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Study of Power Market Simulation Based on distributed Multi-Agent System

机译:基于分布式多助理系统的电力市场仿真研究

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Commonly used power market simulation systems can only simulate the small-scale market with a simple result and do not consider the market participators as those who have the adaptive learning mechanism. By modeling the market participators as Agents, we approached a MAS-based distributed simulation system on JADE platform, which has the ability to simulate complex, large-scale markets with different strategies on different Agents. The Q-Learning and some other methods are introduced into the bidding strategy of the system. The system performance and convergence of Q-Learning strategy are evaluated by designed instances. As a result, the distributed system performance is better than the centralized system in many respects and Q-Learning strategy always leading to a high profit.
机译:常用的电力市场仿真系统只能以简单的结果模拟小规模市场,并不认为市场参与者作为具有自适应学习机制的人。通过将市场参与者为代理商建模,我们在玉器平台上接近了一个基于MAS的分布式仿真系统,能够模拟具有不同代理商的不同策略的复杂,大规模市场。 Q-Learning和其他一些方法被引入系统的竞标策略。通过设计的实例评估了Q学习策略的系统性能和融合。结果,分布式系统性能在许多方面和Q学习策略中始终导致高利润的集中系统。

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