Energy
“AI applications in the sectors of agriculture, water, energy and transport could lead to a 4% cut in greenhouse gas emissions by 2030.”
Manage Data,
Harness Power.
Energy generation technology is undergoing disruptive transformations. Solutions that seemed out of reach only a few years ago are now made possible by innovative companies leveraging the power of Big Data. Green energy companies can integrate Machine Learning functionality to leverage test or yield data to develop new sustainable energy solutions. ML models incorporating forecast data like weather patterns can maximize wind and solar energy generation.
Data Analytics can provide insights into energy consumption and offer tools to manage peak/off-peak usage, mitigate power outage periods, and establish pricing schemes. Data generated from smart grid systems can facilitate an automated power delivery network capable of 2-way flow of electricity and information. Smart meters can be utilized to predict, supply, and manage energy usage across regions, campuses or data centers. Refinery processes and distribution and real-time adjustments can be optimized to market demand.
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Utilize Machine Learning to test processes and maximize output of potential energy sources that can be optimized to yield the lowest cost per KWh.
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Mitigate grid breaches or loss by implementing AI modeling and Machine Learning systems to detect anomalies in energy usage patterns from cyber-attacks or theft.
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Leverage data collected from energy consumption, peak period usage patterns, and capacity to gain insight into anticipated demand and pricing levels.
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Incorporate enhanced learning models to leverage weather patterns and estimated operational costs to maximize the efficiency of renewable energy sources.
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Deploy data driven, real-time solutions for energy management between consumers, utilities, intermittent sources, battery storage facilities, and micro grids.
info@emergentdata.ai