【摘要】：需求側(cè)管理措施、分布式電源并網(wǎng)和配電自動(dòng)化等電網(wǎng)新技術(shù)的持續(xù)穩(wěn)定發(fā)展為傳統(tǒng)配電網(wǎng)的運(yùn)行和規(guī)劃方法帶來(lái)了巨大的挑戰(zhàn)。持續(xù)快速增長(zhǎng)的負(fù)荷需求如果僅依靠配電網(wǎng)擴(kuò)容來(lái)滿(mǎn)足,電力系統(tǒng)建設(shè)周期長(zhǎng)和擴(kuò)建投資較大的情況就會(huì)出現(xiàn),導(dǎo)致經(jīng)濟(jì)性要求無(wú)法被滿(mǎn)足,并且無(wú)法充分考慮需求側(cè)響應(yīng)及分布式發(fā)電等因素,不利于智能電網(wǎng)的發(fā)展。在高比例分布式電源并網(wǎng)、負(fù)荷需求側(cè)急需管理的環(huán)境下,將分布式發(fā)電和需求側(cè)管理引入配電網(wǎng)規(guī)劃,建立基于分布式電源和需求側(cè)管理的規(guī)劃框架,具有重要的研究?jī)r(jià)值與工程意義。本文介紹分布式發(fā)電和需求側(cè)管理技術(shù)的概念和分類(lèi),介紹配電網(wǎng)中接入分布式電源導(dǎo)致的如系統(tǒng)潮流、電能質(zhì)量、可靠性等影響,分析簡(jiǎn)述以新能源為代表的分布式發(fā)電技術(shù)的數(shù)學(xué)模型并說(shuō)明各自的工作原理;分析需求側(cè)管理技術(shù)措施以及對(duì)分布式電源并網(wǎng)的影響,提出分析需求側(cè)管理實(shí)施過(guò)程中可能遇到的問(wèn)題。在分布式電源的形式不確定的情況下,考慮其對(duì)配電網(wǎng)規(guī)劃中的影響,以分布式電源的網(wǎng)損費(fèi)用、投資及運(yùn)行費(fèi)用、引入分布式電源后環(huán)境效益、購(gòu)電費(fèi)用等為目標(biāo)確定目標(biāo)函數(shù),在聯(lián)合規(guī)劃的配電網(wǎng)規(guī)劃模型中引入需求側(cè)管理。研究分布式電源接入主動(dòng)配電網(wǎng)的優(yōu)化配置問(wèn)題,建立多目標(biāo)優(yōu)化配置模型,提出一種混合智能粒子群算法,在優(yōu)化過(guò)程中改善其全局搜索能力。編寫(xiě)混合智能粒子群算法計(jì)算程序,尋優(yōu)目標(biāo)函數(shù),得到包括經(jīng)濟(jì)性和可靠性在內(nèi)的最優(yōu)的規(guī)劃方案。分別計(jì)算對(duì)IEEE-33節(jié)點(diǎn)以及PGE-69節(jié)點(diǎn)配電系統(tǒng),分析在不同負(fù)荷水平下各指標(biāo)的變化情況,研究負(fù)荷變化時(shí)DG的最佳配置,驗(yàn)證算法和模型的有效性。
[Abstract]:The continuous and stable development of new technologies such as demand-side management, distributed power grid connection and distribution automation has brought great challenges to the traditional distribution network operation and planning methods. If the continuous and rapid growth of load demand is satisfied only by distribution network expansion, the long construction period and large investment in the expansion of power system will occur, resulting in economic requirements can not be met. And the demand side response and distributed generation can not be fully considered, which is not conducive to the development of smart grid. In the environment of high proportion of distributed power generation and urgent need of load demand side management, the distributed generation and demand side management are introduced into distribution network planning, and the planning framework based on distributed generation and demand side management is established. It has important research value and engineering significance. In this paper, the concept and classification of distributed generation and demand-side management technology are introduced, and the influence of power flow, power quality, reliability and so on caused by access to distributed generation in distribution network is introduced. The mathematical models of distributed power generation technology represented by new energy are analyzed and their working principles are explained. This paper analyzes the technical measures of demand-side management and its influence on the grid connection of distributed power supply, and puts forward the problems that may be encountered in the implementation of demand-side management. In the case of uncertain form of distributed generation, considering its influence on distribution network planning, the environmental benefits of distributed generation are introduced in terms of network loss cost, investment and operation cost of distributed generation. The cost of purchasing electricity is the objective function, and demand-side management is introduced into the distribution network planning model of joint planning. This paper studies the optimal configuration of distributed power supply access active distribution network, establishes a multi-objective optimal configuration model, and proposes a hybrid intelligent particle swarm optimization algorithm to improve its global search ability in the process of optimization. The program of hybrid intelligent particle swarm optimization algorithm is written to optimize the objective function and obtain the optimal programming scheme including economy and reliability. The distribution system of IEEE-33 node and PGE-69 node is calculated, the variation of each index under different load level is analyzed, the optimal configuration of DG is studied, and the validity of algorithm and model is verified.
【學(xué)位授予單位】：東北電力大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TM73;TM715

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