A Predicted-Risk-Based Protection Approach for Turbine Generator Shafts against Fatigue Damage due to Islanding

Bombay Babi, Pitshou N. Bokoro

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

A distributed generation steam turbine generator (hereafter referred to as turbine generator) improves the supply reliability of the local load when operated as a backup supply during islanding. Interconnection standards recommend removing the utility load from the island. Transient torques induced at the moments of islanding and removing the utility load from the island may cause shaft fatigue life loss and lead to fatigue damage. Therefore, a protection method is proposed in this work. The method is based on predicting the risk of shaft fatigue damage. Induced transient torque is first modeled. Fatigue study determines the local load size required to mitigate shaft torsional vibrations and avoid fatigue life loss during islanding. This is substituted in the torque function to obtain the critical torque. The risk of shaft fatigue damage is predicted by comparing the actual shaft torque with the critical torque. The turbine generator is shut down when the actual shaft torque during islanding exceeds the critical torque. Islanding on the local load is allowed when the actual shaft torque is smaller than the critical torque. The proposed method yields 0.011% shaft fatigue life loss under the most adverse islanding condition against 100% obtained with an online monitoring and protection system (OMPS).

Original languageEnglish
Article number1599
JournalEnergies
Volume15
Issue number5
DOIs
Publication statusPublished - 1 Mar 2022

Keywords

  • Distributed generation
  • Fatigue damage
  • Islanding
  • Shaft
  • Torque
  • Turbine generator

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Building and Construction
  • Fuel Technology
  • Engineering (miscellaneous)
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)
  • Control and Optimization
  • Electrical and Electronic Engineering

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