Co-Optimizing Battery Dispatch for Seasonal Rates and Demand Response Events: A Markov Decision Process Approach for a Vermont Commercial Building
Leppla, Chris
Leppla, Chris
Citations
Altmetric:
License
License
Abstract
As dynamic pricing and demand response (DR) programs expand across Vermont and other states, commercial building operators need dispatch strategies that respond to both seasonal rates and targeted curtailment events. This research presents an event-aware battery energy storage system (BESS) dispatch model for a 67,000-square-foot county courthouse in Vermont served under a Flexible Load Management (FLM) flat seasonal rate structure. The model integrates a Markov Load State Model, which characterizes building demand as a stochastic process with state-dependent transition matrices, with a finite-horizon Markov Decision Process (MDP) to co-optimize 15-minute battery charge and discharge decisions over a full day. Two coupled policy sets are derived: a normal policy for routine operation and an event policy activated by a day-ahead curtailment signal, enabling structured pre-charge, bridge, event, and recovery phases. The framework evaluates multiple battery capacities and power ratings to quantify sizing tradeoffs, comparing utilization patterns and their impact on operating cost savings and total system cost. The cost analysis compares four scenarios across billing periods: (1) FLM without a battery; (2) FLM with normal-only MDP dispatch; (3) FLM with event-aware dispatch; and (4) a traditional Rate 63 tariff with event-aware dispatch. Preliminary results indicate that event-aware dispatch meaningfully reduces peak demand charges and improves BESS utilization relative to normal-only operation, with the magnitude of savings depending on battery sizing and event frequency. The methods presented are generalizable to other commercial buildings facing similar DR- and event-driven tariffs regionally and nationwide.
Description
Date
1/1/2026
Student Status
Graduate Student
Journal Title
Journal ISSN
Volume Title
Type of presentation
Poster
Collections
Research Projects
Organizational Units
Journal Issue
Citation
DOI
Advisor(s)
Department
Program/Major
Complex Systems and Data Science
College/School
College of Engineering and Mathematical Sciences
Organization
Research Category
Engineering