As energy prices across the world rise to unprecedented levels and the cost of living crisis continues to bite, energy independence, fuelled by renewables, is more critical than ever. Big data and new tech can make this a reality.

  • Next-Generation Weather Detection Tech Can Make Renewable Energy More Reliable

  • Benchmark Is Producing Revolutionary Weather Forecast Tech Using The Internet Of Things

  • CEO Carlos Gaitan Is Leading The Charge In Revolutionary Renewable Energy

In a world where 29% of the world’s energy comes from some form of renewable energy, it’s clear we are finally moving in the right direction in trying to stem the climate crisis.

However, renewable energy has its limits. Hydropower, wind and solar, the top three renewable energy sources are dependent on weather patterns. Solar panels are useless on a grey day, hydropower is made redundant in a drought, and wind turbines can only generate energy if they are spinning in the wind.

In turn, we can only predict how much energy each of these sources will produce if we can predict the weather patterns. The reality of relying entirely on renewable energy is that our electricity supplies would be unpredictable. One solution is to use weather forecasts to plan our renewable energy consumption.

The Future Of Forecasts

However, on a seven-day forecast, a traditional weather forecast is only 80% accurate in general and this reduces to under 50% for a ten-day forecast.

This is remarkable when we have the technology to predict astronomical events thousands of years in the future.

One company trying to change this is Benchmark Labs. They have created a revolutionary forecasting system to help predict local weather using artificial intelligence and machine learning.

Most weather forecasts are carried out by public bodies and apply to a wide area. Benchmark Labs uses micro-forecasts that relate to a local area that takes into account latitude, longitude, and elevation. Their technology also allows users to compare public data with the private, more local data compiled by Benchmark.

Every forecast is compared with real-live data and added to a computer database which analyses the results and readjusts its calculations accordingly using machine learning.

Some of the environmental variables Benchmark Labs forecasts include relative humidity, surface temperature, wind speed, precipitation, evapotranspiration, and a variety of fire risk indices such as the KBDI Index (Keetch-Byram Drought Index).

Benchmark Labs’s groundbreaking tech is supported by a range of high-profile partners including NASA, Techstars, NSF, Nextview, and San Diego Regional EDC and World Trade Center.

Economic Benefits

Benchmark Labs’s pitch is economic as well as purely environmentalist. By generating much more accurate forecasts, Benchmark Labs’s tech can be used to estimate the power generation of wind turbines and solar farms, to forecast forest fires’ inducing conditions, and lower the operating costs over time.

In their words, this new technology allows users and insurance companies the ability ‘to contextualize today’s weather more effectively, thus allowing better management & pricing decisions.’

This couldn’t be more important at a time when non-renewable energy prices across the world are rising to record highs as coal and oil shortages bite. Running parallel to this is the cost of living crisis as inflation soars to a 40 year high in the U.S and countries struggle with the economic impact of COVID-19.

Benchmark Labs
Benchmark Labs Benchmark Labs

Science, Data and Weather

Benchmark Labs is the brainchild of Carlos Gaitan. Gaitan has combined his love of technology with a passion for weather science. He has successfully married those two interests into a successful business.

‘I want to help bridge the gap between science, engineering and the society's interest,’ Gaitain explains, ‘I particularly enjoy using novel data science techniques in conjunction with machine learning algorithms to extract knowledge from big datasets, like global climate models, weather station networks and gridded observation-based products.’

Gaitan’s career began after securing a PhD in Atmospheric Science from the University of British Colombia in 2012. Straight after he went on to join the Geophysical Fluid Dynamics Laboratory at Princeton, NJ and the Committee on Artificial Intelligence Applications to Environmental Science at the American Meteorological Society.

He was the Vice President of Machine Learning for Weather Forecasting at Arable Labs where he was responsible for using Hydro-informatics and state-of-the-art Machine Learning techniques to improve forecasting capabilities at different time scales. He built on this work as Chief Climate Scientist at Stanford-incubated startup by researching Deep Neural Networks models and how they can be applied to hydrological forecasting, and most recently worked alongside NASA scientists to forecast the impact of COVID restrictions on forest fires .

It’s clear we are living in unprecedented times and it’s easy to feel despair at the scale of the complex problems created by climate change and COVID. However, companies like Benchmark are leading lights when it comes to renewable energy and help us see a brighter future.

Gaitan's innovative use of big data, machine learning, and A.I have the ability to disrupt the renewable energy sector for the better.