Random-Fuzzy Programming and its Hybrid Intelligent Algorithm to Building Optimal Bidding Strategies for Generation Companies in Electricity Market

摘要

In a competitive electricity market with sealed auction,building the optimal bidding strategies for generation companies (Gencos) couM be based on many uncertain information including rival's bidding behaviors,forecasted load and other market parameters.All the uncertain parameters to be considered in the procedure of bidding strategies have the random and fuzzy character.As a result,two main approaches to build optimal bidding strategies for Gencos were based on probability theory and possibility theory.However,as a limit of mathematical theory,there could not simultaneously deal with both random variable and fuzzy variable in a model developed in the past work.Based on credibility theory that was recently founded,a new framework of random-fuzzy programming was proposed for building optimal bidding strategies with risk management in this paper,and a hybrid intelligent algorithm by integrating simulation,artificial neural network and genetic algorithm were presented to find optimal bidding strategies.A numerical example of a simulated electricity market with six participating Gencos is served to demonstrate the feasibility of the developed model and solution method.