本文選題：智能電網(wǎng) + 電力調(diào)度　； 參考：《天津理工大學》2014年碩士論文

【摘要】：隨著電力建設(shè)規(guī)模的擴大和電力企業(yè)的市場化改革，現(xiàn)代電力系統(tǒng)正朝著分布式、信息化、自動化的方向發(fā)展，其生產(chǎn)結(jié)構(gòu)和運行方式將會日益復雜化。在新形勢之下，電力調(diào)度中心作為整個電網(wǎng)運行的指揮控制中心，，其數(shù)據(jù)信息分布之廣泛、數(shù)量之龐大、結(jié)構(gòu)之復雜以及處理和存儲信息要求之高，這都使得傳統(tǒng)的電網(wǎng)調(diào)度信息平臺在信息集成、分析、計算和存儲等方面難以滿足電網(wǎng)運行監(jiān)控的需求。為了能夠解決這些問題，本文將云計算引入智能電網(wǎng)調(diào)度系統(tǒng)中，利用云計算的相關(guān)技術(shù)為電力調(diào)度提供更為智能化的決策支持和實現(xiàn)方式。 云計算是分布式計算技術(shù)的進化、虛擬化技術(shù)的發(fā)展、面向服務(wù)的體系架構(gòu)（SOA）的延伸、信息資源的智能管理和調(diào)配機制的體現(xiàn)，具有超高性能、超大規(guī)模、廉價等特點，是電網(wǎng)智能化計算平臺有力的技術(shù)組成。目前，云計算在計算機信息等領(lǐng)域中的應(yīng)用已取得顯著成果，但在電力系統(tǒng)中還處于起步階段，電力系統(tǒng)的云計算平臺還處于構(gòu)想和規(guī)劃階段。電力調(diào)度是整個電網(wǎng)的“大腦”，擔負著全網(wǎng)安全穩(wěn)定、高效運行、管理調(diào)配、節(jié)能環(huán)保的重要職責。因此，基于云計算的智能電網(wǎng)調(diào)度系統(tǒng)的研究有助于在更大范圍內(nèi)促進云計算在智能電網(wǎng)中的應(yīng)用。 本文首先介紹了云計算的基本概念、主要特點以及Map/Reduce計算模型和HDFS系統(tǒng)等云計算相關(guān)的核心技術(shù)，并結(jié)合智能電網(wǎng)調(diào)度系統(tǒng)的結(jié)構(gòu)和特點，設(shè)計了基于云計算的智能電網(wǎng)調(diào)度系統(tǒng)平臺的邏輯架構(gòu)；然后在對傳統(tǒng)任務(wù)調(diào)度算法和遺傳算法（GA）研究的基礎(chǔ)上，結(jié)合智能電網(wǎng)調(diào)度系統(tǒng)數(shù)據(jù)信息采集和處理的特點，提出了一種基于改進遺傳算法（IGA）的任務(wù)調(diào)度算法，目的在于提高智能電網(wǎng)調(diào)度系統(tǒng)的分布式數(shù)據(jù)處理能力和資源優(yōu)化配置能力；最后部署了模擬智能電網(wǎng)運行調(diào)度數(shù)據(jù)中心的Hadoop實驗平臺，在該平臺上通過仿真算例和數(shù)據(jù)分析，將先進先出調(diào)度算法、公平調(diào)度算法、計算能力調(diào)度算法、自適應(yīng)遺傳算法（AGA）與改進遺傳算法進行性能比較，驗證了基于IGA的云計算任務(wù)調(diào)度算法是一種能夠有效提高智能電網(wǎng)調(diào)度系統(tǒng)中海量任務(wù)的分析與計算效率的任務(wù)調(diào)度算法。
[Abstract]:With the expansion of electric power construction scale and the marketization reform of electric power enterprises, the modern power system is developing towards the direction of distribution, information and automation, and its production structure and operation mode will become more and more complicated. Under the new situation, as the command and control center of the whole power network, the power dispatching center has a wide distribution of data and information, a large number of data, a complex structure, and a high requirement for processing and storing information. This makes it difficult for the traditional grid dispatching information platform to meet the needs of power grid operation monitoring in the aspects of information integration, analysis, calculation and storage. In order to solve these problems, this paper introduces cloud computing into smart grid dispatching system, using cloud computing technology to provide more intelligent decision support and implementation for power dispatching. Cloud computing is the evolution of distributed computing technology, the development of virtualization technology, the extension of Service-Oriented Architecture (SOA), and the embodiment of intelligent management and deployment mechanism of information resources. It is a powerful technical component of intelligent computing platform for power grid. At present, the application of cloud computing in computer information and other fields has achieved remarkable results, but in the power system is still in its infancy, and the cloud computing platform of power system is still in the stage of conception and planning. Power dispatching is the "brain" of the whole power grid, which is responsible for the safety and stability, efficient operation, management and allocation, energy saving and environmental protection. Therefore, the research of smart grid dispatching system based on cloud computing is helpful to promote the application of cloud computing in smart grid. This paper first introduces the basic concept of cloud computing, the main characteristics and the core technologies related to cloud computing, such as Map/Reduce computing model and HDFS system, and combines the structure and characteristics of smart grid dispatching system. The logical framework of smart grid dispatching system platform based on cloud computing is designed, and then based on the research of traditional task scheduling algorithm and genetic algorithm, the paper combines the characteristics of smart grid dispatching system data collection and processing. A task scheduling algorithm based on improved genetic algorithm (IGA) is proposed to improve the distributed data processing capability and resource optimal allocation ability of smart grid dispatching system. Finally, the Hadoop experimental platform is deployed to simulate the smart grid dispatching data center. Through the simulation examples and data analysis, the first-in-first-out scheduling algorithm, the fair scheduling algorithm, the computing ability scheduling algorithm are put forward. Comparing the performance of adaptive genetic algorithm (AGA) and improved genetic algorithm (GA), it is verified that cloud computing task scheduling algorithm based on IGA is a task scheduling algorithm which can effectively improve the efficiency of analyzing and computing mass tasks in smart grid scheduling system.
【學位授予單位】：天津理工大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM76;TM73

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本文編號：1874931