Energy Data Science in a Nutshell
Nowadays, data is increasingly cheap and ubiquitous. We are now digitizing analog content in buildings that was created over years and collecting new types of data from equipment, sensors, meters, web services, ERP, CRM, SCADA systems, instruments, critical power infrastructure and other transactions in facilities.
At the same time, new technologies are emerging to organize and make sense of this avalanche of data. We can now identify patterns, regularities and abnormalities in data of all sorts that thanks to open source algorithms, allowing us to advance energy efficiency, improve the sustainability, reduce the equipment down time risk and increse the operational efficiency. The rise of “big data” has the potential to deepen our understanding of how people, sensors, electrical and mechanical systems, and outside parameters like electricity tariff and ambiant temperature relate to each other.
Before, we were not able to act upon data driven conclusions. The current advances in sensors and analytics let facility managers and building operators to go from reactive to proactive operation. Before they were asking what happened in their facility after some certain abnormality or malfunction, right now they can ask what is the best that can happen. That means we shift from descriptive analytics to predictive optimization. IoT and data science let this transition happen.
The transition to data driven operations changed the energy management concept fundamentally. Yesterdays static and dummy automation systems are disrupted by real time predictive optimizations and cloud based energy intelligence solutions. As the volume, frequency and type of data we collect from the facilities increases, the analytics that we can apply get richer and richer. In return, the energy saving and operational efficiency and the great visibility makes clear ROI and faster energy retrofit projects. Today, the ROI is dependent on capital and the people but in the future, the ROI will just be dependent on the power of the energy data science module run on top of your energy IoT platform at your facility.