M2IEGS Project Goals & Impacts

The goals of the Faster-than-Real-Time Simulation with Demonstration for Resilient Distributed Energy Resource Integration project are to:
  • Provide intelligence for rapidly detecting abnormalities, including cybersecurity breaches
  • Manage voltage stability with rapidly changing renewable generation using faster-than-real-time, time-series analyses of an integrated power system model, and employing real-time measurements and forecasts
  • Use conservation voltage reduction (CVR) to improve efficiency while simultaneously increasing photovoltaic (PV) hosting capacity
  • Coordinate control between customer-owned inverters and utility control equipment
The impacts of this project will help shape the future of the electric power industry, with the areas below being particularly impacted.
  • Power system real-time analysis accuracy
    Increasing the model details over traditionally used models, including modeling transmission as three-phase and modeling secondary circuits, improves the real-time analysis accuracy.
  • Faster computation and robust analysis of large-scale systems via a matrix-free approach
    The power flow analysis in this project extends from the transmission system through the secondary circuits, all in one model. The matrix-free analysis approach employed has been shown to be more robust than traditional, matrix-based analysis approaches, and is used to analyze both the transmission and distribution systems.
  • Real-time voltage stability analysis
    The matrix-free power flow analysis is employed in real-time analysis to monitor weak busses and transmission lines, calculating the additional bus load or transmission line flow that will result in a voltage instability for each bus or line.
  • Short-term load/PV generation forecasting
    The project uses 30-minute forecasts of load and PV generation variations in the Faster-Than-Real-Time simulation. These forecasts are unique in two respects: the load forecast is based on stochastic, weather-dependent load models derived from each customer’s AMI load data; and the PV forecast contains a statistical analysis of the PV variability for each PV generator.
  • Real-time control
    Customer-owned inverter controls and utility controls are coordinated to minimize utility control device motion while controlling the voltage profile of the feeder. The specified feeder voltage profile for control will vary depending upon events such as abnormalities detected or approaching voltage instability.
DOE Project Briefing by EDD - Faster-than-Real-Time Simulation
for Resilient DER Integration
SEPA-EDD Webinar - October 2020