Aplicação de algoritmos de otimização heurística à energia eólica: determinação dos parâmetros da curva de Weibull para duas regiões brasileiras

Detalhes bibliográficos
Ano de defesa: 2018
Autor(a) principal: Macedo, Marcus Vinícius Silveira
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://www.repositorio.ufc.br/handle/riufc/36486
Resumo: Wind power is considered one of the most promising natural sources in the world. The wind farm site construction choice requires a careful study of the site, which includes, as one of the decision parameters, the quality of the wind regime in the region. The wind regime local study reduces wind farms building risk in places with low energy efficiency. The heuristic methods application in optimization for adjustment of Weibull curves, for the characterization of the wind regime, has been shown to be quite effective. In this study, it was tried to evaluate three different Objective Functions, the minimization of the square error sum (E.Q), the error minimization applied to the values of the deviation of production (E.W) and the sum of the them (E.Q.W), select the parameters for each method and compare them with each other, the methods are Particle Swarm (PSO), Harmonic Search (HS), Cuckoo Search Optimization (CSO), Imperialist Competitive Algorithm (ICA), Migrating Birds Optimization (MBO) and Ant Colony Optimization (ACO) with the purpose of finding the shape k and scale c factor parameters factor Weibull distribution that best characterize the regime of winds and the energy production for two data sets from the System of Environmental Data Organization (SONDA) of the cities of Triunfo-PE and São João do Cariri-PB. The performance of the adjustment was evaluated by the Root Mean Square Error (RMSE), Main Absolute Error (MAE), Coefficient of determination (R2) tests and by the Wind Production Deviation (WPD). The objective function (E.Q.W) was selected for the two regions with the exception of the HS method for Pernambuco region whose chosen function was (E.Q). The six methods were compared to each other for the regions of Pernambuco and Paraíba. It was concluded that the Imperialist Competition Algorithm, using the Objective Function (E.Q.W), was the most efficient method to determine the Weibull distribution parameters for the city of Triunfo-PE for presenting the WPD test value of 0.007% and that the ACO method was the least effective for adjusting the Weibull distribution curve for the wind speed data from the Paraíba region using the data analyzed for the city of São João do Cariri, due to the discrepancy of the results in relation to the others and the appearance of the distribution curve in relation to the histogram of the region.