| Full text | |
| Author(s): |
Total Authors: 3
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| Affiliation: | [1] Univ State Sao Paulo, UNESP, Dept Elect Engn, Ilha Solteira, SP - Brazil
[2] State Univ West Parana UNIOESTE, Ctr Engn & Math Sci CECE, Iguacu, PR - Brazil
Total Affiliations: 2
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| Document type: | Journal article |
| Source: | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS; v. 67, p. 299-305, MAY 2015. |
| Web of Science Citations: | 9 |
| Abstract | |
The paper presents a spatial analysis of points especially suited to estimate a preference map for new consumers, which is then used as an analytical tool in spatial electric load forecasting. This approach is an exploratory spatial data analysis used to discover useful point patterns in the spatial location of distribution transformers to calculate a preference value for each area, rating it with respect to a hypothetical load change that may occur. We consider the locations of distribution transformers occupied land. Random points are generated in the study area where the new loads are expected; these points are referred to as unoccupied land. The method uses a generalized additive model (GAM) to estimate the probability of unoccupied land becoming occupied land. We test the approach with data from a real distribution system in a mid-size city in Brazil; the result is a preference map that shows the areas where new consumers are most likely to be allocated. The main advantage of this method is the ability work with a small-scale resolution, which enables the use of a resolution suitable for spatial load forecasting method chosen. We test the calculated probabilities in a spatial load forecasting simulation, yielding results with lower spatial error when compared with the heuristic technique. (C) 2014 Elsevier Ltd. All rights reserved. (AU) | |
| FAPESP's process: | 14/06629-0 - SPATIAL LOAD FORECASTING FOR DISTRIBUTION SUBSTATION USING A HYBRID METHOD |
| Grantee: | Joel David Melo Trujillo |
| Support Opportunities: | Scholarships in Brazil - Post-Doctoral |