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Dr G. C. Ejebe, Fellow IEEE University of Minnesota Graduate Power Seminar University of Minnesota Graduate Power Seminar The Two Settlement System and.

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Presentation on theme: "Dr G. C. Ejebe, Fellow IEEE University of Minnesota Graduate Power Seminar University of Minnesota Graduate Power Seminar The Two Settlement System and."— Presentation transcript:

1 Dr G. C. Ejebe, Fellow IEEE University of Minnesota Graduate Power Seminar University of Minnesota Graduate Power Seminar The Two Settlement System and Virtual Bidding in Electricity Markets & Financial Transmission Rights The Two Settlement System and Virtual Bidding in Electricity Markets & Financial Transmission Rights

2 2-Settlement & Virtual Bidding : Presentation Outline Two Energy Market basics Day-Ahead Market Real-Time Market Day-Ahead and Real-Time Market interactions Virtual Bidding Increment offers (incs) and decrement bids (decs) Roles of incs and decs Virtual Bidding Examples Financial Transmission Rights in Energy Markets

3 FERC Requires Energy Markets Federal Energy Regulatory Commission (FERC) developed Standard Market Design initiative requiring: Independent System Operators (ISOs) and Regional Transmission Organizations (RTOs) to implement two markets: a day-ahead (DA) market and a real-time (RT) balancing PJM, NYISO, ISONE, MISO CAISO (2009) ERCOT(2010)

4 Independent System Operators (ISOs) and Regional Transmission Operators(RTOs ) CAISO 57,124 MW 25,526 miles Tx 30m ISO-NE 33,700 8,130 14m Midwest ISO 144,132 55,090 43m NYISO 40,685 10,893 19m PJM 164,895 56,499 51m SPP 66,175 50,575 15m ERCOT 72,712 40,000 22m

5 ISO/RTO Functions Coordinate Movement of Wholesale Electricity in footprint Ensure Grid Reliability Efficient Grid Dispatch with Price Transparency Market Monitoring & Market Flexibility Liquidity in the Marketplace Demand Response Development Ease of Entry and Private Investment Green Power Added to Grid Long term regional transmission planning

6 Two Energy Markets Day-Ahead Energy Market – Develop day-ahead schedule using least-cost security constrained unit commitment and dispatch – Calculate hourly LMPs for next operating day using generation offers, demand bids and bilateral transaction schedules – Objective is to develop set of financial schedules that are physically feasible Real-Time Energy Market – Calculate hourly LMPs based on actual system operating conditions

7 Locational Marginal Prices (LMPs) LMPs are determined by a linear programming OPF Minimizes total energy costs subject to a set of constraints reflecting physical limitations of the power system. There are three components of LMPs: LMP ($/MW) = Energy component + Loss component + Congestion component The energy component is the same for all locations. The loss component reflects the marginal cost of system losses specific to each location, The congestion component represents the individual locations marginal transmission congestion cost. The energy component is the cost of providing an additional MW of energy to the distributed market reference bus, assuming optimally dispatched generation

8 Day Ahead Energy Market A Day-ahead hourly forward market for energy Provides the option to obtain increased certainty: – Purchase of MW at Day-ahead prices – Sale of MW at Day-ahead prices – Day-ahead congestion Inputs to DA Market Price-sensitive demand Increment offers Decrement bids Capacity Resources must submit offers in DA Participation by load is optional

9 Reserve Adequacy Assessment Designed to ensure adequate generating resources to meet forecast actual load in real time Additional generating resources scheduled after day-ahead market clears Based on RTO load forecast, physical generation assets, actual transaction schedules (net tie schedules) RTO operating reserve requirements Virtual bids and offers not included Any additional unit commitment is based on minimizing cost to provide additional reserves (minimize startup and no-load costs) RAA performed after DA Market run

10 Two Energy Market Settlement Day-Ahead Market Settlement – Based on scheduled hourly MW quantities and day ahead LMPs Real-Time (Balancing) Market Settlement – Based on hourly MW quantity deviations between real-time and day-ahead MW quantity deviations – Settled at real-time LMPs

11 Day-Ahead Market Implications Day-ahead schedules are financially binding Demand scheduled day-ahead – Pays day-ahead LMP for day-ahead MW scheduled – Pays real-time LMP for actual MW above scheduled – Paid real-time LMP for actual MW below scheduled Generation scheduled day-ahead – Paid day-ahead LMP for day-ahead MW scheduled – Paid real-time LMP for actual MW above scheduled – Pays real-time LMP for actual MW below scheduled

12 Virtual Bidding Virtual Bidding is a market mechanism that allows Market Participants to purchase (or sell) power in the Day Ahead Market with the explicit requirement that they sell (or buy back) same amount of power in the Real Time Market Purely financial Original intent is to pressure the convergence of DA and RT prices

13 Virtual Bidding Incremental Offers & Decrement Bids Available to all Market Participants Do not require physical generation or load Consist of: – MW offer or bid – Price of offer or bid (may be negative) Submitted at any hub, transmission zone, aggregate, or single bus for which LMP is calculated Supported in Day-ahead market only – Deviation in Real-time market Operating Reserve Implications Minimal charges for VB

14 Increment Offers & Decrement Bids Increment Offers Looks like a spot sale or dispatchable resource If the price goes above X, then MP will sell to the RTO day-ahead market Decrement Bids Looks like spot purchase or price sensitive demand If price goes below X then MP will buy from the RTO day-ahead market

15 Reasons for Using Virtual Bidding Price Arbitrage for profit maximization Arbitrage Day-ahead to Real-time pricing Use an increment offer if DA > RT Use decrement bid if DA < RT Physical Hedging Hedge Day-ahead Demand bid Hedge a Day-ahead generation offer Hedge against real-time price spikes in case of forced outage

16 Numerical Example #1 Decrement Bid Day-ahead Market Participant believes DA will be lower than RT and Dec Bids for HE 10 as follows : 50 MW at $45 : 50 MW at $38 : 50 MW at $30: 50 MW at $25 Day Ahead Market clears at $36 Day-ahead position is therefore 100 MW If Real-time Market Clears at $52 Market Participant makes a profit of ($52-$36)*100= $1600 If Real-time Market Clears at $32 Market Participants loss is ($32-$36)*100= -$400

17 Day-ahead Market Participant believes DA will be higher than RT and Inc Offers for HE15 as follows : 25 MW at $65 : 25 MW at $75 : 25 MW at $80: 25 MW at $90 Day Ahead Market clears at $78 Day-ahead position is therefore 50 MW@$78 If Real-time Market Clears at $56 Market Participant makes a profit of ($78- $56)*50= $1100 If Real-time Market Clears at $82 Market Participants loss is ($78-$82)*50= -$200 Numerical Example #2 Increment Offer

18 Numerical Example #3 Hedging a Generator Offer Day-ahead Market Participant bids scheduled Generation of 100 MW @ $50. Also Dec bids 10 MW @ $65 (virtual) Assume Day Ahead Market clears at $60 Both bids clear @ $60 Day-ahead position is therefore -commitment of 100MW @$60 and 10 MW virtual length REAL TIME – Scenario 1 Higher RT Price If Real-time Market Clears at $70 And Generator produces full output of 100MW Market Participant gets a credit of $60*100= $6000 from DA Gen settle Also a credit 0f ($70-$60)* 10= $100 from the virtual bid Market Participants Net = $6100

19 Numerical Example #3 Hedging a Generator Offer(Continued) REAL TIME – Scenario 2 Lower RT Price If Real-time Market Clears at $50 And Generator produces full output of 100MW Market Participant gets a credit of $60*100= $6000 from DA Gen settle Also a credit 0f ($50-$60)* 10= -$100 from the virtual bid Market Participants Net = $5900

20 Numerical Example #3 Hedging a Generator Offer(Continued) REAL TIME – Scenario 3 Higher RT Price If Real-time Market Clears at $70 And Generator produces reduced output of 90MW due to minor mech problems Market Participant gets a credit of $60*100= $6000 from DA Gen settle Also a credit 0f ($70-$60)* 10= $100 from the virtual bid of 10 MW A charge for under delivery of 10 MW in RTMarket = -10*$70 = -$700 Market Participants Net = $6000+$100- $700=$5400

21 Numerical Example #3 Hedging a Generator Offer(Continued) REAL TIME – Scenario 4 Lower RT Price If Real-time Market Clears at $50 And Generator produces reduced output of 90MW due to minor mech problems Market Participant gets a credit of $60*100= $6000 from DA Gen settle A charge 0f ($50-$60)* 10= -$100 from the virtual bid of 10MW A charge for under delivery of 10 MW in RTMarket = - 10*$50 = -$500 Market Participants Net = $6000-$100-$500 = $5400 Hedging with VB allows MP to contract in DA for RT price

22 Summary: 2-Settlement in Electricity Markets RTOs required to implement two markets Day Ahead and Real Time Markets A Day-ahead hourly forward market for energy produces hourly Clearing prices Real Time Market produces Hourly prices based on actual system conditions LMPs used to clear both markets

23 Summary: Virtual Bidding in Day Ahead Markets VB allows purely financial energy transactions without physical generation or load Increment Offers and Decrement Bids Increment Bids If the price goes above X, then MP will sell to the day-ahead market Decrement Bids If price goes below X then MP will buy from the day-ahead market Price Arbitrage for Profit Physical Hedging Currently working in US Energy Markets – PJM, NYISO, ISO-New England, MISO and ERCOT (December 2010) Starting in CaISO in February 2011

24 24 Financial Transmission Rights (FTRs) … Understand the concepts and principles of FTRs FTRs - PJM, ISONE, MISO Congestion Revenue Rights (CRRs)- CAISO, ERCOT Transmission Congestion Contracts(TCCs)- NYISO Explain how FTRs are acquired in RTOs

25 25 Why Do We Need FTRs? Challenge: LMP exposes Market Participants to price uncertainty for congestion cost charges During constrained conditions, the RTO collects more from loads than it pays generators Solution: Provides ability to have price certainty FTRs provide hedging mechanism that can be traded separately from transmission service ? ? ?

26 26 What Are FTRs?(CRRs,TCCs) Financial Transmission Rights are … a financial contract that entitles the holder to a stream of revenues (or charges) based on the hourly energy price differences across the path(between source/sink)

27 27 Why Use FTRs? To create a financial hedge that provides price certainty to Market Participants when delivering energy across the RTO system To provide firm transmission service without congestion cost To provide methodology to allocate congestion charges to those who pay the fixed cost of the RTO transmission system

28 28 Obtaining FTRs Network service- Allocation by RTO based on annual peak load designated from resources to aggregate loads Firm point-to-point service may be requested with transmission reservation designated from source to sink Secondary market -- bilateral trading FTRs that exist are bought or sold FTR Auction -- centralized market purchase left over capability

29 29 What are FTRs Worth? Economic value determined by hourly LMPs Benefit (Credit) same direction as congested flow If sink LMP congestion component>source LMP cong Liability (Charge) opposite direction as congested flow

30 30 FTRs & Congestion Charges Point-to-Point FTR Credit MW * (Day-ahead Sink LMP - Day-ahead Source LMP) MW * (Day-ahead Sink Congestion Component of LMP - Day-ahead Source Congestion Component of LMP) Network Service FTR Credit MW * (Day-ahead Aggregate Load LMP - Day-ahead Generation Bus LMPs) Congestion Charge = MWh*(Day-ahead Sink LMP - Day-ahead Source LMP)

31 31 Energy Delivery Consistent with FTR Thermal Limit FTR = 100 MW Congestion Charge = 100 MWh * ($30-$15) = $1500 FTR Credit = 100 MW * ($30-$15) = $1500 LMP = $30LMP = $15 Source (Sending End) Sink (Receiving End) Bus B Bus A Energy Delivery = 100 MWh

32 32 Energy Delivery Not Consistent with FTR (I) FTR Credit = 100 MW * ($30-$10) = $2000 Congestion Charge = 100 MWh * ($30-$15) = $1500 Bus A LMP = $10 Bus C LMP = $15 LMP = $30 Bus B Energy Delivery = 100 MWh FTR = 100 MW

33 33 Energy Delivery Not Consistent with FTR (II) FTR Credit = 100 MW * ($30-$20) = $1000 Congestion Charge = 100 MWh * ($30-$15) = $1500 Bus A LMP = $20 Bus C LMP = $15 LMP = $30 Bus B Energy Delivery = 100 MWh FTR = 100 MW

34 34 Characteristics of FTRs Defined from source to sink MW level based on transmission reservation Financially binding Financial entitlement, not physical right Independent of energy delivery

35 35 Acquiring FTRs from Auctions The RTO conducts periodic auctions -annually and monthly to allow eligible FTR Account Holders to acquire FTRs. to allow FTR Owners to sell FTRs that they hold. The RTO auctions the two basic types of FTRs: (a)Point to Point (PTP) Options (b)Point to Point (PTP) Obligations

36 OPTIONS or OBLIGATIONS PTP Options are evaluated hourly in each FTR Auction as the positive power flows on directional network elements created by the injection and withdrawal at the specified source and sink points in the quantity represented by the FTR bid or offer (MW),excluding all negative flows on all directional network elements. PTP Obligations are evaluated hourly in each FTR Auction as the positive and negative power flows on all directional network elements created by the injection and withdrawal at the specified source and sink points of the quantity represented by the FTR bid or offer (MW).

37 FTR Packaged as Peak & Off Peak FTRs are auctioned in the following blocks: (a)5x16 blocks for hours ending 0800-2300, Monday through Friday (excluding NERC holidays), in one-month strips; (b)2x16 blocks for hours ending 0800-2300, Saturday and Sunday, and NERC holidays in one- month strips; and (c)7x8 blocks for hours ending 0100-0700 and hours ending 2400 Sunday through Saturday, in one-month strips; and (d)7x24 blocks (combinatorial by specifying the previous three types of blocks), in one-month strips.

38 FTR Network Model The FTR Network Model is based on the Network Operational Model. The FTR Network Model normally includes the same topology, contingencies, and operating procedures as used in the Network Operational Model as reasonably expected to be in place for the applicable auction term (two years, one year, or one month, as applicable). The expected network topology for any month should include any planned outages of any transmission element known to be 16 hours or longer in that month. The FTR Network Model uses the peak Load conditions of the month being modeled.

39 FTR Simultaneous Feasibility Test SFT is performed to ensure that all FTRs are feasible and deliverable within the control area reliability criteria on an annual basis for each planning period. SFT is a power flow with FTRs modeled as injections at the source node and withdrawals at the sinks, Objective is to ensure that all subscribed Transmission rights are within the capability of the existing Transmission System. SFT is designed to ensure that the RTO Energy Market will be revenue adequate under normal system conditions. Problems with FTR Short Pay in Some RTOs.


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