Exergy and exergoeconomic analysis and multi-objective optimisation of gas turbine power plant by evolutionary algorithms. Case study: Aliabad Katoul power plant

Abstract

In this paper, exergy and exergoeconomic analysis and optimisation of a gas turbine cycle (case study) were performed by using three algorithms: NSGA-II, MOPSO and MOEA-D. Two objective functions were considered: total cost rate and exergy efficiency. In Pareto solution, the middle point was considered as the optimal solution, which is the lowest total cost rate (1.922 US$/s) was obtained which was 30% less than MOPSO algorithm and 6.2% less than MOEA-D algorithm. Also, the exergy efficiency in the NSGA-II algorithm was obtained about 55.1% which was 12% greater than MOPSO algorithm and 10% greater than MOEA-D algorithm. Also a sensitivity analysis of the design variables on objective functions is performed. Results show the highest rate of exergy destruction in all three optimisation methods was related to the combustion chamber. After overall comparison of the performance of these algorithms, the results showed that the NSGA-II algorithm had the best performance than the two others.