本文關(guān)鍵詞： 風(fēng)光互補(bǔ)發(fā)電系統(tǒng) 相關(guān)性 Copula函數(shù) 負(fù)荷追蹤 機(jī)會(huì)約束　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】：為解決環(huán)境污染和能源危機(jī),可再生能源發(fā)電受到廣泛關(guān)注。然而風(fēng)速和光照強(qiáng)度的隨機(jī)性給含風(fēng)力發(fā)電和光伏發(fā)電的電力系統(tǒng)調(diào)度運(yùn)行帶來(lái)了巨大的困難和挑戰(zhàn),因此,研究風(fēng)光互補(bǔ)電站的優(yōu)化調(diào)度問(wèn)題具有重要的理論意義和應(yīng)用價(jià)值。 由于風(fēng)電和光伏出力具有很強(qiáng)的隨機(jī)性和互補(bǔ)性,這使得風(fēng)電和光伏發(fā)電的出力難以準(zhǔn)確預(yù)測(cè),因此本文重點(diǎn)分析了風(fēng)力和光伏出力之間的相關(guān)性。利用Weibull分布函數(shù)和Beta分布描述風(fēng)速和光照強(qiáng)度的概率分布,并基于風(fēng)速-出力關(guān)系和光照強(qiáng)度-出力關(guān)系,得到了風(fēng)電場(chǎng)和光伏電站出力的概率分布�？紤]到同一地點(diǎn)風(fēng)電場(chǎng)和光伏電站出力之間的厚尾特性,利用Clay-Copula函數(shù)構(gòu)建其聯(lián)合概率分布模型,并驗(yàn)證了擬合優(yōu)度,隨后基于聯(lián)合概率分布的Copula函數(shù)計(jì)算出風(fēng)力和光伏出力的Spearman相關(guān)系數(shù)。 由于風(fēng)電場(chǎng)和光伏電站出力可調(diào)性較差,本文使用了儲(chǔ)能設(shè)備作為風(fēng)光互補(bǔ)發(fā)電系統(tǒng)的備用電源,提高可再生能源發(fā)電的利用率。考慮到風(fēng)光互補(bǔ)發(fā)電系統(tǒng)優(yōu)化調(diào)度中供電的連續(xù)性和安全性問(wèn)題,本文基于Spearman相關(guān)系數(shù),以電站對(duì)當(dāng)?shù)刎?fù)荷的追蹤情況為優(yōu)化目標(biāo),建立了基于隨機(jī)變量相關(guān)性的風(fēng)光互補(bǔ)發(fā)電系統(tǒng)的優(yōu)化調(diào)度模型,并采用了帶有權(quán)重慣性因子的改進(jìn)粒子群算法進(jìn)行求解計(jì)算。 風(fēng)力和光伏出力的隨機(jī)性使得優(yōu)化調(diào)度的可靠性大大降低。因此,本文以聯(lián)合概率分布來(lái)描述風(fēng)電場(chǎng)和光伏電站出力的隨機(jī)性,利用機(jī)會(huì)約束規(guī)劃建立風(fēng)光互補(bǔ)發(fā)電系統(tǒng)隨機(jī)優(yōu)化調(diào)度模型,從而保證系統(tǒng)調(diào)度的安全性、經(jīng)濟(jì)性和靈活性。利用抽樣平均近似法對(duì)機(jī)會(huì)約束條件進(jìn)行近似處理,將其轉(zhuǎn)換為確定性非線性規(guī)劃優(yōu)化調(diào)度問(wèn)題,從而利用現(xiàn)有的優(yōu)化算法求解。 以某地的風(fēng)光互補(bǔ)發(fā)電系統(tǒng)為例驗(yàn)證,計(jì)算結(jié)果證明了：1)本文構(gòu)建的Clay-Copula函數(shù)可以很好的刻畫風(fēng)電場(chǎng)和光伏電站出力的聯(lián)合分布,并能夠有效地描述其尾部相關(guān)性。2)在考慮隨機(jī)變量相關(guān)性的情況下,風(fēng)光互補(bǔ)發(fā)電系統(tǒng)可以有效提高可再生能源的利用率,并且能夠更好的追蹤負(fù)荷。3)基于機(jī)會(huì)約束模型的計(jì)算結(jié)果表明,隨機(jī)優(yōu)化調(diào)度模型及其轉(zhuǎn)化方法可以有效提高系統(tǒng)調(diào)度計(jì)劃的可行性、靈活性和安全性,提高可再生能源利用率,改善風(fēng)電和儲(chǔ)能單元的工作環(huán)境,提高系統(tǒng)追蹤負(fù)荷的能力,從而為風(fēng)光互補(bǔ)發(fā)電系統(tǒng)的優(yōu)化調(diào)度提供了理論基礎(chǔ)。
[Abstract]:In order to solve the environmental pollution and energy crisis, renewable energy generation has received extensive attention. However, the randomness of wind speed and light intensity brings great difficulties and challenges to the dispatching and operation of power system, which includes wind power generation and photovoltaic power generation. It is of great theoretical significance and practical value to study the optimal dispatching problem of wind power stations. Due to the strong randomness and complementarity of wind power and photovoltaic output, it is difficult to accurately predict the wind power and photovoltaic output. Therefore, the correlation between wind force and photovoltaic force is analyzed in this paper. The probability distribution of wind speed and light intensity is described by using Weibull distribution function and Beta distribution. The probability distribution of output force of wind farm and photovoltaic power station is obtained. Considering the thick tail characteristic between wind farm and photovoltaic power station at the same location, the joint probability distribution model is constructed by using Clay-Copula function, and the goodness of fit is verified. Then the Spearman correlation coefficients of wind and photovoltaic forces are calculated based on the Copula function of joint probability distribution. Because of the poor adjustable power output of wind farm and photovoltaic power station, the energy storage equipment is used as the backup power source for the wind and photovoltaic power generation system. To improve the utilization ratio of renewable power generation, considering the continuity and security of power supply in the optimal dispatching of wind-to-wind complementary generation system, based on the Spearman correlation coefficient, this paper takes the tracking of local load in power station as the optimization goal. The optimal scheduling model of wind-wind complementary power generation system based on the correlation of random variables is established, and the improved particle swarm optimization algorithm with weight inertia factor is used to solve the problem. The randomness of wind power and photovoltaic output force makes the reliability of optimal dispatching much less. Therefore, the joint probability distribution is used to describe the randomness of wind farm and photovoltaic power station. The stochastic optimal scheduling model of wind-wind complementary power generation system is established by using opportunity-constrained programming, which ensures the security, economy and flexibility of the system scheduling. The sampling average approximation method is used to approximate the opportunistic constraints. It is transformed into a deterministic nonlinear programming optimal scheduling problem and solved by existing optimization algorithms. The calculation results show that the Clay-Copula function constructed in this paper can well describe the joint distribution of wind farm and photovoltaic power station. And can effectively describe its tail correlation. 2) considering the correlation of random variables, the wind and wind complementary power generation system can effectively improve the utilization of renewable energy. The calculation results based on the chance constraint model show that the stochastic optimal scheduling model and its transformation method can effectively improve the feasibility, flexibility and security of the system scheduling plan. It can improve the utilization of renewable energy, improve the working environment of wind power and energy storage units, and enhance the ability of system to track load, which provides a theoretical basis for the optimal scheduling of wind and wind complementary power generation systems.
【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)】：TM614

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