TC Energy
TC Energy transforms its pipeline management with AVEVA solutions
TC Energy wanted to seize revenue-generation and cost-reduction opportunities across its pipelines, while its scenario planning process remained complex and time-consuming. The operator needed to extract faster, more relevant insights from its operational data and leverage machine learning models hosted on AWS to power predictive dashboards. The group combined AVEVA Enterprise Pipeline Management, AVEVA PI System and AVEVA Enterprise SCADA, integrated with AI and machine learning models, as part of an advanced industrial monitoring approach. Teams can now evaluate millions of potential scenarios, receive recommendations and make accurate forecasts directly from their interfaces. The benefits speak for themselves: $8 million in demonstrated value from strategic dashboards, and a once-complex planning process transformed into a real-time, one-page operational summary. New team members make confident decisions faster, supporting overall pipeline performance.
FAQ
How does AVEVA Enterprise Pipeline Management generate $8M in value at TC Energy?
TC Energy combined AVEVA Enterprise Pipeline Management, PI System and Enterprise SCADA with AI/ML models hosted on AWS. This integration makes it possible to evaluate millions of potential scenarios and produce real-time recommendations. The benefits are concrete: $8 million in value demonstrated through strategic dashboards, and a once-complex planning process transformed into a one-page operational summary. New controllers make confident decisions faster, supporting overall pipeline performance.
How does AVEVA enable TC Energy to evaluate millions of pipeline scenarios?
The integration of AVEVA Enterprise Pipeline Management, PI System and AWS ML models enables TC Energy to evaluate a large number of operational scenarios in parallel (pressures, flow rates, sequencing, batches). This simulation power, impossible to achieve manually, turns the planning process into a structured, data-driven activity. The recommendations delivered to operators are precise, contextualized and immediately actionable. It is a major step forward for long-distance pipelines, where every optimization quickly adds up to millions of dollars.
Why is capturing the knowledge of senior controllers strategic at TC Energy?
Senior controllers of a pipeline network accumulate decades of experience on the real-world behavior of assets, complex interactions and operational best practices. TC Energy uses AVEVA Enterprise Pipeline Management and PI System to capture this knowledge and integrate it into recommendation models. New controllers thus benefit from structured support that speeds up their autonomy and standardizes decisions. This is a major strategic issue in a context of workforce turnover and ever-increasing operational complexity.
What role does AWS integration play in predictive pipeline maintenance?
AVEVA PI System (particularly PI Asset Framework) integrates natively with AWS to run machine learning models on operational data at scale. For TC Energy, this cloud architecture extends the existing AVEVA Enterprise Pipeline Management solution and feeds advanced predictive dashboards. The massive volumes of pipeline data thus become an exploitable source of value, turning operational planning into a measurable and lasting competitive advantage.
How can a complex planning process be turned into a one-page operational summary?
Previously, scenario planning at TC Energy tied up multidisciplinary teams for long periods. AVEVA Enterprise Pipeline Management combined with ML models now condenses the analysis into a one-page operational summary accessible in real time. This concentration of information dramatically speeds up decision-making, frees teams for higher-value analysis and makes best practices more accessible to newcomers. It is an excellent example of how AI augments people rather than replacing them.