本文關(guān)鍵詞：考慮不確定性的多能源微電網(wǎng)優(yōu)化配置與協(xié)調(diào)控制　出處：《太原理工大學(xué)》2017年碩士論文　論文類(lèi)型：學(xué)位論文

  更多相關(guān)文章： 不確定性 多能源 微電網(wǎng) 優(yōu)化配置 協(xié)調(diào)控制

【摘要】：不可再生能源的日益衰竭與供電需求的逐漸增長(zhǎng)使得供求矛盾不斷加深,但同也促使了可再生能源發(fā)電技術(shù)的發(fā)展。特別是對(duì)于難以與大電網(wǎng)互聯(lián)的海島和偏遠(yuǎn)山區(qū),建立含多種可再生能源發(fā)電設(shè)備的微電網(wǎng)已成為解決無(wú)電戶(hù)的重要方式之一。全世界各國(guó)逐漸開(kāi)始重視微電網(wǎng)的研究與發(fā)展,微電網(wǎng)逐漸成為電力工程和能源領(lǐng)域的前沿技術(shù)和研究焦點(diǎn)。大量學(xué)者和研究機(jī)構(gòu)針對(duì)微電網(wǎng)的規(guī)劃與控制進(jìn)行了研究。然而,由于微電網(wǎng)中風(fēng)機(jī)、光伏以及負(fù)荷均具有一定的不確定性,這給微電網(wǎng)的規(guī)劃和調(diào)度帶來(lái)了新的挑戰(zhàn)。因此,本文針對(duì)微電網(wǎng)中不同可再生能源的不確定性,并圍繞著電源容量規(guī)劃和能量?jī)?yōu)化調(diào)度這兩大問(wèn)題進(jìn)行研究,具有重要的理論價(jià)值和實(shí)際意義。由于微電網(wǎng)需要具備獨(dú)立運(yùn)行的能力,故對(duì)電源容量配置和能量?jī)?yōu)化調(diào)度提出了很高的要求。因此,本文首先分析了風(fēng)力發(fā)電機(jī)和光伏陣列的風(fēng)速和光照強(qiáng)度的概率分布情況,確定了擬合風(fēng)速和光照強(qiáng)度的Weibull函數(shù)與Beta函數(shù),采用了基于風(fēng)速和光照強(qiáng)度概率特性的隨機(jī)抽樣方法。然后使用Matlab建立了風(fēng)/光/儲(chǔ)微電網(wǎng)系統(tǒng)的電源容量?jī)?yōu)化配置模型,并采用改進(jìn)的粒子群算法進(jìn)行求解,大量的仿真算例驗(yàn)證了模型的可行性,得到了不同配置要求下的最優(yōu)解,并對(duì)各項(xiàng)指標(biāo)對(duì)電源容量配置結(jié)果的影響進(jìn)行了靈敏度分析。針對(duì)微電網(wǎng)的協(xié)調(diào)控制,本文首先闡述了電壓源型換流器的控制方式,接著針對(duì)基于換流器并網(wǎng)的風(fēng)/光/儲(chǔ)微電網(wǎng)的能量?jī)?yōu)化控制,提出了微電網(wǎng)內(nèi)多種能源的協(xié)調(diào)優(yōu)化策略,并采用機(jī)會(huì)約束規(guī)劃得到置信區(qū)間下的最優(yōu)解。其中,優(yōu)化模型以全天購(gòu)電成本最小為目標(biāo)函數(shù),同時(shí)考慮支路功率概率約束、節(jié)點(diǎn)電壓概率約束、功率平衡約束與各時(shí)段內(nèi)儲(chǔ)能單元水平變化量約束,使用Matlab建立數(shù)學(xué)模型,并采用分段編碼分段操作方式的帶精英保留策略的改進(jìn)遺傳算法求解。最后,文章針對(duì)三相不平衡問(wèn)題,簡(jiǎn)述了風(fēng)機(jī)接入微電網(wǎng)中電壓源逆變器的控制作用,分析了一種基于負(fù)序電壓前饋補(bǔ)償?shù)目刂撇呗?達(dá)到抑制諧波的效果,并使用Matlab進(jìn)行建模仿真。
[Abstract]:Non renewable energy supply and demand increasingly failure gradually growth makes the contradiction between supply and demand continues to deepen, but also contributed to the development of renewable energy technologies. Especially for difficult and large power grid interconnected islands and remote mountainous areas, the establishment of a micro grid containing a variety of renewable energy power generation equipment has become one of the important ways to solve the households without electricity all countries in the world gradually began to pay attention to the research and development of micro grid, microgrid has become the electric power engineering and energy field of cutting-edge technology and research focus. A large number of scholars and research institutions for the study of micro grid planning and control. However, due to the micro grid PV and load stroke, showed some uncertainty and this brings new challenges to the planning and scheduling of the micro grid. Therefore, according to the different renewable energy micro grid uncertainties in and around electricity The source of capacity planning and energy optimization of scheduling the two big problems, it has important theoretical value and practical significance. The micro grid need to be able to run independently, it has put forward higher request to the power supply capacity configuration and energy optimization scheduling. Therefore, the probability distribution of wind speed and light in this paper firstly analyzed the wind power generator and the light intensity of photovoltaic array, determine the Weibull function and Beta function fitting of wind speed and light intensity, the wind speed and intensity of light based on the probability characteristics of the random sampling method. Then Matlab is used to create the wind / light / energy storage power system power supply capacity optimization model, and solved by using the improved the particle swarm algorithm, a large number of simulation examples to verify the feasibility of the model, the optimal configuration requirements under different solutions can be obtained, and the indicators of power supply capacity allocation effect into The sensitivity analysis for coordinated control of the micro grid, this paper describes the control method of voltage source converter, then the inverter grid connected wind / light / storage based on micro grid energy optimization control, put forward the micro coordination and optimization strategy of various energy sources in the grid, and get the optimal confidence constraint programming interval solutions under the opportunity. Among them, all day long optimization model with the minimum purchase cost as the objective function, considering the power of probabilistic constraints, node voltage probabilistic constraints, power balance constraint and the time variation of the storage unit level constraints, using Matlab to establish mathematical model and using elitist sub encoding gradient operation the improved genetic algorithm for solving strategies. Finally, aiming at the three-phase imbalance, the control effect of fan access voltage source inverter in microgrid, based on the analysis of a The control strategy of negative sequence voltage feedforward compensation achieves the effect of restraining harmonic, and uses Matlab for modeling and simulation.

【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(lèi)號(hào)】：TM727

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 陳麗;張晉國(guó);蘇海鋒;;考慮并網(wǎng)光伏電源出力時(shí)序特性的配電網(wǎng)無(wú)功規(guī)劃[J];電工技術(shù)學(xué)報(bào);2014年12期

2 程曉悅;盧錦玲;;考慮不確定性的分布式電源多目標(biāo)優(yōu)化配置[J];電力科學(xué)與工程;2014年11期

3 饒順斌;陳宇;;考慮負(fù)荷隨機(jī)性的含DG多目標(biāo)配電網(wǎng)重構(gòu)[J];電氣應(yīng)用;2014年21期

4 張曦;康重慶;張寧;黃越輝;劉純;徐健飛;;太陽(yáng)能光伏發(fā)電的中長(zhǎng)期隨機(jī)特性分析[J];電力系統(tǒng)自動(dòng)化;2014年06期

5 何俊;鄧長(zhǎng)虹;徐秋實(shí);劉翠琳;潘華;;基于等可信容量的風(fēng)光儲(chǔ)電源優(yōu)化配置方法[J];電網(wǎng)技術(shù);2013年12期

6 李登峰;謝開(kāi)貴;胡博;陳濤;萬(wàn)凌云;;基于凈效益最大化的微電網(wǎng)電源優(yōu)化配置[J];電力系統(tǒng)保護(hù)與控制;2013年20期

7 周松林;茆美琴;蘇建徽;;考慮風(fēng)力發(fā)電隨機(jī)性的微電網(wǎng)潮流預(yù)測(cè)[J];中國(guó)電機(jī)工程學(xué)報(bào);2013年22期

8 許昌;李e，

本文編號(hào)：1429066