Control and Coordination in a
Transactive Energy Environment
JEFFREY D. TAFT, PHD
CHIEF ARCHITECT FOR ELECTRIC GRID TRANSFORMATION
JAKOB STOUSTRUP, PHD
CHIEF SCIENTIST / ADVANCED CONTROLS PROGRAM MANAGER
PACIFIC NORTHWEST NATIONAL LABORATORY
28 MARCH 2014
1
Our Grids Are Changing
•
•
•
•
•
Generation is dispatchable
No significant energy storage in the grid
We are in the
Power must be kept
in balance
process
of
Generation follows
loadthese
violating
Distribution “floats”
on transmission
principles!
• Designed/operated for reliability, not economy
Now we want to operate pervasively for joint
economic/control optimization in this newer highly
complex environment with potentially millions of
interactive endpoints.
2
Emerging Trends for US Utilities
Integration of renewable sources at T and D levels
Reduction of grid rotational inertia
Interactive loads/prosumers/expanded markets
Time scale shift (to faster grid behaviors)
T&D level power electronics penetration
DG/DR penetration and local energy networks
(microgrids)
30%
3
New(er) Grid Functions
• VER integration (wind, solar, etc.)
• Wide area measurement, protection,
and closed loop control
• DER/DG integration (distribution level)
• Energy storage integration
• Responsive loads (command, price,
and /or system frequency)
• Integrated Volt/VAr control (LTC/cap)
• Advanced distribution fault
isolation/service restoration
• Third party energy services
integration
• Grid stabilization (H reduction)
• Electric Vehicle (EV) charge
management
• Inverter control for fast VAr regulation
• Local energy network and microgrid
power balance, load sharing and flow control
• Multi-tier virtual power plants
• Energy/power market interactions for
prosumers; Transactive Energy
• Electronic grid stabilization (FACTS
for transmission; DSTATCOM for
distribution)
• Load modulation of buildings, electric
vehicle chargers, and data centers for local
balancing
No single use case predominates; the control approach must support
ensembles of new functions; utilities are being driven to select their unique
function sets.
Issue: Grid Coupling/Feedback
• Electrical physics rules the grid – shaped by grid
connectivity
• Business models and software cannot change this
• Must be taken into account in control design to avoid
unintended consequences
 IVVR/DR*
 CVR/PV
 Market/responsive loads
• Becomes important as new rollouts of smart devices
scale to full deployment
• Implications for architecture, design, and control
*Jose Medina, Nelson Muller, and Ilya Roytelman, Demand Response and Distribution Grid Operations: Opportunities and
Challenges, IEEE Trans. On Smart Grid, vol. 1, pp. 193-198, Sept. 2010.
5
Issue: The Coordination Problem
Power grids do not have a strong multi-tier
coordination framework
o Power grids are inherently tiered now
o QSE’s-> Bulk System-> DSO’s->End Users
o Distribution “floats” on transmission
DER as a “threat” and an opportunity
A proper coordination mechanism is key to enabling
new business models
Interop standards alone do not solve this issue
Systemic Issues/Requirements
The most obvious:
o Reliability/scalability
o Stability
o Security
In fact, there are about 80 “ity” type characteristics that
everyone quotes*
Less obvious:
o
o
o
o
o
Federation/constraint fusion
Disaggregation
Boundary deference
Local “selfish” optimization (organizational autonomy)
Communications compatibility
scalar control
*John Doyle and John G Brown, Caltech, Universal Laws and Architecture. Available online as
1_DoyleSageLec1_May7_2012.pdf
7
Wide Area Scalar Control Approaches
Solve the communications and
disaggregation issues simultaneously and
scalably (maybe!)
Send scalar signals to endpoints
o Global common signal broadcast
o Location-dependent values
Various Approaches
o Distribution-Locational Marginal Pricing
o Transactive Energy
o “Prices to Devices”
8
Embedded Markets and Prices to
Devices
Scalar signal
disaggregation
models
Scalability
Directionally good but still lacking
coordination capability, so needs a
better foundation/framework
Embedded market and
prices-to-devices models
Instability
Roozbehani, M., et al, Volatility of Power Grids under Real-Time Pricing, MIT, 2011, available online
Transactive Energy
Definition from GridWise Architecture Council
“The term “transactive energy” is used here to refer to techniques
for managing the generation, consumption or flow of electric power
within an electric power system through the use of economic or
market based constructs while considering grid reliability
constraints. The term “transactive” comes from considering that
decisions are made based on a value. These decisions may be
analogous to or literally economic transactions.”
Key elements:
• Decisions (and control) based on value
• Reliability constraints
10
Network Utility Maximization:
Layering for Optimization Decomposition
Combine ideas from Control Engineering and Networking
Multi-tier control coordination
Benefits from layered architectural paradigm
LAMINAR
COORDINATION
Mung Chiang, Steven Low, et. al., Layering as Optimization Decomposition: A Mathematical Theory of Network
Architectures, Proceedings of the IEEE, Vol. 95, No. 1, January 2007.
11
Coordination: Essential Structure
Matches the “clean” layered
model for the grid hierarchy
Provides scalable
coordination while respecting
organizational and system
boundaries
Consistent with solid
architectural principles
Laminar coordinators* can
incorporate TE nodes
o Replaces ad hoc TE node
approach with uniform control
architecture for joint
economic-control optimization
*J. Taft and P. De Martini, Scalability, Resilience, and Complexity Management in Laminar
Control of Ultra-Large Scale Systems, available online.
Transactive Energy and Laminar
Framework
By adding the Laminar Coordination concept to TE,
can we address the issues listed earlier?
Decomposition allows mapping to real systems
Formulations provide constraint fusion and local goals
Physical Power System
Layered Optimization Mapping
Master
Problem
ISO
ISO
TO
Gen
Generation
Sub-problem
DSO
TO
DSO
DSO
Storage
Controller
DSO
Substation
Sub-problem
Secondary
problem
DSO
Substation
Substation
Tertiary
Problem
PV DG
Cap Bank
Controller
Tertiary
Problem
Substation
Local Area Grid
PV Panel
Secondary
problem
DSO
Sub-problem
Bulk Storage
Secondary
Problem
Local Area Grid
EV
Charging
Sub-problem
Sub-problem
IVVC
Customer
Device
Sub-problem
B2G/DR
Sub-problem
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Make It a Platform and They Will
Innovate
We cannot predict all the new business models and
applications that may emerge:
o
o
o
o
o
o
o
Local energy balance via B2G
Third party ancillary services
Feeder stabilization/regulation services via smart inverters
Utility-owned, customer-sited DER
Customer-owned, utility-managed DER
Multi-microgrid management
DSO as DER coordinator
But, we can position the grid as platform and the DSO
as an energy business hub if the control architecture is
done properly
14
thank you
Jeffrey D. Taft
jeffrey.taft@pnnl.gov
15
resource slides
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Issues with Prices to Devices
•
•
•
•
•
Hidden feedback, flash crashes, lack of tools to ensure
stability leads to price and grid instability
Multiple prices for the same kW-hr to a single end used from
separate parties/processes; price-overwriting at the endpoint
Differing prices to different endpoints for what is an apparently
equivalent kW-hr
Time scale mismatch between necessary control actions and
market functions
Presumed over-disaggregation (cannot really have individual
components of a system, say in a factory, responding
differently to prices, so cannot disaggregate to individual
devices)
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Embedded Markets/Prices to Devices
Embedded market approaches may act as a control elements in a feedback control
loops, whether intended or not.
Hidden feedback, flash crashes, lack of tools to ensure stability -> price and grid
instability
Multiple prices for the same kW-hr to a single end used from separate
parties/processes; price-overwriting at the endpoint
Differing prices to different endpoints for what is apparently equivalent kW-hr (due to
D-LMP or non-system, i.e. very local, markets)
Time scale mismatch between necessary control actions and market functions
Presumed over-disaggregation (cannot really have individual components of a
system, say in a factory, responding differently to prices, so cannot disaggregate to
this level)
Value Representation in TE
Value might be represented in a traditional currency form
(dollars and cents)
o Advantage: easily understandable
More generally, signals do not have to be currency to be
economic or value-based
Not all values are necessarily converted to $
o Economic signals do not have to be currency – behavior and math are
determining factors
o Dual decomposition uses abstract price signals for coordination, for
example*
Want to enable value unlocking in general, regardless of
business model or market structure
* Alternative Distributed Algorithms for Network Utility Maximization: Framework and Applications , Daniel P. Palomar and Mung Chiang,
IEEE Trans. Automatic Control, Vol. 52, No. 12, December 2007.
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Issue: Emerging Lines of Grid Control
Emerging
Architectural
Chaos!