Statistical Analysis and Forecasting of Damping in the Nordic Power System

Francesco Sulla, Matti Koivisto, Janne Seppanen, Jukka Turunen, Liisa C. Haarla, Olof Samuelsson

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents an application of multiple linear regression (MLR) to extract significant correlations between damping of electromechanical modes and system operating conditions and to forecast future damping values, based on existing day-ahead market forecasts for power flows and generation. The presented analysis uses measurements from the Nordic power system. First, a static MLR model is developed to explain the variability of the damping of the 0.35-Hz inter-area mode in the Nordic system. Together with the static model, a dynamic MLR model is used for forecasting the damping 24 hours ahead, using day-ahead market forecasts. Test results indicate the proposed methods are able to correctly predict about 90% of the low damped operating conditions observed during a year, if day-ahead market forecasts are accurate. These results suggest that the methods could be used to issue early warnings about future operating conditions with low damping.
Original languageEnglish
Pages (from-to)306-315
JournalIEEE Transactions on Power Systems
Volume30
Issue number1
DOIs
Publication statusPublished - 2015

Subject classification (UKÄ)

  • Other Electrical Engineering, Electronic Engineering, Information Engineering

Free keywords

  • Damping forecast
  • electromechanical oscillations
  • multiple linear
  • regression (MLR)
  • phasor measurement unit (PMU) data

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