Severe weather continues to be a major thorn in the side of utility companies, and climate change has only increased the challenges in recent years. The resulting power outages have a devastating effect, shutting down schools and businesses and even slowing down emergency services. The subsequent cost to the economy has literally run into the hundreds of billions of dollars.
In response, you need to look at more than the weather forecast to develop power outage predictions and infer the impact of the severe weather on your customers and operations. With Storm Impact Analytics by DTN, you can turn forecasts into actionable data to improve power restoration efficiencies and raise your level of preparedness.
Power outage prediction
Power outages that result from catastrophic weather events are much more than an inconvenience. Being without power is something that your customers in the U.S. refuse to tolerate. Yet another issue to factor in is the increased scrutiny that utilities come under in the wake of such extreme weather events from regulatory and political bodies.
The ongoing threat of natural disasters, increasing customer expectations, and other factors combine to make power outage prediction a timely and necessary preparedness strategy.
For your post-storm recovery to be fast and efficient, your team needs to be adequately prepared. Don’t leave the nature and extent of the resources you allocate to your readiness and response to guesswork. You need to know as much as possible about the nuances of each potential severe weather event as far in advance as possible.
Knowing about severe weather events is vital if you are going to avoid the costly error of being over-prepared and the even greater cost of being under-prepared. If caught off guard, you will be facing the fallout from lengthy restoration times. You will also undoubtedly want to avoid the inefficiency of calling on mutual assistance to combat the impact of severe weather only to discover after the event that such costly measures were not necessary.
However, when you have a proper prediction model in place, you can allocate sufficient staffing and materials in readiness for the event. Properly allocating resources is the best possible scenario to minimize the impact on your facilities and distribution network.
How power outages can occur
The process of delivering electricity begins with its generation at power plants. After that, high voltage lines transmit electricity to the required location. Lastly, the distribution network delivers electricity to the end-user.
Delivering electricity to consumers involves many steps. If something goes wrong at any one of those transfer points and the equipment and materials are affected, a power outage can occur.
Severe weather causes a majority of power outages. The following few scenarios are just a small sample of the many ways that the effects of adverse weather can lead to power outages.
Several of the nation’s large power plants and substations are coastal. As sea levels rise, there is a risk of these facilities being affected by storm surges.
For example, as a hurricane approaches, it can cause the sea level to rise as much as 30 feet. Actionable tropical weather analytics are critical for coastal cities.
Higher air temperatures mean surface runoff from melting snow. This surface runoff results in vegetation becoming drier earlier, fueling wildfires. Thus, wildfires are not only a direct threat to transmission and distribution structures but also smoke and particulate pollution pose an even greater threat.
These particulates during a storm result in ionized air, creating an electrical path from the transmission line to the ground. Transmissions from line to ground may result in a power outage.
Another outage example occurs when power companies deliberately shut off the power supply. The purpose of these intentional outages is to limit the damage caused by power surges or electrical interruptions during a weather-related disaster.
Deliberate outages are also done as a precautionary measure. For example, during threats of wildfire, or very dry conditions, power is shut off to prevent the electricity from causing a spart and starting a fire.
Inadequate approaches to power outage prediction
Reliance on consulting weather forecasts and past experience to gauge the impact of weather events on your electric distribution network is not enough. Experienced employees will eventually retire, leaving an experience vacuum, and the effectiveness of consulting weather forecasts and meteorologists alone only goes so far.
Analysis of past severe weather events and their consequences usually employs rudimentary methods, and the results are unsatisfactory. Others have tried more advanced techniques, like regression analysis. However, these approaches also often prove too simplistic by failing to fit the complex data sets properly.
You need a more robust data source and a more sophisticated set of analytical tools to give you an understanding of the impact of potential damage. An insightful data set will allow you to allocate appropriate resources in the face of a severe weather event.
How accurate data helps utilities with power outage prediction
Is there a better option for the all-important need for power outage prediction? Yes, thanks to machine learning, artificial intelligence (AI), or neural network algorithms. This technology suits the utility damage prediction model well. The concept relies on AI mining data to identify patterns that allow for power outage prediction.
Every utility is completely different, from its design to its maintenance procedures, and weather events will uniquely impact each. The same weather event will also variously affect different areas within the same utility.
AI used in this context is technology at its best. The sophistication of AI can take all these complexities into account and intelligently learn about their contrasting reactions.
Utilities are now realizing that consulting weather forecasts and other data and AI learnings results in anticipating outage incidents before the storm has an impact. These predicted outages allow you to make faster and better decisions on your power outage restoration strategy.
Using AI can be a game-changer for utility companies, providing a supporting basis for your preparation decisions before the storm hits. With today’s rapidly-changing climate, you need to have the ability to accurately anticipate the impact of severe weather on your customers and operations. With Storm Impact Analytics by DTN, you can turn forecasts into actionable insights to improve power restoration efficiencies and raise your level of preparedness.