Power Supply Restoration Strategy for Distribution Network Based on Robust Model Prediction Control

With the development of microgrid technology, after the distribution network fails, microgrids in the distribution network can be employed to provide emergency power supply to the outage load, which can reduce the power outage range and improve the power supply reliability. Due to the uncertainties of renewable energy output and load demand in the microgrid, the existing studies mainly adopt single-time-step stochastic optimization methods to generate power supply restoration strategies. However, the accurate probability distribution model is difficult to obtain, and single-time-step optimization methods only optimize the operation scheme for the next one time period and ignore the relevance of states in multiple time periods, which results in a decrease in operation efficiency. Therefore, this paper proposes a resilience operation strategy based on robust model predictive control (RMPC). First, with the lowest cost of multiple time steps in each control cycle as the optimization goal, an optimal decision-making model based on RMPC is established. Since the proposed model is formulated as a min-max problem and cannot be solved directly, the strong duality theory is adopted to transform it into a single-layer mixed-integer model. Finally, the IEEE 69-bus distribution system is used to verify the effectiveness of the proposed method. © 2021 Automation of Electric Power Systems Press.