Artificial intelligence (AI) in solar energy is already a reality. Far from being an experimental technology, it is now used in practical ways to improve production, reduce failures, and optimize the operation of photovoltaic plants, especially at utility scale.

In a sector where small improvements in performance have a direct impact on profitability, the combination of operational data and artificial intelligence has become an essential factor for solar asset owners and operators.

In this Bluence article, we explain in a simple way what AI brings to solar energy, what its main applications are, and how it can be integrated into the daily operation of a plant.

Why is AI in solar energy decisive for the future?

Today’s solar plants are increasingly larger, geographically dispersed, and connected to complex systems such as storage or electricity markets. In addition, each plant generates millions of data points every day, which—if properly interpreted—can provide valuable insights.

AI helps manage this complexity with a much more practical approach, delivering concrete operational benefits:

• More available energy, thanks to real-time optimized operations.
• Fewer failures and lower maintenance costs, by detecting issues before they escalate.
• Better production forecasts, which are essential for planning and grid integration.
• Intelligent automation that shortens response times and improves decision-making.

All of this enables operators to move from reactive operations to anticipatory management, where action is taken before a problem occurs.

Data reflecting trends in the solar sector

The growth of solar energy in recent years has been remarkable worldwide. In fact, according to IRENA, global photovoltaic capacity exceeded 1,865 GW, with a record increase of 452 GW in 2024.

In addition, in regions such as the United States, solar generation has grown very rapidly, even surpassing traditional energy sources in certain markets.

These cases confirm that adopting technologies such as AI is both a competitive advantage and a necessity for operating large-scale solar plants efficiently and profitably.

Main uses and trends of AI in photovoltaic plants

Therefore, the emergence of AI in the solar energy industry has already begun to reveal what the next trends will be in renewable energy and across the broader energy sector.

Production optimization

AI continuously analyzes plant behavior and adjusts operations to maximize output under each set of conditions. To do this, it takes into account factors such as weather, equipment status, and grid constraints.

Early fault detection

Instead of waiting for an inverter or string to fail, AI identifies abnormal behavior and issues alerts in advance. This makes it possible to act earlier, reduce energy losses, and optimize maintenance.

Improved generation forecasts

Production forecasts are essential for operating solar plants, especially when they participate in electricity markets or are combined with batteries. AI improves the accuracy of these forecasts, minimizing errors and penalties.

Example: according to api4.ai, an AI system could recognize that clouds over a solar park limit production by 20% per hour.

Decision-making support

AI does not replace human teams; rather, it helps them prioritize. For example, it supports decisions about which incidents are most critical, where to act first, or which choices have the greatest economic impact.

How is AI integrated into a real solar project?

One of the most common mistakes is thinking of AI as an isolated layer. In reality, it works best when it is progressively integrated into day-to-day operations.

A typical approach to integrating artificial intelligence into solar energy could be:

1. Organizing and validating plant data, ensuring that information is reliable.
2. Starting with specific use cases, such as generation forecasting or fault detection.
3. Integrating AI into operations and maintenance workflows so that alerts translate into real actions.
4. Continuously improving the system by learning from plant behavior over time.

How does Bluence apply AI in solar operations?

At Bluence, AI is integrated directly into platforms designed for the industrial operation of solar plants and hybrid assets. The goal is not to showcase complex technology, but to make it useful and operational on a day-to-day basis.

For this reason, the most important capabilities we offer include:

• Normalization of plant, weather, grid, and storage data.
• Advanced production forecasting based on real data.
• Automatic anomaly detection with prioritization based on impact.
• Performance analysis to improve decision-making.
• Automation of operations and maintenance workflows.
• Unified management of solar portfolios across different countries.

In this way, AI becomes a highly practical and useful tool for improving performance, reducing costs, and increasing the reliability of photovoltaic plants.

Artificial intelligence is already vital for competitiveness in solar energy. Its benefits are clear: higher production, fewer incidents, and more efficient and scalable operations. With Bluence, AI becomes a practical, fully operational tool integrated into the daily management of solar plants and assets. Want to bring AI to your photovoltaic plants? Request your personalized demo with Bluence and discover how.