Semester of Graduation

Spring 2026

Degree

Master of Science in Electrical Engineering (MSEE)

Department

Electrical and Computer Engineering

Document Type

Thesis

Abstract

Traditional reliability planning for conventional distribution systems is largely utility-oriented, with a focus on collective system performance metrics like Expected Energy Not Supplied (EENS), where implicitly all unserved energy is considered of equal weight in terms of post-outage economic hardship. Yet, it is well understood that extended outage durations cause an uneven level of hardship to socioeconomically disadvantaged communities. This thesis proposes a community-informed reliability planning framework where the hardship caused by outages is explicitly considered in the battery energy storage system (BESS) location and sizing problem. First, a hardship-weighted Energy Not Supplied (WENS) measure is proposed, where income, education, and homeownership are identified as primary factors of outage hardship. A proof-of-concept case study on a 13-bus distribution system illustrates that community-informed BESS location can substantially alleviate hardship-weighted outage effects in low-income areas with system performance comparable to utility-oriented planning. Based on this starting point, a regression analysis approach is formulated using survey data to estimate the socioeconomic factors of outage hardship. Tract-level data from the U.S. Census Bureau is normalized using a min-max risk formulation to derive bounded and interpretable hardship weights. These weights are incorporated into a two-stage stochastic mixed-integer linear programming (MILP) model that jointly optimizes BESS location and sizing decisions under outage. A city-scale 96-feeder synthetic testbed representing East Baton Rouge Parish is created to evaluate the proposed framework. Results indicate that the community-aware optimization reduces hardship-weighted unserved energy by 12.87% compared to a conventional utility-centric objective, with only a 2.44% increase in traditional EENS. This modest trade-off reflects a deliberate reallocation of storage resources toward ix feeders where outages impose the greatest societal burden. Overall, this work provides a reproducible and mathematically tractable pathway for integrating social vulnerability into distribution system reliability planning, bridging the gap between technical grid optimization and community energy needs.

Date

3-11-2026

Committee Chair

Amin Kargarian Marvasti

LSU Acknowledgement

1

LSU Accessibility Acknowledgment

1

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