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DOI:
电力大数据:2024,27(10):-
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基于大数据和云空间技术的电力系统变电检修策略研究
路赵, 王红全, 田园, 史振伟, 郭靖
(乌兰察布供电公司)
Research of Power System Substation Maintenance Strategies Based on Big Data and Cloud Space Technology
Lu Zhao, Wang Hongquan, Tian Yuan, Shi Zhenwei, Guo Jing
(Ulanqab Power Supply Company,Ulanqab,Inner Mongolia,China)
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投稿时间:2024-06-12    修订日期:2024-10-18
中文摘要: 随着我国经济的快速发展,电力需求不断增长,电力系统规模不断扩大,对电力系统的安全、稳定运行提出了更高的要求。变电检修作为电力系统运行维护的重要环节,对保障电力系统的可靠运行具有至关重要的作用。本文针对传统变电检修策略的不足,提出了一种基于大数据和云空间技术的新型电力系统变电检修策略。通过对大量历史数据的挖掘和分析,实现对变电设备运行状态的实时监测和预测,从而提高变电检修的针对性和效率,降低检修成本,为电力系统的安全、稳定运行提供有力保障。
Abstract:With the rapid development of China"s economy, the demand for electricity continues to grow, and the scale of the power system continues to expand, which puts forward higher requirements for the safe and stable operation of the power system. Substation maintenance, as an important part of power system operation and maintenance, plays a crucial role in ensuring the reliable operation of the power system. This article proposes a new power system substation maintenance strategy based on big data and cloud space technology to address the shortcomings of traditional substation maintenance strategies. By mining and analyzing a large amount of historical data, real-time monitoring and prediction of the operation status of substation equipment can be achieved, thereby improving the pertinence and efficiency of substation maintenance, reducing maintenance costs, and providing strong guarantees for the safe and stable operation of the power system.
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