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An islanding partition method of active distribution networks based on chance-constrained programming

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  • Zhao, Jinli
  • Zhang, Mengzhen
  • Yu, Hao
  • Ji, Haoran
  • Song, Guanyu
  • Li, Peng
  • Wang, Chengshan
  • Wu, Jianzhong

Abstract

With the high integration of uncontrollable distributed generators (NDGs) comprising photovoltaic arrays (PVs) and wind turbines (WTs), many technical issues have become increasingly prominent in the islanding operation of active distribution networks (ADNs). Such problems including branch overloading and voltage violations threaten the secure operation of distribution systems and a continuous power supply. To address the uncertainties of NDG outputs when implementing islanding partition strategies, this paper proposes a new method of the islanding partition of ADNs based on chance-constrained programming. First, power generation scenarios and probability distributions for these scenarios are generated according to historical data considering the time series characteristics and uncertainties of NDGs. Then, the chance-constrained description of islanding operation is expanded to consider the effect of uncertainties related to NDGs. Moreover, an islanding partition model of ADNs based on chance-constrained programming is established. By applying convex relaxation and introducing auxiliary variables, the model is converted to a mixed-integer quadratically constrained programming model that can be effectively solved. Finally, case studies involving the modified IEEE 33-node system, IEEE 123-node system and an actual distribution system are conducted to verify the effectiveness and scalability of the proposed method.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:242:y:2019:i:c:p:78-91
    DOI: 10.1016/j.apenergy.2019.03.118
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    References listed on IDEAS

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    1. 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.
    2. Dong, Xiaohong & Mu, Yunfei & Xu, Xiandong & Jia, Hongjie & Wu, Jianzhong & Yu, Xiaodan & Qi, Yan, 2018. "A charging pricing strategy of electric vehicle fast charging stations for the voltage control of electricity distribution networks," Applied Energy, Elsevier, vol. 225(C), pages 857-868.
    3. Wang, Chengshan & Song, Guanyu & Li, Peng & Ji, Haoran & Zhao, Jinli & Wu, Jianzhong, 2017. "Optimal siting and sizing of soft open points in active electrical distribution networks," Applied Energy, Elsevier, vol. 189(C), pages 301-309.
    4. Ding, Tao & Lin, Yanling & Bie, Zhaohong & Chen, Chen, 2017. "A resilient microgrid formation strategy for load restoration considering master-slave distributed generators and topology reconfiguration," Applied Energy, Elsevier, vol. 199(C), pages 205-216.
    5. El-Sharafy, M. Zaki & Farag, Hany E.Z., 2017. "Back-feed power restoration using distributed constraint optimization in smart distribution grids clustered into microgrids," Applied Energy, Elsevier, vol. 206(C), pages 1102-1117.
    6. Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2014. "Integration of PV and BES units in commercial distribution systems considering energy loss and voltage stability," Applied Energy, Elsevier, vol. 113(C), pages 1162-1170.
    7. Marzband, Mousa & Ghadimi, Majid & Sumper, Andreas & Domínguez-García, José Luis, 2014. "Experimental validation of a real-time energy management system using multi-period gravitational search algorithm for microgrids in islanded mode," Applied Energy, Elsevier, vol. 128(C), pages 164-174.
    8. Mousavizadeh, Saeed & Haghifam, Mahmoud-Reza & Shariatkhah, Mohammad-Hossein, 2018. "A linear two-stage method for resiliency analysis in distribution systems considering renewable energy and demand response resources," Applied Energy, Elsevier, vol. 211(C), pages 443-460.
    9. Ji, Haoran & Wang, Chengshan & Li, Peng & Song, Guanyu & Wu, Jianzhong, 2018. "SOP-based islanding partition method of active distribution networks considering the characteristics of DG, energy storage system and load," Energy, Elsevier, vol. 155(C), pages 312-325.
    10. Abdullah, M.A. & Agalgaonkar, A.P. & Muttaqi, K.M., 2014. "Assessment of energy supply and continuity of service in distribution network with renewable distributed generation," Applied Energy, Elsevier, vol. 113(C), pages 1015-1026.
    11. Ji, Haoran & Wang, Chengshan & Li, Peng & Zhao, Jinli & Song, Guanyu & Ding, Fei & Wu, Jianzhong, 2018. "A centralized-based method to determine the local voltage control strategies of distributed generator operation in active distribution networks," Applied Energy, Elsevier, vol. 228(C), pages 2024-2036.
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    5. Jiahao Chen & Bing Sun & Yuan Zeng & Ruipeng Jing & Shimeng Dong & Jingran Wang, 2023. "An Optimal Scheduling Method of Shared Energy Storage System Considering Distribution Network Operation Risk," Energies, MDPI, vol. 16(5), pages 1-24, March.
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    7. Zhou, Bo & Ai, Xiaomeng & Fang, Jiakun & Yao, Wei & Zuo, Wenping & Chen, Zhe & Wen, Jinyu, 2019. "Data-adaptive robust unit commitment in the hybrid AC/DC power system," Applied Energy, Elsevier, vol. 254(C).
    8. Faqiry, M. Nazif & Edmonds, Lawryn & Wu, Hongyu & Pahwa, Anil, 2020. "Distribution locational marginal price-based transactive day-ahead market with variable renewable generation," Applied Energy, Elsevier, vol. 259(C).

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