LAPSE:2023.13433
Published Article

LAPSE:2023.13433
Mixed-Integer Linear Programming Model to Assess Lithium-Ion Battery Degradation Cost
March 1, 2023
Abstract
This work proposes a mixed-integer linear programming model for the operational cost function of lithium-ion batteries that should be applied in a microgrid centralized controller. Such a controller aims to supply loads while optimizing the leveled cost of energy, and for that, the cost function of the battery must compete with the cost functions of other energy resources, such as distribution network, dispatchable generators, and renewable sources. In this paper, in order to consider the battery lifetime degradation, the proposed operational cost model is based on the variation in its state of health (SOH). This variation is determined by experimental data that relate the number of charge and discharge cycles to some of the most important factors that degrade the lifespan of lithium-ion batteries, resulting in a simple empirical model that depends on the battery dispatch power and the current state of charge (SOC). As proof-of-concept, hardware-in-the-loop (HIL) simulations of a real microgrid are performed considering a centralized controller with the proposed battery degradation cost function model. The obtained results demonstrate that the proposed cost model properly maintains the charging/discharging rates and the SOC at adequate levels, avoiding accelerating the battery degradation with use. For the different scenarios analyzed, the battery is only dispatched to avoid excess demand charges and to absorb extra power produced by the non-dispatchable resources, while the daily average SOC ranges from 48.86% to 65.87% and the final SOC converges to a value close to 50%, regardless of the initial SOC considered.
This work proposes a mixed-integer linear programming model for the operational cost function of lithium-ion batteries that should be applied in a microgrid centralized controller. Such a controller aims to supply loads while optimizing the leveled cost of energy, and for that, the cost function of the battery must compete with the cost functions of other energy resources, such as distribution network, dispatchable generators, and renewable sources. In this paper, in order to consider the battery lifetime degradation, the proposed operational cost model is based on the variation in its state of health (SOH). This variation is determined by experimental data that relate the number of charge and discharge cycles to some of the most important factors that degrade the lifespan of lithium-ion batteries, resulting in a simple empirical model that depends on the battery dispatch power and the current state of charge (SOC). As proof-of-concept, hardware-in-the-loop (HIL) simulations of a real microgrid are performed considering a centralized controller with the proposed battery degradation cost function model. The obtained results demonstrate that the proposed cost model properly maintains the charging/discharging rates and the SOC at adequate levels, avoiding accelerating the battery degradation with use. For the different scenarios analyzed, the battery is only dispatched to avoid excess demand charges and to absorb extra power produced by the non-dispatchable resources, while the daily average SOC ranges from 48.86% to 65.87% and the final SOC converges to a value close to 50%, regardless of the initial SOC considered.
Record ID
Keywords
battery energy storage system, degradation cost model, lithium-ion battery, microgrid power dispatch, mixed-integer linear programming
Subject
Suggested Citation
Oliveira DBS, Glória LL, Kraemer RAS, Silva AC, Dias DP, Oliveira AC, Martins MAI, Ludwig MA, Gruner VF, Schmitz L, Coelho RF. Mixed-Integer Linear Programming Model to Assess Lithium-Ion Battery Degradation Cost. (2023). LAPSE:2023.13433
Author Affiliations
Oliveira DBS: Center for Sustainable Energy, CERTI Foundation, Florianopolis 88040-900, Brazil
Glória LL: Center for Sustainable Energy, CERTI Foundation, Florianopolis 88040-900, Brazil [ORCID]
Kraemer RAS: Center for Sustainable Energy, CERTI Foundation, Florianopolis 88040-900, Brazil [ORCID]
Silva AC: Center for Sustainable Energy, CERTI Foundation, Florianopolis 88040-900, Brazil
Dias DP: Center for Sustainable Energy, CERTI Foundation, Florianopolis 88040-900, Brazil
Oliveira AC: Center for Sustainable Energy, CERTI Foundation, Florianopolis 88040-900, Brazil
Martins MAI: Center for Sustainable Energy, CERTI Foundation, Florianopolis 88040-900, Brazil [ORCID]
Ludwig MA: AES Brazil, R&D and Innovation, São Paulo 04578-000, Brazil
Gruner VF: Electrical Engineering Department, Federal University of Santa Catarina, Florianopolis 88040-900, Brazil
Schmitz L: Electrical Engineering Department, Federal University of Santa Catarina, Florianopolis 88040-900, Brazil [ORCID]
Coelho RF: Electrical Engineering Department, Federal University of Santa Catarina, Florianopolis 88040-900, Brazil
Glória LL: Center for Sustainable Energy, CERTI Foundation, Florianopolis 88040-900, Brazil [ORCID]
Kraemer RAS: Center for Sustainable Energy, CERTI Foundation, Florianopolis 88040-900, Brazil [ORCID]
Silva AC: Center for Sustainable Energy, CERTI Foundation, Florianopolis 88040-900, Brazil
Dias DP: Center for Sustainable Energy, CERTI Foundation, Florianopolis 88040-900, Brazil
Oliveira AC: Center for Sustainable Energy, CERTI Foundation, Florianopolis 88040-900, Brazil
Martins MAI: Center for Sustainable Energy, CERTI Foundation, Florianopolis 88040-900, Brazil [ORCID]
Ludwig MA: AES Brazil, R&D and Innovation, São Paulo 04578-000, Brazil
Gruner VF: Electrical Engineering Department, Federal University of Santa Catarina, Florianopolis 88040-900, Brazil
Schmitz L: Electrical Engineering Department, Federal University of Santa Catarina, Florianopolis 88040-900, Brazil [ORCID]
Coelho RF: Electrical Engineering Department, Federal University of Santa Catarina, Florianopolis 88040-900, Brazil
Journal Name
Energies
Volume
15
Issue
9
First Page
3060
Year
2022
Publication Date
2022-04-22
ISSN
1996-1073
Version Comments
Original Submission
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PII: en15093060, Publication Type: Journal Article
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LAPSE:2023.13433
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https://doi.org/10.3390/en15093060
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