Fuzzy Mamdani-based Model Predictive Load Frequency Control

Mohammad Saeid Akbari; Ali Akbar Safavi; Navid Vafamand; Tomislav Dragicevic; Jose Rodriguez

doi:10.1109/PEDG48541.2020.9244311

Fuzzy Mamdani-based Model Predictive Load Frequency Control

Mohammad Saeid Akbari, Ali Akbar Safavi, Navid Vafamand, Tomislav Dragicevic, Jose Rodriguez

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

Abstract

In this paper, an adaptive artificial fuzzy Mamdani-based model predictive approach for load frequency regulation of an isolated microgrid (IMG) is presented. A generalized state-space representation of an IMG comprising power sources is derived and exploited to predict the future behavior and control inputs for the IMG in order to regulate the frequency. The considered adaptive MPC is on the basis of a conventional model predictive approach that is equipped by a fuzzy logic tuning mechanism. A rule-based fuzzy logic is considered to tune the weight of the cost function in the model predictive controller (MPC), which highly impacts the minimization of the frequency deviation in the system. To show the advantages of the fuzzy adaptive MPC, it is compared with a conventional MPC in which the weights of the cost function is chosen by trial and error and fixed during the simulation. OPAL Real-time (RT) results show that the closed-loop system response performance based on the suggested fuzzy MPC is enhanced for different scenarios of the IMG load frequency system.

Original language	English
Title of host publication	Proceedings of 2020 IEEE 11^th International Symposium on Power Electronics for Distributed Generation Systems
Publisher	IEEE
Publication date	2020
Pages	7-12
ISBN (Print)	9781728169897
DOIs	https://doi.org/10.1109/PEDG48541.2020.9244311
Publication status	Published - 2020
Event	IEEE 11^th International Symposium on Power Electronics for Distributed Generation Systems - Virtual event, Dubrovnik, Croatia Duration: 28 Sep 2020 → 1 Oct 2020

Conference

Conference	IEEE 11^th International Symposium on Power Electronics for Distributed Generation Systems
Location	Virtual event
Country	Croatia
City	Dubrovnik
Period	28/09/2020 → 01/10/2020

Series	2020 Ieee 11th International Symposium on Power Electronics for Distributed Generation Systems (pedg)
ISSN	2329-5767

Keywords

Load frequency control (LFC)
Model predictive control (MPC)
Fuzzy logic
Online cost function tuning
Isolated microgrid

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Akbari, M. S., Safavi, A. A., Vafamand, N., Dragicevic, T., & Rodriguez, J. (2020). Fuzzy Mamdani-based Model Predictive Load Frequency Control. In Proceedings of 2020 IEEE 11^th International Symposium on Power Electronics for Distributed Generation Systems (pp. 7-12). IEEE. 2020 Ieee 11th International Symposium on Power Electronics for Distributed Generation Systems (pedg) https://doi.org/10.1109/PEDG48541.2020.9244311

Akbari, Mohammad Saeid ; Safavi, Ali Akbar ; Vafamand, Navid ; Dragicevic, Tomislav ; Rodriguez, Jose. / Fuzzy Mamdani-based Model Predictive Load Frequency Control. Proceedings of 2020 IEEE 11^th International Symposium on Power Electronics for Distributed Generation Systems. IEEE, 2020. pp. 7-12 (2020 Ieee 11th International Symposium on Power Electronics for Distributed Generation Systems (pedg)).

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title = "Fuzzy Mamdani-based Model Predictive Load Frequency Control",

abstract = "In this paper, an adaptive artificial fuzzy Mamdani-based model predictive approach for load frequency regulation of an isolated microgrid (IMG) is presented. A generalized state-space representation of an IMG comprising power sources is derived and exploited to predict the future behavior and control inputs for the IMG in order to regulate the frequency. The considered adaptive MPC is on the basis of a conventional model predictive approach that is equipped by a fuzzy logic tuning mechanism. A rule-based fuzzy logic is considered to tune the weight of the cost function in the model predictive controller (MPC), which highly impacts the minimization of the frequency deviation in the system. To show the advantages of the fuzzy adaptive MPC, it is compared with a conventional MPC in which the weights of the cost function is chosen by trial and error and fixed during the simulation. OPAL Real-time (RT) results show that the closed-loop system response performance based on the suggested fuzzy MPC is enhanced for different scenarios of the IMG load frequency system.",

keywords = "Load frequency control (LFC), Model predictive control (MPC), Fuzzy logic, Online cost function tuning, Isolated microgrid",

author = "Akbari, {Mohammad Saeid} and Safavi, {Ali Akbar} and Navid Vafamand and Tomislav Dragicevic and Jose Rodriguez",

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Akbari, MS, Safavi, AA, Vafamand, N, Dragicevic, T & Rodriguez, J 2020, Fuzzy Mamdani-based Model Predictive Load Frequency Control. in Proceedings of 2020 IEEE 11^th International Symposium on Power Electronics for Distributed Generation Systems. IEEE, 2020 Ieee 11th International Symposium on Power Electronics for Distributed Generation Systems (pedg), pp. 7-12, IEEE 11^th International Symposium on Power Electronics for Distributed Generation Systems , Dubrovnik, Croatia, 28/09/2020. https://doi.org/10.1109/PEDG48541.2020.9244311

Fuzzy Mamdani-based Model Predictive Load Frequency Control. / Akbari, Mohammad Saeid; Safavi, Ali Akbar; Vafamand, Navid; Dragicevic, Tomislav; Rodriguez, Jose.

Proceedings of 2020 IEEE 11^th International Symposium on Power Electronics for Distributed Generation Systems. IEEE, 2020. p. 7-12 (2020 Ieee 11th International Symposium on Power Electronics for Distributed Generation Systems (pedg)).

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

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T1 - Fuzzy Mamdani-based Model Predictive Load Frequency Control

AU - Akbari, Mohammad Saeid

AU - Safavi, Ali Akbar

AU - Vafamand, Navid

AU - Dragicevic, Tomislav

AU - Rodriguez, Jose

PY - 2020

Y1 - 2020

N2 - In this paper, an adaptive artificial fuzzy Mamdani-based model predictive approach for load frequency regulation of an isolated microgrid (IMG) is presented. A generalized state-space representation of an IMG comprising power sources is derived and exploited to predict the future behavior and control inputs for the IMG in order to regulate the frequency. The considered adaptive MPC is on the basis of a conventional model predictive approach that is equipped by a fuzzy logic tuning mechanism. A rule-based fuzzy logic is considered to tune the weight of the cost function in the model predictive controller (MPC), which highly impacts the minimization of the frequency deviation in the system. To show the advantages of the fuzzy adaptive MPC, it is compared with a conventional MPC in which the weights of the cost function is chosen by trial and error and fixed during the simulation. OPAL Real-time (RT) results show that the closed-loop system response performance based on the suggested fuzzy MPC is enhanced for different scenarios of the IMG load frequency system.

AB - In this paper, an adaptive artificial fuzzy Mamdani-based model predictive approach for load frequency regulation of an isolated microgrid (IMG) is presented. A generalized state-space representation of an IMG comprising power sources is derived and exploited to predict the future behavior and control inputs for the IMG in order to regulate the frequency. The considered adaptive MPC is on the basis of a conventional model predictive approach that is equipped by a fuzzy logic tuning mechanism. A rule-based fuzzy logic is considered to tune the weight of the cost function in the model predictive controller (MPC), which highly impacts the minimization of the frequency deviation in the system. To show the advantages of the fuzzy adaptive MPC, it is compared with a conventional MPC in which the weights of the cost function is chosen by trial and error and fixed during the simulation. OPAL Real-time (RT) results show that the closed-loop system response performance based on the suggested fuzzy MPC is enhanced for different scenarios of the IMG load frequency system.

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KW - Model predictive control (MPC)

KW - Fuzzy logic

KW - Online cost function tuning

KW - Isolated microgrid

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DO - 10.1109/PEDG48541.2020.9244311

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T3 - 2020 Ieee 11th International Symposium on Power Electronics for Distributed Generation Systems (pedg)

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BT - Proceedings of 2020 IEEE 11th International Symposium on Power Electronics for Distributed Generation Systems

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T2 - IEEE 11<sup>th</sup> International Symposium on Power Electronics for Distributed Generation Systems

Y2 - 28 September 2020 through 1 October 2020

ER -

Akbari MS, Safavi AA, Vafamand N, Dragicevic T, Rodriguez J. Fuzzy Mamdani-based Model Predictive Load Frequency Control. In Proceedings of 2020 IEEE 11^th International Symposium on Power Electronics for Distributed Generation Systems. IEEE. 2020. p. 7-12. (2020 Ieee 11th International Symposium on Power Electronics for Distributed Generation Systems (pedg)). https://doi.org/10.1109/PEDG48541.2020.9244311