A Dantzig-Wolfe Decomposition Algorithm for Linear Economic MPC of a Power Plant Portfolio

Publication: Research - peer-reviewConference abstract in proceedings – Annual report year: 2012

Standard

A Dantzig-Wolfe Decomposition Algorithm for Linear Economic MPC of a Power Plant Portfolio. / Standardi, Laura; Edlund, Kristian; Poulsen, Niels Kjølstad; Jørgensen, John Bagterp.

Proceedings of the 17th Nordic Process Control Workshop. ed. / John Bagterp Jørgensen; Jakob Kjøbsted Huusom; Gürkan Sin. Kogens Lyngby : Technical University of Denmark, 2012. p. 141.

Publication: Research - peer-reviewConference abstract in proceedings – Annual report year: 2012

Harvard

Standardi, L, Edlund, K, Poulsen, NK & Jørgensen, JB 2012, 'A Dantzig-Wolfe Decomposition Algorithm for Linear Economic MPC of a Power Plant Portfolio'. in JB Jørgensen, JK Huusom & G Sin (eds), Proceedings of the 17th Nordic Process Control Workshop. Technical University of Denmark, Kogens Lyngby, pp. 141.

APA

Standardi, L., Edlund, K., Poulsen, N. K., & Jørgensen, J. B. (2012). A Dantzig-Wolfe Decomposition Algorithm for Linear Economic MPC of a Power Plant Portfolio. In J. B. Jørgensen, J. K. Huusom, & G. Sin (Eds.), Proceedings of the 17th Nordic Process Control Workshop. (pp. 141). Kogens Lyngby: Technical University of Denmark.

CBE

Standardi L, Edlund K, Poulsen NK, Jørgensen JB. 2012. A Dantzig-Wolfe Decomposition Algorithm for Linear Economic MPC of a Power Plant Portfolio. Jørgensen JB, Huusom JK, Sin G, editors. In Proceedings of the 17th Nordic Process Control Workshop. Kogens Lyngby: Technical University of Denmark. pp. 141.

MLA

Standardi, Laura et al. "A Dantzig-Wolfe Decomposition Algorithm for Linear Economic MPC of a Power Plant Portfolio"., Jørgensen, John Bagterp Huusom, Jakob Kjøbsted Sin, Gürkan (ed.). Proceedings of the 17th Nordic Process Control Workshop. Kogens Lyngby: Technical University of Denmark. 2012. 141.

Vancouver

Standardi L, Edlund K, Poulsen NK, Jørgensen JB. A Dantzig-Wolfe Decomposition Algorithm for Linear Economic MPC of a Power Plant Portfolio. In Jørgensen JB, Huusom JK, Sin G, editors, Proceedings of the 17th Nordic Process Control Workshop. Kogens Lyngby: Technical University of Denmark. 2012. p. 141.

Author

Standardi, Laura; Edlund, Kristian; Poulsen, Niels Kjølstad; Jørgensen, John Bagterp / A Dantzig-Wolfe Decomposition Algorithm for Linear Economic MPC of a Power Plant Portfolio.

Proceedings of the 17th Nordic Process Control Workshop. ed. / John Bagterp Jørgensen; Jakob Kjøbsted Huusom; Gürkan Sin. Kogens Lyngby : Technical University of Denmark, 2012. p. 141.

Publication: Research - peer-reviewConference abstract in proceedings – Annual report year: 2012

Bibtex

@inbook{e55704becb9e411a9d25600d1367b1fc,
title = "A Dantzig-Wolfe Decomposition Algorithm for Linear Economic MPC of a Power Plant Portfolio",
keywords = "Decoupled subsystems, Power system control, Model based control, Predictive control, Decomposition, Optimization",
publisher = "Technical University of Denmark",
author = "Laura Standardi and Kristian Edlund and Poulsen, {Niels Kjølstad} and Jørgensen, {John Bagterp}",
year = "2012",
editor = "Jørgensen, {John Bagterp} and Huusom, {Jakob Kjøbsted} and Gürkan Sin",
isbn = "978-87-643-0946-1",
pages = "141",
booktitle = "Proceedings of the 17th Nordic Process Control Workshop",

}

RIS

TY - ABST

T1 - A Dantzig-Wolfe Decomposition Algorithm for Linear Economic MPC of a Power Plant Portfolio

A1 - Standardi,Laura

A1 - Edlund,Kristian

A1 - Poulsen,Niels Kjølstad

A1 - Jørgensen,John Bagterp

AU - Standardi,Laura

AU - Edlund,Kristian

AU - Poulsen,Niels Kjølstad

AU - Jørgensen,John Bagterp

PB - Technical University of Denmark

CY - Kogens Lyngby

PY - 2012

Y1 - 2012

N2 - Recently, the interest in renewable energy sources is increasing. In the short future, their penetration in the power systems will be signicantly higher than today. Denmark is working on achieving its goal by 2020 of having 30% of the energy production provided by renewable sources. 50% of the total power consumption is expected to stem from wind turbines. Due to the inherent stochasticity in renewable energy systems (RES), their energy production is usually complicated to forecast and control. The aim of the smart grid in which consumers as well as producers are controlled is to allow for larger variation in the power production due to the signicant amount of renewable energy. The multiple power generators and consumers must be coordinated to balance the supply and demand for power at all times. The aim of this study is to examine a control technique for large scale distributed energy systems (DES), where a signicant amount of renewable energy sources are present. Economic Model Predictive Control (MPC) is applied to control the power generators, minimizing the cost and producing the amount of energy required. We examine the large scale scenario, where multiple power generators and consumers such as e.g. electrical vehicles, heat pumps for domestic heating, and refrigeration and cooling systems must be controlled to balance the supply and demand for power. The system is very large scale. To address the large scale of the system and be able to compute the control decisions within a sample period, Dantzig-Wolfe decomposition is used for solution of the resulting linear program describing the Economic MPC of such systems. The controller obtained has been tested by simulations of a power portfolio system.

AB - Recently, the interest in renewable energy sources is increasing. In the short future, their penetration in the power systems will be signicantly higher than today. Denmark is working on achieving its goal by 2020 of having 30% of the energy production provided by renewable sources. 50% of the total power consumption is expected to stem from wind turbines. Due to the inherent stochasticity in renewable energy systems (RES), their energy production is usually complicated to forecast and control. The aim of the smart grid in which consumers as well as producers are controlled is to allow for larger variation in the power production due to the signicant amount of renewable energy. The multiple power generators and consumers must be coordinated to balance the supply and demand for power at all times. The aim of this study is to examine a control technique for large scale distributed energy systems (DES), where a signicant amount of renewable energy sources are present. Economic Model Predictive Control (MPC) is applied to control the power generators, minimizing the cost and producing the amount of energy required. We examine the large scale scenario, where multiple power generators and consumers such as e.g. electrical vehicles, heat pumps for domestic heating, and refrigeration and cooling systems must be controlled to balance the supply and demand for power. The system is very large scale. To address the large scale of the system and be able to compute the control decisions within a sample period, Dantzig-Wolfe decomposition is used for solution of the resulting linear program describing the Economic MPC of such systems. The controller obtained has been tested by simulations of a power portfolio system.

KW - Decoupled subsystems

KW - Power system control

KW - Model based control

KW - Predictive control

KW - Decomposition

KW - Optimization

UR - http://npcw17.imm.dtu.dk/

SN - 978-87-643-0946-1

BT - Proceedings of the 17th Nordic Process Control Workshop

T2 - Proceedings of the 17th Nordic Process Control Workshop

A2 - Sin,Gürkan

ED - Sin,Gürkan

SP - 141

ER -