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文章摘要
面向区域综合能源系统的电-气负荷联合预测研究
Research on combined forecasting of electricity-gas load for regional integrated energy system
Received:July 20, 2020  Revised:August 04, 2020
DOI:10.19753/j.issn1001-1390.2023.05.022
中文关键词: 能源互联网  电-气联合负荷预测  长短记忆网络  任务关联  相关系数
英文关键词: energy Internet, combined load forecasting method for electricity and gas, long-short term memory network, task correlation, correlation coefficient
基金项目:国家自然科学基金项目(51277067)
Author NameAffiliationE-mail
Jiang Yan* Yunnan Electric Power Dispatching Control Center, Kunming 650011, China jiangyan12305@163.com 
Li Xiufeng Yunnan Electric Power Dispatching Control Center, Kunming 650011, China 26240067@qq.com 
Gao Daochun Yunnan Electric Power Dispatching Control Center, Kunming 650011, China 748654207@qq.com 
Duan Ruiqin Yunnan Electric Power Dispatching Control Center, Kunming 650011, China 229869427@qq.com 
Zhou Hui Beijing Qingruan Innovation Technology Co., Ltd., Beijing 100085, China. zhzhouhui@outlook.com 
Liu Yang North China Electric Power University, Beijing 102206, China 2576562261@qq.com 
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中文摘要:
      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。
英文摘要:
      The increasing dependence of power system and natural gas system in energy Internet brings higher challenge to the load forecasting of power system and natural gas system in integrated energy system. 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 two 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 electricity and gas loads. An example is given to verify the effectiveness of the algorithm by using the data of Yunnan integrated energy system demonstration project. The results show that the algorithm proposed in this paper can effectively improve the accuracy of electricity-natural gas load forecasting in the integrated energy system, which has high application value.
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