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Network partition and distributed voltage coordination control strategy of active distribution network system considering photovoltaic uncertainty

Author

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  • Meng, Lingzhuochao
  • Yang, Xiyun
  • Zhu, Jiang
  • Wang, Xinzhe
  • Meng, Xin

Abstract

Aiming at the voltage exceeding problem caused by the introduction of Photovoltaic (PV) in Active distribution network (ADN), a comprehensive electrical distance index was established considering active and reactive voltage sensitivity, and the uncertainty of traditional PV probability density function (PDF) was optimized by random simulation method. The electrical distance expectation matrix between nodes was established by discretization of PV output probability distribution characteristics, and the ADN system was partitioned by affinity propagation (AP) algorithm. Taking active power loss as the objective function, the non-convex reactive power optimization control problem is transformed into a convex quadratic programming problem by LinDistFlow equation. An improved alternating direction method of multipliers (ADMM) which adaptively adjusts the penalty parameters is used to convert the finite boundaries of adjacent regions into data. By coordinating on-load tap-changer (OLTC), capacitor banks (CBs), and PV inverters on different time scales, the fast optimal control of global voltage in ADN is realized. The proposed method is tested on IEEE 33-bus and IEEE 123-bus distribution systems. After the optimization control algorithm described in this paper, the system network loss was reduced by 3.88%. Compared with the semi-definite programming relaxation, the calculation speed of LinDistFlow equation is increased by 72.2%. The results fully verify the feasibility and high efficiency of the control strategy described in this paper.

Suggested Citation

  • Meng, Lingzhuochao & Yang, Xiyun & Zhu, Jiang & Wang, Xinzhe & Meng, Xin, 2024. "Network partition and distributed voltage coordination control strategy of active distribution network system considering photovoltaic uncertainty," Applied Energy, Elsevier, vol. 362(C).
  • Handle: RePEc:eee:appene:v:362:y:2024:i:c:s0306261924002290
    DOI: 10.1016/j.apenergy.2024.122846
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