考虑相关性的风光互补发电系统优化调度研究

发布时间：2018-03-01 00:09

本文关键词： 风光互补发电系统相关性 Copula函数负荷追踪机会约束　出处：《华北电力大学》2014年硕士论文　论文类型：学位论文

【摘要】：为解决环境污染和能源危机,可再生能源发电受到广泛关注。然而风速和光照强度的随机性给含风力发电和光伏发电的电力系统调度运行带来了巨大的困难和挑战,因此,研究风光互补电站的优化调度问题具有重要的理论意义和应用价值。由于风电和光伏出力具有很强的随机性和互补性,这使得风电和光伏发电的出力难以准确预测,因此本文重点分析了风力和光伏出力之间的相关性。利用Weibull分布函数和Beta分布描述风速和光照强度的概率分布,并基于风速-出力关系和光照强度-出力关系,得到了风电场和光伏电站出力的概率分布。考虑到同一地点风电场和光伏电站出力之间的厚尾特性,利用Clay-Copula函数构建其联合概率分布模型,并验证了拟合优度,随后基于联合概率分布的Copula函数计算出风力和光伏出力的Spearman相关系数。由于风电场和光伏电站出力可调性较差,本文使用了储能设备作为风光互补发电系统的备用电源,提高可再生能源发电的利用率。考虑到风光互补发电系统优化调度中供电的连续性和安全性问题,本文基于Spearman相关系数,以电站对当地负荷的追踪情况为优化目标,建立了基于随机变量相关性的风光互补发电系统的优化调度模型,并采用了带有权重惯性因子的改进粒子群算法进行求解计算。风力和光伏出力的随机性使得优化调度的可靠性大大降低。因此,本文以联合概率分布来描述风电场和光伏电站出力的随机性,利用机会约束规划建立风光互补发电系统随机优化调度模型,从而保证系统调度的安全性、经济性和灵活性。利用抽样平均近似法对机会约束条件进行近似处理,将其转换为确定性非线性规划优化调度问题,从而利用现有的优化算法求解。以某地的风光互补发电系统为例验证,计算结果证明了：1)本文构建的Clay-Copula函数可以很好的刻画风电场和光伏电站出力的联合分布,并能够有效地描述其尾部相关性。2)在考虑随机变量相关性的情况下,风光互补发电系统可以有效提高可再生能源的利用率,并且能够更好的追踪负荷。3)基于机会约束模型的计算结果表明,随机优化调度模型及其转化方法可以有效提高系统调度计划的可行性、灵活性和安全性,提高可再生能源利用率,改善风电和储能单元的工作环境,提高系统追踪负荷的能力,从而为风光互补发电系统的优化调度提供了理论基础。
[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.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM614

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