基于云平台的电力系统能源负荷预测研究

Study on energy data acquisition and load forecasting of power system based on cloud platform

为提高电力系统能源负荷预测的效率和精度,提出了一种基于云平台的电力系统能源负荷预测方法。首先,为提高电力系统采集数据的入库效率和查询效率,提出一种分布式的数据采集系统结构框架,并设计了大数据云平台架构;其次,运用极限学习机对区域日负荷进行了准确预测。研究结果表明,该方法有效提高了电力系统能源负荷预测的效率和精度,为电力管理和调度部门及时制定调度计划与运控策略提供了科学决策的依据。

In order to improve the efficiency and accuracy of power system energy load forecasting,a power system energy load forecasting method based on cloud platform is proposed.Firstly,in order to improve the storage efficiency and query efficiency of power system data collection,a distributed data collection system framework is proposed,and a big data cloud platform is designed,the regional daily load is accurately predicted by using the limit learning machine.The results show that the proposed methods can effectively improve the efficiency and accuracy of power system energy load forecasting,and provide scientific basis for power management and dispatch departments to make dispatching plan and operation control strategy in time.