摘要
配电网合环操作在提高用户供电可靠性的同时,也可能存在馈线过流跳闸的风险。在不依赖具体网络参数的情况下,提出了一种数据驱动的配电网合环判定方法,分析环网配电网电压和功率分布计算方法,对开环运行下各节点电气数据进行预处理以满足合环条件下运行数据,建立环网配电网神经网络数据驱动模型,通过计算合环时配电网功率和合环电流,判断待环网是否能合环。实例应用结果表明,该方法考虑了合环时配电网潮流变化情况,合环电流计算更准确,实用性更强。
Loop closing operation in distribution networks can improve the reliability of power supply,at the same time,there may be the risk of feeder over-current tripping.In this paper,a criterion approach of loop closing operation based on data-driven in distribution networks is proposed,which does not depend on the specific network parameters.The calculation method of voltage and power distribution under looped distribution network is analyzed.The electrical data of each node under open-loop operation is preprocessed to meet the run data in closed-loop operation.The data-driven neural network model for the looped distribution networks is established.The power and loop closing current of the distribution networks under loop closing operation are calculated to judge whether the loop is closed or not.The example shows that the method takes into account the power flow variation of distribution networks when closing the loop,and the calculation of closing current is more accurate and practical.
作者
安义
陈琛
范瑞祥
李升健
朱志杰
陈霖
AN Yi;CHEN Chen;FAN Rui-xiang;LI Sheng-jian;ZHU Zhi-jie;CHEN Lin(State Grid Jiangxi Electric Power Research Institute,Nanchang 330096,China;State Grid Jiangxi Electric Power Co.,Ltd.,Nanchang 330077,China)
出处
《水电能源科学》
北大核心
2019年第12期152-156,共5页
Water Resources and Power
基金
国网江西省电力有限公司科学技术项目(521820180018)
关键词
配电网
数据驱动
合环
神经网络
潮流计算
distribution networks
data-driven
loop closing operation
neural network
power flow calculation