Title :
Cogeneration systems for industrial sector: An optimal power
Author :
Al Asmar, Joseph ; Kouta, Raed ; Laghrouche, Salah ; El Assad, Joseph ; Wack, Maxime
Author_Institution :
OPERA Lab., Univ. of Technol. of Belfort-Montbeliard, Belfort-Montbeliard, France
Abstract :
Today´s industrial sector depends more and more upon cogeneration systems 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 is installed as a distributed generation and on-site generation source to profit from the produced heat. The utility can motivate factories to install such systems by permitting them to link their residual production capacity to the electrical grid. This work presents a study concerning the optimized cogeneration capacity to be installed in a factory. Genetic algorithm (GA) optimization method is then used with a sensitivity analysis to find a compromise between the economic and the environmental issues.
Keywords :
cogeneration; distributed power generation; genetic algorithms; industrial power systems; power generation economics; power grids; regression analysis; sensitivity analysis; GA optimization method; cogeneration systems; conventional fuel sources; distributed generation; economic issues; electrical grid; environmental issues; genetic algorithm optimization method; industrial sector; on-site generation source; optimized cogeneration capacity; renewable energy sources; residual production capacity; sensitivity analysis; Cogeneration; Economics; Genetic algorithms; Optimization; Pollution; Production facilities; Sensitivity analysis; cogeneration systems integration; combined heat and power (CHP); energy management; genetic algorithm (GA); multiple linear regression; sensitivity analysis; smart-grid;
Conference_Titel :
Control Applications (CCA), 2014 IEEE Conference on
Conference_Location :
Juan Les Antibes
DOI :
10.1109/CCA.2014.6981415
