Superstorm Sandy provided the US energy industry with a powerful wake-up call as to the steps that need to be taken to reduce vulnerabilities in the nation’s energy grid.
Weather patterns from the past 50 years no longer serve as reliable data sets for predicting the likelihood for or intensity of storms, according to a blog post by consultant Christine Hertzog.
In fact, Sandy was so powerful that earthquake sensors as far away as the Pacific Northwest detected the storm’s energy as it surged up the East Coast.
Yet by the time Sandy had passed the Northeast US, power outage prediction models that were supported by the use of big data analytics turned out to be fairly accurate.
A team of researchers at Johns Hopkins and Texas A&M universities fed weather forecasts along with real-time and historical hurricane data into a computer model to predict the total number of power outages that would result from Sandy.
The team’s final estimate regarding the total number of people expected to lose power was between eight million and 10 million. The U.S. Department of Energy’s peak outage total was approximately 8.5 million customers.
Experts believe there’s little that power companies can do to prevent 100 mile-per-hour winds from snapping utility poles and causing other types of damage to above-ground infrastructure. But there are steps that energy firms can take to assess the overall health of the electric grid and predict which components are most likely to be affected by a major storm.
Doing so can help utilities prepare more effectively for allocating crews to areas where damage is most likely to occur as well as to stock and distribute replacement equipment in order to improve outage restoration times.
For instance, power companies can apply analytics to identify locations where they should trim trees or maintain utility poles under what industry experts refer to as “storm hardening measures.”
It’s true that efforts to bury power lines underground for long distances may be cost prohibitive. But utility executives can also use analytics to examine the areas of the power grid where the costs of such efforts may outweigh the costs to repair or replace above-ground equipment over time.
Decision makers at power companies can also evaluate the overall costs of such projects, the likely sources of funding, and the potential economic benefits that would result from these investments.
Meanwhile, as the industry continues to expand its investment in smart grid technologies, analytics can help to decipher the role that smart grid technologies, such as smart meters, can play in the restoration of power once an outage has occurred.
For instance, if a home or neighborhood suffers a power outage, smart meters that provide two-way communications between a home or business and a power company can provide the power company with more detailed information about the nature of an outage and help speed restoration efforts.
Next Steps:
- Subscribe to our blog to stay up to date on the latest insights and trends in data analysis and the energy industry.
