The integration of renewable energy sources, relatable as Solar Photovoltaic (PV) and Wind Power, into the radial distribution system has gained significant attention due to their eco-friendly and sustainable attributes. This article presents a narrative advent for achieving the finest share of Solar PV and Wind force power through a radial distribution system using the innovative Spider Monkey Optimization (SMO) algorithm. Multi-objective function for the minimization of distribution loss and voltage deviation with the constraints of power balance equation and boundary limits of voltage and power is considered. The Spider Monkey Optimization algorithm, stimulated via the community activities of spider monkeys, be employed to effectively search for the finest allotment of Solar PV and Wind Energy Power within the distribution network. The SMO algorithm exhibits robustness in handling non-linear and multi-dimensional optimization problems, making it suitable for this complex task. To authorize the usefulness and efficiency of the planned approach, it is functional to standard 33-bus radial division coordination. Comparative analyses of optimization techniques are reported and SMO reduces the losses to 104 KW and the voltage deviation is minimized to 0.0458 pu. The valuable perception is that incorporating Solar PV and Wind Energy sources into radial distribution systems improves the quality.

中文翻译：

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基于蜘蛛猴优化的放射状配电系统太阳能光伏和风能电力优化分配

将太阳能光伏（PV）和风力发电等可再生能源整合到径向配电系统中，由于其环保和可持续的特性而受到了广泛关注。本文介绍了使用创新的蜘蛛猴优化 (SMO) 算法通过径向配电系统实现太阳能光伏和风力发电的最佳份额的叙述。考虑了在功率平衡方程以及电压和功率边界限制的约束下配电损耗和电压偏差最小化的多目标函数。通过蜘蛛猴社区活动激发的蜘蛛猴优化算法，可用于有效搜索配电网络内太阳能光伏和风能发电的最佳分配。 SMO算法在处理非线性和多维优化问题方面表现出鲁棒性，使其适合这种复杂的任务。为了验证所计划方法的实用性和效率，它适用于标准 33 总线径向分区协调。报告了优化技术的比较分析，SMO 将损耗降低至 104 KW，电压偏差最小化至 0.0458 pu。有价值的观点是，将太阳能光伏和风能资源纳入径向配电系统可以提高质量。