Enhancing distribution system resiliency with microgrids formation using weighted average consensus

Integration of distributed energy resources (DERs) including renewable and storage, digital automation and the advanced metering infrastructure (AMI) provides an opportunity to further enhance resiliency during outage of main feeder. Access to local DERs with enhanced control ensures the sustainability of energy continuity to urban critical (vital) loads, by forming DER-based microgrids. Microgrid formation is challenging considering detecting failures; priority of loads; detecting location and boundary of load outages, while meeting the energy constraints and data sharing limitations to maximize resiliency. Consensus algorithms provide an opportunity to share data in limited manner but still allowing to reach consensus on the resource and network control for microgrids formation and enhance resiliency. In this work, a weighted average consensus mechanism has been proposed to detect failures due to faults and/or data loss and, hence, determine the isolated nodes as a first layer. Additionally, a mixed-integer linear programming (MILP) optimization problem is formulated and solved as part of the second layer to form the DER-based microgrids with the goal to improve the resiliency of the distribution system, while satisfying the consensus-based constraints. The proposed method is evaluated using the standard IEEE 123-node feeder. Simulation results demonstrate the effectiveness of the proposed weighted average consensus method in enhancing the distribution system resiliency by detecting failures and node isolation; and forming DER-based microgrids considering critical and non-critical loads.