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By Doug Robinson, CEO, LGCY Power

Go green. Climate change. Sustainability today. These are all growing chants for change in how we work, shop and live. Americans are in an energy transition, looking to replace fossil fuel and natural gas resources with green energy to power our homes.

In 2021, the conversation becomes reality. At the height of a cold winter, all eyes are on Texas, as a severe power grid failure has left millions of Texans frozen and without power. The crisis brings home many lessons, especially when the basic needs of a home – such as heat and power – are challenged by unexpected changes, it is time to explore alternative energy options. And green energy is on people’s minds.

Pew Research shows that almost 70% of Americans believe that the country should prioritize the development of energy sources such as solar and wind rather than expanding the production of oil, coal and natural gas. However, the same study found that only 31% of Americans support a complete cessation of oil, coal and natural gas consumption. However, 67% of those surveyed believe that 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 nearly half of homeowners plan to install solar panels in the future. But they also want to make sure the light turns on every time they flick the switch and their shower is hot in the morning.

As part of the solar energy industry, you will be the one to turn to customers with questions, not just about the investment but the total cost of installing solar energy in their homes. Solar energy is an exciting step forward, but it is not without limitations. It is as unpredictable as the weather, and limited storage can create obstacles to providing consistent power. So, how can you promote solar energy as a sustainable solution?

Increasingly, renewable energy leaders are turning to artificial intelligence (AI) technology for predictive forecasting models.

“Developing a reliable algorithm that minimizes the errors associated with predicting near-future PV power generation is very useful for the efficient integration of variable energy resources (VER) in the grid. The prediction of PV power can play an important role in facing these challenges,” said experts from 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 source of energy or a city evaluating collective energy sources to production can be controlled through a power grid. The more data provided, the more accurate the algorithms. And that information ensures consistent access to electricity for homeowners using renewable energy while improving infrastructure conditions on many issues such as preparing for grid maintenance and more good optimization of energy sources.

“Artificial intelligence can collect and use data to coordinate the entire energy system from generation, transmission and consumption of energy,” wrote Behzad Benam, CEO and founder of Safeline. “This intelligent coordination improves system performance based on repeated user consumption patterns.”

If you want to provide your solar energy solution 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 becomes personal

It’s not rocket science to understand that more customers using solar energy to supplement electricity can contribute more power to the city’s grid, which helps lower costs because the power grid can use free renewable energy before turn to fossil fuels.

Analyzing meteorological data and strategic customer energy demand to maintain consistent energy supplies and to help identify lower energy output rates, which helps in scheduling grid continuity.

The data also looks at the weather

Although based primarily on history, seasons and a bit of professional instinct, AI-based forecasting relies on good old-fashioned weather patterns to coordinate energy sources. But the value of weather forecasting extends beyond efficient power grids. Scientists use AI-based algorithms to predict dramatic global and potentially catastrophic weather patterns, and some of the world’s largest supercomputers are dedicated to weather forecasts.

“Artificial intelligence, in theory, can provide on-par predictions with minimal computing,” according to Mark Bergen, who has written about the impact of AI forecasting on the preparedness of underdeveloped countries. for severe weather. “Early research shows progress in rain forecasting and ‘nowcasting,’ which predicts the weather in the next hour or two.”

This technology, with its ability to target extreme weather during the day — even by the hour — will have a major impact on preparing the city’s power grid with the necessary resources to ensure that customers have constant access to electricity.

Data goes to mobile

Sometimes, the best data is based on what you can see. And an effective tool for collecting observational data – a key factor in energy forecasting – is drones.

“Drones play an important role in solar panel inspection, when paired with machine vision tools,” wrote Peter Kudlacek, CEO of 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 best value from their investment.

As the world advances in renewable energy initiatives, the methods to use important energy sources as we transition to others are as important as the energy source itself. The path to designing affordable and practical long-term solutions has obstacles – but AI technology is quickly emerging as a strategic predictive asset to coordinate and optimize valuable energy resources while protect those who depend on it.


Doug Robinson is the CEO of residential solar sales platform LGCY Power.

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