One of the crucial problems in the power systems is the selection of energy-efficient systems with suitable efficiency, cost, and environmental performance. Accordingly, this paper introduces a new power generation system that supplies a significant part of the required energy from solar energy and uses liquefied natural gas (LNG) fuel as an auxiliary source. To evaluation of the system, exergo-enviro-economic analysis and thermohydraulic design of are performed using Matlab code. A comparison of the governed results with the base cycle (ThermoFlex simulation) shows good improvement in exergy efficiency fuel consumption. Since the preparation of an analytical model has a practical effect on the selection of optimum configuration, an analytical model for objective functions is provided based on the exergoeconomic and environmental numerical model. For this analytical model, A large data bank from the numerical simulation results is obtained, and the artificial intelligence tool known as Genetic Programming is used for multivariate fitting. Finally, to find the optimal configuration, various optimizations (using the particle swarm optimization) have been made, and the final optimal design has been selected. The results indicated that the thermal and exergetic efficiencies in the ultimate optimum point increased about 6.252 and 8.842 percent, respectively.

电力系统中的关键问题之一是选择具有适当效率，成本和环境性能的节能系统。因此，本文介绍了一种新的发电系统，该系统可提供来自太阳能的大部分所需能量，并使用液化天然气（LNG）燃料作为辅助能源。为了评估系统，使用Matlab代码进行了系统的能环境经济分析和热工水力设计。将控制结果与基本周期进行比较（ThermoFlex仿真），显示出在火用效率方面的燃油消耗有了很好的改善。由于分析模型的准备对最佳配置的选择有实际影响，因此基于能效经济和环境数值模型提供了目标函数的分析模型。对于该分析模型，从数值模拟结果中获得了一个大型数据库，并将名为遗传编程的人工智能工具用于多变量拟合。最后，为了找到最佳配置，进行了各种优化（使用粒子群优化），并选择了最终的最佳设计。结果表明，最终最佳点的热效率和能量效率分别增加了约6.252和8.842％。并选择了最终的最佳设计。结果表明，最终最佳点的热效率和能量效率分别提高了约6.252和8.842％。并选择了最终的最佳设计。结果表明，最终最佳点的热效率和能量效率分别提高了约6.252和8.842％。