收稿日期: 2022-05-24
修回日期: 2022-07-19
录用日期: 2022-09-15
网络出版日期: 2023-04-26
基金资助
国家自然科学基金面上项目(72072114)
Wind Power Scenario Generation Method and Application Based on Spatiotemporal Covariance Function
Received date: 2022-05-24
Revised date: 2022-07-19
Accepted date: 2022-09-15
Online published: 2023-04-26
与传统发电不同,风力发电具有较大的随机性与时空相关性.在风力发电并网的电力系统优化调度问题中,保障电力调度在不同风力发电功率场景中的最优执行是决策问题的关键点,因此高质量的风能场景生成非常重要.基于高斯随机过程和时空协方差函数表征风力发电站输出功率的时空相关性,由Pair Copula模型建立联合概率分布,通过经验概率逆变换方法实现具体场景.评估生成场景的多种指标,验证生成场景的优越性.基于修改的IEEE 6总线系统建立电力系统机组组合的混合整数规划模型,求解不同场景下的问题,验证场景生成方法在风力发电并网调度问题中所具有的经济性和可行性.
彭星皓, 李艳婷 . 基于时空协方差函数的风能场景生成方法与应用[J]. 上海交通大学学报, 2023 , 57(12) : 1531 -1542 . DOI: 10.16183/j.cnki.jsjtu.2022.180
Wind power generation is different from traditional power generation in which wind power output is highly stochastic and spatio-temporally dependent. In the optimal scheduling problem of wind power grid-connected power system, ensuring the optimal execution of power scheduling in different wind power scenarios is the key of the decision-making problem. Therefore, high quality wind power scenario generation is of great importance. The spatiotemporal correlation of the output power of wind power plants are characterized based on Gaussian stochastic process and spatiotemporal covariance function, and the joint probability distribution is established by the Pair Copula model, and specific scenarios are implemented by the method of empirical probability inverse transformation. A variety of scene metrics of the generated scene are generated, which verifies the superiority of the generated scene. Finally, based on the modified IEEE 6-bus system, a mixed integer programming model for the unit output of the power system is established to solve the problems in different scenarios and verify the economic advantages of the scenario generation method in the dispatching problem of wind power grid connection.
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