本文選題：需求側(cè)管理 + 峰谷分時(shí)電價(jià)　； 參考：《天津大學(xué)》2014年碩士論文

【摘要】：峰谷分時(shí)電價(jià)(Time of use pricing,簡稱TOU)是電力需求側(cè)管理(Demand Side Management,簡稱DSM)中一項(xiàng)非常重要的措施。依據(jù)原始負(fù)荷大小情況,對(duì)不同用電時(shí)段制定不同的電價(jià),以利用電價(jià)在電力市場中的經(jīng)濟(jì)引導(dǎo)作用,調(diào)節(jié)電力用戶的用電行為,改變負(fù)荷的分布情況,實(shí)現(xiàn)削峰填谷、節(jié)能減排的作用,更符合國家可持續(xù)發(fā)展的大政方針。從而解決高峰時(shí)段的電力缺口,有效緩解了供電方和用電方之間的矛盾,同時(shí)為雙方帶來效益,實(shí)現(xiàn)雙贏的局面。本文對(duì)國內(nèi)外關(guān)于需求側(cè)管理峰谷分時(shí)電價(jià)的研究進(jìn)行分析,發(fā)現(xiàn)分時(shí)電價(jià)的研究中仍存在著問題。以往在制定分時(shí)電價(jià)的過程中,往往過于側(cè)重削峰填谷效果而忽略了不同電價(jià)對(duì)于用戶的影響,忽略了用戶的接受程度及其對(duì)分時(shí)電價(jià)實(shí)施效果的影響,使得優(yōu)化結(jié)果準(zhǔn)確度欠佳。對(duì)此,本文基于智能算法建立了一套從時(shí)段劃分到各時(shí)段電價(jià)制定都綜合考慮的多目標(biāo)分時(shí)電價(jià)遞進(jìn)優(yōu)化方案,綜合考慮各方面因素對(duì)分時(shí)電價(jià)進(jìn)行制定和優(yōu)化。本文利用聚類分析的方法進(jìn)行時(shí)段劃分,以使各時(shí)段之間有更大的區(qū)分度,使劃分結(jié)果更具科學(xué)性。同時(shí),采用帶有精英策略的快速非支配遺傳算法,對(duì)峰谷分時(shí)電價(jià)的多個(gè)目標(biāo)同時(shí)優(yōu)化,以得到平衡多個(gè)目標(biāo)的Pareto最優(yōu)解集,進(jìn)而利用多屬性決策原理選擇出具有更高綜合滿意度的最優(yōu)折衷解。在此基礎(chǔ)上,本文綜合考慮實(shí)施分時(shí)電價(jià)后用戶對(duì)于電價(jià)方案的滿意程度和接受程度對(duì)于實(shí)施效果的影響,提出了對(duì)峰谷分時(shí)電價(jià)的遞進(jìn)優(yōu)化策略,對(duì)用戶響應(yīng)曲線和負(fù)荷曲線進(jìn)行遞進(jìn)優(yōu)化。對(duì)響應(yīng)曲線進(jìn)行遞進(jìn)修正,以更準(zhǔn)確地預(yù)測實(shí)施分時(shí)電價(jià)后的用戶負(fù)荷曲線;同時(shí),用優(yōu)化后的負(fù)荷曲線代替原始的負(fù)荷曲線進(jìn)行遞進(jìn)優(yōu)化,以進(jìn)一步削峰填谷,探索最優(yōu)的削峰填谷效果。對(duì)于分時(shí)電價(jià)實(shí)施過程中用戶接受程度的考慮以及對(duì)分時(shí)電價(jià)進(jìn)一步遞進(jìn)優(yōu)化是在需求側(cè)管理領(lǐng)域的創(chuàng)新應(yīng)用,對(duì)于峰谷分時(shí)電價(jià)的普及及優(yōu)化具有重要意義。通過仿真分析,驗(yàn)證該優(yōu)化方法在削峰填谷上的顯著效果的同時(shí),也證實(shí)了遞進(jìn)策略通過效地實(shí)現(xiàn)了負(fù)荷的進(jìn)一步優(yōu)化。
[Abstract]:Time of use pricing (TOU) is a very important measure in DSM (demand and Side Management).According to the size of the original load, different electricity prices are made for different periods of time, in order to make use of the economic leading role of electricity price in the electricity market, to adjust the power consumption behavior of the power users, to change the distribution of the load, and to realize cutting the peak and filling the valley.The role of energy conservation and emission reduction, more in line with the national policy for sustainable development.In order to solve the power gap during the peak period, effectively alleviate the contradiction between the power supply side and the power side, at the same time bring benefits to both sides, and achieve a win-win situation.In this paper, the domestic and foreign research on demand side management peak-valley time-sharing price is analyzed, and it is found that there are still some problems in the study of time-sharing price.In the past, in the process of making time-sharing electricity price, the effect of peak cutting and valley filling was often emphasized too much, and the influence of different electricity price on the user, the acceptance degree of the user and the effect on the implementation effect of time-sharing electricity price were ignored.The accuracy of the optimization results is poor.In this paper, based on the intelligent algorithm, a set of multi-objective time-sharing price progressive optimization scheme is established, from the time division to the pricing formulation of each time period, which considers all factors to formulate and optimize the time-sharing electricity price.In this paper, the method of clustering analysis is used to divide the time interval, so that there is a greater degree of distinction between the different periods and the result of the division is more scientific.At the same time, a fast non-dominated genetic algorithm with elitist strategy is used to optimize multiple targets of peak-valley time-sharing electricity price at the same time, so as to obtain the Pareto optimal solution set that balances multiple targets.Then the optimal compromise solution with higher comprehensive satisfaction degree is selected by using the principle of multiple attribute decision making.On this basis, this paper considers the effect of customer satisfaction and acceptance on the effect of electricity price scheme after the implementation of time-sharing price, and puts forward a progressive optimization strategy for peak and valley time-sharing electricity price.The user response curve and load curve are progressively optimized.The response curve is modified step by step in order to predict the user load curve more accurately, and the optimized load curve is used instead of the original load curve to further cut the peak and fill the valley.To explore the optimal peak cutting and filling effect.It is an innovative application in the field of demand-side management to consider the user acceptance degree in the implementation process of time-sharing electricity price and to further optimize the time-sharing electricity price, which is of great significance to the popularization and optimization of peak and valley time-sharing price.The simulation results show that the proposed optimization method has significant effect on peak cutting and valley filling, and it also proves that the progressive strategy can achieve further optimization of load effectively.
【學(xué)位授予單位】：天津大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：F426.61

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 武漢美;鄒云;;考慮CDM的分時(shí)電價(jià)建模與分析[J];控制工程;2011年06期

2 譚忠富;王綿斌;乞建勛;侯建朝;李雪;;峰谷分時(shí)電價(jià)優(yōu)化模型及其模糊求解方法[J];系統(tǒng)工程理論與實(shí)踐;2008年09期

3 唐捷;任震;高志華;陳亮;劉奇;;峰谷分時(shí)電價(jià)的成本效益分析模型及其應(yīng)用[J];電網(wǎng)技術(shù);2007年06期

4 陶莉;;國外分時(shí)電價(jià)政策簡介及探究[J];江蘇電機(jī)工程;2007年01期

5 任玉瓏;李俊;陽忠明;季玉華;;基于博弈控制的分時(shí)電價(jià)研究[J];科技管理研究;2006年02期

6 丁偉,袁家海,胡兆光;基于用戶價(jià)格響應(yīng)和滿意度的峰谷分時(shí)電價(jià)決策模型[J];電力系統(tǒng)自動(dòng)化;2005年20期

7 劉昌,李繼傳,姚建剛,劉真,房華,董繼征;峰谷分時(shí)電價(jià)的分析與建模[J];電力需求側(cè)管理;2005年05期

8 劉觀起,張建,劉瀚;基于用戶對(duì)電價(jià)反應(yīng)曲線的分時(shí)電價(jià)的研究[J];華北電力大學(xué)學(xué)報(bào);2005年03期

9 趙娟,譚忠富,李強(qiáng);我國峰谷分時(shí)電價(jià)的狀況分析[J];現(xiàn)代電力;2005年02期

10 段登偉,劉俊勇,吳集光;計(jì)及風(fēng)險(xiǎn)的配電公司最優(yōu)分時(shí)零售電價(jià)模型[J];電力系統(tǒng)自動(dòng)化;2005年03期

相關(guān)博士學(xué)位論文 前1條

1 王梅霖;電力需求側(cè)管理研究[D];北京交通大學(xué);2011年

相關(guān)碩士學(xué)位論文 前1條

1 羅伶;基于模糊c均值聚類的分類分時(shí)電價(jià)研究[D];山東大學(xué);2013年

，

本文編號(hào)：1755107