Transactive Control:
A Novel Technology for Smart Grids
Anuradha Annaswamy
Active-adaptive Control Laboratory
Department of Mechanical Engineering
Massachusetts Institute of Technology
1
Depart of Mechanical Engineering
Seminar Series, WPI, October 9, 2013
Outline
• A Smart Grid – A Paradigm Shift
• Transactive Control
– Dynamic Market Mechanisms
– Integrated Secondary and Primary Control
• Case Studies
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Anuradha Annaswamy,
Transactive Control
Paradigm Shift: From Current to Smart Grids
Increasing supply-demand gap
Network
Operations
Environmental concerns
Transmission
Utilities
Aging infrastructures
Industrial
Consumers
Distribution
Demand Response
Smart Meters
Distribution
Consumers
Smart Devices
Industrial
Consumers
Utilities
Generation Facilities
Conventional Grid
Distribution
Consumers
Network
Operations
Main features:
Energy providers
• Renewable energy
DERs
resources
Microgrid
• Demand Response
• Storage
Transmission
• Advanced Metering
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Infrastructure
Anuradha Annaswamy, Transactive Control
Distributed
Community
Storage
Distribution
Smart Grid Control
• To maintain power balance in the system.
• To ensure that operating limits are maintained
– Generators limit
– Tie-lines limit
• To ensure that the system frequency is
constant (at 50 Hz or 60Hz).
• To achieve the above with renewable energy
despite intermittency & uncertainty
• To ensure affordable power
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Anuradha Annaswamy, Transactive Control
GRID CONTROL:
CURRENT PRACTICE
Anuradha Annaswamy, Transactive Control
TRANSACTIVE
CONTROL: The
connecting
entity
Anuradha Annaswamy, Transactive Control
THE OVERALL
VISION
Vision for Smart Grid Control: 2030 and Beyond:
Reference Model and Roadmap (Eds. M. Amin, A.M.
Annaswamy, C. DeMarco, and T. Samad), IEEE
Standards Publication, November 2013.
Anuradha Annaswamy, Transactive Control
Distributed Decision and Control
• Primary control
– Immediate (automatic) action to sudden change of load.
– For example, reaction to frequency change.
• Secondary control
– Restore system frequency,
– Restore tie-line capacities to the scheduled value, and,
– Make the areas absorb their own load.
• Tertiary control
– Make sure that the units are scheduled in the most
economical way.
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Anuradha Annaswamy, Transactive Control
Transactive control: An Emerging Paradigm*
The use of dynamic market mechanism to send an
incentive signal and receive a feedback signal within
the power system’s node structure
• Incentive Signal: Dynamic Pricing
• Feedback Signal: Adjustable Demand
* Hammerstorm et al., “Standardization of a Hierarchical Transactive Control System”
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Anuradha Annaswamy, Transactive Control
Transactive Control: Example
• Pacific Northwest
Demonstration Project
• 112 Households participating in
2009
• 60,000 households in an
ongoing project (2010-2015)
• Spans several states
Courtesy of Olympic Peninsula Project, IBM
TIS: Transactive Incentive Signal
TFS: Transactive Feedback Signal
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Anuradha Annaswamy, Transactive Control
Transactive control:
Our Definition
The use of dynamic market mechanism to send an incentive
signal and receive a feedback signal within the power system’s
node structure
• Incentive Signal: Ex. Dynamic Pricing
• Feedback Signal:
• Adjustable Demand (Market Level)
•
(Price Responsive, and Regulation Responsive)
• Area Control Error (Secondary Level)
• Governor Control (Primary Level)
Transactive Control
Control architecture that coordinates
 Market Transactions
 Active Control at the AGC level with Regulation Demand Response
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Anuradha Annaswamy, Transactive Control
Transactive Control Framework*
Incentive Signal
Feedback Signal
Market Transactions
Demand
Demand
Generation
Generation
Demand
…
Generation
~5 mins
TRANSACTIVE
Area Control Error (ACE)
~10secs
~sec
CONTROL
AREA-LEVEL
Set-points
SECONDARY (FREQUENCY) CONTROL
UNIT- LEVEL
PRIMARY (POWER) CONTROL
Set-points
* A. Kiani, A.M. Annaswamy, and T. Samad, “A Hierarchical Transactive Control Architecture for
Renewables Integration in Smart Grids.” HYCON Workshop, Brussels, 2012.
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Anuradha Annaswamy, Transactive Control
Primary Level
- time scale t
é PG ù
ú
zp = ê
êë PL úû
Steady state
é w [k] ù
ref
ú
u[k] = ê ref
ê PL [k] ú
ë
û
f : Tie - Line flow
D : uncertainty
0 = Ax pss [k] + Bz pss [k] + Fu[k] + D pss
0 = Cx pss [k] + Dz pss [k] + f pss [k] + Df pss
xGss
Primary
Secondary k
K
Tertiary
t
k+1
K+1
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Anuradha Annaswamy, Transactive Control
Secondary Level
0 = Ax pss [k] + Bz pss [k] + Fu[k] + D pss
0 = Cx pss [k] + Dz pss [k] + f pss [k] + Df pss
ß
xs [k +1] = xs [k] + Bsus [k]+ Cs D s [k]
xs [k] : wGss us [k]: u[k +1]- u[k]
D s [k] : Uncertainty in generation, load, and tie-line flow
Goal:
xs ® xt
xt
es
a reference signal set by the tertiary level
Controller
Secondary Level Dynamics
es = xs - xt : Area Control Error (ACE)
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Anuradha Annaswamy, Transactive Control
xs
Tertiary Level
Controller
Tertiary
xt [K]
Gain
es [k]
Gain
Secondary level dynamics
Primary Level Dynamics
How do we design the Tertiary Level?
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Anuradha Annaswamy, Transactive Control
xs [k]
Electricity Market
• Centralized mechanism that facilitates trading of energy between buyers
and sellers.
• The market operator conducts an auction market and schedules generators
based on bids received.
• Determines a market clearing price (Locational Marginal Price (LMP)) and
provides commitments and schedules based on security-constrained unit
commitments
• Day-ahead (DA) Markets
• Real-time Markets (RTM)
Wholesale Market
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Anuradha Annaswamy, Transactive Control
Wholesale Market: A Dynamic System
Operating Day
22:00
18:00
Operating Day-1
Real Time
Energy
Market
clears
00:10
Day ahead reliability
unit commitment
00:00
16:00
Clear Day-ahead
Market using Unit
commitment and
Economic Dispatch
Real Time
Energy
Market
opens
DA Energy
Market
results
published
16:00
12:00
DA Energy
Market
offer and bid
period closes
Revising bids
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ISO finalizes
operating plan
for the next
day
Power Delivery Time
Market Mechanisms - LMP
Node 1
Node 2
Node n
Demand
Demand
Demand
…
Generation
Generation
Generation
LMPi,
Schedules
Bids (MW-h, $)
ISO
Nodes in New England, USA
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Anuradha Annaswamy, Transactive Control
Top Layer: A Dynamic Market Mechanism
Suggested Price
Suggested Price
Congestion Rent
Generation
(with Renewable Energy
Resources)
Suggested MW
Consumption
Consumers
Substations
Suggested MW
Generation
Phase Angle
Real-time Market
1. Equilibrium under constant flux.
2. GenCos and ConCos adjust their power level using a recursive process.
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3. Price is a Public Signal that guides
all entities to adjust efficiently.
Anuradha Annaswamy, Transactive Control
Modeling of Generating Company
•
𝜌 : market price
~ Locational Marginal Price
at market equilibrium.
• The cost function of each generators unit is
That is, if a generator observes a market price
above the
marginal cost
,
will expand production until the
marginal cost of production equals the price.
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Anuradha Annaswamy, Transactive Control
Modeling of Consumers Company
•
:
marginal benefit of Pd
• Consumer utility
function:
j
i.e. Demand
with a marginal benefit above the marginal
price will lead to an expansion in consumption until equilibrium is attained.
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Anuradha Annaswamy, Transactive Control
Pricing Strategy
• Energy imbalance Ek at time k
• The pricing policy should depend on the
degree of energy imbalance
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Anuradha Annaswamy, Transactive Control
A Dynamic Market Model
• The market participants need
not have global market
information.
• Convergence of the dynamic
system to the equilibrium
condition implies that the
market reaches the condition
of Nash equilibrium.
Distributed
Gaming
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Anuradha Annaswamy, Transactive Control
Dynamic Market Mechanism (contd.)
xt[K]
Xt
xt
• Quantifies effect of volatility and stability
• Can help reduce reserve costs with wind uncertainty
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Anuradha Annaswamy, Transactive Control
Interconnections
Controller
Tertiary
xt [K]
Gain
es [k]
Gain
Secondary level dynamics
Primary Level Dynamics
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Anuradha Annaswamy, Transactive Control
xs [k]
Transactive Control: Lower Levels
The overall model, including the primary, secondary, and tertiary level
dynamics at multiple time-scales
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Anuradha Annaswamy, Transactive Control
Transactive Control: Stability*
* A. Kiani and A.M. Annaswamy, “A Hierarchical Transactive Control Architecture for Renewables Integration
in Smart Grids,“ CDC 2012, Maui, Hawaii.
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Anuradha Annaswamy, Transactive Control
Transactive control architecture
The use of dynamic market mechanism to send an incentive
signal and receive a feedback signal within the power system’s
node structure
• Incentive Signal: Ex. Dynamic Pricing
• Feedback Signal:
• Adjustable Demand (Market Level)
•
(Price Responsive, and Regulation Responsive)
• Area Control Error (Secondary Level)
• Governor Control (Primary Level)
Transactive Control
Control architecture that coordinates
 Market Transactions
 Active Control at the AGC level with Regulation Demand Response
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Anuradha Annaswamy, Transactive Control
Simulation Results
• 4-bus network with two generator units at
node 1 and wind at bus 2 (Pg1: Base-load;
Pg2: Reserve)
• L1, L2: DR-Compatible demand
Parameters with following values:
Pg2
Pg1
G
G
Area 2
L1
cg1 = 0.25; cg2 = 0.55; generator cost
coefficients
bg1 = 40.2; bg2 = 60; generator cost
coefficients
kg1 = 0.3; kg2 = 0.8; generator time constants
cd1 = cd2 = 0.4; consumer utility coefficients
bd1 = bd2 = 70; consumer cost coefficients
kd1 = kd2 = 0.3; demand time constants
k = 0:7; LMP time constant (market time
constant)
W
Area 1
L2
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Anuradha Annaswamy, Transactive Control
Market Stability & Volatility
Volatility: With increased
demand-elasticity (kd)
Stability: With increased
latency (kr)
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Anuradha Annaswamy, Transactive Control
Simulation Results: Market Stability & Volatility
Volatility: With increased
demand-elasticity (kd)
Stability: With increased
latency (kr)
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Anuradha Annaswamy, Transactive Control
Simulation Results
Wind Properties:
: Actual Wind Power
: Mean value of the projected wind.  Current Market Practice
: ARMA model of the actual wind power.  With Transactive
5.3 Control
Stability Analysis of Transactiv
G
G
1
2
Area 2
Area 1
4
3
L2
PD 2
PD 1 L1
Figure 5.3: 4-bus system example for Transactive control
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Anuradha ItAnnaswamy,
Transactive
Control
follows that the
equilibrium
of (5.59)-(5.60) is asymptotically stable if an
Simulation Results: Effect of Wind Uncertainty
Less reserve is required.
Hierarchical coordination
Anuradha Annaswamy, Transactive Control
Simulation Results: IEEE 30 bus Case
Reserve
Anuradha Annaswamy, Transactive Control
Summary
• Transactive Control
– Dynamic Market Mechanisms
– Integrated Secondary and Primary Control
• Case Studies
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Anuradha Annaswamy,
Transactive Control
A 2013 Publication!
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Anuradha Annaswamy, Transactive Control
Thank You!
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Anuradha Annaswamy, Transactive Control