Advanced Monitoring for Power Systems

  Power System -> State Estimation -> Control Center Copyright: © ACS  

Modern power systems increasingly need advanced tools for their real-time management, control and automation. The first step to implement these advanced functionalities is to have the accurate knowledge of the grid operating conditions. Real-time monitoring is commonly adopted to this purpose within the control centers of power systems. Monitoring tools are usually based on specific state estimation techniques, which allow integrating redundant measurements, filtering out measurement errors and providing the most likely picture of the grid operating conditions based on the available input information.

The course Advanced Monitoring for Power System is intended to provide the students the basics about state estimation theory and to present the most common approaches adopted as state-of-the-art solutions for the monitoring of power systems. Together with the classical techniques implemented in transmission systems, an overview of challenges and solutions for the deployment of state estimation at the distribution level is also provided. In addition, different options and architectural schemes for the implementation of distributed state estimation approaches are discussed, while the final part of the course deals with the models for dynamic state estimation using the Kalman filter theory.

The course is divided into the following parts:

  • State Estimation in Transmission Systems
    • Power system modelling
    • Maximum Likelihood Estimation theory
    • Weighted Least Squares method
    • Hybrid estimation with Phasor Measurement Units
    • Observability Analysis
    • Bad data detection and identification
  • State Estimation in Distribution Systems
    • Differences between transmission and distribution SE
    • Distribution system modelling
    • Concept of pseudo-measurements
    • Alternative WLS formulations
  • Other State Estimation techniques
    • Weighted Least Absolute Value method
    • Backward/Forward sweep procedures
    • Data driven approaches
    • Metrics for SE performance evaluation
  • Multi-Area State Estimation approaches
    • Uncertainty propagation theory
    • Classification of multi-area approaches
    • Hierarchical state estimation approaches
    • Decentralized state estimation approaches
  • Dynamic State Estimation
    • Kalman filter theory
    • Kalman filter models for power system SE
    • Extended Kalman filter
    • Nonlinear Kalman filer state estimation


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