT~flBGervirormuntal
Response model, which mequprm consumers engagement
An~~~~~ote model tha hep utilites wit adequacy mnagmen Is
the Information of consumers load, provided by Sequentric
model.
0"g
0 _eeabdeqgenerationy
__
0
00
0
DES-reated business models that provide operation services
("Operxt business model attribute) takte care of most of the
Mw required by the DES, fuoey meeting the Time Consumption
Affordabity need.
Behavora m an
quitdlower In thethOpowed
thlsfurdsponsehelT
Needs' Fulfillment Scores
0-
--
o
Time Consiamption Affirdi~ty
meet their Environmental Affordability needs0
0
of EnerNOC and Opower, or by buying
-0
ragu Wion from Konterra to allow a higher penKtratlon of
0 reneal generation, but this requires the availability of
0
0_ renewable generation to enter the system".
0
0
10
Utiltes can
1through the DR models
66
Feasibility and Challenges of the Business Models in the Chilean Context
Revisiting the "DER/DES Consumer Adoption Dynamics for the Chilean Context"
diagram on Figure 3-4, it can be seen that -besides the valuation that consumers
give to DESs (which is captured on the needs' analyses explained in the previous
pages)- there are four other inputs affecting "DER-DES Consumer Adoption", that
may not be as relevant as the alignment with needs, but that could make a business
model unfeasible or significantly decrease its success probability. These inputs are
the cost of grid electricity, eventual financial incentives (or disincentives), the
adequacy of DES-related business models to the Chilean market, and the regulatory
adequacy for DES adoption in Chile. A section of the diagram on Figure 3-4 that
shows this factors is presented below in Figure 5-1.
DER-DES
+
Adpo
DER-DES
valuation
Reglator
Adequacy for
DES-DER
Financial
Cost of Grid
Electricity for
Inwndves from
GovN
mnet,
or
consumsUility
Aggregator
Socio-Economic
Adequacy of
Business Models
Figure 5-1: Factors that affect DER/DES Consumer Adoption
Based on the information presented on Section 3.1 regarding electricity prices in
Chile, where the average daily marginal price for the last 12 months was over 160
US/MWh, the "Cost of Grid Electricity for Consumers" is going to be considered as
"High", even when these prices are not immediately or totally transferred to
consumers given the Chilean structure of supply contracts between generators and
distribution utilities. This definition of "High" means that business models that are
financially viable in an average country are very likely to be financially viable in
Chile.
67
Regarding financial incentives, the analysis will consider this in a neutral position,
neither helping nor constraining (specific taxes) DES business models, which has
been the market-oriented policy in Chile for the past four decades.
While the cost of grid electricity and a neutral position regarding incentives affect all
business models in a similar way, the adequacy of the Chilean regulation for the
adoption of a DES and the adequacy of a DES to the Chilean market could be
different for each one of the business models. Aligned with that, the output of
challenges and constraints analysis for the 8 DES-related business models is
presented below.
1) Real Time Pricing for Demand Response: Demand Response companies
will have to face the challenge of an inadequate information time rate for
real prices in the Chilean electric power system. Even when this does not
make the model unfeasible, it significantly reduces the profit it can make,
decreasing the interest of companies to apply it in Chile. This challenge,
which affects EnerNOC and Opower, is considered likely to be overcome
in the next few years.
2) Wholesale Energy market and Ancillary Services market not open for
non-generators: Business models considering transactions in wholesale
market to buy electricity and to sell regulation might not be financially
viable if that access is not granted. This challenge, which affects TIL and
Konterra, could face some opposition from incumbent utilities and could
be hard to overcome.
3) Cultural particularities: In Chile, renters -not landlords- pay electricity
bills, and they pay fully volumetric tariffs. This would complicate business
models involving fixed payments made by the landlord based on PV
installed capacity. This challenge, which affects TIL, seems very hard to
overcome.
68
4) Technological threshold and market size: Most DES Enablers business
models assume that there is a base of consumers using or willing to use
Home Energy Management Systems. Today that critical mass does not
exist, and the size of the Chilean market makes that -even when these
devices penetration reaches an adequate percentage- the amount of
devices might be too low to profit. This challenge seems very hard to
overcome for WeatherBug and Energy Aware. Opower and Sequentric
could get some help from the utilities they serve, as sponsors for the
penetration of their devices, but it will be hard anyways.
Based on that information, and following the same scheme of the Pugh method, the
feasibility scores for the 8 DES-related business models are presented in Table 5-8
below.
Table 5-8: Feasibility Scores of the 8 Business Models
VeyHard
Hard
VeyHard
Hard
69
5.2 Pugh's Method Output
One of the benefits of the Pugh method is that all the qualitative information that in
the previous section was translated into quantitative data can now be aggregated to
make decisions, to state preferences or to indicate success likeliness.
The first step of the process is to determine each business model's aggregated need
fulfillment score. To obtain that, a weighted sum of each need fulfillment scores has
to be performed for each business model in each scenario. Table 5-9 shows the case
for consumers in scenario 1 (other scenarios can be found in Appendix B). There,
the scores of each business model in each need -rows with gray headers- are
multiplied by the needs' weights for the scenario -black row at the top-. The
product of these multiplications -yellow header rows- is then added for consumers
and utilities, resulting in the need fulfillment scores presented in Table 5-10.
Table 5-9: Scenario 1 Consumers Needs' Weighting Table
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Table 5-10: Scenario 1 Needs' Weighted Fulfillment Scores
MW
...
I
70
Table 5-11, which presents the need fulfillment scores for the 8 scenarios, shows
that -even when there are some variations among them- business models having
good scores in one scenario also have good scores in the rest of them. The same
happens with bad scores. This can be seen more clearly in Table 5-12 that highlights
those scores above 1.5, assumed as the threshold for good performance.
Table 5-11: Need Fulfillment Scores for the 8 Business Models in the 8 Scenarios
MTKAP.ML79
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1.49 13
The trend of good performance in the scenarios, as well as the linear average of the
scores, coincides in signaling business models 1,2, 4 and 5 as the ones that perform
well in fulfilling stakeholders' needs.
71
If we now consider the feasibility scores, which were introduced in the previous
section and presented in Table 5-8, TIL's business model gets off the success list, as
-with its score of 1- it is considered very hard to be implemented.
Table 5-13: Feasible Business Models that Fulfill Stakeholder's Needs
Table 5-13 indicates the DES-related business models that are considered likely to
be successful if implemented in the context of the envisioned future state (5-15
years) of Chilean electric power system. This final list is composed by EnerNOC's
"Capacity Demand Response" model, Opower's "Behavioral Demand Response"
model and Solar City's "Residential Distributed Generation and Storage" model,
which were already presented and described in Section 4.1.
72
Chapter 6 - Conclusions and Recommendations
6.1 Conclusions
This section discusses the most relevant conclusions that have been presented
throughout this document, as well as those overall recommendations that can be
drawn when combining them.
Diverse Systems have diverse needs, requiringdiverse solutions
The statement given in Chapter 1 which said that "technologicalsolutions,
innovative business models or regulatorybest practicesshould not be exported
from one geography to another without a sound analysis",was originally
thought in the context of bringing this solutions, business models and best
practices from one country to another. Since Chilean electric power systems
are so diverse in terms of climate, economic activity, energy sources and
demography, it is very likely that the relative weight of the needs will differ
in each of them. Then, it seems reasonable to apply this statement inside the
country's boundaries, differentiating among the four main Chilean electric
power systems. For instance a business model based on the installation of
distributed storage to provide reliability, could be more valuable for
consumers in the Aysen system -due to weather related factors- than in the
Central system, but might only be financially viable in the Central system, as
its population density is by far higher than the one in the Aysen system.
ICT boosts DESs' value creationover DERs
As presented in Chapter 2, most of the value creation of DESs -above that of a
DER- is based on the synergy achieved by involving ICT capabilities of
remote sensing, data management, and remote control. These new
capabilities are key to allow different synergy models that range from load
profile information sharing to generation or demand response aggregation.
73
Throughout time, different electronic devices and electric appliances are
incorporating networking interfaces 23 , making these capabilities -and
particularly those related with managing huge amounts of data, like Big
Data- become even more relevant, as they provide tools to address the new
needs and requirements imposed by the system's environment. This
conclusion is valid for any EPS, and not only for the Chilean ones.
The value of Pugh'smethod for assessing business models based on qualitativedata
The output of the evaluation process performed in Chapter 5 indicated a
subset of business models that, as scoring high in the need-fulfillment scale
and in the feasibility scale, were considered likely to be successful if
implemented in the envisioned states of the Chilean electric power system
(represented in this calculations by the needs of the Central System).
However, this specific information regarding this particular business models'
set, may vary significantly depending on the choice of business models to be
included in the first sample. In that context, the real value of the Pugh's
method 24 for any electric power system, is not on the results, but on the fact
of providing a systematic tool for decision-making processes in business
models selections based on qualitative data, through a method regularly used
for concept's selection in Systems Engineering practice.
The value of trends in relationsbetween business models, needs, and technology
Probably the most interesting conclusions can be drawn after the analysis of
the trends in the relations existing in real-life business models among
business model attributes, needs and technologies. The analysis of the
aggregated matrices presented in Figure 4-1 and in Table 4-17 generates a
long set of conclusions, which were already presented on Section 4.2, and
that are valid for the Chilean system as well as any other particular system.
http://www.mckinsey.com/insights/high-tech-telecoms-internet/the-internet-of-things
24 For more information on Pugh's method, see Section 5.1.
23
74
The value of identifying and understandingthe systems' dynamics
The analysis of the "Electric Power System's Dynamics" causal loop diagram
(Figure 2-4) provides valuable information regarding the factors that drive
change in the system, and about the relation that defines how that change
affects other variables through reinforcing or balancing loops. The Business
Model Analytic Framework [BMAF] presented in Chapter 2, which is the
main tool to analyze and understand business models in this thesis, is based
on the three key dimensions of the EPS' dynamics (given a regulatory
framework):
*
Unfulfilled Needs -which will be addressed differently by each
business model, depending if the stakeholder is a consumer, a DES
administrator, a DES entrepreneur, or an incumbent utility.
e
Technology Development -that defines the technology mix used by
the business model to provide a service-, and
*
Business Models' Innovation -characterized by new business model's
attributes combinations in their value proposition.
A complete analysis of these three dimensions should provide a sound
understanding of the specific characteristics of a business model, being able
to understand how each business model relates with its surrounding system
and its dynamics. With that knowledge the business model could be tailored
to face the challenges that come with systems' evolution, maximizing its
value.
75
6.2 Recommendations
Based on the conclusions of Section 6.1 and the general knowledge base of this
thesis, the following recommendations are suggested for the different stakeholders
involved in this system.
Recommendations To Consumers, DES Administrators,or DES Entrepreneurs
When selecting energy solutions:
Decisions regarding electric supply usually require -even at residential
level- considerable investments that take several years to be recovered. This
fact highlights the relevance of understanding the dynamics driving the
evolution of systems, and particularly the evolution of needs. The better the
vision of the system's evolution, the better the choice of the energy solution
to be implemented. This considers that the selected solution has to fulfill, as
much as possible, the system's needs in the short and in the long run.
When developing greenfield business model projects:
The playing field for DES business models presents a couple of
characteristics that the DES entrepreneur should be aware of. The first one, is
the low margin of the simple energy supply, produced by the usually low
marginal costs of centralized generators and the relatively low transmission
and distribution tolls. The second one, is that competitive advantages -based
on technology- are risky as they can be copied or beaten by better
technologies, which isn't an unlikely scenario considering the amount of
companies in the technology devices market.
In such a competitive scenario, the focus should be set on developing a lean
and effective business model, that efficiently takes advantage of all possible
synergies based on a correct understanding of stakeholders' needs. Here the
business model attribute framework presented in Section 2.3, on its matrices
76
1 and 2, provides useful recommendations regarding the potential synergies
(or the absence of them) that the new business model could take advantage
of (or think on outsourcing), as well as the different business model
attributes that can be used to meet a particular need.
Recommendations To Incumbent Utilities
When analyzing their long-term strategy:
Just as it was recommended to consumers, utilities should also focus on
understanding the dynamics driving the evolution of systems, and
particularly the evolution of needs. Those evolving needs will probably be
the drivers of new business models ideas, which will fuel the technology
development machine, thus leading to potential scenarios of value migration.
As explained by Slywotzky (1996), value migration occurs when incumbents'
outdated business models do not meet the evolution of customers needs,
creating new business design opportunities. Incumbents often ignore or
overlook these opportunities to address new customer needs,
presenting significant openings for newcomers.
It seems evident that value migration could harm utilities if they do not start
moving soon, which is clearly an uncomfortable change for these companies
known by their rigidity and risk aversion. There are, however, some
interesting examples of utilities that -at least in words- are embracing
changes towards a more decentralized grid, and whose statements might
serve as reference for utilities looking for a way to move in this changing
scenario.
One of them is RWE -Germany's second largest utility-, which announced a
shift in the company's business model, to a "project enabler and operator,
and system integrator of renewables" model. They also stated that
77
"Developing an innovative and profitable prosumer25 business model is a
challenge we also need to address successfully". This statement clearly goes
in the direction of DERs and DESs.
The other company that -especially through its CEO, David Crane- is
continuously talking about these changes is NRG. Crane says that the
centralized electricity supply model is "in jeopardy" due the increase in
distributed generation and distributed storage technologies which will make
consumers "only turn to the 'the Grid' as a last resort". In this context, and
regarding NRG's vision, he states, "This is not to say there is no role for
utilities down the line. But that prize will go to those that evolve with the
times and NRG certainly hopes to be one of the leaders serving this new
future."
When developing brownfield business model projects:
Aligned with the vision of NRG's CEO, this innovative DES-related business
models are also open for those utilities willing to be more flexible. If that is
the case, utilities could also take advantage of the business model attributes
framework, and particularly from "Matrix 1". The plan is to look for the
synergies between the existing business model attributes of the utility, and
the new business model attributes of the DES-related project. A variation of
"Matrix 1" developed by the author in the context of the "Utility of the
Future" project and presented in its Phase I report (Bharatkumar et al.,
2014), lists some of the opportunities and challenges for regulated
distribution utilities implementing brownfield DES-related business model
projects (Table 6-1).
"A prosumer is a person who is both a producer and consumer of electricity -usually in the form
of having some solar PV on the rooftop."
(Source: http://www.greentechmedia.com/articles/read/clean-techs-10-buzzwords-of-2013)
25
78
Fund
Utilities are not well suited to
manage large amounts of
information (compared to
Amazon Web Services, or other
Big Data companies)
As a company interfacing
directly with end-users and
transmission companies/system
operators, it could obtain
valuable information
It is not suited to be a
If dedicated to it, it might be
manufacturer of DES
suited to design and implement
components and might face
the system integration of DESs,
challenges keeping the fast pace
as a small version of electric
of technology changes in this
power systems
sector
Funding is a business attribute
that is not in present utilities,
and they would probably face Fund
competition from financial
industry
Challenges
As a long-term and stable
investment class, it could rather
easilyget capital to fund DESs
As a company that has the knowhow of electricity distribution
network operation, it might
have an advantage when
operating DESs
As an asset heavy company, its
financial profile won't be
affected by the addition of new
DER or ICT assets
Opportunities
Regulated Distribution Utility's
/
1~
x
Recommendations To Regulators
When defining general regulations:
Defining a regulatory environment that presents barriers to DES integration,
one that is neutral, or one that supports it, will affect the rate and quality of
DES integration in the power system. Regulators then -and just like
consumers and utilities- should be aware of the dynamics of the system and
its stakeholders' needs. Their objective should be set the right level of
support or constraints in order to provide a leveled playing field for new
entrants and incumbents. The focus should be on finding a fair way to
promote business model innovation -either by utilities or new entrants- as a
way to fulfill stakeholders' needs 26 .
In the case of Chilean regulation, the leveled playing field for innovative
business models will be mostly related with the information asymmetries
between DSOs and DES entrepreneurs. One example of these asymmetries is
the charge that DESs have to pay to DSOs if their DG exceeds the maximum
penetration capacity that doesn't require additional works and modifications
in the grid. In this case -which could affect Solar City's business model- the
information to perform charge calculations is clearly asymmetrical, and the
regulator should take actions to ensure the charge is fairly calculated.
As mentioned in Section 5.1 -when assessing the feasibility of business
models-, the Chilean Spot (Wholesale) Market can only be accessed by
generators trying to fill the power or capacity gaps between their operation
and their contracts. This structure should be changed if the goal is to allow
business model innovation. A change like this should be required for the
operation of Demand Response programs, in order to be paid by the energy
Business model innovation is required because, as stated in Figure 2-4, "traditional business
models and regulatory frameworks might not be able to change at a rate adequate enough to keep
the pace of consumer needs' evolution". However, "the rate in which innovative business models
meet unfulfilled needs is much faster than that of traditional business models" (see Section 2.2).
26
80
reduction they are able to provide to the system, instead of dispatching
another power plant. Also models like TIL's in Germany -who need to buy
energy in order to cover the short position of their PPAs- require access to
the lower prices available in the wholesale market.
When defining technical regulations:
Sometimes technological evolution makes playing fields that for years were
considered leveled, to become unfair or restrictive for new entrants. That
might be the scenario that companies like EnerNOC would face if they
implement their business model in Chile. This happens because Demand
Response models, even if able to access wholesale markets, might loose most
of its profitability if they do not have access to marginal cost of electricity
information. The information of the marginal cost of electricity is currently
managed by the CDEC (TSO controlled by incumbent utilities) who publishes
marginal cost values with a couple of days of delay. In this context, the
challenge for the regulator is to define a regulatory framework that
motivates the different stakeholders to collaborate in the development and
operation of an information platform for marginal prices.
In addition, other technical regulations may have strong impacts in
Distributed Energy Systems' adoption. One of these regulations refers to the
certification and authorization procedures for the technologies that compose
DESs. The office that regulates this devices and their connection to the grid in this case the Sub-secretary of Electricity and Fuels [SEC]- should look to
facilitate the integration of DESs, by establishing certification procedures
affordable in time and resources for new entrants, which meet the required
safety and reliability standards.
81
6.3 Further Work
A holistic approach -to electric power systems as socio-technical systems- like the
one developed in this thesis, will for sure leave some questions unanswered or some
fields in which different methods could be utilized. Some of that work is in the
roadmap of the "Utility of the Future Project", which will continue researching about
the scenario that will be faced by the utilities in the next 15 to 25 years.
Specifically, a quantitative assessment of the value that the different DESs add to the
grid will be developed. The author -in the context of Phase I of the UoF projectdedicated a long time to analyze the code of DNV KEMA's MicroGrid Optimizer
[MGO] tool 2 7, trying to expand its valuation for microgrids to assess generic DESs.
This expansion was not possible in the time frame of UoF's Phase I, but it will
probably be possible in the time frame of the whole project.
In a less-quantitative analysis, much work could be derived from the analysis of
both Causal-Loop diagrams -Electric Power Systems' Dynamics (Figure 2-4) and
DER/DES Consumer Adoption Dynamics (Figure 3-4)-, which could range from the
effects of tariff structures in consumer adoption, to the role of regulatory innovation
in fulfilling consumer unmet needs by allowing business model innovation.
Whatever the focus of the research is, the recommendation is to keep the systemic
view, considering electric power systems, not as technical, but as socio-technical
systems.
27
A deeper view into MGO can be found in this Appendix A.
82
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84
Appendices
Appendix A: DNV KEMA's Microgrid Optimizer Toolfor Valuation of DESs' Impact
As mentioned in Chapter 5 and Chapter 6, the first option to value DESs' impact on
the EPS -for this thesis and for the "Utility of the Future" project- was to work with
a tool able to quantify the Net Present Value of a DES, as well as its improvements in
reliability, emissions and other metrics related to stakeholders needs.
Instead of building a new tool from scratch, the decision was made to look for a
partnership with one the developers of similar tools available in the market, which
could then be expanded and modified to meet DESs' requirements. Two main tools
were analyzed: DNV KEMA's MicroGrid Optimizer [MGO], and Lawrence Berkeley
National Laboratory's DER-CAM. The choice was made to start working with MGO,
and the author of this thesis dedicated a considerable time trying to modify the
software's code to make it work for generic DESs. Even when this first effort was not
successful, the enhancement of this tool will keep going in the next phase of the UoF
project. The information cited below, retrieved from DNV KEMA's website 28, lists
most of MGO's capabilities and characteristics.
"DNV KEMA's proprietary MicroGrid Optimizer (MGO) is a comprehensive
cost/benefit analysis model that evaluates the financial decisions of
microgrid development and planned operation. The model incorporates
investment choices for a wide range of technologies including:
*
*
e
*
e
*
Micro-generation, Combined Heat and Power
Energy and thermal storage
Building and lighting efficiency
Load management
Reliability assessment of critical loads
Distribution system infrastructure
Telemetry and controls"
28 http://www.dnvkema.com/mages/04-12-13_MOCMicrogrid-4%20page%20versionFINAL%20MOC.PDF
85
"At the core of the model is DNV KEMA's proprietary Mixed Integer Linear
Program (MILP) solver which simulates a central Microgrid controller
optimizing energy asset management including: Demand Response (DR)
participation, reliability of non-interruptible and critical loads, inter-grid and
intra-grid energy transfers to minimize operational expense. Also included
are future trends in consumer load management. Incentives for sustainable
energy programs and utility rates are also incorporated."
"The MGO model enables:
Financial analyses of alternative capital and operational investment
scenarios
* Valuation of risk by modeling uncertainty in parameters associated
with climate, demand energy prices and technology costs,
- A comprehensive view of energy asset portfolio management and
operations for a microgrid developer and operator"
*
"The capabilities of the MGO tool allow you to:
-
*
*
*
*
Model multiple building types (e.g., commercial office or retail space,
residential condominium, community center, restaurant, hospital,
campus building and others) and their energy efficiency performance
based on regional weather characteristics;
Assess the financial effects of building improvements and building
energy efficiency;
Simulate tenant behavior;
Test hourly intra-day resource optimization against wholesale market
day-ahead and intra-day prices;
Conduct multi-year microgrid investment optimization based on risk
adjusted hourly simulation; and
Customize simulations of specific microgrid technology offerings
while measuring resulting system performance against a variety of
metrics."
86
Appendix B: Calculation Tables for Business Model's Need Fulfillment Scores
In Section 5.1 we presented Table 5-3, which showed the relative weights of
consumer needs for the 8 scenarios. That same calculation was made for utilities
needs, as can be seen in the Table B.1.
Table
B.1: 8
Scenarios' Utilities Needs' Weights
AffordabOV
I-
I
WI =-=
I
Once the needs' weight in the 8 scenarios -yellow rows in Table 5.3 and Table B.1and the score that each business model received in each particular need -shown in
Table 5.4 and Table 5.5- were determined, the weighting calculations were made to
obtain a single Needs' Fulfillment Score for each business model.
87
While the calculations for consumers in Scenario 1 were included in Section 5.1
(Table 5.9), the rest of the scenarios and Scenario 1 for utilities were not. Those
additional tables are presented below.
Table B.2: Scenario 2 Consumers Needs' Weighting Table
I
I Armma"&pAI~ N~
Mel
mmnr
-1I
3
I
1
1
3
2
3
0
3
3
0
1
3
0
0.00
0.00
0
M
0.00
a
0
056
06
01
000
O.
119
00
OM
MO0
.00
0.00
000
0
0
0
0
0
0
0
00
019
0.00
0O
0M
M
0.00
0.00
2
1
0
0
0.23
0.06
0.06
0.00
0.00
-0.06
0.00
0.00
iw m
0
1
0
sansaeass
3
1
0
0
0
I
isessmr'smser'sm
0
1
0
0
0
035
0.
0.35
MD
0.a00
00
OD
0Q
23
3
3
_
0
3
3
01
19
0
MN
6
036
036
0.6
0
0
3
025
05
025
0
0.19
0.19
0M1
0M00
M
M.00
.3
O0
0.00
36
039
1
0M
03
Table B.3: Scenario 3 Consumers Needs' Weighting Table
I
Ag-
3
0
0
0
0
0
0
0.00
0.23
.00
00
00
00
A00
n0
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Adown
1
1
0
0
1
0
0
015
OM
0.0
0.00
0.00
0.06
O
00
I a sNrI Ia Ie.m
I
0
2
0
0
1
0
0
0.31
00
0.31
0.0
0.00
0.15
0m
0M
sawuma
.... iI
wamUsaha
lasa
Is III
RMNON I Shoib
n.....
... a fts
Akf..&
0
0
0
0
0
0
0
M
0.00
0.00
0.00
000
000
0.00
00
3
1
0
0
0
0
0
0.69
.6
023
0.0
0
0.6
0M
00
IFa"""I'
"
1
0
3
3
3
3
3
0.15
015
0.00
0.46
A6
2
2
3
3
3
3
3
0.31
0.31
0.31
0.46
046
0.46
0A6
0
046
04
3
3
0
0
0
0
0
0.23
0.23
0.23
0.0
0M
00
0.00
Table B.4: Scenario 4 Consumers Needs' Weighting Table
I .I""
I
I "
A
3
0
I
1
1
0
2
0
0
1
0
0
3
1
0
1
0
0
0
0
0
0
0
0
0
0
0
3
3
3
3
3
0.60
0
0
1
0
0
0.13
aO
0.00
0.20
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0.00
0.00
0.00
am
007
om
0a40
am
0.00
e
a0
00
0.00
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0.00
0.00
020
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0
1
0
0
0
0
0
0
0.0
0.00
00
'""
0.00
0.00
0.00
0.00
00
0.13
2
2
3
3
3
3
3
0.27
0
0
0
0
0
0.20
3
3
0.13
0.27
0.
0.20
am0
0.00
0.o
0.00
0a
0.40
OL27
0-20
1
0.40
0.40
1
0.0
0.40
0.40
0.40
O.40
0.00
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Table B.14: Scenario 6 Utilities Needs' Weighting Table
a
Noss 0
0
0
0
0
0
0
0
0
O.O
0.00
0,0
see
0
0
0
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2
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0
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0
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1
3
0
0
0
0
0
0
0
0
0
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0
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0
0
0
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0.1
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0.0
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OAO
-0.00
Table B.15: Scenario 7 Utilities Needs' Weighting Table
I
I
0
0
0-
2
0
0
0-
0
0
0
0
0
a
a
a
0.
0
0.00
I
I
QM.ARD
0
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014
0.36
0.57
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O.W0
O-S7
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0
0.00
0.00
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0.00
0
0
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1
2
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00
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I
0
0
00
00
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am
am10
0
0.00
0.00
aim
0
0.00
0.
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0.14
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-
0
0
0.0
000
0.00
0
0
0
0
0
0.00
00
3
0
0.00
0.00
0.00
am00
0
0
1
a
0_03
0
00
00
0
Men
0.0
aim
0.43
0.43
aim
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am
.
amg
ama
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0.00
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.0,
am0
0.0
0.00
000
.
aim
Table B.16: Scenario 8 Utilities Needs' Weighting Table
P'N
i
AdW$MW
~ ~~
a 2mssu
Po In
n III-MO
~~ I sWWUPINN
.
a
0
0
0
0
0
0
0
0.00
0.00
00
0.00
0.00
0.00
am
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0
0
0
1
3
2
0
0
2
0.00
0.00
00
0
a
0
0
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0
0
0
0M
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000
0.00
0.00
0
0
0
0
0
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00
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0.00
am
am0
ftm
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050
0
0
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asam.aaa-nn
Cutman
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0
0
0
0
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0.00
0.00
0.00
0.00
0.
atm
m
...
a0
0
0
0
0
0
0.00
0.00
0.00
0.00
0.00
0.00
amD
aim
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000
iv
uawuft
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0
1
0
0
3
0
0
3
0
0
0
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0.38
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0.00
.
Om
Om
0
0
0
0
0M
0.
A00
0.00
000
0.00
400
000
The addition of the weighted scores for consumer and utilities in every scenario,
which defines the need fulfillment scores already presented in Table 5-11.
92