Research Topics

Phasor Measurement Units

Phasor Measurement Units (PMUs) perform measurements of synchronized phasors (synchrophasors), and are a key asset in power network monitoring.

  • Design, testing, characterization and pre-compliance of PMUs, with new solutions aimed at increasing the overall robustness of the management and control systems.
  • Studies on all the sources that may contribute to the uncertainty introduced by PMUs (transformers/transducers, synchronization system, phasor estimation models either under steady-state or non-steady-state conditions, etc.).
  • Studies on the impact of PMUs metrological behavior in applications such as state estimation, voltage stability monitoring, fault location.

Measurements for Smart Grids

Monitoring systems are expected to play a major role in the future active distribution grid.

  • Design of advanced measurement infrastructures
  • Design of reliable methodologies to perform accurately the state estimation of the network, in order to both optimize the management of the energy sources and implement advanced protection schemes.

Measurements for Power Quality

Any deviation of voltage and current characteristics from sinusoidal, symmetrical conditions and nominal frequency is commonly referred to as a Power Quality (PQ) issue.

  • Studies on PQ issues
  • Studies on harmonic sources estimation processes

Characterization of Voltage and Current Transformers/Transducers

The voltage and current transducers often represent the main source of uncertainty in measurements performed modern electrical power plants, since the quantities to be measured often include either harmonics or transients.

  • Studies on the behavior of some devices commonly used for voltage and current measurements, experimental comparison both in low voltage and medium voltage systems, considering either sinusoidal or distorted conditions.
  • Modelling of voltage and current transformers/transducers

Uncertainty Analysis in DSP-based Measurements

Numerical approaches based on a Monte Carlo probabilistic method can be used as an advantageous alternative to the traditional analytical methods for the evaluation of the uncertainty in measurements achieved by digitally processing sampled input data.

  • Design of algorithms/virtual instruments able to present the measurement result along with its uncertainty.
  • Design of optimization solutions.