含大型风电场的电力系统潮流优化研究

发布时间：2018-03-20 05:20

本文选题：风电场　切入点：风速相关性　出处：《华北电力大学》2014年硕士论文　论文类型：学位论文

【摘要】：鉴于风电的随机性与相关性等不确定性因素，如何在保证安全和可靠供电的前提下更加合理地利用风能，是一个亟待解决且十分必要的问题。电力系统的最优潮流为上述问题提供了有效的解决途径。针对有大型风电场接入的电力系统的潮流优化问题，研究与探讨了风电场分组等值建模、具有相关性的风电场风速建模、含风电场电力系统的最优潮流模型与计算，提出了新的建模算法，为含风电场电力系统的潮流优化研究提供了新的思路。考虑风电场内机组间尾流的相互影响，，提出了一种计及尾流效应的风电场等值建模方法。该方法定义了“尾流影响因子”以表征机组间尾流影响的程度，并以此作为风电场内风电机组的分组依据。对风电机组进行分组及合并等值后，得到风电场的多机等值模型。算例结果显示，与传统等值方法相比，该模型更加准确地体现了风电场的功率输出特性。针对风电场间风速具有相关性的特点，提出了基于Copula函数的相关性风速建模方法。该方法利用Copula函数构建多风电场间风速的联合概率分布，进而生成具有相关性的风速分布样本空间，根据风电机组的出力特性可得到各风电场出力。算例表明，模型有效地描述了风电场间具有相关性的风速，得到的多元风速样本可用于含风电场集群的电力系统的潮流优化分析。传统的最优潮流模型与算法多以确定性模型作为前提，然而风电的接入为电力系统带来了不确定性因素。考虑到这一问题，介绍了基于机会约束规划的最优潮流模型，并利用基于随机模拟技术的粒子群优化算法作为求解方法。风电场的接入势必对电力系统的可用输电能力（ATC）产生影响，在上述模型的基础上，建立了基于最优潮流的含风电场电力系统的ATC计算模型，并对模型进行了求解。IEEE30节点和IEEE118节点测试系统算例表明，风速的随机性和相关性、风电场所在的节点位置、机会约束规划的置信水平等因素都对系统的可用输电能力有一定影响，为含风电场电力系统的规划与运行提供了参考和依据。
[Abstract]:In view of the uncertainties such as the randomness and correlation of wind power, how to make more rational use of wind energy on the premise of ensuring safe and reliable power supply, The optimal power flow of power system provides an effective way to solve the above problems. This paper studies and discusses wind farm grouping equivalent modeling, wind speed modeling with correlation, optimal power flow model and calculation of wind farm power system, and puts forward a new modeling algorithm. It provides a new idea for the study of power flow optimization in power system with wind farm. Considering the interaction between units in wind farm, a wind farm equivalent modeling method considering wake effect is proposed. In this method, the "wake influence factor" is defined to characterize the degree of wakes influence between units. After grouping and merging the wind turbine units, the multi-machine equivalent model of wind farm is obtained. The results show that compared with the traditional equivalent method, the wind power unit is divided into two groups. The model more accurately reflects the power output characteristics of the wind farm. According to the correlation of wind speed between wind farms, a method of wind speed modeling based on Copula function is proposed, which uses Copula function to construct the joint probability distribution of wind speed between multi-wind farms. Then the wind velocity distribution sample space with correlation is generated, and the wind farm output force can be obtained according to the wind turbine output characteristics. Numerical examples show that the model can effectively describe the wind speed with correlation between wind farms. The multivariate wind speed samples obtained can be used for power flow optimization analysis of power systems with wind farm clusters. Most of the traditional optimal power flow models and algorithms are based on deterministic models, but the access of wind power brings uncertainty to power system. Considering this problem, an optimal power flow model based on opportunistic constrained programming is introduced. The particle swarm optimization algorithm based on stochastic simulation technology is used as the solution. The connection of wind farm is bound to have an effect on the available transmission capacity of power system. Based on the above model, the ATC calculation model of power system with wind farm based on optimal power flow is established. An example of the test system for solving the. IEEE30 and IEEE118 nodes shows that the wind speed is randomness and correlation, and the location of the node in which the wind farm is located. The confidence level of the chance constrained programming has a certain influence on the available transmission capacity of the system, which provides a reference and basis for the planning and operation of the power system with wind farm.
【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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