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AF-Mercados EMI
Ancillary Services Market in India
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Ancillary Services
Voltage Support Service
Regulation and Frequency Response Service
Energy Imbalance Service
Operating Reserve Service
Black Start Capability Service
2
In each of the above it is important to specify
Nature of Service
When is the service required?
Source of Service and Supplier Qualification
Procurement Mechanism
Charging Mechanism
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Regulation and Frequency Support Service
3
Regulation and frequency response services are necessary for the
continuous balancing of resources (generation and Control Area
interchange) with load, and to assist in maintaining scheduled
Interconnection frequency at 50 Hz.
The above frequency profile is obtained after considerable load
shedding by the states (illustrated in the Next Slide)
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Load Shedding during peak hours and off peak hours on 08.04.2013
4
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Considerations
Regulation and Frequency support service is provided by
Primary Control
Secondary Control
Tertiary Control
The states already resort to load shedding, RLDCs are able to “observe”
curtailed demand
Tertiary Control can be provided to manage deviations between the
“curtailed demand” and generation
Can the Frequency Support Services operate to always match this
“curtailed demand” with generation obtained through tertiary frequency
control ancillary service?
Or, do we need frequency triggers?
5
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Pre-requisites
What quantum of ancillary services should be sought?
Regulation Service requirements need to be determined consistent with reliability
standards to be set by NLDC/CEA and approved by CERC.
The Regulation Service requirements need to include locational requirements
and consider transmission constraints
Deviation is different in different states and there may be transmission constraints
between states
What happens when
Insufficient Regulation service is bid into the market
Scheduled Resources are not available
More than anticipated regulation service is required
Regulation Service providers may receive Regulation Service signals directly
from the RLDC (even if they are located in the control area of the SLDC).
Receiving regulation signals directly from the NLDC does not eliminate the need
to receive signals directly from the SLDC
Regulation Response Rate needs to be established to qualify resources for
this service (can vary on hourly / seasonal basis)
Are service allocation principles based only on costs (bids) or also
Response Rates? 6
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Mechanisms for Performance Tracking
7
If the resource providing FS service deviates from schedule –
payment mechanism needs to be linked to performance
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Procurement Mechanism
Through Power Exchanges based on supply offers
Offer parameters – price (Rs/MW), Response Rate, location, MW
Joint management of Congestion and FS would require SCUC with network
How is the demand curve determined?
Demand curve would need to be considered inelastic initially (till we have
adequate supplies)
Since procurement would be “location-based” (markets balkanized by
transmission constraints), state-specific considerations might be required
Two Settlement
Day Ahead
Real Time (since capacity requirements and Response Rate requirements
may change close to real time)
Regulation to prevent abuse of Market Power
Price Cap / moving yardstick (discussed later)
8
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Charging Mechanism
In NYISO, LSEs / Generators (who do not provide FS service and do not
follow RTD base points sufficiently accurately) in proportion of their
load/generation
Alternatively, more efficient Shapley pricing and computationally more
efficient Aumann-Shapley pricing mechanisms could be used
These have extensively been applied in allocation of transmission costs
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VOLTAGE SUPPORT SERVICE
10
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How do the ISOs / RTOs compensate the Generators for Reactive Power?
Most make capacity payments according to
compensate the allocated revenue requirements
Some pay the “opportunity cost” of reactive power
when the generators need to back down real power
output
Some impose penalties on generators for failing to
provide reactive power
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International Experience (Taken from Richard O’Neill) In England and Wales, a generator can accept a
default payment of ~ $2.40/Mvarh leading or lagging, or
it may offer contracts with a minimum term of one year.
In Australian ISO, generators and synchronous condensers.
receive an availability payment,
an enabling payment when dispatched and
opportunity costs from forgone sales of real power.
In India, the regulator imposes a 10 paise/kVArh price on reactive power when the 1.03 < voltage < .97
In the Netherlands, generators are
contracted are paid for reactive power capability
no additional payment is made when it is supplied.
In Sweden reactive power is supplied by generators on a mandatory basis, and there is no compensation.
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Spot Markets for Reactive Power
FERC recognizes that real time prices could be determined in the market through auctions. the reactive power prices could either be calculated directly or
derived from the implicit opportunity costs associated with real power prices and supplier’s real power energy bids.
The mechanics of price determination in each of these approaches is: Under the direct pricing approach, reactive power sellers would
submit price bids for supplying specific amounts of reactive power and the reactive power price would be the highest accepted price bid.
Under the derived approach, reactive power suppliers would submit price bids for supplying real power as well as information indicating the trade-off between supplying various amounts of real and reactive power
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Market Power in Reactive Power Markets
Simulation and experimentation are needed to understand the effects of alternative auction market designs before such a spot market is implemented.
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Objectives of Simulations
The objectives of the simulations done (on CIGRE 32 Bus ssystem) are two-fold:
To formulate and simulate strategic behavior of players (System Operator (SO) and the GenCos),
The results are intended to suggest mechanisms for addressing market power concerns of the regulator.
To study the “potency” of price cap regulation in alleviating abuse of market power, and suggest an alternative regulatory mechanism.
A comparison of the price cap regulation and the proposed alternative regulatory mechanism is drawn in terms of their respective abilities to produce “production efficiency” and “allocative efficiency” at the same level as a pure competitive benchmark case.
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The Analysis
What is the impact of strategic behaviour of players in the reactive power market on reactive power dispatch?
How do the strategically behaving GenCos respond to price-cap regulation?
Does ownership of a generator / synchronous condenser by the Public Sector (Government owned) help to mitigate market power?
Does the suggested regulatory mechanism induce efficiency?
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The Game: Formulation
Multi-leader follower game
Multiple dominant players – GenCos
One follower – the SO
Response of SO is constrained to be identical for each leader
GenCos bid different quantities of reactive power at different prices to maximize profits
Supply function competition
SO dispatches the system given these bids so as to minimize the cost of reactive power procurement
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Reactive Power Management Scheme
Day ahead real power markets clear first. The reactive power market clears in real time.
The generators know that they can be called upon to generate reactive power, which might require them to change their real power dispatch.
This may alter their expected cash flow in the real power market. Hence they bid a supply curve for reactive power.
The system operator (SO) minimizes the cost of procurement of reactive power and dispatches reactive power subject to the security constraints
All reactive power suppliers (generators) in a geographic area get the same price
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Solution Method (1)
The SO’s KKT conditions are parameterized in strategic variables k
The KKT conditions of the SO’s problem are concatenated with the constraints of the GenCo’s problem
Each GenCo’s problem is then a Mathematical Problem with Complementarity Constraints (MPCC)
The Equilibrium problem among the above MPCCs represents a “generalized Nash game” and it could have zero or multiple Nash equilibria
Since SO’s problem is non-convex, the solution to the KKT conditions may lead to a saddle point or a local maximum… practical way to overcome this is to try with different initial point
Cont…
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Solution Method (2)
GenCos are assumed to compete with each other in terms of their Supply Functions
Hence to find Nash Equilibrium (Equilibria), KKT conditions of all the GenCos need to be solved simultaneously
This is actually a non square Non-linear Complementarity Problem
This makes these problems harder to solve as compared to standard Nash game
Cont…
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Solution Methods (3)
Leyffer and Munson (2005) have proposed a NLP formulation which aims to avoid this difficulty by minimizing the complementarity constraints
The constraints do not include any complementarity conditions
It is shown in Leyffer and Munson that local solution to above problem with the objective function value = 0, is a strongly stationary point of the multi-leader follower game
In all the cases presented in this paper, the value of the objective function was less than 10-9
This compares well with the only other similar model (Bautista, Anjos, Vanelli, IEEE Trans. on Power Systems 2007), where the objective function value reported is 10-4
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How do the GenCos and the System Operator respond to the
reactive power management scheme proposed above?
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The three cases
Case A: Competitive Setting
Case B: Oligopolistic Setting: Supply Function Equilibrium
(SFE) with Price Cap
Case C: SFE with a Price Cap and Government-owned
GenCo
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6 Bus Example: Case A
1
2 3
4
5
6 Q=0.449
Q=0.749
Q=0.539
= $0.399 pu
Payment for Reactive
Power = 0.693 $/hr
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6 Bus Example: Case B
1 = 9.759 $/hr
2 = 3.403 $/hr
1
2 3
4
5
6 Q=0.449
Q=0.749
Q=0.539
= $7.981 pu
Payment for Reactive
Power = 13.855 $/hr
GenCo 1 owns generators at Nodes 1 and 3, GenCo 2 owns generator at
Node 2
All Values in pu
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6 Bus Example: Case C
1
2 3
4
5
6 Q=0.093
Q=0.883
Q=0.067
= $1.000 pu
Payment for Reactive
Power = 2.043 $/hr
GenCo 1 owns generators at Nodes 1 and 3, GenCo 2 owns generator at
Node 2, SO puts up a 100 MVAr Synchronous Condenser at Node 1
Q=1.00
K = 2
k = 2.12
k = 12.11 k = 20.00
All values in pu
1= 0.532 $/hr
2= 1.000 $/hr
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Nordic 32-Bus System
Similar results are obtained here
However, in the earlier cases the placement of the SO-Owned generator lead to a deviation in the voltage profile and real power generation from Case A
The placement on Bus no. 4072 in this case was such that not only were the voltages closer to those in Case A
But real power dispatch and voltage angles remained unchanged
Why is this result important?
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Production Efficiency and Allocative Efficiency
The real power dispatch is 11331.1 MW in Case A, 11330.2 MW in Case B and 11330.9 MW in the Case C
Also the state variables (V and ) are very close to the competitive case.
The effectiveness of a regulatory mechanism is to be measured in terms of its ability to mimic conditions of pure competition.
Hence it is demonstrated that prudent application of the alternative regulatory mechanism leads to the same production efficiency as the competitive case.
The allocative efficiency is however compromised and leads the GenCos to charge a higher price than that under competitive conditions (Case A).
The outcome of the alternative mechanism (Case C) is however shown to be better than the uniform price cap mechanism (Case B) in terms of both production and allocative efficiency.
‘prudent’ here is used in terms of the selection of the optimal site and capacity of Government-owned generator
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Conclusions
The Simulation investigates the problem of market power in real time spot reactive power markets
We model the equilibrium which emerges from the strategic interaction between GenCos using the supply function equilibrium framework.
When applied prudently, the proposed regulatory mechanism is shown to incentivize the competing GenCos to lower their bids and hence reduce the procurement cost of reactive power.
This mechanism of regulation is non-intrusive and yet is shown to mimic the outcome of a competitive market better than a plain price cap regulation.
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THANK YOU
30
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The SO’s Problem
Maximize J =
fi
f i
Q
Subject to
1
cos( ) sin( )N
P
fi i i j ij i j ij i j i
f j
P PD V V G B i
1
sin( ) cos( )N
fi i i j ij i j ij i j
f j
Q
iQ QD V V G B i
min min
i i iV V i max max
i i iV V i
min min
fi fi fiQ Q i f max max
fi fi fiQ Q i f
min min
fi fi fiP P i f max max
fi fi fiP P i f
( )fi fi fi fi fik a b Q i f
0
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The GenCo’s Problem
. ( )f fi fi fi fi fi
i i
Max R Q a b Q Q Subject to
min min0fi fi fik k i
max max0fi fi fik k
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Solution Method …Contd
Let denote the bidding strategy of the generating company f.
The KKT conditions of SO are parameterized in terms of
The KKT conditions are necessary for optimality of the ISO’s optimization problem.
Since the SO’s problem is not convex, the solution to the KKT conditions may lead to a saddle point or a local maximum.
,f fi fK k fi H
, 1,2,....,fK f F
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Let y denote the vector of all decision variables and
lagrange multipliers of the ISO’s problem
min max min max
min max
1, , , , , , , , ,
, , , ,
,
Q P
fi fi i i i i i i fi fi
fi fi fi
OP Q V
y y y
, , , , ,o Q P
fi fi i i i iy P Q V
1 min max min max min max, , , , , , ,i i fi fi fi fi fiy
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Let the following represent SO’s Equality, Inequality and
Complementarity KKT conditions
1 2 3( , , ,..., , ) 0E
Fz K K K K y
1 2 3( , , ,..., , ) 0I
Fz K K K K y
1 2 3( , , ,..., , ) 0C
Fz K K K K y
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The GenCo f’s problem now is
. ( )f fi fi fi fi fi
i i
Max R Q a b Q Q Subject to
min min0fi fi fik k i max max0fi fi fik k i
1 2 3( , , ,..., , ) 0 ( )E
E
F fz K K K K y w dual vector
1 2 3( , , ,..., , ) 0 ( )I
I
F fz K K K K y w dual vector
1 2 3( , , ,..., , ) 0 ( )C
C
F fz K K K K y w dual vector
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Subject to penMinimize C
1
1 1 1 1. . .
TI E C
f I E C
f
R z z zw w w y
y y y y
1 2 3( , , ,..., , )T
II
F fz K K K K y w
min min.( )f f fK K
max max.( )f f fK K
. . . 0I E C
f I E C
fo o o o
R z z zw w w
y y y y
1 1 1 1. . . 0
I E Cf I E C
f
R z z zw w w
y y y y
min max. . . 0
I E C
f f f fI E C
f f f f f
f f f f
R z z zw w w
K K K K
min 0f fK K max 0f fK K
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Two-Bus Example: Case A
1 2 GenCo 1 GenCo 2
PD=0.7,
QD=0.7
PD=0.7,
QD=0.7
11 220.881 0.528Q pu Q pu
Flow1 to
2: 0.181
pu
Flow2 to
1: -
0.172 pu
System
Marginal Price:
0.533*0.881 =
$0.469 pu
Generator Nodes
1 2
Pmin 0.450 0.850
Pmax 0.550 0.950
Qmax 1.000 1.000
bfi 0.533 0.889
afi 0 0
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Two-Bus Example: Case B
1 2 GenCo 1 GenCo 2
PD=0.7,
QD=0.7
PD=0.7,
QD=0.7
11 220.881 0.528Q pu Q pu
Dispatch Remains the same, however, the GenCos jack up their
bids to the maximum possible level (k = 20)
The System Marginal Price ($/pu) = 9.393
If either GenCo deviates from this outcome they lose their profits
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Two-Bus Example: Case C
1 2 GenCo 1 GenCo 2
PD=0.7,
QD=0.7
PD=0.7,
QD=0.7
11 22
,1
0.365 0.112
1.000so
Q pu Q pu
Q pu
11 22
,1
5.477 10.738
2.000so
k k
k
Uniform System Marginal Price = $1.066 pu
Solution does not change with initial values
