top of page

AI Use Case

Predict energy demand trends based on data sources ranging from sensors to social media

Predict energy demand trends based on data sources ranging from sensors to social media. In a competitive market the more varied and unique the data sources accessed the more refined (if not always more accurate) the model can become.

Function

Benefits

Revenue - Improve trading decisions (eg market demand estimates),Operational Support - Demand forecasting

Case Studies

Verv Trading Platform~Verv plans to predict renewable energy generation and usage for its p2p marketplace using deep learning,St. Vincent's Hospital~St. Vincent's Hospital achieves 20% in energy savings by implementing a predictive energy control system for its HVAC from BuildingIQ,Australian Renewable Energy Agency~Australian Renewable Energy Agency improved accuracy of solar energy predictions by 31% using machine learning methods based on a distributed network

Potential Vendors

BuildingIQ

Industry

Utilities

Electricity

Data Sets

Structured / Semi-structured,Time series

AI Technologies

Machine Learning (ML),ML Task - Prediction - Regression,Product Type - NLP - Text Entity Extraction,Product Type - Natural Language Processing (NLP),ML Task - Prediction - Data Translation/Transformation,ML Task - Prediction - Annotation,Product - Data Capture - Sensor IoT,ML Task - Prediction - Multi-class Classification,ML Task - Prediction - Binary Classification

bottom of page