Design of a Battery Energy Management System for Capacity Charge Reduction

This paper presents a novel dispatch and evaluation framework for battery energy storage systems (BESSs) to minimize a load servicing entity's coincident demand during system peak hours. The framework consists of i) a two-step BESS dispatch process that accounts for uncertainties in forecasting...

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Bibliographic Details
Published in:IEEE open access journal of power and energy 2022, Vol.9, p.351-360
Main Authors: Wu, Di, Ma, Xu, Fu, Tao, Hou, Zhangshuan, Rehm, P. J., Lu, Ning
Format: Article
Language:English
Subjects:
Batteries
Battery cycles
battery degradation
Battery energy management system
capacity charge
Cost accounting
Costs
Design parameters
Discharges (electric)
Effectiveness
Energy consumption
Energy management
Energy storage
Load forecasting
Load modeling
optimization
Peak demand
Predictive control
Reduction
Storage systems
Thresholds
Uncertainty
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Summary:This paper presents a novel dispatch and evaluation framework for battery energy storage systems (BESSs) to minimize a load servicing entity's coincident demand during system peak hours. The framework consists of i) a two-step BESS dispatch process that accounts for uncertainties in forecasting system peak and using limited battery cycle life, and ii) procedures to design control parameters, determine BESS duration, and estimate the corresponding net benefits. In the proposed dispatch, a rule-based triggering mechanism is executed to determine whether to dispatch a BESS on an operating day by comparing the peak-day probability with a predetermined threshold. Once the dispatch is triggered, a model predictive control is carried out to maximize the expected reduction in peak demand. By exercising this two-step dispatch method with different thresholds, one can explore the trade-off between peak demand reduction effectiveness and loss of battery life, and thereby identify the optimal thresholds to maximize cumulative economic benefits. Case studies are conducted using the data provided by utilities in North Carolina. Simulation results are presented to demonstrate the effectiveness of the proposed method.
ISSN:2687-7910
2687-7910
2644-1314
DOI:10.1109/OAJPE.2022.3196690