Capacity evaluation of central air conditioning load participating in peak shaving of renewable dominated power systems

The development of renewable‐dominated power systems (RDPS) in the context of pursuing deep decarbonisation targets necessitates suitable exploitation of the peak shaving capacity (PSC) of central air conditioning loads (CACL) in multiple time scales. Based on the evaluation framework of CACL participating in the RDPS PSC and the CAC apparent temperature model and its operation mode, the CACL PSC evaluation model related to the resource allocation in multiple time scales is proposed. For the time scale of online dispatching, the capacity evaluation model for rapid CACL response to power system emergency peak shaving command and its continuous response potential is constructed. The method of optimising CACL PSC based on the load aggregator model is developed. For the intraday pre‐scheduling time scale, the evaluation model of CACL's remaining capacity after undertaking the peak shaving task and the ability to respond continuously to the peak shaving command is constructed. For the day‐ahead dispatching time scale, the PSC of CACL under different weather conditions, temperatures, holidays, and other typical scenarios is evaluated. Finally, case studies carried out on 14 central air‐conditioned buildings in Shanghai city comprehensively validate the effectiveness of the proposed CACL PSC evaluation model. The construction of renewable dominated power systems (RDPS) pursing deep decarbonization targets necessiates suitable expolition of the peak shaving capacity of central air conditioning load (CACL) in multiple time scales. Based on the evaluation framework of CACL participating in the RDPS peak shaving capacity (PSC), CAC apparent temperature model, and operation mode, CACL peak shaving capacity evaluation model related to the resource allocation and use process in multiple time scales is proposed. The method proposed in this paper provides technical support for RDPS operation.