We examine the bidding behavior of firms competing in the newly created spot market for electricity in Texas, where electricity generating firms submit hourly supply schedules to sell power. We characterize an equilibrium model of bidding into this market and use detailed firm-level data on bids and marginal costs of production to compare actual bidding behavior to theoretical benchmarks derived from our model. We find that firms with large stakes in the market performed close to the theoretical benchmark of static profit-maximization. However, several smaller firms utilized excessively steep bid schedules that significantly deviated from this benchmark. Our results suggest that payoff scale has an important effect on firms ’ willingness and ability to participate in complex, strategic market environments. We find that the bidding behavior of the smaller firms contributed significantly to productive inefficiency in this new market, although the smaller firms moved closer to the theoretical bidding benchmarks over time.

In the aftermath of the California energy crisis, there has been a shift in the focus of electricity regulators away from the fostering of a competitive market structure and towards the application of regulations to specific market outcomes. Such a focus stands in marked contrast to the general principles governing competition policies in other industries. This shift is in part influenced by the clear failure of earlier attempts to establish a competitive market structure in California. But was this a failure of the policy, or of the tools that were used to implement it? In this chapter, I describe the tests historically used by regulators as screens for the potential abuse of market power by suppliers. More advanced methods, such as models of oligopoly competition, can potentially provide a much better understanding of the competitive outlook for a market. However, much uncertainty surrounds the development and application of such models. I apply an oligopoly model of the California market to actual market data to test the ability of such models to recreate true market outcomes. I also explore the potential impacts of structural changes in the California market on both the supply and demand-side. The results indicate that either a reduction in supplier concentration or an application of realtime pricing to end-users would have yielded cost savings on the order of billions of dollars during the summer of 2000. 1.0

Abstract: The Day-Ahead electricity market is modeled as a multi-agent system with interacting agents including supplier agents, Load Serving Entities, and a Market Operator. Simulation of the market clearing results under the scenario in which agents have learning capabilities is compared with the scenario where agents report true marginal costs. It is shown that, with Q-Learning, electricity suppliers are making more profits compared to the scenario without learning due to strategic gaming. As a result, the LMP at each bus is substantially higher.

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The economic literature on online auctions is rapidly growing, because the enormous amount of freely available field data and the emergence of numerous innovative auction design features on auction platforms such as eBay have created excellent research opportunities. In this article, we survey the theoretical, empirical and experimental research on bidding strategies (including the timing of bids and winner’s curse effects) and seller strategies (including reserve price policies and the use of buy-now options) in online auctions, as well as some of the literature dealing with online auction design (including the stopping rule and multi-object auction rules). Section 1: Why do information systems make auctions (even) more popular? Long before any electronic information systems were in place, people used auctions to trade all kinds of goods and services. In his comprehensive overview of the history of auctions, Cassady (1967) reports auctions of items of almost any size, from jewels and spices to ships and provinces. The range of services that have been auctioned is also enormous, including anything from a dance on a local church festivity to the lifetime work force of a slave. While being widespread, however, auctions were not the most common way of trading because the costs of conducting and participating in an auction were typically too high for the every-day trade of common goods. Evidently, the use of auctions is subject to the trade-off between the advantage of price discovery (i.e. discovering the highest valuation bidder) and the disadvantage of having high transaction costs (i.e. the costs of finding a buyer and negotiating a sale). Because of this, auctions are most valuable when the party running the auction (both in buy and sell auctions) is

Climate change, driven by rising carbon dioxide (CO2) levels, has become one of the most pressing economic and political issues. Governments around the world are implementing environmental regulations that tax or price carbon dioxide emissions or significantly increase renewable energy production. This paper seeks to understand the response of electricity producers to policy changes, taken as given the current market structure. Electricity producers are the leading emitters of CO2 and other pollutants. They make their output decisions in response to fluctuating prices for electricity given their costs of production which include substantial startup costs. This paper, recovers the cost parameters of the industry with a dynamic price taking model. The parameters are used to solve for equilibrium prices and to simulate the supply of electricity, consumer surplus and firm profits under counterfactual environmental policies. Results evaluating a carbon tax policy show that total emissions from the industry do not change significantly when faced with tax rates at the levels currently under consideration by legislators. Even a very large carbon tax of twice that of expected levels, lowers emissions by only 7 % in the short run. 1 1

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Abstract—During the summer (2000), wholesale electricity prices in California were approximately 500 % higher than those during the same months in 1998-1999. The price hike was unexpected by many policy makers and individuals who were involved in the electric utility industry. They have been long wondering whether the electricity deregulation policy (1996) produced benefits of competition promised to consumers. This study proposes a use of a multi-agent intelligent simulator (MAIS) to numerically examine several reasons regarding why the crisis has occurred during May 2000-Janurary 2001. The MAIS explains the price fluctuation of wholesale electricity during the crisis with an estimation accuracy (91.15%). We also find that 40.46 % of the price increase was due to an increase in marginal production cost, 17.85 % to traders ’ greediness, 5.27 % to a real demand change and 3.56 % to market power. The remaining 32.86 % came from other unknown components. This result indicates that the price hike has occurred due to an increase in fuel prices and real demand. The two market fundamentals explained 45.73% ( = 40.46%+5.27%) of the price increase. The responsibility of energy firms was 21.41 % ( = 17.85%+3.56%). The numerical evidences are different from the very well-known research of Joskow and Kahn (2002), which has attributed the exercise of market power by large energy firms. I.

Abstract—Deregulated electricity markets in the U.S. currently use an auction mechanism that minimizes total supply bid costs to select bids and their levels. Payments are then settled based on market-clearingprices. Under this setup, the consumer payments could be significantly higher than the minimized bid costs obtained from auctions. This gives rise to “payment cost minimization,” an alternative auction mechanism that minimizes consumer payments. We previously presented an augmented Lagrangian and surrogate optimization framework to solve payment cost minimization problems without considering transmission. This paper extends that approach to incorporate transmission capacity constraints. The consideration of transmission constraints complicates the problem by entailing power flow and introducing locational marginal orices (LMPs). DC power flow is used for simplicity and LMPs are defined by “economic dispatch ” for the selected supply bids. To characterize LMPs that appear in the payment cost objective function, Karush–Kuhn–Tucker (KKT) conditions of economic dispatch are established and embedded as constraints. The reformulated problem is difficult in view of the complex role of LMPs and the violation of constraint qualifications caused by the complementarity constraints of KKT conditions. Our key idea is to extend the surrogate optimization framework and use a regularization technique. Specific methods to satisfy the “surrogate optimization condition ” in the presence of transmission capacity constraints are highlighted. Numerical testing results of small examples and the IEEE Reliability Test System with randomly generated supply bids demonstrate the quality, effectiveness, and scalability of the method. Index Terms—Deregulated electricity markets, electricity auctions, locational marginal price (LMP), mathematical programs with equilibrium constraints, payment cost minimization, surrogate optimization, transmission constraints. I.

Liberalisation of generation and supply activities in the electricity sectors is often followed by regulatory reform of distribution networks. In order to improve the efficiency of distribution utilities, some regulators have adopted incentive regulation schemes that rely on performance benchmarking. Although regulation benchmarking can influence the “regulation game”, the subject has received limited attention. This paper discusses how strategic behaviour can result in inefficient behaviour by firms. We also present a survey of issues encountered by electricity regulators. We then use the Data Envelopment Analysis (DEA) method with US utility data to examine implications of selected cases of strategic behaviour. The results show that gaming can have significant effects on the measured performance and profitability of firms.