本文關(guān)鍵詞： 抽水蓄能 光伏發(fā)電 風(fēng)力發(fā)電 免疫粒子群算法 經(jīng)濟(jì)效益 功率波動(dòng)　出處：《華北電力大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：目前,為解決化石能源短缺和能源浪費(fèi)問(wèn)題,新能源的開(kāi)發(fā)利用就顯得尤為重要,集合風(fēng)、光優(yōu)勢(shì)互補(bǔ)的一種新的多能互補(bǔ)開(kāi)發(fā)方式具有較好的經(jīng)濟(jì)意義和可持續(xù)發(fā)展意義。風(fēng)力發(fā)電和太陽(yáng)能光伏發(fā)電具有無(wú)法準(zhǔn)確預(yù)測(cè)、隨機(jī)性以及不穩(wěn)定性的特點(diǎn),導(dǎo)致風(fēng)力和光伏發(fā)電無(wú)法被有效地利用并引起功率輸出的波動(dòng)。將風(fēng)力發(fā)電、光伏發(fā)電與抽水蓄能組成風(fēng)光水聯(lián)合發(fā)電系統(tǒng),很好的解決了這些問(wèn)題,不僅可平滑風(fēng)電和光伏發(fā)電的功率輸出,而且隨著電力市場(chǎng)的改革,實(shí)行了峰谷電價(jià),也可以達(dá)到充分利用風(fēng)電和光伏發(fā)電的目的。 本文首先分析了風(fēng)電場(chǎng)、太陽(yáng)能光伏電站和抽水蓄能電站的相關(guān)知識(shí),風(fēng)光發(fā)電的互補(bǔ)特性。提出在風(fēng)光發(fā)電互補(bǔ)的基礎(chǔ)上結(jié)合抽水蓄能電站,構(gòu)建了風(fēng)光水聯(lián)合系統(tǒng)的發(fā)電運(yùn)行模型。針對(duì)聯(lián)合系統(tǒng)的特點(diǎn),對(duì)系統(tǒng)中抽水蓄能電站的容量進(jìn)行計(jì)算,達(dá)到優(yōu)化配置的目的,最終起到了降低功率波動(dòng)、減少棄能的效果。為使風(fēng)光水聯(lián)合發(fā)電系統(tǒng)達(dá)到經(jīng)濟(jì)效益最大化優(yōu)化調(diào)度并且平抑功率波動(dòng)的目的,本文將以功率波動(dòng)最小為目標(biāo)的函數(shù)引入到經(jīng)濟(jì)效益最大化模型中。本文在粒子群算法的基礎(chǔ)上,由于其易早熟、后期搜索速度慢而且精度較低的特點(diǎn),提出一種動(dòng)態(tài)調(diào)整學(xué)習(xí)因子的免疫粒子群算法。該算法通過(guò)對(duì)算法速度公式中的學(xué)習(xí)因子進(jìn)行改進(jìn),采用非對(duì)稱線性動(dòng)態(tài)調(diào)整學(xué)習(xí)因子的方法,增強(qiáng)前期的全局搜索能力以及后期的局部搜索能力,快速得到最優(yōu)解。該算法在該多目標(biāo)聯(lián)合優(yōu)化調(diào)度系統(tǒng)的求解中顯著提高了搜索精度,表明了模型和算法的有效性。 本文研究了基于改進(jìn)免疫粒子群算法在風(fēng)光水聯(lián)合運(yùn)行系統(tǒng)中的應(yīng)用,結(jié)果表明,這是合理利用風(fēng)能和太陽(yáng)能資源的有效途徑,不但提高了使用新能源的效益,同時(shí)達(dá)到了降低風(fēng)電場(chǎng)、光伏電站輸出功率波動(dòng)的目的,具有可觀的經(jīng)濟(jì)效益和社會(huì)效益。
[Abstract]:At present, in order to solve the problems of fossil energy shortage and energy waste, the development and utilization of new energy is particularly important. A new multi-energy complementary development method with complementary optical advantages has better economic and sustainable development significance. Wind power generation and solar photovoltaic power generation have the characteristics of uncertainty, randomness and instability. Wind and photovoltaic power generation can not be effectively used and cause the fluctuation of power output. Wind power generation, photovoltaic power generation and pumped storage constitute the wind water combined power generation system, which solves these problems very well. Not only the power output of wind power and photovoltaic generation can be smoothed, but also with the reform of power market, peak-valley electricity price has been implemented, and the purpose of making full use of wind power and photovoltaic power generation can also be achieved. This paper first analyzes the knowledge of wind farm, solar photovoltaic power station and pumped storage power station, and the complementary characteristics of wind power generation. According to the characteristics of the combined system, the capacity of the pumped-storage power station in the system is calculated to achieve the purpose of optimizing the configuration, and finally to reduce the power fluctuation. In order to maximize the economic benefit of the combined generation system and to stabilize the power fluctuation, In this paper, the function of minimum power fluctuation is introduced into the economic benefit maximization model. On the basis of particle swarm optimization algorithm, due to its precocity, slow search speed and low precision, This paper presents an immune particle swarm optimization algorithm which dynamically adjusts the learning factor. By improving the learning factor in the speed formula of the algorithm, an asymmetric linear dynamic adjustment method is used to adjust the learning factor. The global search ability in the early stage and the local search ability in the later stage are enhanced, and the optimal solution is obtained quickly. The algorithm improves the search accuracy significantly in the solution of the multi-objective joint optimal scheduling system, and shows the validity of the model and the algorithm. In this paper, the application of improved immune particle swarm optimization algorithm in wind and water combined operation system is studied. The results show that it is an effective way to utilize wind and solar energy resources reasonably, and not only improves the efficiency of using new energy. At the same time, it can reduce the fluctuation of output power of wind farm and photovoltaic power station, and has considerable economic and social benefits.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM61;TP18

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