A major challenge for designers of competitive electricity markets is to devise market rules that limit the capability of electricity producers to exercise market power. Market power is the ability of a firm owning generation assets to raise the market price by its bidding behavior and to profit from this price increase. In addition, an important plan of market monitoring units in long term and competition policy framework is to persuade the participants to bid prices near to their marginal costs. Therefore, estimation of marginal cost function is important in way that Regulatory use it to increase competition in electricity markets. Bid price of the power plant to the power market contains some important information that can lead to more exact estimation of their marginal cost.In this paper the marginal cost of a typical power plant is estimated using optimal bidding behavior model in a competitive electricity market and Iran power market data.Index Terms-Marginal cost function, Model of optimal bidding behavior, Bertrand oligopoly model.
Summary
In a restructured wholesale electricity market, finding an optimal bidding strategy is important from 3 perspectives: maximizing firms' expected profit; identifying their exercised market power by the firms, from a regulatory point of view; and analyzing the effect of the auction format on firms' bidding strategies. While studying the optimal bidding strategy in the uniform‐price electricity auctions is common, little attention has been paid to pay‐as‐bid (discriminative) auctions. This paper tests ex‐post optimality of a firm's actual bid in the Iran wholesale electricity market with a pay‐as‐bid auction using 2 methods: The first one considers the submission of a “single‐step bid” in the intersection point of “a firm's actual bid” and “realized residual demand” curves, and the second one is to submit “single‐step bid” in the intersection point of “best response” to “realized residual demand.” Results show that firms' bidding behaviors in the Iran wholesale electricity market are not ex‐post optimal. In this regard, medium‐size firms display better performance than their larger counterparts, and large firms perform better than small ones. Also, firms under different ownership and technology bid suboptimally with significant differences. Furthermore, firms' performances were best in peak hours and got progressively worse during shoulder and off‐peak hours. These results strongly conform with panel regression models.
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