Distributed leader-follower based adaptive consensus control for networked microgrids
Networked microgrids (NMGs) provide a promising solution for accommodating various distributed energy resources (DERs) and enhance its performance. However, the coordinated operation of the system with integration of a large number of DERs is major challenge. Therefore, this article aims to provide...
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| Format: | Article |
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Elsevier Ltd
2024
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| _version_ | 1811137701496225792 |
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| author | Kandasamy, Jeevitha Ramachandran, Rajeswari Veerasamy, Veerapandiyan Irudayaraj, Andrew Xavier Raj |
| author_facet | Kandasamy, Jeevitha Ramachandran, Rajeswari Veerasamy, Veerapandiyan Irudayaraj, Andrew Xavier Raj |
| author_sort | Kandasamy, Jeevitha |
| collection | UPM |
| description | Networked microgrids (NMGs) provide a promising solution for accommodating various distributed energy resources (DERs) and enhance its performance. However, the coordinated operation of the system with integration of a large number of DERs is major challenge. Therefore, this article aims to provide a distributed control strategy (DCS) based on a leader-follower framework for the coordination of multiple DERs in NMGs. A fuzzy optimized Recurrent Hopfield Neural Network (F-HNN) designed self-adaptive fractional order proportional integral derivative (FOPID) controller is proposed for distributed frequency control of NMGs. Initially, a Lyapunov-based objective function is derived for weight updation of the proposed network. The fuzzy approach is used to optimize the output of the HNN based on its gradients. The proposed F-HNN based DCS is implemented in MATLAB/Simulink and validated for frequency regulation of NMGs through hardware-in-the-loop simulation (HIL) using OPAL-RT. The results obtained are compared with the conventional FOPID HNN tuned and other classical controls. The self-adaptiveness of the controller is demonstrated for change in renewable power generation. Furthermore, the resiliency of the controller is tested with communication failures and, plug and play operation of MGs. The results obtained showed that the frequency of the NMG system is well regulated within the band of ±0.2 Hz. Also, the transient and steady state performance reveals that the proposed DCS is more significant than other techniques. |
| first_indexed | 2024-09-25T03:38:29Z |
| format | Article |
| id | upm.eprints-105837 |
| institution | Universiti Putra Malaysia |
| last_indexed | 2024-09-25T03:38:29Z |
| publishDate | 2024 |
| publisher | Elsevier Ltd |
| record_format | dspace |
| spelling | upm.eprints-1058372024-05-08T14:30:45Z http://psasir.upm.edu.my/id/eprint/105837/ Distributed leader-follower based adaptive consensus control for networked microgrids Kandasamy, Jeevitha Ramachandran, Rajeswari Veerasamy, Veerapandiyan Irudayaraj, Andrew Xavier Raj Networked microgrids (NMGs) provide a promising solution for accommodating various distributed energy resources (DERs) and enhance its performance. However, the coordinated operation of the system with integration of a large number of DERs is major challenge. Therefore, this article aims to provide a distributed control strategy (DCS) based on a leader-follower framework for the coordination of multiple DERs in NMGs. A fuzzy optimized Recurrent Hopfield Neural Network (F-HNN) designed self-adaptive fractional order proportional integral derivative (FOPID) controller is proposed for distributed frequency control of NMGs. Initially, a Lyapunov-based objective function is derived for weight updation of the proposed network. The fuzzy approach is used to optimize the output of the HNN based on its gradients. The proposed F-HNN based DCS is implemented in MATLAB/Simulink and validated for frequency regulation of NMGs through hardware-in-the-loop simulation (HIL) using OPAL-RT. The results obtained are compared with the conventional FOPID HNN tuned and other classical controls. The self-adaptiveness of the controller is demonstrated for change in renewable power generation. Furthermore, the resiliency of the controller is tested with communication failures and, plug and play operation of MGs. The results obtained showed that the frequency of the NMG system is well regulated within the band of ±0.2 Hz. Also, the transient and steady state performance reveals that the proposed DCS is more significant than other techniques. Elsevier Ltd 2024-01 Article PeerReviewed Kandasamy, Jeevitha and Ramachandran, Rajeswari and Veerasamy, Veerapandiyan and Irudayaraj, Andrew Xavier Raj (2024) Distributed leader-follower based adaptive consensus control for networked microgrids. Applied Energy, 353 (pt.A). art. no. 122083. pp. 1-22. ISSN 0306-2619; ESSN: 1872-9118 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173313879&doi=10.1016%2fj.apenergy.2023.122083&partnerID=40&md5=4da8dc2f2ef8f606dedc41956e9f2d51 10.1016/j.apenergy.2023.122083 |
| spellingShingle | Kandasamy, Jeevitha Ramachandran, Rajeswari Veerasamy, Veerapandiyan Irudayaraj, Andrew Xavier Raj Distributed leader-follower based adaptive consensus control for networked microgrids |
| title | Distributed leader-follower based adaptive consensus control for networked microgrids |
| title_full | Distributed leader-follower based adaptive consensus control for networked microgrids |
| title_fullStr | Distributed leader-follower based adaptive consensus control for networked microgrids |
| title_full_unstemmed | Distributed leader-follower based adaptive consensus control for networked microgrids |
| title_short | Distributed leader-follower based adaptive consensus control for networked microgrids |
| title_sort | distributed leader follower based adaptive consensus control for networked microgrids |
| work_keys_str_mv | AT kandasamyjeevitha distributedleaderfollowerbasedadaptiveconsensuscontrolfornetworkedmicrogrids AT ramachandranrajeswari distributedleaderfollowerbasedadaptiveconsensuscontrolfornetworkedmicrogrids AT veerasamyveerapandiyan distributedleaderfollowerbasedadaptiveconsensuscontrolfornetworkedmicrogrids AT irudayarajandrewxavierraj distributedleaderfollowerbasedadaptiveconsensuscontrolfornetworkedmicrogrids |