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Abstract：
This study presents a novel approach for the optimal placement of distributed generation (DG) resources, electric vehicle (EV) charging stations, and shunt capacitors (SC) in power distribution systems. The primary objective is to improve power efficiency and voltage profiles while considering practical and nonlinear constraints. The proposed model combines competitive search optimization (CSO) with fuzzy and chaotic theory to develop an efficient and effective solution. The use of fuzzy theory in the model enables the identification of optimal locations for DG sources and SCs, leading to significant enhancements in power index, generation, power losses, and system voltage. Moreover, the proposed fuzzy method is employed to determine the best locations for EV charging stations, further optimizing the overall system performance. The theoretical analysis demonstrates substantial improvements in both accuracy and convergence speed, highlighting the robustness of the proposed approach. In addition, the utilization of chaos theory enhances the local search optimization process, making the proposed method more efficient in finding high-quality solutions. To validate the performance of the model, extensive simulations are conducted on a 69-bus distribution system and various test functions. The results consistently reveal the superiority of the proposed method compared to other conventional optimization techniques. The key contribution of this study lies in its development of a comprehensive and efficient approach for the optimal placement of DG, EV charging stations, and SCs in power distribution systems. The integration of CSO, fuzzy theory, and chaotic theory enables the simultaneous consideration of multiple objectives and constraints, resulting in enhanced power dissipation reduction and voltage profile improvement. The obtained results demonstrate the practical applicability and superiority of the proposed method, which can significantly benefit power system planners and operators in real-world scenarios.
摘要：
本研究提出了一种优化分布式发电(DG)资源布局的新方法，电动汽车（EV）充电站，和配电系统中的并联电容器(SC)。主要目标是在考虑实际和非线性约束的同时提高功率效率和电压分布。所提出的模型将竞争搜索优化（CSO）与模糊和混沌理论相结合，以开发出高效有效的解决方案。在模型中使用模糊理论可以识别DG源和SC的最佳位置，导致幂指数显著提高，代,功率损耗,和系统电压。此外，提出的模糊方法用于确定电动汽车充电站的最佳位置，进一步优化整体系统性能。理论分析表明，在精度和收敛速度上都有了实质性的提高，突出了所提出方法的鲁棒性。此外,混沌理论的利用增强了局部搜索优化过程，使所提出的方法更有效地找到高质量的解决方案。为了验证模型的性能，在69总线配电系统和各种测试功能上进行了广泛的模拟。与其他常规优化技术相比，结果一致地揭示了所提出方法的优越性。这项研究的关键贡献在于其开发了一种全面有效的DG最佳放置方法，电动汽车充电站，和配电系统中的SC。CSO的整合，模糊理论，混沌理论可以同时考虑多个目标和约束，导致增强的功耗降低和电压曲线改善。得到的结果证明了该方法的实用性和优越性。这可以显著有利于电力系统规划人员和运营商在现实世界的场景。
