Dominion Energy is a leader in the clean energy transition, providing reliable, affordable power to nearly 7 million US customers. As part of their efforts to accelerate net-zero, the team was searching for a way to make sustainability data from across their grid available to customers in real-time. We worked with them to make it happen.

The team at Dominion Energy knew that their grid data could become a powerful competitive advantage. As consumers increasingly choose their providers based on their environmental footprint, having the ability to share energy source and performance information from across the network with stakeholders could help them stand out in a crowded field.

They came to us looking for cloud-based technology that would let them capture this data and share it easily and securely. They needed strong, scalable systems that could handle high volumes accurately and quickly — while ensuring cybersecurity.

We helped the team deploy AVEVA™ Data Hub and AVEVA™ PI System. Now, data from across the network can be captured in real-time and easily shared across the organization and with key stakeholders.

This, in turn, allows Dominion’s customers to prove their own net-zero commitments to investors and environmental, social and governance (ESG) auditors.

This data is now a crucial selling point for Dominion, encouraging potential customers to choose their services over other providers.

As an added benefit, AVEVA™ PI System has helped Dominion bring their vision of an autonomous data-driven culture to life.

Being able to rapidly pull different data sources and insights together has given teams the ability to quickly diagnose and return power-generation units to service. These technologies have also opened up monitoring of power station performance and early detection of performance issues and controllable losses. Today, Dominion continues to build on the system as they pursue their goal of reaching net-zero.

Arizona Public Service (APS) provides the state’s inhabitants with essential utilities. Today, they’re responsible for delivering reliable electricity to 2.7 million Arizonians –
a vital service in a region known for its long, hot summers.

With some 50% of its 6,000-strong workforce approaching retirement, the team knew training new operators had to be a key part of its operational excellence strategy. But with teammates spread far and wide across the state, they needed a way to deliver world-class training remotely.

We partnered with APS to introduce cloud-based training using AVEVA™ Operator Training Simulator on our industrial cloud platform, AVEVA™ Connect. Using generic power plant models, the team could learn processes and procedures across plants, regardless of how they were configured.

Now, operators can train for all scenarios from their home plant, replacing the usual three days away from their role. With an effective, continuous training strategy, APS can ensure operational excellence without heavy spending – keeping electricity affordable for their customers and driving significant sustainability benefits from lower travel and more intuitive training systems.

AGL is one of the nation’s leading power providers, managing one-third of the energy generated for Australia’s eastern seaboard, where the majority of Australians live. Growth has accelerated in recent years, fueled by acquisitions and the adoption of renewables including thermal, wind, and solar power.

But visibility had lagged behind growth. When David Bartolo joined as AGL’s head of asset performance, the company was effectively data blind. To change that, he and his team soon settled on the solution: AVEVA™ PI System.

With the new system in place, anyone could access real-time data — empowering them to make changes that could benefit the bottom line. After a single day of training, people began creating new and innovative uses for the system. One engineer built a display to see the aggregate view of how two solar farm sites were performing. Chemists set alarms to add years to the lives of boiler-cycle assets. And other users built screens to monitor generator temperatures.

A non-engineer built a screen to monitor trends in small hydro units located 700 kilometers away. Immediately, he could see why his machines were tripping and remotely directed on-site subcontractors to the source of the problem. In just three months, the availability of those units rose by 7%.

AGL chose to move beyond real-time awareness to predictive monitoring with the launch of its Operational Diagnostics Center. Building on the foundation provided by AVEVA™ PI System, the team built 2,700 models that monitor 45,000 critical data points every five minutes, checking incoming data against historical data. When correlations vary, the team knows that something is wrong.

In just three years, the new system saved A$18.7m in reduced forced outages and optimized maintenance. The AVEVA™ PI System alarms even caught and avoided a catastrophic failure in a 560 MW hydrogen-cooled stator — preventing an outage that would have cost an estimated A$50-70m.

Today, AVEVA™ PI System is at the center of AGL’s resilience, efficiency and sustainability strategies, playing a crucial role in two new initiatives. The first, a thermodynamic performance-optimization system, aims to reduce fuel consumption by 0.5% and reduce CO² emissions — translating to savings of millions of dollars per year. The second, a wind-yield-optimization system, targets a one to two percent increased yield in AGL’s wind portfolio.

With 60 plants in seven states, Duke Energy is responsible for providing reliable, affordable electricity to a population of 7.2m. The team’s ambitious sustainability vision is founded on their digital operating model.

The Monitoring & Diagnostics team had been using operational data management combined with predictive analytics at small scale for more than a decade. But, after a failure caused four months of lost generation the team came to AVEVA to reshape the program, infusing AI to predict and prevent future incidents and accelerate their sustainability vision.

The new M&D Center uses several tools, including AVEVA™ PI System operational data management and AVEVA’s predictive analytics capability to observe assets, analyze performance and catch impending problems. With 11,000 models and over 500,000 data points, just five analysts can monitor over 87% of Duke’s portfolio.

Strategically placed IIoT sensors produce data that is used by AVEVA™ Predictive Analytics AI-infused software to detect equipment failure before it happens – driving better performance and improving uptime.

The combination of market-leading operational data management with world-class analytics has already produced significant cost and sustainability benefits, delivering savings of over $34 million with a single early catch event in 2016. Now, the team is focused on further improving their sensor and instrumentation infrastructure, so they can better supply their community with affordable, reliable, efficiently produced power.