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Reinforcement Learning approaches to Economic Dispatch problem

机译:强化学习方法解决经济调度问题

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This paper presents Reinforcement Learning (RL) approaches to Economic Dispatch problem. In this paper, formulation of Economic Dispatch as a multi stage decision making problem is carried out, then two variants of RL algorithms are presented. A third algorithm which takes into consideration the transmission losses is also explained. Efficiency and flexibility of the proposed algorithms are demonstrated through different representative systems: a three generator system with given generation cost table, IEEE 30 bus system with quadratic cost functions, 10 generator system having piecewise quadratic cost functions and a 20 generator system considering transmission losses. A comparison of the computation times of different algorithms is also carried out.
机译:本文介绍了强化学习(RL)的方法来解决经济调度问题。本文将经济调度作为一个多阶段决策问题进行了阐述,然后提出了RL算法的两种变体。还说明了考虑传输损耗的第三种算法。通过不同的代表性系统展示了所提出算法的效率和灵活性:具有给定发电成本表的三发电机系统,具有二次成本函数的IEEE 30总线系统,具有分段二次成本函数的10发电机系统以及考虑传输损耗的20发电机系统。还对不同算法的计算时间进行了比较。

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