چکیده مقاله
The electricity production of wind farms is fluctuating because its dependency on the wind speed, so, improving of technical and economic integration of wind energy into the electricity supply system requires improving wind speed prediction accuracy This paper deals with a neural network approach for Short term wind speed forecasting Now a day, short term wind speed forecasts have become gradually more important for the power system management or energy trading due to the large penetration of wind power technology and development of wind energy markets In this new era, short term wind speed forecasting is necessary for producers and consumers to become stable in the electricity market as in the electricity grid at any moment balance must be maintained between electricity consumption and generation In this paper, a multi layere perceptron MLP neural network, trained by the back propagation learning algorithm has been used for hourly forecasting of wind speed in the region of Khoram Abad
کلیدواژهها
نویسندگان
Alireza Rostami
Student of Power engineering, Islamic Azad University, Imam Khomemni branch, Borujerd, Iran
Peyman Naderi MeyAbadi
Assistant professor of Shahid Rajaee Teacher Training University, Tehran, Iran
Mehdi Nikzad
Department of Electrical Engineering, Islamshahr Branch, Islamic Azad University, Tehran, Iran
شیوه ارجاع
Rostami, Alireza and Naderi MeyAbadi, Peyman and Nikzad, Mehdi,1395,Wind speed forecasting using Multi-Layer Perceptron (MLP) neural network,2nd National Congress of Electrical and Computer Engineering of Iran,Ramsar
ارائهشده در
مجموعه مقالات دومین کنفرانس بین المللی یافته های نوین پژوهشی در مهندسی برق و علوم کامپیوتر24 اردیبهشت 1395 · رامسر