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Distributed multi-agent transmission system restoration using dynamic programming in an uncertain environment

机译:在不确定环境中使用动态规划的分布式多智能传输系统恢复

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摘要

In this paper, a decentralized multi-agent system (MAS) has been proposed to solve the power system restoration problem. In the proposed MAS, an agent with its own specific logic and interactions with other agents is devoted to any piece of equipment in the grid, including bus, black start, non-black start, photovoltaic and wind generating units. Power system restoration is devised as a single objective problem to minimize the energy not supplied (ENS), which is solved by bus agents using dynamic programming. The uncertainty of the wind and photovoltaic sources is considered in the corresponding agents, which is dealed by the Monte Carlo method. In addition, not only the genetic algorithm but also dynamic programming are employed in a top-down approach to solve the problem. The proposed algorithms are applied successfully to the IEEE 39-bus system. Comparing the results of both MAS and top-down approaches demonstrate that the proposed MAS outperforms the centralized method either optimized by genetic algorithm or dynamic programming in the sense of ENS.
机译:本文已提出分散的多助理系统(MAS)来解决电力系统恢复问题。在拟议的MAS中,具有其自身特定逻辑和与其他代理相互作用的代理商专门用于网格中的任何设备,包括总线,黑色开始,非黑色开始,光伏和风力发电机。电力系统恢复设计为单个客观问题,以最大限度地减少未提供的能量(ENS),其使用动态编程通过总线代理解决。在相应的药剂中考虑风和光伏源的不确定性,该代理由蒙特卡罗方法处理。此外,不仅是遗传算法还是动态编程,采用自上而下的方法来解决问题。所提出的算法成功应用于IEEE 39总线系统。比较MAS和自上而下方法的结果表明,所提出的MAS优于通过遗传算法优化的集中方法或在ENS意义上进行了优化的方法。

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