Optimal Control Framework for Battery Controls in Modern Community Microgrids
Faculty Mentor
Dr. Masoud Davari
Location
Russell Union Ballroom
If Other was choses above, please indicate your topic area here:
Power & Energy Systems
Type of Research
Completed
Session Format
Poster Presentation
College
Allen E. Paulson College of Engineering & Computing
Department
Electrical & Computer Engineering
Abstract
In microgrids (MGs), batteries are among the most expensive components, so extending their lifespan is crucial for reliable and cost-effective operation. Battery aging, driven by continuous cycling and conditions such as temperature, reduces capacity and increases internal resistance. This study proposes a microgrid control framework that allocates optimal current among battery packs. Specifically, the framework preserves weaker, lower-capacity packs and those that experience severe temperature conditions, which accelerate aging. This objective is achieved by continuously adjusting the control parameters based on real-time system operating conditions. System stability is verified through established analysis, while additional stability monitoring helps maintain robust operating margins. The study applies the proposed framework to a five-battery MG and estimates that at least 95% of aging-risk samples indicate low aging risk, confirms robust stability, achieves an average daily operating cost of about $4.00 per pack, and projects continuous, efficient service for roughly 7.2 to 7.9 years before reaching their end-of-life limits.
Program Description
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Start Date
4-23-2026 10:00 AM
End Date
4-23-2026 12:00 PM
Recommended Citation
Tagayi, Roland Kobla, "Optimal Control Framework for Battery Controls in Modern Community Microgrids" (2026). GS4 Student Scholars Symposium. 33.
https://digitalcommons.georgiasouthern.edu/research_symposium/2026/2026/33
Optimal Control Framework for Battery Controls in Modern Community Microgrids
Russell Union Ballroom
In microgrids (MGs), batteries are among the most expensive components, so extending their lifespan is crucial for reliable and cost-effective operation. Battery aging, driven by continuous cycling and conditions such as temperature, reduces capacity and increases internal resistance. This study proposes a microgrid control framework that allocates optimal current among battery packs. Specifically, the framework preserves weaker, lower-capacity packs and those that experience severe temperature conditions, which accelerate aging. This objective is achieved by continuously adjusting the control parameters based on real-time system operating conditions. System stability is verified through established analysis, while additional stability monitoring helps maintain robust operating margins. The study applies the proposed framework to a five-battery MG and estimates that at least 95% of aging-risk samples indicate low aging risk, confirms robust stability, achieves an average daily operating cost of about $4.00 per pack, and projects continuous, efficient service for roughly 7.2 to 7.9 years before reaching their end-of-life limits.
