The Story
This climate-focused power provider client wanted to use machine learning to generate power when resources are available, storing it for later use to optimise production and consumption. Chesamel worked with the organisation to accurately forecast power output from a renewable energy plant.
Impact
PV output and consumption could be predicted with 10% & 5% forecasting error respectively. Combining these two models, we developed a control strategy and reduced grid consumption by 40%.
Methodology
Chesamel worked in collaboration with the power provider to create a machine learning model that can forecast renewable energy production and accurately predict energy demand (consumption).
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