The increasing use of Renewable Energy Sources (RES) has raised the demand for coordinated scheduling due to economic and environmental considerations. Combined Heat and Power (CHP) generation units can protect the system from fluctuations in renewable energy sources due to their high efficiency and quick reaction capabilities. This research proposes to optimize the scheduling of cryogenic energy storage (CES) arbitrage to handle operational problems related to RES by maximizing owner benefits and minimizing RES variability. In order to modify the load profile of the system through changes in user consumption patterns, the proposed model makes use of plug-in electric automobiles as responsible loads. To solve this problem, we use the dominated group search optimization technique on a second-order cone programming model. Four distinct case research were conducted to confirm the suitability and efficacy of the suggested method. © 2025 Elsevier B.V., All rights reserved.