A plurality of data sets are compiled in a memory. A first data set comprises a location mapping of an item of interest within a predetermined environment, and a second set comprises energy usage data within the predetermined environment. The first data set is correlated, via a processor, with the second data set to locate a subset of energy usage data in the second data set associated with the item of interest. A third data set is generated by combining the first data set with the subset of energy usage data in the second data set to increase an accuracy of the location mapping of the item of interest based upon the subset of energy usage data. The third data set is applied to a computing resource.

Dynamic tiering of datacenter power for workloads is disclosed. A power capacity, including redundant power capacity and granular power capacity values within a datacenter, is determined. An outage time duration requirement for the power capacity that was determined is evaluated, where the outage time duration requirement is a number of minutes. A hold time duration requirement for the power capacity is evaluated, where the hold time duration is a number of minutes. A number of allowable occurrences of power outage for the power capacity is evaluated. A power requirement metric, based on the outage time duration requirement, the hold time duration requirement, and the number of occurrences, is calculated. A power topology within the datacenter is modified based on the power requirement metric. The modifying provides dynamic power tiering within the datacenter. The dynamic tiering includes a variable service level agreement for power within the datacenter.

A method evaluates power engineering data using a data request that is transmitted to a coupling device by a first communication link. The coupling device is used to convert the data request from a coupling data format into a further data request that is specific to an energy engineering device in a device-specific data format. The further data request is transmitted to the power engineering device by a second communication link. The power engineering device transmits its power engineering data, requested by the further data request, to the coupling device by the second communication link. The power engineering data are in a data format that is specific to the power engineering device, and the coupling device converts all the power engineering data requested by further data requests into a data response in the coupling data format and uses the first communication link to transmit them to the evaluation device.

A system and method for performing power conservation actions is described. In some examples, the system determines a power conservation policy based on information from the system, and implements that policy in an enterprise or in one or more buildings, such as within a data storage environment. In some examples, the system adds or modifies global filters or system performance based on information from the system.

A system that allows a contractor to remotely monitor and/or interact with its customers' building control systems, such as heating, ventilating and air conditioning (HVAC) systems, and analyze information obtained from the building control systems over time. Such a system may help the contractor monitor and diagnosis customer building control systems, setup service calls, achieve better customer relations, create more effective marketing opportunities, as well as other functions. In some cases, the disclosed system may include a controller that analyzes data from HVAC systems, determines a thermal model of a space environmentally controlled by an HVAC system, and provides an energy audit of the space that is environmentally controlled by the HVAC system. The controller may output a result of the energy audit to a user.

A method monitors the energy cost for the production of a product lot using a manufacturing execution system (MES) that enables the operator of a production facility to optimize the production process in terms of energy costs. The method includes a) executing a production process being scheduled and controlled by the MES to produce the product lot; b) for each individual production step measuring the energy consumption over the course of the execution of the individual production step; c) creating a data model within the MES that correlates production specific data and the energy consumption data related to the product lot; d) defining commands to manage the production specific data and the energy consumption data wherein the commands are web APIs; and e) evaluating the production specific data and the energy consumption data and creating an energy consumption profile for the production process related to the product lot.

Described herein are methods and systems, including computer program products, for determining a load control schedule for energy control devices using a load shifting optimization model and applying the load control schedule to adjust the energy control devices. A server receives thermodynamic models, energy price data and energy load forecast data. The server generates price probability distribution curves based upon the price data and load probability distribution curves based upon the load forecast data. The server executes a load shifting optimization model to determine a profit probability distribution curve for demand response decision rules. The server determines a profit curve that has an optimal profit value. The server generates a load control schedule based upon the optimal profit curve and generates operational parameters for energy control devices using the load control schedule. The server transmits the operational parameters to the energy control devices to adjust operational parameters.

A computer-implemented method and system is provided. The system manipulates load curves corresponding to time-variant energy demand and consumption of a built environment. The system analyzes a first, second, third, fourth and a fifth set of data. The first set of data is associated with energy consuming devices. The second set of data is associated with an occupancy behavior of users. The third set of data is associated with energy storage and supply means. The fourth set of data is associated with environmental sensors. The fifth set of data is associated with energy pricing models. The system executes control routines for controlling peak loading conditions associated with the built environment. The system manipulates an optimized operating state of the energy consuming devices. The system integrates the energy storage and supply means for optimal reduction of the peak level of energy demand concentrated over the limited period of time.

A system for managing devices supplied through a power grid is proposed. Each device is configured to consume over time electric power according to at least one respective power profile when operating. The system comprises at least one unit interfaced with the devices for exchanging data. The at least one unit collects power profile data indicative of the power profiles of the devices, and generates a time schedule of the device operations by distributing over time start times of the power profiles in such a way that at any time the total power consumption of the devices is kept under a maximum power threshold of the power grid.

The invention teaches a system and method for reducing energy consumption in commercial buildings. The invention provides development of certain mechanical heat profiles and use of such profiles in an automated optimization method. Outputs communicate with the building management system of the commercial building, and regulate the heating system during a season when the building activates the heating system. Various embodiments are taught.