本文選題：微電網(wǎng) + 點(diǎn)估計(jì)法��； 參考：《長(zhǎng)沙理工大學(xué)》2015年碩士論文

【摘要】：隨著科學(xué)技術(shù)的快速發(fā)展給傳統(tǒng)的能源帶來(lái)巨大的挑戰(zhàn)。微電網(wǎng)作為智能電網(wǎng)的重要組成部分,以其接在用戶側(cè),具有成本低、電壓低及污染小等特點(diǎn)而開始被人們重視。微網(wǎng)可以看作是連接分布式電源與主電網(wǎng)的橋梁,這使得主電網(wǎng)系統(tǒng)與微網(wǎng)系統(tǒng)可以友好地進(jìn)行能量交互、協(xié)調(diào)主電網(wǎng)與分布式電源之間的矛盾,而主電網(wǎng)不必直接面臨數(shù)量眾多、類型不同、出力波動(dòng)的微源的影響。但是,各種不確定變量給微電網(wǎng)優(yōu)化運(yùn)行帶來(lái)巨大影響。怎么評(píng)價(jià)這些不確定性因素對(duì)微電網(wǎng)經(jīng)濟(jì)運(yùn)行的影響值得深入的研究。風(fēng)力、光伏出力的間歇性以及負(fù)荷的不確定性使得微電網(wǎng)潮流計(jì)算具有隨機(jī)特征,基于此,在建立不同間歇性電源出力以及負(fù)荷需求的概率密度函數(shù)的基礎(chǔ)上,利用點(diǎn)估計(jì)法處理不確定信息,然后建立了微電網(wǎng)隨機(jī)潮流的計(jì)算方法。根據(jù)分布式電源出力概率密度函數(shù)和負(fù)荷需求的概率分布構(gòu)造其估計(jì)點(diǎn),將分布估計(jì)點(diǎn)嵌入到前推回代法中進(jìn)行隨機(jī)潮流計(jì)算,得到可靠性評(píng)估數(shù)據(jù)的均值和標(biāo)準(zhǔn)差,以估計(jì)微電網(wǎng)系統(tǒng)節(jié)點(diǎn)電壓以及支路功率的概率密度函數(shù)。通過(guò)節(jié)點(diǎn)電壓和支路功率的概率密度函數(shù)為微電網(wǎng)的可靠性評(píng)估分析提供良好的基礎(chǔ)。最后為了驗(yàn)證點(diǎn)估計(jì)法在處理不確定性的優(yōu)越性,將蒙特卡羅抽樣模擬法用在隨機(jī)潮流的計(jì)算中,并通過(guò)實(shí)際算例證明基于點(diǎn)估計(jì)法的微電網(wǎng)隨機(jī)潮流計(jì)算不僅次數(shù)比蒙特卡羅法少,而且處理速度較快�；谝陨系乃悸�,該文提出利用點(diǎn)估計(jì)處理單位時(shí)間段負(fù)荷需求和太陽(yáng)能、風(fēng)能出力的不確定性問(wèn)題,根據(jù)分布式電源出力的概率密度函數(shù)和負(fù)荷需求的概率分布構(gòu)造其估計(jì)點(diǎn),通過(guò)估計(jì)點(diǎn)建立微電網(wǎng)多目標(biāo)概率優(yōu)化調(diào)度模型,然后用Gram-Charlier級(jí)數(shù)展開方法得到微電網(wǎng)總運(yùn)行目標(biāo)函數(shù)的累計(jì)分布函數(shù)及概率分布函數(shù),為了研究負(fù)荷波動(dòng)對(duì)于微電網(wǎng)優(yōu)化管理的影響,建立三種負(fù)荷水平下的微電網(wǎng)概率優(yōu)化調(diào)度模型,通過(guò)概率密度函數(shù)和累計(jì)分布函數(shù)驗(yàn)證負(fù)荷波動(dòng)對(duì)于微電網(wǎng)優(yōu)化運(yùn)行的影響。另外,本章通過(guò)實(shí)際算例研究三估計(jì)法與兩點(diǎn)估計(jì)法的優(yōu)缺點(diǎn),結(jié)果表明,三點(diǎn)估計(jì)雖然比兩點(diǎn)取值點(diǎn)多,但是它的計(jì)算速度以及計(jì)算的精度都高于兩點(diǎn)估計(jì)法。鑒于微電網(wǎng)概率優(yōu)化管理屬于多維度,非線性優(yōu)化問(wèn)題,然后利用改進(jìn)蝙蝠優(yōu)化算法進(jìn)行問(wèn)題求解。最后,通過(guò)算例驗(yàn)證蝙蝠算法具有良好實(shí)用性和適應(yīng)性,并且也驗(yàn)證所提模型的實(shí)際意義。
[Abstract]:With the rapid development of science and technology, traditional energy brings great challenges. As an important part of smart grid, microgrid has been paid more and more attention because of its low cost, low voltage and low pollution. Microgrid can be regarded as a bridge between distributed generation and main grid, which makes the main grid system and microgrid system can interact with each other amicably and coordinate the contradiction between main grid and distributed generation. The main power grid does not have to directly face the influence of a large number of microsources with different types and force fluctuation. However, all kinds of uncertain variables have a great impact on the optimal operation of microgrid. How to evaluate the impact of these uncertainties on the economic operation of microgrid deserves further study. The intermittency of wind, photovoltaic output and the uncertainty of load make the power flow calculation of microgrid have stochastic characteristics. Based on this, the probability density function of different intermittent power supply and load demand is established. The point estimation method is used to deal with the uncertain information, and then the calculation method of stochastic power flow for microgrid is established. According to the probability density function of distributed power generation and the probability distribution of load demand, the estimation points are constructed, and the distribution estimation points are embedded into the forward pushback method to calculate the random power flow, and the mean value and standard deviation of the reliability evaluation data are obtained. The probability density function of node voltage and branch power is estimated. The probability density function of node voltage and branch power provides a good basis for reliability evaluation and analysis of microgrid. Finally, in order to verify the superiority of point estimation method in dealing with uncertainty, Monte Carlo sampling simulation method is used in the calculation of stochastic power flow. A practical example shows that the stochastic power flow calculation based on point estimation method is less than that of Monte Carlo method, and the processing speed is faster than that of Monte Carlo method. Based on the above ideas, this paper proposes using point estimation to deal with the uncertainty of unit time load demand and solar and wind power. According to the probability density function of distributed power generation and the probability distribution of load demand, the estimation points are constructed, and the multi-objective probabilistic optimal dispatching model of microgrid is established by estimating points. Then the accumulative distribution function and probability distribution function of the total operation objective function of microgrid are obtained by using Gram-Charlier series expansion method. In order to study the influence of load fluctuation on the optimization management of microgrid, The probabilistic optimal dispatching model of microgrid under three load levels is established. The effect of load fluctuation on the optimal operation of microgrid is verified by probability density function and cumulative distribution function. In addition, the advantages and disadvantages of the three-point estimation method and the two-point estimation method are studied by practical examples. The results show that the three-point estimation method is more than the two-point estimation method, but its calculation speed and accuracy are higher than that of the two-point estimation method. Since the probability optimization management of microgrid belongs to multi-dimensional nonlinear optimization problem the improved bat optimization algorithm is used to solve the problem. Finally, an example is given to verify that the bat algorithm has good practicability and adaptability, and the practical significance of the proposed model is also verified.
【學(xué)位授予單位】：長(zhǎng)沙理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TM73

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