本文選題：微電網(wǎng) + 鋰電池運(yùn)行成本�。� 參考：《太原理工大學(xué)》2017年碩士論文

【摘要】：近年來,新能源發(fā)電發(fā)展迅速,人們通過建立微電網(wǎng)優(yōu)化調(diào)度方法來實(shí)現(xiàn)微網(wǎng)經(jīng)濟(jì)運(yùn)行和微網(wǎng)內(nèi)各可控單元的功率優(yōu)化分配。然而,風(fēng)、光等新能源出力具有波動(dòng)性,基于歷史數(shù)據(jù)的負(fù)荷預(yù)測也存在偏差,對(duì)單一時(shí)間尺度下的微電網(wǎng)優(yōu)化調(diào)度策略而言,這些不確定性因素易造成微網(wǎng)調(diào)度計(jì)劃備用不足或運(yùn)行經(jīng)濟(jì)性變差等后果。所以,亟需建立考慮更為全面的微電網(wǎng)優(yōu)化調(diào)度策略。本文首先介紹了光伏、鋰電池、超級(jí)電容和燃料電池等分布式單元的特點(diǎn)、并網(wǎng)結(jié)構(gòu)、工作原理與運(yùn)行特性,總結(jié)了各分布式單元在微網(wǎng)層面中的處理方式;推導(dǎo)出鋰電池運(yùn)行成本函數(shù),建立了鋰電池和燃料電池的運(yùn)行、維護(hù)成本數(shù)學(xué)模型;針對(duì)主從結(jié)構(gòu)的微電網(wǎng)分別研究了并網(wǎng)和離網(wǎng)運(yùn)行狀態(tài)主控分布式電源的控制原理和控制方法,并且搭建了相應(yīng)Simulink仿真模型。第二,研究了雙層優(yōu)化的數(shù)學(xué)模型和雙層優(yōu)化思想在微電網(wǎng)中的應(yīng)用,建立基于負(fù)荷向量基的綜合負(fù)荷模型,引入了魯棒懲罰成本,考慮光伏和負(fù)荷功率預(yù)測值偏差的影響,建立了一種基于魯棒性的微電網(wǎng)雙層優(yōu)化調(diào)度模型,使用LINGO軟件編程完成了算例仿真,進(jìn)行了結(jié)果分析,并分別分析了預(yù)測誤差因數(shù)和需求側(cè)響應(yīng)模型對(duì)結(jié)果的影響。第三,以交流微電網(wǎng)為研究對(duì)象,提出了普適性的包含日前和日內(nèi)兩個(gè)階段的多時(shí)間尺度微電網(wǎng)能量管理優(yōu)化調(diào)度方案,將鋰電池和超級(jí)電容不置于同一時(shí)間尺度下調(diào)用。在日前階段,應(yīng)用推出的鋰電池運(yùn)行成本函數(shù),根據(jù)日前光伏預(yù)測與負(fù)荷預(yù)測,以總運(yùn)行成本為目標(biāo)函數(shù)進(jìn)行功率優(yōu)化分配,考慮了分時(shí)電價(jià)和光伏運(yùn)行于MPPT和輸出功率可控兩種發(fā)電狀態(tài);在日內(nèi)調(diào)度階段,從經(jīng)濟(jì)性角度出發(fā),根據(jù)功率波動(dòng)調(diào)度分布式單元的運(yùn)行,并且引入附加成本便于總運(yùn)行成本的準(zhǔn)確計(jì)算,便于進(jìn)行幾種多時(shí)間尺度優(yōu)化調(diào)度方案的結(jié)果對(duì)比。并通過仿真分析驗(yàn)證了所提優(yōu)化調(diào)度策略的合理性。根據(jù)本文第二部分建立的考慮魯棒性的經(jīng)濟(jì)優(yōu)化調(diào)度模型和第三部分建立的多時(shí)間尺度優(yōu)化調(diào)度模型,對(duì)考慮不確定性的微網(wǎng)優(yōu)化調(diào)度方法進(jìn)行了對(duì)比分析。并且針對(duì)第三部分建立的調(diào)度策略,基于微電網(wǎng)實(shí)際運(yùn)行需要,分別對(duì)日前和日內(nèi)階段進(jìn)行了改進(jìn)。最后,介紹了微電網(wǎng)實(shí)驗(yàn)室的物理結(jié)構(gòu)、通訊架構(gòu)和能量管理系統(tǒng);基于第三部分建立的計(jì)及實(shí)驗(yàn)需求的改進(jìn)的微電網(wǎng)多時(shí)間尺度經(jīng)濟(jì)優(yōu)化調(diào)度策略,應(yīng)用Qt Creator平臺(tái)編寫程序,完善能量管理系統(tǒng)中的控制功能,并且基于典型場景法實(shí)現(xiàn)微電網(wǎng)優(yōu)化調(diào)度運(yùn)行實(shí)驗(yàn),實(shí)驗(yàn)結(jié)果驗(yàn)證了本文所提微電網(wǎng)優(yōu)化調(diào)度方案的有效性和可行性。
[Abstract]:In recent years, the rapid development of new energy power generation, people through the establishment of micro grid scheduling optimization method to realize the power distribution of each control unit economic operation of micro grid and micro network optimization. However, the wind, light and other new energy output volatility, load forecasting based on historical data also exists deviation, on a single time scale. Micro grid optimization scheduling strategy, these uncertainties caused by micro grid scheduling or lack of spare economy poor consequences. Therefore, considering the need to establish a more comprehensive micro grid scheduling strategy. This paper first introduces the characteristics of photovoltaic, lithium battery, super capacitor and fuel cell distributed unit the grid structure, working principle and operation characteristics, summed up the mode of the distributed processing unit in the micro level in the network; deduced the lithium battery operation cost function, a lithium battery and fuel cell The operation and maintenance cost mathematical model; for microgrid master-slave structure were studied from the grid and control principle and control method of the main control network running state of distributed power, and set up the corresponding Simulink simulation model. Second, the application of mathematical model of bilevel optimization and double optimization in micro grid, the establishment of a comprehensive load vector based model based on robust penalty cost, taking into account the influence of PV and load forecast value deviation, established a double micro grid scheduling model based on robustness, using LINGO software programming to complete the numerical simulation, the results are analyzed, and analyzed the prediction error factor and demand side response influence model to the result. In third, AC micro grid as the research object, put forward two stages of the universality of the day before and the days of the multi time scale micro Optimal scheduling scheme of energy management of power grid, the same time scale lithium batteries and super capacitors not under the call. In the previous stage, the lithium battery operation cost function application introduced, according to the day before the PV prediction and forecasting, with a total operating cost as the objective function of optimal power allocation, considering tou and PV running on the MPPT and the output power of two power controllable state; scheduling in the days of stage, from the perspective of the economy, according to the power fluctuation of distributed scheduling unit operation, and the introduction of additional cost for accurate calculation of total operation cost, easy to compare multiple time scale of several scheduling scheme optimization results and proved. Reasonable optimization scheduling strategy by simulation analysis. According to the second part of this paper is established considering the robustness of the economic dispatch model and the third part of the establishment of the multi time scale advantages Scheduling model, considering the uncertainty of the micro grid optimization scheduling methods are analyzed. And in the third part of the scheduling strategy is established, the actual operation of micro grid based on the need of the day before and days respectively stage is improved. Finally, the physical structure of the micro grid laboratory, communication architecture and energy management system improvement and experiment demand; the third part of the establishment of the micro grid multi time scale economic optimization scheduling strategy based on Creator platform, using Qt written procedures, improve the control function in energy management system, and realize the micro grid scheduling method based on the experimental scenario, the experimental results verify the validity of proposed microgrid optimal scheduling scheme and feasibility.

【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM73

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 陳昊宇;黃順杰;樊志華;方華亮;許沛東;;基于博弈的多微網(wǎng)需求響應(yīng)[J];南方電網(wǎng)技術(shù);2017年02期

2 張程熠;唐雅潔;李永杰;高強(qiáng);江全元;;適用于小樣本的神經(jīng)網(wǎng)絡(luò)光伏預(yù)測方法[J];電力自動(dòng)化設(shè)備;2017年01期

3 劉思;傅旭華;葉承晉;丁嘉涵;馬潤澤;黃民翔;;應(yīng)用聚類分析與非參數(shù)核密度估計(jì)的空間負(fù)荷分布規(guī)律[J];電網(wǎng)技術(shù);2017年02期

4 肖浩;裴瑋;孔力;;基于模型預(yù)測控制的微電網(wǎng)多時(shí)間尺度協(xié)調(diào)優(yōu)化調(diào)度[J];電力系統(tǒng)自動(dòng)化;2016年18期

5 王剛;孫文健;李歧強(qiáng);王魯浩;;基于魯棒后悔度的光儲(chǔ)微網(wǎng)優(yōu)化調(diào)度[J];電網(wǎng)技術(shù);2017年01期

6 郭帥;劉魯嘉;楊萌;艾欣;;計(jì)及可控負(fù)荷的微網(wǎng)自治調(diào)度模型[J];電網(wǎng)技術(shù);2017年01期

7 李建林;馬會(huì)萌;惠東;;儲(chǔ)能技術(shù)融合分布式可再生能源的現(xiàn)狀及發(fā)展趨勢[J];電工技術(shù)學(xué)報(bào);2016年14期

8 竇曉波;徐_藁，

本文編號(hào)：1758297