Learning-based flexible load aggregation for secondary frequency regulation in co-simulated transmission and distribution networks
Aggregated flexible loads offer a promising solution for secondary frequency regulation (SFR) in power systems with increasing intermittent renewable energy sources. However, uncertainties in users’ behaviors may create a mismatch between the aggregated power of flexible loads and the control target...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | International Journal of Electrical Power & Energy Systems |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061524005623 |
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| _version_ | 1846162804483031040 |
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| author | Mengtong Chen Qinran Hu Tao Qian Xinyi Chen Rushuai Han Yongxu Zhu |
| author_facet | Mengtong Chen Qinran Hu Tao Qian Xinyi Chen Rushuai Han Yongxu Zhu |
| author_sort | Mengtong Chen |
| collection | DOAJ |
| description | Aggregated flexible loads offer a promising solution for secondary frequency regulation (SFR) in power systems with increasing intermittent renewable energy sources. However, uncertainties in users’ behaviors may create a mismatch between the aggregated power of flexible loads and the control target of SFR. Furthermore, as these loads are dispersed across distribution networks, distribution network’s topology and its interplay with the transmission network may affect the performance of aggregated flexible loads in SFR. Therefore, this paper proposes an adaptive combinatorial multi-armed bandit (CMAB) flexible load aggregation strategy to enhance SFR performance in co-simulated transmission and distribution (T&D) networks. First, a dynamic T&D co-simulation framework is proposed based on the HELICS platform. Then, the combinatorial upper confidence bound-average (CUCB-Avg)-based CMAB algorithm is employed to manage users’ uncertain responses. Case studies on the IEEE 14-bus system with five IEEE 8,500-node feeders demonstrate the effectiveness of the proposed framework and method. The SFR performance of the proposed strategy based on CUCB-Avg algorithm outperforms the average and CUCB strategies in terms of accuracy, rapidity, robustness, and the number of affected users. |
| format | Article |
| id | doaj-art-fa0365bdcb7b46578cfe4c22accfd757 |
| institution | Kabale University |
| issn | 0142-0615 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Electrical Power & Energy Systems |
| spelling | doaj-art-fa0365bdcb7b46578cfe4c22accfd7572024-11-20T05:06:13ZengElsevierInternational Journal of Electrical Power & Energy Systems0142-06152024-12-01163110339Learning-based flexible load aggregation for secondary frequency regulation in co-simulated transmission and distribution networksMengtong Chen0Qinran Hu1Tao Qian2Xinyi Chen3Rushuai Han4Yongxu Zhu5School of Electrical Engineering, Southeast University, Nanjing 210000, ChinaSchool of Electrical Engineering, Southeast University, Nanjing 210000, China; Jiangsu Key Laboratory of Smart Grid Technology and Equipment, ChinaSchool of Electrical Engineering, Southeast University, Nanjing 210000, China; Corresponding author.School of Electrical Engineering, Southeast University, Nanjing 210000, ChinaSchool of Electrical Engineering, Southeast University, Nanjing 210000, ChinaSchool of Information Science and Engineering, Southeast University, Nanjing 210000, ChinaAggregated flexible loads offer a promising solution for secondary frequency regulation (SFR) in power systems with increasing intermittent renewable energy sources. However, uncertainties in users’ behaviors may create a mismatch between the aggregated power of flexible loads and the control target of SFR. Furthermore, as these loads are dispersed across distribution networks, distribution network’s topology and its interplay with the transmission network may affect the performance of aggregated flexible loads in SFR. Therefore, this paper proposes an adaptive combinatorial multi-armed bandit (CMAB) flexible load aggregation strategy to enhance SFR performance in co-simulated transmission and distribution (T&D) networks. First, a dynamic T&D co-simulation framework is proposed based on the HELICS platform. Then, the combinatorial upper confidence bound-average (CUCB-Avg)-based CMAB algorithm is employed to manage users’ uncertain responses. Case studies on the IEEE 14-bus system with five IEEE 8,500-node feeders demonstrate the effectiveness of the proposed framework and method. The SFR performance of the proposed strategy based on CUCB-Avg algorithm outperforms the average and CUCB strategies in terms of accuracy, rapidity, robustness, and the number of affected users.http://www.sciencedirect.com/science/article/pii/S0142061524005623Combinatorial multi-armed banditFlexible load online aggregated controlSecondary frequency regulationTransmission and distribution dynamic co-simulation |
| spellingShingle | Mengtong Chen Qinran Hu Tao Qian Xinyi Chen Rushuai Han Yongxu Zhu Learning-based flexible load aggregation for secondary frequency regulation in co-simulated transmission and distribution networks International Journal of Electrical Power & Energy Systems Combinatorial multi-armed bandit Flexible load online aggregated control Secondary frequency regulation Transmission and distribution dynamic co-simulation |
| title | Learning-based flexible load aggregation for secondary frequency regulation in co-simulated transmission and distribution networks |
| title_full | Learning-based flexible load aggregation for secondary frequency regulation in co-simulated transmission and distribution networks |
| title_fullStr | Learning-based flexible load aggregation for secondary frequency regulation in co-simulated transmission and distribution networks |
| title_full_unstemmed | Learning-based flexible load aggregation for secondary frequency regulation in co-simulated transmission and distribution networks |
| title_short | Learning-based flexible load aggregation for secondary frequency regulation in co-simulated transmission and distribution networks |
| title_sort | learning based flexible load aggregation for secondary frequency regulation in co simulated transmission and distribution networks |
| topic | Combinatorial multi-armed bandit Flexible load online aggregated control Secondary frequency regulation Transmission and distribution dynamic co-simulation |
| url | http://www.sciencedirect.com/science/article/pii/S0142061524005623 |
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