Desenvolvimento de modelos e algoritmos sequenciais e paralelos para o planejamento da expansão de sistemas de transmissão de energia elétrica / Development of mathematical models, sequential and parallel algorithms for transmission expansion planning


IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia




The main objective of this study is to propose a new methodology to deal with the long-term transmission system expansion planning with multiple generation dispatch scenarios problem (TEP-MDG). With the methodology proposed in this thesis we aim to build expansion plans with minimum investment cost and also capable of meeting the new demands of modern electrical systems, such as uncertainty about the future generation scenarios and congestion in the transmission systems. By modeling the TEP-MDG aiming to build transmission networks that circumvent the uncertainties regarding the future generation scenarios and simultaneously minimize the cost of investment for transmission networks expansion, the planner faces a multiobjective optimization problem. One can find various algorithms that aim to deal with multiobjective problems in the literature of operations research. In this thesis, we apply two of these algorithms: Nondominated Sorting Genetic Algorithms-II (NSGA-II) and SPEA2: Strength Pareto Evolutionary Algorithm (SPEA2). In a first analysis, we have found that the most critical issue with the TEP-MOG is the high computational demand. Therefore, in order to circumvent this difficulty we have implemented parallel versions of the sequential algorithms tested. In performed tests, the parallel algorithms have found solutions of superior quality than the solutions found by the sequential algorithms. In this thesis we also show that optimal solutions considering only the classical least cost objective are unable to meet the electric power systems new demands. Tests have been performed and analyzed in this work. By considering the methods known in the literature convinced to measure the quality of solutions found by multiobjective algorithms, we concluded that the proposed approach to TEP-MDG may be feasible from the point of view of both engineering and computational mathematics.


algoritmos multiobjetivos evolutionary algorithms metaheurísticas multiple generation dispatch scenarios múltiplos cenários de geração optimization otimização parallel programming planejamento de sistemas de transmissão programação paralela transmission systems expansion planning metaheuristics

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