Within the utility industry, making sure customers (that would be you and I) have power at our houses, businesses, etc. is very important to the utilities themselves, but obviously to us as well. Kathy Ball, who now works for SAS but also has 20 years of utility expertise, teamed up with a couple of SAS co-workers, Albert Hopping and Jim Duarte along with Mark Konya, a customer from Ameren Missouri, decided to tackle this topic.
The top 3 ways SAS advanced analytics can help minimize storm related power outages and restore power faster fall into three categories:
- Before the Storm
- During the Storm
- After the Storm
Before the Storm
Advanced analytics can be used prior to the storm in many ways. One way is to help predict the storm's impact. Let's say there are 6000 transformers in the projected path of a storm, advanced analytics can help identify the 4000 transformers that will most likely be impacted. They can also predict network impact, allocate the proper mix of additional staff to be deployed and even to optimize crew staging areas.
During the Storm
During the storm advanced analytics can be applied to improve real-time communication with staff, customers, as well as regulators. They can help identify number of outages, concentration of outages, types of outages, prioritize power restoration efforts and even incorporate social media related information to complement their existing outage management system (OMS) that could help identify more outages or more dangerous situations needing faster responses.
After the Storm
Finally, after the storm has passed advanced analytics can continue to improve communications with staff, customers, and regulators by using real-time information to improve return-to-service time accuracy and to dynamically schedule crews to reduce time customers are without power. As a matter of fact, we saw a 14 percent improvement in restoring power using advanced analytics alone, but that wasn't enough. Kathy helped to develop a new patent-pending algorithm to improve the routing of restoration crews. By combining the "normal" SAS advanced analytics with this new technique we saw a 22 percent improvement in the time to restore power.
For more details related to this topic please see Kathy and Mark's SAS Global forum paper: Weathering the Storm: Using Predictive Analytics to Minimize Utility Outages and join the SAS Utility Users Group (SUUG) and the SUUG Linkedin group.