基于大数据高维分析的电力负荷参数提取方法研究

Research on power load parameter extraction method based on high dimensional analysis of big data

现有的电力负荷参数提取方法存在负荷参数识别效果差的问题,为了解决上述问题,提出基于大数据高维分析的电力负荷参数提取方法。依据电力系统特征构建电力负荷模型,以此为基础,利用大数据高维分析模型并行化处理电力负荷数据。构建电力负荷数据分解模型,采用蚁群算法识别分解后的电力负荷数据,通过粒子群算法提取电力负荷参数,实现了电力负荷参数的提取。仿真对比实验结果显示:与现有的电力负荷参数提取方法相比,提出的基于大数据高维分析的电力负荷参数提取方法极大地提升了电力负荷参数识别效果,充分说明提出方法具备更好的性能。

The existing power load parameter extraction method has the problem of poor performance of load parameter identification.In order to solve the above problems,a power load parameter extraction method based on big data high⁃dimensional analysis is proposed.According to the characteristics of the power system,the power load model is constructed,and on this basis,the power load data is processed in parallel by using the big data high⁃dimensional analysis model.The power load data decomposition model was built,and the decomposed power load data was identified by ant colony algorithm,and the power load parameters were extracted by particle swarm optimization algorithm.The simulation results show that compared with the existing power load parameter extraction method,the proposed power load parameter extraction method based on big data high⁃dimensional analysis greatly improves the power load parameter identification effect,which fully shows that the proposed method has better performance.