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基于agent的市场仿真方法描绘了存在二氧化碳排放权交易的市场环境下发电商的报价博弈过程,采用模拟退火Q学习算法模拟了发电商追求利润最大的行为,并给出了市场出清结果,进而分析了碳排放权交易机制对电力市场运营的影响。仿真计算表明,计及二氧化碳排放权交易后,agent发电商能够根据状态改变以利润最大为目标做出有利的报价决策,实施碳排放权交易会促进清洁能源的发展。
Agent-based market simulation method depicts the bidding game process of generator in the market with carbon dioxide emission trading. Simulated annealing Q learning algorithm is used to simulate the behavior of generator seeking profit, and the result of market clearing is given. The impact of carbon trading mechanism on electricity market operation is analyzed. Simulation results show that, considering the transaction of carbon dioxide emission rights, the agent power generator can make a favorable bidding decision based on the change of state in order to maximize profits, and the carbon emission trading fair will promote the development of clean energy.