10.1007/s40095-018-0285-5

Four heuristic optimization algorithms applied to wind energy: determination of Weibull curve parameters for three Brazilian sites

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  • Carla Freitas de Andrade1,
  • Lindemberg Ferreira dos Santos1,
  • Marcus V. Silveira Macedo*1,
  • Paulo A. Costa Rocha1,
  • Felipe Ferreira Gomes1,
  1. Mechanical Engineering Department, Federal University of Ceará, Fortaleza, Ceará, BR
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Published in Issue 2018-09-26

How to Cite

Freitas de Andrade, C., Ferreira dos Santos, L., Silveira Macedo, M. V., Costa Rocha, P. A., & Ferreira Gomes, F. (2018). Four heuristic optimization algorithms applied to wind energy: determination of Weibull curve parameters for three Brazilian sites. International Journal of Energy and Environmental Engineering, 10(1 (March 2019). https://doi.org/10.1007/s40095-018-0285-5
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Abstract

Abstract Minimizing errors in wind resource analysis brings significant reliability gains for any wind power generation project. The characterization of the wind regime is one of fundamental importance, and the two parameters Weibull distribution is the most applied function for it. This study aims to determine the scale and shape factor in an attempt to establish acceptable criteria to a better utilization of wind power in the states of Pernambuco and Rio Grande do Sul, which is a national prominence in the use of renewable sources for electricity generation in Brazil. The following heuristic optimization algorithms were applied: Harmony Search, Cuckoo Search Optimization, Particle Swarm Optimization and Ant Colony Optimization. The fit tests were performed with data from the Brazilian Federal Government’s SONDA (National System of Environmental Data Organization) project, referring to Triunfo, Petrolina and São Martinho da Serra, states of Pernambuco and Rio Grande do Sul, cities in the northeast and south regions of Brazil, during the period of 1 year. The tests were made in 2006 and 2010, all at 50 m from ground level. The results were analyzed and compared with those obtained by the maximum likelihood method, moment method, empirical method and equivalent energy method, methods that presented significant results in regions with characteristics similar to the regions studied in this study. The performance of each method was evaluated by the RMSE (root mean square error), MAE (mean absolute error), R 2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^2$$\end{document} (coefficient of determination) and WPD (wind production deviation) tests . The statistical tests showed that ACO is the most efficient method for determining the parameters of the Weibull distribution for Triunfo and São Martinho da Serra and CSO is the most efficient for Petrolina.

Keywords

  • Wind energy,
  • Weibull distribution,
  • Heuristic,
  • Cuckoo search optimization,
  • Particle swarm optimization,
  • Ant colony optimization
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