基于大数据的电网负荷预测研究

Research on Power Grid Load Forecasting Based on Big Data

现代电网运行过程中会产生大量的数据信息,进行电网负荷预测时,传统的方式往往存在适应性不佳、预测结果误差明显的问题。为了从根本上解决这些问题,利用大数据开展现代智能电网三相不平衡负荷预测研究。在系统硬件设计上,采用STM32F103系列单片机作为运算核心完成数据的采集及处理,并利用RS485通信按照MODBUS总线协议实现预测数据的实时共享。根据所设计的系统对实际运行电网进行不平衡负荷预测,结果表明所设计的系统具有较小的预测误差,对于电网运行预测分析具有实际应用价值。

A large amount of data information is generated in the operation of modern power grids.In the process of power grid load forecasting,traditional methods often have problems with poor adaptability and obvious error in prediction results.In order to fundamentally solve these problems,the research on three-phase unbalanced load forecasting of modern smart grid was carried out by using big data.In the system hardware design,the STM32F103 series of single-chip microcomputers were used as the computing core to complete the data collection and processing,and the real-time sharing of prediction data was realized according to the MODBUS bus protocol using RS485 communication.According to the designed system,an unbalanced load forecast was made for the actual operating power grid.According to the experimental results,the designed system has a small forecast error and has practical application value for the forecasting analysis of the power grid operation.