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An Intelligent Control Scheme to Support Voltage of Smart Power Systems

机译:支持智能电源系统电压的智能控制方案

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The intelligent control of power systems is one of the main tasks for realizing a smart grid. Because of the high-dimensional dynamics and discrete control of power systems, realizing an optimal control to support system voltages is a hard combinatorial optimization problem. In this paper, a new intelligent scheme based on a genetic learning progress for optimal voltage control is proposed. This learning control scheme combines the genetic algorithm (GA) with a memory which saves knowledge accumulated from past experiences. In each run of search by GA, past experiences in memory is exploited to speed up the searching of GA and improve the quality of the solutions while the knowledge in memory is also refined by the new solutions. With the help of this learning capability, a fast and self-healing voltage control is realized and the control performance can be improved gradually over time. A case study on the New England 39-bus power system showed that the purposed learning control can successfully prevent the system from voltage instability and at the same time a fast and adaptive system response is provided.
机译:电力系统的智能控制是实现智能电网的主要任务之一。由于电力系统具有高维动态特性和离散控制,因此实现支持系统电压的最佳控制是一项难以组合的优化问题。提出了一种基于遗传学习过程的最优电压控制智能方案。这种学习控制方案将遗传算法(GA)与内存结合起来,可以保存从过去的经验中积累的知识。在GA进行的每次搜索过程中,都会利用内存中的以往经验来加快GA的搜索速度并提高解决方案的质量,同时新解决方案还可以改进内存中的知识。借助这种学习能力,可以实现快速,自愈的电压控制,并且随着时间的流逝,控制性能可以逐步提高。对新英格兰39总线电源系统的案例研究表明,有目的的学习控制可以成功地防止系统出现电压不稳定性,并同时提供快速,自适应的系统响应。

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