Parameter optimization of the biohydrogen real time power generating system using differential evolution algorithm

By comparing the differential evolution and genetic algorithms, this study attempts to optimize estimation of a biohydrogen real time power generating system in which circuit parameters fluctuate with operating temperature and current density. Based on uses of the differential evolution algorithm method, optimal estimation of the circuit parameters is achieved by data from a V–I characteristic experiment on the proposed biohydrogen real time power generating system. The circuit feature is then solved by formulating the estimated circuit parameters based on Kirchhoff’s law to elucidate its feature of the biohydrogen real time power generating system and results show that DE is faster than GA and more accurate. Next, the estimated V–I characteristics are compared with measurement results to demonstrate the feasibility of the proposed method.