用于光伏低压径向配电网中无功功率优化补偿的北方大鹰优化技术

Shaikh Sohail Mohiyodin , Rajesh Maharudra Patil , Dr MS Nagaraj
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引用次数: 0

摘要

近年来,越来越多的光伏系统(PV)被集成到径向配电网(RDN)中。然而,由于光伏系统是零星的,网络运营商遇到了很大的问题。为了降低主电网的负荷并提高网络性能,电容器组(CB)经常被用于功率因数校正和 VAr 补偿。然而,必须根据负荷和光伏发电量的变化同时切换大量的电容器组,以维持馈电电压调节并改善其性能。本研究的 CB 控制优化策略考虑了多种目标。利用季节性负荷曲线和光伏发电模式,创建了一种新颖高效的北部大鹰优化(NGO),以确定对 CB 的适当控制。通过解决 EDN 中典型的 CBs 分配问题,并将结果与文献中的结果进行比较,NGO 的有效性得到了初步的交叉验证。在第二阶段,非政府组织的作用是在保持对 CBs 最佳控制的同时,最大限度地实现年度净节约。考虑到网络的 PV 和 CB,使用了一个改进的 IEEE 33 总线测试系统来评估所建议方法的有效性。
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Northern goshawk optimization for optimal reactive power compensation in photovoltaic low-voltage radial distribution networks
In recent years, photovoltaic systems (PVs) have been increasingly integrated into radial distribution networks (RDNs). However, network operators experience significant issues because they are sporadic. To reduce the load on the main grid and improve the network performance, capacitor banks (CBs) are frequently employed for power factor correction and VAr compensation. However, a large number of CBs must be switched at once in accordance with variations in load and PV generation to maintain feeder voltage regulation and improve its performance. This study's optimization strategy for CB control considers a variety of goals. Using seasonal load profiles and PV generation patterns, a novel and efficient northern goshawk optimization (NGO) was created to determine the appropriate control of CBs. By resolving the typical CBs allocation problem in EDNs and comparing the findings with those in the literature, the effectiveness of NGO was initially cross-verified. In the second stage, an NGO is used to maximize annual net savings while maintaining the best possible control over CBs. Considering the PVs and CBs of the network, a modified IEEE 33-bus test system was used to evaluate the effectiveness of the suggested methodology.
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