Power outages can be inconvenient, costly and – at their worst – dangerous.
Long-term outages can mean residential customers of utilities don’t have heat, cooling, light, refrigeration or other essential aspects of the modern home. For commercial and industrial customers, they can result in downtime, which costs most organizations around $100,000 per hour.
Outages can also cause utilities to lose customers and restoration costs can be extremely high – especially if the company isn't adequately prepared.
In addition to ensuring you’re ready for them, being able to predict outages could significantly reduce their impacts. Big data is helping utilities, companies and customers to do just that.
Intelligent outage prediction
Storms are a significant cause of outages. Vegetation coverage, contact with animals and the age of infrastructure are also factors. By analyzing these risks, utilities can predict where outages are likely to occur. Recent outage history can also help energy companies determine where risks are exceptionally high.
Visit Innovation Enterprise's Big Data Innovation Summit in Boston on September 11–12, 2018
Utilities can comb through this information manually, but doing so takes considerable amounts of time and energy – especially since the factors are continuously changing. Smart technologies can make this data analysis a faster, more efficient process.
Numerous utilities have started incorporating big data and smart analysis into their outage prevention plans.
In 2017, researchers from Texas A&M University developed one method of using data in this way. They created an intelligent model that can predict how vulnerable each of a utility’s assets is and generate a map showing where and when outages may occur.
The researchers said their method consists of three phases:
In a similar vein, people with emergency generators can have those forms of backup energy paired with smart tank monitoring services, which will automatically have their emergency fuel refilled when it gets too low.
Smarter weather forecasting
Energy companies have long used weather forecasts to predict potential issues. Today, though, they can customize weather data so it’s relevant to them. For example, knowing how many inches of snow an area will get is useful, but combining that knowledge with information on the density of the snow and the speed and direction of wind makes it more valuable.
The Weather Company has created a tool that uses machine learning to notify utilities of forthcoming weather events and give them the information they need. They can also use the system to run their own potential scenarios, so they can better develop response plans in advance.
Utilities also use smart technologies to collect their own data. Smart meters, for example, automatically inform the company of outages. Sensors attached to distribution infrastructure can also alert crews to damage.
The benefits of improved outage prediction
Better predictions of outages can significantly reduce their impacts or even prevent them. Having advance knowledge of where outages are most likely to occur allows companies to position crews and resources close to those places so they can restore power more quickly. It also helps them ensure they have enough resources to restore power after a large-scale incident.
Predicting outages may even enable utilities to prevent some outages entirely. If they can discover which areas are at risk due to old infrastructure or more vegetation, they can do the necessary work ahead of storms or other incidents to stop outages from occurring.
Preventing outages and mitigating their impacts is important because it eliminates or reduces the health and safety risks, as well as the economic damage they can cause.
Like in so many other sectors, big data and smart technologies are changing the way the electricity industry works. Using these technological resources can enable utilities to improve their prediction and prevention of outages, as well as their responses to them.