Grid Visibility and Situational Awareness

  • The electric distribution system is largely blind. Only ~20% of the North American distribution feeders have any form of monitoring.
  • Even for feeders with sensors, only a small subset of the lines and assets are being monitored (e.g. CT/PT on SCADA, AMI for grid edge).
  • It is cost prohibitive to sweep the distribution system with sensors.
  • Localized sensing does not imply situational awareness.
  • Situational awareness provides information beyond locally monitored points and contextually aware (e.g. voltage thresholds, capacity limits).
  • Low cost, rapid deployment, and highly scalable solution for grid visibility.
  • Provide valuable insights for asset investments, capacity planning, power quality, DER integration and system operations.
  • Rapid modernization strategy for urban, suburban and rural systems.
  • Model-based system for maximum accuracy and adapts to real time network topology, even under complex two-way power flow.
  • Highly modular and lightweight, “one-feeder-at-a-time”, yet scalable for full enterprise integration.
  • State estimation of converging power flows down to 1% accuracy every few seconds from a mix of data inputs.
  • Inputs include the 3Φ AC unbalanced electrical model of the network, with real time network topology, along with a limited number of field measurements (e.g. SCADA, AMI).
  • GridOS performs a unique and powerful distributions system state estimation (DSSE) algorithm full feeder situational awareness.
  • Yields online power flow results, including single-phase voltages, currents, real/reactive power, real/reactive losses, load duration curves, and more, across the distribution network.
  • For real time operations, quasi-time series analysis in operational planning, exports into planning systems, and running “what-if” scenarios.