Energy Data Analysis and Machine Learning Real Life Examples
Originally Aired 02/10/2022
Viewers can take a/ brief quiz based on this webinar to earn 1 AIA Learning Unit (LU):
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Download the presentation slides here:
https://www.dropbox.com/s/ipjj70k8oju...
Presented By:
JAN ŠIROKÝ, Energocentrum Plus, s.r.o.
JOHN PETZE, Co-Founder and COO, SkyFoundry
Energy usage data is critical to assessing and improving building performance. A variety of tools and techniques are used to work with energy data. State-of-the-art software tools and software algorithms can significantly streamline the process of working with data and uncover relationships and insights that are very hard to do manually. Machine Learning (ML) is one of the techniques seeing increased use and a fair amount of hype. While ML is not a silver bullet for all energy data analysis applications, ML is much more than a buzzword. There are numerous scenarios where you can start using ML right now to benefit from deeper, more efficient energy data analysis. In this webinar, we will see real examples of ML for evaluating energy consumption (with hourly, daily, weekly or monthly aggregation) using regression models in a single tool that allows users to focus on the data trends and relationships without tedious manual processing, such as manually exporting data to spreadsheets and using chart trend lines. One of the most significant advantages of an ML-enabled approach is avoiding potential erroneous data transfer, resulting in more efficient energy analysis. It also allows you to get results in near real-time, quickly identify outliers in your data, and choose the best model depending on metrics such as R2, RMSE, or model shape validation. Challenges arising from the analysis of a large buildings’ portfolio will be addressed in the webinar, as well as real-world examples.
Learning Objectives:
• Energy consumption regression models – model types, purposes, and limitations
• Major difference between daily and hourly aggregation in energy data analysis
• Importance of automation of energy data preprocessing and models management
• De-mystifying ML through specific use case examples
Sponsored By:
SkyFoundry
Energocentrum Plus
Save the date for CxEnergy 2022 on April 19-22, Orlando, FL. Visit www.CxEnergy.com for additional information.