| 引用本文: | 汤 波,郑宇鹏,余光正,等.电气-环境耦合作用下的引流线可靠性评估方法[J].电力系统保护与控制,2022,50(10):84-93.[点击复制] |
| TANG Bo,ZHENG Yupeng,YU Guangzheng,et al.Reliability assessment method of drainage lines under electrical environmental coupling[J].Power System Protection and Control,2022,50(10):84-93[点击复制] |
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| 摘要: |
| 自然灾害下电力设备故障成为用户停电和灾后抢修的主要因素，电力设备的健康程度和抗灾能力与其长期运行环境密切相关，评估其健康水平对提升设备可靠性具有重要意义。以自然灾害特征最为明显的海岛配电网和故障频率最高的引流线为对象，根据其在多因素、强相关性环境特征影响下的运行状况，提出一种基于双重优化改进集成神经网络的引流线可靠性评估方法。首先，通过最大信息系数筛选配电线路故障特征，形成历史故障数据集。其次，为提取海岛微气象环境下的引流线故障规律，结合主成分分析和Kmeans对引流线进行故障区域划分。在此基础上，构建电气-环境耦合的集成神经网络预测模型，关联海岛气象特征和引流线故障特征进行寿命预测。并通过Attention机制和双重优化体系进行改进，突出海岛典型气象因素影响、提升预测准确性。最后，基于浙江舟山实际数据进行算例验证。结果表明：所提方法能够有效评估海岛配电网引流线的寿命状况，对提高配电网设备可靠性具有重要实用价值。 |
| 关键词: 配电网 电力设备 电气-环境耦合 改进集成神经网络 可靠性评估 |
| DOI：DOI: 10.19783/j.cnki.pspc.211045 |
| 投稿时间：2021-08-07修订日期：2021-11-10 |
| 基金项目:上海市科委创新行动计划资助(8DZ1203200)；国网浙江省电力有限公司科技项目资助(5211ZS190071) |
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| Reliability assessment method of drainage lines under electrical environmental coupling |
| TANG Bo,ZHENG Yupeng,YU Guangzheng,ZHOU Jianke,WANG Zhen,YANG Xiu |
| (1. College of Electrical Power, Shanghai University of Electric Power, Shanghai 200090, China;
2. Zhoushan Power Supply Company, State Grid Zhejiang Electric Power Co., Ltd., Zhoushan 316000, China) |
| Abstract: |
| Power equipment failures have become the main reasonss for user power outages and emergency repairs when there are natural disasters. The health and resilience of power equipment are closely related to their long-term operating environment. Assessing their health level is of great significance in improving equipment reliability. This paper takes the island distribution network with the most obvious natural disaster characteristics and the drainage line with the highest fault frequency as the object. Given its operating conditions under the influence of multiple factors and strong correlation environmental characteristics, we propose a method for assessing the reliability of drainage lines based on an improved integrated neural network with double optimization. First, the maximal information coefficient (MIC) algorithm is used to filter the fault characteristics to form an historical fault data set. Secondly, to extract the fault rules of drainage lines in the island micro-weather environment, principal component analysis (PCA) combined with K-means is used to divide the fault area. Then an electrical-environmental coupling integrated neural network prediction model is constructed for life prediction by correlating island weather characteristics and drainage line fault characteristics, and is improved by an attention mechanism and dual optimization system to highlight the impact of typical island weather factors and improve prediction accuracy. Finally, based on the actual data of Zhoushan, Zhejiang Province, a calculation example is given. The results show that the proposed method can effectively assess the life of the drainage line of an island distribution network, and has important practical value for improving the reliability of distribution network equipment.
This work is supported by the Innovation Action Plan of Science and Technology Commission of Shanghai Municipality (No. 8DZ1203200). |
| Key words: distribution network power equipment electrical-environmental coupling improved integrated neural network reliability assessment |
