智能电网电力大数据高性能处理方法优化

传统的电力大数据处理方法难以控制数据的全局变量,导致数据处理工作量过大,影响处理效率。为此,文中基于SaaS模式设计了新的智能电网电力大数据高性能处理方法。首先建立SaaS模式下的数据处理平台,并确认数据处理目标函数的最大值与最小值。在完成目标函数确认后,通过构建多维超立方数据模型控制数据全局变量,在此基础上,使用神经网络处理电力数据,通过消除数据偏差,保证处理后的电力数据可直接通过在平台上使用。实验结果表明,与传统处理方法相比,文中方法的载入和处理速度更快,充分证明了该方法的可行性。

Optimization of high performance processing method for smart grid power big data

Traditional power big data processing method is difficult to control the global variables of the data,resulting in too much data processing workload,affecting the processing efficiency.Therefore,a new smart grid power big data high-performance processing method is designed based on SaaS model.Firstly,the data processing platform is established under the SaaS model,and the maximum and minimum values of the data processing objective function is confirmed.After the completion of the confirmation of the objective function,the multi-dimensional hypercube data model is built to control the global variables of the data.On this basis,the neural network is used to process the power data.By eliminating the data deviation,the processed power data can be directly used on the platform.Experimental results show that the loading and processing speed of the proposed method is faster than that of the traditional method,which fully proves the feasibility of the proposed method.