Frequency regulation using optimal demand and governor response in a deregulated environment

Ragini Patel; Chaojie Li; Liuping Wang; Brendan McGrath; Xinghuo Yu

doi:10.1109/IECON.2017.8217303

Frequency regulation using optimal demand and governor response in a deregulated environment

Ragini Patel
, Chaojie Li
, Liuping Wang
, Brendan McGrath
, Xinghuo Yu

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

Abstract

A distributed control law based on Model predictive Control (MPC) scheme is proposed for secondary frequency control in a deregulated market, which utilizes Demand Response (DR) along with Automatic generation Control (AGC). The proposed strategy of combining DR and AGC is termed as Load frequency Control (LFC) in the paper. The main contribution of the paper focuses on developing a model for LFC, which combines DR as well as Governor Response (GR) as manipulated variables. The new model is then used in an embedded integrator based distributed MPC algorithm to optimally choose between the GR and DR for the frequency regulation within system's constraints and cost. The algorithm is tested on a system with two areas interconnected by means of a tie line and shows that by choosing DR the frequency response not only improves but also the cost of frequency regulation reduces. © 2017 IEEE.

Original language	English
Title of host publication	Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
Publisher	IEEE
Pages	7439-7444
Volume	2017-January
ISBN (Print)	9781538611272
DOIs	https://doi.org/10.1109/IECON.2017.8217303
Publication status	Published - 15 Dec 2017
Externally published	Yes
Event	43rd Annual Conference of the IEEE Industrial Electronics Society (IECON 2017) - China National Convention Center, Beijing, China Duration: 29 Oct 2017 → 1 Nov 2017 https://ieeexplore.ieee.org/xpl/conhome/8168197/proceeding

Publication series

Name	Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
Volume	2017-January

Conference

Conference	43rd Annual Conference of the IEEE Industrial Electronics Society (IECON 2017)
Place	China
City	Beijing
Period	29/10/17 → 1/11/17
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8168197/proceeding

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

Aggregator
Demand Response
Embedded integrator
Interconnected power system
Load frequency control
Model predictive control

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10.1109/IECON.2017.8217303

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Patel, R., Li, C., Wang, L., McGrath, B., & Yu, X. (2017). Frequency regulation using optimal demand and governor response in a deregulated environment. In Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society (Vol. 2017-January, pp. 7439-7444). (Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society; Vol. 2017-January). IEEE. https://doi.org/10.1109/IECON.2017.8217303

Patel, Ragini ; Li, Chaojie ; Wang, Liuping et al. / Frequency regulation using optimal demand and governor response in a deregulated environment. Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. Vol. 2017-January IEEE, 2017. pp. 7439-7444 (Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society).

@inproceedings{b525ae584c58463f8b2a0157b7cb8c99,

title = "Frequency regulation using optimal demand and governor response in a deregulated environment",

abstract = "A distributed control law based on Model predictive Control (MPC) scheme is proposed for secondary frequency control in a deregulated market, which utilizes Demand Response (DR) along with Automatic generation Control (AGC). The proposed strategy of combining DR and AGC is termed as Load frequency Control (LFC) in the paper. The main contribution of the paper focuses on developing a model for LFC, which combines DR as well as Governor Response (GR) as manipulated variables. The new model is then used in an embedded integrator based distributed MPC algorithm to optimally choose between the GR and DR for the frequency regulation within system's constraints and cost. The algorithm is tested on a system with two areas interconnected by means of a tie line and shows that by choosing DR the frequency response not only improves but also the cost of frequency regulation reduces. {\textcopyright} 2017 IEEE.",

keywords = "Aggregator, Demand Response, Embedded integrator, Interconnected power system, Load frequency control, Model predictive control",

author = "Ragini Patel and Chaojie Li and Liuping Wang and Brendan McGrath and Xinghuo Yu",

note = "Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].; 43rd Annual Conference of the IEEE Industrial Electronics Society (IECON 2017) ; Conference date: 29-10-2017 Through 01-11-2017",

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doi = "10.1109/IECON.2017.8217303",

language = "English",

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Patel, R, Li, C, Wang, L, McGrath, B & Yu, X 2017, Frequency regulation using optimal demand and governor response in a deregulated environment. in Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. vol. 2017-January, Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, vol. 2017-January, IEEE, pp. 7439-7444, 43rd Annual Conference of the IEEE Industrial Electronics Society (IECON 2017), Beijing, China, 29/10/17. https://doi.org/10.1109/IECON.2017.8217303

Frequency regulation using optimal demand and governor response in a deregulated environment. / Patel, Ragini; Li, Chaojie; Wang, Liuping et al.
Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. Vol. 2017-January IEEE, 2017. p. 7439-7444 (Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society; Vol. 2017-January).

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

TY - GEN

T1 - Frequency regulation using optimal demand and governor response in a deregulated environment

AU - Patel, Ragini

AU - Li, Chaojie

AU - Wang, Liuping

AU - McGrath, Brendan

AU - Yu, Xinghuo

N1 - Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

PY - 2017/12/15

Y1 - 2017/12/15

N2 - A distributed control law based on Model predictive Control (MPC) scheme is proposed for secondary frequency control in a deregulated market, which utilizes Demand Response (DR) along with Automatic generation Control (AGC). The proposed strategy of combining DR and AGC is termed as Load frequency Control (LFC) in the paper. The main contribution of the paper focuses on developing a model for LFC, which combines DR as well as Governor Response (GR) as manipulated variables. The new model is then used in an embedded integrator based distributed MPC algorithm to optimally choose between the GR and DR for the frequency regulation within system's constraints and cost. The algorithm is tested on a system with two areas interconnected by means of a tie line and shows that by choosing DR the frequency response not only improves but also the cost of frequency regulation reduces. © 2017 IEEE.

AB - A distributed control law based on Model predictive Control (MPC) scheme is proposed for secondary frequency control in a deregulated market, which utilizes Demand Response (DR) along with Automatic generation Control (AGC). The proposed strategy of combining DR and AGC is termed as Load frequency Control (LFC) in the paper. The main contribution of the paper focuses on developing a model for LFC, which combines DR as well as Governor Response (GR) as manipulated variables. The new model is then used in an embedded integrator based distributed MPC algorithm to optimally choose between the GR and DR for the frequency regulation within system's constraints and cost. The algorithm is tested on a system with two areas interconnected by means of a tie line and shows that by choosing DR the frequency response not only improves but also the cost of frequency regulation reduces. © 2017 IEEE.

KW - Aggregator

KW - Demand Response

KW - Embedded integrator

KW - Interconnected power system

KW - Load frequency control

KW - Model predictive control

UR - https://www.scopus.com/pages/publications/85046662276

UR - https://www.scopus.com/pages/publications/85046662276#tab=impact

U2 - 10.1109/IECON.2017.8217303

DO - 10.1109/IECON.2017.8217303

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

SN - 9781538611272

VL - 2017-January

T3 - Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society

SP - 7439

EP - 7444

BT - Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society

PB - IEEE

T2 - 43rd Annual Conference of the IEEE Industrial Electronics Society (IECON 2017)

Y2 - 29 October 2017 through 1 November 2017

ER -

Patel R, Li C, Wang L, McGrath B, Yu X. Frequency regulation using optimal demand and governor response in a deregulated environment. In Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. Vol. 2017-January. IEEE. 2017. p. 7439-7444. (Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society). doi: 10.1109/IECON.2017.8217303

Frequency regulation using optimal demand and governor response in a deregulated environment

Abstract

Publication series

Conference

Bibliographical note

Research Keywords

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