AUTHORS: Wei Sun, Yi Liang, Minquan Ye

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ABSTRACT: With the development of the of China's electric power system, wind power, as a clean energy, can be used to optimize the structure of electrical energy, thus can largely reduce the emission of pollutants and contribute to the sustainable development of the national economy. In wind power projects, scientific and rational choice for the wind turbine generator in actual wind farm is the core part, and it is directly related to the economic benefits of wind power projects. This paper analyze the status of current wind power capacity in global and China and reveals the regularity of the growing proportion of wind power in future energy. On this basis, this paper determines the comprehensive evaluation system of wind turbine generator selection and establishes a comprehensive evaluation model based on BP neural network which optimized by particle swarm optimization. A specific example verifies the validity of the proposed method, thus can provide guidance of the evaluation of the wind turbine generators selection in wind farms.

KEYWORDS: Wind turbine generators selection, Comprehensive evaluation, BP neural network, Particle swarm optimization, Parameter optimization

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