John duPont, EnerNOC

Audit timing and execution is typically driven by regular schedules or LEED requirements. Regularly scheduled audits are critical to maintaining a high-performing organization, but it’s also important to conduct audits for another equally essential reason: when building performance data highlights anomalies that need to be addressed.

The industry has converged on three levels of audits based on guidelines created by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE). Regardless of the audit level pursued, the most effective teams take a comprehensive five-step approach to energy audits to unlock the greatest operational efficiencies drive the biggest savings.

Historically, the most challenging aspect of a comprehensive audit approach is the huge time investment required from facilities teams. But effective use of data can drastically reduce the time spent across these five phases:

• Discovery – examining mechanical, electrical, and control systems across the facility to identify energy waste and inefficient operations;

• Investigation – determining whether eliminating the inefficiencies found would negatively impact other systems, or whether they’re isolated problems;

• Evaluation – calculating the impact and cost of each opportunity and deciding on timelines for which to pursue;

• Implementation – executing low-cost operational changes based on audit findings, and planning for longer-term capital upgrades; and

• Verification – ensuring inefficiencies have actually been resolved and getting a clear picture of how much has been saved.

Cutting Discovery and Investigation Time Technology is playing an increasingly critical role in energy management. Energy intelligence software (EIS), for instance, now allows chief engineers to quickly compare consumption in different energy centers (e.g., elevator banks, chillers, hot water pumps) to past performance data, allowing them to move rapidly from “Are the boilers operating efficiently?” to “Why aren’t the boilers operating efficiently?”

Streamlining Evaluation Once the source of the problem is located, and costs of repairs determined, audit teams need to analyze which projects will deliver the highest ROI. Any ROI analysis needs to account for the way the facility is billed for energy from its utility. It’s not as simple as multiplying potential energy consumption savings by blended unit costs: the payback on the same lighting retrofit could vary dramatically based on whether it’s possible to capture the benefit of demand and capacity charge reduction, for example.

(To understand the concept of demand and capacity, think about demand as what’s captured on your speedometer at the moment you hit your max speed. Capacity is typically based on your “peak” energy use during a specific period.)

Most people agree that an ROI analysis incorporating all the different line-items on your electric bills can be daunting. ROI calculated using simple blended cost is industry-standard precisely because it’s so difficult to do it the right way.

As a better solution, EIS meshes energy data with your actual energy tariff information, making it easy to prioritize projects based on true ROI.

Implementing and Verifying Your Projects Faster Too many energy audits end in a report that collects dust on the Director of Engineering’s desk. And even for the most high-performing teams who’ve tackled projects identified in their audits, actually verifying the savings to justify further investment in audits and other projects is tricky.

How do you know whether a reduction in energy consumption was due to your energy projects, based on a reduction in building occupancy, or driven by unseasonably mild weather? Here too, EIS helps by providing the data that you need in the appropriate context to meet measurement & verification (M&V) requirements.

All projects should be measured based on performance against energy baselines, using energy data from the whole building utility meter, system-level sub-meters, or the building automation system. That data should be normalized against the major drivers of change, such as weather and facility occupancy. With quick access to regression models and other M&V tools provided with EIS, audit teams spend less time justifying their savings to upper management and utility program administrators, and more time implementing further projects to make an impact on the bottom line.

John duPont is part of the product marketing team at EnerNOC, Boston, Mass.