AI for the Solar Power Industry

AI talks are all over the world nowadays — AI here, AI there, AI everywhere. So, let’s not miss this chance to follow the global trend and talk about AI and solar power. 

Although we might encounter the dilemma, “AI optimizes the solar panel’s power output, and that optimized power is spent on the AI that optimizes the solar panel power output,” let’s examine how AI can be useful for the solar energy industry and how it influences the end product for residential solar systems.

Idea and Design

The solar panel is first born in the heads of scientists and engineers. Here is an example of how long a single solar invention may take. For instance, it took almost seven years for a Renkube team to develop motion-free optical tracking (MFOT) of solar panels. It is a new way of cell structure that can catch direct sunlight without the physical movement of the solar panel. Yes, just like the internal sunflower inside every solar cell. Imagine how fast they would have done it if AI had already been introduced by that time. 

In other words, AI can do the following “dirty job” much faster:

1) Data-Driven Research: AI can look into the past and analyze scientific literature, patents, and research papers to identify trends, gaps, and opportunities in solar panel technology. Who knows, maybe there is genuine scientific research that appeared too early in the past, but it can already be useful. Just like with EVs: google, when was the first electrical vehicle built. You’ll be amazed. 

 2) Material Discovery and Optimization:  AI can analyze vast datasets of material properties to identify promising candidates for new photovoltaic materials. Machine learning algorithms can predict the performance of these materials, accelerating the discovery process. It can simulate the behavior of new materials under different conditions, helping researchers understand their properties and potential applications in solar panels. 

2) Design Innovation: AI can optimize the micro and nano-structures of solar cells to enhance their efficiency, such as optimizing the arrangement of nanostructures to maximize light capture. 

3) Performance Prediction and Optimization: Who knows how all these new materials will work with new designs? It would take years and resources to experiment. AI can do this in hours by developing models to predict performance by considering efficiency, cost, and durability.

4) Accelerated Discovery and Development: AI can uncover hidden patterns and relationships in data that may not be obvious through traditional analysis, leading to discoveries. 

In other words, AI may be a combination of universal super scientist and engineer-of-all-tools that can create and build. 

Production

That is the simplest and, at the same time, the most complicated part of using AI. It’s simple because there are just a few production points where you need AI: quality control and production panning. Quality control can be done by AI-powered computer vision systems that inspect solar cells and panels for defects during production, ensuring high-quality output. 

Production planning is an everyday analysis of the factory’s output combined with data from sales and orders. At this stage, AI’s final result is a set of recommendations and decisions that optimize the total factory output.

And what’s so complicated about it? A factory with integrated AI has to be built brand new. You can’t just rebuild an existing factory or install new sensors or computers around the production line. That could be an extremely expensive factory, but such an approach will make solar panels cheaper and more affordable for regular folks.

Cost Reduction for the Residential Solar Systems

The above is a simplified overview of how AI may become a game-changer for solar panel production. So, what about the end user? 

While AI can decrease the costs of production, what about the cost of installing it? Solar installers employ people who design, evaluate, calculate, and chat with customers. These people are paid salaries, and their staff costs are included in the final price of the residential solar project.

Here is a list of the areas where AI can dramatically decrease the installation costs.

• Customer acquisition. AI and chatbots might become the first point of contact with a solar panel installer, allowing them to ask questions and get important information before ever talking to a real person. The automated first contact would save time and money for both the customer and the salesperson.

• Pre-construction planning. Many solar installers have some kind of solar planner on their websites. However, these models are behind what AI can do with PV system planning. AI could generate real-time design options for customers that consider address, climate, historical weather data, local legal aspects, rules of the regional grid operators, customer power demands, etc. Depending on what you’re optimizing for (low cost, maximum energy production, resilience, or something else entirely), AI could model it for you.

• Power supply and demand predictions. Once a customer has installed solar, the AI software embedded in the system (especially if it’s paired with a home battery) could optimize for whatever a customer wants: solar production, energy storage, net-metering income, or backup during a power outage. Also, machine learning models can manage the power using weather forecasts and historical data.
• Predictive maintenance. Solar maintenance is easy to forget about. By integrating modern sensors and machine learning algorithms, AI algorithms continually monitor many factors, including temperature, voltage, and current. AI can predict solar panel failures with up to 95% accuracy.

• Installation. Robots will install the solar panels. That is not a prediction; it is a proven fact. AES Corporation introduced a first-of-its-kind robot to ride around the dedicated land and install thousands of heavy panels. The size of a pickup truck, Maximo (that’s what the robot was called) has a large arm that uses suction cups to pick up solar panels one by one and lay them into rows, using artificial intelligence and computer vision to position them properly into designated areas. This innovation will lead to automated residential installation systems that will cut the costs of residential solar panel systems, increasing sales. Rooftop workers will be educated on how the robots do their jobs. 

Dilemma

AI needs power, too. Therefore, it is fair to ask whether all the optimized and saved power will be used to supply AI’s work. In other words, it sounds like a zero-sum game with no end profit. 

What does AI itself think about it? We’ve asked three different AIs the same question: “True or False? AI optimizes the solar panel’s power output, and that optimized power is only enough to supply the AI that optimizes the solar panel power output.” 

ChatGPT 3.5	False. The primary goal of using AI to optimize solar panel power output is to achieve a net increase in overall energy efficiency and production. If the optimized power output were only enough to supply the AI systems themselves, it would not be a practical or beneficial use of resources. The AI optimization should result in a significant enough improvement in solar panel efficiency that it produces excess energy beyond what is required to power the AI systems. This surplus energy can then be used for other applications, ensuring a net positive outcome.
Gemini by Google	False. While AI can optimize the power output of a solar panel, the optimized power is typically much larger than the amount needed to power the AI itself. AI systems are designed to be energy-efficient, and the power required to operate them is generally a tiny fraction of the overall energy generated by the solar panel.
Copilot by Microsoft	False! The optimized power generated by solar panels is not solely used to supply the AI that optimizes them. Instead, it serves a dual purpose:Solar Panel Optimization:AI algorithms analyze data from solar panels to maximize their energy capture.By adjusting panel orientation and tilt, AI ensures efficient energy conversion.AI Power Consumption:The energy generated by the optimized panels powers the AI system.However, this energy is also used for other tasks beyond AI optimization, such as data processing, maintenance, and inference.In summary, the optimized power benefits both the AI system and other operational needs, not just the AI itself.

It was fun to play with these answers. But if we take it seriously, it needs a human to make a final calculation and decision about which AI model, equipment, or combination of solar panel systems would perfectly meet your power demands.

Regarding that, visit our dedicated website, Solar Power Systems, for the best selection of solar installers in your area. Get a solar quote from a human who will make you the best proposal.

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