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Getting Started with Energy Measurement using Å Insite

Written by Petter Hessen | Oct 23, 2023 8:20:33 AM

High-quality energy data is key foundation for energy management, cost allocation, reporting and automation. However, getting started with measurements and managing this over time tend to be both time-consuming and costly. 

Å Insite is committed to spare you this hassle by taking responsibility for everything associated with data collection and delivery, from inception to ongoing operation and maintenance.

 

Making onboarding painless

- The end client 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 limited to granting access to the building. The extent of involvement 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 new metering to electrical panels.

The third category involves third-party energy meters, like district heating meters. In these instances, we depend on the client to request data access from the energy provider.

How does a collaboration with Å Insite work?

 

Tailoring measurements to your needs

During inspections, the primary objective is to understand 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 main intake, thereby capturing the total energy consumption for the entire installation.

We have experienced customers initially requesting 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.