一种风光联合出力概率模型建模方法

随着风电和光伏等新能源渗透率的逐年提高,其波动性和随机性对电力系统的安全稳定运行产生重要影响。考虑风电和光伏在时空上的波动性和相关性,提出基于混合高斯模型的多时空尺度的风电-光伏联合概率建模方法。该方法首先基于历史数据的数理统计结果,提出三阶混合高斯模型。使用K-means聚类方法求得模型各参数的迭代初值,运用最大期望算法求取混合高斯模型参数最优值。该模型具有同时考虑风电和光伏相关性和波动性的优点。以我国东南地区风电场和光伏实际数据为例进行仿真。仿真结果表明,所提出的3阶混合高斯模型对风光联合出力的概率特性具有良好的拟合效果。

A modeling method for a wind and photovoltaic joint power probability model

As the penetration rate of new energy, such as wind power and photovoltaics, increases year by year, its volatility and randomness have an important impact on the safe and stable operation of the power system. In this paper, considering the volatility and correlation of wind power and photovoltaics in time and space scale, a mixed Gaussian model is proposed to establish a wind-photovoltaic joint power probability model based on multiple temporal and spatial scales. First, based on the statistical results of historical data, a third-order mixed Gaussian model is proposed. The K-means clustering method is used to obtain iterative initial values of the parameters of the model. A maximum expectation algorithm is used to obtain the optimal parameters of the mixed Gaussian model. The model has the advantage of considering the correlation and volatility of wind power and photovoltaic energy. The simulation results of wind farm and photovoltaic data in southeast China are taken as examples. These show that the proposed 3rd-order mixed Gaussian model has a good fitting effect on the probability characteristics of wind and photovoltaic joint output. This work is supported by National Natural Science Foundation of China (No. 51422701) and Science and Technology Project of State Grid Jiangsu Electric Power Co., Ltd. (No. GJS0000FZJS1800853).