With increasing environmental sensitivity and developing technology, Distributed Generations (DGs), Electric Vehicles Charging Stations (EVCSs), and Energy Storage Systems (ESSs) have been significant part of a distribution grid. However, inappropriate sitting and sizing of these components may negatively affect the performance of distribution grid. Besides, efficient operation of distribution grid can be achieved by only choosing the proper sizes of DGs, EVCSs, ESSs and placing them at the appropriate locations in the grid. In this paper, a weighted sum multi-objective function is formulated for reducing power loss, increasing voltage level and integration capacity of DGs, EVCSs, ESSs, simultaneously. Also, hybrid Soccer League Competition–Pattern Search (hSLC-PS) optimization algorithm is proposed to improve fine-tune performance of optimization. Simulations are carried out considering time-varying and stochastic nature of Photovoltaics (PVs) and Wind Turbines (WTs) generations and EVCSs load demand. The performance of the proposed method has been investigated on 33-bus and 85-bus test systems under different conditions and the statistical results are compared to SLC and Grey Wolf Optimization (GWO) algorithms to validate the effectiveness of the proposed algorithm. Statistical results clearly reveal the superiority of hSLC-PS in simultaneous sitting and sizing of DGs, EVCSs and ESSs.

随着环境敏感性的提高和技术的发展，分布式发电（DG），电动汽车充电站（EVCS）和能量存储系统（ESS）已成为配电网的重要组成部分。但是，这些组件的不适当的放置和尺寸调整可能会对配电网的性能产生负面影响。此外，仅通过选择适当大小的DG，EVCS，ESS并将它们放置在电网中的适当位置即可实现配电网的高效运行。本文提出了加权总和的多目标函数，以减少DG，EVCS，ESS的功率损耗，提高电压水平和集成能力。此外，提出了混合足球联赛竞赛模式搜索（hSLC-PS）优化算法，以提高优化的微调性能。考虑光伏发电（PVs）和风力涡轮机（WTs）的发电量以及EVCS的负荷需求的时变和随机特性，进行了仿真。对33种总线和85种总线测试系统在不同条件下的性能进行了研究，并将统计结果与SLC和灰狼优化算法（GWO）进行了比较，验证了所提方法的有效性。统计结果清楚地表明，hSLC-PS在同时坐放和确定DG，EVCS和ESS方面的优越性。对33种总线和85种总线测试系统在不同条件下的性能进行了研究，并将统计结果与SLC和灰狼优化算法（GWO）进行了比较，验证了所提方法的有效性。统计结果清楚地表明，hSLC-PS在同时坐放和确定DG，EVCS和ESS方面的优越性。对33种总线和85种总线测试系统在不同条件下的性能进行了研究，并将统计结果与SLC和灰狼优化算法（GWO）进行了比较，验证了所提方法的有效性。统计结果清楚地表明，hSLC-PS在同时坐放和确定DG，EVCS和ESS方面的优越性。