Publication: A Cellular Automaton Approach to Spatial Electric Load Forecasting
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Coadvisor
Graduate program
Undergraduate course
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Volume Title
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Type
Article
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Abstract
A method for spatial electric load forecasting using a reduced set of data is presented. The method uses a cellular automata model for the spatiotemporal allocation of new loads in the service zone. The density of electrical load for each of the major consumer classes in each cell is used as the current state, and a series of update rules are established to simulate S-growth behavior and the complementarity among classes. The most important features of this method are good performance, few data and the simplicity of the algorithm, allowing for future scalability. The approach is tested in a real system from a mid-size city showing good performance. Results are presented in future preference maps.
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Keywords
Cellular automata, distribution planning, knowledge extraction, land use, spatial electric load forecasting
Language
English
Citation
IEEE Transactions on Power Systems. Piscataway: IEEE-Inst Electrical Electronics Engineers Inc, v. 26, n. 2, p. 532-540, 2011.
