Improve the Prediction of Wind Speed using Hyperbolic Tangent Function with Artificial Neural Network

Abstract

India is truculent to meet the electric power demands of a fast-expanding economy. Restructuring of the power industry has only increased several challenges for the power system engineers. The two largest challenges facing the Indian power sector are: Fuel supply uncertainty and deteriorating distribution companies (discoms) finances. Considering dominance of coal in India's fuel mix, coal shortages can severely impede investments in the generation segment. India is aiming to attain 175 GW of renewable energy which would consist of 100 GW from solar energy, 10 GW from bio-power, 60 GW from wind power, and 5 GW from small hydropower plants by the year 2020. Investors have promised to achieve more than 270 GW, which is significantly above the ambitious targets. Wind energy generation, at present facing many problems like wind speed prediction. In this paper to improve the wind speed prediction by using hyperbolic tangent function with artificial neural network. Hyperbolic tangent with artificial neural network, we know that ANN work like a human brain to perform computations on real time or hyperbolic tangent function lies between 1 to -1 would be near the zero.