Analysis of the performance of PID-based new-generation metaheuristic algorithms for automatic voltage regulation system

Stephen Oladipo; Yanxia Sun

doi:10.1145/3638584.3638622

Analysis of the performance of PID-based new-generation metaheuristic algorithms for automatic voltage regulation system

Stephen Oladipo
, Yanxia Sun

Electrical and Electronic Engineering Science

University of Johannesburg

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

1 Citation (Scopus)

Abstract

In recent decades, the expansion of industrial organizations in both scale and scope has necessitated dependable output voltage supplies. However, persistent oscillations in electromechanical devices can impede power efficiency and stability, underscoring the importance of reliable automatic generation regulation (AVR) systems and power system design in the manufacturing sector. To address this issue, this study presents a performance analysis of a proportional integral derivative (PID) controller based on new-generation metaheuristic algorithms (MAs) for the AVR system. Five recent and novel MAs were employed to optimize the PID controller for the AVR system, with the controllers' performances evaluated under five distinct performance metrics. The findings revealed that the Northern Goshawk Optimization (NGO) algorithm was the most effective optimization approach, exhibiting the lowest values of overshoot (33.2784%), peak time (0.2120 s), and objective value (0.0077). These results suggest that the NGO algorithm is a promising optimization method for improving AVR system performance in industrial settings.

Original language	English
Title of host publication	CSAI 2023 - 2023 7th International Conference on Computer Science and Artificial Intelligence
Publisher	Association for Computing Machinery
Pages	449-454
Number of pages	6
ISBN (Electronic)	9798400708688
DOIs	https://doi.org/10.1145/3638584.3638622
Publication status	Published - 8 Dec 2023
Event	7th International Conference on Computer Science and Artificial Intelligence, CSAI 2023 - Beijing, China Duration: 8 Dec 2023 → 10 Dec 2023

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	7th International Conference on Computer Science and Artificial Intelligence, CSAI 2023
Country/Territory	China
City	Beijing
Period	8/12/23 → 10/12/23

UN SDGs

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

SDG 8 Decent Work and Economic Growth
SDG 9 Industry, Innovation, and Infrastructure

Keywords

Automatic voltage regulation system
algorithm
metaheuristic
northern goshawk optimization
proportional integral derivative

ASJC Scopus subject areas

Human-Computer Interaction
Computer Networks and Communications
Computer Vision and Pattern Recognition
Software

Access to Document

10.1145/3638584.3638622

Cite this

Oladipo, S., & Sun, Y. (2023). Analysis of the performance of PID-based new-generation metaheuristic algorithms for automatic voltage regulation system. In CSAI 2023 - 2023 7th International Conference on Computer Science and Artificial Intelligence (pp. 449-454). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3638584.3638622

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title = "Analysis of the performance of PID-based new-generation metaheuristic algorithms for automatic voltage regulation system",

abstract = "In recent decades, the expansion of industrial organizations in both scale and scope has necessitated dependable output voltage supplies. However, persistent oscillations in electromechanical devices can impede power efficiency and stability, underscoring the importance of reliable automatic generation regulation (AVR) systems and power system design in the manufacturing sector. To address this issue, this study presents a performance analysis of a proportional integral derivative (PID) controller based on new-generation metaheuristic algorithms (MAs) for the AVR system. Five recent and novel MAs were employed to optimize the PID controller for the AVR system, with the controllers' performances evaluated under five distinct performance metrics. The findings revealed that the Northern Goshawk Optimization (NGO) algorithm was the most effective optimization approach, exhibiting the lowest values of overshoot (33.2784\%), peak time (0.2120 s), and objective value (0.0077). These results suggest that the NGO algorithm is a promising optimization method for improving AVR system performance in industrial settings.",

keywords = "Automatic voltage regulation system, algorithm, metaheuristic, northern goshawk optimization, proportional integral derivative",

author = "Stephen Oladipo and Yanxia Sun",

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Oladipo, S & Sun, Y 2023, Analysis of the performance of PID-based new-generation metaheuristic algorithms for automatic voltage regulation system. in CSAI 2023 - 2023 7th International Conference on Computer Science and Artificial Intelligence. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 449-454, 7th International Conference on Computer Science and Artificial Intelligence, CSAI 2023, Beijing, China, 8/12/23. https://doi.org/10.1145/3638584.3638622

Analysis of the performance of PID-based new-generation metaheuristic algorithms for automatic voltage regulation system. / Oladipo, Stephen; Sun, Yanxia.
CSAI 2023 - 2023 7th International Conference on Computer Science and Artificial Intelligence. Association for Computing Machinery, 2023. p. 449-454 (ACM International Conference Proceeding Series).

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

TY - GEN

T1 - Analysis of the performance of PID-based new-generation metaheuristic algorithms for automatic voltage regulation system

AU - Oladipo, Stephen

AU - Sun, Yanxia

PY - 2023/12/8

Y1 - 2023/12/8

N2 - In recent decades, the expansion of industrial organizations in both scale and scope has necessitated dependable output voltage supplies. However, persistent oscillations in electromechanical devices can impede power efficiency and stability, underscoring the importance of reliable automatic generation regulation (AVR) systems and power system design in the manufacturing sector. To address this issue, this study presents a performance analysis of a proportional integral derivative (PID) controller based on new-generation metaheuristic algorithms (MAs) for the AVR system. Five recent and novel MAs were employed to optimize the PID controller for the AVR system, with the controllers' performances evaluated under five distinct performance metrics. The findings revealed that the Northern Goshawk Optimization (NGO) algorithm was the most effective optimization approach, exhibiting the lowest values of overshoot (33.2784%), peak time (0.2120 s), and objective value (0.0077). These results suggest that the NGO algorithm is a promising optimization method for improving AVR system performance in industrial settings.

AB - In recent decades, the expansion of industrial organizations in both scale and scope has necessitated dependable output voltage supplies. However, persistent oscillations in electromechanical devices can impede power efficiency and stability, underscoring the importance of reliable automatic generation regulation (AVR) systems and power system design in the manufacturing sector. To address this issue, this study presents a performance analysis of a proportional integral derivative (PID) controller based on new-generation metaheuristic algorithms (MAs) for the AVR system. Five recent and novel MAs were employed to optimize the PID controller for the AVR system, with the controllers' performances evaluated under five distinct performance metrics. The findings revealed that the Northern Goshawk Optimization (NGO) algorithm was the most effective optimization approach, exhibiting the lowest values of overshoot (33.2784%), peak time (0.2120 s), and objective value (0.0077). These results suggest that the NGO algorithm is a promising optimization method for improving AVR system performance in industrial settings.

KW - Automatic voltage regulation system

KW - algorithm

KW - metaheuristic

KW - northern goshawk optimization

KW - proportional integral derivative

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U2 - 10.1145/3638584.3638622

DO - 10.1145/3638584.3638622

M3 - Conference contribution

AN - SCOPUS:85188289116

T3 - ACM International Conference Proceeding Series

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ER -

Oladipo S, Sun Y. Analysis of the performance of PID-based new-generation metaheuristic algorithms for automatic voltage regulation system. In CSAI 2023 - 2023 7th International Conference on Computer Science and Artificial Intelligence. Association for Computing Machinery. 2023. p. 449-454. (ACM International Conference Proceeding Series). doi: 10.1145/3638584.3638622

Analysis of the performance of PID-based new-generation metaheuristic algorithms for automatic voltage regulation system

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

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