How energy and utility companies prevent outages and resolve problems with HPE in-memory computing

[David_Dichmann]

Discover how energy and utilities companies predict and prevent outages and resolve problems faster with HPE Superdome Flex in-memory computing solutions for SAP HANA.

As an energy and utilities organization, you are under constant price pressure to modernize, to better predict and to respond more efficiently to outages—while maintaining very competitive prices. Modern energy and utilities consumers expect online and real time resources with up‑to-date information on outages, restoration times and their own usage.

You also need to modernize production and distribution processes, as well as digitize management process to meet new regulations. What's more, you need better prediction tools to manage unexpected capacity growth and demand surges—and prepare for them and respond to them with greater efficiency. Modern equipment with sensor data generated from the Internet of Things (IoT) and other smart devices gives you massive volumes of information that can be used for predictive analysis for allocating supplies as well as preventing outages.

To help energy and utilities organizations succeed, you need to be able to analyze a tremendous amount of information from a huge number of sources. And you need to be able to quickly address, collect, and analyze all relevant data and use it to create timely insights. Performance of these data systems is not enough. You also require mission-critical solutions to ensure business continuity, as any downtime equals both lost revenues and customers.

The new era of in-memory databases like SAP® HANA® has allowed energy and utilities organizations worldwide to dramatically increase the speed at which data can be identified, gathered and analyzed. Innovative systems like the new HPE Superdome Flex feature large-scale in-memory computing by being able to have up to 32 processors and 48 TB memory—enough for even the most demanding SAP workloads, while also offering the highest levels of mission-critical availability to ensure the continuity of your energy or utilities business operations.

Use case: CenterPoint Energy leverage large-scale in-memory computing to improve outage response

For example, at CenterPoint Energy in Houston, Texas, selling and delivering electricity and natural gas for 140 years, they wanted to better predict and prevent power outages and improve customer satisfaction. For its five million customers, censors generate more than 240 million meter-readings daily, adding up to more than 5 PB of data. This is an 837% increase in sensor and meter reading data over the last five years. By using high-scale in-memory HPE systems with SAP HANA, CenterPoint Energy is able to get real-time analytics with a more reliable infrastructure. Analyzing the deep IoT sensor data in a timely manner help CenterPoint Energy predict and prevent power outages. 

By reducing the time to analyze data by at least 60x (from hours to seconds) CenterPoint Energy can now predict the purpose of calls within a 90% probability, reducing average call center wait time and allowing faster resolution of customer issues. Overall, CenterPoint Energy is able to improve customer satisfaction and call center efficiency, as well as better predict outage—while increasing customer satisfaction and improving efficiency.

Your energy and utilities organization can benefit significantly with large-scale in-memory computing such as the HPE Superdome Flex for SAP HANA. By creating new analysis methods that provide real-time information to decision makers far faster, you can predict, reduce and respond more efficiently to outages, provide your consumers with a better experience driving higher satisfaction and deliver essential services to meet regulatory compliance.