Asset & Grid Performance
Predict and visualize asset performance. Be a reliability champion.
How SAS® Enables Superior Asset & Grid Performance
Optimized management of the distribution grid with data-driven analytics is no longer a luxury. The growth of DERs, the emergence of prosumers and the resulting grid management complexities require deeper data-driven insights to maintain and improve asset and system reliability. Our utility analytics solutions provide a broad scope of analytic and predictive capabilities to capitalize on IoT investments on the grid and give you better results.
Asset reliability analytics
Reduce the number of unplanned outages and optimize maintenance schedules for grid and renewable energy assets.
Optimal EV & DER integration
Forecast specific needs and time frames to leverage the right distributed energy resource at the right time, place and cost.
Shrink outage duration by employing analytics before, during and after a storm to improve the effectiveness of your preparation and restoration efforts.
Smart meter analytics
Leverage the data-rich smart meter environment to gain customer insights and model grid and asset behavior to improve reliability.
Explore and analyze data from diverse connected grid assets through robust dashboards and interactive maps.
Integrate data from your historian, ERP and field notes to build predictive models for asset maintenance.
Why do utilities choose SAS® for asset & grid performance?
With utility analytics from SAS, you can capture and analyze data in any format from any source to gain insights and make better maintenance decisions. Know the best corrective actions to take in each situation – and when to take them. Maximize asset performance and save time and expenses by using monitoring, predictive models and alerts issued at predefined thresholds.
Accurately predict potential problems
Integrated data – from sensors, inspections, maintenance, weather, inventory, history and warranties – combines with root-cause analysis to reveal the drivers for performance issues from hundreds or thousands of measures and conditions.
Optimize maintenance plan impacts
Get ahead of the vegetation management challenges. Build predictive maintenance schedules. Predict vulnerable assets and stage resources prior to adverse events in order to minimize the impact to customers.
Manage outages before they manage you
From momentary to event-driven outages, gain insights to prevent equipment failures, speed restoration and improve customer satisfaction.
Boost uptime, performance & productivity
Get alerts so maintenance teams can make pending repairs as part of regularly scheduled maintenance. And determine the most cost-effective way to replace degrading assets.
Reduce maintenance costs & risk of revenue loss
Advanced analytics lengthens maintenance cycles without jeopardizing uptime or risking failures. Rapidly diagnose and repair issues with near-real-time insight into performance.
How is the largest distribution operator in Belgium modernizing its infrastructure to accommodate renewable energy sources and better managing a new smart grid to meet consumer demands?
SAS is helping Eandis better visualize the volumes of grid data available for analysis, enabling the company to:
- Decrease time spent measuring the in-feed data from transmission stations supplying power – a project that once took three to six months can now be completed within minutes.
- Plan for efficient use of government funds for the smart grid.
- Pose what-if questions on the data and explore numerous business scenarios.
- Make sound business decisions much faster than before.
How does one of the largest public power utilities in the US – in one of the fastest growing regions – minimize generator downtime and anticipate future demands on the power grid?
SAS is helping Salt River Project in the Arizona Valley desert, which reaches highs that can exceed 100 degrees Fahrenheit nearly 100 days a year:
- Ensure an accurate schedule for preventive maintenance to prevent unplanned generator downtime by analyzing hundreds of thousands of machine sensor data points to predict when combustion turbines that generate power will require maintenance.
- Improve compliance with warranties for critical assets.
- Balance planned downtime across dozens of power plants.
- Predict available energy supply and demand over a five-year period, enabling traders to more effectively make up shortfalls or sell excess energy.
- Help traders lock in better prices by predicting when they’ll need to purchase power in advance.
Related Products & Solutions
- Advanced Analytics for IoT from SASAnalytics for IoT is a powerful platform with embedded AI and industry-leading streaming capabilities that enables you to drive innovation, efficiencies and results. SAS LU
- Data Management SoftwareGo beyond managing your data to unleashing its full potential.
- SAS/ACCESS® SoftwareRead, write and update data regardless of its native database or platform.
- SAS® Asset Performance AnalyticsHarness M2M and sensor data to boost uptime, performance and productivity while lowering maintenance costs and reducing your risk of revenue loss.
- SAS® Event Stream ProcessingGet immediate analytic insights from real-time big data streaming into your organization.
- SAS® Visual AnalyticsVisually explore all data, discover new patterns and publish reports to the web and mobile devices.
- SAS® Visual Data Mining and Machine LearningSolve your most complex problems faster with a single, integrated in-memory environment.