Data-Driven Control and Its Applications to Microgrids

Alireza Karimi; Behrooz Bahrani; Dongdong Zheng; Seyed Sohail Madani

doi:10.1109/CCTA49430.2022.9966006

Data-Driven Control and Its Applications to Microgrids

Alireza Karimi
, Behrooz Bahrani
, Dongdong Zheng
, Seyed Sohail Madani

School of Automation

Swiss Federal Institute of Technology Lausanne
Monash University

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

2 Citations (Scopus)

Abstract

Renewable energy resources have an increasing share of the electrical power, and the concept of distributed generation and storage units is about to completely change the basic architecture and control algorithms of the electric power grids. In this tutorial paper, first a survey on data-driven control algorithms is presented. Then, an overview of different control problems related to the integration of the distributed energy resources into the electrical grid is given. Finally, a time-domain data-driven solution based on the neural networks and a frequency-domain solution using convex optimization techniques are presented for some challenging control problems in microgrids. The solutions are validated by simulation and hardware-in-the-loop (HIL) experiments.

Original language	English
Title of host publication	2022 IEEE Conference on Control Technology and Applications, CCTA 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665473385
DOIs	https://doi.org/10.1109/CCTA49430.2022.9966006
Publication status	Published - 2022
Event	2022 IEEE Conference on Control Technology and Applications, CCTA 2022 - Trieste, Italy Duration: 23 Aug 2022 → 25 Aug 2022

Publication series

Name	2022 IEEE Conference on Control Technology and Applications, CCTA 2022

Conference

Conference	2022 IEEE Conference on Control Technology and Applications, CCTA 2022
Country/Territory	Italy
City	Trieste
Period	23/08/22 → 25/08/22

UN SDGs

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

SDG 7 Affordable and Clean Energy

Access to Document

10.1109/CCTA49430.2022.9966006

Cite this

@inproceedings{5242a91e7c2644da9d20c891cd5f795f,

title = "Data-Driven Control and Its Applications to Microgrids",

abstract = "Renewable energy resources have an increasing share of the electrical power, and the concept of distributed generation and storage units is about to completely change the basic architecture and control algorithms of the electric power grids. In this tutorial paper, first a survey on data-driven control algorithms is presented. Then, an overview of different control problems related to the integration of the distributed energy resources into the electrical grid is given. Finally, a time-domain data-driven solution based on the neural networks and a frequency-domain solution using convex optimization techniques are presented for some challenging control problems in microgrids. The solutions are validated by simulation and hardware-in-the-loop (HIL) experiments.",

author = "Alireza Karimi and Behrooz Bahrani and Dongdong Zheng and Madani, \{Seyed Sohail\}",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE Conference on Control Technology and Applications, CCTA 2022 ; Conference date: 23-08-2022 Through 25-08-2022",

year = "2022",

doi = "10.1109/CCTA49430.2022.9966006",

language = "English",

series = "2022 IEEE Conference on Control Technology and Applications, CCTA 2022",

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

booktitle = "2022 IEEE Conference on Control Technology and Applications, CCTA 2022",

address = "United States",

}

Karimi, A, Bahrani, B, Zheng, D & Madani, SS 2022, Data-Driven Control and Its Applications to Microgrids. in 2022 IEEE Conference on Control Technology and Applications, CCTA 2022. 2022 IEEE Conference on Control Technology and Applications, CCTA 2022, Institute of Electrical and Electronics Engineers Inc., 2022 IEEE Conference on Control Technology and Applications, CCTA 2022, Trieste, Italy, 23/08/22. https://doi.org/10.1109/CCTA49430.2022.9966006

Data-Driven Control and Its Applications to Microgrids. / Karimi, Alireza; Bahrani, Behrooz; Zheng, Dongdong et al.
2022 IEEE Conference on Control Technology and Applications, CCTA 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (2022 IEEE Conference on Control Technology and Applications, CCTA 2022).

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

TY - GEN

T1 - Data-Driven Control and Its Applications to Microgrids

AU - Karimi, Alireza

AU - Bahrani, Behrooz

AU - Zheng, Dongdong

AU - Madani, Seyed Sohail

PY - 2022

Y1 - 2022

N2 - Renewable energy resources have an increasing share of the electrical power, and the concept of distributed generation and storage units is about to completely change the basic architecture and control algorithms of the electric power grids. In this tutorial paper, first a survey on data-driven control algorithms is presented. Then, an overview of different control problems related to the integration of the distributed energy resources into the electrical grid is given. Finally, a time-domain data-driven solution based on the neural networks and a frequency-domain solution using convex optimization techniques are presented for some challenging control problems in microgrids. The solutions are validated by simulation and hardware-in-the-loop (HIL) experiments.

AB - Renewable energy resources have an increasing share of the electrical power, and the concept of distributed generation and storage units is about to completely change the basic architecture and control algorithms of the electric power grids. In this tutorial paper, first a survey on data-driven control algorithms is presented. Then, an overview of different control problems related to the integration of the distributed energy resources into the electrical grid is given. Finally, a time-domain data-driven solution based on the neural networks and a frequency-domain solution using convex optimization techniques are presented for some challenging control problems in microgrids. The solutions are validated by simulation and hardware-in-the-loop (HIL) experiments.

UR - https://www.scopus.com/pages/publications/85144598933

U2 - 10.1109/CCTA49430.2022.9966006

DO - 10.1109/CCTA49430.2022.9966006

M3 - Conference contribution

AN - SCOPUS:85144598933

T3 - 2022 IEEE Conference on Control Technology and Applications, CCTA 2022

BT - 2022 IEEE Conference on Control Technology and Applications, CCTA 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 IEEE Conference on Control Technology and Applications, CCTA 2022

Y2 - 23 August 2022 through 25 August 2022

ER -

Data-Driven Control and Its Applications to Microgrids

Abstract

Publication series

Conference

UN SDGs

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