Author Identifier (ORCID)
Mehdi Khiadani: https://orcid.org/0000-0003-1703-9342
Abstract
This study presents a hybrid multi-generation energy system designed to overcome solar intermittency while meeting the global demand for integrated delivery of electricity, water, cooling, and sustainable fuels in the transition to decarbonization. The engineering application integrates solar thermal and wind energy with a modified Brayton cycle, a Steam Rankine Cycle (SRC), and a Thermoelectric Generator (TEG) to simultaneously produce electricity, fresh water via Reverse Osmosis (RO), hydrogen and oxygen via Proton Exchange Membrane Electrolyzer (PEME), and cooling (via absorption chiller) within a unified optimization framework. The system was modeled using Engineering Equation Solver (EES) and optimized via Response Surface Methodology (RSM) based on 11 decision variables. To address the complexity of optimization, a second phase applied Artificial Intelligence (AI) techniques: Adaptive Boosting (AdaBoost) for predictive modelling and Particle Swarm Optimization (PSO) for global optimization. Under optimal conditions, the Response Surface Methodology yielded an exergy efficiency of 45.8 % with a cost rate of 576.76 United States Dollars per hour (USD/h), while AI reduced costs to 211.2 USD/h with a moderate efficiency trade-off. Simulation of the optimized configuration across eight diverse climates identified Quebec as most viable, generating 22,629.6 Megawatt-hours per year (MWh/year) of electricity and avoiding 4616.4 tons of Carbon Dioxide (CO2) emissions annually. Integration of wind energy stabilizes solar variability, enhancing performance. AI contributes to optimizing complex interactions, nonlinear constraints, and multiple conflicting objectives. The methodology offers a scalable, generalizable framework for designing intelligent, climate-resilient infrastructures. Future research includes AI-enabled real-time control, experimental validation, and broader deployment strategies.
Document Type
Journal Article
Date of Publication
12-20-2025
Volume
162
Publication Title
Engineering Applications of Artificial Intelligence
Publisher
Elsevier
School
Mineral Recovery Research Centre / School of Engineering
RAS ID
87989
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Comments
Assareh, E., Izadyar, N., Tandis, E., Khiadani, M., Shahavand, A., Agarwal, N., Gerami, A., Rezk, A., Kim, M., Kord, R., Pirhoushyaran, T., Hosseinzadeh, M., & Mobayen, S. (2025). Thermoeconomic optimization of climate-adaptive solar and wind multi-generation systems using artificial intelligence and thermal energy recovery. Engineering Applications of Artificial Intelligence, 162, 112481. https://doi.org/10.1016/j.engappai.2025.112481