Research Article
Time Series Modeling of Power System
@INPROCEEDINGS{10.4108/eai.17-11-2023.2342779, author={Weixuan Liu}, title={Time Series Modeling of Power System}, proceedings={Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development, ICSETPSD 2023, 17th-18th November 2023, Coimbatore, Tamilnadu, India}, publisher={EAI}, proceedings_a={ICSETPSD}, year={2024}, month={1}, keywords={power system arima lstm time series analysis}, doi={10.4108/eai.17-11-2023.2342779} }- Weixuan Liu
Year: 2024
Time Series Modeling of Power System
ICSETPSD
EAI
DOI: 10.4108/eai.17-11-2023.2342779
Abstract
Europe hopes to wean itself off energy dependence by diversifying its energy supply, developing clean energy and conserving energy. There might be both opportunities and challenges in the future. It is worth studying the reasons and rules behind current situations and making contributions to sustainable energy development in China. We use Holt and ARIMA models to forecast annual and monthly data with small data volume, and LSTM neural network to forecast weekly and daily data with large data volume and stronger periodicity. We find that a total load of Europe will decrease in the next three years, but the clean energy power generation will increase. After the modeling work, we test the performance of the model through residual sequence test, proving the robustness and accuracy of the models. Finally, we end our research by giving a comprehensive conclusion.
