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发电厂商竞价上网能否获胜的关键是如何确定合理的报价曲线, 通过建立符合电力市场竞价实际情况的决策方法来获取电厂机组报价曲线又是竞价成功的关键。在运用传统博弈论方法来获取报价曲线面临诸多不太合理的情况下, 文中引入智能 Agent技术, 建立了完全信息下的决策模型, 并用二元进化算法模拟各竞价主体的学习方法,给出了算法模型与学习步骤。通过对智能 Agent技术与传统博弈方法的比较, 并分析其程序运行结果, 表明在电厂机组报价决策中运用智能 Agent技术来研究发电厂的决策报价具有较好的科学性与优越性, 为我国电力市场发电侧投标报价提供了一条新的思路。
The key to whether a bidder can win the Internet bidding is how to determine a reasonable bidding curve. It is also the key to bidding success by establishing a bidding curve of a power plant unit by establishing a decision-making method in line with the actual situation in the electricity market. In the case that the traditional game theory approach to get the quotation curve faces many unreasonable situations, this paper introduces the intelligent Agent technology, establishes the decision model under the complete information, and uses the binary evolutionary algorithm to simulate the learning methods of the bidding participants. Algorithm model and learning steps. By comparing the intelligent Agent technology with the traditional game method and analyzing the results of its program operation, it is shown that using Intelligent Agent technology to study decision-making quotations of power plants has a good scientific and superiority in power plant unit pricing decision-making, Market power generation bid offer provides a new idea.