Optimizing air conditioning loads scheduling: A bi-objective dynamic optimization algorithm considering life loss impact

Air conditioning loads (ACLs) can actively contribute to optimizing energy usage and increasing renewable energy utilization rate through scheduling. Existing studies on the participation of ACLs in DR have mainly focused on developing ON/OFF strategies, little consideration has been given to the impact of DR on the life loss of ACLs. In light of this, the present study first introduces an equation for quantifying the life loss of ACLs. Building upon this, an optimizing ACLs scheduling model is established considering life loss impact. As the relationship between life loss and refrigeration power is a complex non-linear high-order fractional function, it cannot be solved by conventional commercial solvers. Therefore, a bi-objective dynamic optimization algorithm is proposed based on non-linear fractional programming (NFP) to address this problem. To assess the effectiveness of our algorithm, it is used in a microgrid case with three schemes. Scheme 3 is aquatinted to consider the economic cost and the life loss of ACLs simultaneously, aiming to maximize the comprehensive benefit of the scheduling scheme. The results confirm the efficiency and superiority of the proposed algorithm. We propose a new formula that quantifies reduced life loss of ACLs and establishes an efficient scheduling model, using an NFP algorithm. In a microgrid test, one approach maximizes benefits by considering cost and life loss, showcasing effectiveness. image