【摘要】：在正常情況下,商業(yè)樓宇型微網(wǎng)采用并網(wǎng)運行方式,當(dāng)配網(wǎng)出現(xiàn)故障時,商業(yè)樓宇型微網(wǎng)切換至孤島運行。在微網(wǎng)應(yīng)急運行的過程中,能量管理系統(tǒng)需兼顧減小停電影響范圍與維持微網(wǎng)的可靠持續(xù)供電兩方面。由于微網(wǎng)孤島運行后,光伏出力的不確定性依然存在,計及不確定因素的能量管理將更有利于系統(tǒng)的可靠運行。本文針對含有光儲系統(tǒng)的商業(yè)樓宇型微網(wǎng),提出了一種基于魯棒優(yōu)化的應(yīng)急能量管理策略。應(yīng)急能量管理的優(yōu)化目標(biāo)為減小停電損失、維持供電時間,且引入權(quán)重因子以權(quán)衡二者的重要程度,約束條件則考慮到功率平衡、可控負(fù)荷與儲能系統(tǒng)的運行限制。此外,在優(yōu)化模型中設(shè)置了不確定度以表征魯棒優(yōu)化的保守程度,且不確定度的大小決定了不確定因素對問題的影響程度。優(yōu)化模型中權(quán)重因子和不確定度的數(shù)值可根據(jù)實際情況靈活設(shè)定。此外,在魯棒優(yōu)化模型的基礎(chǔ)上引入了滾動優(yōu)化的思想,以定時更新光伏的實際出力數(shù)據(jù),從而獲得更為準(zhǔn)確的光伏預(yù)測數(shù)據(jù)。在由上述應(yīng)急能量管理策略確定可控負(fù)荷投入量后,給出了以“先調(diào)節(jié)、后切除”為原則的可控負(fù)荷調(diào)控策略,其中,電動汽車采用“柔性調(diào)節(jié)-剛性調(diào)節(jié)”兩階段調(diào)節(jié)方案,空調(diào)采用“奇數(shù)組-偶數(shù)組”輪換式調(diào)節(jié)方案,由此可得到停電后電動汽車的實時充電倍率與空調(diào)的實時功耗。通過算例對比分析可知,該策略可通過合理調(diào)整可控負(fù)荷投入量,以實現(xiàn)預(yù)期目標(biāo);通過算例靈敏度分析與不確定度分析可知,該策略可通過靈活設(shè)定權(quán)重因子與不確定度的數(shù)值,以調(diào)節(jié)兩個子目標(biāo)的重要程度及不確定因素對問題的影響程度。
[Abstract]:Under normal conditions, commercial building microgrids operate in a grid-connected mode. When the distribution network fails, the commercial building-type microgrids switch to islanding operation. In the process of emergency operation of microgrid, the energy management system should take into account two aspects: reducing the influence of power outage and maintaining the reliable and continuous power supply of microgrid. Since the uncertainty of photovoltaic force still exists after the operation of microgrid isolated islands, energy management with uncertain factors will be more favorable to the reliable operation of the system. In this paper, an emergency energy management strategy based on robust optimization is proposed for commercial building microgrids with optical storage systems. The optimization goal of emergency energy management is to reduce the power loss, maintain the power supply time, and introduce the weight factor to weigh the importance of the two factors, and the constraints take into account the power balance, controllable load and energy storage system operation constraints. In addition, uncertainty is set in the optimization model to represent the conservative degree of robust optimization, and the degree of uncertainty determines the influence of uncertainty on the problem. The value of weight factor and uncertainty in the optimization model can be flexibly set according to the actual situation. In addition, the idea of rolling optimization is introduced on the basis of the robust optimization model to update the actual output data of photovoltaic periodically, so as to obtain more accurate photovoltaic prediction data. After determining the amount of controllable load input from the above emergency energy management strategy, a controllable load control strategy based on the principle of "first adjusting, then removing" is presented, in which the "flexible regulation-rigid regulation" two-stage regulation scheme is adopted for electric vehicles. The air conditioning system adopts "odd group-even array" rotation regulation scheme, which can get the real time charging rate of electric vehicle after power failure and the real time power consumption of air conditioning system. Through the comparison and analysis of examples, it can be concluded that the strategy can achieve the expected goal by reasonably adjusting the amount of controllable load input. The sensitivity analysis and uncertainty analysis show that the strategy can adjust the importance of the two sub-targets and the influence of uncertainty on the problem by flexibly setting the value of weight factor and uncertainty.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TM73

【參考文獻】

相關(guān)期刊論文 前10條

1 艾小猛;韓杏寧;文勁宇;姚偉;羅衛(wèi)華;;考慮風(fēng)電爬坡事件的魯棒機組組合[J];電工技術(shù)學(xué)報;2015年24期

2 丁浩;高峰;劉坤;管曉宏;吳江;;基于魯棒優(yōu)化的含風(fēng)電工業(yè)微電網(wǎng)經(jīng)濟調(diào)度模型[J];電力系統(tǒng)自動化;2015年17期

3 劉志文;夏文波;劉明波;;實現(xiàn)微網(wǎng)供電恢復(fù)的分布式電源自組網(wǎng)策略[J];電力系統(tǒng)自動化;2015年09期

4 韓杏寧;黎嘉明;文勁宇;艾小猛;黎靜華;羅衛(wèi)華;;含多風(fēng)電場的電力系統(tǒng)儲能魯棒優(yōu)化配置方法[J];中國電機工程學(xué)報;2015年09期

5 季峰;蔡興國;岳彩國;;含風(fēng)電場電力系統(tǒng)的模糊魯棒優(yōu)化調(diào)度[J];中國電機工程學(xué)報;2014年28期

6 彭春華;謝鵬;陳臣;;大規(guī)模光伏電站接入電網(wǎng)可調(diào)節(jié)魯棒優(yōu)化調(diào)度[J];中國電機工程學(xué)報;2014年25期

7 向月;劉俊勇;魏震波;曹銀利;江東林;馮艾;;考慮可再生能源出力不確定性的微電網(wǎng)能量優(yōu)化魯棒模型[J];中國電機工程學(xué)報;2014年19期

8 梁偉;靳小龍;穆云飛;賈宏杰;王明深;王楠;;含微網(wǎng)及電動汽車的主動配電網(wǎng)供電恢復(fù)策略[J];電力系統(tǒng)及其自動化學(xué)報;2014年06期

9 徐秋實;鄧長虹;趙維興;何俊;吳之奎;;含風(fēng)電電力系統(tǒng)的多場景魯棒調(diào)度方法[J];電網(wǎng)技術(shù);2014年03期

10 張建華;于雷;劉念;肖銳;;含風(fēng)/光/柴/蓄及海水淡化負(fù)荷的微電網(wǎng)容量優(yōu)化配置[J];電工技術(shù)學(xué)報;2014年02期

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