Energy consumption increases gradually due to the rapid advancement in the industrial sectors; increase in population and also due to fast growing of urbanization. The conventional energy sources which include power plants using fossil fuels are widely used as a source of energy all over the world so far. As these conventional energy sources used nowadays are coming to an end in a near future, the sustainability of power supplies is one of the most challenging issues that the world faces today. To overcome the increasing power demand and depletion of conventional energy sources around the world, the use of clean, non-polluting and renewable energy is very important. Global warming and environmental pollution are major challenges to the earth's safety and security. Wind energy has become a best alternative of traditional fossil fuel power plants with the successful operation of multi-megawatt sized wind turbines. The fluctuating and unpredictable nature of wind is the major problem in harnessing wind energy. So, it is very important to improve the operation of wind turbine for its safety and better efficiency of wind energy harvesting system. Several methods have been used to improve the quality and efficiency of wind power system. An Adaptive Neuro-Fuzzy Inference System (ANFIS) model was used by many researchers to control factors affecting wind and predict the power output from wind to increase the efficiency of the WEHS. This review paper focuses on wind energy systems to develop a model to produce optimal energy components for a typical rural community for minimizing the total net present cost of the system through the life time of the project.
Renewable Energy, Wind Energy Harvesting System (WEHS), Wind turbines
