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Synchrophasor applications for load estimation and stability analysis

Synchrophasor applications for load estimation and stability analysis

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The use of advanced real-time monitoring and control technologies have made it possible to transform the existing power grid into smart grid. With the development of phasor measurement units (PMUs) and the availability of real-time measurements, it has become possible to develop data-driven power system applications to enhance the stability and reliability of the power grid. The application of synchrophasor measurements for online assessment of voltage stability, real-time load parameter estimation, and transient stability prediction is presented in this chapter. The different voltage stability monitoring tools used in the industry are reviewed and analyzed. PMU-based distributed voltage stability monitoring technique is also presented in this chapter. The load modeling tool used in the industry and comprehensive research effort in load modeling is discussed in this chapter. The adaptive search-based recursive least-square algorithm is presented for improved online estimation of load parameters. The existing techniques available in the literature for transient stability assessment are reviewed in this chapter. Application of maximum Lyapunov exponent (MLE) for PMU-based online transient stability detection is discussed. The effectiveness of MLE-based method is demonstrated on real-time simulation of New England 39 bus system.

Chapter Contents:

  • 9.1 Introduction
  • 9.2 Voltage stability assessment using synchrophasor data
  • 9.2.1 Review of existing PMU-based voltage stability
  • 9.2.2 Industrial voltage stability application
  • 9.2.2.1 RTDMS by EPG
  • 9.2.2.2 Voltage stability using SDI
  • 9.2.2.3 WAVI in KEPCO system
  • 9.2.2.4 Voltage stability tool by quanta
  • 9.2.2.5 ROSE by VR energy
  • 9.2.3 Decentralized voltage stability assessment
  • 9.2.3.1 Distributed coordination platform
  • 9.2.3.2 Initialization of decentralized application
  • 9.2.3.3 Decentralized voltage stability monitoring method
  • 9.3 PMU-based load modeling
  • 9.3.1 Definition of load modeling
  • 9.3.2 Classification of load models
  • 9.3.2.1 Static load
  • 9.3.2.2 Dynamic load
  • 9.3.2.3 Composite load (static load + dynamic load)
  • 9.3.3 Review of estimation of load model parameters
  • 9.3.3.1 Physical-component based approach
  • 9.3.3.2 Measurement-data based approach
  • 9.3.4 Advantages of using synchronized phasor measurements for load modeling
  • 9.3.5 Parameter identification techniques
  • 9.3.5.1 Analytical-based approach
  • 9.3.5.2 Optimization-based approach
  • 9.3.6 Estimation of static load parameters
  • 9.3.6.1 Recursive least-square estimation
  • 9.3.6.2 Adaptive search-based algorithm
  • 9.4 Transient stability assessment using synchrophasor data
  • 9.4.1 Review of existing techniques for transient stability
  • 9.4.1.1 Time domain approach
  • 9.4.1.2 Equal area criteria-based approach
  • 9.4.1.3 Energy function-based approach
  • 9.4.1.4 Other methods
  • 9.4.2 MLE-based transient stability assessment
  • 9.4.2.1 Estimation of MLE from PMU data
  • 9.4.2.2 Test study
  • 9.5 Conclusion
  • References

Inspec keywords: search problems; Lyapunov methods; least squares approximations; smart power grids; recursive estimation; power system reliability; power system transient stability; phasor measurement

Other keywords: load modeling tool; maximum Lyapunov exponent application; MLE-based method; power grid transformation; load stability analysis; voltage stability online assessment; phasor measurement unit; synchrophasor application; adaptive search-based recursive least-square algorithm; smart grid; real-time load parameter estimation; New England 39 bus system real-time simulation; power grid reliability enhancement; PMU-based online transient stability detection; real-time monitoring and control technology; data-driven power system application; PMU-based distributed voltage stability monitoring technique; PMU; transient stability prediction; power grid stability enhancement

Subjects: Reliability; Interpolation and function approximation (numerical analysis); Combinatorial mathematics; Other topics in statistics; Optimisation techniques; Power system control; Power system measurement and metering

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