基于点估计法的微电网随机优化调度

发布时间：2018-05-17 23:10

本文选题：微电网 + 点估计法　；参考：《长沙理工大学》2015年硕士论文

【摘要】：随着科学技术的快速发展给传统的能源带来巨大的挑战。微电网作为智能电网的重要组成部分,以其接在用户侧,具有成本低、电压低及污染小等特点而开始被人们重视。微网可以看作是连接分布式电源与主电网的桥梁,这使得主电网系统与微网系统可以友好地进行能量交互、协调主电网与分布式电源之间的矛盾,而主电网不必直接面临数量众多、类型不同、出力波动的微源的影响。但是,各种不确定变量给微电网优化运行带来巨大影响。怎么评价这些不确定性因素对微电网经济运行的影响值得深入的研究。风力、光伏出力的间歇性以及负荷的不确定性使得微电网潮流计算具有随机特征,基于此,在建立不同间歇性电源出力以及负荷需求的概率密度函数的基础上,利用点估计法处理不确定信息,然后建立了微电网随机潮流的计算方法。根据分布式电源出力概率密度函数和负荷需求的概率分布构造其估计点,将分布估计点嵌入到前推回代法中进行随机潮流计算,得到可靠性评估数据的均值和标准差,以估计微电网系统节点电压以及支路功率的概率密度函数。通过节点电压和支路功率的概率密度函数为微电网的可靠性评估分析提供良好的基础。最后为了验证点估计法在处理不确定性的优越性,将蒙特卡罗抽样模拟法用在随机潮流的计算中,并通过实际算例证明基于点估计法的微电网随机潮流计算不仅次数比蒙特卡罗法少,而且处理速度较快。基于以上的思路,该文提出利用点估计处理单位时间段负荷需求和太阳能、风能出力的不确定性问题,根据分布式电源出力的概率密度函数和负荷需求的概率分布构造其估计点,通过估计点建立微电网多目标概率优化调度模型,然后用Gram-Charlier级数展开方法得到微电网总运行目标函数的累计分布函数及概率分布函数,为了研究负荷波动对于微电网优化管理的影响,建立三种负荷水平下的微电网概率优化调度模型,通过概率密度函数和累计分布函数验证负荷波动对于微电网优化运行的影响。另外,本章通过实际算例研究三估计法与两点估计法的优缺点,结果表明,三点估计虽然比两点取值点多,但是它的计算速度以及计算的精度都高于两点估计法。鉴于微电网概率优化管理属于多维度,非线性优化问题,然后利用改进蝙蝠优化算法进行问题求解。最后,通过算例验证蝙蝠算法具有良好实用性和适应性,并且也验证所提模型的实际意义。
[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.
【学位授予单位】：长沙理工大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TM73

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