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 forec...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Open Access Journal of Power and Energy |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9852253/ |
| _version_ | 1811283742586568704 |
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| author | Di Wu Xu Ma Tao Fu Zhangshuan Hou P. J. Rehm Ning Lu |
| author_facet | Di Wu Xu Ma Tao Fu Zhangshuan Hou P. J. Rehm Ning Lu |
| author_sort | Di Wu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-13T02:16:52Z |
| format | Article |
| id | doaj.art-58dadfc98b5a4003a9f38696f3290d6a |
| institution | Directory Open Access Journal |
| issn | 2687-7910 |
| language | English |
| last_indexed | 2024-04-13T02:16:52Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Access Journal of Power and Energy |
| spelling | doaj.art-58dadfc98b5a4003a9f38696f3290d6a2022-12-22T03:07:07ZengIEEEIEEE Open Access Journal of Power and Energy2687-79102022-01-01935136010.1109/OAJPE.2022.31966909852253Design of a Battery Energy Management System for Capacity Charge ReductionDi Wu0https://orcid.org/0000-0001-6955-4333Xu Ma1Tao Fu2Zhangshuan Hou3https://orcid.org/0000-0002-9388-6060P. J. Rehm4Ning Lu5https://orcid.org/0000-0003-0125-0653Energy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA, USAEnergy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA, USAEnergy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA, USAEnergy and Environment Directorate, Pacific Northwest National Laboratory, Richland, WA, USAElectriCities of North Carolina, Raleigh, NC, USADepartment of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC, USAThis 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.https://ieeexplore.ieee.org/document/9852253/Battery energy management systembattery degradationcapacity chargeoptimizationuncertainty |
| spellingShingle | Di Wu Xu Ma Tao Fu Zhangshuan Hou P. J. Rehm Ning Lu Design of a Battery Energy Management System for Capacity Charge Reduction IEEE Open Access Journal of Power and Energy Battery energy management system battery degradation capacity charge optimization uncertainty |
| title | Design of a Battery Energy Management System for Capacity Charge Reduction |
| title_full | Design of a Battery Energy Management System for Capacity Charge Reduction |
| title_fullStr | Design of a Battery Energy Management System for Capacity Charge Reduction |
| title_full_unstemmed | Design of a Battery Energy Management System for Capacity Charge Reduction |
| title_short | Design of a Battery Energy Management System for Capacity Charge Reduction |
| title_sort | design of a battery energy management system for capacity charge reduction |
| topic | Battery energy management system battery degradation capacity charge optimization uncertainty |
| url | https://ieeexplore.ieee.org/document/9852253/ |
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