Waste-to-Energy Optimization with AI

Alex Sas, Tersa:

"AI is a hot topic, but how could we seamlessly integrate it into our daily operations? That was our challenge. Within just 4 months, AI helped us achieve 30-35% steam savings—transforming how we generate electricity."

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As the Waste-to-Energy (WtE) sector faces growing challenges like technological gaps and the need to improve efficiency, Tersa, a leading WtE facility in Barcelona, stands out as a beacon of innovation. Faced with the dual pressures of rising global waste and the need for enhanced efficiency, Tersa recognized that traditional methods were no longer sufficient. What they needed was a revolutionary approach—enter AG Solution’s AI-driven technologies.

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The Challenge: Rising Waste and Operational Pressures

The World Bank’s forecast of a 73% increase in global waste by 2050 underscores the urgent need for WtE facilities to innovate. Tersa, like many in the industry, needed to ensure that the boiler ducts were cleaned to comply with emissions regulations, but this process was manual and required boiler shutdowns that reduced electrical output, which meant less megawatts generated to trade. It was clear that to remain competitive and sustainable, Tersa needed to rethink its operational strategy.

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Xavier Morera, Online Diagnostic Technician at Tersa:

"By using real-time data and algorithms, we pinpointed the exact cleaning times, saving energy and improving efficiency.AI wasn't just about automation; it was about gaining deeper insights into our production processes."

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The Solution: Leveraging AI for Operational Excellence

AG Solution brought a comprehensive suite of AI and machine learning technologies to Tersa’s plant, setting the stage for a transformation that would redefine their operations:

• Real-Time Data Integration: The introduction of real-time data systems provided Tersa with unprecedented insight into its operations. This capability allowed for quick adjustments and more informed decision-making, which is crucial as waste compositions continue to change.
• Predictive Maintenance: One of the most significant breakthroughs was in predictive maintenance. By moving away from fixed maintenance schedules to AI-driven predictions, Tersa was able to anticipate and address maintenance needs before they became issues, leading to significant efficiency gains and cost reductions.
• Process Optimization: The AI system continuously monitored and optimized plant processes, resulting in a 30-35% reduction in steam consumption. This not only enhanced energy production but also positioned Tersa as a leader in sustainable energy generation.

The Results: A New Standard for Waste-to-Energy

Tersa’s journey showcases the tangible benefits of integrating AI into WtE operations. The reduction in steam consumption, improved maintenance practices, and overall enhanced efficiency are not just wins for Tersa—they set a new standard for the industry. As global waste levels continue to rise, Tersa’s example demonstrates that innovation is not just desirable—it’s necessary for survival in a rapidly evolving industry.

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Marc Gardella, Diagnostic Manager at Tersa:

"The insights we've gained have had an enormous positive impact—recovering more waste and producing more energy. AI has revolutionized how we approach decision-making, enabling us to maximize both our environmental and operational goals."

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The Results: A New Standard for Waste-to-Energy

Tersa’s journey showcases the tangible benefits of integrating AI into WtE operations. The reduction in steam consumption, improved maintenance practices, and overall enhanced efficiency are not just wins for Tersa—they set a new standard for the industry. As global waste levels continue to rise, Tersa’s example demonstrates that innovation is not just desirable—it’s necessary for survival in a rapidly evolving industry.

Why Tersa’s Case Study Matters

Tersa’s experience is more than a case study; it’s a powerful example of how AI can drive meaningful change in the Waste-to-Energy sector. As the industry faces growing challenges, the lessons learned from Tersa’s transformation are invaluable for any facility looking to boost efficiency, reduce costs, and contribute more effectively to a sustainable future.

Learn how AI drove Tersa’s success in WtE

Read the case study.