Optimal Bidding Strategies for Load Server Entities in Double-Sided Auction Electricity Markets with Risk Management

In double-sided auction electricity markets, load server entities (LSEs) are required to participate in the market competition. When LSEs adopt bidding strategies, the profits of selling electric power to end customers are greatly reduced by lack of supplied power, or the high unnecessary electric prices for purchasing electric power are paid out because of the bidding is too high. Then, it is obviously that LSEs are faced with risks when they adopt bidding strategies. In this paper, a conceptual study is made on developing optimal bidding strategies with risk management for LSEs participating in double-sided auction electricity markets in which step-wise bidding functions and pay-as-bid settlement protocols are utilized. A normal probability distribution function is used to describe the bidding behaviors of rivals, and the problem of building optimal bidding strategies with risk management for LSEs is then formulated as a multi-objective stochastic optimization model, and solved by Monte-Carlo simulation and genetic algorithm. Finally, taking an electricity market with 3 power companies (Gencos) and 4 LSEs as an example, the proposed bidding strategies model is demonstrated by the simulation results