This research work presents an advanced optimization framework for integrating Electric Vehicles (EVs) with microgrid (MG) operations, utilizing Combined Heat and Power (CHP) technologies, renewable energy sources (RES), and Battery Energy Storage Systems (BESS). Despite the benefits of CHP technologies in providing both electricity and heat, their potential in EV Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) operations remains largely unexplored. To bridge this gap, this paper proposes a hybrid electric-thermal load strategy for CHP systems that autonomously toggles between electric and thermal load-following modes, thereby maximizing environmental and economic advantages. The optimization process is augmented by the Zebra Optimization Algorithm (ZOA), which draws inspiration from zebra social behavior to effectively balance exploration and exploitation within the complex, stochastic MG environment. To further enhance solution quality and address uncertainties in RES generation, EV charging/discharging patterns, and load consumption, the Differential Evolution (DE) algorithm is introduced. The framework is validated through three case studies: the first focused solely on CHP technologies, the second on a combination of CHP and RES, and the third integrating BESS to facilitate V2G operations. The proposed hybrid ZOA-DE approach achieves a notable reduction in operational costs, decreasing by up to 25%, and CO 2 emissions, which are reduced by approximately 30%. This comprehensive approach provides a sustainable energy management solution for EVs within MGs.