基于深度人工神经网络和GIS数据的最优停电模型研究

王继业; 朱欣焰; 赵光; 刘金长; 杨成月; 曾楠

引用本文:	王继业,朱欣焰,赵光,等.基于深度人工神经网络和GIS数据的最优停电模型研究[J].电力系统保护与控制,2019,47(16):58-63.
	WANG Jiye,ZHU Xinyan,ZHAO Guang,et al.Research on optimal outage model based on deep artificial neural network and GIS data[J].Power System Protection and Control,2019,47(16):58-63

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基于深度人工神经网络和GIS数据的最优停电模型研究
王继业¹,朱欣焰²,赵光³,刘金长⁴,杨成月⁴,曾楠¹
(1.国家电网公司信息通信部，北京 100031;2.武汉大学测绘遥感信息工程国家重点实验室，湖北武汉 430072; 3.厦门亿力吉奥信息科技有限公司，福建厦门 361009;4.国网思极神往位置服务有限公司，北京 102211)

摘要:

为了有效利用地理信息技术支撑复杂大电网的信息化建设，针对停电事故对电力系统运行和日常生活带来的诸多影响，提出基于深度人工神经网络和GIS数据的最优停电模型。结合电力系统运行的特殊性，把最优参数设置和增量反馈结合用来优化受限玻尔兹曼机算法。通过仿真分析了算法的性能。仿真结果表明，采用深度神经网络的最优停电模型可以提高计算效率和精度。

关键词: 最优停电模型 GIS技术深度神经网络复杂大电网

DOI：10.19783/j.cnki.pspc.181274

分类号:

基金项目:国家863计划项目资助(2011AA05A116);国家电网公司科技项目资助(KJ00-01-08-02)

Research on optimal outage model based on deep artificial neural network and GIS data

WANG Jiye¹,ZHU Xinyan²,ZHAO Guang³,LIU Jinchang⁴,YANG Chengyue⁴,ZENG Nan¹

(1. Information and Communication Department of State Grid, Beijing 100031, China;2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430072, China;3. Xiamen Great Power GEO Information Technology Co., Ltd., Xiamen 361009, China;4. State Grid Shenwang LBS (Beijing) Co., Ltd., Beijing 102211, China)

Abstract:

In order to effectively utilize geographic information technology to support the information construction of complex large power grid, the impact of blackouts on power system operation and daily life, an optimal outage model based on deep artificial neural network and GIS data is proposed. Combining the particularity of power system operation, the optimal parameter setting is united with incremental feedback to optimize constrained Boltzmann algorithm. The performance of the algorithm is analyzed by simulation, and simulation results show that the optimal power outage model using deep neural network can improve the efficiency and accuracy of computation. This work is supported by National High-tech R & D Program of China (863 Program) (No. 2011AA05A116) and Science and Technology Project of State Grid Corporation of China (No. KJ00-01-08-02).

Key words: optimal power outage model GIS technology deep neural network complex large power grid

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