Journal
IEEE TRANSACTIONS ON POWER SYSTEMS
Volume 26, Issue 2, Pages 532-540Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2010.2061877
Keywords
Cellular automata; distribution planning; knowledge extraction; land use; spatial electric load forecasting
Categories
Funding
- CNPq [500485/2009-7, 303741/2009-0, TPWRS-00352-2009]
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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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