Prediction of Power Generation of Wind Turbine Using Fuzzy Logic


Excerpts From the Project

Energy is the essential input for the national development in the form of mechanical power or any other. It has major contribution for improving the quality of life and enhancing economic growth. In addition to conventional energy resources, renewable energy can also play a vital role for energy demand, of which wind energy is one. Wind energy is the kinetic energy associated with the movement of atmospheric air. It has been used for hundreds of years for sailing, grinding grain, and for irrigation.

Wind energy systems for irrigation and milling have been in use since ancient times and since the beginning of the 20th century it is being used to generate electric power. Windmills for water pumping have been installed in many countries particularly in the rural areas. Electrical power generation is a fast-growing source of clean power production from wind in large, relatively remote wind farms which is then transferred to residential and commercial places. The total amount of electricity that could potentially be generated from wind in the United States has been estimated at 10,777 billion kWh annually.
 Power generation by wind velocity is a complex process with many interacting factors. For this reason, mathematical models have been developed to help to understand this phenomenon. At present, various techniques in soft computing such as statistics, machine learning, neural network and fuzzy data analysis are being used for exploratory data analysis. Fuzzy Logic has been applied successfully to a large number of expert applications. Fuzzy expert system, a relatively new, intelligent, knowledge based technique performs exceptionally well in non linear, complex systems. 
Fuzzy set theory is an artificial intelligence technique that makes use of fuzzy sets and fuzzy ‘linguistic’ rules to incorporate this uncertainty into the model. Classical set theory can be extended to handle partial memberships, enabling to express vague human concepts using fuzzy sets and also describe the corresponding inference systems based on fuzzy rules.
Project Courtesy :
Amrutha N
Sruthy Dileep
KrishnaPriya Unnikrishnan

Leave a Reply

Your email address will not be published. Required fields are marked *