Prediction of energy load profiles
| Thesis title in Czech: | Predikce profilů spotřeby elektrické energie |
|---|---|
| Thesis title in English: | Prediction of energy load profiles |
| Key words: | časové řady, stavo-prostorové modely, neuronové sítě, imputace, předzpracování |
| English key words: | time series, state-space models, neural networks, imputation, preprocessing |
| Academic year of topic announcement: | 2016/2017 |
| Thesis type: | diploma thesis |
| Thesis language: | angličtina |
| Department: | Department of Theoretical Computer Science and Mathematical Logic (32-KTIML) |
| Supervisor: | RNDr. Jiří Fink, Ph.D. |
| Author: | hidden - assigned and confirmed by the Study Dept. |
| Date of registration: | 06.12.2016 |
| Date of assignment: | 06.12.2016 |
| Confirmed by Study dept. on: | 20.12.2016 |
| Date and time of defence: | 07.09.2017 10:30 |
| Date of electronic submission: | 17.07.2017 |
| Date of submission of printed version: | 19.07.2017 |
| Date of proceeded defence: | 07.09.2017 |
| Opponents: | Richard Van Leeuwen |
| Guidelines |
| The student shall review the following topics in his diploma thesis:
- overview and comparison of various techniques applicable to predicting energy loads profiles - implementation of selected models - interpretation of results and extracted knowledge The student will focus on some of these topics in more detail. Furthermore, he will propose a suitable technique for load profile prediction based on real-world data. The evaluation of the obtained results and gained experience shall form an important part of the thesis. The thesis will be written in English. |
| References |
| Některé z dostupných základních učebnic, resp. přehledových článků vhodných pro zvolené téma, např.:
- Russell, Stuart Jonathan, et al. Artificial intelligence: a modern approach. Vol. 2. Upper Saddle River: Prentice hall, 2003. - Mitchell, Thomas M. "Machine learning." Mc G raw ill.(forthcoming) (1997). - Haykin, Simon S., et al. Neural networks and learning machines. Vol. 3. Upper Saddle River, NJ, USA:: Pearson, 2009. Články, např: - Datta, D., S. A. Tassou, and D. Marriott. "Application of neural networks for the prediction of the energy consumption in a supermarket." Proceedings of the International Conference CLIMA. 2000. - Neto, Alberto Hernandez, and Flávio Augusto Sanzovo Fiorelli. "Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption." Energy and buildings 40.12 (2008): 2169-2176. - Kalogirou, Soteris A., and Milorad Bojic. "Artificial neural networks for the prediction of the energy consumption of a passive solar building." Energy 25.5 (2000): 479-491. - Sulaiman, S. M., P. Aruna Jeyanthy, and D. Devaraj. "Artificial neural network based day ahead load forecasting using Smart Meter data." Power and Energy Systems: Towards Sustainable Energy (PESTSE), 2016 Biennial International Conference on. IEEE, 2016. |