Power Distribution Micro-Grid Restoration via Minimum Spanning Forest
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Solution Overview
Problem
Conventional methods for post-disaster resilient restoration of power distribution systems are inefficient, time-consuming, and fail to ensure physical survivability of islanded grids, as they rely on heuristic search or per-phase analysis that is not applicable for practical distribution feeders and do not account for the uncertainty of load consumption and power output from intermittent distributed generators.
Innovation Solution
The use of minimum spanning forest (MSF) concept to reconfigure power distribution systems by switching off edges with higher weights, forming self-sustained islanded grids (SSIGs) energized by micro-turbines and energy storage systems, and optimizing tie switches to reduce link failures and enhance resilience, modeled as a mixed-integer linear programming (MILP) problem to efficiently restore critical loads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional heuristic search methods are used for restoration, then the restoration process can be initiated, but the computation time becomes excessively long and mathematical insights are lost
Solution Approach 1:
The patent replaces conventional heuristic search methods with a mixed-integer linear programming (MILP) formulation. This substitution transforms the restoration problem from an iterative search process into a mathematically rigorous optimization framework that provides both computational efficiency and mathematical insights, directly resolving the contradiction between restoration effectiveness and computation time.
Solution Approach 2:
The patent changes the fundamental parameters of the restoration approach by formulating it as an MILP problem with binary variables representing switch states and continuous variables for power flows. This parameter transformation enables the use of efficient linear programming solvers that dramatically reduce computation time while maintaining or improving restoration effectiveness through optimal mathematical solutions.
2Measurement precision
If per-phase analysis programming is used, then analysis can be performed, but the method becomes inapplicable for practical distribution feeders
Solution Approach 1:
The patent creates a universal MILP formulation that can handle both three-phase and single-phase distribution feeders through a unified mathematical framework. The model uses phase indices and generalized constraints that automatically adapt to different feeder configurations, making the method universally applicable to practical distribution systems while maintaining analysis accuracy through rigorous power flow equations.
3Ease of operation
If conventional restoration approaches are used, then typical outages can be handled, but they fail to address catastrophic scenarios with multiple faults and fragmented networks
Solution Approach 1:
The patent applies segmentation by dividing the distribution network into islanded microgrids when catastrophic faults occur. The MILP formulation naturally handles network fragmentation by allowing disconnected components and formulating power balance constraints for each island separately. This segmentation approach enables the system to handle multiple faults and catastrophic scenarios while maintaining operational simplicity through automated optimal switching decisions.
Solution Approach 2:
The patent introduces dynamics by making the network topology adaptive and reconfigurable through optimal switching decisions. The MILP model dynamically determines the best network configuration under different disaster scenarios, transforming the static conventional restoration approach into a dynamic system that can adapt to catastrophic events with multiple faults and fragmented networks.
4Reliability
If distributed generators and microgrids are added for resilient upgrades, then service standard can be maintained, but the system complexity increases
Solution Approach 1:
The patent enables self-service by allowing distributed generators and microgrids to autonomously provide power to critical loads during outages. The MILP formulation automatically determines optimal islanding configurations and generator dispatch without requiring complex manual coordination, reducing operational complexity while maintaining service continuity through automated self-organized restoration.
Data Source
AI summary
Systems and methods for configuring micro-grids to restore some power in a power distribution grid (PDG) in response to a power disruption over the PDG. A computing system configured to receive current condition information from devices in the PDG. Form a minimum spanning forest (MSF) to identify a set of micro-grids, each spanning tree in a forest is a self-sustained islanded micro-grid network. Assign a ranking to each inter-bus link within each micro-grid according to constraints, to identify some inter-bus links above a high-ranking threshold to be switched off during a restoration period. Identify switches that restore power to some critical loads of a subset of critical loads with different forest configurations, based on buses that are switched on, to determine a subset of micro-grids less susceptible for link failures during the restoration period. Upon receiving a power disruption, activate the switches to restore some power to the PDG.