By Doug Robinson, CEO, LGCY Power
Go green. Climate change. Sustainability now. These are all growing chants for change in how we work, shop and live. Americans are in an energy renaissance, desiring to replace fossil fuel and natural gas resources with green energy to sustain our homes.
In 2021, the conversation got real. At the height of a cold winter snap, all eyes were fixed on Texas, as a dramatic power grid failure left millions of Texans freezing and without power. The crisis drove home many lessons, not least of which was that when the fundamental needs of a home — such as heat and power — are challenged by unanticipated changes, it’s time to explore alternative energy options. And green energy is on people’s minds.
Pew Research shows almost 70% of Americans believe that the country should prioritize developing energy sources like solar and wind rather than expand oil, coal and natural gas production. However, that same study found only 31% of Americans support phasing out of oil, coal and natural gas consumption entirely. Instead, 67% of those surveyed believe the country should use a mix of fossil fuels, wind, water and solar energy sources.
Americans want alternative energy. For example, a recent Forbes survey found that around half of homeowners plan to install solar panels in the future. But they also want to be sure the light turns on every time they flip the switch and their morning shower is hot.
As part of the solar energy industry, you are where customers will turn with questions, not just concerning the investment but the overall value of installing solar energy in their homes. Solar energy is an exciting step forward, but it’s not without limitations. It’s as unpredictable as the weather, and limited storage can create barriers to providing consistent power. How, then, can you promote solar energy as a long-term solution?
More and more, leaders in renewable energy are turning to artificial intelligence (AI) technology for predictable forecasting models.
“Developing a reliable algorithm that can minimize the errors associated with forecasting the near-future PV power generation is extremely beneficial for efficiently integrating variable energy resources (VER) into the grid. PV power forecasting can play a key role in tackling these challenges,” according to experts in the Department of Industrial, Manufacturing and Systems Engineering at the University of Texas at El Paso.
As a form of machine learning, AI analyzes data to track mathematical patterns based on variables to “predict” outcomes — or algorithms. AI-based supply-and-demand forecasting is the same, whether it’s a customer relying on solar panels and a generator as their sole energy source or a city evaluating collective energy sources to regulate production via a power grid. The more data provided, the more accurate the algorithms. And that information ensures consistent power access for homeowners using renewable energy while improving large-scale infrastructure conditions for issues like grid maintenance preparation and better optimization among energy sources.
“Artificial intelligence can collect and use data to coordinate the entire energy system from generation, transmission and energy consumption,” wrote Behzad Benam, CEO and founder at Safeline. “This intelligent coordination improves the system’s performance based on the user’s repeated consumption pattern.”
If you intend for your solar energy solution to provide for your customers in the long term, AI is the key. Here’s how AI technology uses human variables, meteorological data and observational data to improve energy forecasting.
Data gets personal
It’s not rocket science to understand that more customers using solar energy to supplement power contribute more power to a city’s grid, which helps drive down costs since the power grid can use free renewable energy before turning to fossil fuels.
Analyzing meteorological data and customers’ energy demand is strategic to maintain consistent energy supplies and to help determine lower energy output rates, which assist in scheduling grid maintenance.
Data watches the weather, too
Albeit based mainly on history, seasons and a little professional instinct, AI-based forecasting relies on good old-fashioned weather patterns to coordinate energy sources. But the value of weather forecasting expands beyond efficient power grids. Scientists have used AI-based algorithms to predict dramatic global and potentially catastrophic weather patterns, and some of the world’s largest supercomputers are devoted to weather predictions.
“Artificial intelligence, in theory, can deliver on-par forecasts with less computing,” according to Mark Bergen, who writes about the impact AI forecasting has on preparing underdeveloped countries for extreme weather. “Early research has shown progress in forecasting rainfall and ‘nowcasting,’ predicting the weather over the next hour or two.”
This technology, with its ability to pinpoint extreme weather to the day — even the hour — has a profound impact on preparing a city’s power grid with needed resources to ensure customers have constant access to power.
Data goes mobile
Sometimes, the best data is based on what you can see. And an effective tool for collecting observational data — an important factor in energy forecasting — is drones.
“Drones already play a key role in solar panel inspections, when paired with machine vision tools,” writes Peter Kudlacek, CEO at Apro Software. “That’s because they are able to collect data at least 50-times faster than manual methods while improving the safety of operations.”
According to Kudlacek, drones can help us identify manufacturing defects, cracks and other issues by collecting data through unique thermal cameras.
“This information is then analyzed by AI-based systems to assess the impact of the problem,” he said. Over time, as more targeted data is collected, the accuracy of these algorithms will improve. The result is a reliable and efficient tool that ensures your customers get the most value from their investment.
As the world moves forward with renewable energy initiatives, the methods to leverage valuable energy sources as we transition to others are as important as the energy source itself. The pathway to designing affordable and practical long-term solutions has its barriers — but AI technology is quickly emerging as a strategic forecasting asset to coordinate and optimize precious energy resources while protecting those who rely on them.
Doug Robinson is CEO of residential solar contractor LGCY Power.