A new strategy for wind turbine selection using optimization based on rated wind speed

• Published in: Energy procedia 2019-01, Vol.160, p.582-589
• Main Authors: Sedaghat, Ahmad, Alkhatib, Fadi, Eilaghi, Armin, Sabati, Mohamad, Borvayeh, Leila, Mostafaeipour, Ali
• Format: Article
• Language: English
• Subjects: Annual energy production (AEP); Capacity factor; Genetic algorithm; Levelized cost of electricity; Rated wind speed; Wind turbine
• ISSN: 1876-6102; 1876-6102
• DOI: 10.1016/j.egypro.2019.02.209

It is generally anticipated that larger wind turbines result in better electrical power generation in more efficient and economical manner. However, the question remains is that how large a wind turbine is the optimum size for a selected wind site? To answer this, three important objective functions, the levelized cost of electricity (LCOE), the capacity factor (CF) and a normalized annual energy production (AEP) are optimized versus the rated wind speed. Four empirical power curve models for large wind turbines and Weibull wind distribution are investigated to produce a Pareto front within range of practical wind conditions. It is observed that the optimized values of the objective functions are merely dependant on the Weibull shape factor, k. Also, the optimum rated wind speed is a linear function of the Weibull scale factor, c. Therefore, it is concluded that, there are limits for the optimum rated wind power and the costs. Consequently within the Pareto front, the lower rated power wind turbines may be selected to reduce LCOE albeit the higher rated power wind turbines may be adopted to produce higher AEP and CF.