基于大爆炸-大压缩优化方法的智能配电网智能重构

Vavid Maleki Meyabadi, M. Farajzadeh
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引用次数: 5

摘要

提出了一种智能配电网智能重构控制框架。控制框架基于点对点通信和事件指挥系统。这个控制框架需要一个优化算法来做出决策。本文对Big Bang- Big Crunch (BB-BC)算法进行了改进(Modify BB-BC),以解决重构问题。在控制框架的决策中心采用MBB- BC算法,使智能配电网的功率损耗接近最小。控制框架可以实现智能和更好的控制。并以两个知名的配电系统为例,验证了优化算法在控制框架中的有效性。将MBB-BC算法与Big Bang-Big Crunch算法以及遗传算法、蚁群算法等优化方法进行了比较。仿真结果表明,与其他优化算法相比,特别是与BB-BC算法相比,该方法更加有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Smart reconfiguration in smart distribution grids by using of the new optimization method: big bang-big crunch
This paper presents a control framework for smart reconfiguration in smart distribution grids. The control framework is based on peer-to-peer communications and on Incident Command System. This control framework requires an optimization algorithm in order to make a decision. In this paper, Big Bang- Big Crunch (BB-BC) algorithm is modified (Modify BB-BC) to deal with the reconfiguration problems. MBB- BC algorithm in the decision center of the control framework helps achieve the near minimum power loss of smart distribution grids. The control framework can lead to smart and better control. Also, two well-known distribution systems are selected to demonstrate the efficiency of the optimization algorithm used in the control framework. MBB-BC is compared with Big Bang-Big Crunch and other optimization methods including Genetic Algorithm and Ant Colony Optimization. In addition, the simulation results show that this method is more effective compared to other optimization algorithms, especially BB-BC.
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