Getting Started with Energy Measurement using Å Insite
The process of establishing and delivering energy data can be both intricate and costly, often accompanied by frustrations. Å Insite simplifies the journey, making it easy and predictable for you and your customers.
High-quality energy data holds the key to enhanced energy efficiency, but setting up and delivering this data typically involves a time-consuming and expensive ordeal.
Å Insite is committed to sparing you this hassle by taking charge of the complexity associated with data establishment and delivery, from inception to ongoing operation and maintenance.
Making Onboarding Painless
- The customer should experience minimal disruption when we perform an installation. We ensure everything is set up, pack up, and depart, explains Thomas Krekling, Head of Delivery at Å Insite.
Ideally, the building owner's involvement is minimal, typically limited to granting access to the building. The extent of work depends on the existing setup in the building.
Some buildings have existing systems on protocol where we install data loggers to transmit data to our cloud. In other cases, we perform retrofit installations, adding power metering to electrical panels.
The third category involves third-party energy meters, like district heating meters. In these instances, customer participation is needed to request data access from the energy provider.
During inspections, the primary objective is to grasp the facility comprehensively to make informed decisions about what to measure. While some seek an exhaustive understanding of their energy consumption, others have specific preferences.
As a general practice, we measure the primary intake, thereby capturing the total energy consumption for the entire installation.
We have experienced customers initially request specific measurements, only to discover that a substantial portion of consumption is unaccounted for. This highlights the value of measuring the total energy intake.
The goal isn't mere data accumulation; it's about enhancing the quality of the data through various analyses. Techniques such as data quality checks, algorithm application, and anomaly detection help strengthen your data foundation.