In this study, a new optimal allocation and sizing have been proposed for an Electric Vehicle Charging Station (EVCS) on a Distribution System in Allahabad, India. The main idea is to optimize the EVCS configuration by considering Voltage Profile Improvement Index (VPII), Reactive Power Loss Reduction Index (QLRI), Real Power Loss Reduction Index (PLRI), and the preliminary development cost to get the minimum value of the installation cost and to provide higher quality of parameters for the power grid. For solving the studied nonlinear mixed-integer optimization problem, a new improved metaheuristic, called Balanced Mayfly Algorithm (BMA) is proposed. The modification is established to improve the accuracy and to resolve the exploration issue of the algorithm. The BMA used two modifications including elite mayfly couples and chaos mechanism to resolve these issues as it is possible. After validating the algorithm, it is applied to 30-bus distribution system in Allahabad, India and its results are compared with GAIPSO and basic MA. The results indicated that the voltage shape is smoothened and a reasonable balance between voltage profile and network losses is obtained. The results also show that the suggested method with 18.358 MW active power loss, 73.826 MVar reactive power loss, 10961 s computational burden, and 415 number of charging ports gives superior performance with lesser power losses. The number of CS allocated through GAIPSO and MA does not satisfy the demand of the city’s consumers.

中文翻译：

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使用元启发法优化配电系统中 EVCS 的规模和位置：案例研究

在本研究中，为印度阿拉哈巴德配电系统上的电动汽车充电站 (EVCS) 提出了新的最佳分配和规模确定方法。主要思想是通过考虑电压分布改善指数（VPII）、无功功率损耗降低指数（QLRI）、实际功率损耗降低指数（PLRI）和初步开发成本来优化EVCS配置，以获得安装的最小值成本并为电网提供更高质量的参数。为了解决所研究的非线性混合整数优化问题，提出了一种新的改进元启发式算法，称为平衡蜉蝣算法（BMA）。进行修改是为了提高准确性并解决算法的探索问题。BMA使用了包括精英蜉蝣对和混沌机制在内的两种修改来尽可能解决这些问题。对该算法进行验证后，将其应用于印度阿拉哈巴德的30路公交车配电系统，并将其结果与GAIPSO和基本MA进行了比较。结果表明，电压波形变得平滑，并且在电压分布和网络损耗之间获得了合理的平衡。结果还表明，所提出的方法具有 18.358 MW 有功功率损耗、73.826 MVar 无功功率损耗、10961 s 的计算负担和 415 个充电端口，具有优异的性能和较小的功率损耗。通过GAIPSO和MA分配的CS数量不能满足城市消费者的需求。