Dynamic Simulation and Optimization of an Innovative Cogeneration System Using TRNSYS, EES, and Response Surface Methodology as a Machine learning method

• A fully integrated solar-powered multi-generation system was developed to supply the annual electricity, heating, cooling, domestic hot water, and freshwater needs of a 100-unit residential complex. • The proposed configuration combines a solar dish concentrator, organic Rankine cycle (ORC), heat pump, thermal energy storage units (hot and cold tanks), an auxiliary steam boiler, and a reverse osmosis (RO) desalination unit within a unified operational framework. • Dynamic simulations were carried out using TRNSYS for transient system modeling, while thermodynamic calculations of the ORC were performed in Engineering Equation Solver (EES). • A multi-objective optimization was performed using Response Surface Methodology (RSM) to minimize life cycle cost (LCC), annual boiler fuel consumption, and electricity use, while maximizing thermal comfort quantified via the Predicted Mean Vote (PMV) index. • Compared to a conventional PV + grid + boiler configuration, the proposed system reduced LCC by 18.4% and annual CO₂ emissions by over 13 tones. • A dimensionless scaling approach was introduced to adapt the design to other climatic zones, enabling re-optimization without complete re-simulation, enhancing system replicability and market potential. The rapid growth in global energy demand, coupled with the urgent need to reduce greenhouse gas emissions, necessitates the development of sustainable, multi-output energy systems. This study presents the design, simulation, and optimization of an innovative solar-powered cogeneration system capable of simultaneously meeting the annual electricity, heating, cooling, and freshwater demands of a 100-unit residential complex in Tehran, Iran. The proposed configuration integrates a solar dish concentrator, organic Rankine cycle (ORC), heat pump, reverse osmosis desalination, hot and cold water storage tanks, and an auxiliary boiler. Dynamic simulations were conducted using TRNSYS, with thermodynamic modeling of the ORC performed in Engineering Equation Solver (EES). A multi-objective optimization framework, based on Response Surface Methodology (RSM) in Design Expert, was applied to minimize life cycle cost (LCC), boiler fuel consumption, and electricity usage, while maximizing thermal comfort (predicted mean vote, PMV).The optimal design—comprising a 101.25 m² solar dish, 20.27 kW cooling capacity, 36.29 kW heating capacity, and benzene as the ORC working fluid—achieves an LCC of $134,130, annual boiler fuel consumption of 6,918.0 m³, and electricity consumption of 6,437.4 kWh, while producing freshwater with a total dissolved solids (TDS) level below 500 mg/L in compliance with WHO drinking water standards. Compared with a conventional PV + grid + boiler system, the proposed design reduces the LCC by 18.4% and annual CO₂ emissions by over 13 tonnes. Although benzene emerged as optimal in the numerical optimization, alternative low-global-warming-potential fluids such as R1233zd(E) are discussed as safer, environmentally favorable options with minimal efficiency trade-offs. In particular, R1233zd(E) and toluene are highlighted as practical alternatives, balancing acceptable efficiency with improved safety and environmental compliance. Beyond the Tehran case study, a dimensionless scaling approach is proposed for adapting the system to other climatic zones, enabling re-optimization of key parameters such as solar dish area and heat pump capacities based on local meteorological and demand profiles. The results demonstrate that the integrated TRNSYS–EES–RSM framework can deliver cost-effective, environmentally sustainable, and technically robust cogeneration solutions for residential applications in sun-rich regions.