摘要
准确快速的故障定位对配电系统的运行质量和可靠性至关重要。目前多分支配电系统故障定位方法大多通过在配网中增加量测装置实现,但配电网拓扑结构复杂,监控设备数量有限,大规模安装额外量测设备的成本较高,难以在实际系统中广泛应用。为此,提出了一种基于有限量测信息的多分支配电线路故障定位方法。首先,对多分支配电线路中电气量信息与故障距离的非线性关系进行理论分析,证明了采用深度学习构建映射函数完成故障定位任务的可行性;其次,利用堆栈自编码器和长短期记忆网络建立故障测距模型,降低配电线路多分支对故障定位产生的误差;再次,结合配电自动化系统的量测信息,通过逻辑推理和智能测距模型实现故障线路判定和测距;最后,基于深度迁移学习提出一种智能定位实施方案,以增强所提方法泛化能力。在MATLAB/SIMULINK平台上对所提方法进行测试验证,仿真结果证明了该方法在复杂工况和分布式电源接入条件下的有效性和鲁棒性。研究结果可为现有故障定位方法提供辅助决策功能。
Fast and accurate fault location is very important to the running quality and reliability of power distribution system.At present,most of the fault location methods of multi-branch distribution are realized by adding measuring devices in distribution network.However,the topology structure of the distribution network is complex,the number of existing monitoring equipment is limited,and the large-scale installation of additional measuring equipment is expensive,which makes it difficult to be widely used in the actual system.Therefore,a fault location method for multi-branch distribution lines based on limited measurement information is proposed.Firstly,the nonlinear relationship between the capacitance information and the fault distance in multi-branch distribution lines is analyzed theoretically,and the feasibility of using deep learning to construct mapping function to complete the fault location task is proved.Then,the stack auto-encoder and long-short term memory network are used to establish an intelligent location model to reduce the error estimation of multi-branch distribution lines for fault location.Secondly,based on the measurement information in the distribution automation system,the determination and location for fault lines are realized by logical reasoning and intelligent location model.Finally,an intelligent localization implementation scheme based on deep transfer learning is proposed to improve the performance of the proposed method in various applications.The proposed location method is tested and verified on MATLAB/SIMULINK platform,and the simulation results show the effectiveness and generalization ability of the proposed method under complex working conditions and distributed generation access conditions.The results of this study can provide an auxiliary decision function for existing fault location methods.
作者
尚博阳
罗国敏
茹嘉昕
王小君
刘畅宇
SHANG Boyang;LUO Guomin;RU Jiaxin;WANG Xiaojun;LIU Changyu(School of Electrical Engineering,Beijing Jiaotong University,Beijing 100044,China)
出处
《高电压技术》
EI
CAS
CSCD
北大核心
2023年第6期2308-2317,共10页
High Voltage Engineering
基金
国家自然科学基金(国家电网公司智能电网联合基金)(U2066210)。
关键词
故障定位
堆栈自编码器
长短期记忆网络
智能量测装置
多分支配电线路
fault location
stacked auto encoder
long short term memory network
intelligent electronic devices
multi-branch distribution systems
