This case study accurately illustrates the possible practical benefits of machine learning for HVAC operation. Thanks to ET, a significant potential for energy savings was found and fully exploited during subsequent modifications of the building management system resulting in successful savings in energy consumption and building operation costs.
This case study is a good example of how AI can improve our work. In this case, AI does not replace an expert; it just makes their work more efficient. AI performs the repetitive and dull part of the job – such as comparing all measured data and detecting anomalies. The expert then spends precious time only with the events that matter and are worth investigating.
During the pandemic, buildings were exposed to nonstandard regimes (reduced number of occupants, nonstop ventilation, total lockdown, etc.). Valuable data
were measured by Building Management Systems.
Analysis of these data provide valuable knowledge about the effectiveness of setback regimes.
This case study demonstrates the potential of energy-saving measures to achieve significant cost savings and reduction of energy consumption, even in challenging market environments. Immediate impact evaluation tools, such as Energy Twin Interactive and SkySpark, can enhance the efficiency of implementing such measures. These tools provide prompt feedback for fine-tuning and adjusting measures, while automating mundane tasks, thus reducing the workload of energy experts.
AI for Main Electricity Meter Analysis: The Basics Artificial Intelligence (AI) is revolutionizing energy analysis by turning granular smart meter data into actionable insights. It
It’s always good practice to double-check your input data before diving into analysis. Sometimes you’ll catch small inconsistencies — and sometimes, you’ll uncover something more
Author Jan Siroky View all posts
At Energy Twin, we’ve been working on a research project exploring how machine learning can be used for general fault detection. Like any good research,
Companies often understand the importance of deploying smart meters and getting data online. They see it as a key milestone—and while it is, it’s only
Detecting anomalies in energy data is key to optimizing consumption, reducing costs, and ensuring building systems run efficiently. With the vast amount of data from
