Dual stage approach for optimal sizing and siting of fuel cell in distributed generation systems

This paper addresses the challenges in localizing and determining the sizing of fuel cells to connect to distributed generation systems. To handle the problem, dual stage intelligent methodology is adopted in the paper. In the first stage, the neural network is exploited to determine the optimal location, whereas the second stage determines the optimal sizing for fuel cells is done by Artificial Bee Colony (ABC) algorithm. An improved version of ABC is proposed to determine the optimal sizing (in combination with the network). The proposed methodology is experimented with four IEEE benchmark test bus systems and compared with five conventional algorithms. The results demonstrate the superior performance of the proposed methodology. Finally, the simulation results revealed that the proposed method is superior to the other conventional methods.