The integration of substantial renewable energy and controllable resources disrupts the supply–demand balance in distribution grids. Secur
The integration of substantial renewable energy and controllable resources disrupts the supply–demand balance in distribution grids. Secure operations are dependent on the participation of user-side resources in demand response at both the day-ahead and intraday levels. Current studies typically overlook the spatial–-temporal variations and coordination between these timescales, leading to significant day-ahead optimization errors, high intraday costs, and slow convergence. To address these challenges, we developed a multiagent, multitimescale aggregated regulation method for spatial–-temporal coordinated demand response of user-side resources. Firstly, we established a framework considering the spatial–-temporal coordinated characteristics of user-side resources with the objective to minimize the total regulation cost and weighted sum of distribution grid losses. The optimization problem was then solved for two different timescales: day-ahead and intraday. For the day-ahead timescale, we developed an improved particle swarm optimization (IPSO) algorithm that dynamically adjusts the number of particles based on intraday outcomes to optimize the regulation strategies. For the intraday timescale, we developed an improved alternating direction method of multipliers (IADMM) algorithm that distributes tasks across edge distribution stations, dynamically adjusting penalty factors by using historical day-ahead data to synchronize the regulations and enhance precision. The simulation results indicate that this method can fully achieve multitimescale spatial–-temporal coordinated aggregated regulation between day-ahead and intraday, effectively reduce the total regulation cost and distribution grid losses, and enhance smart grid resilience.
