1D electrochemical model of lithium-ion battery for a sizing methodology of thermal power plant integrated storage system

François KREMER; Stéphane RAEL; Matthieu URBAIN; François KREMER; Stéphane RAEL; Matthieu URBAIN

doi:10.3934/energy.2020.5.721

AIMS Energy

2020, Volume 8, Issue 5: 721-748. doi: 10.3934/energy.2020.5.721

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1D electrochemical model of lithium-ion battery for a sizing methodology of thermal power plant integrated storage system

1.
General Electric GEEPF, Rue de la découverte, 90000 Belfort, France
2.
GREEN, 2 avenue de la forêt de Haye, 54500 Vandœuvre-lès-Nancy, France
3.
LEMTA, 2 avenue de la forêt de Haye, 54500 Vandœuvre-lès-Nancy, France

Received: 05 May 2020 Accepted: 26 July 2020 Published: 14 August 2020

The interest of using storage system has been investigated by grid operators over the past decades. Currently, some power plant manufacturers propose to integrate the storage system into thermal plants to meet grid codes requirements and improve the plant operability. Thermal powerplants change the way of the generation becoming peaking or cycling unit instead of baseload unit as few decades ago. This change of grid operability compels the power plant operators to enhance their flexibility, emission and efficiency. Storage systems seem to be a promising solution that can help achieve this change. Regarding the cost, it is mainly driven by the battery elements (a third of the total cost). Therefore, an oversizing of the solution will decrease the economic benefits. This article proposes a new electrochemical model of Li-ion battery implemented in a sizing methodology to enhance the business case. This method will also include asset losses, battery aging model and plant profiles. The new electrical model is based on the single particle and single electrode. It mainly focuses on the energy aspect and it exhibits good accuracy for the study purpose. Moreover, it has a simplified configuration using only supplier datasheet which logically leads to loss of accuracy. The model assessment is achieved by several battery technologies (Lithium Titanate Oxide, Lithium Iron Phosphate and Nickel Manganese Cobalt) and shows its use restrictions. At last, different plant profiles are run to show the benefits of the proposed approach.
- Lithium-ion battery,
- Single particle model,
- Battery energy storage system,
- Battery sizing methodology
Citation: François KREMER, Stéphane RAEL, Matthieu URBAIN. 1D electrochemical model of lithium-ion battery for a sizing methodology of thermal power plant integrated storage system[J]. AIMS Energy, 2020, 8(5): 721-748. doi: 10.3934/energy.2020.5.721

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Abstract

The interest of using storage system has been investigated by grid operators over the past decades. Currently, some power plant manufacturers propose to integrate the storage system into thermal plants to meet grid codes requirements and improve the plant operability. Thermal powerplants change the way of the generation becoming peaking or cycling unit instead of baseload unit as few decades ago. This change of grid operability compels the power plant operators to enhance their flexibility, emission and efficiency. Storage systems seem to be a promising solution that can help achieve this change. Regarding the cost, it is mainly driven by the battery elements (a third of the total cost). Therefore, an oversizing of the solution will decrease the economic benefits. This article proposes a new electrochemical model of Li-ion battery implemented in a sizing methodology to enhance the business case. This method will also include asset losses, battery aging model and plant profiles. The new electrical model is based on the single particle and single electrode. It mainly focuses on the energy aspect and it exhibits good accuracy for the study purpose. Moreover, it has a simplified configuration using only supplier datasheet which logically leads to loss of accuracy. The model assessment is achieved by several battery technologies (Lithium Titanate Oxide, Lithium Iron Phosphate and Nickel Manganese Cobalt) and shows its use restrictions. At last, different plant profiles are run to show the benefits of the proposed approach.

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