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URI permanente para esta coleçãohttps://rigalileo.itegam.org.br/handle/123456789/219
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Item Planning Passive Filters using NSGA II for Industry Applications(INSTITUTO DE TECNOLOGIA, 2014) LEITE, Jandecy Cabral; SILVA, Waterloo Ferreira da; CASTRO, Anderson de Oliveira; NOGUEIRA, Rildo de Mendonça; AZEVEDO, Manoel Socorro Santos; Prof. Dra. ADRIANA RIBEIRO CARNEIRO FOLADORThis paper presents a multi-objective optimization approach for planning passive harmonic filters in industrial systems using the NSGA-II genetic algorithm. The method maximizes reactive power compensation benefits, minimizes harmonic distortion in the PCC current and bus voltages, and complies with power quality standards. The algorithm determines the filters' location, configuration, and parameters, demonstrating effectiveness in a practical example.Item Despacho Econômico e Ambiental de Energia Elétrica Usando Técnicas Computacionais em LabVIEW: Uma Abordagem Multiobjetivo para Sistemas de Geração Termelétrica(INSTITUTO DE TECNOLOGIA, 2013) AZEVEDO, Raimundo Edney dos Santos; BEZERRA, Ubiratan Holanda; LEITE, Jandecy Cabral; AZEVEDO, Manoel Socorro Santos; NETO, Vilmar Domingos da Silva; MAGALHÃES, Edilson MarquesThis paper proposes an analytical strategy based on mathematical models to address the load dispatch problem in thermal power plants, simultaneously considering economic and environmental criteria. Using the computational tool LabVIEW, the study develops a multi-objective model that minimizes operational costs and pollutant emissions (SO₂ and NOₓ) while meeting energy demand. The results demonstrate the approach's effectiveness across different load scenarios, highlighting solutions that balance energy efficiency and environmental impact reduction.Item Optimización Multiobjetivo de Filtros Pasivos(INSTITUTO DE TECNOLOGIA, 2012) LEITE, Jandecy Cabral; ABRIL, Ignacio Pérez; TOSTES, Maria Emilia de Lima; OLIVEIRA, Roberto Celio Limão de; MAGALHÃES, Edilson MarquesDifferent approaches have been used to formulate the problem of passive filter design, classified into single or multi-objective formulations. While previous contributions solve the multi-objective problem by minimizing a single objective function composed of a weighted sum of sub-objectives, this work uses the Non-dominated Sorting Genetic Algorithm (NSGA-II) to address the problem. The developed program determines the number, location, configuration, and parameters of passive filters required to obtain non-dominated optimal solutions, considering four predefined filter types. The solution of a practical example demonstrates the effectiveness of the proposed procedure.