Multi-objective optimization and sensitivity analysis of a cogeneration system for a hospital facility
CHALLENGE - The achievement of optimal energetic and economic results through combined heat and power plants is a complex problem and are recognized as very effective solutions to meet the increasingly stringent requirements in primary energy savings. This paper addresses the use of a specifically developed methodology to conduct several analyses on the basis of the loads of a specific hospital facility and through the study of the cogeneration system-user interaction.
SOLUTION - Predictive analyses are carried out using a multi-objective approach to find optimized plant configurations that approach the best energetic results while ensuring a reasonable profit. The two objective functions are maximization of TPES (total primary energy supply) and minimization of SPB (simple payback period). In order to find optimum solutions (engine size, plant configuration, management logic, engine number, etc.), a multi-objective optimization approach was used. The analysis was conducted using the algorithm MOGA II, belonging to the class of genetic methods and implemented in the optimization software modeFRONTIER. Finally, a sensitivity analysis was carried out to evaluate the robustness and reliability of the calculated results.
BENEFITS - The plant configurations and management strategies analyzed in this work, liable to further improvements, indicate primary energy savings over 17% for hospital facilities along with SPB of approximately 3.5 years for multi-gas engine solutions. The result is even more interesting considering that the load variability in the civil sector often affects the potential benefits of combined heat and power.