智能代理模拟在电力市场中的运用

Application of Intelligent Agent-Based Simulation to Electricity Market

基于智能代理的模拟仿真方法已成为电力市场研究的一种新颖而有效的途径.文中结合某一实际区域电力市场模拟系统的构建,介绍了适合模拟发电厂商报价的智能代理学习算法,详细阐述了VRE learning算法、Q-learning算法以及贪婪算法在模拟系统中的运用及实现框架,并分别探讨了学习算法在代理报价收敛问题上的不同处理方式.算例结果表明,智能代理模型及学习算法能够模拟发电厂商的理性竞价行为.

The intelligent agent-based simulation has become a novel and powerful tool in the study of electricity market. This paper deals with the construction of a simulation system of electricity market. In the investigation, first, the intelligent-agent learning algorithms suitable for simulating the strategic bidding of electricity firms are in- troduced. Next, the applications of the VRE-learning algorithm, the Q-learning algorithm and the greedy algorithm to the simulation system are illustrated, and the corresponding implementation frameworks are proposed. Then, the techniques for the learning algotrithms to handle the convergence of agent bidding are discussed. Finally, an exam- pie is performed to test the effectiveness of the intelligent agent-based simulation. The results indicate that the intel- ligent-agent learning algorithms are capable of simulating the rational bidding behavior of electricity firms.