Integrating Peer-to-Peer Energy Trading of Microgrids into Deregulated Electricity Market by Cascaded Model Predictive Control

Cheng LYU; Youwei JIA; Mengge SHI; Zhao XU

doi:10.1109/EI252483.2021.9713576

Integrating Peer-to-Peer Energy Trading of Microgrids into Deregulated Electricity Market by Cascaded Model Predictive Control

Cheng LYU^*, Youwei JIA, Mengge SHI, Zhao XU

^*Corresponding author for this work

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

1 Citation (Scopus)

Abstract

Peer-to-peer (P2P) energy trading of microgrids is considered as a promising solution in reducing the carbon emission of renewable-embedded energy systems. This paper proposes a novel energy market framework for enabling the P2P local transactions under the deregulated market environment. The proposed market model is aimed to provide a practical mechanism design to incentivize optimal P2P energy trading in the existing electricity market. A cascaded model predictive control (MPC) problem formulation is devised for both the day-ahead market and adjustment markets. Finally, numerical results demonstrate the effectiveness of the proposed framework in integrating microgrid P2P trading into the electricity market.

Original language	English
Title of host publication	2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2 2021)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	114-118
Number of pages	5
ISBN (Electronic)	9781665434256
ISBN (Print)	9781665434263
DOIs	https://doi.org/10.1109/EI252483.2021.9713576
Publication status	Published - Apr 2022
Externally published	Yes
Event	5th IEEE Conference on Energy Internet and Energy System Integration, EI2 2021 - Taiyuan, China Duration: 22 Oct 2021 → 25 Oct 2021

Conference

Conference	5th IEEE Conference on Energy Internet and Energy System Integration, EI2 2021
Country/Territory	China
City	Taiyuan
Period	22/10/21 → 25/10/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE

Keywords

electricity market
microgrids
model predictive control
Peer-to-peer energy trading

UN SDGs

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

Access to Document

10.1109/EI252483.2021.9713576

Cite this

LYU, C., JIA, Y., SHI, M., & XU, Z. (2022). Integrating Peer-to-Peer Energy Trading of Microgrids into Deregulated Electricity Market by Cascaded Model Predictive Control. In 2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2 2021) (pp. 114-118). Article POA-021 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EI252483.2021.9713576

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title = "Integrating Peer-to-Peer Energy Trading of Microgrids into Deregulated Electricity Market by Cascaded Model Predictive Control",

abstract = "Peer-to-peer (P2P) energy trading of microgrids is considered as a promising solution in reducing the carbon emission of renewable-embedded energy systems. This paper proposes a novel energy market framework for enabling the P2P local transactions under the deregulated market environment. The proposed market model is aimed to provide a practical mechanism design to incentivize optimal P2P energy trading in the existing electricity market. A cascaded model predictive control (MPC) problem formulation is devised for both the day-ahead market and adjustment markets. Finally, numerical results demonstrate the effectiveness of the proposed framework in integrating microgrid P2P trading into the electricity market.",

keywords = "electricity market, microgrids, model predictive control, Peer-to-peer energy trading",

author = "Cheng LYU and Youwei JIA and Mengge SHI and Zhao XU",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE; 5th IEEE Conference on Energy Internet and Energy System Integration, EI2 2021 ; Conference date: 22-10-2021 Through 25-10-2021",

year = "2022",

month = apr,

doi = "10.1109/EI252483.2021.9713576",

language = "English",

isbn = "9781665434263",

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booktitle = "2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2 2021)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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LYU, C, JIA, Y, SHI, M & XU, Z 2022, Integrating Peer-to-Peer Energy Trading of Microgrids into Deregulated Electricity Market by Cascaded Model Predictive Control. in 2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2 2021)., POA-021, Institute of Electrical and Electronics Engineers Inc., pp. 114-118, 5th IEEE Conference on Energy Internet and Energy System Integration, EI2 2021, Taiyuan, China, 22/10/21. https://doi.org/10.1109/EI252483.2021.9713576

Integrating Peer-to-Peer Energy Trading of Microgrids into Deregulated Electricity Market by Cascaded Model Predictive Control. / LYU, Cheng; JIA, Youwei; SHI, Mengge et al.
2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2 2021). Institute of Electrical and Electronics Engineers Inc., 2022. p. 114-118 POA-021.

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

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T1 - Integrating Peer-to-Peer Energy Trading of Microgrids into Deregulated Electricity Market by Cascaded Model Predictive Control

AU - LYU, Cheng

AU - JIA, Youwei

AU - SHI, Mengge

AU - XU, Zhao

PY - 2022/4

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N2 - Peer-to-peer (P2P) energy trading of microgrids is considered as a promising solution in reducing the carbon emission of renewable-embedded energy systems. This paper proposes a novel energy market framework for enabling the P2P local transactions under the deregulated market environment. The proposed market model is aimed to provide a practical mechanism design to incentivize optimal P2P energy trading in the existing electricity market. A cascaded model predictive control (MPC) problem formulation is devised for both the day-ahead market and adjustment markets. Finally, numerical results demonstrate the effectiveness of the proposed framework in integrating microgrid P2P trading into the electricity market.

AB - Peer-to-peer (P2P) energy trading of microgrids is considered as a promising solution in reducing the carbon emission of renewable-embedded energy systems. This paper proposes a novel energy market framework for enabling the P2P local transactions under the deregulated market environment. The proposed market model is aimed to provide a practical mechanism design to incentivize optimal P2P energy trading in the existing electricity market. A cascaded model predictive control (MPC) problem formulation is devised for both the day-ahead market and adjustment markets. Finally, numerical results demonstrate the effectiveness of the proposed framework in integrating microgrid P2P trading into the electricity market.

KW - electricity market

KW - microgrids

KW - model predictive control

KW - Peer-to-peer energy trading

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DO - 10.1109/EI252483.2021.9713576

M3 - Conference paper (refereed)

AN - SCOPUS:85128197113

SN - 9781665434263

SP - 114

EP - 118

BT - 2021 IEEE 5th Conference on Energy Internet and Energy System Integration (EI2 2021)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 5th IEEE Conference on Energy Internet and Energy System Integration, EI2 2021

Y2 - 22 October 2021 through 25 October 2021

ER -

Integrating Peer-to-Peer Energy Trading of Microgrids into Deregulated Electricity Market by Cascaded Model Predictive Control

Abstract

Conference

Bibliographical note

Keywords

UN SDGs

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