【摘要】：近年來,電力GIS憑借其在空間信息展現(xiàn)能力以及管理分析能力上的優(yōu)勢,有效地提高了電網(wǎng)設備的可視化水平,增強了電網(wǎng)的實時監(jiān)管能力,已經(jīng)成為電力信息化建設中不可或缺的一部分。隨著智能電網(wǎng)建設的迅速推進以及電網(wǎng)規(guī)模的不斷擴大,電力行業(yè)正面臨一系列新的挑戰(zhàn),如電網(wǎng)信息更加龐大、數(shù)據(jù)分布更加廣泛、電氣接線日益復雜、電力分析難度不斷加大等,傳統(tǒng)的存儲策略與計算模式越來越難以適應電力GIS新的需求,現(xiàn)有的GIS服務器在計算資源、數(shù)據(jù)處理與響應速度等方面的局限性也逐漸體現(xiàn)出來,如何高效地存儲與管理海量數(shù)據(jù),是電力GIS急需解決的問題。云計算作為一種具有良好擴展性和可用性的分布式計算架構(gòu),為海量電力GIS數(shù)據(jù)的管理提供了新的解決思路。本文選用Hadoop開源云平臺,對云計算在電力GIS領域的應用進行了積極的探索與研究。在對電力GIS各類數(shù)據(jù)進行歸納和分析的基礎上,充分考慮關系型數(shù)據(jù)庫和非關系型數(shù)據(jù)庫的優(yōu)勢,給出了電力GIS數(shù)據(jù)存儲策略以及基于Hadoop的數(shù)據(jù)管理架構(gòu)。設計了遵循OGC標準的空間數(shù)據(jù)模型、基于橫縱表結(jié)構(gòu)的運行數(shù)據(jù)模型以及其它核心對象模型,并利用MapReduce實現(xiàn)了電力GIS數(shù)據(jù)并行處理的相關技術,包括瓦片金字塔的并行構(gòu)建技術、空間索引的并行生成技術、空間數(shù)據(jù)的并行分析技術和運行數(shù)據(jù)的并行查詢技術。為了對所提出的電力GIS數(shù)據(jù)處理方法進行驗證,本文在傳統(tǒng)單機環(huán)境和Hadoop集群環(huán)境下進行了一系列對比實驗,實驗結(jié)果表明,基于MapReduce的數(shù)據(jù)并行處理方法效率較高,擴展性較好,在數(shù)據(jù)量達到一定規(guī)模時,瓦片金字塔構(gòu)建時間、索引生成時間、數(shù)據(jù)分析與查詢的平均時間大幅度縮短,能夠很好的滿足海量電力GIS數(shù)據(jù)存儲與管理的需求。
[Abstract]:In recent years, with its advantages in spatial information presentation and management analysis, power GIS has effectively improved the visualization level of power grid equipment and enhanced the real-time supervision ability of power grid. It has become an indispensable part of electric power information construction. With the rapid development of smart grid construction and the continuous expansion of power grid scale, the electric power industry is facing a series of new challenges, such as the information of power grid is larger, the data distribution is more extensive, and the electrical connection is increasingly complex. With the increasing difficulty of power analysis, the traditional storage strategy and computing mode are becoming more and more difficult to adapt to the new demands of power GIS, and the limitations of existing GIS servers in computing resources, data processing and response speed are gradually reflected. How to store and manage massive data efficiently is an urgent problem for GIS. Cloud computing, as a distributed computing architecture with good scalability and availability, provides a new solution for the management of massive power GIS data. In this paper, Hadoop open source cloud platform is used to explore and research the application of cloud computing in the field of electric power GIS. On the basis of summarizing and analyzing all kinds of data of power GIS, considering the advantages of relational database and non-relational database, the data storage strategy of power GIS and the data management architecture based on Hadoop are given. The spatial data model following OGC standard, the running data model based on the structure of horizontal and vertical table and other core object models are designed, and the related technology of parallel processing of power GIS data is realized by using MapReduce. It includes the parallel construction technology of tile pyramid, the parallel generation technology of spatial index, the parallel analysis technology of spatial data and the parallel query technology of running data. In order to verify the proposed method of power GIS data processing, a series of comparative experiments are carried out in the traditional single-machine environment and Hadoop cluster environment. The experimental results show that the parallel data processing method based on MapReduce is more efficient. When the amount of data reaches a certain scale, the building time of tile pyramid, the time of index generation, the average time of data analysis and query are greatly shortened, which can meet the demand of massive power GIS data storage and management.
【學位授予單位】：華北電力大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TM769;TP311.13

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