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Integration flexibility of renewable distributed energy resources in active distribution networks: A two-module data-driven characterization method

Author

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  • Lin, Wei
  • Wang, Chongyu
  • Zhang, Wenjie
  • Liang, Zipeng
  • Chung, C.Y.

Abstract

Characterizing the integration flexibility of renewable distributed energy resources (RDERs), which describes the feasible region of RDER accommodations with which the operational constraints of an active distribution network (ADN) can be respected, facilitates the ADN operations. However, traditional characterization methods face the challenge of concurrently dealing with inevitable AC power flow and numerous RDERs. To resolve this issue, this paper develops a novel characterization method that contains two interconnected modules: learning and updating modules. The two modules jointly and iteratively calculate the parameters to characterize the integration flexibility of RDERs (IFR). In the learning module, a new loss function is designed to train the IFR parameters using a training data set. In the updating module, two optimization problems are developed based on the optimization-based performance estimation of the trained parameters to generate more data points for performance improvement in the learning module. The effectiveness of the proposed method is corroborated in the IEEE 33-bus and IEEE 136-bus test systems.

Suggested Citation

  • Lin, Wei & Wang, Chongyu & Zhang, Wenjie & Liang, Zipeng & Chung, C.Y., 2024. "Integration flexibility of renewable distributed energy resources in active distribution networks: A two-module data-driven characterization method," Energy, Elsevier, vol. 304(C).
    • Handle: RePEc:eee:energy:v:304:y:2024:i:c:s0360544224019133
    DOI: 10.1016/j.energy.2024.132139
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    References listed on IDEAS

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    1. Copp, David A. & Nguyen, Tu A. & Byrne, Raymond H. & Chalamala, Babu R., 2022. "Optimal sizing of distributed energy resources for planning 100% renewable electric power systems," Energy, Elsevier, vol. 239(PE).
    2. Yang, Zhifang & Zhong, Haiwang & Lin, Wei & Lin, Jeremy & Chen, Yonghong & Xia, Qing & Liu, Wentao & Zhang, Xuan, 2019. "Mapping between transmission constraint penalty factor and OPF solution in electricity markets: analysis and fast calculation," Energy, Elsevier, vol. 168(C), pages 1181-1191.
    3. Dewi, Retno Gumilang & Siagian, Ucok Welo Risma & Asmara, Briantama & Anggraini, Syahrina Dyah & Ichihara, Jun & Kobashi, Takuro, 2023. "Equitable, affordable, and deep decarbonization pathways for low-latitude developing cities by rooftop photovoltaics integrated with electric vehicles," Applied Energy, Elsevier, vol. 332(C).
    4. Chen, Boyu & Che, Yanbo & Zheng, Zhihao & Zhao, Shuaijun, 2023. "Multi-objective robust optimal bidding strategy for a data center operator based on bi-level optimization," Energy, Elsevier, vol. 269(C).
    5. Wang, Jiangjiang & Deng, Hongda & Qi, Xiaoling, 2022. "Cost-based site and capacity optimization of multi-energy storage system in the regional integrated energy networks," Energy, Elsevier, vol. 261(PA).
    6. Tie, Yingqi & Hu, Bo & Shao, Changzheng & Huang, Wei & Qi, Feng & Xie, Kaigui, 2023. "Integrated flexibility characterization and measurement of distributed multi-energy systems considering temporal coupling constraints," Energy, Elsevier, vol. 283(C).
    7. Lin, Wei & Jiang, Hua & Jian, Haojun & Xue, Jingwei & Wu, Jianghua & Wang, Chongyu & Lin, Zhenjia, 2023. "High-dimension tie-line security regions for renewable accommodations," Energy, Elsevier, vol. 270(C).
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