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PORTFOLIO OPTIMIZATION FOR OPEN ACCESSCONSUMERS/DISCOMS
DEPARTMENT OF INDUSTRIAL AND MANAGEMENT ENGINEERING
INDIAN INSTITUTE OF TECHNOLOGY KANPUR
2017
15-05-2017 1
By
Dr. PARUL MATHURIAPOST DOCTORAL FELLOW
BID AREAS IN INDIA
1 N1 North Region Jammu and Kashmir, Himachal Pradesh,Chandigarh, Haryana
2 N2 North Region Uttar Pradesh , Uttaranchal, Rajasthan, Delhi
3 N3 North Region Punjab
4 E1 East Region West Bengal, Sikkim, Bihar, Jharkhand
5 E2 East Region Orissa
6 W1 West Region Madhaya Pradesh
7 W2 West Region Maharashtra, Gujarat, Daman and Diu, Dadarand Nagar Haveli, North Goa
8 W3 West Region Chhattisgarh
9 S1 South Region Andhra Pradesh, Telangana, Karnataka,Pondicherry (Yanam), South Goa
10 S2 South Region Tamil Nadu, Pondicherry (Puducherry),Pondicherry (Karaikal), Pondicherry (Mahe)
11 S3 South Region Kerala
12 A1 North EastRegion
Tripura, Manipur, Mizoram, Nagaland
13 A2 North EastRegion
Assam, Arunachal Pradesh, MeghalayaSource: IEX
VOLATILITY
Source: IEX
HISTORICAL DATA OF MCP
• APRIL 2013-1017
Source: IEX
WHY ELECTRICITY PRICES REPRESENTS
HIGH VOLATILITY ?ISSUES
Demand supply balance
Non-storable nature of electricity
Trading decisions are made well in advance
Prices depends upon the real time conditions
REASONS
Uncertain demand
Availability of production units & network components
Power production of non-dispatchable generators
Availability of generation resources
Energy prices of other markets such as fuel, emission
Legal reasons (market rules & structure)
Others
15-05-2017 5
15-05-2017 6
Timeline of Participation
more than one day ahead one day ahead
Intraday Market
real-timeoperation
Schedulingown generation
for real-time
Day Ahead Market
ForwardMarket
Hedging against the price risk & optimizing the financial part of the power portfolio
Short termMedium termLong term
more than a year Week to year
Construction & Investment
Planning
Long Term Power Purchase
Agreements
Optimizingphysical partof the power
portfolio
Balancing Market
MARKET TIMEFRAME
PERFECT MARKET
• Many Buyers– many eligible consumers/retailers with the
willingness & ability to buy the product at A certain price
• Many Sellers– with the willingness & ability to supply the product at
A certain price
• No Market Power – due to competition no seller can abuse his
position & control prices
• Sufficient Liquidity – sufficient traders so that planned trading is
achievable
• Price Taker – firms aim to sell where marginal costs meet marginal
revenue
• Regular Market Updates – for both consumers & producers
• Homogeneous Products – the products of the different firms are
similar15-05-2017 7
RISK & UNCERTAINTY
15-05-2017 8
• RISK
A chance that future value of considered parameter would be different
than expected
Viewed as A “negative”
Possibility of suffering harm or loss
Costs of future uncertainty
• REASONS
No information about future events at the time of planning
Exact estimation is not possible
UNCERTAINTY SOURCES INCLUDES
Technical, Institutional & Legal issues
RISK MANAGEMENT
METHODOLOGY THAT MAKE BEST USE OF AVAILABLE
RESOURCES
• THREE STEPS PROCESS
Risky v/s Risk Free trading options
MANY POSSIBLE OBJECTIVES:
• To minimize exposure to risk
• To maximize profit for A controlled level of risk
• Optimum selection of risk-return trade-off
15-05-2017 9
RISK IDENTIFICATION RISK ASSESSMENT RISK CONTROL
RISK CONTROL V/S RISK MITIGATION
• MANAGEMENT
• Diversification
• Risk sharing
• Uncertain outcomes are
correlated to reduce
certain variability
• Interdependency
• AVOIDANCE
• Hedging
• Contingent claims
• Contractual arrangement as
insurance
• Controlling financial
consequences
RISK CONTROL BY DIVERSIFICATION
• Diversification is about diversifying the investment in multiple trading
options, so that exposure to risk associated with any particular asset is
limited
• This concept is applied through portfolio construction by investing energy
in available different trading options.
DIVERSIFICATION
DERIVATIVE TRADING/ HEDGING
• Having a Position In Security Using Derivatives
• Trading with Financial Instruments or Contracts (Agreements) such
as Forward, Future , Option , Swap, CfD, FTR Or TCC
• Limitations
– Market Of Hedging Contracts Is Limited
– Requires Additional Payment
– Restricts Opportunities For Higher Profit
15-05-2017 12
PORTFOLIO
• Energy combination of available trading approaches
• Aiming to maximizing participants’ benefits (profits/ returns/ cost)
& minimizing the corresponding risk
• Substantially reduces the variability of returns without an
equivalent reduction in expected returns
• There is a reward for bearing risk
13
PORTFOLIO OPTIMIZATION
MARKET MECHANISM
• Two Types Of Markets
– PHYSICAL MARKET
• Spot Market (Exchange)
• Bilateral Contracts (OTC)
– FINANCIAL MARKET
• Forward, Future , Option ,
Swap, CfD, FTR Or TCC
Derivative Instruments
15-05-2017 14
GenCos
Power Pool
Loads
Bilateral/OTC Transactions
Pool
Trading
Mandatory Transaction Notification
Transactions are scheduled by
MO+SO
Day-ahead Market
Adjustment Market
Balancing Market
PoolOTC (Over the
counter ) trading
Exchange Traded
Derivatives
FORWARD
FUTURE
OPTION
SWAP
MARKET PRODUCT PORTFOLIO INDIA
Source: PPT 2016, Mr. Prasanna Rao, IEX
BUYERS IN ELECTRICITY MARKET
Buyers
Open Access Consumers
Captive
Consumers
DisComs
Retailers/ Aggregators
ALLOWED TO TRADE IN POWER EXCHANGE
• With Higher Voltage Grade
• Larger Power Consumption
• Procures Electricity for Forecasted
Demand
• Risk of price
• Risk of availability of transmission
corridor
• Risk of getting cleared in market
OBJECTIVE
• Minimize Total Purchasing Cost
• Minimize Risk
RETAILERS V/S DISCOMS
15-05-2017 17
• Retailers are subsidiary of a DISCOM
• Manage two sets of contracts, on supply & demand side
• Supply Side: Electricity procurement from various contracts and
pool for fulfilling customer demand
• Demand Side : Obliged to serve varying customer demand
• Retailer’s RM problem is basically bi-level optimization problem
– Purchase Cost Minimization
– Selling Price Determination with consideration of elastic nature
of demand
POWER PROCUREMENT PROBLEM
• Participate in wholesale trading
• Procures electricity for its known
demand
• Optimally decide its mix of
electricity purchase from
– Pool, (day ahead )
– Bilateral contracts (local and
non-local)
– Self production
• Free to purchase from any
supplier, irrespective of its
location
• Prices are correlated with each
other
15-05-2017 18
Large Consumer
Supplier 1
Supplier 2
Supplier 3
Self Generation
Spot Market
PROCUREMENT COST
• Bilateral contract, with home location supplier
• Bilateral contract with supplier of non-home location would be
• Spot market
• Self-generation Facility
• Total electricity procurement cost
1 1, 1,
1
1T
B B B
t t
t
C P for i
, 1, , ,
1
2 ~T
B B S S B
i i t t i t i t
t
C P for i n
1,
1
TS S S
t t
t
C P
2
1
( ) ( )T
G G G su
t t t t
t
C c u b P a P c
1
nS G B
P i
i
C C C C
15-05-2017 19
PURCHASE PORTFOLIO SELECTION
– Expected Procurement Cost
– Risk of Cost
– Minimize Risk Weighted Cost
0 0
1
N
P i i
i
E C w C w E C
2 2
1 1 1 1 1
, ,N N N N N
P i j i j i i i j i j i ji j i i j
w w Cov C C w Var C w w Cov C C
2min P PZ E C
0
1N
i
i
w
0iw
2
2 2 2 2
( ) 2 , ,n n n n
S B S B B B
P P i i i j
i i i j i j
Var C Var C Var C Cov C C Cov C C
1
2
nG B S B
P i
i
E C C C E C E C
15-05-2017 20
OVERALL OPTIMIZATION PROBLEM
,
2
, , , ,min .su
i t t tP Pw c u i t
Z E C
,
1
nS G B
t t t i t
i
PD P P P t
1
su su
t t tc c u u t
min max
G G G
t t tP u P P u t
1
G G up
t t tP P R u t
1 1
G G dw
t t tP P R u t
min , , max ,
B B B
i i t i t i i tP v P P v t
, 0S su
t tP c t
,, 0,1t i tu v t
• OBJECTIVE FUNCTION
• POWER BALANCE CONSTRAINT
• STARTUP COST
• GENERATION LIMITS
• RAMP UP LIMIT
• RAMP DOWN LIMIT
• LIMITS ON BILATERAL CONTRACTS
• VARIABLE DECLARATION CONSTRAINT
15-05-2017 21
CASE STUDY
Contract Index Location Contracted Price Minimum Limit per hour Maximum Limit per hour
Contract 1 APS 52 $/ MWh 60 MW 400 MW
Contract 2 PECO 56.5 $/ MWh 20 MW 200 MW
Contract 3 DOM 58.5 $/ MWh 50 MW 500 MW
Total capacity 120 MW
Minimum power output 20 MW
Ramp rate 80 MW/h
Quadratic cost 0.01 $/MW2h
Linear cost 42 $/ MWh
No-load cost $ 600
Start-up cost $ 200
TABLE II Specifications for Self-Generation Facility
Spot Market Contract 2 Contract 3
Spot Market 1207830135 -96097141.9 -382901659.8
Contract 2 -96097141.9 71896411.19 40024748.14
Contract 3 -382901659.8 40024748.14 708777796.3
TABLE III Variance-Covariance Matrix between Uncertain Costs at 0.0001
Large Consumer located at APS
Case Study Of PJM Electricity Market
Planning Period Is 120 Hours, With Each Hour As A Trading IntervalTABLE I Specifications for Bilateral Contracts
15-05-2017 22
CASE STUDY…
20
30
40
50
60
70
80
90
100
110
1 11 21 31 41 51 61 71 81 91 101 111
Pri
ce in
$/M
Wh
Hours
APS DOM PECO
390
410
430
450
470
490
510
530
550
570
1 11 21 31 41 51 61 71 81 91 101 111
Dem
and
in M
W
Hours
Demand dataDay ahead LMPs of three different locations
38
40
42
44
46
48
50
52
54
56
1 11 21 31 41 51 61 71 81 91 101 111
Pri
ce $
/MW
h
Hours
Contract 1 Contract 2 Contract 3
Hourly expected procurement price from risky bilateral contracts15-05-2017 23
RESULTS
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
3
0.5 1.5 2.5 3.5 4.5 5.5 6.5
Exp
ecte
d P
ort
folio
Co
st $
X1
06
Standard Deviation $X104
Scenario IScenario II
α=0.1
α=0
Electricity purchase from different contracts for various values of α
0
5
10
15
20
25
30
35
40
0 0.002 0.004 0.006 0.008 0.01
Trad
ed P
ow
er in
MW
hX
10
3
Risk weighing factor α
Self-generation Contract 1Self-generation II Contract 1 II
0
5
10
15
20
25
30
0 0.002 0.004 0.006 0.008 0.01
Trad
ed P
ow
er in
MW
h X
10
3
Risk weighing factor α
Spot Market Contract 2 Contract 3
Spot Market Contract 2 Contract 3
(b) Risk-free Procurement Options
(a) Risky Procurement Options
Efficient Frontier
15-05-2017 24
SCENARIO I WITH CORRELATION
SCENARIO II WITHOUT CORRELATION
RESULTS…
Mix of electricity purchase for each trading interval at α =0
0
100
200
300
400
500
600
1 21 41 61 81 101
Ener
gy in
MW
Hours
Spot Market Self Generation Contract 1 Contract 2 Contract 3 Demand
0
100
200
300
400
500
600
1 21 41 61 81 101
Ener
gy in
MW
Hours
Spot Market Self Generation Contract 1 Contract 2 Contract 3 PD
Mix of electricity purchase for each trading interval at α =0.0115-05-2017 25
OPEN ACCESS CONSUMER: INDIAN CONTEXT
.
5/15/2017 26/16
Open Access Consumer
Short term power trading
Unscheduled Interchange (UI)Mechanism
UI Charge for deviation fromScheduled withdrawal
Renewable purchase obligations (RPO)
Price uncertainty and
demand flexibility
Frequency linked UI charge
FiT
REC
RPO
PROBLEM DESCRIPTION
• UI Mechanism
• Part of Availability Based Tariff
• Penalty for deviation from schedule
(against grid frequency)
• Incentivizes to support grid
frequency
• Real time balancing mechanism
• Maintain grid frequency in narrow
band
• Post transaction charges
• Deviation Settlement Mechanism
and Regulations (DSM, 2014)
• RPO
• Fixed percentage renewable energy
purchase
• FiT contracts as long term PPAs
• FiT near to cost of production of
renewable energy
• RECs as environmental attributes
• 1 REC = 1 MW h of electricity
injected into grid.
• RECs traded in PXs
5/15/2017 27/16
PROBLEM DESCRIPTION
5/15/2017 7
Open Access Large
Consumer
DA Contracts
Bilateral Contracts
IEXDA
PXILDA
Self generation RPO
Indian Grid System
UI Charge
Demand
Generation
REC FiT
FrequencyMean-
Variance
PROBLEM DESCRIPTION
• Grid frequency is calculated from [12]
• ft = Grid frequency
• Lt=System Load
• Gt=System generation
• PFR= Power deficit- frequency fall ratio
• Mean Variance approach for Indian case study.
• Demand shifting using flexibility in projected mind accounting UI
deviations
5/15/2017 29/16
[ ]50
*
t t tt
t
L G UIf
PFR L
OBJECTIVE
• To develop a planning model for short term power
procurement of a large Indian electricity consumer considering
uncertainties (DAM price) and renewable promotional policies
while addressing real time grid frequency imbalances using
demand flexibility.
5/15/2017 6/16
MODELLING
• Objective
• Cost and Risk Minimization
• Cost = Cost of power purchase from (bilateral contracts + Spot Markets + FiT Contacts+ Self
Generation) + UI Penalty/Revenue.
• Risk = Uncertainty of spot market prices
• Constraints
• Demand Balance
• Base Demand + Demand Fluctuations = Shifted Demand + UI deviations
• Expected Demand = Scheduled Demand
• RPO
• Purchasing a percentage from FiT contracts
5/15/2017 6/16
PLANNING MODEL
Minimum and Maximum Purchase Constraints
Bilateral contracts, Spot market
Self Generation Constraints
Quadratic Cost Function
Minimum and Maximum Generation
Ramp up and Ramp down
UI Charge
Calculated from grid frequency
Deviation limitations according to DSM 2014.
5/15/2017 6/16
CASE STUDY
.
5/15/2017 33/16
Capacity 120 MW
Minimum power output
20 MW
Ramping limit (up/down)
80 MW
Quadratic Cost 0.6 Rs./(MW)2h
Linear Cost 2700 Rs./MWh
No-load Cost 2000 Rs.
Startup Cost 1000 Rs.
Generation Unit
Bilateral contract price 3000 Rs./MW h
Min./Max bilateral vol.
limit
30 MW/800MW
Demand Flexibility 12%
Min./Max limit on SI 900 MW/ 1100 MW
Min./Max limit on flexible
load
-40MW/40 MW
RPO, PFR 10 %, 4%
Trading intervals 168 hours
RPO purchase price 5000 Rs./MW
System demand/gen. 100 GW
Other Data Values
960
1010
1060
1110
0 50 100 150Ac
tua
l D
em
an
d (
MW
)
Time (hours)
2000
3000
4000
5000
0 50 100 150Ave
rag
e D
AM
Pri
ce
(R
s./
MW
)
Time (Hours)
PXIL avg price IEX avg price
1b
RESULTS
5/15/201712/16
587
592
597
602
607
612
617
1.4 3.4 5.4
Co
st
(×10
6R
s.)
Standard deviation (× 106 Rs.)
Efficient Frontier
0
50000
100000
150000
0 0.000005 0.00001
Po
we
r P
roc
ure
me
nt
(MW
)
α
Self Generation Bilateral
IEX DAM PXIL DAM
49.94
49.96
49.98
50
50.02
50.04
50.06
-140
-120
-100
-80
-60
-40
-20
0
0 100
Fre
qu
en
cy (
Hz)
UI A
llo
ca
tio
n (
MW
)
Time (Hours)
UI Allocation Grid Frequency
49.96
49.98
50
50.02
50.04
0 100
Fre
qu
en
cy (
Hz)
Time (Hours)
Improved Frequency Grid Frequency
RESULTS
5/15/201712/16
850900950
100010501100115012001250
1 49 97 145
De
ma
nd
(M
W)
Time (Hours)
SCHEDULED DEMAND EXPECTED DEMAND
850
950
1050
1150
1250
0 10 20 30 40
De
ma
nd
(M
W)
Time (Hours)
Scheduled Demand Expected Demand
THANK YOU
15-05-2017 36