Strategies of Achieving Community Resilience Under Extreme Weathers
A Reconfigurably Time-Sharing Community Microgrid with PV+Storage
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In recent years, extreme weather events such as hurricanes have had a significant impact on power systems. Low-income communities are especially vulnerable due to the high costs of enhancing system resilience. Traditional solutions like reinforcing poles or installing underground cables, while effective, are often too expensive for these communities. As a result, they face prolonged isolation and darkness during outages until the system is restored. The increasing frequency of extreme weather has made the resilience of distribution power systems more crucial, emphasizing the need for more affordable and equitable solutions to ensure grid stability for all communities.
Time-Sharing Resilience Strategy
A time-sharing framework has been developed to improve the resilience of power distribution systems in low-income communities during extreme weather events. This framework optimizes the allocation of distributed energy resources (DERs) and reclosers to sequentially energize different segments of the distribution system, thereby reducing the capital costs associated with enhancing resilience. The team has formulated this problem as a mixed-integer linear programming (MILP) challenge and has proposed two key algorithms: one for optimal recloser placement and another for DER selection based on budget constraints.
By applying this framework to a modified IEEE 33-bus distribution system, the study shows that this approach can enhance resilience during outages while staying within limited community budgets. The framework provides a practical and economically feasible solution for vulnerable communities, offering a strategic way to improve energy resilience through efficient system reconfiguration and resource planning.
Figure 1. A time-sharing solution for the IEEE 33-bus distribution system
2. Community Center with PV + BESS Providing Resilience
PV+Storage is investigated by considering at a community center (CC) equipped with photovoltaic (PV) systems and battery energy storage systems (BESS) in a synthetic distribution network corresponding to a community in Orlando. By strategically placing reclosers within the radial network, their Time-Sharing Resilience Strategy ensures equitable power distribution among network clusters, adjusting service times based on real-time solar irradiance. The study highlights the benefits of PV integration, showing that it improves grid resilience compared to battery-only systems under various solar conditions.
This framework provides practical guidance for utilities and community planners aiming to enhance power system resilience in the face of increasing extreme weather events. The study is a resource for those focused on sustainable energy solutions and community-level resilience planning, offering a clear methodology and real-world case studies that demonstrate the effectiveness of these strategies.
Figure 2. TSRS implementation with PV+BESS integrated at the CC
Figure 3. Resilience duration across two days at varying irradiance levels and PV panel sizes (each block represents one day)
3. Time-Sharing Resilience Strategies for Power Distribution Systems Based on Social Vulnerability Index (SoVI) Scores
Here, we further refine the Time-Sharing Resilience Strategy (TSRS) that rotationally energizes network partitions using minimal distributed energy resources (DERs), prioritizing equitable restoration based on Social Vulnerability Index (SoVI) scores.
TSRS leverages a bilevel mixed-integer nonlinear programming (MINLP) framework. The upper level optimizes battery energy storage system (BESS) sizing and placement to minimize costs while ensuring SoVI-weighted energization durations, whereas the lower level employs a reverse breadth-first search (RBFS) algorithm to form load-balanced partitions, placing bypass and segmentation switches to satisfy voltage and reactive power constraints.
Key contributions include: 1) an equity-driven partitioning approach that extends energization for high-SoVI communities; 2) a scalable bilevel MINLP model that optimizes DER and switch costs; and 3) validation on a 13,623-node synthetic Ocoee City, FL, network and the IEEE 34-bus feeder, achieving significant cost savings with multi-site BESS under TSRS versus conventional methods, along with enhanced resilience via PV-augmented storage.
Simulations confirm TSRS’s cost-effectiveness, scalability, and prioritization of vulnerable communities, offering a practical resilience solution.
Figure 4. Proposed bilevel framework
Figure 5. Synthetic Ocoee City distribution network with complete 13,623-node topology
Based on the above work, decision-makers such as utility companies or communities will be offered a portfolio of resilience enhancement solutions.
A Example for Community Decision Making
Feeder DF225 From Tallahassee
Data Included:
GIS: Coordinates of lines, equipment (switches, transformers).
Load: Hourly total load time series (9/24/2024–10/3/2024) for DF225.
Due to the incompleteness of the dataset, some data assumptions are made as follows:
Loads: Individual loads vary from 7.43 to 17.8 kW, randomly allocated per bus, with a total gross load of 5.07 MW.
Primary lines (12.47 kV): Resistance r1 = 0.1 Ω/km and reactance x1 = 0.2 Ω/km.
Secondary lines (208/120 V): Resistance r1 = 0.3 Ω/km , and reactance x1 = 0.4 Ω/km.
Transformers:
Three-phase, step-down, 12.47 kV to 208 V secondary (wye, 120 V line-neutral), 500 kVA each.
Load losses 0.5%, short-circuit reactance 5%; no-load losses 0.5% (2.5 kW).
Based on details of topology and physical features, a meaningful distribution power network can be modeled by OpenDSS.
Feeder DF225 model in OpenDSS
By implementing TSRS, the investment comparison with the conventional approach for feeder DF225 is as follows:
Adjusting the budget limit and required duration toggles helps facilitate the decision-making process.
Team Member
Prof. Zhihua Qu
Dr. Bo Tu
Kenneth McDonald
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