Model predictive control for wind power generation smoothing with controlled battery storage

Muhammad Khalid; Andrey V. Savkin

doi:10.1109/CDC.2009.5400002

Model predictive control for wind power generation smoothing with controlled battery storage

Muhammad Khalid^*
, Andrey V. Savkin

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

27 Scopus citations

Abstract

The aim of this study is to design a controller based on model predictive control (MPC) theory to smooth wind power generation along with the controlled storage of the wind energy in batteries in presence of variety of constraints. In this study, a proposed wind power prediction system is utilized to optimize the performance of the controller. The proposed controller is capable of smoothing wind power by utilizing the inputs from our prediction system which in turn optimizes the maximum ramp rate requirement. At the same time this controller optimizes the state of charge of battery under practical constraints. The prediction model involved is capable of predicting wind power multi-step ahead which are used in the optimization part of the controller. The proposed system is tested for different scenarios and under variety of hard constraints. The effectiveness of our proposed model is shown by simulation results.

Original language	English
Title of host publication	Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	7849-7853
Number of pages	5
ISBN (Print)	9781424438716
DOIs	https://doi.org/10.1109/CDC.2009.5400002
State	Published - 2009
Externally published	Yes
Event	48th IEEE Conference on Decision and Control, CDC 2009, held Jointly with the 28th Chinese Control Conference, CCC 2009 - Shanghai, China Duration: 15 Dec 2009 → 18 Dec 2009

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	48th IEEE Conference on Decision and Control, CDC 2009, held Jointly with the 28th Chinese Control Conference, CCC 2009
Country/Territory	China
City	Shanghai
Period	15/12/09 → 18/12/09

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Battery energy storage
Model predictive control
Smoothing
Wind power prediction

ASJC Scopus subject areas

Control and Systems Engineering
Modeling and Simulation
Control and Optimization

Access to Document

10.1109/CDC.2009.5400002

Cite this

Khalid, M., & Savkin, A. V. (2009). Model predictive control for wind power generation smoothing with controlled battery storage. In Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 (pp. 7849-7853). Article 5400002 (Proceedings of the IEEE Conference on Decision and Control). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2009.5400002

Khalid, Muhammad ; Savkin, Andrey V. / Model predictive control for wind power generation smoothing with controlled battery storage. Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009. Institute of Electrical and Electronics Engineers Inc., 2009. pp. 7849-7853 (Proceedings of the IEEE Conference on Decision and Control).

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title = "Model predictive control for wind power generation smoothing with controlled battery storage",

abstract = "The aim of this study is to design a controller based on model predictive control (MPC) theory to smooth wind power generation along with the controlled storage of the wind energy in batteries in presence of variety of constraints. In this study, a proposed wind power prediction system is utilized to optimize the performance of the controller. The proposed controller is capable of smoothing wind power by utilizing the inputs from our prediction system which in turn optimizes the maximum ramp rate requirement. At the same time this controller optimizes the state of charge of battery under practical constraints. The prediction model involved is capable of predicting wind power multi-step ahead which are used in the optimization part of the controller. The proposed system is tested for different scenarios and under variety of hard constraints. The effectiveness of our proposed model is shown by simulation results.",

keywords = "Battery energy storage, Model predictive control, Smoothing, Wind power prediction",

author = "Muhammad Khalid and Savkin, \{Andrey V.\}",

year = "2009",

doi = "10.1109/CDC.2009.5400002",

language = "English",

isbn = "9781424438716",

series = "Proceedings of the IEEE Conference on Decision and Control",

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

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booktitle = "Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009",

address = "United States",

note = "48th IEEE Conference on Decision and Control, CDC 2009, held Jointly with the 28th Chinese Control Conference, CCC 2009 ; Conference date: 15-12-2009 Through 18-12-2009",

}

Khalid, M & Savkin, AV 2009, Model predictive control for wind power generation smoothing with controlled battery storage. in Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009., 5400002, Proceedings of the IEEE Conference on Decision and Control, Institute of Electrical and Electronics Engineers Inc., pp. 7849-7853, 48th IEEE Conference on Decision and Control, CDC 2009, held Jointly with the 28th Chinese Control Conference, CCC 2009, Shanghai, China, 15/12/09. https://doi.org/10.1109/CDC.2009.5400002

Model predictive control for wind power generation smoothing with controlled battery storage. / Khalid, Muhammad; Savkin, Andrey V.
Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009. Institute of Electrical and Electronics Engineers Inc., 2009. p. 7849-7853 5400002 (Proceedings of the IEEE Conference on Decision and Control).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Model predictive control for wind power generation smoothing with controlled battery storage

AU - Khalid, Muhammad

AU - Savkin, Andrey V.

PY - 2009

Y1 - 2009

N2 - The aim of this study is to design a controller based on model predictive control (MPC) theory to smooth wind power generation along with the controlled storage of the wind energy in batteries in presence of variety of constraints. In this study, a proposed wind power prediction system is utilized to optimize the performance of the controller. The proposed controller is capable of smoothing wind power by utilizing the inputs from our prediction system which in turn optimizes the maximum ramp rate requirement. At the same time this controller optimizes the state of charge of battery under practical constraints. The prediction model involved is capable of predicting wind power multi-step ahead which are used in the optimization part of the controller. The proposed system is tested for different scenarios and under variety of hard constraints. The effectiveness of our proposed model is shown by simulation results.

AB - The aim of this study is to design a controller based on model predictive control (MPC) theory to smooth wind power generation along with the controlled storage of the wind energy in batteries in presence of variety of constraints. In this study, a proposed wind power prediction system is utilized to optimize the performance of the controller. The proposed controller is capable of smoothing wind power by utilizing the inputs from our prediction system which in turn optimizes the maximum ramp rate requirement. At the same time this controller optimizes the state of charge of battery under practical constraints. The prediction model involved is capable of predicting wind power multi-step ahead which are used in the optimization part of the controller. The proposed system is tested for different scenarios and under variety of hard constraints. The effectiveness of our proposed model is shown by simulation results.

KW - Battery energy storage

KW - Model predictive control

KW - Smoothing

KW - Wind power prediction

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U2 - 10.1109/CDC.2009.5400002

DO - 10.1109/CDC.2009.5400002

M3 - Conference contribution

AN - SCOPUS:77950825455

SN - 9781424438716

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 7849

EP - 7853

BT - Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 48th IEEE Conference on Decision and Control, CDC 2009, held Jointly with the 28th Chinese Control Conference, CCC 2009

Y2 - 15 December 2009 through 18 December 2009

ER -

Khalid M, Savkin AV. Model predictive control for wind power generation smoothing with controlled battery storage. In Proceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009. Institute of Electrical and Electronics Engineers Inc. 2009. p. 7849-7853. 5400002. (Proceedings of the IEEE Conference on Decision and Control). doi: 10.1109/CDC.2009.5400002

Model predictive control for wind power generation smoothing with controlled battery storage

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this