Optimal sizing of behind-the-meter BESS for providing stackable services

Yichao Zhang; Amjad Anvari-Moghaddam; Saeed Peyghami; Tomislav Dragičević; Yuan Li; Frede Blaabjerg

doi:10.1109/PEDG54999.2022.9923222

Optimal sizing of behind-the-meter BESS for providing stackable services

Yichao Zhang, Amjad Anvari-Moghaddam, Saeed Peyghami, Tomislav Dragičević, Yuan Li, Frede Blaabjerg

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

4 Citationer (Scopus)

98 Downloads (Pure)

Abstract

The behind-the-meter (BTM) battery energy storage system (BESS) is mainly utilized for providing load management. But the saved electricity bill hardly offsets the high upfront investment cost. The multi-revenue streams created by certain stackable services can offset the initial cost by reasonably designing the size and operation strategy of BESS. Therefore, to maximize the return rate on BESS investment, a two-stage optimal model for optimizing the power and energy capacity of a BTM BESS is proposed in this paper. The provided stackable services by BESS include energy arbitrage and frequency regulation. A hybrid algorithm combining the genetic algorithm and a mixed-integer linear programming model is employed to co-optimize the size and operation strategy of BESS. The real load data from the plastic manufacturing industry and the frequency regulation information from the PJM market are employed as databases to validate the availability and effectiveness of the proposed model and the hybrid algorithm.

Originalsprog	Engelsk
Titel	Proceedings of the 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems (PEDG)
Antal sider	6
Forlag	IEEE
Publikationsdato	jun. 2022
Sider	1-6
Artikelnummer	9923222
ISBN (Trykt)	978-1-6654-6619-6
ISBN (Elektronisk)	978-1-6654-6618-9
DOI	https://doi.org/10.1109/PEDG54999.2022.9923222
Status	Udgivet - jun. 2022
Begivenhed	13th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022 - Kiel, Tyskland Varighed: 26 jun. 2022 → 29 jun. 2022

Konference

Konference	13th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022
Land/Område	Tyskland
By	Kiel
Periode	26/06/2022 → 29/06/2022

Navn	IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG)
ISSN	2329-5767

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Zhang, Y., Anvari-Moghaddam, A., Peyghami, S., Dragičević, T., Li, Y., & Blaabjerg, F. (2022). Optimal sizing of behind-the-meter BESS for providing stackable services. I Proceedings of the 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems (PEDG) (s. 1-6). Artikel 9923222 IEEE. https://doi.org/10.1109/PEDG54999.2022.9923222

Zhang, Yichao ; Anvari-Moghaddam, Amjad ; Peyghami, Saeed et al. / Optimal sizing of behind-the-meter BESS for providing stackable services. Proceedings of the 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems (PEDG). IEEE, 2022. s. 1-6 (IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG) ).

@inproceedings{a9898b8ab51143eeb6f2d31efce938ae,

title = "Optimal sizing of behind-the-meter BESS for providing stackable services",

abstract = "The behind-the-meter (BTM) battery energy storage system (BESS) is mainly utilized for providing load management. But the saved electricity bill hardly offsets the high upfront investment cost. The multi-revenue streams created by certain stackable services can offset the initial cost by reasonably designing the size and operation strategy of BESS. Therefore, to maximize the return rate on BESS investment, a two-stage optimal model for optimizing the power and energy capacity of a BTM BESS is proposed in this paper. The provided stackable services by BESS include energy arbitrage and frequency regulation. A hybrid algorithm combining the genetic algorithm and a mixed-integer linear programming model is employed to co-optimize the size and operation strategy of BESS. The real load data from the plastic manufacturing industry and the frequency regulation information from the PJM market are employed as databases to validate the availability and effectiveness of the proposed model and the hybrid algorithm.",

keywords = "BTM BESS, Mixed integer linear programming, Power electronics, capacity sizing, energy arbitrage, frequency regulation, multi-revenue streams, size optimization",

author = "Yichao Zhang and Amjad Anvari-Moghaddam and Saeed Peyghami and Tomislav Dragi{\v c}evi{\'c} and Yuan Li and Frede Blaabjerg",

year = "2022",

month = jun,

doi = "10.1109/PEDG54999.2022.9923222",

language = "English",

isbn = "978-1-6654-6619-6",

series = "IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG) ",

pages = "1--6",

booktitle = "Proceedings of the 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems (PEDG)",

publisher = "IEEE",

address = "United States",

note = "13th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022 ; Conference date: 26-06-2022 Through 29-06-2022",

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Zhang, Y , Anvari-Moghaddam, A , Peyghami, S, Dragičević, T, Li, Y & Blaabjerg, F 2022, Optimal sizing of behind-the-meter BESS for providing stackable services. i Proceedings of the 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems (PEDG)., 9923222, IEEE, IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG) , s. 1-6, 13th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022, Kiel, Tyskland, 26/06/2022. https://doi.org/10.1109/PEDG54999.2022.9923222

Optimal sizing of behind-the-meter BESS for providing stackable services. / Zhang, Yichao ; Anvari-Moghaddam, Amjad ; Peyghami, Saeed et al.
Proceedings of the 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems (PEDG). IEEE, 2022. s. 1-6 9923222 (IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG) ).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

TY - GEN

T1 - Optimal sizing of behind-the-meter BESS for providing stackable services

AU - Zhang, Yichao

AU - Anvari-Moghaddam, Amjad

AU - Peyghami, Saeed

AU - Dragičević, Tomislav

AU - Li, Yuan

AU - Blaabjerg, Frede

PY - 2022/6

Y1 - 2022/6

N2 - The behind-the-meter (BTM) battery energy storage system (BESS) is mainly utilized for providing load management. But the saved electricity bill hardly offsets the high upfront investment cost. The multi-revenue streams created by certain stackable services can offset the initial cost by reasonably designing the size and operation strategy of BESS. Therefore, to maximize the return rate on BESS investment, a two-stage optimal model for optimizing the power and energy capacity of a BTM BESS is proposed in this paper. The provided stackable services by BESS include energy arbitrage and frequency regulation. A hybrid algorithm combining the genetic algorithm and a mixed-integer linear programming model is employed to co-optimize the size and operation strategy of BESS. The real load data from the plastic manufacturing industry and the frequency regulation information from the PJM market are employed as databases to validate the availability and effectiveness of the proposed model and the hybrid algorithm.

AB - The behind-the-meter (BTM) battery energy storage system (BESS) is mainly utilized for providing load management. But the saved electricity bill hardly offsets the high upfront investment cost. The multi-revenue streams created by certain stackable services can offset the initial cost by reasonably designing the size and operation strategy of BESS. Therefore, to maximize the return rate on BESS investment, a two-stage optimal model for optimizing the power and energy capacity of a BTM BESS is proposed in this paper. The provided stackable services by BESS include energy arbitrage and frequency regulation. A hybrid algorithm combining the genetic algorithm and a mixed-integer linear programming model is employed to co-optimize the size and operation strategy of BESS. The real load data from the plastic manufacturing industry and the frequency regulation information from the PJM market are employed as databases to validate the availability and effectiveness of the proposed model and the hybrid algorithm.

KW - BTM BESS

KW - Mixed integer linear programming

KW - Power electronics

KW - capacity sizing

KW - energy arbitrage

KW - frequency regulation

KW - multi-revenue streams

KW - size optimization

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DO - 10.1109/PEDG54999.2022.9923222

M3 - Article in proceeding

SN - 978-1-6654-6619-6

T3 - IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG)

SP - 1

EP - 6

BT - Proceedings of the 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems (PEDG)

PB - IEEE

T2 - 13th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2022

Y2 - 26 June 2022 through 29 June 2022

ER -

Zhang Y , Anvari-Moghaddam A , Peyghami S, Dragičević T, Li Y , Blaabjerg F. Optimal sizing of behind-the-meter BESS for providing stackable services. I Proceedings of the 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems (PEDG). IEEE. 2022. s. 1-6. 9923222. (IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG) ). doi: 10.1109/PEDG54999.2022.9923222

Optimal sizing of behind-the-meter BESS for providing stackable services

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