How Continuous Real-Time Data Helps Streamline Energy Audits

How Continuous Real-Time Data Helps Streamline Energy Audits

Share this Post

 

Conducting regular audits into your facility's energy systems is a key way to boost your efficiency and your bottom line. According to the Department of Energy, implementing facility-wide audit recommendations can decrease total energy costs by 10 - 15%.

For many organizations, however, this process is incredibly daunting, not to mention resource-intensive, requiring additional time, money, and man hours that some businesses simply do not have. Large-scale change is difficult, and an in-depth audit requires massive amounts of accurate data and analysis. After the process is over, analyzing the impact of any changes made is yet another hurdle that requires even more time and labor in order to be effective. To make matters more complicated, all of these processes are vulnerable to human error.

While ASHRAE delineates three standard levels of energy audit, teams that are most effective at discovering and reducing inefficiencies conduct multi-stage, comprehensive audits. Especially for larger facilities, your audit team could be spending large amounts of time conducting thorough investigations.

Fortunately, new technology allows facilities to collect real-time data on all energy usage, effectively streamlining the audit process. Cloud-connectivity allows constant monitoring of all systems and instantaneous recording of all resource usage patterns. Effective use of this data can drastically reduce the amount of time and man-power needed to conduct thorough audits.

 

Below we will address each stage of a hypothetical energy audit process and examine how continuous real-time data can help.

1.Benchmark and examine the facility's profile of resource use.

In this phase, your team is inspecting control systems, such as mechanical and electrical systems, for any waste and potential improvements in efficiency, as well as ascertaining standard energy consumption for other similar facilities.

If your building's usage of electricity, gas, water, and steam is being constantly monitored and recorded, this step is simplified. The usage profile, performance, and cost of each sub-system over time is instantaneously available. If you have access to this data for other similar facilities, the places where your efficiency is low will be clear. It allows easy comparison with the facility's historic usage as well, with guaranteed accuracy and elimination of human error.

2. Locate and Investigate potential opportunities for greater efficiency.

Having precise data for each subsystem's usage allows for clear identification of areas that are drawing more energy than necessary. How would eliminating this inefficiency impact the facility as a whole?

Real-time data shows the impact of load-shedding changes immediately, so there's no need to guess.

3. Implement changes that are cost effective.

Need to change a few light bulbs or upgrade pumping equipment? With access to precise usage data from each subsystem and accurate ROI predictions for each change, you can ensure that you are implementing only the most important changes.

4. Monitor and evaluate the outcome.

By immediately comparing new usage data with old, calculating actual ROI becomes simple. Start by accurately measuring shifts in performance for any electrically powered equipment. Access to aggregated data let’s facilities track changes from the audit over the long-term in order to discover which changes really support long-term savings, rather than just short-term fixes. Verifying the impact of your changes with data will help justify future investments, because nothing inspires stakeholders like clear results.

How IoT smart Building Solutions Can Maximize ROI

After you've established a new benchmark for energy usage, continuously monitoring performance will facilitate your next scheduled audit. In the meantime, it will allow for preemptive maintenance and the assurance of peak efficiency in between audits. Changes in energy draw often occur before equipment failure, so if a system's load increases more than is expected, it might be a sign of deterioration.

 

Advancing Data Collection Strategy Using IoT

Recent Posts