A system and method of analysing energy/utility usage receives (316) data describing energy/utility usage derived from an energy/utility monitor, and analyses (2-11) the data describing energy/utility usage to generate data representing an energy/utility usage behavioural classification model. The model includes at least one classification and is useable for determining whether data describing further energy/utility usage fits into a said classification.

A computer-implemented system and method are disclosed for performing engineering review of energy consumption by one or more equipment. One or more computers are connected to a specifications database. The computers are configured to receive end-user configurations corresponding to first equipment; retrieve one or more second equipment, as well as second equipment specifications from the specifications database; calculate an invoicing statement for the second equipment; and provide an engineering review report of the energy savings realized by implementing the second equipment. The first equipment may be an existing equipment, while the second equipment is one or more energy-efficient replacement alternatives to the first equipment. Each step is performed in real-time, using automated software modules and sub-modules. The engineering review report is applicable as an instant approval or pre-approval, qualifying the end-user for purchase incentives, which apply when the energy-efficient equipment alternatives are adopted by the end-user.

The present disclosure provides a computer-implemented method for prioritizing one or more instructional control strategies to reduce time-variant energy demand of a built environment associated with renewable energy sources. The computer-implemented method includes collection of a first set of statistical data, fetching of a second set of statistical data, accumulation of a third set of statistical data, reception of a fourth set of statistical data and gathering of fifth set of statistical data. Further, the computer-implemented method includes parsing and comparison of the first set of statistical data, the second set of statistical data, the third set of statistical data, the fourth set of statistical data and the fifth set of statistical data. In addition, the computer-implemented method includes identification and prioritization of one or more instructional control strategies to reduce the time-variant energy demand associated with the built environment.

Embodiments of the disclosure relate to methods and systems for modeling, controlling and computer-platform implementation of a Synthetic Reserve Provisioning System (SRPS) needed to aggregate and integrate small devices closer to consumers, referred to as Distributed Energy Resources (DERs). This know-how is based on data-driven physics-based modeling and it supports the dispatch and scheduling of DERs so that they can participate in system level provision of electricity service. An SRPS generally comprises multiple levels of consumer aggregators (Synthetic Reserve Provisioning (SRP) modules) which interact by exchanging well-defined information about provable consumer characteristics and their own loading and pricing conditions. Three different SRPS designs are described. They differ with respect to implementation requirements for communications, control, technical and economic risks assumed by different SRP modules. Depending on the control and available communication architecture, it is ultimately possible to ensure DER integration at value, even with a limited number of participating devices.

A method for evaluating energy consumption in an industrial plant, includes capturing sensor data from at least one level of the industrial plant, from the sensor data, digitally obtaining energy consumption curves, an energy consumption curve representing, along a certain time period, discrete values of energy consumption corresponding to time intervals ?t. The method also includes applying a clustering algorithm for digitally computing K energy consumption patterns, wherein each pattern represents a set of energy consumption curves grouped according to a similarity metric and includes discrete values of energy consumption corresponding to time intervals ?t; capturing data of production achieved during the time period at at least one level; calculating the aggregated sum of the discrete values, thus obtaining the aggregated energy consumption for each curve; and digitally establishing a relationship between aggregated energy consumption for each energy consumption curve during the time period and captured data of production.

A method of planning and/or performing an energy industry operation includes estimating variable coefficient of friction (CoF) functions defining the variation of a CoF as a function of a downhole condition dependent on a selected operational parameter of an energy industry operation, the operation including deploying a downhole component configured to perform the operation, each variable CoF function associated with a different value of the selected operational parameter. The method also includes defining a plurality of operational parameters related to the energy industry operation, including choosing a value of the selected operational parameter, and generating a mathematical model of the operation, the mathematical model describing frictional forces on the carrier based on the plurality of operational parameters, the chosen value of the selected operational parameter and the downhole condition, where generating the model includes calculating the CoF based on the variable CoF function associated with the chosen value.

A method for controlling an air handler including a fan, a heater and/or a compressor, by installing an energy saving controller between a thermostat and the air handler, shutting down the compressor or heater for a first predetermined duration if the compressor or heater have run continuously for a second predetermined duration during the current cycle, while allowing the fan to run for a fan's first run time extension amount equal with the first predetermined duration.

Disclosed herein is method and system for determining energy savings target for distributed sites of an entity. Energy profiles of the distributed sites in a service window are identified. Energy coefficients related to the energy profiles are determined by performing optimization of values of operational parameters of the distributed sites. Energy consumption within the service window is predicted using modular transformation of the energy coefficients. Finally, the energy savings target is determined based on modular transformation of the energy coefficients and current energy savings of the distributed sites. The present disclosure discloses a unique framework for defining a generic set of operational energy savings strategies that are applicable to each type of asset and service window of the distributed sites of an entity.

An energy audit system (1400), including at least one controller (1410) which may obtain attribute information (AI) for an energy consuming space, the AI including information related to a plurality of attributes and corresponding attribute choice information for each of the plurality of attributes; determine dependencies of each of the plurality of attributes; determine a ranking of each of the attributes based upon a dependency score of each of the attributes; determine an optimized workflow based upon the ranking of each of the attributes; and/or renders a user interface (UI) in accordance with the optimized workflow.

Method and system for facilitating auditing of power generation and allocation thereof to consumption loads, and a method and system of certifying generation and consumption transactional pairings over a contiguous power grid network. The method of facilitating auditing of power generation and allocation thereof to consumption loads comprises determining respective power generation time series for one or more power sources connected to a power grid; pairing the generation time series with one or more consumption loads connected to the power grid such that one generation time series is paired with one or more consumption loads and vice versa; and publishing publication data representing power generated by the power sources according to the measured power generation time series and an allocation of the generated power to the consumption loads.