سال انتشار: ۱۳۹۳

محل انتشار: کنفرانس بین المللی مهندسی، هنر و محیط زیست

تعداد صفحات: ۱۱

نویسنده(ها):

Hossein lotfi – Islamic university of bojnourd, bojnourd, Iran
Sepehr Soltani – Islamic university of sabzevar, sabzevar, Iran
Toktam Lotfi – Islamic university of gonabad, gonabad, Iran

چکیده:

Wind energy as a source of renewable energy and with the low pollution had a significant growth in recent years. One of the main problems in the use of wind turbines is rapid changes in output power of these turbines. wind power is considered to be a significant alternate source of energy in the times of energy crisis. As wind power penetration increases, power forecasting is crucially important for integrating wind power into a conventional power grid. This paper presents a wind power prediction model based on Feed forward neural network -Genetic algorithm, Available data used by the two stanford and chester sites in usa in 2008 and 2009. These data include wind speed, temperature,output power.