Livros e capítulo

URI permanente para esta coleçãohttps://rigalileo.itegam.org.br/handle/123456789/6

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2018 - 201912020 - 20232

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Autor: search.filters.author.NASCIMENTO, Manoel Henrique ReisTem arquivos: Sim

Resultados da Pesquisa

Agora exibindo 1 - 3 de 3
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    Optimization of Economic and Environmental Dispatch Using Bio-inspired Computer Metaheuristics
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2023) NASCIMENTO, Manoel Henrique Reis; CAMPOS, Paola Souto
    This chapter addresses the optimization of economic and environmental dispatch in electric power systems using bio-inspired computational metaheuristics. Techniques such as Genetic Algorithms, Particle Swarm Optimization, and Ant Colony-Based Algorithms are analyzed. The study demonstrates how these approaches can reduce operational costs and minimize environmental impacts, ensuring energy efficiency and sustainability.
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    Multi-Objective Optimization Techniques to Solve the Economic Emission Load Dispatch Problem Using Various Heuristic and Metaheuristic Algorithms
    (IntechOpen, 2018) NASCIMENTO, Manoel Henrique Reis; LEITE, Jandecy Cabral
    The chapter addresses the economic emission load dispatch problem, focusing on minimizing emission levels and total generation cost in thermal power plants. Various multi-objective optimization techniques, including heuristic and metaheuristic algorithms such as Simulated Annealing, Ant Lion, Dragonfly, NSGA II, and Differential Evolution, are analyzed. The chapter also compares the effectiveness of these approaches through a case study applied to a thermal generation plant.
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    Different Deterministic Optimization Methods for Economic Load Dispatch, Switching Off Less Efficient Generators
    (Instituto de Tecnologia e Educação Galileo da Amazônia, 2023) NASCIMENTO, Manoel Henrique Reis; ALENCAR, David Barbosa de
    This chapter discusses different deterministic optimization methods applied to economic load dispatch, focusing on switching off less efficient generators. The study investigates the efficiency of methods such as linear programming, quadratic programming, and other mathematical approaches to reduce operational costs and improve energy efficiency in power generation systems. The research highlights how optimization can contribute to more cost-effective and environmentally friendly decision-making, proposing strategies to integrate these methodologies into power generation systems.