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Two-stage cooperative real-time autonomy control strategy considering vulnerability of active distribution networks

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  • Li, Pan
  • Wang, Feng
  • Ma, Teng
  • Zhang, Shuqing

Abstract

A two-stage cooperative real-time autonomy control strategy considering vulnerability of active distribution networks (ADNs) is proposed to solve the problems of intensified voltage fluctuation, increased network loss, and risk of voltage violation. A vulnerability index of the power grid is proposed to optimize the model from “point” to “area”, which can more comprehensively evaluate the power quality of ADNs. The day-ahead stage, considering the action times of the on-load tap changer (OLTC) and capacitor bank (CB) and the reactive power response ability of the photovoltaic (PV) inverter, a relaxation-clustering-correction decoupling strategy based on Ward clustering is proposed to make the optimization results more reasonable; based on the curve-increasing particle swarm optimization (CIPSO) algorithm, a high-dimensional, strongly coupled mixed integer nonlinear model was solved. The real-time stage, taking the optimization results of the day-ahead stage as the benchmark data, based on the relationship between the reactive power increment and real-time output prediction error of PV inverter, a real-time autonomy control strategy that only relies on local real-time information is proposed by fusing voltage sensitivity information. The rationality and superiority of the proposed strategy are verified through the simulation analysis of the modified IEEE 33 bus system.

Suggested Citation

  • Li, Pan & Wang, Feng & Ma, Teng & Zhang, Shuqing, 2023. "Two-stage cooperative real-time autonomy control strategy considering vulnerability of active distribution networks," Renewable Energy, Elsevier, vol. 219(P1).
    • Handle: RePEc:eee:renene:v:219:y:2023:i:p1:s0960148123014295
    DOI: 10.1016/j.renene.2023.119514
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    References listed on IDEAS

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    1. Smriti Mallapaty, 2020. "How China could be carbon neutral by mid-century," Nature, Nature, vol. 586(7830), pages 482-483, October.
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