How Digital Twins Are Changing The Game For Solar Energy Projects

By Chris Bambacus , Director of Social and Environmental Responsibility at Aquent

Key Takeaways:

• Digital twins empower organisations to optimise renewable energy assets, improve decision-making, and drive progress toward a more sustainable future.
• Organisations can use digital twins to monitor performance in real time, predict potential issues, and optimise energy output, leading to increased efficiency and reduced downtime in renewable energy systems.
• Using a Supervisory Control and Data Acquisition (SCADA system) to send data to digital twins allows for the immediate detection of performance issues and enables proactive maintenance in renewable energy installations.
• Digital twins provide valuable data insights for informed decision-making regarding the environmental and financial impact of renewable energy projects.
• Immersive visual models linked to real-time performance data enable better communication and collaboration between stakeholders in renewable energy projects.

At Aquent, we're fiercely dedicated to leaving the world better than we found it. This commitment extends beyond simply reducing our environmental impact; we're on a mission to erase our entire historical carbon footprint. We're proud to announce that we've recently achieved carbon negative status, an important milestone on this journey. To reach this point, we've invested in a portfolio of solar projects across the U.S. and implemented innovative solutions to manage these assets effectively.

Like many organisations investing in renewable energy, we face challenges in maximizing the impact of these projects. From site selection and financing to ongoing maintenance and optimisation, ensuring the success of these projects requires a sophisticated approach.

That's why we've implemented a cutting-edge solution: a digital twin powered by real-time data from Supervisory Control and Data Acquisition (SCADA) systems. In this blog post, we'll explore how our digital twin is helping us achieve our significant sustainability goals and why this technology is a game-changer for the renewable energy industry.

Leveraging digital twins for enhanced efficiency

A digital twin is a virtual representation of a physical asset or system. This dynamic model, created using real-time data, allows us to monitor, analyse, and optimise the performance of our solar projects in a way that was never before possible.

For sustainability professionals, digital twins offer invaluable insights into the performance of renewable energy assets. Here's how we leverage them:

• SCADA integration: We are deploying Supervisory Control and Data Acquisition (SCADA) systems across our solar sites. These systems will collect granular data from inverters, meters, and other critical components, providing a constant stream of information on energy production, equipment performance, and environmental conditions.
• Digital twin creation: This data is fed into our digital twin platform, which creates a dynamic virtual model of each solar project. This model allows us to visualise and interact with the system in a way that was never before possible. Imagine a 3D model of a solar farm where you can zoom in on individual panels, see real-time energy output, and even simulate the impact of shading or equipment failure.
• Advanced analytics: By applying machine learning algorithms to the data within the digital twin environment, we can identify patterns, predict potential issues, and optimise performance in real time. This might involve detecting a gradual decline in output from a specific inverter, signaling a potential malfunction that can be addressed proactively.

“For sustainability professionals, digital twins offer invaluable insights into the performance of renewable energy assets.”

As our solar grid grows, having a real-time overview of installations is crucial. Prior to the implementation of digital twins, one of our solar sites experienced a 35% decrease in output that went undetected for three months. Now, by utilising streamed analytics in our digital twin, we continuously monitor inverter data and apply machine learning algorithms to detect energy output trends. System alerts notify users if output deviates from normal parameters, allowing for immediate site inspections. In one case, this led to the discovery of panels obstructed by leaves and mud after a storm. Trend analysis and fault monitoring significantly reduce downtime and increase efficiency in our solar installations.

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