AGL Energy is an integrated energy company that produces energy from thermal power, natural gas, wind power, hydroelectricity, solar energy, gas storage, coal and battery storage. In recent years, the company has seen massive growth. In just nine years, AGL’s supply capacity grew from 300 megawatts of electricity generation in 2012 to over 10,000 megawatts in 2021. But through acquisition growth and increased renewable adoption, the company has also seen massive growth in its data. Using AVEVA™ PI System™, AGL centralized its time-series data from every generation site, so everyone across the organization has secure access to near-real-time data. AGL effectively built a data-driven culture where everyone is empowered to make changes that can improve many aspects of business performance, and ultimately, their customers’ experience.
“What came along was a solution that really fit what we needed and that was [AVEVA PI System]. It could connect to any one of our controllers. We could harvest every piece of real-time data and make it available to every person at AGL.”
–David Bartolo, Former Head of Asset Intelligence, AGL
Goals
- Give teams across the organization access to real-time data
- Expand from real-time awareness to predictive modeling
- Share power generation data securely with partners, optimizing usage across distributed power generation sites
Challenges
- Company growth presented challenges to managing data systems
- Needed high-resolution data to optimize operational performance, especially with aging infrastructure
- Needed to consolidate scattered and isolated data, with multiple SCADA technologies in play
Solutions
- Deployed AVEVA PI System to centralize data and deliver situational awareness of its operational portfolio
- Used CONNECT data services to securely share wind and solar generation data in the cloud with authorized partners in remote locations to gain insights into its power generation sites
Results
- Saved approximately 6-10 million AUD per year in avoided failures (via Advanced Pattern Recognition diagnostics).
- Reduce data capture time from 10 mins to 1 sec across 200 wind turbines, helping optimize performance improvements and justify site-wide turbine upgrade.
- Benefited from upgrade ROI payback of 4 months and enhanced efficiency performance as a result.
- Real-time wind power generation data from turbines is shared securely with university partners to uncover further academic insights.
