Impacts of Emission Trading on Optimal Bidding Strategies of Generation Companies in Day-Ahead Electricity Markets

Abstract:

The impacts of Emission trading on building the optimal bidding strategy for a generation company participating in a day-ahead electricity market is investigated. The CO₂ emission price in an emissions trading market is evaluated by using an optimization approach similar to the well-developed probabilistic production simulation method. Then upon the assumption that the probability distribution functions of rivals bidding are known, a stochastic optimization model for building the risk-constrained optimal bidding strategy for the generation company in the framework of the chance-constrained programming is presented. Finally, a numerical example is served for demonstrating the feasibility of the developed model and method, and the optimal bidding results are compared for the two situations with and without the CO₂ emissions trading.

• Periodical: Applied Mechanics and Materials (Volume 521)
• Pages: 476-479
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.521.476
• Online since: February 2014
• Authors: Guo Zhong Liu
• Keywords: Bidding Strategy, Chance-Constrained Programming, CO₂ Emissions Trading, Day-Ahead Market, Electricity Market, Generation Company

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