Abstract: Methods and systems are described for detecting a wide variety of fault conditions in a HVAC system based on analysis of current and historical energy consumption patterns, and on comparison with energy consumption patterns of other similarly situated RTUs. Energy consumption comparisons are preferably made in regard to a normalized load ratio or NLR or more preferably to a daily maximum normalized load ratio or MDNLR, which provide more robust and reliable bases for comparison of faulty and fault-free RTUs, and hence for generalized fault detection, than other previously known metrics or criteria.

Abstract: Methods and systems are described for detecting a wide variety of fault conditions in a HVAC system based on analysis of current and historical energy consumption patterns, and on comparison with energy consumption patterns of other similarly situated RTUs. Energy consumption comparisons are preferably made in regard to a normalized load ratio or NLR or more preferably to a daily maximum normalized load ratio or MDNLR, which provide more robust and reliable bases for comparison of faulty and fault-free RTUs, and hence for generalized fault detection, than other previously known metrics or criteria.

Abstract: Systems and methods for orchestrating the operation of energy-consuming loads, so as to minimize power consumption, are described. In some embodiments, the loads can be HVAC, refrigeration systems, air compressors, and the like, and orchestration is effected either directly or by means of the loads' respective controllers. In some aspects, the controllers can be Smart Thermostats and orchestration is effected through a Cloud-based orchestration platform or “COP.” In certain aspects, a COP uses specifically programmed application programming interfaces, or APIs, to control the operation of a single manufacturer's Smart Thermostats, where the manufacturer provides its own Cloud-based control platform, through which the COP operates. The COP can similarly orchestrate the operation of two or more manufacturers' Smart Thermostats through their respective Cloud-based control platforms. By these and other means, the operation of a variety of energy-consuming loads can be more easily and efficiently orchestrated.

Abstract: Systems and methods for orchestrating the operation of energy-consuming loads, so as to minimize power consumption, are described. In some embodiments, the loads can be HVAC, refrigeration systems, air compressors, and the like, and orchestration is effected either directly or by means of the loads' respective controllers. In some aspects, the controllers can be Smart Thermostats and orchestration is effected through a Cloud-based orchestration platform or “COP.” In certain aspects, a COP uses specifically programmed application programming interfaces, or APIs, to control the operation of a single manufacturer's Smart Thermostats, where the manufacturer provides its own Cloud-based control platform, through which the COP operates. The COP can similarly orchestrate the operation of two or more manufacturers' Smart Thermostats through their respective Cloud-based control platforms. By these and other means, the operation of a variety of energy-consuming loads can be more easily and efficiently orchestrated.

Abstract: Systems and methods for orchestrating the operation of energy-consuming loads, so as to minimize power consumption, are described. In some embodiments, the loads can be HVAC, refrigeration systems, air compressors, and the like, and orchestration is effected either directly or by means of the loads' respective controllers. In some aspects, the controllers can be Smart Thermostats and orchestration is effected through a Cloud-based orchestration platform or “COP.” In certain aspects, a COP uses specifically programmed application programming interfaces, or APIs, to control the operation of a single manufacturer's Smart Thermostats, where the manufacturer provides its own Cloud-based control platform, through which the COP operates. The COP can similarly orchestrate the operation of two or more manufacturers' Smart Thermostats through their respective Cloud-based control platforms. By these and other means, the operation of a variety of energy-consuming loads can be more easily and efficiently orchestrated.

Abstract: Systems and methods for orchestrating the operation of energy consuming loads so as to minimize power consumption are described. In some embodiments, the loads can be HVAC, refrigeration systems, air compressors, and the like, and orchestration is effected either directly or by means of the loads' respective controllers. In some aspects, the controllers can be Smart Thermostats and orchestration is effected through a Cloud-based orchestration platform or “COP.” In certain aspects, a COP uses specifically programmed application programming interfaces or APIs to control the operation of a single manufacturer's Smart Thermostats, where the manufacturer provides its own Cloud based control platform through which the COP operates. The COP can similarly orchestrate the operation of two or more manufacturers' Smart Thermostats through their respective Cloud based control platforms. By these and other means, the operation of a variety of energy consuming loads can be more easily and efficiently orchestrated.

Abstract: A method for managing an energy consuming load in a group of energy consuming loads and a method for managing the group of energy consuming loads. The method includes generating sets of load state data from the loads, making enablement state decisions for one or more loads using the sets of load state data, and implementing the enablement state decisions. Each of the enablement state decisions reflects an enablement state of a load, wherein the enablement state is either a load enabled state where the load is capable of operating even when the load is not actually operating or a load disabled state where the load is not capable of operating. A computer readable medium may include computer readable instructions for directing a processor to perform the methods and make the enablement state decision. Further, an apparatus comprised of a processor may be programmed to perform the methods.

Abstract: Systems and methods for orchestrating the operation of energy consuming loads so as to minimize power consumption are described. In some embodiments, the loads can be HVAC, refrigeration systems, air compressors, and the like, and orchestration is effected either directly or by means of the loads' respective controllers. In some aspects, the controllers can be Smart Thermostats and orchestration is effected through a Cloud-based orchestration platform or “COP.” In certain aspects, a COP uses specifically programmed application programming interfaces or APIs to control the operation of a single manufacturer's Smart Thermostats, where the manufacturer provides its own Cloud based control platform through which the COP operates. The COP can similarly orchestrate the operation of two or more manufacturers' Smart Thermostats through their respective Cloud based control platforms. By these and other means, the operation of a variety of energy consuming loads can be more easily and efficiently orchestrated.

Abstract: Methods and systems are described for detecting a wide variety of fault conditions in a HVAC system based on analysis of current and historical energy consumption patterns, and on comparison with energy consumption patterns of other similarly situated RTUs. Energy consumption comparisons are preferably made in regard to a normalized load ratio or NLR or more preferably to a daily maximum normalized load ratio or MDNLR, which provide more robust and reliable bases for comparison of faulty and fault-free RTUs, and hence for generalized fault detection, than other previously known metrics or criteria.

Abstract: A method for managing an energy consuming load in a group of energy consuming loads. The method includes generating and compiling sets of load state data from the load and other loads, making an enablement state decision for the load using the compiled sets of data, wherein the enablement state decision reflects either a load enabled or load disabled state, and implementing the enablement state decision for the load. An apparatus for managing an energy consuming load in a group of energy consuming loads, including a transmitter for transmitting the set of load state data from the load, a receiver for receiving sets of load state data from other loads, a processor for processing the load state data to make an enablement state decision, and a controller for implementing the decision. A computer readable medium provides computer readable instructions for directing the processor, wherein the instructions perform the method.