1 RELIABILITY AND COMPETITIVE ELECTRICITY MARKETS POWER Research Conference UC Berkeley March 19, 2004 Paul Joskow MIT, CEEPR, CMI and Jean Tirole IDEI, GREMAQ, CERAS,MIT

2 INTRODUCTION capacity obligations placed on LSEs, Despite all the talk about "deregulation“ procurement obligations placed on ISOs, OpRes, and other ancillary service requirements, protocols for non-price rationing and management of system emergencies, Lack of understanding between economists (focused on market design and evaluation), engineers (focused on reliability rules). wholesale price caps, etc.

3 Benchmark Proposition: Competitive wholesale and retail markets “work” (second-best) despite Our Research Program’s Structure: Examine implications of relaxing each of the five key assumptions in two papers: presence of price-insensitive consumers, rationing but only under five sets of key assumptions. This paper: Wholesale markets with price caps, capacity obligations, ISO procurement, network collapses and operating reserves. Companion paper: Retail competition with load profiling, partially price sensitive consumers and zonal rationing.

4 BASIC ELECTRICITY SYSTEM MODEL Uncertain demand indexed by contingent states i Price insensitive consumers on traditional meters who are offered two-part tariffs [A, p] by the LSE Price sensitive consumers who see real time wholesale prices passed through by LSE LSE sees real time prices and may contract with customers to be (priority) rationed in state i with a fraction  i served by the LSE Supply side characterized by a continuum of CRS investment opportunities indexed by marginal cost of production c. I(c) denotes the investment costs of a plant with marginal production costs c. I′(c) < 0. u i (c) utilization rate of type c. Straightforward to introduce uncertainty on the supply side (e.g. probability of forced outage) but left to section on network collapses and OpRes

5 THE BENCHMARK MODEL Continuum of states of nature Consumers: Price-insensitive: Demand: if no rationing expected consumption: gross surplus: Price-sensitive : Demand: if no rationing expected consumption: gross surplus:

6 Producers: constant returns to scale: I (c) = investment cost for plant producing 1MW at MC c. Social optimum (given price-insensitive retail consumers):

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8 Benchmark Decentralization proposition

9 Five key assumptions (e) Consumers are homogeneous up to a scaling factor. More complex consumer heterogeneity may lead to adverse selection and competitive screening

10 WHOLESALE PRICE DISTORTIONS; WHOLESALE PRICE CAPS AND CAPACITY OBLIGATIONS (As is well known) wholesale price caps may be a response to market power or the outcome of regulatory opportunism, may lead to under-investment in peaking generation. Capacity obligations: LSE must forward contract with generators to make their capacity available to ISO during peak demand periods yielding a « capacity price ». Model reflects assumption that price cap is below the competitive market price in some (high) demand states (e.g. p i = VOLL i < $1000/Mwh)

11 With up to three states of nature, combination of price cap and capacity obligation (and associated capacity price) can address market power, investment, and end-use consumer price incentives provided that: All generating capacity is eligible to meet LSE capacity obligations and receive capacity payments not just peaking capacity, all consumers, including price-sensitive ones, count for determining capacity obligations and capacity prices are passed through to all retail consumers, forward market for capacity is competitive With more than three states of nature, regulatory tradeoff between alleviating market power and providing proper investment incentives, unless there is market power in only one state of nature, in which case there is no tradeoff.

12 ISO PROCUREMENT Northeastern ISOs debating whether ISOs should acquire peaking capacity and interruptible demand – ISO dispatching protocols? – How much should the ISO purchase? – Recovery through uplift? We consider impacts of ISO behavior – out-of-merit dispatching (Patton et. al. 2004) – with purchase of no more than optimal amount of peaking capacity – with purchase of more than optimal amount of peaking capacity – with different types of uplift recovery rules These ISO behaviors distort investment decisions, may crowd out significant amounts of private investment, and may lead to the ISO buying a lot more capacity than it may plan initially in order to balance supply and demand Better get ISO goals and incentives right

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15 NETWORK SUPPORT SERVICES AND BLACKOUTS Contrast: collapse: available generation rendered useless. rolling blackout: available generation very valuable (actually, value = VOLL), Simple model of OpRes: States of nature Inelastic demand Unit value v (v = VOLL). dispatched demand : load shedding. Capacity K: investment cost I K. Marginal cost of energy : c. Availability factor cumulative distribution function (could be state contingent). Reserves: (cost: )

16 Timing: ●● ●● Long term choice of capacity K Load D i in state i realized (Day-ahead) Choice of - dispatched load d i < D i - reserves r i d i - (1+r i )d i < K ready to be dispatched - r H > r i > r L Availability λ i realized: - If λ i (1+r L )d i < d i, d i satisfied -If λ i (1+r L )d i > d i, system collapses Available generating capacity is realized after generating capacity is scheduled to meet “dispatched” demand

17 The possibility of system collapses makes operating reserves a public good We characterize the attributes of the optimal investment in generating capacity and the prices needed to support it given the possibility of network collapses Absent mandatory OpRes requirements there will be underinvestment in reserves and too many system collapses It may be difficult to get a market to yield the optimal prices consistent with the OpRes requirement due to pricing challenges in the “reserve reduction” region

18 The socially optimal dispatch, curtailment and pricing policy involves three regimes as demand grows other things equal: Off peak: (d i = D i < λ i (1+r H )K ) and p i = MC i + r H s ) Load-shedding: (d i < D i ; d i = λ i (1+r L )K and p i = VOLL/(1+r L )) Reserve reduction: (d i = D i = λ i (1+r r )K and p i = MC i + r r s + Z/(1+r r )) r L < r r < r H Z = cost of increased probability of network collapse with an increasing probability of a network collapse in each regime

19 Socially optimal policy: P i = MC i + r H s P i = MC i + r r s + Z/1+r r Price jump? P i = VOLL i /(1+r L ) d i = D i

20 Implementation Mandatory OpRes purchases (public good) Off-peak: competitive price (MC). Load shedding region: price = VOLL. Reserve reduction region: price = between MC and VOLL Difficult (knife edge) pricing problem in reserve reduction region: - small change in reserve requirement can move price to MC or VOLL. - but prices in this region have significant effects on investment in reserves