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Optimal Capacitor Placement in Distribution Systems Employing Ant Colony Search Algorithm

机译：蚁群搜索算法在配电系统中的最优电容器布置

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This article introduces an ant colony search algorithm (ACSA) to solve the optimal capacitor placement problem. This ACSA is a relatively new meta-heuristic for solving hard combinational optimization problems. It is a population-based approach that uses exploration of positive feedback as well as greedy search. The ACSA was inspired from the natural behavior of the ant colonies on how they find the food source and bring them back to their nest by building the unique trail formation. Therefore, through a collection of cooperative agents called ants, the near-optimal solution to the capacitor placement problem can be effectively achieved. In addition, in the algorithm, the state transition rule, local pheromone-updating rule, and global pheromone-updating rule are all added to facilitate the computation. Through operating the population of agents simultaneously, the process stagnation can be effectively prevented. Namely the optimization capability can thus be significantly enhanced. Moreover, the capacitor placement problem is a combinatorial optimization problem having an objective function composed of power losses and capacitor installation costs subject to bus voltage constraints, which is commonly solved by employing mathematical programming methods, and will be solved using ACSA in this article. The proposed approach is demonstrated employing two application examples. Numerical results of a small-size example system show that the proposed method can achieve an optimal solution like the exhaustive search, but with much less computational burden. Also, this proposed method is superior to some other methods adopted herein in terms of power loss and costs.
机译：本文介绍了一种蚁群搜索算法（ACSA）以解决最佳电容器放置问题。此ACSA是解决硬组合优化问题的一种相对较新的元启发式方法。这是一种基于人群的方法，它使用对正反馈的探索以及贪婪的搜索。 ACSA的灵感来自于蚂蚁殖民地的自然行为，即它们如何寻找食物来源，并通过建立独特的步道结构将它们带回巢穴。因此，通过收集称为蚂蚁的合作代理，可以有效地实现电容器放置问题的最佳解决方案。另外，在该算法中，添加了状态转移规则，局部信息素更新规则和全局信息素更新规则以方便计算。通过同时操作代理群，可以有效地防止过程停滞。即，因此可以显着增强优化能力。此外，电容器放置问题是一种组合优化问题，其目标函数由受总线电压约束的功率损耗和电容器安装成本组成，通常通过采用数学编程方法来解决，并且将在本文中使用ACSA进行解决。通过两个应用示例演示了所提出的方法。小型实例系统的数值结果表明，所提出的方法可以实现像穷举搜索那样的最佳解决方案，但计算量却少得多。而且，就功率损耗和成本而言，该提出的方法优于本文采用的一些其他方法。

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