Modeling and Design Optimization of Variable-Speed Wind Turbine Systems


Eminoglu U., Ayasun S.

ENERGIES, cilt.7, sa.1, ss.402-419, 2014 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 7 Sayı: 1
  • Basım Tarihi: 2014
  • Doi Numarası: 10.3390/en7010402
  • Dergi Adı: ENERGIES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.402-419
  • Anahtar Kelimeler: cost of energy, design optimization, modeling, wind turbine systems, NONLINEAR CONTROL
  • Gazi Üniversitesi Adresli: Hayır

Özet

As a result of the increase in energy demand and government subsidies, the usage of wind turbine system (WTS) has increased dramatically. Due to the higher energy production of a variable-speed WTS as compared to a fixed-speed WTS, the demand for this type of WTS has increased. In this study, a new method for the calculation of the power output of variable-speed WTSs is proposed. The proposed model is developed from the S-type curve used for population growth, and is only a function of the rated power and rated (nominal) wind speed. It has the advantage of enabling the user to calculate power output without using the rotor power coefficient. Additionally, by using the developed model, a mathematical method to calculate the value of rated wind speed in terms of turbine capacity factor and the scale parameter of the Weibull distribution for a given wind site is also proposed. Design optimization studies are performed by using the particle swarm optimization (PSO) and artificial bee colony (ABC) algorithms, which are applied into this type of problem for the first time. Different sites such as Northern and Mediterranean sites of Europe have been studied. Analyses for various parameters are also presented in order to evaluate the effect of rated wind speed on the design parameters and produced energy cost. Results show that proposed models are reliable and very useful for modeling and optimization of WTSs design by taking into account the wind potential of the region. Results also show that the PSO algorithm has better performance than the ABC algorithm for this type of problem.