Utilization of Genetic Algorithm to Optimize Biogas Production from Livestock Waste to Use in a CHP Plant in Agricultural Farms.

ABSTRACT

The optimization of biogas production with respect to external influences and various process disturbances is essential for efficient plant operation. However, the optimization of such plants is a challenging issue due the underlying nonlinear and complex digestion processes. One approach to solving this problem is to use the flexibility and power of computational intelligence methods such as Genetic Algorithms (GAs). The present study utilizes GA as tools for simulating and optimizing of biogas production process. Considering the effect of digester operational parameters, such as temperature (T), total solids (TS), volatile fatty acid (VFA), pH and A/TIC-ratio (amount of Acids (A) compared to Total Inorganic Carbon (TIC)), the optimal amount of biogas was converged to be 53910 cubic meters per month. In order to reach the main goals on the energy problems, it is important to study and analyze the distributed CHP plant for agricultural companies and farms. This paper also describes a feasibility study of a biogas CHP (Cogeneration of Heat and Power )plant in a cow farm in Iran. With the developed model, it is specified that using 53,910 cubic meters of biogas, an internal combustion engine with electrical power of 375 kW can be operated continuously. Obtained results illustrated how the utilization of gaseous product from cow farm effluent (biogas) as fuel for heat and power generation can reduce primary energy consumption and its associated costs.