面向区域综合能源系统的电-气负荷联合预测研究

能源互联网中电力系统与天然气系统的依赖增强，给综合能源系统中电力系统与天然气系统的负荷预测带来了更高的挑战。文中提出了基于长短记忆网络与权值共享的电-气联合负荷预测方法。文中在预测模型中使用了相关系数对天气因素进行了分析，提取了对两种负荷的重要气象因素，将长短记忆网络作为主要预测算法，权值共享模式分析了电-气两种负荷之间的相关性。算例中使用云南省综合能源系统示范工程数据对算法有效性进行了验证，结果显示该算法有效提高了综合能源系统中电力与天然气负荷预测的精度，有着较高的应用价值。

Combined forecasting of electricity and gas load for regional integrated energy system

The increasing dependence of electrical power system and natural gas system in the energy Internet makes the integrated energy system provide higher requirements for load forecasting of different energy systems. In this paper, a combined load forecasting method for electricity and gas based on long-short term memory network and weight sharing is proposed. In the prediction model, firstly, the correlation coefficient is used to analyze the weather factors, and the important weather factors of the energy loads are extracted. The long-short term memory network is used as the main forecasting algorithm, and the weight sharing mode is used to analyze the correlation between the two loads. The results show that the algorithm in this paper can effectively improve the accuracy of electrical power load and natural gas load forecasting in the integrated energy system, which has promotion for application.