Impact of the Automation Outage Management Strategy and Self-healing on Reliability of Smart Distribution Networks Under the Penetration of Distributed Energy Resources

Self-healing as one of the most important features of smart distribution networks that increases network reliability and resiliency. Considering the necessity of studying the challenges facing outage management in smart distribution networks and developing the proposed solutions in this field, this paper investigate the impact of self-healing and automatic outage management on smart distribution networks on network reliability. In this paper, a new algorithm is proposed to evaluate the reliability of smart distribution networks by describing the problem scope and providing a control and operation model in both normal and self-healing modes. In the proposed algorithm, the Monte Carlo method is used to simulate equipment outage scenarios. In each outage scenario, in the optimization problem framework, the status of the controllable switch  to create the structure of the multi microgrid, direct load control program and the scheduling of thermal sources and energy storage in the fault period are determined. The capabilities of the proposed model are to consider the wind resources uncertainties and the distribution network operational constraint such as voltage constraints and line thermal constraints. The results of the implementation of the proposed algorithm on the modified IEEE RBTS network will improve the reliability of the network by adopting outage management strategies in smart distribution networks.