Multi-time scale customer directrix load-based demand response under renewable energy and customer uncertainties

Demand response (DR) programs have been proven as efficient and practical approaches to unlock the demand-side flexibility and support flexible regulation of the power system. However, the existing DR mechanisms struggle to simultaneously address the dual uncertainties from both renewable energy (RE) and customers, resulting in relatively low efficiency of currently applied DR programs. To bridge these research gaps, this paper proposes a multi-time scale joint day-ahead and intraday DR mechanism based on customer directrix load (CDL). Multi-time scale CDL is the guiding target that in-corporates the uncertainty information of RE at multi-time scales, consisting of band-shaped day-ahead CDL (A-CDL) in the day-ahead stage and rolling-updated intra-day CDLs (I-CDLs) in the intraday stage. The DR incentive mechanism, comprising a day-ahead bilevel model and an intraday rolling optimization model, is proposed to exploit the flexibility potential of various demand-side resources across multi-time scales. Additionally, a deviation reporting mechanism is designed to allow Load Aggregators (LAs) to independently formulate and manage response deviations based on their resources' performance characteristics, effectively mitigating customers' uncertainties. Case study results demonstrate that the proposed mechanism can effectively address the uncertainties from both RE and customers, thereby improving DR efficiency. Specifically, it reduces RE curtailment by 15%, decreases Independent System Operator's operating costs by 10%, and increases LAs' revenue, resulting in a mutually beneficial outcome.