Survey of Modeling Capabilities and
Needs for the Stationary Energy
Storage Industry
Prepared for:
Energy Storage Association
1155 15th Street, NW
Suite 500
Washington, DC 20005
202.293.0537
energystorage.org
Prepared by:
Navigant Consulting, Inc.
1200 19th Street, NW
Suite 700
Washington, DC 20036
202.973.2400
www.navigant.com
May 2014
Table of Contents
Acknowledgements ................................................................................................................. iv
Executive Summary ................................................................................................................... v
Study Objectives and Value.......................................................................................................................... v
Study Findings .............................................................................................................................................. vi
System Planning ................................................................................................................................. vi
Real-Time Grid Operation ............................................................................................................... vii
Energy Storage Systems ................................................................................................................... vii
Additional Gaps ...............................................................................................................................viii
1
Introduction ....................................................................................................................... 1
1.1
1.2
2
Study Overview................................................................................................................................... 1
Approach .............................................................................................................................................. 2
1.2.1
Characterize Existing Models and Tools ........................................................................... 2
1.2.2
Define Stakeholder Needs ................................................................................................... 3
1.2.3
Identify Gaps ......................................................................................................................... 3
Characterization of Existing Models and Tools .......................................................... 4
2.1
2.2
2.3
System Planning .................................................................................................................................. 5
2.1.1
Portfolio Planning ................................................................................................................. 5
2.1.2
Energy Production Cost Simulation ................................................................................... 6
2.1.3
Transmission System Planning ......................................................................................... 10
2.1.4
Distribution System Modeling .......................................................................................... 12
Real-Time Grid Operation ............................................................................................................... 14
Energy Storage Systems ................................................................................................................... 16
3
Definition of Stakeholder Needs ................................................................................. 20
4
Identification of Gaps .................................................................................................... 23
4.1
4.2
4.3
4.4
System Planning ................................................................................................................................ 23
4.1.1
Portfolio Planning ............................................................................................................... 23
4.1.2
Energy Production Cost Simulation ................................................................................. 24
4.1.3
Transmission System Planning ......................................................................................... 25
4.1.4
Distribution System Planning ........................................................................................... 26
Real-Time Grid Operation ............................................................................................................... 26
Energy Storage Systems ................................................................................................................... 27
Additional Gaps and Improvements .............................................................................................. 27
4.4.1
Energy Storage System Performance ............................................................................... 28
4.4.2
Renewable Plant Data ........................................................................................................ 28
4.4.3
Engineering Standards ....................................................................................................... 28
Survey of Models and Tools for the Stationary Energy Storage Industry
Page i
Appendix A Contributing Companies/Entities ................................................................. 29
Appendix B Descriptions of Software Products ................................................................ 30
B.1 Portfolio Planning ................................................................................................................................. 33
B.2 Energy Production Cost Simulation ................................................................................................... 40
B.3 Transmission System Planning............................................................................................................ 50
B.4 Distribution System Planning .............................................................................................................. 56
B.5 Real-Time Grid Operation .................................................................................................................... 63
B.6 Energy Storage Systems........................................................................................................................ 65
Survey of Models and Tools for the Stationary Energy Storage Industry
Page ii
List of Figures and Tables
Figures:
Figure 1. Study Objectives ....................................................................................................................................... 1
Figure 2. Categories of Models and Tools Surveyed ........................................................................................... 4
Figure 3. North American Interconnections ....................................................................................................... 10
Tables:
Table 1. Modeling Tools Reviewed by Category ................................................................................................. 2
Table 2. Portfolio Planning Models ........................................................................................................................ 5
Table 3. Production Cost Models............................................................................................................................ 7
Table 4. Transmission Planning Models.............................................................................................................. 11
Table 5. Distribution Planning Models Matrix ................................................................................................... 13
Table 6. Primary Real Time Grid Operation Vendors ....................................................................................... 15
Table 7. Energy Storage-Specific Applications Matrix ...................................................................................... 18
Table 8. Energy Storage Industry Stakeholder and Analysis Needs ............................................................... 20
Survey of Models and Tools for the Stationary Energy Storage Industry
Page iii
Acknowledgements
Navigant would like to thank the Energy Storage Association (ESA) for funding this important study. In
addition, we would like to express our thanks to the ESA Tools Task Force for their insight, guidance,
and review of this study. Members of the Task Force included:
»
Eva Gardow, FirstEnergy Service Company
»
Udi Helman, Independent consultant
»
Praveen Kathpal, AES Energy Storage
»
Ben Kaun, Electric Power Research Institute
»
Jim McDowall, Saft
»
Ali Nourai, DNV GL
We also would like to acknowledge the input we received from the individuals who participated in our
survey. A full list of contributing organizations is presented in Appendix A.
Survey of Models and Tools for the Stationary Energy Storage Industry
Page iv
Executive Summary
Study Objectives and Value
Energy Storage (ES) can be used to enhance and support the electric distribution and transmission
network, and support the integration and operation of intermittent electric generating resources. The
first pumped storage hydroelectric project in the United States was developed nearly a century ago.
Compressed air energy storage (CAES) plants have been operated commercially for a few decades.
Thermal storage integrated with concentrating solar plants has been operated at utility-scale for about
eight years. Ice storage is also being used to shift electrical demand and consumption to off-peak
periods in commercial deployments. More recently, battery and flywheel based systems have begun
commercial operations on the grid to provide ancillary services, and have met performance
requirements. Building on this commercial experience as well as technical studies and demonstration
projects on these and other storage technologies, such as flow batteries and ultracapacitors, interest in
the grid support and transformative potential for these technologies has led to a renewed interest in both
distributed and bulk scale ES. An example of this trend is the first U.S. ES mandate resulting from the
2013 California Public Utility Commission (CPUC) Decision requiring the state’s three major utilities
(Pacific Gas & Electric, Southern California Edison, and San Diego Gas & Electric) to procure a total of
1,325 megawatts of ES capacity by 2020.
A significant driver for ES is the increasing deployment of solar photovoltaic and wind resources, where
the rapid response of ES can mitigate output variability. Even more important is the flexible operating
range of ES, ramping from full charge to full discharge during the increasingly severe late afternoon
system ramp as the output of solar resources wanes and loads increase.
The increasing interest in ES highlights the urgent need to properly value, integrate, and operate ES
systems. However, given the limited role that ES historically has played in the electric system, many of
the traditional utility planning models were not designed to fully assess ES alternatives. For ES to
become widely and cost-effectively adopted, it is critical that stakeholders have the tools and models
needed to make informed ES decisions.
The Energy Storage Association (ESA) recognized this need and contracted with Navigant Consulting,
Inc. (Navigant) to assess the current ES modeling capabilities in the industry. Based on Navigant’s
investigation, while there has been substantial model development related to ES, there are still a number
of key gaps, including: 1) incomplete representation of ES characteristics in many models; 2) stand-alone
ES planning tools that are not fully integrated with other utility planning models; 3) a lack of
standardization among tools used to evaluate ES; and 4) limits on the data available on ES technologies.
Each of these shortcomings will need to be addressed to improve the analysis of ES applications and
their associated costs and benefits.
This study describes each of the models currently used in the industry to evaluate ES technologies. This
study does not evaluate the quality or performance of the specific models and tools but rather describes
their current capabilities and future development plans, as expressed by the software developers
surveyed and other industry experts. The results will help ES industry stakeholders assess whether a
Survey of Models and Tools for the Stationary Energy Storage Industry
Page v
particular model can fulfill their needs. The study also
highlights shortcomings in current ES modeling to
potentially spur the development of new features and
software packages to meet the growing demand.
Study Findings
Outside of large pumped hydroelectric facilities, ES is an
emerging technology and has historically had a limited
role in the operation of the bulk power grid. As a result,
the widely used system planning models have generally
neglected to account for the complex and variable
operations of ES systems. Most planning software
programs do not concentrate on the unique modeling
required to represent ES accurately. The few models that
do have the flexibility to incorporate the various
characteristics of an ES system are complex and require very long computational runtimes.
Importantly, the need to appropriately represent ES technologies and systems coincides with the need to
model rapidly changing system operations and reliability due to increasing penetration of variable wind
and solar generation, which in itself has presented challenges.
Since ES can aid in the reliable operation of generation, transmission, and distribution, particularly
under the conditions emerging with growing interconnection of variable energy technologies, further
developments are necessary in the existing utility procurement and planning models to properly
represent the value of ES. Additionally, the real-time operation of the grid requires software that will
fully incorporate ES system operating parameters and dispatch units accordingly. Finally, ES-specific
tools are needed to assess and inform the optimal ES system size and control algorithms to maximize
economic, reliability, and environmental benefits.
The following sections provide an overview of the different categories of planning and operations and
their relevance to ES.
System Planning
Portfolio planning models are used to determine the optimal set of least-cost resources to meet the needs
of a utility system or region. Currently, conventional commercially available portfolio planning models
are unable to fully co-optimize between the energy and ancillary service markets, where the operational
capabilities of ES are particularly valuable. Additionally, these models do not account for the ability of
energy storage to minimize ramping constraints compared to traditional technologies.
Energy production cost simulation models are used to perform long-term assessments of system and
market operations, including forecasts of generation, wholesale electric costs, and locational marginal
prices. Energy production cost simulation models incorporate significant system operational detail, but
currently have difficulty capturing the comprehensive value of ES systems. Moreover, due to long runtimes, there may be limits to the number of production cost simulations used to evaluate alternative
portfolios, including those with different specifications on storage. These models are primarily intended
to simulate the hourly level of system operations assuming perfect foresight. On the other hand, ES
Survey of Models and Tools for the Stationary Energy Storage Industry
Page vi
provides significant benefits within very short time-frames and by flexibly responding to unexpected
occurrences. While sub-hourly dispatch is available or is being developed in many of these models, the
capability to model ES operations at the 5-minute level and in response to regulation signals is still in the
early stages. Some vendors have developed system models that can simulate frequency response, and
use these in conjunction with production cost models, but for limited time-frames. For those models that
do have sub-hourly dispatch capability and options for creating specific ES unit parameters, long
modeling run times become an issue. Despite longer run times, there are a number of storage valuation
studies that conduct sufficient numbers of storage scenarios using production simulation to inform longterm ES planning purposes on the grid by extrapolating representative day’s results. Further progress is
still needed.
Transmission system planning models are used to assess large transmission networks. These software
packages help evaluate the operations and reliability of the transmission network under various system
conditions. Transmission system planning models have the ability to incorporate ES and quantify the
associated contribution to system reliability. However, doing so often requires the user to create ESspecific individualized models, which can be a time-consuming process. It is recommended that the
transmission system planning software vendors invest in creating and including ES-specific models in
their annual updates.
Distribution system models are often used by utilities for short- and long-term distribution planning.
The largest gap in modeling ES on distribution systems is that there isn’t a tool that can handle optimum
dispatch plans for different applications. It’s also important to note that the necessary inputs are not
available within the model itself and therefore, ES components often have to be designed outside of the
model. Also, tools to evaluate the impacts of transmission support applications on distribution circuits
are not yet available.
Real-Time Grid Operation
Real-time grid operation includes software used by independent system operators/regional transmission
organizations (ISOs/RTOs) and utilities to develop day-ahead and hour-ahead schedules and market
prices for energy and ancillary services, and to operate the grid and markets in real time. Increasingly,
conventional grid operational tools and market solutions have been supplemented with tools to forecast
ancillary service and ramping needs due to variable energy resources. Many of these tools will affect ES
operations, although their details are often not available to ES developers. With respect to transmission
level operations, energy management systems (EMS) and market management systems (MMS) may need
to be modified to accommodate ES in applications such as frequency regulation. These modifications are
achievable and have already been implemented in certain ISOs/RTOs. The industry should press for
additional specifications and transparency on these tools.
While utility distribution management systems (DMS) offer a potential platform for integrating the
results from various system planning software, advanced DMS systems are still evolving to incorporate
these capabilities.
Energy Storage Systems
ES system tools are developed for specific industry needs such as estimating and demonstrating the
value of ES, calculating optimal system size, controlling ES systems, and optimizing ES system
Survey of Models and Tools for the Stationary Energy Storage Industry
Page vii
performance. These types of models allow for much greater detail in operational specifications, but use
fixed historical or simulated data on market prices and system conditions as inputs. The major
shortcomings with these tools are the lack of available data on ES system operations and the proprietary
nature of many of the existing tools. Shared knowledge would allow developers to create more robust
tools that could then be customized for specific needs. An additional linkage is between simulated data
on future system conditions to be used as inputs to these types of models, to allow for further analysis of
changing system conditions.
Additional Gaps
The most common gap highlighted by stakeholders is the lack of a single ES tool to integrate the inputs
and results of various system planning tools. While an integrated tool may not be feasible due to
computational limits and complexity, a standardized approach on how to value ES using available tools
is also lacking. The development of such a standardized approach would aid the proper application and
value-assessment of ES when compared to traditional resources.
Survey of Models and Tools for the Stationary Energy Storage Industry
Page viii