Application of the Mixed Integer Linearized Exergoeconomic (MILE) method with evolutionary optimization to a cogeneration and district heating system
CHALLENGE - A deeper integration among energy systems is expected to significantly contribute to reducing primary energy consumption, as well as global pollutant emissions and energy costs for final users. More recently, the Mixed Integer Linearized Exergoeconomic (MILE) method has been introduced for the optimization of multi-component energy systems. In the present paper, optimizing difficulties are overcome by using a bi-level optimization strategy, where the MILP approach and the system decomposition, that characterize the original MILE formulation, are integrated with a evolutionary algorithm.
SOLUTION - The aim of the work is minimizing the total annual cost of ownership, maintenance and operation of the whole system, as well as reduced CO2 emissions and energy savings. The optimization model takes as reference the consumption of six public buildings in the center of the city of Pordenone, Italy. The objective of this project is the optimization of a complex cogenerative system, which is a highly efficient form of energy conversion combining heat and power production (CHP). The commercial optimization software modeFRONTIER is integrated with FICO® Xpress Optimization Suite.
BENEFITS - The modeFRONTIER software allowed not only to keep the original MILP model but also to explore different numeric optimization tools, in particular the genetic algorithm NSGA-II and the hybrid proprietary algorithm pilOPT. Repeated optimization test runs resulted in the optimal problem solution in less than 15 minutes, with an accurate exploration of the design space. In the case study, the minimum cost solution allows a monetary saving equal of about 53.000 €/ year and a CO2 saving of about 3240 t/year.