Hybrid Energy Planning for Residential EV‐Charging Complexes: A HOMER–Monte Carlo 3E Evaluation in Pakistani Cities

Rapid urbanization, increasing electricity demand, and the widespread adoption of electric vehicles (EVs) have made the development of efficient renewable energy systems capable of simultaneously supplying residential loads and EV charging infrastructure an essential requirement. The objective of this study is to develop a comprehensive energy–economic–environment (3E) framework for evaluating three energy system configurations, namely PV–wind–grid, PV‐only, and wind‐only, for a 10‐story residential building comprising 20 apartments and five EV charging stations across five densely populated cities in Pakistan. By integrating multiregional assessment with Monte Carlo uncertainty analysis, a generalizable framework is proposed for identifying the most suitable energy system under different climatic conditions. System optimization was performed using HOMER based on 20 years of climatic data, and the net present cost (NPC), levelized cost of energy (LCOE), renewable fraction (RF), and annual CO ₂ emissions were evaluated. Furthermore, a Monte Carlo uncertainty analysis with 10,000 iterations and a ±10% variation range was conducted to assess the robustness of the obtained results. The results demonstrated that the PV–wind–grid configuration achieved the best overall performance in Hyderabad and Karachi, with an NPC of approximately USD –512,000 and a CO ₂ emission reduction of up to –727,356 kg/year, outperforming the other configurations. In contrast, the PV‐only configuration was found to be slightly more economical in Peshawar and Faisalabad, whereas the wind‐only configuration was determined to be unsuitable for practical implementation because of its high cost, low renewable energy contribution, and poor environmental performance. The uncertainty analysis confirmed the robustness of the results and the superiority of the hybrid configuration, demonstrating that the integration of solar and wind energy resources not only improves economic and environmental performance but also enhances the reliability of planning EV charging infrastructure. The proposed framework can therefore serve as a reliable decision‐support tool for the design of renewable energy systems and the development of EV charging infrastructure in urban regions with diverse climatic conditions.