Spatial electric load forecasting using an evolutionary heuristic
| Autor: | E. M. Carreno, Adriano Galindo Leal, A. Padilha-Feltrin |
|---|---|
| Přispěvatelé: | Universidade Estadual Paulista (Unesp), ELUCID SOLUTIONS |
| Jazyk: | angličtina |
| Rok vydání: | 2010 |
| Předmět: |
Electrical load
Computer science Heuristic Spatial database Evolutionary algorithm land use knowledge extraction computer.software_genre Computer Science Applications Spatial electric load forecasting Knowledge extraction Control and Systems Engineering Scalability Data mining Electrical and Electronic Engineering Representation (mathematics) Preference (economics) computer distribution planning |
| Zdroj: | Sba: Controle & Automação Sociedade Brasileira de Automatica v.21 n.4 2010 Sba: Controle & Automação Sociedade Brasileira de Automatica Sociedade Brasileira de Automática (SBA) instacron:SBA SciELO Repositório Institucional da UNESP Universidade Estadual Paulista (UNESP) instacron:UNESP Sba: Controle & Automação Sociedade Brasileira de Automatica, Volume: 21, Issue: 4, Pages: 379-388, Published: AUG 2010 Scopus-Elsevier |
| ISSN: | 0103-1759 |
| Popis: | Submitted by Guilherme Lemeszenski (guilherme@nead.unesp.br) on 2013-08-22T18:58:38Z No. of bitstreams: 1 S0103-17592010000400005.pdf: 213509 bytes, checksum: fc3fc16f93f4a0a163cddafd7f570dc0 (MD5) Made available in DSpace on 2013-08-22T18:58:38Z (GMT). No. of bitstreams: 1 S0103-17592010000400005.pdf: 213509 bytes, checksum: fc3fc16f93f4a0a163cddafd7f570dc0 (MD5) Previous issue date: 2010-08-01 Made available in DSpace on 2013-09-30T19:54:31Z (GMT). No. of bitstreams: 2 S0103-17592010000400005.pdf: 213509 bytes, checksum: fc3fc16f93f4a0a163cddafd7f570dc0 (MD5) S0103-17592010000400005.pdf.txt: 37213 bytes, checksum: b7760eedc726dcedf070eb83ef17b199 (MD5) Previous issue date: 2010-08-01 Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-20T15:14:11Z No. of bitstreams: 2 S0103-17592010000400005.pdf: 213509 bytes, checksum: fc3fc16f93f4a0a163cddafd7f570dc0 (MD5) S0103-17592010000400005.pdf.txt: 37213 bytes, checksum: b7760eedc726dcedf070eb83ef17b199 (MD5) Made available in DSpace on 2014-05-20T15:14:11Z (GMT). No. of bitstreams: 2 S0103-17592010000400005.pdf: 213509 bytes, checksum: fc3fc16f93f4a0a163cddafd7f570dc0 (MD5) S0103-17592010000400005.pdf.txt: 37213 bytes, checksum: b7760eedc726dcedf070eb83ef17b199 (MD5) Previous issue date: 2010-08-01 A method for spatial electric load forecasting using elements from evolutionary algorithms is presented. The method uses concepts from knowledge extraction algorithms and linguistic rules' representation to characterize the preferences for land use into a spatial database. The future land use preferences in undeveloped zones in the electrical utility service area are determined using an evolutionary heuristic, which considers a stochastic behavior by crossing over similar rules. The method considers development of new zones and also redevelopment of existing ones. The results are presented in future preference maps. The tests in a real system from a midsized city show a high rate of success when results are compared with information gathered from the utility planning department. The most important features of this method are the need for few data and the simplicity of the algorithm, allowing for future scalability. UNESP Faculdade de Engenharia de Ilha Solteira ELUCID SOLUTIONS UNESP Faculdade de Engenharia de Ilha Solteira |
| Databáze: | OpenAIRE |
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