Since state variables pose challenges for direct measurement, the SCADA system provides a wealth of measurements, encompassing voltage magnitudes, power flows, and power injections. With these SCADA measurements at hand, the primary objective of PSSE is to deduce the state variables, specifically the complex voltages at all network buses. To circumvent the challenges posed by nonconvex optimization in power system monitoring and control, recent studies have shifted their focus toward the development of data-driven and model-driven NNs solutions, as documented in references.

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Data-Driven Graph Priors for State Estimation

  • Gang Wang,
  • Jian Sun,
  • Jie Chen

摘要

Since state variables pose challenges for direct measurement, the SCADA system provides a wealth of measurements, encompassing voltage magnitudes, power flows, and power injections. With these SCADA measurements at hand, the primary objective of PSSE is to deduce the state variables, specifically the complex voltages at all network buses. To circumvent the challenges posed by nonconvex optimization in power system monitoring and control, recent studies have shifted their focus toward the development of data-driven and model-driven NNs solutions, as documented in references.