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CopperTree’s Fault Detection and Diagnostics (FDD) Platform for A Long-Term Care Home

CopperTree’s Fault Detection and Diagnostics (FDD) Platform for A Long Term Care Home

A major construction company in North America partnered with CopperTree Analytics to provide building analytics services for a modern long-term care home being built using an innovative accelerated build process.

Yearly Savings
$ 0
Yearly kWh Reduced
0
Homes energy used yearly
0

Our Challenge

To combat the pressures of COVID-19 on this Canadian Province’s long-term care sector, an ambitious plan to build a new long-term care home was formed. What was the challenge? The home was required to be built in months, instead of years that would be commonplace for this type of project. The client’s accelerated build timeline required out-of-the-box thinking and a near-perfect strategy.

The new long-term care home is a six-story, 320-bed state-of-the-art care facility. Designed with health and wellness of residents at the forefront, the home is equipped with a sustainable green roof, courtyards and energy efficient systems.

Given the nature of an accelerated build process, it was critical for the success of the analytics project to integrate with the BAS system quickly and apply analytics on the data to generate actionable findings during the shortened commissioning phase in order to facilitate a clean and error-free turnover to the client and the building’s new residents.

Our Solution

CopperTree’s flexible data integration approach allowed the client to integrate with the BAS while the commissioning work was still ongoing in a phased approach to ensure the project stayed on schedule.

CopperTree’s Kaizen sotware was also tasked with identifying deficiencies from the commissioning process. This meant that, on top of the standard FDD rules, the platform had to be capable of applying custom rules based on the building’s sequencesof operation to identify issues. Kaizen’s Logic Builder functionality was used to implement building-specific rules that were applied on the BAS data to identify issues that would otherwise go unnoticed.

Our Results

Kaizen’s analysis of building data over a period of 2 months resulted in CopperTree Kaizen identifying some key faults equivalent to 213,636 kWh of energy savings and $23,500 potential savings.

  • Among other findings, it was identified that three secondary hot water pumps were running at the same speed whenever the system was operational. Addition of a lead-lag sequence for pump operation along with a review of the differential pressure setpoint was recommended. These strategies will reduce energy consumption but also wear and tear on the mechanical systems, reducing maintenance and the potential for early replacement.

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