Energia Mayakan (Mayakan) is Mexico's first privately owned gas pipeline venture. This 432 mile 24" diameter pipeline transports natural gas from a PEMEX plant to several cyclic-load power plants in the Yucatán peninsula of Mexico. On-line leak detection, off-line predicting, and off-line training models were commissioned in the summer of 2000 and have proven successful in assisting control room operators to safely and efficiently operate this pipeline. Specific real-world experiences will be presented that demonstrate how the various simulation tools have benefited the operation. Mayakan's operators use real-time and predictor simulation models to plan compressor schedules, budget fuel usage, detect leaks, and recognize maintenance needs. The training model has been used to train and to certify all control room operators. This case history also presents lessons learned during the first year of operation, and uses of the model that had not been anticipated.
Mayakan initiated commercial operation in September 1999 as the first privately owned pipeline to deliver gas to third parties in Mexico. A SCADA system was installed to monitor and control the pipeline. Computer modeling tools were configured to supplement SCADA and to provide leak detection, predictive modeling, and operator training. These tools are intended to provide support to the solo control room operator in making operational decisions and to promote safety, reliability and efficiency. This paper intends to present a description of the modeling system configuration and the benefits of using these tools in Mayakan during the first year of operation.
Mayakan currently operates without any in-house engineering staff. Solo operators in the control room use the on-line model for linepack analysis, leak detection, SCADA instrument troubleshooting, survival time analysis, and predictive modeling analysis. They use a predictor model to make decisions regarding compressor schedules, fuel budgeting, and whether they will approve or deny customer's requests to increase their gas rates over the rates that have been previously allocated. The training model is used to educate and to certify Mayakan's staff. All three of the models are described in more detail in the sections that follow.
All of the various models communicate with SCADA using bi-directional interfaces. SCADA data feeds the on-line leak detection model, whereas the predictor and training models can begin from either a current or saved on-line model state, or manually set conditions. All models can display their results using graphical display screens and also communicate modeling results back to SCADA. The on-line and predictor models send very few data items back to SCADA, whereas the training model, which simulates all pipeline hydraulics, sends hundreds of values to a copy of the SCADA system every few seconds.
The on-line model has become an integral part of gas control. Continuous monitoring of pipeline hydraulics provides leak detection alarms, leak location calculations, and line pack calculations. The on-line model is also used to provide an evergreen starting hydraulic pipeline state for predictive modeling simulations.
