Robust coordination of multiple power sources for sequential service restoration of distribution systems

Abstract

When a distribution system encounters a major outage due to extreme events, an efficient sequential service restoration (SSR) strategy is required to restore the outage system. However, uncertainties associated with renewable energy generation and load demands pose significant and complex challenges for the optimization of SSR strategies. This paper proposes a robust multiple power source co-optimization approach for the SSR of an outage distribution system. First, network configuration and sequential switching actions are jointly optimized to sequentially form microgrids (MGs). Second, multiple types of power sources, such as distributed generators and energy storage units, are re-energized and coordinated to pick up critical loads in parallel restored MGs. In addition, uncertainties associated with renewable energy generation and load demands are considered during the restoration process, thereby requiring a robust SSR scheme to increase the reliability of MG operations, The mathematical problem is modelled as a mixed-integer tri-level programming problem with inner-level binary variables. Thus, the extended column-and-constraint generation (EC&CG) algorithm is employed to solve the proposed robust model. The numerical results demonstrate the effective performance of the proposed approach and its robustness and advantages compared to existing models that do not consider uncertainties.