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Energy Research
2025-2025

Hierarchical Coordinated Automatic Generation Control Involving Distributed Energy Resources: An Aggregation Approach
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Yukang Shen; Wenchuan Wu; Qi Wang; Yong Li; +2 Authors
Yukang Shen; Wenchuan Wu; Qi Wang; Yong Li; Sun Li; Wei Teng;
doi: 10.1109/tsg.2024.3493124
doi: 10.1109/tsg.2024.3493124
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IEEE Transactions on Smart Grid
Article . 2025 . Peer-reviewed
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A Distributed Dispatch of Bi-Directional Power and Hydrogen Systems for Enhancing the Renewable Energy Integration in Grid-Connected Microgrids
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Longfei Li; Chenhui Lin; Ye Guo; Wenchuan Wu; +1 Authors
Longfei Li; Chenhui Lin; Ye Guo; Wenchuan Wu; Mohammad Shahidehpour;
doi: 10.1109/tste.2025.3564652
doi: 10.1109/tste.2025.3564652
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IEEE Transactions on Sustainable Energy
Article . 2025 . Peer-reviewed
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RL2: Reinforce Large Language Model to Assist Safe Reinforcement Learning for Energy Management of Active Distribution Networks
descriptionPublicationkeyboard_double_arrow_right Article , Preprint 2025Embargo end date: 01 Jan 2024Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Xu Yang; Chenhui Lin; Haotian Liu; Wenchuan Wu;
doi: 10.1109/tsg.2025.3568226 , 10.48550/arxiv.2412.01303
arXiv: http://arxiv.org/abs/2412.01303 , 2412.01303
doi: 10.1109/tsg.2025.3568226 , 10.48550/arxiv.2412.01303
arXiv: http://arxiv.org/abs/2412.01303 , 2412.01303
As large-scale distributed energy resources are integrated into the active distribution networks (ADNs), effective energy management in ADNs becomes increasingly prominent compared to traditional distribution networks. Although advanced reinforcement learning (RL) methods, which alleviate the burden of complicated modelling and optimization, have greatly improved the efficiency of energy management in ADNs, safety becomes a critical concern for RL applications in real-world problems. Since the design and adjustment of penalty functions, which correspond to operational safety constraints, requires extensive domain knowledge in RL and power system operation, the emerging ADN operators call for a more flexible and customized approach to address the penalty functions so that the operational safety and efficiency can be further enhanced. Empowered with strong comprehension, reasoning, and in-context learning capabilities, large language models (LLMs) provide a promising way to assist safe RL for energy management in ADNs. In this paper, we introduce the LLM to comprehend operational safety requirements in ADNs and generate corresponding penalty functions. In addition, we propose an RL2 mechanism to refine the generated functions iteratively and adaptively through multi-round dialogues, in which the LLM agent adjusts the functions' pattern and parameters based on training and test performance of the downstream RL agent. The proposed method significantly reduces the intervention of the ADN operators. Comprehensive test results demonstrate the effectiveness of the proposed method.
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Article . 2024
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Preprint . 2024
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Article . 2024
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Cooperative Strategies for Frequency Control of Wind Turbines to Mitigate Secondary Frequency Dip: Coefficient Allocation and Exit Techniques
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Zishuo Huang; Wenchuan Wu; Chenhui Lin; Zizhen Guo;
doi: 10.1109/tste.2024.3498006
doi: 10.1109/tste.2024.3498006
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Article . 2025 . Peer-reviewed
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Adaptive Data-Driven Secondary Control for Renewables Dominated Islanded Microgrids and Field Tests
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Siyun Li; Wenchuan Wu; Zizhen Guo; Haotian Liu; +1 Authors
Siyun Li; Wenchuan Wu; Zizhen Guo; Haotian Liu; Yuwei Cheng;
doi: 10.1109/tsg.2025.3574483
doi: 10.1109/tsg.2025.3574483
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Globally Optimal Distributed Operation of Integrated Electric and Heating Systems
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Yuan Du; Yixun Xue; Mohammad Shahidehpour; Wenchuan Wu; +3 Authors
Yuan Du; Yixun Xue; Mohammad Shahidehpour; Wenchuan Wu; Xinyue Chang; Zening Li; Hongbin Sun;
doi: 10.1109/tste.2024.3450608
doi: 10.1109/tste.2024.3450608
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Efficient Solution of Adjustable Affine Chance-Constrained Real-Time Dispatch
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Shuwei Xu; Wenchuan Wu; Chenhui Lin; Qi Wang; +1 Authors
Shuwei Xu; Wenchuan Wu; Chenhui Lin; Qi Wang; Siyuan Wang;
doi: 10.1109/tpwrs.2024.3498455
doi: 10.1109/tpwrs.2024.3498455
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Article . 2025 . Peer-reviewed
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Dual-Stage MPC-Based AGC for Wind Farm Considering Aerodynamic Interactions
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Zishuo Huang; Wenchuan Wu;
doi: 10.1109/tste.2024.3502518
doi: 10.1109/tste.2024.3502518
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Accelerating Optimal Power Flow With Structure-Aware Automatic Differentiation and Code Generation
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Yue Yang; Chenhui Lin; Luo Xu; Xiaodong Yang; +2 Authors
Yue Yang; Chenhui Lin; Luo Xu; Xiaodong Yang; Wenchuan Wu; Bin Wang;
doi: 10.1109/tpwrs.2024.3483489
doi: 10.1109/tpwrs.2024.3483489
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The following results are related to Energy Research. Are you interested to view more results? Visit OpenAIRE - Explore.

9 Research products

download

Hierarchical Coordinated Automatic Generation Control Involving Distributed Energy Resources: An Aggregation Approach
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Yukang Shen; Wenchuan Wu; Qi Wang; Yong Li; +2 Authors
Yukang Shen; Wenchuan Wu; Qi Wang; Yong Li; Sun Li; Wei Teng;
doi: 10.1109/tsg.2024.3493124
doi: 10.1109/tsg.2024.3493124
IEEE Transactions on...arrow_drop_down
IEEE Transactions on Smart Grid
Article . 2025 . Peer-reviewed
License: IEEE Copyright
Data sources: Crossref
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A Distributed Dispatch of Bi-Directional Power and Hydrogen Systems for Enhancing the Renewable Energy Integration in Grid-Connected Microgrids
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Longfei Li; Chenhui Lin; Ye Guo; Wenchuan Wu; +1 Authors
Longfei Li; Chenhui Lin; Ye Guo; Wenchuan Wu; Mohammad Shahidehpour;
doi: 10.1109/tste.2025.3564652
doi: 10.1109/tste.2025.3564652
IEEE Transactions on...arrow_drop_down
IEEE Transactions on Sustainable Energy
Article . 2025 . Peer-reviewed
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RL2: Reinforce Large Language Model to Assist Safe Reinforcement Learning for Energy Management of Active Distribution Networks
descriptionPublicationkeyboard_double_arrow_right Article , Preprint 2025Embargo end date: 01 Jan 2024Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Xu Yang; Chenhui Lin; Haotian Liu; Wenchuan Wu;
doi: 10.1109/tsg.2025.3568226 , 10.48550/arxiv.2412.01303
arXiv: http://arxiv.org/abs/2412.01303 , 2412.01303
doi: 10.1109/tsg.2025.3568226 , 10.48550/arxiv.2412.01303
arXiv: http://arxiv.org/abs/2412.01303 , 2412.01303
As large-scale distributed energy resources are integrated into the active distribution networks (ADNs), effective energy management in ADNs becomes increasingly prominent compared to traditional distribution networks. Although advanced reinforcement learning (RL) methods, which alleviate the burden of complicated modelling and optimization, have greatly improved the efficiency of energy management in ADNs, safety becomes a critical concern for RL applications in real-world problems. Since the design and adjustment of penalty functions, which correspond to operational safety constraints, requires extensive domain knowledge in RL and power system operation, the emerging ADN operators call for a more flexible and customized approach to address the penalty functions so that the operational safety and efficiency can be further enhanced. Empowered with strong comprehension, reasoning, and in-context learning capabilities, large language models (LLMs) provide a promising way to assist safe RL for energy management in ADNs. In this paper, we introduce the LLM to comprehend operational safety requirements in ADNs and generate corresponding penalty functions. In addition, we propose an RL2 mechanism to refine the generated functions iteratively and adaptively through multi-round dialogues, in which the LLM agent adjusts the functions' pattern and parameters based on training and test performance of the downstream RL agent. The proposed method significantly reduces the intervention of the ADN operators. Comprehensive test results demonstrate the effectiveness of the proposed method.
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IEEE Transactions on Smart Grid
Article . 2025 . Peer-reviewed
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Article . 2024
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Cooperative Strategies for Frequency Control of Wind Turbines to Mitigate Secondary Frequency Dip: Coefficient Allocation and Exit Techniques
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Zishuo Huang; Wenchuan Wu; Chenhui Lin; Zizhen Guo;
doi: 10.1109/tste.2024.3498006
doi: 10.1109/tste.2024.3498006
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Adaptive Data-Driven Secondary Control for Renewables Dominated Islanded Microgrids and Field Tests
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Siyun Li; Wenchuan Wu; Zizhen Guo; Haotian Liu; +1 Authors
Siyun Li; Wenchuan Wu; Zizhen Guo; Haotian Liu; Yuwei Cheng;
doi: 10.1109/tsg.2025.3574483
doi: 10.1109/tsg.2025.3574483
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Globally Optimal Distributed Operation of Integrated Electric and Heating Systems
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Yuan Du; Yixun Xue; Mohammad Shahidehpour; Wenchuan Wu; +3 Authors
Yuan Du; Yixun Xue; Mohammad Shahidehpour; Wenchuan Wu; Xinyue Chang; Zening Li; Hongbin Sun;
doi: 10.1109/tste.2024.3450608
doi: 10.1109/tste.2024.3450608
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Efficient Solution of Adjustable Affine Chance-Constrained Real-Time Dispatch
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Shuwei Xu; Wenchuan Wu; Chenhui Lin; Qi Wang; +1 Authors
Shuwei Xu; Wenchuan Wu; Chenhui Lin; Qi Wang; Siyuan Wang;
doi: 10.1109/tpwrs.2024.3498455
doi: 10.1109/tpwrs.2024.3498455
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Dual-Stage MPC-Based AGC for Wind Farm Considering Aerodynamic Interactions
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Zishuo Huang; Wenchuan Wu;
doi: 10.1109/tste.2024.3502518
doi: 10.1109/tste.2024.3502518
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Accelerating Optimal Power Flow With Structure-Aware Automatic Differentiation and Code Generation
descriptionPublicationkeyboard_double_arrow_right Article 2025Publisher:Institute of Electrical and Electronics Engineers (IEEE)
Authors: Yue Yang; Chenhui Lin; Luo Xu; Xiaodong Yang; +2 Authors
Yue Yang; Chenhui Lin; Luo Xu; Xiaodong Yang; Wenchuan Wu; Bin Wang;
doi: 10.1109/tpwrs.2024.3483489
doi: 10.1109/tpwrs.2024.3483489
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Energy Research
2025-2025

Hierarchical Coordinated Automatic Generation Control Involving Distributed Energy Resources: An Aggregation Approach

A Distributed Dispatch of Bi-Directional Power and Hydrogen Systems for Enhancing the Renewable Energy Integration in Grid-Connected Microgrids

RL2: Reinforce Large Language Model to Assist Safe Reinforcement Learning for Energy Management of Active Distribution Networks

Cooperative Strategies for Frequency Control of Wind Turbines to Mitigate Secondary Frequency Dip: Coefficient Allocation and Exit Techniques

Adaptive Data-Driven Secondary Control for Renewables Dominated Islanded Microgrids and Field Tests

Globally Optimal Distributed Operation of Integrated Electric and Heating Systems

Efficient Solution of Adjustable Affine Chance-Constrained Real-Time Dispatch

Dual-Stage MPC-Based AGC for Wind Farm Considering Aerodynamic Interactions

Accelerating Optimal Power Flow With Structure-Aware Automatic Differentiation and Code Generation

Hierarchical Coordinated Automatic Generation Control Involving Distributed Energy Resources: An Aggregation Approach

A Distributed Dispatch of Bi-Directional Power and Hydrogen Systems for Enhancing the Renewable Energy Integration in Grid-Connected Microgrids

RL2: Reinforce Large Language Model to Assist Safe Reinforcement Learning for Energy Management of Active Distribution Networks

Cooperative Strategies for Frequency Control of Wind Turbines to Mitigate Secondary Frequency Dip: Coefficient Allocation and Exit Techniques

Adaptive Data-Driven Secondary Control for Renewables Dominated Islanded Microgrids and Field Tests

Globally Optimal Distributed Operation of Integrated Electric and Heating Systems

Efficient Solution of Adjustable Affine Chance-Constrained Real-Time Dispatch

Dual-Stage MPC-Based AGC for Wind Farm Considering Aerodynamic Interactions

Accelerating Optimal Power Flow With Structure-Aware Automatic Differentiation and Code Generation

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