Review of Literature on Strategies for the Extraction of Maximum Power in Wind Energy Conversion Systems

Alternative energy sources have become a good choice of generation friendly to nature. An example of this is the wind power that takes advantage of the mass flow of air; This movement is due to the solar radiation being absorbed by the atmosphere and transformed into kinetic energy. This type of energy is classified as clean energies. With the invention of the dynamo formally appears the wind turbine and, by the end of the nineteenth century, with the invention of the induction motor. By 2014, wind energy in the European Union achieved the highest growth rate of all new electrical installations, reaching 43.7% and 55.3% of all new renewable energy installations. By 2020, wind power can supply about 12% of the total energy demanded worldwide. The benefits offered by wind energy conversion systems are evaluated according to their ability to convert wind kinetic energy into electrical energy. For this purpose, it is necessary to extract the maximum energy at any speed. This challenge requires maintaining the speed of the generator a rotation speed such that it corresponds to the optimum point of the operation of the system. Through the years, mechanical and electromechanical control strategies have been developed, and solutions have been introduced in recent years based on computational intelligence, neural networks and diffuse logic. This article discusses the state of the art review of strategies for the extraction of maximum power in wind turbines, highlighting the advantages and disadvantages presented by the different methods. In the first part, a classification of the aerogenerators is made according to the volume and the weight, swept area and power generated. In the second part, the state of the art is reviewed for the maximum power point tracking algorithms, the available types and their implementations. In the third part, it reviews the application of computational intelligence strategies in the extraction of power in wind energy conversion systems. Finally, a review of the tools used in the simulation and performance evaluation of these wind energy conversion systems is shown.