• DocumentCode
    1717600
  • Title

    Economic Assessment of Voltage Sags Based on Quality Engineering Theory

  • Author

    Li, Gengyin ; Zhou, Ming ; Zhang, Biao ; Yang, Jin

  • Author_Institution
    Key Lab. of Power Syst. Protection & Dynamic Security Monitoring & Control, North China Electr. Power Univ., Beijing
  • fYear
    2007
  • Firstpage
    1509
  • Lastpage
    1514
  • Abstract
    Voltage sag, one of the modern power quality problems, may cause tremendous economic loss, which needs scientific method to evaluate. This paper proposes an approach using quality loss function and signal-to-noise ratio (SNR) in quality engineering theory to make economic assessment to voltage sag. The inverted normal probability loss function is used to describe losses of single-type sags, where SNR method is applied to integrate different types together. The index of sag-caused loss is proposed, which is an important parameter for PQ evaluation. A five-node 35 kV distribution system is used to verify the proposed approach. The result shows that the proposed method could effectively assess financial losses caused by sags and be a reasonable instruction for PQ evaluation, improvement and pricing.
  • Keywords
    power distribution economics; power supply quality; economic assessment; economic loss; inverted normal probability loss function; power quality problems; quality engineering theory; quality loss function; signal-to-noise ratio; voltage sags; Electric variables measurement; IEEE members; Power engineering and energy; Power generation economics; Power markets; Power quality; Power system economics; Pricing; Signal to noise ratio; Voltage fluctuations; Economic evaluation; SNR; quality loss function; voltage sags;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Tech, 2007 IEEE Lausanne
  • Conference_Location
    Lausanne
  • Print_ISBN
    978-1-4244-2189-3
  • Electronic_ISBN
    978-1-4244-2190-9
  • Type

    conf

  • DOI
    10.1109/PCT.2007.4538539
  • Filename
    4538539