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Quantified analysis method for operational flexibility of active distribution networks with high penetration of distributed generators

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  • Ji, Haoran
  • Wang, Chengshan
  • Li, Peng
  • Song, Guanyu
  • Yu, Hao
  • Wu, Jianzhong

Abstract

With the integration of high shares of distributed generators (DGs), it is increasingly difficult to cope with the various uncertainties and puts forward higher requirements for the operational flexibility in active distribution networks (ADNs). Controllability of ADNs has been significantly improved by the application of energy storage and power electronic devices. However, due to the difficulties in effective coordination of various controllable resources, the controllability cannot be fully translated into the system flexibility. In this paper, an analytical framework for quantifying the flexibility of ADNs is proposed, including the quantification of node flexibility, the matching of system flexibility, and the flexibility of network transmission. The proposed framework provides a novel perspective of flexibility to reinterpret operation issues of distribution networks. As the power imbalance and voltage deviation are even more severe caused by the high shares of DG integration, the indexes of flexibility from magnitude, frequency and intensity dimensions are deteriorated in ADNs operation. Through the spatial and temporal regulation of power flow, various controllable devices, such as soft open points (SOPs) and energy storage system (ESS), can effectively mitigate the power imbalance and voltage deviation to improve the indexes of system flexibility. Thus, under the unified analytical framework, the potential benefits of system controllability are fully utilized to provide effective countermeasures for the flexible operation of ADNs. Finally, case studies are performed on the modified IEEE 33-node system to quantify the operational flexibility of ADNs and verify the flexibility enhancement brought by controllable resources.

Suggested Citation

  • Ji, Haoran & Wang, Chengshan & Li, Peng & Song, Guanyu & Yu, Hao & Wu, Jianzhong, 2019. "Quantified analysis method for operational flexibility of active distribution networks with high penetration of distributed generators," Applied Energy, Elsevier, vol. 239(C), pages 706-714.
    • Handle: RePEc:eee:appene:v:239:y:2019:i:c:p:706-714
    DOI: 10.1016/j.apenergy.2019.02.008
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    1. Ji, Haoran & Wang, Chengshan & Li, Peng & Zhao, Jinli & Song, Guanyu & Wu, Jianzhong, 2018. "Quantified flexibility evaluation of soft open points to improve distributed generator penetration in active distribution networks based on difference-of-convex programming," Applied Energy, Elsevier, vol. 218(C), pages 338-348.
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    Cited by:

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    3. Zhao, Jinli & Zhang, Mengzhen & Yu, Hao & Ji, Haoran & Song, Guanyu & Li, Peng & Wang, Chengshan & Wu, Jianzhong, 2019. "An islanding partition method of active distribution networks based on chance-constrained programming," Applied Energy, Elsevier, vol. 242(C), pages 78-91.
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    7. Zhou, Yulu & Zhang, Jingrui, 2020. "Three-layer day-ahead scheduling for active distribution network by considering multiple stakeholders," Energy, Elsevier, vol. 207(C).
    8. Deakin, Matthew & Sarantakos, Ilias & Greenwood, David & Bialek, Janusz & Taylor, Phil C. & Walker, Sara, 2023. "Comparative analysis of services from soft open points using cost–benefit analysis," Applied Energy, Elsevier, vol. 333(C).
    9. Li, Peng & Ji, Haoran & Yu, Hao & Zhao, Jinli & Wang, Chengshan & Song, Guanyu & Wu, Jianzhong, 2019. "Combined decentralized and local voltage control strategy of soft open points in active distribution networks," Applied Energy, Elsevier, vol. 241(C), pages 613-624.
    10. Zare Oskouei, Morteza & Gharehpetian, Gevork B., 2024. "Flexibility enhancement of multi-district DISCOs considering a trade-off between congestion and extractable reserve capacity from virtual energy storage systems," Applied Energy, Elsevier, vol. 353(PB).
    11. Zhao, Zhida & Yu, Hao & Li, Peng & Li, Peng & Kong, Xiangyu & Wu, Jianzhong & Wang, Chengshan, 2019. "Optimal placement of PMUs and communication links for distributed state estimation in distribution networks," Applied Energy, Elsevier, vol. 256(C).
    12. Su, Hongzhi & Wang, Chengshan & Li, Peng & Liu, Zhelin & Yu, Li & Wu, Jianzhong, 2019. "Optimal placement of phasor measurement unit in distribution networks considering the changes in topology," Applied Energy, Elsevier, vol. 250(C), pages 313-322.
    13. Jiao, Heng & Xiao, Jun & Zu, Guoqiang & Song, Chenhui & Lv, Zihan & Bao, Zhenyu & Qiu, Zekai, 2024. "Concavity-convexity of distribution system security region. Part II: Mathematical principle, judgment, and application," Applied Energy, Elsevier, vol. 361(C).
    14. Qiu, Rui & Liao, Qi & Yan, Jie & Yan, Yamin & Guo, Zhichao & Liang, Yongtu & Zhang, Haoran, 2021. "The coupling impact of subsystem interconnection and demand response on the distributed energy systems: A case study of the composite community in China," Energy, Elsevier, vol. 228(C).
    15. Li, Peng & Ji, Jie & Ji, Haoran & Song, Guanyu & Wang, Chengshan & Wu, Jianzhong, 2020. "Self-healing oriented supply restoration method based on the coordination of multiple SOPs in active distribution networks," Energy, Elsevier, vol. 195(C).
    16. Lv, Chaoxian & Yu, Hao & Li, Peng & Wang, Chengshan & Xu, Xiandong & Li, Shuquan & Wu, Jianzhong, 2019. "Model predictive control based robust scheduling of community integrated energy system with operational flexibility," Applied Energy, Elsevier, vol. 243(C), pages 250-265.
    17. Bao, Minglei & Hui, Hengyu & Ding, Yi & Sun, Xiaocong & Zheng, Chenghang & Gao, Xiang, 2023. "An efficient framework for exploiting operational flexibility of load energy hubs in risk management of integrated electricity-gas systems," Applied Energy, Elsevier, vol. 338(C).
    18. Su, Hongzhi & Wang, Chengshan & Li, Peng & Li, Peng & Liu, Zhelin & Wu, Jianzhong, 2019. "Novel voltage-to-power sensitivity estimation for phasor measurement unit-unobservable distribution networks based on network equivalent," Applied Energy, Elsevier, vol. 250(C), pages 302-312.
    19. Klyapovskiy, Sergey & You, Shi & Michiorri, Andrea & Kariniotakis, George & Bindner, Henrik W., 2019. "Incorporating flexibility options into distribution grid reinforcement planning: A techno-economic framework approach," Applied Energy, Elsevier, vol. 254(C).
    20. Perera, A.T.D. & Nik, Vahid M. & Wickramasinghe, P.U. & Scartezzini, Jean-Louis, 2019. "Redefining energy system flexibility for distributed energy system design," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    21. Sulman Shahzad & Elżbieta Jasińska, 2024. "Renewable Revolution: A Review of Strategic Flexibility in Future Power Systems," Sustainability, MDPI, vol. 16(13), pages 1-24, June.
    22. Arul Rajagopalan & Dhivya Swaminathan & Meshal Alharbi & Sudhakar Sengan & Oscar Danilo Montoya & Walid El-Shafai & Mostafa M. Fouda & Moustafa H. Aly, 2022. "Modernized Planning of Smart Grid Based on Distributed Power Generations and Energy Storage Systems Using Soft Computing Methods," Energies, MDPI, vol. 15(23), pages 1-18, November.

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