Optimal sizing of solar PV-wind systems, battery storage, and EV charging infrastructure for efficient energy management in large-scale commercial buildings

Rising energy demands in commercial buildings, coupled with the need to decarbonize and to reduce grid dependence, highlight the importance of renewable energy integration and intelligent energy management. Workplace electric vehicles (EVs) enhance grid flexibility and building autonomy by acting as controllable energy assets. This study introduces two novel metrics: Autonomous Energy Utilization Index (AEUI) and EV Utilization Index (EVUI) as objective functions within an integrated framework for optimal sizing and energy management of a renewable-powered commercial building with workplace EVs. Unlike traditional metrics, AEUI quantifies the effective use of self-generated renewable energy to maximize autonomy, directly improving Self-Sufficiency Ratio (SSR), Self-Consumption Ratio (SCR), and reducing Grid Interaction Ratio (GIR), while EVUI measures EV utilization as dispatchable resources. A multi-objective whale optimization algorithm (MOWOA) optimizes the sizing of solar panels, wind turbines, battery storage, and EV charging infrastructure, balancing the conflicting objectives of minimizing Net Present Cost (NPC) and maximizing AEUI and EVUI. EVs are managed dynamically as controllable loads during surplus renewable generation and dispatchable sources during peak demand. Two EV operational scenarios are evaluated: (1) multiple charging–single discharging and (2) single charging–single discharging, benchmarked against a fully grid-dependent system. Compared to the grid-dependent baseline, Scenario 1 reduces NPC by 34.9 % and peak demand charges by 18 %, while Scenario 2 achieves 39.6 % and 6 % reductions, respectively. Scenario 1 outperforms Scenario 2 with a 15.3 % higher AEUI, 57.9 % lower grid import costs, and improved SSR, SCR, and GIR, offering a scalable solution for decarbonizing commercial buildings.