Voltage-driven autonomous cooperative control of EHLs for load stabilization
Electric heating loads (EHLs) are considered as effective demand-side resources for supply–demand balance. However, the effective control of EHLs becomes challenging due to their large number and extensive distribution. In this context, this paper proposes a voltage-driven autonomous cooperative con...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-04-01
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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/S0142061525000602 |
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| _version_ | 1832087797200060416 |
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| author | Bing Qi Rui Liu Deying Zhang Zhuoqun Wang Qi Qi |
| author_facet | Bing Qi Rui Liu Deying Zhang Zhuoqun Wang Qi Qi |
| author_sort | Bing Qi |
| collection | DOAJ |
| description | Electric heating loads (EHLs) are considered as effective demand-side resources for supply–demand balance. However, the effective control of EHLs becomes challenging due to their large number and extensive distribution. In this context, this paper proposes a voltage-driven autonomous cooperative control method of EHLs for distribution network load stabilization. Firstly, an optimal control model of EHLs is constructed, where the adaptive historical influence factors are introduced to achieve the dynamic trade-off between load rate stability and user comfort. Then, a voltage-driven distributed control model is developed, which utilizes the mapping relation between node voltages and transformer load rate to minimize the high-frequency communication overhead associated with large-scale EHLs dispatch while ensuring the control timeliness. Finally, a Q-decomposition Multi-agent Independent eXtension (QMIX) algorithm is used to learn the mapping relation, and the EHLs real-time optimal control strategies are generated through the utilization of Centralized Training Decentralized Execution (CTDE) framework. Simulation results demonstrate the effectiveness of the proposed control method of EHLs in stabilizing the transformer load rate and guaranteeing the user comfort, where no control instruction is required during the implementation phase. |
| format | Article |
| id | doaj-art-a44e8f397a604275aeadb8056634a552 |
| institution | Kabale University |
| issn | 0142-0615 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Electrical Power & Energy Systems |
| spelling | doaj-art-a44e8f397a604275aeadb8056634a5522025-02-06T05:10:56ZengElsevierInternational Journal of Electrical Power & Energy Systems0142-06152025-04-01165110509Voltage-driven autonomous cooperative control of EHLs for load stabilizationBing Qi0Rui Liu1Deying Zhang2Zhuoqun Wang3Qi Qi4School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, ChinaSchool of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, ChinaSchool of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, ChinaSchool of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, ChinaCorresponding author.; School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, ChinaElectric heating loads (EHLs) are considered as effective demand-side resources for supply–demand balance. However, the effective control of EHLs becomes challenging due to their large number and extensive distribution. In this context, this paper proposes a voltage-driven autonomous cooperative control method of EHLs for distribution network load stabilization. Firstly, an optimal control model of EHLs is constructed, where the adaptive historical influence factors are introduced to achieve the dynamic trade-off between load rate stability and user comfort. Then, a voltage-driven distributed control model is developed, which utilizes the mapping relation between node voltages and transformer load rate to minimize the high-frequency communication overhead associated with large-scale EHLs dispatch while ensuring the control timeliness. Finally, a Q-decomposition Multi-agent Independent eXtension (QMIX) algorithm is used to learn the mapping relation, and the EHLs real-time optimal control strategies are generated through the utilization of Centralized Training Decentralized Execution (CTDE) framework. Simulation results demonstrate the effectiveness of the proposed control method of EHLs in stabilizing the transformer load rate and guaranteeing the user comfort, where no control instruction is required during the implementation phase.http://www.sciencedirect.com/science/article/pii/S0142061525000602Electric heating loadLoad stabilizationUser comfortAutonomous cooperative controlMulti-agent deep reinforcement learning |
| spellingShingle | Bing Qi Rui Liu Deying Zhang Zhuoqun Wang Qi Qi Voltage-driven autonomous cooperative control of EHLs for load stabilization International Journal of Electrical Power & Energy Systems Electric heating load Load stabilization User comfort Autonomous cooperative control Multi-agent deep reinforcement learning |
| title | Voltage-driven autonomous cooperative control of EHLs for load stabilization |
| title_full | Voltage-driven autonomous cooperative control of EHLs for load stabilization |
| title_fullStr | Voltage-driven autonomous cooperative control of EHLs for load stabilization |
| title_full_unstemmed | Voltage-driven autonomous cooperative control of EHLs for load stabilization |
| title_short | Voltage-driven autonomous cooperative control of EHLs for load stabilization |
| title_sort | voltage driven autonomous cooperative control of ehls for load stabilization |
| topic | Electric heating load Load stabilization User comfort Autonomous cooperative control Multi-agent deep reinforcement learning |
| url | http://www.sciencedirect.com/science/article/pii/S0142061525000602 |
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