Abstract Air conditioning loads (ACLs) represent an increasing proportion of power system loads, offering significant potential for optimised scheduling and active participation in demand response (DR) programs. While many studies have focused on ON/OFF control schemes that satisfy system requirements, few have addressed quantifying the life loss of ACLs from the user perspective. To address this gap, a quantitative model of ACL life loss is established and an optimal scheduling model is developed for ACLs participating in DR that incorporates the cost of life loss. The relationship between life loss and refrigeration power is a complex non‐linear high‐order fractional function that cannot be solved by commercial solvers. Therefore, a bi‐objective multi‐weight optimisation algorithm is proposed with a complex non‐linear fraction based on the Dinkelbach algorithm and its feasibility through mathematical examples is verified. Finally, a numerical example based on the IEEE 39‐bus test system is provided to demonstrate the feasibility of the model and the effectiveness of the proposed solution method.