Open AccessOptimization of power output for a wind turbine using methods of artificial intelligence
Author(s) -
Natalia V. Zubova,
V. D. Rudykh
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/552/1/012034
Subject(s) - wind power , turbine , fuzzy logic , control theory (sociology) , power (physics) , convergence (economics) , computer science , mathematical optimization , electric power system , point (geometry) , gaussian , energy (signal processing) , wind speed , control engineering , engineering , mathematics , meteorology , artificial intelligence , statistics , electrical engineering , mechanical engineering , economics , control (management) , physics , geometry , quantum mechanics , economic growth
Percentage of wind energy in worldwide power generation increases year after year. At the present time, problems of increasing the energy efficiency of wind turbines (WT) and optimization of WT power output are of great importance due to instability of wind energy. It stimulates the development, investigation and using of intelligent systems for controlling operating regimes of wind turbines. Such systems also involve those systems that are developed using algorithms based on fuzzy logic. This paper presents the results of investigations devoted to searching for optimal membership functions for fuzzy sets of input and output variables. These variables and membership functions are used in fuzzy algorithms developed for enhancing power output of wind turbines under the given operating conditions. After analyzing the obtained results, it may be concluded that the use of symmetrical Gaussian membership functions gives the fastest convergence of the optimal power into the point.