Recently, the application of the proton exchange membrane fuel cells (PEMFCs) is extensively increasing as a popular renewable energy source. PEMFCs need low temperature for the operation along with high power density and easy implementation ability. These characteristics turned them into the...

Parameter identification of the proton exchange membrane fuel cell (PEMFC) is a good way of increasing their efficiency in the next designs. In this study, an optimized improved Elman neural network based on a new hybrid optimization algorithm is proposed for this purpose. The proposed algorithm...

Model-identification and parameter extraction of the proton exchange membrane fuel cell (PEMFC) is a well-defined procedure for improving the PEMFC efficiency for designing and control purposes. This paper presents a new version of the improved fluid search optimization algorithm for optimal...

In this paper, a multi-objective optimization method has been established on a hybrid PV, wind, fuel cell, and battery system. The optimization is based on three models including energy supply reliability, electricity efficiency, and capital cost of the hybrid system. A new model of the Elephant...