SAS helps to minimize downtime and forecast power grid demand
The electric power grid is more distributed than ever, with energy both generated and used by diverse sources ranging from solar panels to electric vehicles. The resulting complexity of the grid challenges its overall reliability.To manage this complexity and improve reliability, utilities are deploying sensors to give real-time data about location, performance, weather and other factors affecting their power generation and distribution assets. Applying analytics to data streamed from these connected devices – part of the Internet of Things, or IoT – provides crucial information needed to predict asset and overall grid performance, and prevent outages of critical equipment.
At DistribuTECH, SAS and OSIsoft are showcasing how predictive analytics from SAS and infrastructure-management software from OSIsoft can transform asset data from IoT connected devices into an optimized grid. Salt River Project (SRP), a public power company serving the Phoenix metropolitan area, relies on this integration between SAS and OSIsoft.
For a third of the year, the Arizona Valley desert is a blistering 100 degrees or more. SRP understands that demand on the power grid during these scorching days is as high as the mercury. To help customers stay cool, SRP uses SAS Analytics and the PI System software from OSIsoft to chart the future of asset performance and its impact on grid reliability.
Looking to the future is a big piece of SRP’s commitment to its customers. Driven by powerful SAS Analytics applied to IoT data, the utility can meet customer demand, optimize system performance and minimize downtime required for maintenance on connected equipment. For example, the utility uses SAS to analyze data from hundreds of thousands of machine sensors to predict when combustion turbines will require maintenance.
“Reliability is critical for our customers and our business,” said Steve Petruso, Senior Software Developer in SRP’s Supply and Trading Group. “SAS powers our ability to forecast, plan and update in real time, helping Salt River Project keep the lights on for our customers, and the grid reliable whether the temperature is 75 or 105 degrees in Phoenix.”
SAS Analytics also allows SRP to use data captured in the PI System to forecast available power supply and demand over the next five years so it can accurately buy power to make up shortfalls or sell excess energy.As the Internet of Things becomes prevalent in the energy industry, a key challenge facing many utilities is the integration of streaming and business data from connected equipment. The growing amount of data generated from sensors on monitoring equipment is plentiful, but it is only one piece of the puzzle. Sensor data, paired with data-driven analytics helps utilities like SRP make timely, auditable improvements to performance.
SAS has collaborated with OSIsoft, a leading manufacturer of software for real-time data infrastructure solutions, to bring sensor-based data together with other contextual data sources to help make faster, better decisions about equipment maintenance.
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