Artículos de revistas
Evaluation of cogeneration alternative systems integrating biomass gasification applied to a Brazilian sugar industry
Fecha
2021-11-01Registro en:
Renewable Energy, v. 178, p. 318-333.
1879-0682
0960-1481
10.1016/j.renene.2021.06.053
2-s2.0-85108668903
Autor
Universidade Estadual Paulista (UNESP)
(Faculty of Mechanical Engineering) Julio Antonio Mella Headquarters
University of Aveiro
Polytechnic Institute of Portalegre
University of Lisbon
Institución
Resumen
This work presents a technical analysis of an Integrated Biomass Direct Gasification/Gas Turbine (BIG-GT) technology within a sugarcane industry to produce electricity and thermal energy (process heat) using bagasse as fuel. Four possible configurations for the implementation of this technology were considered. A sensitivity analysis was made to assess the risks and the uncertainty level for each proposed solution. The results indicated that with the BIG-GT implementation the power generation efficiency increases for all the studied configurations as compared to the conventional system (η = 14.3%). For the configurations I, II, and III the efficiency increase was 9.1%, 11.0% and 12.6%, respectively. However, to support these configurations of the system, the fuel (bagasse) consumption is increased beyond the production capacity of the mill, and the additional amount of bagasse must be acquired to other mills. On the other hand, in configuration IV it is only considered the gasification of the bagasse produced in the mill, being the additional needs of thermal energy for the industrial process supplemented through the combustion of other biomass types (sugarcane straw produced in the mill plantations) in a Heat Recovery Steam Generator. In configuration IV, the electricity generation efficiency is only 5.9% higher than the conventional cycle, this efficiency is getting without the need for an external supply of bagasse. Ultimately, the sensitivity analysis showed that the plant's energy performance with the implementation of BIG-GT technology is particularly sensitive to variations related to the gasifier's efficiency.