摘要
随着光伏电源并网规模的不断扩大,光伏电源出力的波动性使得负荷预测难度加大,气象因素又对电力系统负荷有显著的影响。考虑剥离光伏电源对电网负荷预测的影响后,研究实时气象因素对电力系统净负荷的影响,然后将净负荷分解为基础负荷和气象敏感负荷,采用灰色模型GM(1,1)和最小二乘支持向量机算法分别对二者进行预测。之后采用主导气象因素辨识方法分析影响净负荷的主要气象因素,合理选取预测模型的输入向量,实现了考虑光伏影响与气象敏感负荷分解的LSSVM负荷预测。实验证明所提出的模型能够明显提高负荷预测的准确度。
With the continuous expansion of photovoltaic power grid scale,the fluctuation of photovoltaic power output makes load forecasting more difficult.In addition,meteorological factors have a significant impact on the load of power system.Therefore,this paper first considers the impact of stripping photovoltaic power supply on grid load forecasting,and then the impact of real-time meteorological factors on the net load of power system is studied.The net load is divided into basic load and gas sensitive load,and the grey model GM(1,1)and least squares support vector machine are used.The algorithm of ort vector machine(LSSVM)predicts both of them.Then,the main meteorological factors affecting the net load are analyzed by using the dominant meteorological factor identification method,and the input vector of the prediction model is reasonably selected to realize the LSSVM load prediction considering the photovoltaic effect and meteorological sensitive load decomposition.Practical application shows that the proposed model can significantly improve the accuracy of load forecasting.
作者
蔡冬阳
赵申
周玮
郭德华
薛书倩
CAI Dong-yang;ZHAO Shen;ZHOU Wei;GUO De-hua;XUE Shu-qian(State Grid Jiangsu Electric Power Co.,Ltd.,Nanjing,Jiangsu 210024,China;Beijing Qingruan Initiative Science and Technology Co.,Ltd.,Beijing 100085,China)
出处
《计算技术与自动化》
2020年第4期81-85,共5页
Computing Technology and Automation
关键词
光伏
实时气象因素
气象敏感负荷分解
最小二乘支持向量机
负荷预测
photovoltaic
hourly weather factors
weather sensitive load decomposition
least squares support vector machine
load forecast
