Regional load frequency control of BP-PI wind power generation based on particle swarm optimization
The large-scale integration of wind turbines (WTs) in renewable power generation induces power oscillations, leading to frequency aberration due to power unbalance. Hence, in this paper, a secondary frequency control strategy called load frequency control (LFC) for power systems with wind turbine pa...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/168830 |
| _version_ | 1811695419446525952 |
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| author | Sun, Jikai Chen, Mingrui Kong, Linghe Hu, Zhijian Veerasamy, Veerapandiyan |
| author2 | School of Electrical and Electronic Engineering |
| author_facet | School of Electrical and Electronic Engineering Sun, Jikai Chen, Mingrui Kong, Linghe Hu, Zhijian Veerasamy, Veerapandiyan |
| author_sort | Sun, Jikai |
| collection | NTU |
| description | The large-scale integration of wind turbines (WTs) in renewable power generation induces power oscillations, leading to frequency aberration due to power unbalance. Hence, in this paper, a secondary frequency control strategy called load frequency control (LFC) for power systems with wind turbine participation is proposed. Specifically, a backpropagation (BP)-trained neural network-based PI control approach is adopted to optimize the conventional PI controller to achieve better adaptiveness. The proposed controller was developed to realize the timely adjustment of PI parameters during unforeseen changes in system operation, to ensure the mutual coordination among wind turbine control circuits. In the meantime, the improved particle swarm optimization (IPSO) algorithm is utilized to adjust the initial neuron weights of the neural network, which can effectively improve the convergence of optimization. The simulation results demonstrate that the proposed IPSO-BP-PI controller performed evidently better than the conventional PI controller in the case of random load disturbance, with a significant reduction to near 10 s in regulation time and a final stable error of less than (Formula presented.) for load frequency. Additionally, compared with the conventional PI controller counterpart, the frequency adjustment rate of the IPSO-BP-PI controller is significantly improved. Furthermore, it achieves higher control accuracy and robustness, demonstrating better integration of wind energy into traditional power systems. |
| first_indexed | 2024-10-01T07:23:10Z |
| format | Journal Article |
| id | ntu-10356/168830 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:23:10Z |
| publishDate | 2023 |
| record_format | dspace |
| spelling | ntu-10356/1688302023-06-23T15:40:37Z Regional load frequency control of BP-PI wind power generation based on particle swarm optimization Sun, Jikai Chen, Mingrui Kong, Linghe Hu, Zhijian Veerasamy, Veerapandiyan School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Wind Power Generation Sudden Load Disturbance The large-scale integration of wind turbines (WTs) in renewable power generation induces power oscillations, leading to frequency aberration due to power unbalance. Hence, in this paper, a secondary frequency control strategy called load frequency control (LFC) for power systems with wind turbine participation is proposed. Specifically, a backpropagation (BP)-trained neural network-based PI control approach is adopted to optimize the conventional PI controller to achieve better adaptiveness. The proposed controller was developed to realize the timely adjustment of PI parameters during unforeseen changes in system operation, to ensure the mutual coordination among wind turbine control circuits. In the meantime, the improved particle swarm optimization (IPSO) algorithm is utilized to adjust the initial neuron weights of the neural network, which can effectively improve the convergence of optimization. The simulation results demonstrate that the proposed IPSO-BP-PI controller performed evidently better than the conventional PI controller in the case of random load disturbance, with a significant reduction to near 10 s in regulation time and a final stable error of less than (Formula presented.) for load frequency. Additionally, compared with the conventional PI controller counterpart, the frequency adjustment rate of the IPSO-BP-PI controller is significantly improved. Furthermore, it achieves higher control accuracy and robustness, demonstrating better integration of wind energy into traditional power systems. Published version 2023-06-20T02:09:24Z 2023-06-20T02:09:24Z 2023 Journal Article Sun, J., Chen, M., Kong, L., Hu, Z. & Veerasamy, V. (2023). Regional load frequency control of BP-PI wind power generation based on particle swarm optimization. Energies, 16(4), 2015-. https://dx.doi.org/10.3390/en16042015 1996-1073 https://hdl.handle.net/10356/168830 10.3390/en16042015 2-s2.0-85149181300 4 16 2015 en Energies © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). application/pdf |
| spellingShingle | Engineering::Electrical and electronic engineering Wind Power Generation Sudden Load Disturbance Sun, Jikai Chen, Mingrui Kong, Linghe Hu, Zhijian Veerasamy, Veerapandiyan Regional load frequency control of BP-PI wind power generation based on particle swarm optimization |
| title | Regional load frequency control of BP-PI wind power generation based on particle swarm optimization |
| title_full | Regional load frequency control of BP-PI wind power generation based on particle swarm optimization |
| title_fullStr | Regional load frequency control of BP-PI wind power generation based on particle swarm optimization |
| title_full_unstemmed | Regional load frequency control of BP-PI wind power generation based on particle swarm optimization |
| title_short | Regional load frequency control of BP-PI wind power generation based on particle swarm optimization |
| title_sort | regional load frequency control of bp pi wind power generation based on particle swarm optimization |
| topic | Engineering::Electrical and electronic engineering Wind Power Generation Sudden Load Disturbance |
| url | https://hdl.handle.net/10356/168830 |
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