智能输电线路监测模式与监测框架研究

发布时间：2018-07-28 11:38

【摘要】：我国建设以特高压电网为骨干网架的智能电网,实现输电线路的智能化是其中的一个重要环节,但对智能输电线路的研究还比较少。本文首先阐释了智能输电线路模式,从安全灵活、响应迅速、经济运行、节能环保四个方面对智能输电线路关键技术进行了分析,对未来智能输电线路提出了进一步设想。输电线路是电力系统的重要组成部分,覆盖面积比变电站更广,我国地域广阔,输电线路途经山区、盆地、丘陵等多种地形,沿输电线路走廊,地质地貌状况复杂,气候环境多变,常有大风、雷电、重污染、冰雪等极端气候状况。输电线路暴露在环境中,运行状况直接受到环境影响。从上世纪以来,我国多个地区都曾发生过由于遭受天气灾害造成的输电线路故障。输电线路一旦发生故障将直接影响电力系统安全稳定运行,会给国民经济的生产生活带来重大损失,危害国家经济发展和社会稳定。对输电线路设备检修是保证电力系统正常运行的有效手段,通过设备检修,可以减少由于设备故障造成的系统停电,提高输电可靠性。过去采用计划检修,已不能适应当前电力生产要求,电力系统状态检修这种方式也应运而生。当前输电线路各类特征参量的在线监测终端已经能够实现对线路状态监测。输电线路往往处于较为复杂的环境当中,这就要求监测系统能够综合监测线路运行状况,并能够根据监测数据诊断出线路故障,为线路安全运行提供决策依据。为此,本文研究了输电线路模糊评价理论,通过对数据的分析、比较、判别,深度挖掘监测数据,实现对输电线路设备状态的风险评估,为运行维护和管理部门提供检修决策依据,提前采取维护措施,及时排除线路潜在隐患。最后从国家电网公司建设智能电网发展战略的背景和需求出发,对智能输电线路监测系统进行了的总体设计,对系统的开发目标、设计原则、系统的软、硬件架构和系统具备的功能进行了具体的论述,研究结果在工程实际应用中易于推广使用,具有重要的理论意义和现实意义。
[Abstract]:Intelligent transmission line is one of the most important links in the construction of smart grid with UHV grid as the backbone in our country, but the research on intelligent transmission line is still few. This paper first explains the intelligent transmission line mode, analyzes the key technology of intelligent transmission line from four aspects of safety and flexibility, rapid response, economic operation, energy saving and environmental protection, and puts forward a further assumption for the future intelligent transmission line. Transmission line is an important part of the power system, covering a wider area than a substation, China has a vast area, transmission lines pass through mountainous areas, basins, hills and other terrain, along the transmission line corridor, geological and geomorphological conditions are complex. Climate environment is changeable, often wind, lightning, heavy pollution, snow and ice and other extreme weather conditions. Transmission lines are exposed to the environment, and the operating conditions are directly affected by the environment. Since last century, transmission line failures caused by weather disasters have occurred in many regions of China. Once the transmission line breaks down, it will directly affect the safe and stable operation of the power system, bring great losses to the production and life of the national economy, and endanger the national economic development and social stability. Maintenance and repair of transmission line equipment is an effective means to ensure the normal operation of power system. Through equipment maintenance, power system outages caused by equipment failures can be reduced and transmission reliability can be improved. In the past, the use of planned maintenance, can not adapt to the current power production requirements, power system condition based maintenance has emerged as the times require. At present, on-line monitoring terminals of various characteristic parameters of transmission lines have been able to realize line state monitoring. Transmission lines are often in a more complex environment, which requires that the monitoring system can comprehensively monitor the operation of the lines, and can diagnose the line faults according to the monitoring data, and provide a decision basis for the safe operation of the lines. In this paper, the fuzzy evaluation theory of transmission line is studied, and the risk assessment of transmission line equipment is realized by analyzing, comparing, discriminating and deeply mining the monitoring data. Provide maintenance decision basis for operation maintenance and management department, take maintenance measures ahead of time, remove potential hidden trouble in time. Finally, based on the background and requirements of the smart grid development strategy of State Grid Company, the overall design of the intelligent transmission line monitoring system, the development objectives, design principles and soft of the system are given. The hardware architecture and the functions of the system are discussed in detail. The research results are easy to be popularized and used in practical engineering, which has important theoretical and practical significance.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM75

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