Energy Management Algorithm for Battery Sharing based on Model Predictive Control integrating Electro-Thermal Simulation and Demand Forecast

Herbert Hackl; Manuel Freiberger; Philip Matzick; Martin Stoiber; Bernhard Auinger

doi:10.1109/EDPE58625.2023.10274028

Energy Management Algorithm for Battery Sharing based on Model Predictive Control integrating Electro-Thermal Simulation and Demand Forecast

Herbert Hackl, Manuel Freiberger, Philip Matzick, Martin Stoiber, Bernhard Auinger

Research output: Conference proceeding/Chapter in Book/Report/ › Conference Paper › peer-review

Abstract

This paper presents the energy management algorithm implemented in an e-bike battery sharing station to control the parallel charging of many tens of batteries. The charging control targets energy-self-sufficient operation from solar energy only. To achieve that, model-based forecasts of the user demands, solar energy production as well as energy demand for thermal conditioning are employed. The latter is generated from electro-thermal simulation considering the self-heating of battery cells as function of charging current. Alternatively, exploiting bi-directional charging capabilities of the used DC/DC converters, the control algorithm predicts the best scheme of grid-oriented operation to maximize profit from energy micro trading, facilitating the batteries in the station as buffer storage and respecting time-variant stock market prices.

Original language	English
Title of host publication	2023 International Conference on Electrical Drives and Power Electronics (EDPE)
Pages	1-7
Number of pages	7
DOIs	https://doi.org/10.1109/EDPE58625.2023.10274028
Publication status	Published - 27 Sept 2023
Event	2023 International Conference on Electrical Drives and Power Electronics (EDPE) - The High Tatras, Slovakia Duration: 25 Sept 2023 → 27 Sept 2023

Conference

Conference	2023 International Conference on Electrical Drives and Power Electronics (EDPE)
Period	25/09/23 → 27/09/23

Keywords

Thermal management of electronics
Temperature
Weather forecasting
Production
Solar energy
Prediction algorithms
Thermal management

Access to Document

10.1109/EDPE58625.2023.10274028

https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10274028

Cite this

Hackl, H., Freiberger, M., Matzick, P., Stoiber, M., & Auinger, B. (2023). Energy Management Algorithm for Battery Sharing based on Model Predictive Control integrating Electro-Thermal Simulation and Demand Forecast. In 2023 International Conference on Electrical Drives and Power Electronics (EDPE) (pp. 1-7). Article 10274028 https://doi.org/10.1109/EDPE58625.2023.10274028

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title = "Energy Management Algorithm for Battery Sharing based on Model Predictive Control integrating Electro-Thermal Simulation and Demand Forecast",

abstract = "This paper presents the energy management algorithm implemented in an e-bike battery sharing station to control the parallel charging of many tens of batteries. The charging control targets energy-self-sufficient operation from solar energy only. To achieve that, model-based forecasts of the user demands, solar energy production as well as energy demand for thermal conditioning are employed. The latter is generated from electro-thermal simulation considering the self-heating of battery cells as function of charging current. Alternatively, exploiting bi-directional charging capabilities of the used DC/DC converters, the control algorithm predicts the best scheme of grid-oriented operation to maximize profit from energy micro trading, facilitating the batteries in the station as buffer storage and respecting time-variant stock market prices.",

keywords = "Thermal management of electronics, Temperature, Weather forecasting, Production, Solar energy, Prediction algorithms, Thermal management",

author = "Herbert Hackl and Manuel Freiberger and Philip Matzick and Martin Stoiber and Bernhard Auinger",

year = "2023",

month = sep,

day = "27",

doi = "10.1109/EDPE58625.2023.10274028",

language = "English",

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pages = "1--7",

booktitle = "2023 International Conference on Electrical Drives and Power Electronics (EDPE)",

note = "2023 International Conference on Electrical Drives and Power Electronics (EDPE) ; Conference date: 25-09-2023 Through 27-09-2023",

}

Hackl, H , Freiberger, M , Matzick, P , Stoiber, M & Auinger, B 2023, Energy Management Algorithm for Battery Sharing based on Model Predictive Control integrating Electro-Thermal Simulation and Demand Forecast. in 2023 International Conference on Electrical Drives and Power Electronics (EDPE)., 10274028, pp. 1-7, 2023 International Conference on Electrical Drives and Power Electronics (EDPE), 25/09/23. https://doi.org/10.1109/EDPE58625.2023.10274028

Energy Management Algorithm for Battery Sharing based on Model Predictive Control integrating Electro-Thermal Simulation and Demand Forecast. / Hackl, Herbert ; Freiberger, Manuel ; Matzick, Philip et al.
2023 International Conference on Electrical Drives and Power Electronics (EDPE). 2023. p. 1-7 10274028.

Research output: Conference proceeding/Chapter in Book/Report/ › Conference Paper › peer-review

TY - GEN

T1 - Energy Management Algorithm for Battery Sharing based on Model Predictive Control integrating Electro-Thermal Simulation and Demand Forecast

AU - Hackl, Herbert

AU - Freiberger, Manuel

AU - Matzick, Philip

AU - Stoiber, Martin

AU - Auinger, Bernhard

PY - 2023/9/27

Y1 - 2023/9/27

N2 - This paper presents the energy management algorithm implemented in an e-bike battery sharing station to control the parallel charging of many tens of batteries. The charging control targets energy-self-sufficient operation from solar energy only. To achieve that, model-based forecasts of the user demands, solar energy production as well as energy demand for thermal conditioning are employed. The latter is generated from electro-thermal simulation considering the self-heating of battery cells as function of charging current. Alternatively, exploiting bi-directional charging capabilities of the used DC/DC converters, the control algorithm predicts the best scheme of grid-oriented operation to maximize profit from energy micro trading, facilitating the batteries in the station as buffer storage and respecting time-variant stock market prices.

AB - This paper presents the energy management algorithm implemented in an e-bike battery sharing station to control the parallel charging of many tens of batteries. The charging control targets energy-self-sufficient operation from solar energy only. To achieve that, model-based forecasts of the user demands, solar energy production as well as energy demand for thermal conditioning are employed. The latter is generated from electro-thermal simulation considering the self-heating of battery cells as function of charging current. Alternatively, exploiting bi-directional charging capabilities of the used DC/DC converters, the control algorithm predicts the best scheme of grid-oriented operation to maximize profit from energy micro trading, facilitating the batteries in the station as buffer storage and respecting time-variant stock market prices.

KW - Thermal management of electronics

KW - Temperature

KW - Weather forecasting

KW - Production

KW - Solar energy

KW - Prediction algorithms

KW - Thermal management

UR - https://ieeexplore.ieee.org/document/10274028/

U2 - 10.1109/EDPE58625.2023.10274028

DO - 10.1109/EDPE58625.2023.10274028

M3 - Conference Paper

SN - 979-8-3503-0000-0

SP - 1

EP - 7

BT - 2023 International Conference on Electrical Drives and Power Electronics (EDPE)

T2 - 2023 International Conference on Electrical Drives and Power Electronics (EDPE)

Y2 - 25 September 2023 through 27 September 2023

ER -

Energy Management Algorithm for Battery Sharing based on Model Predictive Control integrating Electro-Thermal Simulation and Demand Forecast

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