A Centralized-Based Method to Determine the Local Voltage Control Strategies of Distributed Generator Operation in Active Distribution Networks

Fei Ding, Haoran Ji, Chengshan Wang, Peng Li, Jinli Zhao, Guanyu Song, Jianzhong Wu

Research output: Contribution to journalArticlepeer-review

77 Scopus Citations

Abstract

The increasing penetration of distributed generators (DGs) exacerbates the risk of voltage violations in active distribution networks (ADNs). The var capacity provided by DG inverters is a potential solution for voltage regulation. The conventional centralized control strategies limited by computation and communication burdens are difficult to meet the requirement of rapid voltage control. However, the local control strategies based on real-time measurements have a fast response to the frequent fluctuations of DG outputs. The performance of these local controllers depends on the tuning of the control parameters. This paper proposes a centralized-based method to determine the local voltage control strategies for DGs. A centralized parameter tuning model of control curves is built, in which Q-V and Pcurt-V curves of DG inverters are mathematically formulated based on piecewise linearization. The original mixed-integer nonlinear programming (MINLP) model is converted into an effectively solved mixed-integer second-order cone programming (MISOCP) model using convex relaxation. The potential benefits of DG inverters are explored to regulate both reactive and curtailed active power, based on local voltage measurements. Case studies on a modified PG&E 69-node distribution system are carried out to verify the effectiveness of the proposed method. Results show that power losses of ADNs are significantly reduced and voltage profiles are also improved.

Original languageAmerican English
Pages (from-to)2024-2036
Number of pages13
JournalApplied Energy
Volume228
DOIs
StatePublished - 2018

Bibliographical note

Publisher Copyright:
© 2018 Elsevier Ltd

NREL Publication Number

  • NREL/JA-5D00-72222

Keywords

  • Active power curtailment
  • Distributed generator (DG)
  • Local voltage control
  • Mixed-integer second-order cone programming (MISOCP)
  • Reactive power optimization

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