【摘要】：近些年來，隨著化石能源的枯竭，以風(fēng)能和太陽能為主的新能源得到大力的發(fā)展。風(fēng)能和太陽能不僅資源豐富用之不竭，而且對無污染。但是，風(fēng)能和太陽能具有隨機(jī)性、間歇性和不確定性，導(dǎo)致風(fēng)光出力具有波動(dòng)性。隨著風(fēng)電和光伏發(fā)電在電網(wǎng)中所占的比例逐漸增加，并網(wǎng)之后，勢必會(huì)嚴(yán)重影響電網(wǎng)的發(fā)展。為了解決新能源接入帶來的問題，把儲(chǔ)能裝置加入風(fēng)電場和光伏電站形成風(fēng)光儲(chǔ)聯(lián)合發(fā)電系統(tǒng)是解決可再生能源發(fā)展的重要途徑。為了實(shí)現(xiàn)新能源的友好接入，風(fēng)光儲(chǔ)聯(lián)合發(fā)電系統(tǒng)必須具有可調(diào)度性，所以，本文提前一天對以蓄電池為主的儲(chǔ)能裝置進(jìn)行了優(yōu)化控制研究。具體研究內(nèi)容如下： 1、首先，對風(fēng)光儲(chǔ)聯(lián)合發(fā)電系統(tǒng)的基本結(jié)構(gòu)和工作原理進(jìn)行了介紹，了解了整個(gè)系統(tǒng)工作原理和過程。重點(diǎn)研究了以蓄電池為代表的儲(chǔ)能系統(tǒng)的工作特性，包括荷電狀態(tài)、放電深度以及每個(gè)時(shí)段電量的推導(dǎo)公式，這些對儲(chǔ)能的控制和壽命有重要的影響。其次，介紹了風(fēng)力發(fā)電和光伏發(fā)電的預(yù)測方法，并分析了風(fēng)光預(yù)測存在誤差，以及現(xiàn)有文獻(xiàn)中對預(yù)測誤差的處理。 2、針對風(fēng)光預(yù)測出力的誤差具有隨機(jī)性，本文采用機(jī)會(huì)約束規(guī)劃對儲(chǔ)能進(jìn)行優(yōu)化控制。該方法以儲(chǔ)能裝置的功率和電量為約束條件，，以風(fēng)光儲(chǔ)總出力曲線與給定的計(jì)劃出力曲線的余弦相似度為目標(biāo)函數(shù)，使用基于隨機(jī)模擬的粒子群算法求解，得到兩條曲線最接近時(shí)對應(yīng)的儲(chǔ)能充放電功率。算例分析表明，所提出的儲(chǔ)能優(yōu)化控制策略能夠使風(fēng)光儲(chǔ)發(fā)電系統(tǒng)的總出力跟蹤計(jì)劃出力曲線。 3、針對風(fēng)光預(yù)測出力的誤差具有模糊性，本文采用模糊相關(guān)機(jī)會(huì)規(guī)劃對儲(chǔ)能進(jìn)行優(yōu)化控制。該方法以儲(chǔ)能裝置的功率和電量為約束條件，每個(gè)時(shí)段的匹配程度用可信度表示，以一天內(nèi)96個(gè)時(shí)段總的可信度均值最大為目標(biāo)，使用基于模糊模擬的遺傳算法求解，得到可信度均值最大時(shí)不同時(shí)段對應(yīng)的儲(chǔ)能充放電功率。最后，算例表明，所提出的儲(chǔ)能優(yōu)化控制策略能夠使風(fēng)光儲(chǔ)聯(lián)合發(fā)電系統(tǒng)總出力最大程度的跟蹤計(jì)劃出力曲線。
[Abstract]:In recent years, with the depletion of fossil energy, new energy, mainly wind energy and solar energy, has been greatly developed. Wind and solar energy are not only rich in resources, but also non-polluting. However, wind and solar are random, intermittent and uncertain, resulting in volatility of wind power. With the increasing proportion of wind power and photovoltaic power generation in power grid, the development of power grid will be seriously affected after grid connection. In order to solve the problem caused by new energy access, it is an important way to solve the problem of renewable energy development by adding energy storage equipment to wind farm and photovoltaic power station to form wind energy storage combined generation system. In order to realize the friendly connection of new energy, the combined generation system of solar energy storage and storage must be schedulable. Therefore, the optimal control of the energy storage device based on storage battery is studied one day in advance in this paper. The main contents of this paper are as follows: 1. Firstly, the basic structure and working principle of the wind energy storage combined generation system are introduced, and the working principle and process of the whole system are understood. The working characteristics of the energy storage system represented by the storage battery are mainly studied, including the charge state, discharge depth and the formula of the electric quantity in each period, which have an important influence on the control and life of the storage energy. Secondly, the forecasting methods of wind power generation and photovoltaic power generation are introduced. In this paper, the opportunity-constrained programming is used to optimize the control of energy storage. In this method, the power and electricity of the energy storage device are taken as the constraint conditions, and the cosine similarity between the total wind force curve and the given planned force curve is taken as the objective function, and the particle swarm optimization algorithm based on stochastic simulation is used to solve the problem. The charge and discharge power of energy storage is obtained when the two curves are closest to each other. The analysis of an example shows that the proposed optimal control strategy of energy storage can make the total output of the wind energy storage power generation system track the planned output curve. 3. The error of forecasting the wind energy is fuzzy. In this paper, fuzzy correlation opportunity programming is used to optimize the control of energy storage. In this method, the power and electricity of the energy storage device are taken as the constraint conditions, the matching degree of each time period is expressed by the confidence level, and the maximum mean of the total reliability of the 96 periods of the day is taken as the goal, and the genetic algorithm based on fuzzy simulation is used to solve the problem. The energy storage charge and discharge power corresponding to different periods of time is obtained when the confidence average is maximum. Finally, an example shows that the proposed optimal control strategy of energy storage can make the maximum total output of the wind energy storage combined generation system to track the planned output curve.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TM61

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