OPTIMISATION OF BIOMASS FUELLED GAS TURBINES USING GENETIC ALGORITHMS

摘要

The economic and design optimisation of gas turbine cycles using biomass fuel gives a clear picture of which kind of cycle is more suitable for a given application, regarding capital and fuel costs. Due to its low specific energy, raw fuel transportation plays a large role in the final cost of electricity. Other factors of influence are the availability of the biomass in each season and the power plant location. An economic and exergy destruction optimisation of a BIGGT, biomass integrated gasification/gas turbine, and EFGT, externally fired gas turbine, cycles is carried out in this paper. Then the sensitivity of the systems to fuel costs, as well as to investment life, is assessed in order to evaluate the influence of these parameters in the final optimised cost of electricity. The Genetic Algorithms, GA, technique, a well known robust technique, is used for the optimisation in this work. The GA tool, GENIAL 1.1~(~R) has been written in Fortran77 computer language and was developed by Widell, 1997. The software for the cycle design performance was developed under Fortran90. The EFGT cycle seems to be very promising in terms of cost of electricity and efficiency. The calculations also show that the BIGGT cycle still needs further improvements in the gasification process regarding costs and performance. The cycle used as reference is the well known gas natural/gas turbine cycle, NGGT.