Evaluation of Demand Response Potential in Air Conditioning Systems Considering Detailed Energy Flow Characteristics

Evaluating the demand response potential of air-conditioning systems can support mitigating power shortages caused by the surge in air-conditioning loads during summer. Existing evaluation models often fail to fully account for the energy consumption of each subsystem within the air conditioning and the user's willingness to respond. To address this issue, this paper proposes a demand response potential evaluation model for air-conditioning systems based on detailed energy flow characteristics. This model optimizes the energy efficiency of air-conditioning system loads. First, the energy consumption model of the air-conditioning system is developed by analyzing its energy flow characteristics. Next, a regional temperature regulation strategy based on user response willingness is established. An improved adaptive genetic algorithm is then employed to solve the optimization problem. Finally, the model's rationality and effectiveness are verified through simulations of an air-conditioning system in a large shopping mall. The simulation results demonstrate a 46% increase in algorithm iteration speed and a reduction in energy consumption by 2391 kW. Additionally, the demand response potential of the air-conditioning system improves by 7% compared to other models, ensuring the safe and stable operation of the power system.