Gridpoint, Inc.

Admmicro Properties, L.l.c.

Danny K Dyess

Mark Wayland Vinson

Arnie J Tamagni

Gerald Zingraf

Deepak Budhiraja

Armand J Tamagni, Jr

Donald W Howell

Frank Oakley Blevins

Samuel A Taylor

The invention involves the automated testing of HVAC units using an energy management system. The automated HVAC test is performed to understand if one or more HVAC units are operational across one or more locations. If an HVAC unit is not operational, HVAC testing could be performed to understand which component or stage of the HVAC unit is not working as designed. The automated HVAC test is also used to calculate the efficiency of the HVAC unit(s) being tested. The various HVAC tests are performed on all HVAC units as a form of preventative maintenance and diagnostics. These tests can be scheduled on-demand, for a future date and time, or on a recurring schedule (monthly or quarterly). A report is generated for each HVAC test and can be viewed and exported from a cloud-based energy management platform.

Methods and systems for automated HVAC testing

A system and method are disclosed for dynamically learning the optimum energy consumption operating condition for a building and monitor/control energy consuming equipment to keep the peak demand interval at a minimum. The dynamic demand limiting algorithm utilized employs two separate control schemes, one for HVAC loads and one for non-HVAC loads. Separate operating parameters can be applied to the two types of loads and multiple non-HVAC (control zones) loads can be configured. The algorithm uses historical peak demand measurements in its real-time limiting strategy. The algorithm continuously attempts to reduce peak demand within the user configured parameters. When a new peak is inevitable, the algorithm strategically removes and/or introduces loads in a fashion that limits the new peak magnitude and places the operating conditions within the user configured parameters. In an embodiment, the algorithm that examines the previous seven days of metering information to identify a peak demand interval. The system then uses real-time load information to predict the demand peak of the upcoming interval, and strategically curtails assigned loads in order to limit the demand peak so as not to set a new peak.

Dynamic load curtailment system and method

A system that dynamically learns the optimum energy consumption operating condition for a building and monitors/controls energy consuming equipment to keep the peak demand interval at a minimum. The algorithm employs two separate control schemes, one for HVAC loads and one for non-HVAC loads, and uses historical peak demand measurements in its real-time limiting strategy. The algorithm continuously attempts to reduce peak demand within user configured parameters. When a new peak is inevitable, the algorithm removes and/or introduces loads to limit the new peak magnitude and places the operating conditions within the user configured parameters. The algorithm can examine the previous seven days of metering information to identify a peak demand interval, use real-time load information to predict the demand peak of the upcoming interval, and curtail loads in order to limit the demand peak so as not to set a new peak.

A current transformer assembly includes at least one Rogowski coil having a first closeable loop with an electrically conductive coil member and a first pair of terminals. An integrator unit has respectively a cable connected across the first pair of terminals of a respective Rogowski coil. Each respective Rogowski coil provides an output voltage received by the integrator assembly caused by when a respective electrical conductor on a phase of a multiphase circuit is arranged within an opening of the closeable first loop of the respective Rogowski coil, and provides an output signal proportional to a current in a conductor arranged in an opening of a Rogowski coil. At least one of the Rogowski coils includes an inline calibration unit for fast calibration and recalibration when retrofitting a monitor module that monitors a value of the current in one or more conductors.

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Roanoke, VA, United States of America

Danny K Dyess