Distributed Risk-Limiting Load Restoration in Unbalanced Distribution Systems With Networked Microgrids

Abstract

To enhance the resilience of distribution systems (DSs), networked microgrids (MGs) can be employed to restore critical loads after a blackout. However, uncertainties of renewable energy sources (RESs) and loads bring challenges to load restoration. This paper proposes a distributed risk-limiting load restoration strategy for unbalanced DS with networked MGs. In the proposed strategy, the risk is represented by the conditional value-at-risk (CVaR), based on which a risk-limiting load restoration model is formulated considering renewable and load uncertainties. With the projection function-based alternating direction method of multipliers (P-ADMM) and sub-additivity of the CVaR, the proposed risk-limiting model is decoupled and solved in a distributed manner. This enables distributed risk limiting among MGs. Each MG can make load restoration decisions individually, while ensuring that the risk-limiting constraints of the overall system are satisfied. The modified IEEE 123-node system with networked MGs was used to conduct case studies. Simulation results show that the proposed strategy can restore loads efficiently with a smaller risk index and can provide distributed and flexible risk management. Moreover, the proposed distributed strategy can reduce the computation burden and is more robust against controller failures compared with the centralized strategy.