摘要
依据A、C市2015-2017年以及B市2016-2018年历史日负荷数据,针对不同用气结构城市不同季节的燃气日负荷进行预测,比较ARIMA模型、BP模型、RNN模型、LSTM网络模型的预测精度。结果表明,不同模型不同用气结构城市的预测精度不同,LSTM网络模型的适用性和预测精度在各城市均比较高。
According to the historical daily load data of cities A and C from^(2)015 to 2017 and city B from^(2)016 to 2018,the daily gas load of cities with different gas consumption structures in different seasons is predicted,and the prediction accuracy of ARIMA model,BP model,RNN model and LSTM network model is compared.The results show that the prediction accuracy of different models for cities with different gas consumption structures is different,and the applicability and prediction accuracy of the LSTM network model are relatively high in each city.
作者
汤燕刚
房艳立
陈刘洋
黄小美
罗敏
TANG Yangang;FANG Yanli;CHEN Liuyang;HUANG Xiaomei;LUO Min
出处
《煤气与热力》
2022年第4期V0007-V0011,共5页
Gas & Heat
关键词
燃气日负荷预测
用气结构
深度学习
长短期记忆网络
gas daily load forecast
gas consumption structure
deep learning
long-and short-term memory network