Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(7): 215- 222

Scholarlink Research Institute Journals, 2015 (ISSN: 2141-7016)

Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(7):215- 222 (ISSN: 2141-7016)
jeteas.scholarlinkresearch.com

Option Electricity Market Design Under UI Mechanism In India

D. Panda, S. N. Singh, and Vimal Kumar
Dept. of Electrical Engineering
Indian Institute of Technology, Kanpur, India
Corresponding Author: D. Panda
_________________________________________________________________________________________
Abstract
This paper addresses profit risk of a Genco in electricity market, and explores several ways of managing such risks.
It focuses on introduction of option contracts in Indian electricity market. The existing unscheduled interchange
(UI) mechanism is used to control frequency deviation, thereby maintaining the security of the system in real time.
The work applies conceptual option market framework to hedge the profit risk against price fluctuation in Indian
spot market from a power generators prospective. These options instruments are then used to hedge against price
fluctuation because of UI mechanism, in order to maximize producers expected utility. The aim here is to find the
optimal option prices with the known UI price and forecasted unbalanced real time amount. The model described
here considers a fixed number of put options for every time block of a day. Stochastic programming technique is
being used to solve the expected profit maximization problem. The effectiveness of this approach is tested for
power producers in Indian electricity market. A numerical example of a generating station is being illustrated to
show the revenue maximization problem. Further, with known option prices, the paper proposes an optimal
allocation problem for option market to hedge against spot price variation. The proposal addresses some of the
major issues such as involvement of gaming through over injection by generating stations. This way both Genco
and consumer can make benefit of holding option contracts to limit their losses in case of electricity price variation.
________________________________________________________________________________________
Keywords: electricity market, unscheduled interchange (ui), option contracts, profit maximization,
optimal allocation

INTRODUCTION producers caused by volatility of the electricity price

The power companies worldwide are undergoing is referred as price risk. Risk factor such as varying
restructuring to pave the way for competitive electricity and fuel price, variation in UI price, affects
markets. With the restructured environment both the the profit of a power producer participating in trading
power producers and consumers are having the market. The major driving forces for price volatility
options of choosing the competitive market models are load uncertainty, unplanned outage and
which will provide greater incentives for short and congestion. Through proper hedging process this risk
long term efficiencies and provide better economic can be minimized in all or in parts. Therefore the real
regulation. However, developing economies like time balancing is a necessary task for the stable
India, the electricity industry is progressively operation of a power system.
evolving with major reforms and restructuring to
make them cost competitive. The power sector has With the advent of new competitive environment in
grown significantly since the enactment of the electricity industry, the procurement of reserves and
Electricity Act in 2003 (Acts and Notifications, the choice of real time market is the fundamental
available online), introduction of Availability Based responsibility of system operator. As usual, in power
Tariff (ABT) (Bhusan B., 2005), and establishment of systems, because of load variation, the average value
independent regulatory commissions. ABT is one of of actual power generation is smaller than the
the key drivers for the generating utilities to operate required production capacity. In case of unexpectedly
in a competitive manner. high demand and any failure in generation and
transmission lines, there is need of having reserve
The deregulation in electricity markets has led to market. However, the amount of reserve the system
more competitive prices but also higher uncertainties required to carry must be based on risk involved and
in the future electricity price development. Most economy decision making. Therefore these reserve
markets exhibit high volatilities and occasional price markets can be replaced by price signals provided
spikes, which results in demand for derivative through value of options for real time balancing.
products to protect the holder against higher prices.
Day Ahead market with reference to Indian electricity Since the financial markets of electric power systems
industry is exposed to risk uncertainty on account of differs from traditional financial markets in certain
market clearing price (MCP) and market clearing important aspects, pricing and trading in electricity
volume (MCV). The variability of profit of power options is challenging. Ghosh, et al., 1997, discusses
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Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(7):215- 222 (ISSN: 2141-7016)

the development of option market in electricity equivalent option contract. Thus, can predict
trading. Pug et al., 2009, considers the pricing of replacement of gaming in existing UI mechanism and
electricity swing options that hedge the electricity reflect explicitly the manner of price hedging. The
price risk and also partly the risks in the option outcomes to some extent can give answers to the
owners load pattern. Also Hjalmarsson. E., 2003 following issues:
tries to use Black and Scholes formulation for a) Is the electricity market functioning of India is
electricity option pricing. Given that many of the compatible with option market.
existing options on electricity contracts are, in fact, b) If the options were introduced, how would present
options on electricity forwards rather than on the trades appear in value terms.
actual spot price, this involves modelling both c) How to measure the hedging cost of existing UI
electricity spot and forward prices (Hjalmarsson. E., and proposed option contracts.
2003). In (Rashidinejad, et al., 2000) the option price
of spinning reserve is studied using the Black and Prevailing UI Mechanism
Scholes formula. Selling electricity through a forward India has opened up a competitive power market in
contract at a fixed price to hedge against price spikes 2003 after the enactment of Electricity Act. With that
in pool market is discussed in (Conejo, et al., 2008). the sector has experienced participation of private
A technique for price-quantity hedging through players, mainly in generation and distribution. Aiming
power options in Colombian spot market is framed in at proper scheduling and real time operations, power
(Gabriel, et al., 2011). Additionally some relevant exchanges are created. Result to this, now there are
literatures that study real options in electricity are three major markets exist covering generation,
given in (Denton, et al., 2003). However, no study distribution, and retail trading: 1) Day-ahead spot
about a day a-head option model has been proposed market which determines the efficient dispatch of
in the literature. This is essential for electricity generating sources considering the offers submitted by
market like India, to avoid gaming with the existing loads a day ahead of actual dispatch: 2) Bilateral
unscheduled interchange mechanism. Also the studies market with a long trajectory covering contracts of
mentioned above consider transaction between more than a year: 3) Frequency actuated power
demand and supply and none of those were concern transaction through UI for real time balancing market.
about the profit profile of generation companies.
Since there is no reliable option pricing methodology ABT provides a frequency based incentives/penalties
available in literature, the most dependable way to to beneficiaries (e.g., Gencos). It has three part tariff
analyze option pricing on electricity contracts is to calculation; they are a) capacity charges: payment of
estimate models from the existing underlying assets fixed charge of the plant, b) energy charges: payment
and, from these, derive the corresponding option of fuel cost for schedule generation and c) UI
prices. charges: payment for deviation from schedule at a
rate dependent on system frequency. The UI charge is
The frequency control functionality of the UI for supply and consumption of energy in variation
mechanism is explained in (Parida, et al., 2009). Paper from the pre-committed daily schedule. This charge
Channa, et al., 2010, describes implementation of UI varies inversely with the system frequency prevailing
charges in ABT regime to co-ordinate the optimum at the time of supply/consumption. All these three
day a-head declaration. Soonee, et al., 2006, explains components are calculated in 15 min time block for
techno-economical and socio-political burdens for total 96 blocks of a day. UI charges are stochastic in
implementation of various real-time adjustments to nature as it varies with the change in frequency as
price real time demand. A work on stochastic model shown in fig 1. The price of power from UI follows
for day a-head declaration of power in ABT regime the ABT rate which is associated with the frequency
was published in (Vaitheeswaran, et al., 2006). The of the grid.
effect of scarcity, spot volatility and skewness are
8
significant in Indian electricity market, owing to the
U I rates in Rs ./K W h

fact that demand is increasing. These are consistent in 6

propositions on the positive effects of risk aversion. It 4
can be anticipated from existing literature that, the
value of generating unit depends on the generating 2

units efficiency and on market price, which is very 0

49.6 49.8 50 50.2 50.4
uncertain in a restructured power market. The paper
Grid Frequency in Hz
has discussed the concept of option to value
generation profitability from trading point of view in Figure. 1 UI charge variation with respect to grid
Indian power market. It aims to examine the frequency
conditions of electricity market for establishment of
option market along with existing real time market As discussed above, the real time adjustment of
(UI mechanism). The analysis is mainly based on power reference set is carried out by means of a
spot price evolution and in the evaluation of frequency linked UI price mechanism (M. Lively.,
2005). However, the generator droop control is
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Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(7):215- 222 (ISSN: 2141-7016)

managed under regulatory supervision. This sustained basis in a civilized and competitive market.
provision is to generate extra in real time scenario to The whole idea of relying on administered penalties
maintain generation and load balance. The real time is inefficient, subject to disputes and subject to
adjustment of power reference set is carried out by continual pressure to seek modifications and
means of a frequency linked unscheduled interchange exceptions. Non-compliance can also be justified by
price mechanism (Rules and regulations, available claiming an operating problem, etc. Therefore the
online). The UI mechanism is quite similar to the concept of option market design is being proposed in
price based real time balancing mechanism. Under UI this work. This could help in straightening up the
mechanism, all the real time deviations are settled prevailing spot price signal in India.
according to a predefine price curve. The UI price is
monotonically decreasing function of system UI As An Option Contract: Model
frequency. That is, higher the frequency lower is the For a Genco in spot market, the extra power
price. This intern provides incentive to the generator generated would be such that it will maximize the
to increase power generation when the system profit in the prevailing option price. With UI
frequency is lower and for decreasing power mechanism being commercially gambled, the idea of
injections when the frequency is rising. The ability to making UI as an option service can be modeled with
make load and generating entities to participate in two type of market; balancing energy market (UI
real time balancing is one of the key features of the mechanism) and reserve capacity market (Option
UI mechanism. However the purpose of UI contracts). The aim here is to analyze alternative
mechanism is to tighten the frequency band of the design options for these balancing markets. A
system to increase reliability. Recent studies shows theoretical model can be developed linking the above
involvement of gaming through over injection by two markets.
generating stations in excess of 105% generators
declared capacity with an intention to make profit Nowadays there is no future market for electricity in
under UI mechanism. This 5% increment from India. However, if for analytical purposes option
declared capacity depends on generator droop prices must be evaluated, then some future prices or
characteristics. The production level adjustment some kind of adjustment on the spot prices should be
through droop control is known as regulation service. estimated. The method applied in this paper was the
The regulation services are procured through energy- introduction of the adjustment of spot prices at the
reserve co-optimization in the day-ahead or real time beginning. As the option market aims at replacing the
market (Wu T., et al., 2004) (Zheng T., et al., 2006). UI mechanism, so design of a day-ahead option is
proposed here. Fig.1 gives a timeline diagram for the
According to the recent findings on Indian power proposed market model.
market, the UI mechanism faces lack of liquidity
affecting the reliability of the system both from The analysis considers a contractual arrangement
technical and economic aspects. No consideration is between a seller and a buyer for trading one unit of
made in the UI pricing for system congestion i.e., electrical energy at some future time. The same unit
because of excess demand in real time. Therefore, in of energy is being traded both in option and spot
real time there can be overloading in the lines. This market. As per the marginal cost theory the Gencos
can be one possible reason for the recent black out in will get more profit if P > UI . Here UI refers to
India. To avoid such a situation, the UI mechanism
the UI price. It would be beneficial if the generator
should be complemented with some other financial
sells from the available options. Figure 3 below
instruments like options.
explains the theoretical model with choices of both
option and UI
Also Cramton P., et al, 1998, in A Review of ISO
New Englands Proposed Market Rules say,
Reliance on penalties is highly inefficient and
problematic in its workings and is unworkable on a

Figure 2. Timeline diagram of proposed option market model

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UI > C
0, UI C

C C

UI < P
0, P UI
P P

Figure 3. Theoretical model with choices for options and UI

first step to solve the risk constrained problem.
Thus, it is clear from the above model that, a buyer Several machine learning methods such as artificial
who owns the call option is guaranteed to receive the neural networks have been successfully implemented
assigned MW amount from the seller at time T, at a for market price forecasting (Gao, et al., 2000)
strike price C , when the UI charge turns out to be (Rodriguez, et al., 2004). The work presented here,
considers probability distribution of past data.
greater than C . This way it receives a profit of

( UI C ) . Similarly, when UI charges are turned From the ACP and ACV data collected from Indian
Energy Exchange (IEX) for the northern region, the
out to be low, the seller exercises the put option and correlation coefficient is estimated to be 0.37 and
receives a profit of ( P UI ) . Here the author aims 0.71 in the year of 2013 and 2014 respectively. This
shows a steeply rising value of both load and
only Gencos prospective of participating in option generation dependency on spot prices. Therefore the
market with objective of maximizing its profit. author aims to develop an economically convenient
model for Gencos to maximize their pay off in the
To evaluate how a put option is used to hedge against electricity spot market. In the following a detailed
price risk faced by a power producer, consider that procedure is presented.
generator unit does not fail. Also assume that the
realization of high/low pool prices prior to the option Calculation of Option Strike Price
exercising time will lead to high/low pool prices Under Indian electricity market regime, the day a-
during the delivery time. In that case, if electricity head market is cleared at market clearing price
(MCP). Any deviation of real time market from day
t
RP = {S (t ) QS (t ) + UI (t ) QUI (t )} (1)
ahead is awarded through UI mechanism. So the
revenue of a generating unit in real time market can
0
be given by the following equation
prices become high before the expiration time,
producer decides not to exercise option so as to sell where, QUI ( t ) is the unbalanced real time amount in
its production in pool market with higher price. On MWh. With the aim to develop a stochastic model to
the other side, falling pool prices between the maximize Gencos revenue in the option contract
purchase and the exercising time of the option would frame work, the UI term has to be subsided. Instead,
encourage the power producer to exercise the put assume a Genco, signs a contract of quantity QP and
option to sell electricity at a pre-defined strike price. awarded price P in the spot market. Each option
In this way, the put option allows the power producer contract comes with a premium price. The option
to hedge the risk corresponding to high volatility of premium value ( 0 ) is kept constant i.e., Rs.1.5 per
prices.
option unit. Any deviation of real time market from
the day a-head market is awarded in the option
The following simplifying assumptions are considered
market at strike price. Therefore, the revenue of a
to formulate the stochastic model of option pricing.
Gencos unit is
a) The generating units owned by the power t
producer are dispatchable thermal units, whose TRP = {S (t) QS (t) +P(t) ( QG(t) QS (t))} 0 ( QG(t) QS (t)) (2)
cost is modeled by a piecewise linear function. 0

b) The Genco can sell its production both in pool

market, or through option. The pricing of the option contract is calculated solving
c) Gencos behave as a price taker and assume to be the above objective function for maximizing generator
risk averse. Therefore, it only considers sell of put profit, using option price cap as the maximum value of
options. unscheduled interchange rate. Considering all technical
and financial risk constraints of day a-head market,
Problem Formulation Gencos profit can be formulated as
For analyzing profit maximization function of a = TR TC (3)
generator participating in a spot market, the
forecasted spot market price is to be known. By taking the operating cost into account, the
Therefore, forecasting the spot market prices is the expected profit thus is calculated as
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 Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(7):215- 222 (ISSN: 2141-7016)

t analysed. It is being observed that, on peak periods

E(G) = {S (t)QS (t) +P(t)( QG(t) QS (t))} 0 ( QP ) Ci (Qg,sch) Ci (Qg,sch +Qg )
0 (4) are hour 12, 13, 14, 15 and off peak periods are
remaining hours. Corresponding UI price profiles are
Subjected to following constraints drawn. Using Anderson-darling goodness of fit tests,
1) Generation level constraint the log normal probability distribution plot is drawn
QGmin QG QGmax over the UI price values on a monthly basis,
(5a) expecting to implement options in the market. Table
2) Option contract limit constraint 1 below present values of pdf corresponds to
UImim P UImax (5b)
maximum and minimum UI value occurrence over a
period of 60 days.
3) Power balance constraint
QG = QS + QP (5c)
Thus, the sample follows a normal distribution profile
with a mean & standard deviation of 811.9017 and
50.5719 for maximum values of UI and 10.2025 and
So option price cap will be the highest value of UI
41.5767 for minimum values of UI. The work
price for that corresponding time block. This value
considers the min and max values of UI with the
can be calculated taking probability distribution of
corresponding pdf values as lower and upper limit for
past UI data for each time block.
expected option price calculation. Figure 4 below
shows pdf values following a normal distribution of
With the stiffed regulatory and financial bounds in
UI over the month of September 2014.
Indian electricity market, its difficult to replace the
prevailing UI mechanism altogether with the option
Table 1. PDF values of UI prices
market. A comparative analysis between option and UI_max UI_min
UI can be made, with increasing market transparency. pdf pdf
(Paise/kWh) (Paise/kWh)
Thus, the option market will operate in the shadow of 428.08 2.448E-15 0 0.009311
UI mechanism. Therefore, from the prospective of 636.48 1.92E-05 35.6 0.007962
profit maximization, a Genco has choices of selling 678.16 0.000239 106.8 .000646
power either in option or through UI, whichever has 719.84 0.001505 178 2.79E-06
maximum value. Thus payoff for each time block can 761.52 0.004803 303.04 1.62E-13
be calculated as per the following equation, x 10
-4
Probability Distribution of UI Price
t 14
TR={max{P(t),UI (t)} QP +S(t)QS (t)} 0 QP Ci (Qg) Ci (Qg +Qg) (6) 13
0

Subject to constraint (5a)-(5c) 12

11

10
Option Allocation Problem With Risk Mitigation
With option contract, the uncertain spot prices in real 9
time can be considered as stochastic time 8

variables P (t ) . After getting the optimal value of 7

option prices, now the Genco has to determine the 6

optimal hedging position of the option contract and 5

best amount of generation asset to bid in the option 4
0 500 1000 1500 2000 2500
market. It can be formulated as a minimization of
mean variance function. For the purpose of this study, Figure 4. Probability distribution plot of UI prices
r value has been set within [0.1-0.5]. over the month of study.
min QC (t ) = r ( ) (1 r ) ( ) (7)
The aim here is to illustrate how put options can reduce
From (4) and (7)
the price risk faced by a Genco. In order to highlight the
minQC (t) = r() (1r) ()
major features of an option as a mechanism to hedge

= r ( QP(t)) [ P(t)] +( QS (t)) [ S (t)] against price risk, consider the following two cases.
2 2

tT tT (8) The producer does not sell electricity through UI

mechanism during the period of trasanction, in
(1r) QS (t) [ S (t)] + [ P(t)] ( QP(t)) Ci (Qg ) Ci (Qg +Qg )
tT which the pool price happens to be lower than its
Subject to (5a)-(5c) marginal cost for the extra production.

Numerical Test Results The Genco will have the choice of selling
Here, the application of the methodology described in imbalanced power, either in option or through UI,
the prior section is performed with the available whichever have higher value.
information of the Indian power market from January
2014 to October 2014. Block wise spot prices are

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 Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(7):215- 222 (ISSN: 2141-7016)

According to historical information, it is expected

7
that the UI price here follows a log-normal pdf x 10
with log UI N (427.95 297.122 ) . All the price 3
components are in paise/kWh. General result of

E xpected payoff
obtained strike prices are presented in Figure 5 2

below.
1
800
UI
700 Option
0
Spot Price(Paisa/kWh)

600

500 -1
200 250 300 350 400 450 500 550
400
Price(Paise/kWh)
300
Figure 8. Expected payoff functions of Option
200

100
0 10 20 30 40 50 60 70 80 90 100
Figure 7 illustrates the expected payoff function for
Time Index (In 15min Block) UI as a real time market pricing. Similar way Figure
Figure 5. Option (strike price) and UI price. 8 illustrates the expected payoff for option prices.
Considering 1000 scenarios of Monte Carlo
It can be seen that, with option prices a hedging simulations the profit distributions are plotted for
profiles for peak and off peak hours are being before and after price hedging cases. It can be
incurred. Thus helping in supressing effects of observed from Figure 9(a) and 9(b) that, for Gencos;
market gaming. It can be observe from Figure 6 the profits mean slightly rises when following the
below that, Gencos profit are reducing with options price hedging strategy thus satisfying the objective
as compared to UI, this is because that with taken.
-13
increasing UI price, the possibility to exercise the put x 10
2.5
option will be relatively large, which makes the put
option contract price act more like a real time market 2
Probability Density

price. This effect becomes more obvious when the 1.5

put option volume increases. However, with both UI
and option, from profit maximization prospective, 1

Genco will bid with the highest available price bid. 0.5
So Profit will have an increasing trend as shown
below. 0
-0.5 0 0.5 1 1.5 2 2.5
7
x 10 Profit(Crores) 7
3 x 10
Only Option
Only UI
Figure 9(a). Profit distribution before hedging
2.5 -14
Both UI and Option x 10
5
2
Expected Profit (Crores)

4
P ro b ab ility D en sity

1.5

1
3

0.5 2

0 1

-0.5
0 10 20 30 40 50 60 70 80 90
0
Time Index (In 15min Block)
-1 -0.5 0 0.5 1 1.5 2 2.5 3
Profit(Crores) 7
Figure 6. Comparison of profit profiles of Genco. x 10
x 10
7 Figure 9(b). Profit distribution after hedging.
1.5
Here, taking the assumption that total generation (P)
1 = total load (Q), the expected values of profit are not
E x p e c te d p a y o f f

the optimal values since the premium of the options

0.5 are not properly estimated (For this study, it is
considered as fixed value for each time block) to
0
accurately match the payoffs. This mismatch is
positive in case of producers and negative in case of
-0.5
retailers.
-1
0 100 200 300 400 500 600 700 800 Impact of Risk Factor
Price(Paise/kWh) By solving the mean variance minimization problem
Figure 7. Expected payoff functions of UI. in (8), the spot market allocation for option contract

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 Journal of Emerging Trends in Engineering and Applied Sciences (JETEAS) 6(7):215- 222 (ISSN: 2141-7016)

is solved. Figure 10 illustrates the amount with some extent could answer the issues discussed in
different risk factor and contract prices. It can be seen section 2 of the paper.
that, to reduce UI price risk, the Genco will allocate
more capacity in option market with larger risk One limitation of this approach is that, it doesnt
factor. consider LSEs portfolio thereby lacking market
1300 liquidity. To achieve a new electricity derivative
r =0.5 market in India, it is necessary to consider LSEs
1200 portfolios and analyse the practical aspects of
O ption Q uantity (M W )

r=0.3 implementing the financial put and call options. It

1100 r=0.1 would also necessary to develop a proper valuation
methodology to price this kind of options underlying
1000
on the spot price.
900
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