This study examines the modeling, simulation, and optimization of a solar-assisted hybrid renewable energy system for a hotel building based on the U.S. Department of Energy prototype model, evaluated across five major climatic regions of Iran: semi-arid, cold mountainous, desert, humid temperate, and hot-humid coastal. The proposed configuration integrates photovoltaic panels, evacuated-tube solar thermal collectors, battery-based energy storage, auxiliary electric heaters, and absorption chillers to supply a major portion of the building's electricity, space-heating, space-cooling, and domestic hot-water demands. Building loads were generated using Energy Plus, and the dynamic behavior of the hybrid system was simulated in TRNSYS 18. The results demonstrate clear climatic sensitivity, with desert and hot-humid coastal regions showing the highest summer cooling and electricity demand, while cold mountainous regions exhibit dominant winter heating requirements. Solar-fraction analysis further indicates strong seasonal variation, with the desert climate exceeding 0.80 during summer and the humid temperate climate falling below 0.20 in cloudy winter months. The novelty of this study lies in the development of a fully integrated optimization framework that couples year-long TRNSYS simulations with an artificial-neural-network-based surrogate model and a multi-objective evolutionary algorithm, supported by a temperature-based multi-layer control strategy. This approach enables realistic and computationally efficient optimization of a full-building hybrid energy system, an aspect largely absent, in previous TRNSYS-based research. For the semi-arid region, the optimization results reveal clear trade-offs among cost, emissions, and reliability, with the best compromise solution achieving an annual operating cost of 2.06 dollars per hour, carbon-dioxide emissions of 1.35 x 108 g per year, and a loss-of-power-supply probability of 0.42, requiring 298 photovoltaic modules, 65 kW-hours of battery capacity, and 302 square meters of solar collectors. These findings highlight the adaptability of the proposed methodology and its potential to support climate-responsive, low-emission, near-zero-energy buildings.