Load Frequency Control Using Golden Eagle Optimization for Multi-Area Power System Connected Through AC/HVDC Transmission and Supported With Hybrid Energy Storage Devices
The reliability of a power system depends on its ability to handle fluctuations and varying load demands, as uncontrolled frequency deviations can lead to load-shedding and blackouts. Optimally tuned controllers are essential for Load Frequency Control (LFC) applications to efficiently stabilize the...
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10114914/ |
| _version_ | 1797829110500687872 |
|---|---|
| author | Irfan Ahmed Khan Hazlie Mokhlis Nurulafiqah Nadzirah Mansor Hazlee Azil Illias Muhammad Usama Amil Daraz Li Wang Lilik Jamilatul Awalin |
| author_facet | Irfan Ahmed Khan Hazlie Mokhlis Nurulafiqah Nadzirah Mansor Hazlee Azil Illias Muhammad Usama Amil Daraz Li Wang Lilik Jamilatul Awalin |
| author_sort | Irfan Ahmed Khan |
| collection | DOAJ |
| description | The reliability of a power system depends on its ability to handle fluctuations and varying load demands, as uncontrolled frequency deviations can lead to load-shedding and blackouts. Optimally tuned controllers are essential for Load Frequency Control (LFC) applications to efficiently stabilize the power system by minimizing frequency undershoots, overshoots, and settling time. This paper proposed the application of novel Golden Eagle Optimization (GEO) algorithm for the optimal tuning of the LFC controller, which has not been previously employed in any LFC applications. Moreover, this paper presents the first-ever implementation of a hybrid energy storage system consisting of Vanadium Redox Flow Battery (VRFB) and Super Magnetic Energy Storage System (SMES) coupled with AC/HVDC transmission lines in a multi-area power system. A GEO optimized Proportional-Integrative-Derivative (GEO-PID) robust controller is designed with the Integral Time Absolute Error (ITAE) objective function to enhance the power system’s stability. The proposed controller is tested on two and four areas power systems considering the sensitivity and nonlinearity of the power systems. A robustness test is also performed to verify the stability of the system under randomly chosen loading conditions. In comparison with particle swarm optimization, dragonfly algorithm, sine cosine algorithm, ant lion optimization, and whale optimization algorithm, the GEO-PID controller significantly reduced the settling time up to 80% for different area’s frequencies. Simulation results indicate that the proposed controller outperforms other recent optimization algorithms by effectively dampening the frequency and tie-line deviations with less settling times, as well as reduced frequency undershoots and overshoots. |
| first_indexed | 2024-04-09T13:15:11Z |
| format | Article |
| id | doaj.art-007384f4e88840c3970d1cbd866d8434 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-09T13:15:11Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-007384f4e88840c3970d1cbd866d84342023-05-11T23:00:45ZengIEEEIEEE Access2169-35362023-01-0111446724469510.1109/ACCESS.2023.327283610114914Load Frequency Control Using Golden Eagle Optimization for Multi-Area Power System Connected Through AC/HVDC Transmission and Supported With Hybrid Energy Storage DevicesIrfan Ahmed Khan0https://orcid.org/0000-0002-1872-2197Hazlie Mokhlis1https://orcid.org/0000-0002-1166-1934Nurulafiqah Nadzirah Mansor2https://orcid.org/0000-0003-2148-5775Hazlee Azil Illias3https://orcid.org/0000-0002-5061-1809Muhammad Usama4Amil Daraz5https://orcid.org/0000-0002-5532-9175Li Wang6https://orcid.org/0000-0001-5292-3737Lilik Jamilatul Awalin7Department of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur, MalaysiaDepartment of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur, MalaysiaDepartment of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur, MalaysiaDepartment of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur, MalaysiaDepartment of Electrical Engineering, Faculty of Engineering, Universiti Malaya, Kuala Lumpur, MalaysiaA Constituent College of University of Engineering and Technology, Lahore, PakistanA Constituent College of University of Engineering and Technology, Lahore, PakistanFaculty of Advanced Technology and Multidiscipline, Universitas Airlangga, Gedung Kuliah Bersama UNAIR Kampus C, Surabaya, IndonesiaThe reliability of a power system depends on its ability to handle fluctuations and varying load demands, as uncontrolled frequency deviations can lead to load-shedding and blackouts. Optimally tuned controllers are essential for Load Frequency Control (LFC) applications to efficiently stabilize the power system by minimizing frequency undershoots, overshoots, and settling time. This paper proposed the application of novel Golden Eagle Optimization (GEO) algorithm for the optimal tuning of the LFC controller, which has not been previously employed in any LFC applications. Moreover, this paper presents the first-ever implementation of a hybrid energy storage system consisting of Vanadium Redox Flow Battery (VRFB) and Super Magnetic Energy Storage System (SMES) coupled with AC/HVDC transmission lines in a multi-area power system. A GEO optimized Proportional-Integrative-Derivative (GEO-PID) robust controller is designed with the Integral Time Absolute Error (ITAE) objective function to enhance the power system’s stability. The proposed controller is tested on two and four areas power systems considering the sensitivity and nonlinearity of the power systems. A robustness test is also performed to verify the stability of the system under randomly chosen loading conditions. In comparison with particle swarm optimization, dragonfly algorithm, sine cosine algorithm, ant lion optimization, and whale optimization algorithm, the GEO-PID controller significantly reduced the settling time up to 80% for different area’s frequencies. Simulation results indicate that the proposed controller outperforms other recent optimization algorithms by effectively dampening the frequency and tie-line deviations with less settling times, as well as reduced frequency undershoots and overshoots.https://ieeexplore.ieee.org/document/10114914/Energy storage systemgolden eagle optimizationload frequency controlsuper magnetic energy storage system (SMES)vanadium redox flow battery |
| spellingShingle | Irfan Ahmed Khan Hazlie Mokhlis Nurulafiqah Nadzirah Mansor Hazlee Azil Illias Muhammad Usama Amil Daraz Li Wang Lilik Jamilatul Awalin Load Frequency Control Using Golden Eagle Optimization for Multi-Area Power System Connected Through AC/HVDC Transmission and Supported With Hybrid Energy Storage Devices IEEE Access Energy storage system golden eagle optimization load frequency control super magnetic energy storage system (SMES) vanadium redox flow battery |
| title | Load Frequency Control Using Golden Eagle Optimization for Multi-Area Power System Connected Through AC/HVDC Transmission and Supported With Hybrid Energy Storage Devices |
| title_full | Load Frequency Control Using Golden Eagle Optimization for Multi-Area Power System Connected Through AC/HVDC Transmission and Supported With Hybrid Energy Storage Devices |
| title_fullStr | Load Frequency Control Using Golden Eagle Optimization for Multi-Area Power System Connected Through AC/HVDC Transmission and Supported With Hybrid Energy Storage Devices |
| title_full_unstemmed | Load Frequency Control Using Golden Eagle Optimization for Multi-Area Power System Connected Through AC/HVDC Transmission and Supported With Hybrid Energy Storage Devices |
| title_short | Load Frequency Control Using Golden Eagle Optimization for Multi-Area Power System Connected Through AC/HVDC Transmission and Supported With Hybrid Energy Storage Devices |
| title_sort | load frequency control using golden eagle optimization for multi area power system connected through ac hvdc transmission and supported with hybrid energy storage devices |
| topic | Energy storage system golden eagle optimization load frequency control super magnetic energy storage system (SMES) vanadium redox flow battery |
| url | https://ieeexplore.ieee.org/document/10114914/ |
| work_keys_str_mv | AT irfanahmedkhan loadfrequencycontrolusinggoldeneagleoptimizationformultiareapowersystemconnectedthroughachvdctransmissionandsupportedwithhybridenergystoragedevices AT hazliemokhlis loadfrequencycontrolusinggoldeneagleoptimizationformultiareapowersystemconnectedthroughachvdctransmissionandsupportedwithhybridenergystoragedevices AT nurulafiqahnadzirahmansor loadfrequencycontrolusinggoldeneagleoptimizationformultiareapowersystemconnectedthroughachvdctransmissionandsupportedwithhybridenergystoragedevices AT hazleeazilillias loadfrequencycontrolusinggoldeneagleoptimizationformultiareapowersystemconnectedthroughachvdctransmissionandsupportedwithhybridenergystoragedevices AT muhammadusama loadfrequencycontrolusinggoldeneagleoptimizationformultiareapowersystemconnectedthroughachvdctransmissionandsupportedwithhybridenergystoragedevices AT amildaraz loadfrequencycontrolusinggoldeneagleoptimizationformultiareapowersystemconnectedthroughachvdctransmissionandsupportedwithhybridenergystoragedevices AT liwang loadfrequencycontrolusinggoldeneagleoptimizationformultiareapowersystemconnectedthroughachvdctransmissionandsupportedwithhybridenergystoragedevices AT lilikjamilatulawalin loadfrequencycontrolusinggoldeneagleoptimizationformultiareapowersystemconnectedthroughachvdctransmissionandsupportedwithhybridenergystoragedevices |