Artificial intelligence in smart grids
Thesis title in Czech: | Artificial intelligence in smart grids |
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Thesis title in English: | Artificial intelligence in smart grids |
Academic year of topic announcement: | 2016/2017 |
Thesis type: | dissertation |
Thesis language: | |
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: | 22.09.2017 |
Date of assignment: | 22.09.2017 |
Confirmed by Study dept. on: | 03.10.2017 |
Guidelines |
One of the problems Smart Grid faces is forecasting energy consumption of a household. Reliable forecasts can be used by specialized algorithms to anticipate peak consumptions and prevent penalties imposed by electricity companies on exceeding the limit previously agreed in energy supply contract. A common approach to all of the aforementioned problems in Smart Grid is time series analysis. There is a number of techniques frequently used in time series analysis. The student should focus on a selection of state-space models and machine learning methods, and their advantages and disadvantages. |
References |
James Douglas Hamilton.Time series analysis, volume 2. Princeton university press, 1994
Ryszard S Michalski, Jaime G Carbonell, and Tom M Mitchell. Machine learning: An artificial intelligence approach. Springer Science & Business Media, 2013. A Sfetsos and AH Coonick. Univariate and multivariate forecasting of hourly solar radiation with artificial intelligence techniques. Solar Energy, 68(2):169--178, 2000. Amir-Hamed Mohsenian-Rad, Vincent WS Wong, Juri Jatskevich, Robert Schober, and Alberto Leon-Garcia. Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE transactions on Smart Grid, 1(3):320--331, 2010. Recent papers published in impacted journals, e.g. Data Mining and Knowledge Discovery, IEEE Transactions on Knowledge and Data Engineering, Machine Learning, IEEE transactions on smart grid |