Grid Analysis

PSI GMS provides sophisticated analysis tools for gas grids. The monitoring and control of the gas grid will be optimised and more secure through use of simulation, forecasting as well as maintenance and disturbance handling.

PSIganesi is a simulation system which provides a complete insight to the gas grids behavior and future, especially in areas where measurements are not available.

The system provides the following Simulation modes:

Real-Time Simulation

The PSIganesi Real-Time Simulation estimates the current process state taking pressure, flow, gas composition and temperature into account. Simulation results are checked continuously. All information including alarms and warning messages is logged and displayed.

Look-Ahead Simulation

A preselected operation mode might become inappropriate. The PSIganesi Look-Ahead Simulation module identifies any negative drift to undesirable conditions in advance. The system detects the process element that is going to reach a certain threshold and calculates the exact time when the event will occur. The operator can then adjust control or switch operations. A Look-Ahead simulation runs on a cyclical basis.

What-If Simulation

In gas grid operations it is essential to know in advance the consequences of operator-initiated actions. Based on realtime simulation, valve settings, modified set points and other information PSIganesi What-If Simulation calculates the corresponding future process values. Multiple scenarios can be evaluated.

PSIganesi includes the following application modules:

  • Property Tracking
  • Scraper Tracking
  • Velocity Monitoring
  • Fuel Gas Calculation
  • Real-Time Simulation
  • What-If Simulation
  • Look-Ahead Simulation
  • Leak Detection and Location
  • Hydraulic Profiles

Forecasting

PSIprogose is used to estimate gas consumption. It incorporates different methods taking into account weather forecasts or periodic behaviour. The mathematical models utilise calendars, different temperature areas and contract conditions. Based on Kalman filtering, exponential smoothing and trend corrections the system is self-learning. The models are initialised with historical data. The forecaster can use all data objects from GMS applications or third-party systems.

The following methods are provided to predict gas consumption:

  • Regression Analysis
  • Time Series
  • Extrapolation Method
  • Load Profile

Maintenance and Disturbance Analysis
Based on historical data and future planning the system provides several tools to detect and to analyse current or future improper operational situations.

PSIganesi Flyer