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考慮分布式電源的多時(shí)段配電網(wǎng)絡(luò)重構(gòu)

發(fā)布時(shí)間:2018-03-20 08:45

  本文選題:配網(wǎng)重構(gòu) 切入點(diǎn):多時(shí)段 出處:《華北電力大學(xué)(北京)》2017年碩士論文 論文類型:學(xué)位論文


【摘要】:能源危機(jī)和環(huán)境保護(hù)問(wèn)題日益嚴(yán)峻,大力發(fā)展可再生能源勢(shì)在必行,但集中式發(fā)電方式下嚴(yán)重的棄風(fēng)、棄光問(wèn)題也隨之而來(lái)。分布式發(fā)電(DG)則能在充分利用用戶側(cè)可再生能源的同時(shí)避免長(zhǎng)距離輸電帶來(lái)的損耗,具有廣闊的應(yīng)用前景。本文針對(duì)考慮分布式電源的多時(shí)段配電網(wǎng)絡(luò)重構(gòu)問(wèn)題展開(kāi)研究,主要包含了以下幾個(gè)方面的工作:(1)針對(duì)考慮分布式電源的單時(shí)段配網(wǎng)重構(gòu)問(wèn)題,本文建立了以網(wǎng)損最小為目標(biāo)函數(shù)的優(yōu)化模型,深入分析了DG出力與網(wǎng)絡(luò)重構(gòu)之間互相影響的情況,為電網(wǎng)公司裝設(shè)和運(yùn)行DG提出了參考建議。(2)針對(duì)考慮分布式電源的多時(shí)段配電網(wǎng)絡(luò)重構(gòu)問(wèn)題,本文建立了以網(wǎng)損電量和開(kāi)關(guān)操作總費(fèi)用最小為目標(biāo)函數(shù)的優(yōu)化模型,對(duì)不同開(kāi)關(guān)操作費(fèi)用下的重構(gòu)情況進(jìn)行了對(duì)比分析,為調(diào)度運(yùn)行人員進(jìn)行網(wǎng)絡(luò)重構(gòu)提供參考。(3)針對(duì)多時(shí)段配電網(wǎng)絡(luò)重構(gòu)問(wèn)題的復(fù)雜性,為減小算法搜索范圍、提高算法效率,本文提出了一種簡(jiǎn)單、快速、有效的方法以獲取各時(shí)段對(duì)應(yīng)的待選網(wǎng)絡(luò)結(jié)構(gòu)集合。(4)針對(duì)考慮DG和負(fù)荷隨機(jī)性的多時(shí)段配電網(wǎng)絡(luò)重構(gòu)問(wèn)題,本文建立了以某一置信水平下網(wǎng)損和開(kāi)關(guān)操作總費(fèi)用最小為目標(biāo)函數(shù)的多時(shí)段配電網(wǎng)絡(luò)重構(gòu)機(jī)會(huì)約束規(guī)劃模型,所得的多時(shí)段動(dòng)態(tài)重構(gòu)方案不需要依賴準(zhǔn)確的DG出力和負(fù)荷預(yù)測(cè),能以一定概率保證系統(tǒng)的安全經(jīng)濟(jì)運(yùn)行。本文為以上模型設(shè)計(jì)了相應(yīng)的遺傳算法,并通過(guò)算例計(jì)算驗(yàn)證了所提模型和算法的正確性和有效性。
[Abstract]:The energy crisis and environmental protection are becoming more and more serious, so it is imperative to develop renewable energy. DGs can make full use of renewable energy on the user side while avoiding the loss of long distance transmission. This paper focuses on the reconfiguration problem of multi-time distribution network considering distributed power supply, which mainly includes the following aspects: (1) single time distribution network reconfiguration problem considering distributed power supply. In this paper, an optimization model with minimum network loss as objective function is established, and the interaction between DG output and network reconstruction is deeply analyzed. This paper presents a reference proposal for the installation and operation of DG in power grid companies. (2) aiming at the problem of reconfiguration of multi-time distribution networks considering distributed generation, an optimization model with the minimum power loss and the total switching cost as the objective function is established in this paper. This paper makes a comparative analysis of the reconfiguration situation under different switching operation costs, which provides a reference for the dispatcher to reconfigure the network, aiming at the complexity of the reconfiguration problem of multi-time distribution network, in order to reduce the search scope of the algorithm and improve the efficiency of the algorithm. In this paper, a simple, fast and effective method is proposed to obtain the network structure set for each time period. (4) to solve the problem of multi-time distribution network reconfiguration considering the randomness of DG and load, this paper proposes a simple, fast and effective method. In this paper, an opportunity constraint programming model for multi-time distribution network reconfiguration is established, which takes the minimum network loss and the minimum switching operation total cost as the objective function at a certain confidence level. The proposed multi-period dynamic reconstruction scheme does not depend on accurate DG output and load forecasting and can guarantee the safe and economical operation of the system with a certain probability. This paper designs the corresponding genetic algorithm for the above model. The correctness and validity of the proposed model and algorithm are verified by an example.
【學(xué)位授予單位】:華北電力大學(xué)(北京)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2017
【分類號(hào)】:TM711

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 吉興全;劉琪;王成山;于永進(jìn);張曉;;基于協(xié)同進(jìn)化的配網(wǎng)動(dòng)態(tài)重構(gòu)算法[J];安徽大學(xué)學(xué)報(bào)(自然科學(xué)版);2016年04期

2 易海川;張彼德;王海穎;吳宇;袁國(guó)森;呂柔睿;;提高DG接納能力的配電網(wǎng)動(dòng)態(tài)重構(gòu)方法[J];電網(wǎng)技術(shù);2016年05期

3 王琛;,

本文編號(hào):1638336


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