Best suitable cogeneration power for factories from multi-objective data analysis

Abstract

The cogeneration systems in the industrial sector have become an essential part due to their global efficiency and reduced pollution. These systems may operate from conventional fuel sources, as well as from renewable energy sources (biomass, solar, fuel cell). Cogeneration systems could be installed as a distributed generation and onsite generation source in order to take advantage from the produced heat. The utility can motivate factories to install such systems by permitting them to link and sell their residual production capacity to the electrical grid. This work presents a new technique to find the best solution from multiobjective optimization results, using a sensitivity and data analysis method. Genetic Algorithm (GA) optimization method is used with the data analysis method: Multiple Linear Regression (MLR).