摘要
计及分布式电源出力波动性对故障恢复效果带来的不利影响,提出1种利用光伏出力预测的配电网动态故障恢复方案。故障发生后,首先对动态变化的光伏系统输出功率进行预测,并研究了负荷动态特性;其次,以配电网恢复重要负荷总量最大、故障恢复成本最小和故障停电损失最少为目标函数,构建基于动态树背包模型的最优故障恢复模型,该模型可快速适应配电网拓扑变化情况。采用改进模拟退火遗传算法求解最优故障恢复方案,提高了算法的收敛速度与稳定性。最后,在IEEE69节点系统进行仿真,结果表明所提算法可适应复杂配电网的故障恢复,提高配电网供电可靠性,并降低配电网故障带来的恢复成本与停电损失。
Considering the adverse effects of fluctuating output power of distributed power sources on fault recovery,a dynamic fault recovery scheme for distribution networks using photovoltaic output power prediction is proposed.After the fault occurs,the dynamic output power of photovoltaic system is predicted,and load dynamic characteristics are studied.Then,based on the objectives of maximizing the total important load for distribution network recovery,minimizing fault recovery costs,and minimizing fault-induced power outages,an optimal fault recovery model based on dynamic tree knapsack model is constructed.This model can quickly adapt to changes in the distribution network topology.An improved simulated annealing genetic algorithm is used to solve the optimal fault recovery plan,which improves the algorithm's convergence speed and stability.Finally,the simulation is conducted in IEEE 69-node system,and the results show that the proposed algorithm can adapt to the fault recovery of complex distribution networks,improve the reliability of distribution network power supply,and reduce the recovery cost and power outage loss caused by distribution network faults.
作者
王可淇
赵子涵
钟俊
徐方维
WANG Keqi;ZHAO Zihan;ZHONG Jun;XU Fangwei(School of Electrical Engineering,Sichuan University,Chengdu 610065,China;State Grid Sichuan Electric Power Dispatching Control Center,Chengdu 610041,China)
出处
《智慧电力》
北大核心
2024年第6期16-22,共7页
Smart Power
基金
国家自然科学基金资助项目(52277113)
国网四川省电力公司科研项目(11047611)。
关键词
分布式电源
故障恢复
孤岛划分
模拟退火遗传算法
光伏功率预测
支持向量分位数回归
distributed power supply
fault recovery
island partition
simulated annealing genetic algorithms
photovoltaic power forecast
support vector quantile regression
