Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.