How AI can contribute to environmental sustainability – pv magazine USA – pv magazine USA

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Artificial intelligence models can be used during the solar pre-construction planning and design process, as well as afterwards to help with monitoring, weather forecasting, predictive maintenance and more.

April 19, 2024

The energy sector is generally considered to be fairly conservative when it comes to adopting new trends and technologies. After all, much of the energy we consume still comes from sources that have been used for hundreds of years — oil, coal, and natural gas. 

However, in the recent push for sustainability in the energy sector, one technology emerges as a linchpin for the shift towards “green living”: artificial intelligence.

How AI will disrupt the energy industry for the better

Artificial intelligence seems poised to revolutionize the energy sector thanks to its superior data analysis capabilities. Data analysis is a fundamental aspect of any energy operation — from determining where the best sites for development are to how much energy has been consumed for billing. AI can perform all of this analysis at a much more efficient rate than human workers, allowing them to focus more of their efforts on implementing these solutions.

Artificial intelligence can also use the data it is fed to perform advanced predictive analytics. In the energy industry, this could prove invaluable, as the ability to better forecast consumption can allow energy companies to avoid the overuse of resources. Furthermore, as renewable energy resources have historically been somewhat unreliable due to their dependence on external factors such as weather, predictive analytics now powered by AI can allow energy companies to ease some of their concerns about the volatility of these renewable sources.

Using these tools, artificial intelligence could improve the sustainability of the energy sector by enabling the more efficient deployment of resources. Energy companies can both reduce waste and cut costs using analysis and forecasting generated by AI.

The most apparent use of artificial intelligence in the energy sector is “smart meters,” which help users better control their energy consumption and energy providers better understand and manage their load. Smart meters help the energy provider’s sustainability initiatives by reducing overall energy consumption, which will also benefit customers’ wallets. 

Something that must be understood about the shift towards renewable energy sources is that, as more renewable energy sources are introduced, it makes the grid more complex to handle this increasing number and diversity of sources. In turn, more technology is needed to manage it. This is where artificial intelligence emerges as a particularly valuable innovation in the solar power industry — as a tool to help manage the distribution of resources on the grid.

AI in the solar industry

Some more specific applications in the solar power sector show even higher potential. As solar developers continue to expand some reach, some exciting use cases for AI technologies include:

  • Searching for solar-generating properties: AI models can analyze data much more efficiently than humans, making them ideal for identifying solar-generating properties. An AI model can be trained to cross-reference properties on the market with characteristics set by the user — for example, climate, open space, and proximity to grid infrastructure — to quickly identify ideal sites for development and installation. 
  • Pre-construction planning and design: Artificial intelligence models can be used during the pre-construction planning and design process to ensure that solar power arrays are designed for optimal output. Producers can use this technology to test potential scenarios and layouts in advance, reducing the need for on-site labor and the expenses of on-site modifications and customizations.
  • Real-time monitoring and data analytics: Solar power producers can use AI to power real-time monitoring and data analytics of their array’s output. This technology can help producers more efficiently identify and isolate any obstacles in their panels’ productivity, allowing them to conduct repairs much more quickly.
  • Forecasting weather: One of the most exciting potential applications of AI in solar power is weather forecasting. Because the output and efficiency of solar panels are influenced directly by weather conditions, producers must be wary of any inclement weather that can interfere with the panels’ ability to generate power. Artificial intelligence can be used to predict weather conditions, allowing producers to adjust the amount of power being generated and stored during optimal conditions so that disruptions during suboptimal conditions can be minimized.
  • Predictive maintenance: AI can also help enable predictive maintenance for solar panels. Regular maintenance is essential for solar power operations because a solar panel in disrepair cannot perform to its maximum potential. An artificial intelligence model can analyze historical trends and data on current conditions to indicate to producers when it is necessary to enlist a technician for maintenance.

The adoption of AI in the energy sector

AI can potentially revolutionize the energy industry with its advanced data analysis and predictive analytics capabilities. At this point, it is a matter of convincing the energy companies of the validity and necessity of these use cases. 

By better understanding our consumption and needs, the energy sector can be better prepared to adopt renewable energy sources such as solar power. Artificial intelligence is the key to unlocking this deeper insight.

Ed Watal is an AI thought leader and technology investor. One of his key projects includes BigParser (an Ethical AI Platform and Data Commons for the World). He is also the founder of Intellibus, an INC 5000 “Top 100 Fastest Growing Software Firm” in the USA, and the lead faculty of AI Masterclass, a joint operation between NYU SPS and Intellibus. Forbes Books is collaborating with Ed on a seminal book on our AI Future. 

The views and opinions expressed in this article are the author’s own, and do not necessarily reflect those held by pv magazine.

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