Optimal design of integrated electric-power an algal biofuel generation systems
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abstract
This paper presents a multi-objective optimization methodology to determine simultaneously, the optimal design of steam power plants, considering simultaneously economic and environmental criteria, in addition to capturing the CO 2 from the combustion of different fossil fuels (coal, oil and natural gas) and biofuels (biogas, biomass, softwood and hardwood) selected in the boiler for the production of microalgae and the subsequent biomass conversion to biofuel (biodiesel), also part of this algal biomass produced is used as biofuel in the boiler. This system allows the sustainable reduction of the huge CO 2 emissions in the power plants. The methodology considers the optimal selection of the type of fuel to be used because this affects drastically and simultaneously the economic and environmental functions. The methodology is based on a search procedure through genetic algorithms due to the large number of non-convex terms present and to avoid being trapped in local solutions. The environmental objective function is based on the eco-indicator 99 constituted by harmful materials for the health and the ecosystem to measure the global environmental impact of these systems, following the approach of life cycle analysis (LCA), while the economic objective function considers the maximization of gross annual profit, which includes the profit from the electricity produced, tax credit obtained by the reduction of GHG emissions, the revenue generated by the production of biodiesel, and consider the total annual cost including the fuel costs, turbine, boiler, condenser, pumps, feed-water heaters and deaerator, as well as the costs to operate such equipment (fuel, electricity, cooling water, etc.). To show the applicability of the proposed methodology is considered a case study in Mexico. The results are shown through Pareto curves that help to identify a set of optimal solutions that show the relationship between economic and environmental objectives. The problem can be easily solved using the proposed methodology in a relatively small computation time.
