本文選題：需求響應 + 樓宇集群能量系統(tǒng)�。� 參考：《上海電力學院》2017年碩士論文

【摘要】：隨著各種分布式電源和新型用電設備的日益推廣以及電力用戶對需求個性化要求的提升,智能用電的理念及其技術發(fā)展體系應運而生。在該背景下,高級量測和通信系統(tǒng)與智能負荷調控技術的日漸發(fā)展和完善,驅動了以雙向互動智能高效用能為目標的需求響應技術的應用和發(fā)展。為獲得經(jīng)濟、環(huán)境效益的同時提升電能服務質量,研究用電行為并主動整合用戶側資源、優(yōu)化用能調度己成為一項積極而有效的措施。本文首先構建了可實現(xiàn)集群內部能源的互濟、儲用、控制及信息交互的樓宇集群能量管理系統(tǒng)。然后基于分時電價機制和系統(tǒng)內可控元件的功耗模型,提出了一種電網(wǎng)友好型樓宇集群能量優(yōu)化調度策略。以多形式儲能、冷熱電聯(lián)供系統(tǒng)(CCHP)、制冷機組等可控元件為控制目標,同時考慮系統(tǒng)各類約束條件建立了樓宇集群能量協(xié)同優(yōu)化調度模型。在分時電價機制下,以一天運行成本最低為目標,利用機會約束規(guī)劃在處理隨機變量方面的優(yōu)勢,建立了計及風光出力不確定性的樓宇集群能量系統(tǒng)(BCES)經(jīng)濟優(yōu)化調度模型。在LINGO語言環(huán)境下編寫了相應程序,并對模型求最優(yōu)解。算例結果表明通過優(yōu)化求解獲得的BCES中各單元的出力,可以較好的利用多形式儲能系統(tǒng),引導BCES對主網(wǎng)的削峰填谷的同時也有效地提高了自身的經(jīng)濟效益。然后,本文提出了一種基于用戶行為學的家庭日負荷曲線自下向上精細預測模型。在分析影響居民用電行為因素的基礎上,通過非齊次馬爾科夫鏈建立用戶狀態(tài)轉移矩陣并求取家庭中居民所處的狀態(tài);將居民活動與相應電器狀態(tài)關聯(lián),分別建立電器開啟及其使用持續(xù)時長的聯(lián)合概率分布函數(shù);對居民家庭中常用電器進行建模,并基于序貫抽樣法可進行不同日類型、氣象數(shù)據(jù)、家庭人數(shù)下的居民日負荷曲線預測。算例仿真的結果表明負荷曲線預測精度較高,驗證了該模型的有效性。最后,本文對電力用戶側的需求響應行為展開研究。為了揭示用戶用電量對電價、氣象、日類型等相關變化因素的響應程度,提出了一種需求響應綜合模型。該模型實現(xiàn)了用戶在分時電價下的需求響應行為規(guī)律的模擬,可為電力公司制定需求側管理策略提供基礎性指導。
[Abstract]:With the increasing promotion of various distributed power sources and new power equipment and the improvement of the demand individuation requirements of power users, the concept of intelligent power consumption and its technological development system have emerged as the times require. Under this background, the development and perfection of advanced measurement and communication system and intelligent load control technology drive the application and development of demand response technology which aims at two-way interactive intelligence and high utility. In order to achieve economic and environmental benefits and improve the quality of power service, it has become an active and effective measure to study the power consumption behavior and actively integrate the resources of the user side and optimize the energy use scheduling. In this paper, a building cluster energy management system which can realize the mutual aid, storage, control and information interaction of energy in the cluster is constructed. Then, based on the time-sharing pricing mechanism and the power consumption model of controllable components in the system, a grid friendly building cluster energy optimal scheduling strategy is proposed. Taking the controlled elements such as multi-form energy storage, combined cooling and heat supply system, refrigeration unit and so on, as the control target, and considering all kinds of constraints of the system, a building cluster energy cooperative optimal scheduling model is established. Under the time-sharing pricing mechanism, taking the lowest daily operating cost as the goal, and taking advantage of the advantage of opportunistic constrained programming in dealing with random variables, an economic optimal scheduling model of building cluster energy system (BCES) considering the uncertainty of wind power is established. The corresponding program is written in LINGO language environment, and the optimal solution of the model is obtained. The result of example shows that the output force of each unit in BCES can be obtained by optimization, which can make good use of multi-form energy storage system, and guide BCES to cut the peak and fill the valley of the main network, at the same time, it can effectively improve the economic benefit of itself. Then, this paper presents a fine forecast model of family daily load curve from bottom to bottom based on user behavior. Based on the analysis of the factors influencing the residents' electricity consumption behavior, the user state transfer matrix is established through the non-homogeneous Markov chain, and the state of the residents in the family is obtained, and the residents' activities are correlated with the corresponding electrical appliance states. Establishing the joint probability distribution function of the electric appliance opening and the duration of using, modeling the electrical appliances commonly used in the household, and based on the sequential sampling method can carry out the different types of day, meteorological data, Forecast of daily load curve under household size. The simulation results show that the accuracy of load curve forecasting is high, and the validity of the model is verified. Finally, the demand response behavior of power user side is studied in this paper. In order to reveal the response degree of electricity consumption to electricity price, weather, day type and other related factors, a comprehensive model of demand response is proposed. The model can simulate the demand response behavior of users under time-sharing price and can provide basic guidance for power companies to formulate demand-side management strategy.
【學位授予單位】：上海電力學院
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM73

【參考文獻】

相關期刊論文 前10條

1 王劍曉;鐘海旺;夏清;楊勝春;;基于成本—效益分析的溫控負荷需求響應模型與方法[J];電力系統(tǒng)自動化;2016年05期

2 李志偉;趙書強;劉應梅;;電動汽車分布式儲能控制策略及應用[J];電網(wǎng)技術;2016年02期

3 徐青山;楊辰星;顏慶國;;計及規(guī)�；照{熱平衡慣性的電力負荷日前削峰策略[J];電網(wǎng)技術;2016年01期

4 楊永標;顏慶國;徐石明;肖文舉;薛銘楓;;公共樓宇空調負荷參與電網(wǎng)虛擬調峰的思考[J];電力系統(tǒng)自動化;2015年17期

5 李天陽;趙興旺;肖文舉;;面向峰谷平衡的商業(yè)樓宇空調負荷調控技術[J];電力系統(tǒng)自動化;2015年17期

6 范松麗;艾芊;賀興;;基于機會約束規(guī)劃的虛擬電廠調度風險分析[J];中國電機工程學報;2015年16期

7 熊焰;吳杰康;王強;毛曉明;;風光氣儲互補發(fā)電的冷熱電聯(lián)供優(yōu)化協(xié)調模型及求解方法[J];中國電機工程學報;2015年14期

8 舒大松;黃摯雄;李軍葉;李志勇;;基于削峰填谷的微電網(wǎng)并網(wǎng)運行的優(yōu)化調度[J];中南大學學報(自然科學版);2015年06期

9 蘇粟;蔣小超;王瑋;姜久春;V.G.AGELIDIS;耿婧;;計及電動汽車和光伏—儲能的微網(wǎng)能量優(yōu)化管理[J];電力系統(tǒng)自動化;2015年09期

10 毛曉明;陳深;吳杰康;郭壯志;;分時電價機制下含蓄電池微網(wǎng)的優(yōu)化調度[J];電網(wǎng)技術;2015年05期

相關碩士學位論文 前5條

1 牛貞貞;典型電力用戶需求響應分析研究[D];鄭州大學;2015年

2 李娜;可控負荷提供系統(tǒng)備用的機制研究與容量評估[D];山東大學;2013年

3 安u&;主動負荷系統(tǒng)需求響應行為特征分析[D];華北電力大學;2013年

4 萬術來;基于改進粒子群算法的微網(wǎng)環(huán)保經(jīng)濟運行的優(yōu)化[D];華南理工大學;2012年

5 張師玲;基于RBF神經(jīng)網(wǎng)絡與模糊控制的電力系統(tǒng)短期負荷預測[D];江蘇大學;2010年

，

本文編號：1946449