Tools for improving resilience of electric distribution systems with networked microgrids
For utility planners, this work provides a computational tool to optimize investments in microgrids and hardening for resilience against extreme weather, though the results are preliminary and domain-specific.
The authors formulate a resilient distribution grid design problem as a two-stage stochastic program and use decomposition-based heuristics to scale to practical sizes. They demonstrate the tool on a real distribution network model, identifying parametric regions where different architectures (e.g., individual microgrids, hardened networks, networked microgrids) are optimal.
In the electrical grid, the distribution system is themost vulnerable to severe weather events. Well-placed and coordinatedupgrades, such as the combination of microgrids, systemhardening and additional line redundancy, can greatly reduce thenumber of electrical outages during extreme events. Indeed, ithas been suggested that resilience is one of the primary benefitsof networked microgrids. We formulate a resilient distributiongrid design problem as a two-stage stochastic program andmake use of decomposition-based heuristic algorithms to scaleto problems of practical size. We demonstrate the feasibilityof a resilient distribution design tool on a model of an actualdistribution network. We vary the study parameters, i.e., thecapital cost of microgrid generation relative to system hardeningand target system resilience metrics, and find regions in thisparametric space corresponding to different distribution systemarchitectures, such as individual microgrids, hardened networks,and a transition region that suggests the benefits of microgridsnetworked via hardened circuit segments.