摘要
将协同粒子群算法应用到智能代理报价中,通过电力市场仿真试验,对协同粒子群算法在仿真中的代理过程进行了分析;通过不同的成本变化和供需水平变化试验,分析了协同粒子群算法在代理报价中对成本因素和供需水平因素的响应水平;与Q-learning算法代理结果进行了比较,结果表明,协同粒子群算法应用到基于代理的计算经济学电力市场仿真中是可行的。
ACE simulation of electricity market is an important research method of electricity market, however, the results of such a research on the agent simulation method are rarely reported. In this paper, the cooperative particle swarm algorithm is applied to the intelligent agent based bidding, and by means of simulative test of electricity market, the agent process of cooperative particle swarm algorithm during the simulation is analyzed. Through the tests of various cost variance and supply-demand level variance, the responses of cooperative particle swarm algorithm to cost factor and supply-demand factor in the agent based bidding are analyzed and compared with the agent based results adopting Q-learning algorithm. From test results it can be seen that it is feasible to apply cooperative particle swarm algorithm in the agent-based computational economics （ACE） simulation of electricity market.
出处
《电网技术》
EI
CSCD
北大核心
2010年第2期138-142,共5页
Power System Technology
关键词
基于代理的计算经济学
协同粒子群算法
报价策略
多代理系统
agent-based computational economics （ACE）
cooperative particle swarm algorithm
bidding strategy
multi-agent system
作者简介
陈乃仕（1980-），男，硕士，工程师，主要研究方向为智能电网在电力调度中的应用。
