Implementing a Real Time System Where a Majority of Deliveries Are Not on SCADA
- Alisa Bullard (New Mexico Gas Company) | Samon Kashani (Gregg Engineering Inc.)
- Document ID
- Pipeline Simulation Interest Group
- PSIG Annual Meeting, 14-17 May, London, UK
- Publication Date
- Document Type
- Conference Paper
- 2019. PSIG, Inc.
- 2 in the last 30 days
- 29 since 2007
- Show more detail
Oftentimes smaller transmission systems will be designed and built with only essential telemetry in mind. While deliveries are not monitored in real time on SCADA, monthly consumption data is recorded and available. While this amount of telemetry is sufficient to accurately and appropriately monitor the pipeline, it may not provide enough data to produce a hydraulically accurate simulation model.
We set out to determine the feasibility of creating a Transient real time model of one such small transmission system where as much as 80% of the deliveries are not on SCADA. This ~75-mile-long system is mostly comprised of larger seasonal agricultural customers which can draw the system down and impact the few residential distribution systems that are on the mainline. The real time model can be used to analyze potential improvements and/or system expansion alternatives and their effect on pressure at the delivery border station.
We combined the use of a hydraulic simulator, load prediction software, and data analysis to develop a methodology to simulate the transient behavior for these non-SCADA points. Where SCADA was not available, historical data from similar type customers was analyzed to produce profiles that could be applied.
A Real Time Model (RTM) was built utilizing both actual SCADA data and simulated SCADA to accurately model the transmission system. This model demonstrates that despite a large gap in the available real-time SCADA data, where missing data could account for as much as 80% of the total load on the system, we can model the behavior of the system by calculating and accurately estimating flows and pressures.
In addition, users can easily convert the RTM into a transient predictive model where further feasibility and system improvements can be analyzed.
|File Size||590 KB||Number of Pages||11|