Deterministic weather forecasts have their place, but probabilistic forecasts are the clear choice for alternative energy companies that take the weather seriously and need long-term data.

Manage Costs and Risks With Long-Range Probabilistic Weather Forecasts

Ken Carrier | StormGeo

 

For any energy company, knowing what the weather will be in advance can mean the difference between a massive power outage and business as usual. In the alternative energy field, understanding weather patterns is even more important.

A long-term forecast can help companies get a better idea of when wind or solar energy demands will be at their highest, predict energy trading peaks, and manage risk at a much more granular level.

But weather forecasts can only help if they’re serving up the type of information energy companies can actually use. And because most general weather services are meant to cater to the needs of the public, they often come up short for utility companies.

For alternative energy companies, the deterministic approach of a traditional forecast may not always be the way to go. Instead, energy providers should look to a probabilistic point of view if they really want to make the most out of the weather.

 

Why There’s More Certainty in Probability

A deterministic forecast is essentially a prediction. Given specific weather patterns, meteorologists present their best idea of what the weather will be like. In the short term (i.e., within one or two days), this works well. Most weather services have enough certainty by then to make an accurate prediction.

But in the long term, this attempt to determine the future begins to fall apart. And the long term is where energy companies should be looking. A couple days’ notice is hardly enough time to prepare for anything.

Probability forecasts, on the other hand, present a range of possible outcomes alongside the percentage of likelihood for each. In this way, weather forecasts become more customizable and can be acted upon in a variety of ways.

At StormGeo, we combine long-range computer model data with past analog seasons that best mirror today’s pressure patterns to project weather for the coming months. With much of our in-house data done by hand, our unique forecast style could provide the additional information utilities need to make critical decisions.

 

Make the Most of Probabilistic Weather Forecasts

Energy companies that truly want to take advantage of the full potential of weather forecasts should stick with probabilistic forecasts almost exclusively.

 

1. Don’t be satisfied with the status quo. It may seem like the weather prediction system you’re using is doing everything you need, but you might be missing out on significantly more precise tools that can give you a level of granular control that you never thought was possible. Not all weather forecasts are created equally. The more information you have to work with, the more prepared you can be.

For example, StormGeo uses high-resolution project models to help offshore wind farms pinpoint expected production and exact metocean characteristics in the farm area. This helps the farm minimize project risks and avoid costly delays stemming from weather downtime.

 

2. Keep it in-house. Outsourcing weather predictions to an outfit such as AccuWeather or WeatherBELL might seem like a cost-saving measure, but the data they provide may end up losing you money.

These types of services tend to err on the side of caution because their ultimate goal is to make sure the public is prepared for the worst possibility (which is why deterministic predictions are often used more than more detailed probabilities). While this helps keep people safe, it may feel a lot like “the weather service that cried wolf” for utility companies looking for efficient ways to prepare.

 

3. Be proactive. It never pays to be overly cautious, but that doesn’t mean to wait for disaster to strike and deal with the fallout. A proactive approach is vital not only to prevent prolonged downtime, but also to mitigate exposure to weather-related financial loss.

As more energy companies have their feet held to the fire on risk management, a take-charge approach can help appease regulators and shareholders while saving you money and time.

A CEO of a top global renewable energy company recently asked StormGeo about widespread negative wind bias at several sites in late 2014 and early 2015. Our analysis not only uncovered the reasons for this loss of power, but it also revealed what to expect going into 2017. That information, in turn, helped the company’s leadership forecast power needs and ready its response to potential outages.

Deterministic weather forecasts have their place, but probabilistic forecasts are the clear choice for alternative energy companies that take the weather seriously and need long-term data. Make sure you’re getting the best information from a source that has your industry in mind, and you’ll find yourself saving money and getting the most out of your energy source.

 

About Ken Carrier
Ken Carrier, a U.S. Marine Corps veteran and self-proclaimed “weather nut,” is the electric utilities industry expert at StormGeo. Ken is a driving force in the integration of several of StormGeo’s proprietary tools, such as outage prediction and advanced lightning modeling. Connect with StormGeo on Twitter.

 
 

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