Degradation-Aware Bi-Level Optimization of Second-Life Battery Energy Storage System Considering Demand Charge Reduction

Many electric vehicle (EV) batteries will retire in the next 5–10 years around the globe. These batteries are retired when no longer suitable for energy-intensive EV operations despite having 70–80% capacity left. The second-life use of these battery packs has the potential to address the increasing...

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Main Authors: Ali Hassan, Guilherme Vieira Hollweg, Wencong Su, Xuan Zhou, Mengqi Wang
Format: Article
Language:English
Published: MDPI AG 2025-07-01
Series:Energies
Subjects:
Online Access:https://www.mdpi.com/1996-1073/18/15/3894
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author Ali Hassan
Guilherme Vieira Hollweg
Wencong Su
Xuan Zhou
Mengqi Wang
author_facet Ali Hassan
Guilherme Vieira Hollweg
Wencong Su
Xuan Zhou
Mengqi Wang
author_sort Ali Hassan
collection DOAJ
description Many electric vehicle (EV) batteries will retire in the next 5–10 years around the globe. These batteries are retired when no longer suitable for energy-intensive EV operations despite having 70–80% capacity left. The second-life use of these battery packs has the potential to address the increasing demand for battery energy storage systems (BESSs) for the electric grid, which will also create a robust circular economy for EV batteries. This article proposes a two-layered energy management algorithm (monthly layer and daily layer) for demand charge reduction for an industrial consumer using photovoltaic (PV) panels and BESSs made of retired EV batteries. In the proposed algorithm, the monthly layer (ML) calculates the optimal dispatch for the whole month and feeds the output to the daily layer (DL), which optimizes the BESS dispatch, BESSs’ degradation, and energy imported/exported from/to the grid. The effectiveness of the proposed algorithm is tested as a case study of an industrial load using a real-world demand charge and Real-Time Pricing (RTP) tariff. Compared with energy management with no consideration of degradation or demand charge reduction, this algorithm results in 71% less degradation of BESS and 57.3% demand charge reduction for the industrial consumer.
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spelling doaj-art-9a6b0423043c4cd49b3e6f9ade8364a42025-08-20T03:02:55ZengMDPI AGEnergies1996-10732025-07-011815389410.3390/en18153894Degradation-Aware Bi-Level Optimization of Second-Life Battery Energy Storage System Considering Demand Charge ReductionAli Hassan0Guilherme Vieira Hollweg1Wencong Su2Xuan Zhou3Mengqi Wang4Department of Electrical and Computer Engineering, University of Michigan, Dearborn, MI 48128, USADepartment of Electrical and Computer Engineering, University of Michigan, Dearborn, MI 48128, USADepartment of Electrical and Computer Engineering, University of Michigan, Dearborn, MI 48128, USADepartment of Electrical and Computer Engineering, University of Michigan, Dearborn, MI 48128, USADepartment of Electrical and Computer Engineering, University of Michigan, Dearborn, MI 48128, USAMany electric vehicle (EV) batteries will retire in the next 5–10 years around the globe. These batteries are retired when no longer suitable for energy-intensive EV operations despite having 70–80% capacity left. The second-life use of these battery packs has the potential to address the increasing demand for battery energy storage systems (BESSs) for the electric grid, which will also create a robust circular economy for EV batteries. This article proposes a two-layered energy management algorithm (monthly layer and daily layer) for demand charge reduction for an industrial consumer using photovoltaic (PV) panels and BESSs made of retired EV batteries. In the proposed algorithm, the monthly layer (ML) calculates the optimal dispatch for the whole month and feeds the output to the daily layer (DL), which optimizes the BESS dispatch, BESSs’ degradation, and energy imported/exported from/to the grid. The effectiveness of the proposed algorithm is tested as a case study of an industrial load using a real-world demand charge and Real-Time Pricing (RTP) tariff. Compared with energy management with no consideration of degradation or demand charge reduction, this algorithm results in 71% less degradation of BESS and 57.3% demand charge reduction for the industrial consumer.https://www.mdpi.com/1996-1073/18/15/3894battery energy storagesecond-life batteriesdemand chargecircular economyenergy management
spellingShingle Ali Hassan
Guilherme Vieira Hollweg
Wencong Su
Xuan Zhou
Mengqi Wang
Degradation-Aware Bi-Level Optimization of Second-Life Battery Energy Storage System Considering Demand Charge Reduction
Energies
battery energy storage
second-life batteries
demand charge
circular economy
energy management
title Degradation-Aware Bi-Level Optimization of Second-Life Battery Energy Storage System Considering Demand Charge Reduction
title_full Degradation-Aware Bi-Level Optimization of Second-Life Battery Energy Storage System Considering Demand Charge Reduction
title_fullStr Degradation-Aware Bi-Level Optimization of Second-Life Battery Energy Storage System Considering Demand Charge Reduction
title_full_unstemmed Degradation-Aware Bi-Level Optimization of Second-Life Battery Energy Storage System Considering Demand Charge Reduction
title_short Degradation-Aware Bi-Level Optimization of Second-Life Battery Energy Storage System Considering Demand Charge Reduction
title_sort degradation aware bi level optimization of second life battery energy storage system considering demand charge reduction
topic battery energy storage
second-life batteries
demand charge
circular economy
energy management
url https://www.mdpi.com/1996-1073/18/15/3894
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AT guilhermevieirahollweg degradationawarebileveloptimizationofsecondlifebatteryenergystoragesystemconsideringdemandchargereduction
AT wencongsu degradationawarebileveloptimizationofsecondlifebatteryenergystoragesystemconsideringdemandchargereduction
AT xuanzhou degradationawarebileveloptimizationofsecondlifebatteryenergystoragesystemconsideringdemandchargereduction
AT mengqiwang degradationawarebileveloptimizationofsecondlifebatteryenergystoragesystemconsideringdemandchargereduction