Fereshteh Poorahangaryan - Department of Electrical Engineering, Faculty of Engineering, Ayandegan Institute of Higher Education, Tonekabon, Iran
Ali Shahabi - Department of Industrial Engineering, Faculty of Engineering, Ayandegan Institute of Higher Education, Tonekabon, Iran
Esmaeel Nabiee - M.A of Educational Management, Tonekabon Education Department, Tonekabon, Iran

Energy is an essential parameter for economic–social development and quality of life. Sustainable energy is requisite for any economic growth. Nowadays, new options for producing energy and using technologies in its production are reproducible. So, the choice of technology is very important. In this article, 6 different renewable powers have evaluated using a hybrid model of the Artificial - Neural Network (ANN) and data envelopment analysis base on economic-technical indicators. Because, the low number of inputs and outputs of decision making units, (DMUs), leading to a reduction separable power of DMUs at traditional DEA, so then EURO-DEA was used. The simulation results show that offshore wind energy has higher efficiency rather than other studied energy.

DEA, Artificial Neural Network, Neuro-DEA, Renewable Energy Power