Multi-objective techno-economic optimization of a solar based integrated energy system using various optimization methods

Abstract

In this research paper, a novel combined, cooling, heating and, power (CCHP) system is proposed consisting of Parabolic trough solar collectors (PTSC) field, a dual-tank molten salt heat storage, a Proton exchange membrane electrolyzer (PEME), an Organic Rankine Cycle (ORC) and a single effect Li/Br water absorption chiller. The first law of thermodynamics was applied for analyzing the proposed CCHP system. A multi-objective optimization is conducted with respect to exergy efficiency and total cost rate as two objective functions. In order to determine the optimal point in multi-objective optimization, NSGA-II algorithm was applied for the optimization purpose. Matlab software and python are employed to determine the system optimum operating conditions. The optimum solutions for the NSGA-II multi-objective optimization are 79% and 0.058 ($/s) for exergy efficiency and total cost rate, respectively. The results of single objective optimization are 0.0447 ($/s) for the economic objective function and 87.53% for the exergy efficiency objective function. The sensitivity of the Pareto frontier for different interest rates is also investigated and the results show that at the lower system exergy efficiency, the influence of the interest rate is more significant. In addition, Generalized Differential Evaluation (GDE3), Indicator-based evolutionary algorithm (IBEA), speed-constrained Multi-objective (SMPSO), and strength Pareto Evolutionary algorithm (SPEA) algorithms are also applied for the optimization of the proposed CCHP and the results of the algorithm are compared with each other. The IBEA algorithm was found the best approach to obtain the Pareto optimum solution. The comparison between NSGA-II and IBEA shows that the IBEA exergy efficiency of the optimum solution increase by 2.5% in comparison with NSGA-II and the IBEA cost rates decrease by 7% in comparison with NSGA-II.