利用分析模型和量子遗传算法计算和优化光伏系统低压线路的线路损耗

Zhiyan Zhang, Xianghui Guo, Pengju Yang, Taoyun Wang, Yuqi Ji, Lina Yao, Jinshan Power, Supply Company
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引用次数: 0

摘要

:随着分布式光伏(PV)发电越来越多地融入配电网络,出现了电力反向流动和高线路损耗等挑战,导致电力系统的不确定性增加。为解决这些问题,本文提出了一种利用功率流计算的分析模型,用于计算光伏发电低压配电网络中的线路损耗。使用 SIMULINK 开发了一个 15 节点低压网络的仿真模型,以验证分析模型在均匀负载分布 (ULD) 情况下的准确性。此外,还针对分布式光伏发电的低压配电网络提出了基于量子遗传算法 (QGA) 的线损优化算法以及优化模型。优化模型的目标函数基于光伏系统集成后线路损耗的减少。实例结果表明,使用 QGA 进行的线路损耗优化与分析结果一致,凸显了 QGA 在速度和精度方面的显著优势。这项研究为采用分布式光伏发电的低压配电网络的线路损耗优化提供了有价值的见解,并为该领域未来的研究提供了理论参考。
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Line Loss Calculation and Optimization in Low Voltage Lines with Photovoltaic Systems Using an Analytical Model and Quantum Genetic Algorithm
: With the increasing integration of distributed photovoltaic (PV) generation into distribution networks, challenges such as power reverse flow and high line losses have emerged, leading to greater uncertainty in power systems. To address these issues, this paper presents an analytical model for calculating line losses in low-voltage distribution networks with PV generation, utilizing power flow calculations. A simulation model of a 15 node low-voltage network is developed using SIMULINK to validate the accuracy of the analytical model under the scenario of uniform load distribution (ULD). Additionally, a line loss optimization algorithm based on quantum genetic algorithms (QGA) is proposed for low-voltage distribution networks with distributed PV generation, along with an optimization model. The objective function of the optimization model is based on the reduction in line losses resulting from the integration of the PV system. The example results demonstrate the consistency between the line loss optimization using QGA and the analytical results, highlighting the significant advantages of QGA in terms of speed and accuracy. This research provides valuable insights for line loss optimization in low-voltage distribution networks with distributed PV generation and serves as a theoretical reference for future studies in this field.
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