Journal Menu
Related Events
Computational Research Progress in Applied Science and Engineering
CRPASE 2019, 5(2), 34-43
An Intelligent Power Prediction Method for Wind Energy Generation Based on Optimized Fuzzy System
Department of Electrical Engineering, Sirjan Branch, Islamic Azad University, Sirjan, Iran
Faculty of Electrical and Computer Engineering, Babol Noshirvani University of Technology, Babol, Iran
ABSTRACT
Due to the increasingly significant energy crisis nowadays, the exploitation and utilization of new clean energy gain more and more attention. As an important category of renewable energy, wind power generation has become the most rapidly growing renewable energy in the world. However, the intermittency and volatility of wind power have restricted the large-scale integration of wind turbines into power systems. High-precision wind power forecasting is an effective measure to alleviate the negative influence of wind power generation on the power systems. In this paper, an intelligent forecasting method based on fuzzy systems is proposed to wind energy generation prediction. The proposed method includes two main modules: The forecasting module and the optimization module. In the forecasting module, an adaptive neuro-fuzzy inference system is used for prediction. In the adaptive neuro-fuzzy inference system, the value of the radii vector has a great effect on system performance and there is no systematic way to select the optimal value of the radii vector. For this purpose, in the second module, we used the chaotic bat swarm optimization algorithm to select the optimal radii vector. The proposed method is tested on real data and obtained results show that the proposed method has excellent performance.