Optimal Daily Scheduling ofDistributed Battery Energy Storage Systems Considering Battery Degradation Cost

Qingmian Chai; Cuo Zhang; Zhaoyang Dong; Wen Chen

doi:10.1109/PESGM46819.2021.9638252

Optimal Daily Scheduling ofDistributed Battery Energy Storage Systems Considering Battery Degradation Cost

Qingmian Chai^*
, Cuo Zhang
, Zhaoyang Dong
, Wen Chen

^*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

11 Citations (Scopus)

Abstract

Distributed battery energy storage systems (BESSs) have been increasingly installed on the residential side to perform peak shaving and help improve photovoltaic (PV) energy utilization efficiency. However, associated battery degradation issues occur as BESSs are frequently operated, impairing economic benefits. Thus, this paper proposes an optimal daily scheduling method of distributed BESSs considering battery degradation cost. This method aims to maximize operating profits for BESS aggregators participating in electricity market, while minimizing the battery degradation cost. Firstly, a new linear model to calculate battery depth of discharge is developed, which can be efficiently involved in optimization models. Then, a battery daily degradation cost model is developed by utilizing a capital recovery factor and a curve fitting technique. Last, a daily scheduling optimization model considering the battery degradation cost is formulated and a scenario-based stochastic optimization method is applied to address uncertainties of PV generation and loads. Simulations indicate high economic efficiency of the proposed method for distributed BESSs. © 2021 IEEE.

Original language	English
Title of host publication	2021 IEEE Power and Energy Society General Meeting (PESGM)
Publisher	IEEE
ISBN (Electronic)	978-1-6654-0507-2
DOIs	https://doi.org/10.1109/PESGM46819.2021.9638252
Publication status	Published - 2021
Externally published	Yes
Event	2021 IEEE Power & Energy Society General Meeting (PESGM 2021) - Virtual, Washington, United States Duration: 26 Jul 2021 → 29 Jul 2021 https://myemail.constantcontact.com/Welcome-to-Day-1-of-the-2021-IEEE-PES-General-Meeting-.html?soid=1135726914871&aid=Iyxq9tkeV7M

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2021-July
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2021 IEEE Power & Energy Society General Meeting (PESGM 2021)
Place	United States
City	Washington
Period	26/07/21 → 29/07/21
Internet address	https://myemail.constantcontact.com/Welcome-to-Day-1-of-the-2021-IEEE-PES-General-Meeting-.html?soid=1135726914871&aid=Iyxq9tkeV7M

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Research Keywords

Battery energy storage system
capital recovery factor
depth of discharge
stochastic optimization
uncertainty

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10.1109/PESGM46819.2021.9638252

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Cite this

@inproceedings{cb6d82bcd7944df9abac4eb1bdd048f2,

title = "Optimal Daily Scheduling ofDistributed Battery Energy Storage Systems Considering Battery Degradation Cost",

abstract = "Distributed battery energy storage systems (BESSs) have been increasingly installed on the residential side to perform peak shaving and help improve photovoltaic (PV) energy utilization efficiency. However, associated battery degradation issues occur as BESSs are frequently operated, impairing economic benefits. Thus, this paper proposes an optimal daily scheduling method of distributed BESSs considering battery degradation cost. This method aims to maximize operating profits for BESS aggregators participating in electricity market, while minimizing the battery degradation cost. Firstly, a new linear model to calculate battery depth of discharge is developed, which can be efficiently involved in optimization models. Then, a battery daily degradation cost model is developed by utilizing a capital recovery factor and a curve fitting technique. Last, a daily scheduling optimization model considering the battery degradation cost is formulated and a scenario-based stochastic optimization method is applied to address uncertainties of PV generation and loads. Simulations indicate high economic efficiency of the proposed method for distributed BESSs. {\textcopyright} 2021 IEEE.",

keywords = "Battery energy storage system, capital recovery factor, depth of discharge, stochastic optimization, uncertainty",

author = "Qingmian Chai and Cuo Zhang and Zhaoyang Dong and Wen Chen",

year = "2021",

doi = "10.1109/PESGM46819.2021.9638252",

language = "English",

series = "IEEE Power and Energy Society General Meeting",

publisher = "IEEE",

booktitle = "2021 IEEE Power and Energy Society General Meeting (PESGM)",

address = "United States",

note = "2021 IEEE Power \& Energy Society General Meeting (PESGM 2021) ; Conference date: 26-07-2021 Through 29-07-2021",

url = "https://myemail.constantcontact.com/Welcome-to-Day-1-of-the-2021-IEEE-PES-General-Meeting-.html?soid=1135726914871\&aid=Iyxq9tkeV7M",

}

Chai, Q, Zhang, C, Dong, Z & Chen, W 2021, Optimal Daily Scheduling ofDistributed Battery Energy Storage Systems Considering Battery Degradation Cost. in 2021 IEEE Power and Energy Society General Meeting (PESGM). IEEE Power and Energy Society General Meeting, vol. 2021-July, IEEE, 2021 IEEE Power & Energy Society General Meeting (PESGM 2021), Washington, District of Columbia, United States, 26/07/21. https://doi.org/10.1109/PESGM46819.2021.9638252

Optimal Daily Scheduling ofDistributed Battery Energy Storage Systems Considering Battery Degradation Cost. / Chai, Qingmian; Zhang, Cuo; Dong, Zhaoyang et al.
2021 IEEE Power and Energy Society General Meeting (PESGM). IEEE, 2021. (IEEE Power and Energy Society General Meeting; Vol. 2021-July).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Optimal Daily Scheduling ofDistributed Battery Energy Storage Systems Considering Battery Degradation Cost

AU - Chai, Qingmian

AU - Zhang, Cuo

AU - Dong, Zhaoyang

AU - Chen, Wen

PY - 2021

Y1 - 2021

N2 - Distributed battery energy storage systems (BESSs) have been increasingly installed on the residential side to perform peak shaving and help improve photovoltaic (PV) energy utilization efficiency. However, associated battery degradation issues occur as BESSs are frequently operated, impairing economic benefits. Thus, this paper proposes an optimal daily scheduling method of distributed BESSs considering battery degradation cost. This method aims to maximize operating profits for BESS aggregators participating in electricity market, while minimizing the battery degradation cost. Firstly, a new linear model to calculate battery depth of discharge is developed, which can be efficiently involved in optimization models. Then, a battery daily degradation cost model is developed by utilizing a capital recovery factor and a curve fitting technique. Last, a daily scheduling optimization model considering the battery degradation cost is formulated and a scenario-based stochastic optimization method is applied to address uncertainties of PV generation and loads. Simulations indicate high economic efficiency of the proposed method for distributed BESSs. © 2021 IEEE.

AB - Distributed battery energy storage systems (BESSs) have been increasingly installed on the residential side to perform peak shaving and help improve photovoltaic (PV) energy utilization efficiency. However, associated battery degradation issues occur as BESSs are frequently operated, impairing economic benefits. Thus, this paper proposes an optimal daily scheduling method of distributed BESSs considering battery degradation cost. This method aims to maximize operating profits for BESS aggregators participating in electricity market, while minimizing the battery degradation cost. Firstly, a new linear model to calculate battery depth of discharge is developed, which can be efficiently involved in optimization models. Then, a battery daily degradation cost model is developed by utilizing a capital recovery factor and a curve fitting technique. Last, a daily scheduling optimization model considering the battery degradation cost is formulated and a scenario-based stochastic optimization method is applied to address uncertainties of PV generation and loads. Simulations indicate high economic efficiency of the proposed method for distributed BESSs. © 2021 IEEE.

KW - Battery energy storage system

KW - capital recovery factor

KW - depth of discharge

KW - stochastic optimization

KW - uncertainty

UR - https://www.scopus.com/pages/publications/85124156459

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85124156459&origin=recordpage

U2 - 10.1109/PESGM46819.2021.9638252

DO - 10.1109/PESGM46819.2021.9638252

M3 - RGC 32 - Refereed conference paper (with host publication)

T3 - IEEE Power and Energy Society General Meeting

BT - 2021 IEEE Power and Energy Society General Meeting (PESGM)

PB - IEEE

T2 - 2021 IEEE Power & Energy Society General Meeting (PESGM 2021)

Y2 - 26 July 2021 through 29 July 2021

ER -

Optimal Daily Scheduling ofDistributed Battery Energy Storage Systems Considering Battery Degradation Cost

Abstract

Publication series

Conference

UN SDGs

Research Keywords

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