This chapter presents an in-depth analysis of a solar-driven generation plant, which harnesses solar energy for the production of electricity, heating, and cooling. Various technologies such as photovoltaic systems, concentrated solar power (CSP), and advanced multi-generation systems are examined to enhance energy efficiency and reduce costs. The chapter explores thermodynamic and economic models to evaluate the performance of such systems, particularly focusing on exergy efficiency and the sum unit cost of the product (SUCP). Multi-objective optimization is performed using the Grasshopper Optimization Algorithm (GOA), with compressor pressure ratio, helium turbine inlet temperature, ammonia concentration, and Kalina separator inlet pressure as decision variables. The optimization results are validated through comparison with the augmented epsilon constraint method (AUGMENCON). Both optimization techniques are applied to improve the exergy performance and minimize SUCP, providing a comprehensive framework for enhancing the overall efficiency and cost-effectiveness of solar-driven generation plants.