基于大数据的智能变电站的选址模型设计

发布时间：2018-06-06 17:24

本文选题：智能变电站 + 选址　；参考：《吉林大学》2017年硕士论文

【摘要】：智能变电站选址一直是电力行业研究的重要课题之一。从电力角度讲,变电站的站址优劣直接影响未来电力系统的供电质量和运行经济性。以往变电站选址多使用属性数据(如变电站容量),对空间数据分析较少,更不论利用空间大数据进行智能变电站的选址分析。而在变电站选址过程中,需要应用到遥感数据、环境数据、电子表数据等各类数据,尤其是需要对大量空间数据进行分析。这些数据的数据量巨大,在分析时单机模式无法满足其分析要求,所以需引入大数据分析模式,采用分布式分析进行变电站选址。本研究主要包括以下五点内容:1.深入分析变电站选址影响因素,分析、总结变电站选址主要受经济因素、地形地貌因素、国土资源与自然灾害因素、自然资源因素、人文社会因素五大类因素制约。根据分析出的影响因素制定可量化的智能变电站选址指标体系,并对体系中的指标合理赋值。2.综合考虑智能变电站选址模型中的经济模型和空间位置模型,采用层次分析法建立可扩展的、科学的基于大数据的智能变电站的选址模型。3.设计智能变电站选址系统的大数据智能分析系统框架、分布式存储、分布式计算框架,设计系统的功能模型及每一个子功能,并给出智能变电站空间大数据分析或挖掘的数学算法。利用Eclipse、Web Storm作为开发工具,利用目前世界上最新、最先进的Arc GIS Tools for Hadoop与大数据平台交互,采用Arc GIS Server 10.5作为空间大数据分析平台,采用Java、Java Script、AIR等编程实现B/S模式的基于大数据的智能变电站选址系统。采用长春地区部分数据,对基于大数据的智能变电站选址模型进行测试。分析结果表明,模型是可行的、合理的。基于大数据的智能变电站的选址系统为智能变电站选址适应大数据时代发展需求提供新的解决方案,为智能变电站信息化、智能化、高效化提供支持。
[Abstract]:Intelligent substation location has been one of the important research topics in power industry. From the power point of view, the substation site directly affects the power supply quality and operation economy of the future power system. In the past, attribute data (such as substation capacity) were used in substation siting, and spatial data were less analyzed, and spatial big data was used to analyze the location of intelligent substation. In the process of substation location, it needs to be applied to remote sensing data, environmental data, electronic table data and other data, especially to a large number of spatial data analysis. The data volume of these data is so large that the single machine mode can not meet the requirements of the analysis, so it is necessary to introduce the big data analysis mode and adopt distributed analysis to locate the substation. This research mainly includes the following five points: 1. This paper analyzes the influence factors of substation location, analyzes and summarizes that substation location is mainly restricted by five kinds of factors: economic factors, landform factors, land resources and natural disasters factors, natural resources factors, humanities and social factors. According to the analysis of the influencing factors, a quantifiable intelligent substation location index system is established, and the index in the system is assigned to the reasonable value of .2. Considering the economic model and spatial location model of intelligent substation location model, an extensible and scientific intelligent substation location model based on big data. 3 is established by analytic hierarchy process (AHP). The big data intelligent analysis system framework, distributed storage, distributed computing framework, function model and each sub-function of the intelligent substation location system are designed. A mathematical algorithm for spatial big data analysis or mining of intelligent substation is presented. Using Eclipse Arc Storm as the development tool, using the newest and most advanced Arc GIS tools for Hadoop to interact with the big data platform, and using Arc GIS Server 10.5 as the spatial big data analysis platform. The intelligent substation location system based on big data is implemented by Java script and air. The intelligent substation location model based on big data is tested with some data in Changchun area. The results show that the model is feasible and reasonable. The intelligent substation location system based on big data provides a new solution for the intelligent substation location to meet the needs of the development of the big data era, and provides the support for the intelligent substation information, intelligence and high efficiency.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM63;TM76

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