Exergy, Cost and Environment as Objectives in Particle Swarm Optimization of a Benchmark Cogeneration System

Multi-Objective Optimization of a benchmark cogeneration problem known as CGAM cogeneration system has been carried out from Exergetic, Economic and Environmental aspects simultaneously. CGAM Problem designs a cogeneration plant which delivers 30 MW of electricity and 14 kg/s of saturated steam at 20 bars. Since multi-objective calculus based optimization of real energy systems involves very complicated process, one of the most suitable techniques which uses a particular class of search algorithms known as Particle Swarm Optimization (MOPSO) is utilized and the advantages of this method is shown. This approach has been applied to find the set of Pareto optimal solutions with respect to the competing objective functions. In this study the MOPSO algorithm uses 100 particles and 200 iterations. In order to facilitate the problem, the environmental objective function has been defined and expressed in cost terms. The thermodynamic modeling has been implemented comprehensively while economic analysis of this system conducted. Consideration of Five decision variables in modeling process made the final optimal solutions more realistic in comparison with previous studies in this field. Finally the result of optimization is introduced with 100 points on Pareto frontier.