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This area proposes about the optimal location for fixing fuel cells in a distribution system by an innovative technique. The innovation of this method is the combined performance of the Genetic Algorithm and Artificial Intelligence (RNN) technique, thus integrating GA in two stages and Artificial Intelligence (RNN) technique. The optimum placement of fuel cell is attained by the GA first stage (Mohammadi and Nasab in Res J Appl Sci Eng Technol 3:838–842, 2011 [1]). The RNN is suitably trained by the target fuel cell size and the corresponding inputs such as load variation and bus number. The main objective helps to enhance the bus voltage profile and reduce power loss (Zayandehroodi et al. in Int J Phys Sci 6:3999–4007, 2011 [2]). Thus, this approach is implemented in MATLAB/simulink. Its performance is evaluated by comparing different methods like GA, PSO and other hybrid PSO techniques (Mohammadi and Nasab in Res J Appl Sci Eng Technol 2:832–837, 2011 [3]). The comparison result is explicitly demonstrated the supremacy of this method and confirm its sterling potentiality to solve the problem (Chowdhury et al. in IEEE Trans Ind Appl 39:1493–1498, 2003 [4]). |
