{"id":349,"date":"2016-07-14T14:29:56","date_gmt":"2016-07-14T17:29:56","guid":{"rendered":"https:\/\/sbia.org.br\/lnlm\/?page_id=349"},"modified":"2016-07-14T14:29:56","modified_gmt":"2016-07-14T17:29:56","slug":"vol4-no1-art1","status":"publish","type":"page","link":"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol4-no1\/vol4-no1-art1\/","title":{"rendered":"Otimiza\u00e7\u00e3o De Despacho Econ\u00f4mico Com Ponto De V\u00e1lvula Usando Estrat\u00e9gia Evolutiva E M\u00e9todo Quase-Newton"},"content":{"rendered":"<p><strong>T\u00edtulo:<\/strong> Otimiza\u00e7\u00e3o De Despacho Econ\u00f4mico Com Ponto De V\u00e1lvula Usando Estrat\u00e9gia Evolutiva E M\u00e9todo Quase-Newton<\/p>\n<p><strong>Autores:<\/strong> Coelho, Leandro dos Santos; Mariani, Viviana Cocco<\/p>\n<p align=\"justify\"><strong>Resumo:<\/strong> Os algoritmos evolutivos (AEs) s\u00e3o fundamentados em m\u00e9todos de otimiza\u00e7\u00e3o e de busca estoc\u00e1stica, baseados nos princ\u00edpios e modelos da evolu\u00e7\u00e3o biol\u00f3gica natural (sistemas bioinspirados), destacam-se pelo crescente interesse recebido, nas \u00faltimas d\u00e9cadas, devido principalmente a sua versatilidade para a resolu\u00e7\u00e3o de problemas complexos de otimiza\u00e7\u00e3o. As estrat\u00e9gias evolutivas s\u00e3o uma alternativa potencial de AE para a resolu\u00e7\u00e3o de problemas de otimiza\u00e7\u00e3o cont\u00ednua na \u00e1rea de sistemas de pot\u00eancia. As estrat\u00e9gias evolutivas utilizam como operador principal a muta\u00e7\u00e3o, que trabalha diretamente com vetores de valores reais (ponto flutuante) e permite a auto-adapta\u00e7\u00e3o dos par\u00e2metros da estrat\u00e9gia atrav\u00e9s de desvio padr\u00e3o e covari\u00e2ncias. Este artigo apresenta uma abordagem h\u00edbrida de estrat\u00e9gia evolutiva (Evolution Strategies, ES) combinada ao m\u00e9todo quase-Newton (QN) do tipo BFGS (Broyden-Fletcher-Goldfarb-Shanno) para busca local. Esta proposta de metodologia h\u00edbrida de otimiza\u00e7\u00e3o \u00e9 validada em tr\u00eas problemas de despacho econ\u00f4mico de energia el\u00e9trica considerando ponto de v\u00e1lvula. Os sistemas testados consistem de 3, 13 e 40 unidades geradoras. Quando comparados os resultados obtidos pela metodologia h\u00edbrida, observa-se que esta supera em termos de qualidade as melhores solu\u00e7\u00f5es apresentadas na literatura para estes problemas de despacho econ\u00f4mico de energia el\u00e9trica.<\/p>\n<p><strong>Palavras-chave:<\/strong> Algoritmos evolutivos; estrat\u00e9gia evolutiva; sistemas de pot\u00eancia; despacho econ\u00f4mico de energia el\u00e9trica; quase-Newton<\/p>\n<p><strong>P\u00e1ginas:<\/strong> 12<\/p>\n<p><strong>C\u00f3digo DOI:<\/strong> <a href=\"http:\/\/dx.doi.org\/10.21528\/lnlm-vol4-no1-art1\">10.21528\/lmln-vol4-no1-art1<\/a><\/p>\n<p><strong>Artigo em PDF:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2016\/07\/vol4-no1-art1.pdf\" rel=\"\">vol4-no1-art1.pdf<\/a><\/p>\n<p><strong>Arquivo BibTex:<\/strong> <a href=\"https:\/\/sbia.org.br\/lnlm\/wp-content\/uploads\/sites\/4\/2016\/07\/vol4-no1-art1.bib\" rel=\"\">vol4-no1-art1.bib<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>T\u00edtulo: Otimiza\u00e7\u00e3o De Despacho Econ\u00f4mico Com Ponto De V\u00e1lvula Usando Estrat\u00e9gia Evolutiva E M\u00e9todo Quase-Newton Autores: Coelho, Leandro dos Santos; Mariani, Viviana Cocco Resumo: Os algoritmos evolutivos (AEs) s\u00e3o fundamentados em m\u00e9todos de otimiza\u00e7\u00e3o e de busca estoc\u00e1stica, baseados nos <a href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol4-no1\/vol4-no1-art1\/\" class=\"read-more\">Read More &#8230;<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":316,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-349","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Otimiza\u00e7\u00e3o De Despacho Econ\u00f4mico Com Ponto De V\u00e1lvula Usando Estrat\u00e9gia Evolutiva E M\u00e9todo Quase-Newton - Learning and NonLinear Models<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sbia.org.br\/lnlm\/publicacoes\/vol4-no1\/vol4-no1-art1\/\" \/>\n<meta property=\"og:locale\" content=\"pt_BR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Otimiza\u00e7\u00e3o De Despacho Econ\u00f4mico Com Ponto De V\u00e1lvula Usando Estrat\u00e9gia Evolutiva E M\u00e9todo Quase-Newton - Learning and NonLinear Models\" \/>\n<meta property=\"og:description\" content=\"T\u00edtulo: Otimiza\u00e7\u00e3o De Despacho Econ\u00f4mico Com Ponto De V\u00e1lvula Usando Estrat\u00e9gia Evolutiva E M\u00e9todo Quase-Newton Autores: Coelho, Leandro dos Santos; 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