This is a tale of two buildings, Building A and Building B. Both buildings have electrical and natural gas services provided by their local utility companies, with main physical meters sending energy consumption data to their respective Building Automation System (BAS). The energy management team at each building keeps a detailed accounting of their energy usage, comparing electricity and natural gas consumption with utility bills. Whenever an anomaly in energy consumption causes a spike in their utility cost, each building is challenged to find out why.
However, this proves difficult because more granular data is not readily available to give any indication on which equipment is causing additional energy usage. Building A decides to install sub-meters at several electrical distribution panels throughout their facility. This additional instrumentation would provide a better awareness of how energy is being utilized but, unfortunately, budgetary constraints prevent them from going ahead with this costly investment.
Building B, on the other hand, decides to implement a subscription-based Energy Information System (EIS) in their facility, one with virtual metering capabilities, providing them with an interactive breakdown of energy utilization. One driver in their decision was the estimated 10 to 20 percent potential savings to be achieved when deploying energy management initiatives that include an EIS, according to the Better Buildings Initiative’s publication by the U.S Department of Energy.
Virtual Meters Explained
Virtual metering refers to the leveraging of existing sensor data in order to derive other measurements that aren’t being monitored by real sensors. Virtual meters are also known as soft sensors when describing virtual sensing techniques. Facilities with BAS platforms typically have an array of sensors for measurement and control. For example, with a current transducer monitoring the amperage on a supply fan, the BAS determines if the air handling system needs to enter startup or shutdown mode. A virtual meter, using the general three-phase load equation below, would leverage this amperage value and the motor’s nameplate data in order to calculate its electrical power.
The energy consumption for the above supply fan would be obtained by simply integrating its runtime into the equation. In a similar fashion, a virtual meter for a boiler system could be derived following the law of thermodynamics and its sensible heat equation below. Using existing water flow and temperature sensors connected to the BAS, gas demand in Btu’s per hour and total Btu’s of energy can be easily estimated.
Virtual meters using the same formula above, with different parameters, would estimate the energy required to heat or cool the air supplied by rooftop units and variable air volume units. Yet in other virtual meters, affinity laws would derive demand and energy values using the speed feedback signal from variable frequency drives.
Virtual Meter Benefits
Virtual meters provide feasible and economical alternatives to physical instrumentation. Back to our tale of two buildings, while Building A considered adding sub-meters – a costly solution they couldn’t quite carry on, Building B used an EIS to implement proactive strategies to manage their energy consumption. Virtual metering provided the visibility needed to get an energy breakdown by consumption category – air systems, heating plant, chilled water system and lighting – as well as by individual system and equipment. Virtual metering also provided the ability to determine energy baselines for individual systems using historical data. Once these comparison metrics were available, not exceeding these baselines became the centerpiece to improving the building’s energy performance.
Do you see your organization following Building B’s footsteps? Does the Energy Information System being considered supports virtual metering, meter categorization and baselining? Learn more about the use of EIS platforms in the DOE’s article referenced above.