Hybrid Approximate Dynamic Programming Approach for Dynamic Optimal Energy Flow in the Integrated Gas and Power Systems

Hang Shuai; Xiaomeng Ai; Jinyu Wen; Jiakun Fang; Zhe Chen; Haibo He

doi:10.1109/EI2.2017.8245577

Hybrid Approximate Dynamic Programming Approach for Dynamic Optimal Energy Flow in the Integrated Gas and Power Systems

Hang Shuai
, Xiaomeng Ai
, Jinyu Wen
, Jiakun Fang
, Zhe Chen
, Haibo He

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

5 Citationer (Scopus)

Abstract

This paper proposes a hybrid approximate dynamic programming (ADP) approach for the multiple time-period optimal power flow in integrated gas and power systems. ADP successively solves Bellman's equation to make decisions according to the current state of the system. So, the updated near future forecast information is not fully utilized. While model predictive control (MPC) as a look ahead policy can integrate the updated forecast in the optimization process. The proposed hybrid optimization approach makes full use of the advantages of ADP and MPC to obtain a better solution by using the real-time updated forecast information. The simulation results demonstrate the effectiveness of the proposed algorithm.

Originalsprog	Engelsk
Titel	Proceedings of 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2)
Antal sider	6
Forlag	IEEE Press
Publikationsdato	nov. 2017
ISBN (Elektronisk)	978-1-5386-1427-3
DOI	https://doi.org/10.1109/EI2.2017.8245577
Status	Udgivet - nov. 2017
Begivenhed	2017 IEEE Conference on Energy Internet and Energy System Integration (EI2) - Beijing, Kina Varighed: 26 nov. 2017 → 28 nov. 2017

Konference

Konference	2017 IEEE Conference on Energy Internet and Energy System Integration (EI2)
Land/Område	Kina
By	Beijing
Periode	26/11/2017 → 28/11/2017

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10.1109/EI2.2017.8245577

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Citationsformater

@inproceedings{42215225fd0044069830abd643f4dcb2,

title = "Hybrid Approximate Dynamic Programming Approach for Dynamic Optimal Energy Flow in the Integrated Gas and Power Systems",

abstract = "This paper proposes a hybrid approximate dynamic programming (ADP) approach for the multiple time-period optimal power flow in integrated gas and power systems. ADP successively solves Bellman's equation to make decisions according to the current state of the system. So, the updated near future forecast information is not fully utilized. While model predictive control (MPC) as a look ahead policy can integrate the updated forecast in the optimization process. The proposed hybrid optimization approach makes full use of the advantages of ADP and MPC to obtain a better solution by using the real-time updated forecast information. The simulation results demonstrate the effectiveness of the proposed algorithm.",

keywords = "Integrated gas and power systems, Dynamic energy flow, Approximate dynamic programming (ADP), Model predictive control (MPC), Online optimization",

author = "Hang Shuai and Xiaomeng Ai and Jinyu Wen and Jiakun Fang and Zhe Chen and Haibo He",

year = "2017",

month = nov,

doi = "10.1109/EI2.2017.8245577",

language = "English",

booktitle = "Proceedings of 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2)",

publisher = "IEEE Press",

note = "2017 IEEE Conference on Energy Internet and Energy System Integration (EI2) ; Conference date: 26-11-2017 Through 28-11-2017",

}

Shuai, H, Ai, X, Wen, J, Fang, J, Chen, Z & He, H 2017, Hybrid Approximate Dynamic Programming Approach for Dynamic Optimal Energy Flow in the Integrated Gas and Power Systems. i Proceedings of 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2). IEEE Press, 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2), Beijing, Kina, 26/11/2017. https://doi.org/10.1109/EI2.2017.8245577

Hybrid Approximate Dynamic Programming Approach for Dynamic Optimal Energy Flow in the Integrated Gas and Power Systems. / Shuai, Hang; Ai, Xiaomeng; Wen, Jinyu et al.
Proceedings of 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2). IEEE Press, 2017.

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

TY - GEN

T1 - Hybrid Approximate Dynamic Programming Approach for Dynamic Optimal Energy Flow in the Integrated Gas and Power Systems

AU - Shuai, Hang

AU - Ai, Xiaomeng

AU - Wen, Jinyu

AU - Fang, Jiakun

AU - Chen, Zhe

AU - He, Haibo

PY - 2017/11

Y1 - 2017/11

N2 - This paper proposes a hybrid approximate dynamic programming (ADP) approach for the multiple time-period optimal power flow in integrated gas and power systems. ADP successively solves Bellman's equation to make decisions according to the current state of the system. So, the updated near future forecast information is not fully utilized. While model predictive control (MPC) as a look ahead policy can integrate the updated forecast in the optimization process. The proposed hybrid optimization approach makes full use of the advantages of ADP and MPC to obtain a better solution by using the real-time updated forecast information. The simulation results demonstrate the effectiveness of the proposed algorithm.

AB - This paper proposes a hybrid approximate dynamic programming (ADP) approach for the multiple time-period optimal power flow in integrated gas and power systems. ADP successively solves Bellman's equation to make decisions according to the current state of the system. So, the updated near future forecast information is not fully utilized. While model predictive control (MPC) as a look ahead policy can integrate the updated forecast in the optimization process. The proposed hybrid optimization approach makes full use of the advantages of ADP and MPC to obtain a better solution by using the real-time updated forecast information. The simulation results demonstrate the effectiveness of the proposed algorithm.

KW - Integrated gas and power systems

KW - Dynamic energy flow

KW - Approximate dynamic programming (ADP)

KW - Model predictive control (MPC)

KW - Online optimization

U2 - 10.1109/EI2.2017.8245577

DO - 10.1109/EI2.2017.8245577

M3 - Article in proceeding

BT - Proceedings of 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2)

PB - IEEE Press

T2 - 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2)

Y2 - 26 November 2017 through 28 November 2017

ER -

Hybrid Approximate Dynamic Programming Approach for Dynamic Optimal Energy Flow in the Integrated Gas and Power Systems

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