Energy demand forecasting is the base for programming energy system. With the economy development, the increasing amount of energy consumption is in contradiction with the exhausted resource and destroyed environment. For the sake of the sustainable development, the reasonable energy demand forecasting is needed, and it is the scientific reference for establishing energy developing stratagem and energy policy. But the traditional forecasting methods at present have some limitations. Artificial neural network(ANN) is a new and developing subject, whose capability of adaptability and self-study is excellent. Based on the analysis as above, the forecasting model with artificial neural network was established. This model is based on the idea of time series. Compared with the traditional algorithm, this model is more friendly and maneuverability, which is not only able to forecast for a short term, but also able to forecast for a long period. Based on the fact of Chongqing, the energy demand of Chongqing is analyzed, and then it is forecasted from 2002 to 2020 with the model, and the forecasting results are reasonable.
Keywords. energy demand; forecast; ANN
References
Li Da-yong. Macro Forecasting of Electricity Demand and the Study On Electricity System Macro Decision-Making [Doctor Thesis]. 1993.7.
Kun-Long Ho, Yuan-yih Hsu, Chien-Chuen Yang, Short Term Load Forecasting Using a MulyilayerNeural Network with an Adaptive Learning Algorithm, 91 Sm450-7PWRS.
Yuan Zeng-ren. Artificial Neural Network and Its Application. Beijing: Tsinghua University Publishing Company. 1999.10.
Wen Xin, Zhou Lu, Wang Dan-li, etc. Neural Network application Design. BeiJing: Science Publishing Company.
How to cite this article
Yang, J. and Wu, X. (2003). 'The study on energy demand forecast of Chongqing'. SET Proceedings, 2(1), pp. 100-103. https://doi.org/10.65582/set.2003.023