Parametric Optimization for the Maximization of Hydrogen Production by Enterobacter Cloacae

The decrease of fossil fuel energy induces the development of sustaining renewable energy. One of the potential energy to be further developed is hydrogen energy. Most of the hydrogen resources currently come from fossil fuel energy. Besides, some biological processes also can produce hydrogen such as dark fermentation which is being focused on in this project. Enterobacter cloacae are used as the bacteria to be fermented in the nutrient broth. Since this process has yet to achieve economic sustainability, this project focuses on the maximization of the production of hydrogen gas by optimizing the parameters influencing the hydrogen production. The decision variables (process parameters) are the initial glucose concentration, Inoculum age and also the initial pH of the nutrient broth. By using data from the previous research, the parameters are optimized by using three numerical methods, simulated annealing, pattern search and Genetic algorithm. A comparison between these three algorithms used is done to compare the optimization results and discuss their advantages and disadvantages.