State Estimation for Situational Awareness of Active Distribution System with Photovoltaic Power Plants

Zhi Fang, Yuzhang Lin, Shaojian Song, Chi Li, Xiaofeng Lin, Yanbo Chen

Research output: Contribution to journalArticlepeer-review

Abstract

The real-time monitoring of the grid-connected renewable energy generations is of great significance to the operation and control of active distribution systems (ADS). Considering the detailed photovoltaic (PV) system model and ambient influencing factors, this paper develops a state estimation framework for the ADS with integrated PV power plants. Firstly, suitable models of PV arrays and power converters for steady-state state estimation are developed. Based on these models, the state variables of a PV generation system are selected, and the measurement equations are derived. Finally, combined with the state estimation model of distribution networks, a framework for state estimation and bad data processing of an ADS with PV power plants is presented. A parameter estimation approach for PV power plants based on multiple measurement scans is also developed in order to address the practical situation of unknown model parameters. Simulation results show that the proposed framework can effectively capture the operating state of the distribution network and PV power plants. In addition, it enhances the estimation accuracy and bad data processing capability compared to conventional state estimation frameworks.

Original languageEnglish (US)
Article number9141365
Pages (from-to)239-250
Number of pages12
JournalIEEE Transactions on Smart Grid
Volume12
Issue number1
DOIs
StatePublished - Jan 2021

Keywords

  • Active distribution system
  • bad data processing
  • parameter estimation
  • photovoltaic power plant
  • situational awareness
  • state estimation

ASJC Scopus subject areas

  • General Computer Science

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