With the increasing development of renewable energy generation, its volatility and uncertainty pose significant challenges to the power and energy balance of modern power systems. The balance exhibits multi-timescale characteristics, necessitating the coordination of multi-timescale balancing processes. Existing coordination methods typically adopt a top-down approach with fixed boundary conditions, which fails to account for the progressive reduction in renewable energy uncertainty over time. To address this issue, this paper proposes a dynamic adjustment model for monthly–weekly balancing boundary conditions, considering the progressive change in renewable energy uncertainty. Compared with the fixed boundaries, the dynamic model reduces the total system cost and decreases the execution deviation of boundary conditions from the plan. The model analyzes the value equilibrium of boundary conditions as decision variables in both current and future contexts. A case study validates the effectiveness of the proposed method.
Ma et al. (Mon,) studied this question.