A Hierarchical Restoration Mechanism for Distribution Networks Considering Multiple Faults

Service restoration of distribution networks in contingency situations is one of the highly investigated and challenging problems. In the conventional service restoration method, utilities reconfigure the topological structure of the distribution networks to supply the consumer load demands. However, the advancements in renewable distributed generations define a new dimension for developing service restoration methodologies. This paper proposes a hierarchical service restoration mechanism for distribution networks in the presence of distributed generations and multiple faults. The service restoration problem is modeled as a complicated and hierarchical program. The objectives are to achieve the maximization of loads restored with minimization of switch operations while simultaneously satisfying grid operational constraints and ensuring a radial operation configuration. We present the service restoration mechanism, which includes the dynamic topology analysis, matching isolated islands with renewable distributed generations, network reconfiguration, and network optimization. A new code scheme that avoids feasible solutions is applied to generate candidate solutions to reduce the computational burden. We evaluate the proposed mechanism on the IEEE 33 and 69 systems and report on the collected results under multitype fault cases. The results demonstrate the importance of the available renewable distributed generations in the proposed mechanism. Moreover, simulation results verify that the proposed mechanism can obtain reasonable service restoration plans to achieve the maximization of loads restored and minimization of switching operations under different faults.

Implementation of a software defined FLISR solution on an active distribution grid

Background: The resiliency of the distribution grid is of increasing concern to the distribution system operator (DSO) due to factors such as climate change and the resulting faults caused by inclement weather conditions, leading to service disruption to consumers. Loss of service negatively affects key performance indicators (KPI) of the DSO, such as customer minutes lost (CML) and customer interruptions (CI), leading to financial penalties imposed by the regulator. Methods: In this paper we propose a software-driven Fault Location, Isolation and Service Restoration (FLISR) solution, leveraging modern software and communication technologies married with the DSO's existing infrastructure, to aid fault detection and resolution, with the aim of reducing CMLs & CIs and curtailing the financial penalties incurred. Results: The proposed FLISR solution was trialled in an area of south-east Ireland which sees a higher count of service loss as compared to more inland areas, providing an ideal environment to gauge the effectiveness of the solution. It was found that the solution generated outputs that could potentially lead to the resolution of fault events faster than the current systems in place by the DSO. Conclusions: Based on the results gathered from operating the FLISR solution on an active grid, it has demonstrated that leveraging modern software technologies in tandem with existing grid infrastructure benefits the DSO with reference to grid management and operations and the customer in terms of quality of service site.

Intending Island Service Restoration Method With Topology-Powered Directional Traversal Considering the Uncertainty of Distributed Generations

The intending island service restoration method is one of the core technologies of self-healing control for smart distribution systems, which aims to maximize the restoration of the out-of-service loads in the out-of-service area without faults quickly. For this reason, a topology-weighted directional traversal intending island recovery method considering the uncertainty of distributed generation sources is proposed. First, divide the network level of the power-loss feeder and calculate the interval power flow of the feeder before the fault, and obtain the power flow direction when the active and reactive power of the faulted branch is the smallest so as to determine whether the distributed generation supply in the non-faulty power-loss area can restore all load power supply. If not, to determine the island recovery plan, continue to compare the distributed generation supply and the load capacity at all levels, and give priority to recovering loads with higher importance levels and smaller network levels. The traversal of the topological authority and direction effectively reduces the island recovery time and can make full use of the distributed generation output to maximize the recovery of the non-faulty power-loss area. Taking the PG&E 69-node system as an example and using the BFGS trust region algorithm to calculate the island power flow without unbalanced nodes for verification, the results show that this method consumes less time and can restore more load power supply than the existing island recovery method, which verifies the method’s effectiveness and reasonability.