<p>This paper presents a novel framework aimed at enhancing the operational flexibility and energy management of shopping centers in critical conditions and under electricity price uncertainty, focusing on day-ahead peak shaving. To achieve this goal, shopping centers equipped with Heating-Ventilating and Air Conditioning (HVAC) systems are mathematically modeled. To develop demand response (DR) capabilities in shopping centers, electrical energy storage systems and self-generation facilities, including distributed thermal generation, are examined. This research emphasizes the need for optimizing energy consumption and reducing costs in the face of fluctuating electricity prices in the wholesale market. The framework introduces a new mathematical model for a Commercial Demand Response Aggregator (CDRA) that represents shopping centers in the day-ahead electricity market. This model employs robust optimization techniques to manage worst-case scenarios of price uncertainty, ensuring reliable decision-making for participation in DR programs. Implemented in shopping centers within the Iranian electricity market, this framework demonstrates its capability to enhance energy efficiency and operational flexibility, particularly during periods of grid pressure or electricity shortages. Aggregating commercial consumers can lead to significant reductions in overall electricity consumption and costs, offering up to a 10% decrease in energy expenses, especially when facing fluctuating electricity prices. The results indicate improved cost savings and reliability for responsive shopping centers.</p>