Asset & Grid Performance
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.
Storm analytics
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.
Performance visualization
Explore and analyze data from diverse connected grid assets through robust dashboards and interactive maps.
Predictive maintenance
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.
Customer Success
Look Who's Working Smarter With SAS®
Minimizing generator downtime & anticipating future demands on the grid
Salt River Project (SRP) uses SAS to prevent unplanned downtime by accurately determining when combustion turbines are running in order to schedule required maintenance. SAS also helps SRP predict power supply and demand, using a variety of data – e.g., weather, supply, demand and outage – to accurately purchase energy to meet customer demand or sell excess power to keep costs in line.
Related Products & Solutions
- Data Management透過流暢的資料連線能力、強化的轉換功能、強大的治理能力，增強您的 AI 旅程。
- SAS® Analytics for IoTDrive innovation, efficiencies and results by putting IoT analytics in users' hands – from predictive maintenance at scale to superior process optimization and quality, flood prediction and preparedness, energy cost optimization and beyond.
- 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 Processing使用機器學習和串流資料分析，在邊緣發掘洞察，並在雲端中制定即時明智的決策。
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