Solar Asset Performance: How to maximize generation and reduce losses with data intelligence

In this article, you'll learn what solar asset performance is, why it’s a critical factor for your plant’s profitability, and how AI-based technologies can turn operational data into decisions that save time, energy, and money.

In an increasingly competitive market, where every MWh counts, knowing and applying optimization strategies is essential to ensure your assets deliver the expected real-world performance.

What is Solar Asset Performance?

The term solar asset performance refers to a solar plant's actual ability to convert available solar resources into electricity, considering all technical and operational variables that affect this output.

More than just measuring generation, it’s about understanding whether your assets are performing as expected, and if not, identifying what's compromising that performance.

Why Does Solar Asset Performance Matter So Much?

In photovoltaic plants, small issues often go unnoticed, but cause major long-term losses.

Disconnected strings, partial shading, string-box faults, module degradation, inverters running below optimal levels...

Without a smart monitoring system, these silent losses are often discovered too late — after they’ve already impacted monthly revenue or the team’s performance bonuses.

How Does Performance Management Work in Solar Assets?

Performance management is built on three key pillars:

1. Smart Monitoring

Continuous asset tracking through sensors and SCADA systems, integrated into platforms that analyze real-time data.

2. Predictive Analysis

Using AI and machine learning to anticipate failures before they become visible or cause unplanned downtime.

3. Data-Driven Actions

Automated and traceable diagnostics that guide O&M teams straight to the root cause, without wasting time on manual inspections.

When Should You Apply Performance Technologies?

The larger the plant, the harder (and costlier) it is to manually detect performance deviations. That’s why predictive analytics solutions are especially valuable when:

• The plant exceeds 10 MWp
• The O&M team is overloaded
• There are recurring curtailment events or unexplained failures
• Key performance indicators (PLF, PR) fall below expectations
  
  

What Are the Advantages of a Predictive Approach?

✔ Reduction of invisible losses: Detects discreet failures before they become recurring
✔ Lower maintenance costs: Enables earlier interventions and avoids expensive corrective actions
✔ More predictability: Improves operational planning and reduces response times
✔ Data-driven decisions: Generates actionable reports, with traceability by asset, failure type, and SPE

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Real-World Example: AI Applied in a Delfos Solar Plant

In a recent Delfos case, an AI system detected a communication failure and inconsistencies in photovoltaic strings right after a maintenance procedure.

The result?
Immediate action by the team avoided losses of 7,778 MWh over 299 days and reduced O&M costs by up to 30%.

Solar Asset Performance Is More Than a KPI, It’s a Strategy

Ensuring solar asset performance goes far beyond checking a dashboard. It’s about turning data into intelligence, preventing failures, and recovering energy that was previously lost in the details.

With the right tools, your operation becomes more efficient, your team gains confidence, and your assets deliver on their promise: clean, predictable, and profitable energy.

Want to see how AI can recover the performance of your solar assets in practice?
Get in touch with Delfos and discover how to anticipate losses, optimize decisions, and protect your plant’s profitability.

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