摘要
在含风电场的电力系统中,影响系统经济运行的不确定参数往往具有随机波动的特点,其容易在系统潮流优化时造成信息丢失等问题。以风电场中的风速和负荷为研究对象,采用概率盒理论来描述风电场参数的不确定性,首先利用参数的分布函数漂移区间来建立风、荷的概率盒模型,然后以发电成本最小为目标函数,将风、荷的概率盒等信度离散化代入到优化模型中构建基于概率盒理论的最优潮流模型,最后采用内点法来求解该模型得到最优潮流的计算结果,并与蒙特卡洛的方法作对比验证所提方法的有效性。IEEE30节点系统的实验计算结果表明,使用概率盒的方法在准确性上不仅能够更加全面地描述系统的不确定性,有效地求解最优潮流问题,而且在计算时间上用时更短,操作也更加简单有效。
In the power system with wind farms,the uncertain parameters that affect the economic operation of the system often have the characteristics of random fluctuation,which is easy to cause information loss in the process of power flow optimization.In this paper,the wind speed and load of wind farm are taken as the research object,and the probability box theory is used to describe the uncertainty of wind farm parameters.Firstly,the probability box model of wind and load is established by using the drift interval of distribution function.Then the probability box equal reliability discretization is introduced into the optimization model with the minimum generation cost as the objective function,and the optimal power flow model based on probability box theory is constructed.Finally,the interior point method is used to solve the model to obtain the optimal power flow calculation results,and the effectiveness of the proposed method is verified by comparing with the Monte Carlo method.The calculation results of IEEE30 bus system show that the probability box method can not only describe the uncertainty of the system more comprehensively and solve the optimal power flow problem effectively,but also shorten the calculation time and make the operation more simple and effective.
作者
陈芷欣
丁家满
Chen Zhixin;Ding Jiaman(Faculty of Information Engineering and Automation,Kunming University of Science and Technology,Kunming 650500,China)
出处
《电子测量技术》
北大核心
2021年第7期61-68,共8页
Electronic Measurement Technology
基金
国家自然科学基金(51467007)项目资助
关键词
不确定性
概率盒
风电
负荷
最优潮流
证据结构体
uncertainty
probability box
wind power
load
optimal power flow
dempster-shafer structure
