The Greenville Utilities Commission (GUC) provides electric, water, sewer and natural gas services to more than 135,800 customers in the city of Greenville and across Pitt County, North Carolina. The utility’s distribution network is composed of approximately 70% polyvinyl chloride (PVC), 20% asbestos-cement (AC) and 10% cast iron pipelines. Providing a reliable supply of water while effectively managing cost is at the core of the utility’s mission.
Like many water utilities, GUC has placed a priority on reducing leaks throughout its network. Videos on its social media channel urge residential customers to be vigilant about potential leaks in their homes that can lead to significant water waste over time. Just as critical is the need to avoid water main breaks that can lead to significant water loss, causing loss of revenue and requiring costly repairs.
This situation is not unique to GUC. Recent studies have shown that United States water mains are failing at an accelerating rate—even as water utilities are challenged by limited funding.1 A 2018 study found that water pipe breaks in the U.S. and Canada increased 27% over just six years.2 This represents a significant cost for utilities and rate payers and increased burdens on utility staff.
Challenge: Improving Break Detection & Prevention
GUC was challenged by pressure transients that cause damage to network assets leading to leaks and water main breaks. One such break occurred on a weekend night, and it took hours for the utility crew to locate the leak by driving around the service area. While the break was eventually discovered in a 14-inch main in an out-of-the-way industrial location, GUC management realized they needed a better solution for proactively mitigating pressure transient problem areas and for rapidly and accurately locating breaks. Speedy response time is critical to minimizing the impact on customers and costly water loss.
While GUC had pressure monitors deployed at various locations in the network, they did not have the ability to detect and triangulate the source of pressure transients. Recognizing that improved pressure transient monitoring was needed, GUC management then faced the challenge of where to place monitors to best inform its network calming efforts.
Solution: Data-Driven Deployment Planning
A cloud platform deployment planning software tool allowed utility engineers to identify the optimum locations for monitor deployment to maximize coverage for pressure transient monitoring and network management and analysis. The tool simulates different transient event sizes and calculates wave propagation across proposed locations. The tool analyzes pressure wave attenuation and predicts impacts at various network locations. Using geographic information system (GIS) data, it produces color-coded coverage maps to inform decisions about optimal monitor placement. Monitors were then deployed according to the guidance provided by the planning tool.
Triangulate Leak Locations
As pressure drops due to a leak, the cloud platform software analyzes data from the monitors to triangulate the source location. Triangulation is achieved when a transient event is detected using more than two sensors, each offering a precise time-data point. With an integrated GPS receiver recording the unit’s position, an algorithm is applied to the data, pinpointing the location and immediately alerting the utility. GUC deployed a total of 22 units throughout its network monitoring approximately 725 miles of pipe.
The combination of optimal monitor locations and triangulation analysis creates a smart network where pressure and acoustic data is analyzed in real time, enabling a rapid response to potential leaks and bursts to speed mitigation, while minimizing the need for continuous human monitoring.
The system also provides an “S3” severity score, a computed measure of pressure change severity over a specified time period. Significant changes result in a high S3 score, while small changes over the time period measured produce a lower score. A continuously stable pressure results in an S3 score of zero. Using S3 scoring, alerts to unusual pressure events are triggered, so information can be tracked, reviewed and acted on.
This data-driven approach has provided GUC with valuable insights to help inform network calming efforts. With greater understanding of pressure transient patterns, and the ability to identify the source of damaging pressure events, GUC has been able to make operational decisions to help improve performance and reduce wear and tear on critical network assets.
For example, by monitoring transients, GUC staff were able to identify where valves were closing too quickly and creating pressure waves. Armed with this insight, GUC staff mitigated the issue by changing to valves based on newer technology. This produced an immediate reduction in transients being pushed to the distribution network, which would otherwise stress the system, improving network performance and reliability.
By identifying potential problem areas, GUC has been able to lower its S3 scores, indicating a reduction in large transient events throughout the distribution network. This is expected to have a positive impact on the life span of critical components including water mains.
Improved network calming has also enabled GUC to achieve financial savings. Identifying and mitigating transient events proactively sooner reduces wear and tear on pumps, valves, and other assets, helping avoid costly repairs and supporting GUC in meeting its key performance indicator (KPI) targets for system losses. In addition, the data generated by the monitoring system enables GUC to provide justification for funding proactive pipeline replacements.
A Future Driven by Data
Based on its success to date, GUC is looking to make data-driven network monitoring a key element in its operational strategy. With a plan to adopt advanced metering infrastructure (AMI) also under consideration, GUC is looking toward a future where advanced technology and data analysis inform decisions that drive continuous improvement in service reliability, efficiency and environmental responsibility.
References
https://awwa.onlinelibrary.wiley.com/doi/full/10.1002/aws2.1179
https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=1173&context=mae_facpub