The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
Electric load forecasting in smart grids using Long-Short-Term-Memory based Recurrent Neural Network
Abstract
Electric load forecasting plays a vital role in smart grids. Short term electric load forecasting forecasts the load that is several hours to several weeks ahead. Due to the nonlinear, non-stationary and nonseasonal nature of the short term electric load time series in small scale power systems, accurate forecasting is challenging. This paper explores Long-Short-Term-Memory (LSTM) based Recurrent Neural Network (RNN) to deal with this challenge. LSTM-based RNN is able to exploit the long term dependencies in the electric load time series for more accurate forecasting. Experiments are conducted to demonstrate that LSTM-based RNN is capable of forecasting accurately the complex electric load time series with a long forecasting horizon. Its performance compares favorably to many other forecasting methods.
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Jamshidi, M., Lalbakhsh, A., Talla, J., Peroutka, Z., Hadjilooei, F., Lalbakhsh, P., Jamshidi, M., Spada, L. L., Mirmozafari, M., Dehghani, M., et al. (2020) · IEEE Access · doi:10.1109/access.2020.3001973 · Cited by 551
Multi-Sequence LSTM-RNN Deep Learning and Metaheuristics for Electric Load Forecasting
Bouktif, S., Fiaz, A., Ouni, A., & Serhani, M. A. (2020) · Energies · doi:10.3390/en13020391 · Cited by 256
Electrical Load Forecasting Using Edge Computing and Federated Learning
Taik, A., & Cherkaoui, S. (2020) · ICC 2020 - 2020 IEEE International Conference on Communications (ICC) · doi:10.1109/icc40277.2020.9148937 · Cited by 252
Cicceri, G., Tricomi, G., D’Agati, L., Longo, F., Merlino, G., & Puliafito, A. (2023) · Sensors · doi:10.3390/s23094549 · Cited by 58
Metadata
- Authors
- Zheng, J., Xu, C., Zhang, Z., & Li, X.
- Venue
- 2017 51st Annual Conference on Information Sciences and Systems (CISS)
- Publisher
- IEEE
- Published
- 2017-03
- Pages
- 1-6
- OpenAlex
- W2613278213
- Cited by
- 341
- References
- 26
- FWCI
- 47.48
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Zheng, J., Xu, C., Zhang, Z., & Li, X. (2017). Electric load forecasting in smart grids using Long-Short-Term-Memory based Recurrent Neural Network. 2017 51st Annual Conference on Information Sciences and Systems (CISS). https://doi.org/10.1109/ciss.2017.7926112
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