Agent-based Bidding Strategy Of Generators

Since the last century, the reform in power industry has swept the globe. The United States, Britain and other countries have joined in. China has been no exception. In recent years, the development of smart grid requests the market to improve energy efficiency, optimize resource allocation levels, and maximize social benefits. Agent as the intelligent and rational behavior entity provides the issue of the electricity market a good theoretical basis.This paper first summarizes the current status of electric power industry, and has summarized the issues on the generators bidding Research. It presents the way on how to deal the problem of generators bidding.Generators need to take certain strategy considering their costs and win the bidding. This paper analyzes the impact of generators to bid including market operation, power supply and demand, transmission congestion, constraints and so on. By the study of the mode of "SMD", "POOL" and the mode in China, the paper analyzes the impact of operation mode. When the demand and supply change, the price can also change. What's more, generators should adjustment their bidding considering the unit characteristic and transmission congestion.As considering many factors, the traditional methods for modeling bidding strategy will get difficult. The theory of Agent endowing the generators the intelligent character can easily solve the problem. This is because the theory does not require Agent to study deep in heart. Just by observing the environment and the state in which to respond, it can take the appropriate strategy.Using the theory of Agent to model can make the process of generating competition with the agent properties. This paper proposes a method to study the bidding strategy for suppliers through fuzzy Q-learning. It can solve the problem of Q-learning which only has the discrete state-space and discrete action-space. The fuzzy Q learning theory can reduce the storage space, improve the traverse speed, reducing the time to find Q values.The method applied an example to illustrate its adaptation and effectiveness with other limit.Finally, the paper uses an Agent-Based Modeling and Simulation Toolkit called Repast to model the system. It completes system configuration and the corresponding definition of Agent and attributes, definition of space class, definition of the system time series, the definition of input and output. It simulates the generators agent action strategy when congestion occurs in the transmission system.