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Optimal placement of phasor measurement unit in distribution networks considering the changes in topology

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  • Su, Hongzhi
  • Wang, Chengshan
  • Li, Peng
  • Liu, Zhelin
  • Yu, Li
  • Wu, Jianzhong

Abstract

Distribution networks usually have a meshed structure but are operated radially to improve the operating efficiency and ensure the power supply under an emergency situation. It is of great significance to guarantee the observability of the entire system under the topology changes in operation. This paper proposes an optimal placement method of phasor measurement unit (PMU) for distribution networks. A generalized binary integer linear programming (ILP) model for PMU placement is proposed. The changes in topology are considered to guarantee the observability under any possible operation mode. The existence of zero injection nodes (ZINs), the existing measurements, and their relevance are also covered in the proposed method to reduce the installed PMU number. The objective of the ILP problem is weighted by the degree of the corresponding node to obtain a scheme with higher measurement redundancy. The correctness and effectiveness of the proposed method are verified via case studies on the IEEE 33-node test feeder, PG&E 69-node test feeder, and a medium voltage distribution network in Southern China.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:appene:v:250:y:2019:i:c:p:313-322
    DOI: 10.1016/j.apenergy.2019.05.054
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    1. Xu, Jian & Wang, Jing & Liao, Siyang & Sun, Yuanzhang & Ke, Deping & Li, Xiong & Liu, Ji & Jiang, Yibo & Wei, Congying & Tang, Bowen, 2018. "Stochastic multi-objective optimization of photovoltaics integrated three-phase distribution network based on dynamic scenarios," Applied Energy, Elsevier, vol. 231(C), pages 985-996.
    2. 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.
    3. Cao, Wanyu & Wu, Jianzhong & Jenkins, Nick & Wang, Chengshan & Green, Timothy, 2016. "Operating principle of Soft Open Points for electrical distribution network operation," Applied Energy, Elsevier, vol. 164(C), pages 245-257.
    4. Welikala, Shirantha & Thelasingha, Neelanga & Akram, Muhammed & Ekanayake, Parakrama B. & Godaliyadda, Roshan I. & Ekanayake, Janaka B., 2019. "Implementation of a robust real-time non-intrusive load monitoring solution," Applied Energy, Elsevier, vol. 238(C), pages 1519-1529.
    5. Bai, Linquan & Jiang, Tao & Li, Fangxing & Chen, Houhe & Li, Xue, 2018. "Distributed energy storage planning in soft open point based active distribution networks incorporating network reconfiguration and DG reactive power capability," Applied Energy, Elsevier, vol. 210(C), pages 1082-1091.
    6. Zhang, Shenxi & Cheng, Haozhong & Wang, Dan & Zhang, Libo & Li, Furong & Yao, Liangzhong, 2018. "Distributed generation planning in active distribution network considering demand side management and network reconfiguration," Applied Energy, Elsevier, vol. 228(C), pages 1921-1936.
    7. Wang, Xiaoxue & Wang, Chengshan & Xu, Tao & Meng, He & Li, Peng & Yu, Li, 2018. "Distributed voltage control for active distribution networks based on distribution phasor measurement units," Applied Energy, Elsevier, vol. 229(C), pages 804-813.
    8. Nazari-Heris, M. & Mohammadi-Ivatloo, B., 2015. "Application of heuristic algorithms to optimal PMU placement in electric power systems: An updated review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 214-228.
    9. Santos, Sérgio F. & Fitiwi, Desta Z. & Cruz, Marco R.M. & Cabrita, Carlos M.P. & Catalão, João P.S., 2017. "Impacts of optimal energy storage deployment and network reconfiguration on renewable integration level in distribution systems," Applied Energy, Elsevier, vol. 185(P1), pages 44-55.
    10. Yang, Xuan & Zhang, Xiao-Ping & Zhou, Suyang, 2012. "Coordinated algorithms for distributed state estimation with synchronized phasor measurements," Applied Energy, Elsevier, vol. 96(C), pages 253-260.
    11. Wei, Congying & Xu, Jian & Liao, Siyang & Sun, Yuanzhang & Jiang, Yibo & Zhang, Zhen, 2018. "Coordination optimization of multiple thermostatically controlled load groups in distribution network with renewable energy," Applied Energy, Elsevier, vol. 231(C), pages 456-467.
    12. 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.
    13. Cao, Wanyu & Wu, Jianzhong & Jenkins, Nick & Wang, Chengshan & Green, Timothy, 2016. "Benefits analysis of Soft Open Points for electrical distribution network operation," Applied Energy, Elsevier, vol. 165(C), pages 36-47.
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    Cited by:

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    2. 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).
    3. Yu Huang & Shuqin Li & Xinyue Liu & Yan Zhang & Li Sun & Kai Yang, 2019. "A Probabilistic Multi-Objective Model for Phasor Measurement Units Placement in the Presence of Line Outage," Sustainability, MDPI, vol. 11(24), pages 1-12, December.
    4. Li, Yunfeng & Xue, Wenli & Wu, Ting & Wang, Huaizhi & Zhou, Bin & Aziz, Saddam & He, Yang, 2021. "Intrusion detection of cyber physical energy system based on multivariate ensemble classification," Energy, Elsevier, vol. 218(C).
    5. Ghadikolaee, Ebad Talebi & Kazemi, Ahad & Shayanfar, Heydar Ali, 2020. "Novel multi-objective phasor measurement unit placement for improved parallel state estimation in distribution network," Applied Energy, Elsevier, vol. 279(C).

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