本文選題：蓄冰空調(diào) + 樓宇分布式能源系統(tǒng)��； 參考：《華南理工大學(xué)》2014年碩士論文

【摘要】：隨著全球經(jīng)濟(jì)快速發(fā)展與化石能源短缺，提高能源利用率和保護(hù)地球環(huán)境問題日益突出。在此背景下，分布式能源系統(tǒng)受到廣泛重視。但分布式能源系統(tǒng)投資很高，須對(duì)各設(shè)備進(jìn)行合理的配置才能發(fā)揮其優(yōu)勢(shì)。此外，很多地區(qū)峰谷差明顯，在用電高峰時(shí)嚴(yán)重缺電，而低谷時(shí)又有大量容量得不到充分利用，嚴(yán)重影響電網(wǎng)的經(jīng)濟(jì)性。蓄冰空調(diào)能利用夜間的廉價(jià)電力制冰，在白天將夜間所制的冰作為冷源釋放冷。因此，建立含蓄冰空調(diào)的樓宇分布式電源系統(tǒng)，可以降低用電成本，具有重大實(shí)際意義。 本文對(duì)廣東某地區(qū)大型樓宇的樓宇能耗以及其冷電負(fù)荷進(jìn)行了調(diào)研，根據(jù)其電負(fù)荷特征，將樓宇分為了負(fù)荷連續(xù)型樓宇和負(fù)荷間斷型樓宇，又根據(jù)負(fù)荷的重要程度，，將負(fù)荷間斷型樓宇細(xì)分為有重要負(fù)荷和無重要負(fù)荷并分別對(duì)這三種樓宇的單位面積耗電、終端能耗以及各季節(jié)典型日的冷電負(fù)荷進(jìn)行了分析。 為實(shí)現(xiàn)樓宇分布式能源系統(tǒng)的經(jīng)濟(jì)運(yùn)行，本文構(gòu)建了含蓄冰空調(diào)的樓宇分布式能源系統(tǒng)雙層優(yōu)化模型。該模型下層為基于混合整數(shù)規(guī)劃算法的優(yōu)化配置模型，上層則粒子群算法尋找系統(tǒng)最優(yōu)設(shè)備配置容量，以增量投資回收期最短為優(yōu)化目標(biāo)進(jìn)行容量?jī)?yōu)化計(jì)算。上層將設(shè)備類型及設(shè)備容量?jī)?yōu)化結(jié)果傳遞給下層，下層通過日運(yùn)行費(fèi)用最小為目標(biāo)進(jìn)行優(yōu)化，再目標(biāo)值作為粒子群算法的適應(yīng)度返回上層，層層進(jìn)化后最終給出最優(yōu)的投資回收期及設(shè)備容量和運(yùn)行策略方案。 運(yùn)用上述模型，在當(dāng)前市場(chǎng)的電價(jià)和天然氣價(jià)的市場(chǎng)條件下，分別對(duì)三種樓宇的樓宇分布式能源系統(tǒng)進(jìn)行優(yōu)化，得到了各典型樓宇含蓄冰空調(diào)的樓宇分布式能源系統(tǒng)容量和運(yùn)行方案。最后分別針對(duì)各典型樓宇，對(duì)比分析了其分布式能源系統(tǒng)優(yōu)化配置方案與不接入含蓄冰空調(diào)的分布式能源系統(tǒng)的常規(guī)分供系統(tǒng)的經(jīng)濟(jì)性，并探討了建筑面積、冷電比和重要負(fù)荷系數(shù)變化時(shí)對(duì)增量投資回收期和分布式能源系統(tǒng)的容量配置產(chǎn)生的影響。研究表明：含蓄冰空調(diào)的樓宇分布式能源系統(tǒng)經(jīng)過合理的優(yōu)化配置和調(diào)度可取得很好的經(jīng)濟(jì)效益，避開用電高峰，提高環(huán)保性。
[Abstract]:With the rapid development of global economy and the shortage of fossil energy, the problems of improving energy efficiency and protecting the earth's environment are becoming increasingly prominent. In this context, distributed energy systems have received extensive attention. But the investment of distributed energy system is very high. In addition, in many areas, the peak and valley difference is obvious, the power consumption peak time is serious lack of electricity, but at the low point, a large number of capacity is not fully utilized, which seriously affects the economy of power grid. Ice storage air conditioning can use the cheap electricity at night to make ice and release the ice made at night as a cold source during the day. Therefore, it is of great practical significance to set up a building distributed power system with ice-implicit air-conditioning, which can reduce the cost of electricity consumption. This paper investigates the energy consumption and cooling load of large buildings in a certain area of Guangdong province. According to the characteristics of power load, the buildings are divided into continuous load building and discontinuous load building, and according to the importance of load. The discontinuous load buildings are divided into two types: important load and no important load. The unit area power consumption, terminal energy consumption and cooling load of typical days in each season are analyzed respectively. In order to realize the economic operation of building distributed energy system, a bilevel optimization model of building distributed energy system is constructed in this paper. The lower layer of the model is an optimal configuration model based on mixed integer programming algorithm. The upper layer particle swarm optimization algorithm is used to find the optimal configuration capacity of the system, and the optimal capacity is calculated with the shortest payback period of incremental investment as the optimization objective. The upper layer transfers the result of equipment type and equipment capacity optimization to the lower layer, the lower layer optimizes through the minimum daily operation cost, and the target value is returned to the upper layer as the fitness of the particle swarm optimization algorithm. After evolution, the optimal investment payback period, equipment capacity and operation strategy are given. Using the above model, under the current market conditions of electricity price and natural gas price, the distributed energy systems of three kinds of buildings are optimized respectively. The distributed energy system capacity and operation scheme of ice-storage air-conditioning system for typical buildings are obtained. Finally, according to the typical buildings, the economy of the distributed energy system optimal allocation scheme and the conventional energy distribution system without ice storage air conditioning is analyzed, and the building area is discussed. The influence of the change of the cooling power ratio and the important load coefficient on the recovery period of the incremental investment and the capacity allocation of the distributed energy system. The results show that the distributed energy system with ice storage air conditioning system can achieve good economic benefits, avoid the peak power consumption and improve the environmental protection through reasonable optimal allocation and scheduling.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TU831

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 ;國(guó)家發(fā)展改革委發(fā)布我國(guó)第一個(gè)《節(jié)能中長(zhǎng)期專項(xiàng)規(guī)劃》——國(guó)家發(fā)展改革委有關(guān)負(fù)責(zé)人答記者問[J];節(jié)能與環(huán)保;2004年11期

2 忻奇峰;冷熱電三聯(lián)供系統(tǒng)在浦東國(guó)際機(jī)場(chǎng)的應(yīng)用[J];電力需求側(cè)管理;2004年05期

3 黃偉;黃民翔;趙學(xué)順;甘德強(qiáng);;基于主從遞階決策模型的TRM評(píng)估[J];電力系統(tǒng)自動(dòng)化;2006年04期

4 耿建;徐帆;姚建國(guó);高宗和;丁恰;楊爭(zhēng)林;程蕓;陳剛;;求解安全約束機(jī)組組合問題的混合整數(shù)規(guī)劃算法性能分析[J];電力系統(tǒng)自動(dòng)化;2009年21期

5 姚偉鋒;趙俊華;文福拴;薛禹勝;辛建波;;基于雙層優(yōu)化的電動(dòng)汽車充放電調(diào)度策略[J];電力系統(tǒng)自動(dòng)化;2012年11期

6 謝國(guó)輝;張粒子;舒雋;蘇濟(jì)歸;;基于分層分枝定界算法的機(jī)組組合[J];電力自動(dòng)化設(shè)備;2009年12期

7 鄭國(guó)耀,李道林,張時(shí)飛;黃浦區(qū)中心醫(yī)院“熱、電、冷”三聯(lián)供工程設(shè)計(jì)及實(shí)踐[J];動(dòng)力工程;1999年03期

8 茍格;整數(shù)規(guī)劃中的割平面法與分枝定界法比較[J];達(dá)縣師范高等�？茖W(xué)校學(xué)報(bào);2005年02期

9 彭宇,彭喜元,劉兆慶;微粒群算法參數(shù)效能的統(tǒng)計(jì)分析[J];電子學(xué)報(bào);2004年02期

10 江億;;我國(guó)建筑節(jié)能戰(zhàn)略研究[J];中國(guó)工程科學(xué);2011年06期

相關(guān)博士學(xué)位論文 前6條

1 劉衍民;粒子群算法的研究及應(yīng)用[D];山東師范大學(xué);2011年

2 劉建華;粒子群算法的基本理論及其改進(jìn)研究[D];中南大學(xué);2009年

3 劉波;計(jì)及分布式電源的電力系統(tǒng)潮流及可靠性與穩(wěn)定性研究[D];上海交通大學(xué);2009年

4 王江江;樓宇級(jí)冷熱電聯(lián)供系統(tǒng)優(yōu)化及多屬性綜合評(píng)價(jià)方法研究[D];華北電力大學(xué);2012年

5 黃平;粒子群算法改進(jìn)及其在電力系統(tǒng)的應(yīng)用[D];華南理工大學(xué);2012年

6 于波;微網(wǎng)與儲(chǔ)能系統(tǒng)容量?jī)?yōu)化規(guī)劃[D];天津大學(xué);2012年

本文編號(hào)：2065431