Optimizing Energy Efficiency with AI-powered Operations
The client, an industry-leading power producer, had undertaken a strategic sustainability initiative aimed at reducing the environmental impact of their operations. As part of the initiative, the client sought toΒ optimize the thermal efficiencyΒ of their power plants to reduce fuel consumption and lower emissions.
At the clientβs power plants, the optimization process was done manually.Β To achieve optimal performance, human operators must continuously monitor and adjust numerous variables, which is an erroneous and burdensome task.
βHistorically, manual interventions would have been enough, but to achieve ambitious goals we have on sustainability, we needed a more sophisticated and adaptive approach.βΒ βΒ Head of Operations
ConsultportΒ proposed 5 strong candidates within 72 hours. The client interviewed 4 candidates and selected two ex-Capgemini consultants from the companyβs AI-consulting arm. The consultant team started working with the client 6 days after the initial request.
The two consultants joined forces with the client to create an advanced AI model.
The client provided essential input on how the power plants work, along with crucial data collected by on-site sensors, such asΒ temperature changes,Β pressure variations, andΒ energy usage patterns.
With the client insights, the consultants started developing the AI model. Through iterative training and refinement, the AI model analyzed complex relationships between external factors and human decisions, eventually learning toΒ make predictions and suggestions.
The introduction of the AI-powered recommendation engine had a transformative impact on the clientβs power plant operations, with results demonstrating both immediate efficiency gains and long-term organizational value.
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