HK1171089B - System and method for energy consumption management - Google Patents

Description

System and method for energy consumption management

Technical Field

The present invention relates generally to systems and methods for energy management, and more particularly to an overall energy optimization and efficiency system and method that provides a process for optimizing energy generation and storage technologies, energy consumption of energy consuming assets within a building, energy demand, and energy utilization.

Background

Based on data from the energy intelligence agency ("EIA"), residential and commercial end users consume over 40% of all electricity produced in the united states. At the same time, the section of energy ("DOE") estimates that current low energy efficiency in buildings results in as much as 40% of the power system losses.

While in the past decade residential users have experienced increases in efficiency through advances in technology in appliances and HVAC ("heating, ventilation and air conditioning") systems, these increases have been substantially offset by a 40% increase in the number of dwellings, a 49% increase in air conditioning usage, a 72% increase in the size of dwellings, and a steady increase in the number of household electronics used. An average us household now has 26 consumer electrical products, and an estimated presence of 124,000,000 us residences. It is expected that 1500 million new commercial buildings will be built in the next decade.

Furthermore, the global demand for fuel sources (such as coal and natural gas), the increase in more power generation capacity, and the required investment in new transmission and distribution infrastructure will only push the energy prices even higher than on the market today. Renewable and traditional energy supply construction costs are rising overall, energy fuel costs are rising, operating costs are increasing, and significant costs for clean climates can soon be expected.

With ever increasing levels of energy consumption and continued increases in energy costs, laws and regulations on energy efficiency, renewable energy supply, and carbon emissions have led utility entities to seek new technologies to deliver affordable, low-carbon, reliable energy supplies to their consumers. There is a continuing increase in political and economic pressures to reduce carbon emissions and protect the climate from global warming.

For example, national economic re-investment and recovery incentive programs include over 400 billion dollars in invested development of technologies that make countries more energy efficient. This figure represents a 10-fold increase in annual federal investment for energy efficiency over any of the past years. More than 60 billion dollars are expected to be used to improve home energy efficiency and expand the energy efficiency programs of the current state. A special "split" provision is included in the plan to ensure to the utility entity that if the end user consumes less power due to the end user energy efficiency project of the utility entity, the revenue lost by the utility entity will be compensated for.

In addition, the 2005 U.S. energy policy act encouraged the adoption of energy pricing time of use ("TOU") rates to adjust end user consumption behavior, reduce the need for expensive peak power generation, and effectively improve grid utilization. Implementing these strategies requires smart meters and advanced metering infrastructure ("AMI"). The government estimated that 5000 million advanced meters will be in the pipeline by 2010, meaning that the utility entity invests an estimated 10 billion dollars.

The 2007 energy independence and safety scheme supports the establishment of smart grids through the modernization of national power transmission and distribution systems. It is estimated that between 2010 and 2030, a utility entity will invest $ 1.5 trillion in the transport and distribution infrastructure. In the next half of 2008, $ 2.75 billion new private risk funds were invested in companies that developed and manufactured communication networks and other technologies for smart grid solutions.

In general, these smart grid proposals aim to improve the efficiency of the utility entity production and delivery infrastructure. Smart grid and demand response methods and techniques are designed to reduce peak energy demand by consumers. For example, attempts to reduce the total energy consumption used by a dwelling at a particular point in time by rejecting or restricting users of powered devices, but these techniques do not reduce the total energy consumption. Furthermore, these proposals do not affect the aspect of the overall system that contributes most to energy waste, i.e. the low energy efficiency found in buildings and homes.

Furthermore, conventional systems, such as energy management systems, building automation systems, smart meters, home automation systems, in-home displays, programmable communication thermostats, and DDC/air control systems, employ a single method for control and management, focusing only on the performance of a single electrical component asset, or possibly a group of assets, to which it is attached. These conventional systems rely on the occupancy occupant or the occupancy facility manager to understand and input the correct parameters to the control system for proper operation. In addition, these systems require that these parameters be updated as conditions or premise environments change, which requires that premise occupants or premise facility managers have extensive knowledge and knowledge of energy center data facts such as current weather, future weather, current energy price conditions, future energy price conditions, other asset utilization, and interactions between current assets and other premise assets.

Disclosure of Invention

Accordingly, the continued presence of energy waste and inefficiency in the overall power supply system, as well as in residential and commercial buildings, provides the power industry with a number of significant opportunities to conserve energy, reduce carbon emissions, and increase profits. The effects of these losses are superimposed on the energy supply chain, not only forcing the need to generate larger and larger quantities of electricity, but also requiring careful study of the engineering of the transmission and distribution grid infrastructure to meet the resulting higher peaks in energy demand. These inefficiencies result in significant unnecessary costs in the production, distribution and consumption of electricity, as well as the undesirable generation and release of larger amounts of harmful carbon emissions.

Based on current energy consumption prospects, it is clear that energy efficiency is a central strategy to meet energy and climate needs. In addition, no single item or new technology is sufficient to address these challenges. Meeting the demand for affordable, low-carbon energy (electricity) is a challenge with unprecedented complexity. The country can achieve these goals only with a large investment in energy efficiency and renewable energy supply sources.

There is a need for an integrated approach that can predict and/or dynamically adjust operation and performance based on changes in consumer behavior, market or weather conditions, grid infrastructure constraints, and stakeholder programs. A straightforward, practical, low-cost approach to achieve significant, sustainable near-term improvements is provided by applying the technology to clean technologies, zero-emission, alternative sources that eliminate/minimize energy waste and improve energy efficiency to create an energy supply source. Achieving this improvement through a highly interoperable and intelligent platform placed in the dwelling provides a means for integrating and accelerating adoption of key technologies needed to ensure energy supply safety, reduce carbon emissions, eliminate waste, and sustain efficiency improvements.

The energy management system and method disclosed herein provides an integrated residential energy optimization and energy efficiency recovery system, including an interconnected system of software, analysis, and automation processes, that optimizes energy generation and storage technology, energy consumption of energy consuming assets within the residential dwelling, energy demand, and energy utilization.

In addition, the energy management system and method utilizes analytics and software to create an overall intelligent software system and application components that operate independently and automatically, in conjunction with existing and future energy consuming devices and appliances assembled and installed within the dwelling, to optimize the lifecycle and energy efficiency performance of the dwelling-based energy generation and storage technology. Effectively providing a highly interactive, intelligent process that supports and continuously adapts to the behavior and needs of a residence occupant to meet and maintain desired conditions of comfort and reliability by eliminating energy waste, maximizing the energy efficiency potential of the existing installation base of appliances and devices, avoiding corresponding carbon emissions, and reducing peak residence energy demand requirements, while minimizing costs to consumers and to utility entities.

Drawings

FIG. 1 illustrates a block diagram of an energy management system according to an example embodiment.

FIG. 2 illustrates a block diagram of an energy management control center according to an example embodiment.

Figure 3 illustrates a residential automation network according to an example embodiment.

FIG. 4 illustrates a block diagram of an energy management computer, according to an example embodiment.

FIG. 5 illustrates a block diagram of a sensor/controller according to an example embodiment.

Fig. 6 illustrates a flow chart of a method for managing energy consumption according to an example embodiment.

FIG. 7 illustrates a flow diagram of example data analysis, according to an example embodiment.

Detailed Description

The following detailed description sets forth possible embodiments of the described energy management systems and methods for exemplary purposes. As described below, the systems and methods disclosed herein provide a fully-contained, web-based solution that works automatically behind scenes in residential or commercial buildings to eliminate energy waste and optimize energy usage within consumer-defined rules. The systems and methods disclosed herein include the following capabilities: consumer behavior and external influences, such as market, weather, grid infrastructure constraints, regulatory requirements, etc., are learned and adapted in real time or otherwise to maintain and continuously improve energy conservation.

Fig. 1 illustrates a block diagram of an energy management system 100 according to an example embodiment. As shown, energy management system 100 establishes a functional relationship between energy management control center 102, manager/stakeholder 104, and an end user located at premises 106. Fig. 1 illustrates different levels of users that the energy management system 100 may support. The administrator/stakeholder 104 may be a utility provider, a title manager, a title developer, an integrator, a community/state/local agent, and the like. An end user at dwelling 106 may be the owner/resident of dwelling 106, and dwelling 106 may be a residence/dwelling, business dwelling, or the like.

Energy management system 100 provides an integrated set of web-enabled smart control devices, data acquisition sensors, diagnostic and performance algorithms, and adaptive software installed in premise 106, which cooperate with centralized and distributed energy management modules provided by energy management control center 102 to provide user-defined options of comfort, reliability, and cost, while reducing energy demand, usage, and carbon emissions at premise 106.

In operation, transaction data (e.g., energy consumption data) obtained from sensors, mobile clients, and/or controllers is sent to the energy management control center 102. As described in detail below, such transactional data may include performance and usage of HVAC systems, lighting, water heaters, refrigerators, large appliances, and so forth. Effectively, energy management control center 102 is provided with sufficient data to learn the habits, procedures, and routines of the end user and the energy consuming devices operating at premises 106. In addition, energy management control center 102 is configured to efficiently and continuously collect data external to dwelling 106, such as energy market conditions, weather conditions, grid infrastructure constraints, regulatory requirements, and the like. Using some or all of the acquired data, energy management control center 102 is configured to combine, normalize, and analyze the acquired data in conjunction with data previously acquired and stored in energy management control center 102 and generate instructions that provide optimized results for energy consumption at premise 106. Based on the optimization results, energy management control center 102 generates control instructions that are sent back to the sensors, devices, mobile clients and/or controllers to automatically and dynamically adapt the energy assets of the dwelling to provide a more comfortable and reliable environment while substantially eliminating energy waste and significantly reducing energy usage. Effectively, energy management control center 102 is configured to automatically take action to eliminate energy waste and maximize the performance of dwelling 106. This process is preferably performed periodically (e.g., 1 to 10 times per minute) to achieve an optimal set of results desired by the end user and/or administrator/stakeholder 104.

In addition, energy management control center 102 provides an energy management enterprise portal 108 to provide a web-based user interface to end users and/or managers/stakeholders 104. The ess control center 102 includes all hardware and software modules (not shown) necessary to provide a web portal (i.e., the ess portal 108) for a user to interact with the ess control center 102. Specifically, energy management enterprise portal 108 is created for all interactions and configurations within energy management system 100. Thus, energy management enterprise portal 108 provides a core visualization service that serves as a mechanism for providing all of the user interface data. Both the end user at home 106 and administrator/stakeholder 104 have access to all business logic, analysis results, and reports from this portal 108. This portal 108 is utilized by energy management control center personnel for all day-to-day and/or management functions. In particular, energy management enterprise portal 108 enables managers/stakeholders 104 to view data, perform activities, expand networks (i.e., add users and/or add devices, etc.), and all other functions of the system as dictated by its secure login to the system, such as backup/restore, disaster recovery, and server migration. In addition, each end user at their respective premises 106 may view the data and interact with energy management control center 102 (e.g., set energy consumption rules/preferences), but preferably is not able to perform the management functions performed by manager/stakeholder 104.

More specifically, the end user may set energy consumption rules/preferences for the desired performance of the energy consuming devices at dwelling 106. Further, the user interface provided to the end user is preferably an infinite number of tiles (tiles) allowing for specified interaction with the active platform 214, as will be described in detail below. All activities create a feedback loop from the activity platform 214 to the end user interface and ultimately back to the activity platform 214. Thus, this functionality enables a real-time view of all items involved in one or more activities. In addition, the portal is the primary interface for end users to log in and set up and check the configuration, usage patterns, and account status of their residences.

In an example embodiment, energy management enterprise portal 108 creates a security checkpoint to verify, authenticate, or authorize user transactions on energy management system 100. The sign-on portal is capable of performing all required site level operations, all required batch or group site operations, and serves as the primary tunnel for real-time reading of the energy management system 100 as described above.

Moreover, in another refinement of the embodiment, energy management enterprise portal 108 utilizes an interactive platform designed according to licensed social networking technology, notifies the consumer of the achieved results, and suggests to the consumer further improvement opportunities that may be performed. This platform helps to keep consumers engaged in easy management of their residences 106, as well as providing a user interface that enables users to continue to provide critical information to the utility entity. In such a refinement of the example embodiment, the web interface provided to the end user creates an friendly competitive platform that enables the end user to participate in the energy efficiency and carbon footprint (football) reduction. The energy management control center 102 is configured to capture and report benefits (financial or otherwise) from these energy reductions. Thus, end users who wish to play a positive role in their energy management/consumption are provided with the ability to do so.

In yet another refinement, energy management enterprise portal 108 is configured to create a personal energy efficiency "family" page or a "building" page for each end user on the internet. The "page" is provided to aggregate energy saving advice or observations about energy usage by the end user. In addition, end users may connect to each other to provide the delivery of know-how and knowledge, and may easily connect with energy management control center personnel to assist them. Portions of the energy management enterprise portal 108 are also configured to integrate to other social networking sites (e.g., such as) Enabling the user to show themselves in terms of efficiency growth and carbon footprint reduction.

Fig. 2 illustrates a detailed block diagram of the energy management control center 102 according to an example embodiment. As discussed in detail below, energy management control center 102 includes hardware and software modules configured to store data acquired by each of dwellings 106 and received by energy management control center 102. In addition, the energy management control center 102 includes hardware and software modules that enable it to combine, normalize, and analyze the acquired data in connection with external data streams, such as weather, current energy price conditions, future energy price conditions, other asset utilization, and interactions between current assets and other residential assets. Accordingly, it will be appreciated that the energy management control center 102 includes the necessary servers, databases, I/O interfaces, processors, etc. to implement the functions/components discussed below. These hardware components are known to those skilled in the art and are not described in detail so as not to unnecessarily obscure the description of the energy management control center 102 herein.

As shown, the ems control center 102 includes: a communication interface 202 configured to receive data from sensors, devices, mobile clients, and/or interface 202 located at each dwelling 106. In an example embodiment, communication interface 202 may be configured to communicate with dwelling 106 using standard TCP/IP Internet protocol or the like. In one refinement, the communication interface 202 may be implemented as an XMPP gateway configured to receive real-time transaction data. Note that communication interface 202 includes all hardware and software modules (not shown) necessary to enable communication between energy management control center 102 and a remote entity, such as premise 106. These communications hardware components may include conventional I/O interfaces such as modems, network cards, and the like. Such hardware components and software applications are known to those skilled in the art and have not been described in detail so as not to unnecessarily obscure the description of the systems herein.

It should be appreciated that any conventional web service may be employed to enable data communication between energy management control center 102, manager/stakeholder 104 and/or residence 106. The term "web service" as used herein is provided to describe a typical application programming interface ("API") or webAPI that is accessible over a network (e.g., the Internet) and executes on a remote system hosting the requested service. For example, in one refinement, the term "web service" refers to clients and servers that communicate via the hypertext transfer protocol ("HTTP") protocol used on the web. However, for purposes of this disclosure, any application that enables information exchange, diagnosis, and control may be used for this purpose, and is not limited to any particular protocol. In one refinement, the implemented web service is preferably designed to be runningThe operating system runs on a blade (blade) type server that is energy efficient, so that web services can be quickly scaled to meet the needs of a growing installation base simply by adding blades to the blade locker.

As further shown in fig. 2, the energy management control center 102 includes a data store 204 (i.e., a real-time data store or an operational data store, etc.) that provides for storing current values of one or more sensors, devices, mobile clients, or controllers implemented by the energy management system 100 to provide the energy management control center 102 with access to such data. The data store 204 also provides for ensuring that the current system reading before the optimization results are generated verifies that the conditions have not changed to a state that would significantly change the expected optimization results.

The energy management control center 102 also includes a cloud data store 206 (e.g., Cassandra cloud data store) configured as a primary data store for the energy management control center 102. Preferably, cloud data storage 206 utilizes key/value pairs to quickly store large amounts of information with extremely fast read and write times. Effectively, cloud data storage 206 is provided to enable fast reading of input data and storage of data in a structured storage model.

The energy management control center 102 provides a validation rules engine 208, and those skilled in the art will appreciate that the validation rules engine 208 is configured to validate each data element by one or more of the following tests: 1) static limiting; 2) a single value threshold; 3) percentage of change in value; 4) a percentage of difference values to related data objects; 5) a range of standard deviations; 6) a slope differential; 7) a numerical threshold; 8) subject completeness (integrity); 9) and others. Once the received transaction data passes this validation step, it is used in a decision process to produce an optimized result, as discussed below.

The ems control center 102 further includes a unified data repository 210 configured as transactional data storage for the ems 100, storing inputAll history of data, current system components, and optimization results performed. More specifically, the unified data repository 210 is configured to store customer preferences, historical energy usage and device performance data, manufacturer device specifications, market rules, utility rates, weather data, and the like. The unified data warehouse 210 is configured to support analysis, optimization, and data mining for the continuous energy efficiency improvements provided by the energy management system 100. Effectively, the unified data repository 210 serves as a central repository for electronically stored data for the energy management control center 102. Further, it should be understood that the unified data repository 210 may be managed by any suitable software. For example, in an example embodiment, the unified data store 210 is built from generic SQL, and may be in Microsoft SQLOrAnd (4) running.

The ems control center 102 also includes an optimization engine 212 configured to perform the required data calculations for the ems 100. As discussed in detail below, the optimization engine 212 is configured to retrieve and analyze data stored in the unified data warehouse 210 and create new data points as calculations are performed per the requirements of each individual implementation. Preferably, these computations are infinitely nested, providing an infinite ability to create new computation data points.

The energy management control center 102 also includes an activity platform 214 as described above. Once all data is received via communication interface 202, data store 204, cloud data store 206, validation rules engine 208, unified data repository 210, and optimization engine 212 and stored in energy management control center 102, energy management system 100 may be considered to have the existing status of all sensors, devices, mobile clients, or controllers at each premise 106 and the user rules/preferences of the managers/stakeholders 104 and end users at premise 106. Accordingly, the activity platform 214 is configured to enable the respective user to execute pre-compiled routines that represent all of the bundled business rules for standard and enhanced energy management. These activity types include traditional methods of demand reduction (e.g., demand response) and more advanced and emerging energy management methods (e.g., energy optimization). Since an activity is defined as a set of business rules that operate the rules engine 216, new activity types and new activities may be defined for respective users in real-time via the portal 108. Preferably, these activities serve as energy management improvements for the performance of energy management and validation, meaning that each activity becomes a measure of energy demand or energy consumption reduction, where the total energy reduction at any single dwelling is equal to the sum of the energy reductions from all involved activities.

As described above, the energy management control center 102 includes an operation rules engine 216, the operation rules engine 216 configured to perform further validation by linking to the validation rules engine 208. For example, operational rules engine 216 provides "IF Then Else" logic for all connected sensors, devices, mobile clients, or controllers of each dwelling 106. Thus, the operation rules engine 216 reads nodes from the unified data repository 210 and executes corresponding user-defined business rules across independent sensors, devices, mobile clients, or controllers.

Finally, energy management control center 102 includes a service and delivery platform 218, and service and delivery platform 218 is configured to push the overall optimization results to any other connected node (i.e., sensor, device, mobile client, or controller of the respective premises 106). It should be appreciated that service and delivery platform 218 operates in conjunction with communication interface 202, and that communication interface 202 is further configured to deliver optimization results to dwelling 106 using standard TCP/IP Internet protocol, or the like.

Fig. 3 illustrates a home automation network 300 according to an example embodiment. As described above, premise 106 is configured to communicate with energy management control center 102. As shown in fig. 3, a home automation network 300 may be installed at a home 106. In particular, the home automation network 300 includes an energy management computer 302 and a plurality of sensors, devices, mobile clients and/or controllers 304 and 316 (described in detail below). The home automation network 300 is designed to gain effectiveness through techniques that allow for automatic performance of tasks that end users traditionally perform manually. Advantageously, the home automation network 300 is user friendly in that it does not require the user to change any current mode or routine.

During installation, residence automation network 300 is preferably implemented over the existing power wiring of residence 106 such that energy management computer 302 may communicate with a plurality of sensors, devices, mobile clients and/or controllers 304 and 316 over the existing electrical infrastructure. Conventional power line communication or power line carrier ("PLC") technology is a known, reliable network technology infrastructure application deployed in commercial and residential applications for carrying data on conductors that are also used for power transmission. Note that although only 7 types of sensors, devices, mobile clients, and/or controllers are shown in FIG. 3, it will be readily appreciated from the detailed description herein that the specific number of components in a given dwelling is not limited.

Using PLC technology, energy management computer 302 is configured to receive transaction data measured by a plurality of sensors, devices, mobile clients and/or controllers 304 and 316 using the existing electrical infrastructure in dwelling 106. To implement PLC technology in the exemplary embodiment, the network protocol used within the home automation network 300 is preferably a protocol standardized by the international organization for standardization ("ISO"), see the following:

●ISO/IEC 14908-1：Open Data Communication in BuildingAutomation，Controls and Building Management-ControlNetwork Protocol-Part 1：Protocol Stack.

●ISO/IEC 14908-2：Open Data Communication in BuildingAutomation，Controls and Building Management-ControlNetwork Protocol-Part 2：Twisted Pair Communication.

●ISO/IEC 14908-3：Open Data Communication in BuildingAutomation，Controls and Building Management-ControlNetwork Protocol-Part 3：Power Line Channel Specification.

●ISO/IEC 14908-4：Open Data Communication in BuildingAutomation，Controls and Building Management-ControlNetwork Protocol-Part 4：IP Communication.

in an alternative embodiment, energy management computer 302 is configured to use a wireless communication protocol, such as fromAvailable ofA wireless communication protocol,Etc., with a plurality of sensors, devices, mobile clients and/or controllers 304 and 316. Thus, it should be appreciated that energy management computer 302 may implement any existing protocol stack that enables energy management computer 302 to communicate with any auxiliary network protocol implemented by residence automation network 300.

FIG. 4 illustrates a detailed block diagram of energy management computer 302 according to an example embodiment. As described above, energy management computer 302 serves as a supervisory and gateway device for each respective premise automatic network 300 for the particular premise 106 in which energy management computer 302 is installed.

In the preferred embodiment, energy management computer 302 is a single board computer that includes all of the hardware and software components necessary to perform the functions of energy management system 100. Note, however, that the functionality of energy management computer 302 may be implemented in software. In a software implementation, the energy management software may be installed on a legacy host system, such as any type of laptop computer, desktop computer, microprocessor, etc., that may be configured to perform these functions. It should be recognized that any such host system should include a utility factorAd hoc network connection and residential automation network 300 (i.e., PLC network orWireless network, etc.). Advantageously, this configuration will enable existing home technologies (e.g., home computers, set-top boxes, wireless routers/networking devices, etc.) to be used as the energy management computer 302 within the home automation network 300.

Energy management computer 302 includes a residential automation network interface 404, an internet connection 406, a processor 408, a memory 410, and LED indicator lights 412. The home automation network interface 404 is configured to communicate with a plurality of sensors, devices, mobile clients and/or controllers 304 and 316 using a PLC communication protocol, a wireless communication protocol, etc., as described above. If energy management computer 302 is configured to communicate using a PLC communication protocol, note that in this embodiment, energy management computer 302 includes a power transformer (not shown) for power line communication, and energy management computer 302 is configured to plug directly into an existing electrical outlet of dwelling 106. It should also be noted that if the energy management computer 302 is configured to wirelessly communicate with a plurality of sensors, devices, mobile clients and/or controllers in the home automation network 300, the energy management computer 302 is equipped with the necessary expansion slots (not shown) so that wireless communication can be conducted in conjunction with the home automation network interface 404 using wireless cards or the like. For example, energy management computer 302 may be configured to provide energy throughA wireless protocol is communicated in which a low-speed ad-hoc network of nodes (energy management computer 302 and plurality of sensors, devices, mobile clients and/or controllers 304 and 316) is constructed at installation time and automatically updated as the plurality of sensors, devices, mobile clients and/or controllers 304 and 316 are added and removed from the home automation network 300.

Further, the internet connection 406 is preferably configured to communicate with external networks using standard TCP/IP internet protocols or the like. For example, in one embodiment, the internet connection 406 may be a standard internet connection. It should be appreciated, however, that the internet connection 406 may be any wireless connection interface, DSL interface, cable modem, cellular connection, CDMA interface, GSM interface, or the like.

Using an Internet connection 406, the energy management computer 302 is configured to connect to and be able to communicate with the communication interface 202 of the energy management control center 102. Effectively, ems 100 provides free exchange of transactional data between ems control center 102 and premise 106 via an internet communications standard. Accordingly, as discussed in detail below, energy management computer 302 may send the required data to energy management control center 102 via standard TCP/IP internet protocol, and then receive instructions in the form of optimization results that energy management control center 102 generates and sends.

The processor 408 is configured to perform all application functions of the energy management computer 302, including processing the received instructions via the localization rules engine 414 and converting them to native PLC/wireless communication protocols to implement desired routines in the runtime production environment. It should be appreciated that once connected to the ems control center 102, the ems computer 302 effectively becomes an active node within the ems 100. It is also contemplated that at least one energy management computer 302 is installed in a respective residential or commercial building, and that a number of separate residences (each having an energy management computer 302 installed) create a number of respective active nodes within energy management system 100. Further, the processor 408 is configured to use any suitable operating software (e.g., operating software)Etc.) to operate energy management computer 302. In an example embodiment, the programming and configuration of energy management computer 302 may be usedProgramming language, and is installed remotely from the ess control center 102. Can be used forSource management computer 302 is configured to accept a series of modules, each providing a different purpose or process for its monitoring within dwelling 106. It should be appreciated that technology updates can be performed dynamically and remotely through software upgrades, allowing for easy and economical extension of system life.

Further, as explained in detail below, in operation, the energy management computer 302 is configured to obtain data from a plurality of sensors, devices, mobile clients and/or controllers 304 and 316 via the residence automation network 300. Preferably, each system component communicates in a "push" manner with the residential automation network interface 404 of the energy management computer 302 for any changes in value and/or periodically. Memory 410 is configured to temporarily store the data until it is transmitted to energy management control center 102. In an example embodiment, memory 410 is a non-volatile flash memory and the database is inAnd the method is established on a source database platform. However, energy management computer 302 may use any type of memory capable of performing such memory functions. Further, the memory 410 is configured to store backup currently configured data files for all components of the residential automation network 300. In addition, an LED indicator light 412 is provided for alerting the home or business end user of its status.

Referring back to fig. 3, as described above, energy management computer 302 is configured to communicate with a plurality of sensors, devices, mobile clients and/or controllers 304 and 316 via standard PLC technology or via a wireless communication protocol using the existing electrical wiring technology facilities of dwelling 106 in which energy management computer 302 is installed. As shown, the energy management computer 302 is communicatively coupled to one or more energy consumption controllers, which may include a "universal sensing and load control device" ("USLCD controller") 304 and a "dedicated sensor and load control device" ("SSLCD controller") 306.

The USLCD controller 304 is configured to plug into an existing wall outlet and may communicate with the energy management computer 302 using existing electrical wiring infrastructure. For example, the USLCD controller 304 may be implemented with a single, double, triple, or quadruple plug or power strip to enable operation in the residential automation network 300. Alternatively, USLCD controller 304 has conventional wireless communication components to communicate with energy management computer 302 accordingly. Accordingly, USLCD controller 304 is configured to enable energy management computer 302 to control any electrical device attached to a wall outlet by sending control instruction signals to USLCD controller 304.

In an alternative embodiment, USLCD controller 304 may be configured using a software implementation of energy management computer 302. Thus, the ems computer 302 may be configured to communicate directly with the ems control center 102 communications interface 202.

Generally, in response to control instruction signals received from energy management computer 302, USLCD controller 304 and SSLCD controller 306 can perform 3 operations. These operations are: (1) removing the load; (2) redirecting the load; and (3) decreasing/increasing the load. Examples of these control operations are as follows:

(1)removing load. Load removal is the following instruction: the controller corresponding to a particular load (e.g., an appliance connected to the controller) is completely shut down in a "zero draw" mode. The load that has been deemed suitable for removing the load instruction is switched to a "zero draw" mode, which is designated as not requiring modification of another load. Removing the load is the most effective strategy for energy reduction. Turning the HVAC unit "off" since it is not needed for the remainder of the occupied cycle is an example of removing a load command.

(2)Redirecting loads. The redirect load is the following instruction: a particular controller corresponding to a particular load is turned off to a "zero draw" mode, but another load has been or will be more utilized in conjunction with redirecting load instructions. In this sense, the redirect load instruction merely "redirects" energy consumption from one load to another.The aim of this strategy is that the load receiving redirection is more efficient or consumes less total power than the load being redirected. Turning "off the HVAC unit and turning" on "the ceiling fan is an example of redirecting a load from an HVAC that consumes a significant amount of energy to a ceiling fan that consumes much less energy than the HVAC.

(3)Reducing/increasing load. The decrease/increase load is an instruction to: the primary process variable for a particular load is decreased/increased, decreasing or increasing the workload in a manner deemed appropriate by the ems control center 102. For example, adjusting the set point of the HVAC unit from 75 degrees to 72 degrees consumes an amount of energy that is an example of reducing the process variable of the electric radiator to save energy.

FIG. 5 illustrates a detailed block diagram of an example embodiment of USLCD controller 304 according to an example embodiment. As shown, USLCD controller 304 preferably includes a plurality of sensors in sensor array 502, each configured to determine various data related to the operation of an associated energy consuming device/appliance and more general information related to dwelling 106 and/or the designated room in which the device is located. These sensors include, but are not limited to: occupancy sensors 504, energy consumption sensors 506, temperature sensors 508, light sensors 510, and the like. These sensors capture data elements obtained from dwelling 106, and by using the basic information obtained by these sensors, many types of information can be determined that are relevant to the room or area in which a particular USLCD controller 304 is located. For example, energy consumption sensor 506 is configured to measure the current drawn from the appliance/device connected to a particular USLCD controller 304. In this regard, the energy consumption sensor 506 may measure the current consumed by the appliance/device and provide an accurate reading to the energy management computer 302. Note that the occupancy sensor 504, the energy consumption sensor 506, the temperature sensor 508, and the light sensor 510 each include suitable hardware to measure various data as may be appreciated by those skilled in the art. For example, the energy consumption sensor 506 may include an ammeter, voltmeter, multimeter or similar suitable measuring device configured to measure the current drawn by appliances/devices coupled to the energy consumption sensor 506USLCD controller 304.

The USLCD controller 304 is also configured to send the captured data relating to the room or area to the energy management computer 302 using the residence automation network driver 512. As described above, once received by energy management computer 302, this data is combined with data from a plurality of sensors, devices, mobile clients and/or controllers 304 and 316 within dwelling 106, ultimately enabling energy management system 100 to determine the overall status of activities being performed in the home or commercial building and the particular rooms therein. In an additional refinement, each USLCD controller 304 provides: an LED light 514 that alerts home or business end users of their status; and a timing override switch 516 to enable the end user to bypass existing procedures for a preset or indeterminate period of time. Further, the USLCD controller 304 includes performing (1) removing the load; (2) redirecting the load; and (3) necessary hardware (not shown) required for the function of reducing/increasing the load. It will be apparent to those skilled in the art that the necessary hardware may include electrical/electromagnetic switches, variable resistors, and the like.

In one embodiment, USLCD controller 304 can also be provided as a USLCD light switch controller or the like. Effectively, multiple USLCD controllers 304 may be located throughout the residence 106 at wall sockets, light switches, and other suitable locations. With the internal sensors of sensor array 502, plurality of USLCD controllers 304 are preferably designed to replace the sensing terminals of pre-existing thermostats at dwelling 106 and are configured to forward temperature readings and/or light switch data to energy management computer 302 as described above. Accordingly, the plurality of USLCD controllers 304 provide a combination and correlation of temperature readings and light switch data so that energy management computer 302 can determine the usage rate of each HVAC unit installed in dwelling 106. Further, this configuration allows HVAC assets to be utilized dynamically and programmatically not only for normal daily operation, but also in critical energy events such as demand response programs.

In an example embodiment, premise automation network 300 employs 220 volt and 110 volt USLCD socket controllers so that energy consuming devices in premise 106 can be quickly and easily added to the control of energy management computer 302. This allows other home and business building assets to be utilized dynamically and programmatically, not only for normal daily operations, but also in critical energy events such as demand response programs. For example, a simple demand response application of this function may schedule and run a dishwasher, washing machine, dryer, etc. in the middle of a full energy night rather than in a peak daytime period. Furthermore, as the capabilities of such appliances further develop, if the end user decides that it is desirable to run the dryer during the day, the energy management computer 302 may preferably turn off the dryer's heating elements when the energy price is premium, but continue to tumble the clothes, and then turn on the heating elements again when the demand is relaxed.

In another refinement of the present embodiment, USLCD controller 304 is configured to utilize an interoperable self-installation protocol, wherein devices are automatically configured when added to residence automation network 300. In this embodiment, when an end user adds a device to premises automation network 300 by plugging the device into a socket equipped with USLCD controller 304, premises automation network 300 installs the necessary configuration required for operation in energy management computer 302. It should be appreciated that each USLCD controller 304 can employ an operating system 518, including necessary hardware such as a processor and memory (not shown) as would be recognized by those skilled in the art, to control the functions of USLCD controller 304. For example, as described above, USLCD controller 304 may be configured using a software implementation of energy management computer 302. In the present embodiment, the operating system 518 has a processor and memory to execute software implementations accordingly.

Referring back to fig. 3, the energy management computer 302 is also configured to be communicatively coupled to a "dedicated sensor and load control device" controller ("SSLCD controller") 306 within the home automation network 300. In general, each SSLCD controller 306 employs the same core components as the USLCD controller 304 shown in fig. 5, and is fabricated with similar internal components, except for external physical and wiring interfaces. In an example embodiment, each SSLCD controller 306 may be designed in view of a single application and specifically provide specific application functionality. Thus, each SSLCD controller 306 is configured to interface with the end user's specific energy consuming device that is directly wired into the electrical system of dwelling 106, rather than plugged into an electrical outlet. For example, the SSLCD controller 306 is configured to interface with a device that allows three-wire direct connection, such as devices used in modern electric ovens and HVAC systems. For example, the SSLCD controller 306 is designed to be attached between an existing home or commercial building thermostat and a junction box of an HVAC unit. It is designed with a clamping terminal block connector for ease of installation. Typically, residential HVAC systems are designed with standard wiring as specified by the international standards organization, and thus, the wiring of the junction boxes is nearly identical between different homes. The SSLCD controller 306 is preferably designed for HVAC applications and works by mimicking the thermostat of a residential HVAC unit. In this way, the SSLCD controller 306 can be easily integrated into almost any residential HVAC system.

In an example embodiment, SSLCD controller 306 is configured to communicate with energy management computer 302 using a PLC or wireless communication protocol and generally requires control instruction signals from energy management computer 302 to operate and control associated appliances/energy consuming devices. Thus, the core technology of the SSLCD controller 306 resides within the Java-based HVAC module in the energy management computer 302. In an alternative embodiment, SSLCD controller 306 can be configured using a software implementation of energy management computer 302. Accordingly, the SSLCD controller 306 may be configured to communicate directly with the communication interface 202 of the energy management control center 102.

Further, similar to the USLCD controller 304, the SSLCD controller 306 is also configured to utilize an interoperable self-installation protocol, wherein devices are automatically configured when added to the residence automation network 300. In this embodiment, when an end user directly wires the equipment to the electrical system of premise 106, premise automation network 300 installs the necessary configuration required for operation in energy management computer 302.

As described above, the SSLCD controller 306 is designed to be located between the thermostat and the wires leading to the junction box of the HVAC unit. While the SSLCD controller 306 may thus be used to control the operation of the HVAC unit, the SSLCD controller 306 is also configured to receive control instruction signals and/or signals from the HVAC unit upon a fault to disable itself and effectively allow the HVAC unit to resume its standard operating mode. It should also be appreciated that in such a design configuration, the preexisting thermostat may be controlled again in the event of an electrical or network failure.

Finally, employing the SSLCD controller 306 as an HVAC controller provides a component that can accurately measure the exact energy consumption cost saved by the end consumer. This is because energy management computer 302 is further configured to: with respect to which operation the HVAC unit is being instructed by energy management computer 302 to deliver the desired temperature and HVAC control, it is recorded and measured what operation the HVAC unit has been instructed by the pre-existing thermostat in dwelling 106.

In conjunction with the USLCD controller 304 and SSLCD controller 306, the residence automation network 300 includes additional components configured to communicate with the energy management computer 302 using PLCs, wireless communication protocols, and the like. Specifically, the home automation network 300 also includes commercial/home meters 308 (e.g., a.m.i., a.m.r., electromechanical, etc.); an energy generating device 310 (e.g., solar, wind, etc.); energy storage devices 312 (e.g., batteries, etc.); general business/home green or sustainability devices 314; and a commercial/domestic energy converter device 316. Each of these devices is provided according to its conventional hardware and functionality. However, each of these devices may include components of the USLCD controller 304 and/or the SSLCD controller 306 described above with respect to fig. 5. In another refinement, any of the devices 304 and 316 may be configured using a software implementation of the energy management computer 302. Thus, these components may operate as hosts and may be configured to communicate directly with the communication interface 202 of the energy management control center 102. Finally, as shown in FIG. 3, an in-home display 318 may be provided at residence 106 to enable the end user to have an alternate path, in addition to energy management enterprise portal 108, to enter consumption rules/preferences through a touch screen interface, and the like.

Fig. 6 illustrates a flow chart of a method for managing energy consumption according to an example embodiment. As shown, initially at step 605, a premises automation network 300 is installed at an end user's premises 106. Next, at step 610, the current thermostat settings, the temperature in the freezer and refrigerator, and any other variable setting devices are measured by appropriate sensors and/or controllers or technicians completing the installation process. There is no need to measure the on/off devices in any way, such as televisions, lights, pool and spa pumps, radios, computers, washing and drying machines, and any other such energy consuming devices, but its make, model and serial number is provided to the energy management control center 102 for storage in the unified data repository 210. These data are then analyzed to define a user profile and create a digital model for each household, including the type and location of each energy consuming device/appliance.

At step 615, end-user preferences and requirements selections are recorded, such as job schedules, climate environments, necessary equipment (e.g., medical equipment) that must be run at full time, cost preferences, and the like. In an example embodiment, the user may enter this information directly via the user interface in response to a standard set of questions and responses. These data and user preferences are then provided to the energy management control center 102 for storage in the unified data repository 210. At this point, premises automation network 300 for a given premises 106 is ready for operation.

At step 620, the electronic appliances and other energy consuming devices are initially configured according to the preferences initially defined by the user. To perform the initial configuration, the ems control center 102 may generate control command signals that are sent to the ems computers 302 at the end user's premises 106. These control command signals are then processed and sent to a plurality of sensors, devices, mobile clients and/or controllers 304 and 316. As described above, the USLCD controller 304, SSLCD controller 306, etc. are configured to control the operation of the associated appliance/energy consuming device, including (1) removing the load; (2) redirecting the load; and (3) instructions to decrease/increase the load.

In one example, based on the end user's work schedule, control instruction signals are generated for the HVAC system that cause energy management computer 302 to "reduce load" when the end user leaves work and "increase load" when the end user returns home from work, providing the end user with a temperature to be reached in dwelling 106 specified. More specifically, the end user may define 3 different profiles for his residence 106: (1) "at home", (2) "at work", and (3) "at night". The "at home" profile contains all settings when the end user is at home. The "on duty" profile contains all settings of the end user while on duty. Finally, the "night" profile contains all settings while the end user is asleep. These preferences may be set by the end user using the user interface provided by the energy management enterprise portal 108, and then may be automatically scheduled by the energy management control center 102. This allows the entire home or business to be automatically made aware of these scheduled changes and adapt to them without any further effort by the end user.

Once premises automation network 300 is established and all appliances, consumer electronic devices, and any other suitable devices are configured for initial operation, end user premises 106 can begin normal operation with energy management system 100. Specifically, at step 625, the home automation network 300 performs a series of steps to capture data available to a plurality of sensors, devices, mobile clients and/or controllers 304 and 316. More specifically, a plurality of sensors, devices, mobile clients and/or sensors within sensor array 502 of controller 304 and 316, particularly USLCD controller 304 and SSLCD controller 306, collect data such as energy consumption, temperature, lighting, effective ultrasound occupancy data, and the like. As described above, this transaction data is then transmitted to the ems computer 302 via PLC or wireless technology, where it is stored in memory 410 before being transmitted to ems control center 102 in ems computer 302.

Next, after sending the transaction data to the ems 102, the ems 102 further performs data analysis operations on the data using analysis and software in view of external data not related to the transaction data and user-defined rules and preferences (step 630).

As will be explained in detail below with respect to fig. 7, based on the configuration settings selected by the end user during the installation process, the energy management computer 302 can modify the configuration of the appliance/energy consuming device to achieve maximum energy efficiency. In addition, the energy management system 100 calculates, models, and algorithmically analyzes, resulting in inferred and predicted end-user information. More specifically, energy management system 100 includes adaptive software and techniques that enable learning and dynamic optimization of energy usage within end user's premises 106 to match changing patterns of end user behavior. For example, using data mining techniques, appliances, other energy consuming devices, and consumer energy behaviors are associated together at the overall premise or system level within the unified data warehouse 210. Thus, the energy management control center 102 is configured to determine what actions to take to optimize energy usage based on observing the correlation between consumer behavior and the operating conditions of the controllers, sensors, devices, and appliances over time. The historical importance of these correlations applies to optimizing performance.

Further, the energy management control center 102 is configured to observe and use the correlation between external and internal factors in its optimization technique (e.g., executing an internal HVAC system in response to upcoming changes in weather conditions and temperature). The energy management control center 102 is then configured to employ these observations to predictively optimize HVAC operations. For example, if a cold weather front is approaching the geographic location of a given dwelling 106, energy management control center 102 applies this data to the current operating settings of the associated HVAC unit and generates control command signals (e.g., a reduce load command) to reduce the load applied to the air conditioning unit while further accounting for the end user's temperature preferences.

The energy management control center 102 is also configured to analyze the electrical signatures of devices and appliances (e.g., HVAC systems, water heaters, refrigerators, etc.) so that conditions indicative of initial performance degradation or failure can be identified. This analysis provides a means for protective measures to be taken in addressing the potential situation to improve reliability and reduce asset life cycle costs. Thus, in conjunction with energy management computer 302, energy management control center 102 continuously evaluates the performance of residential HVAC systems (cooling, heating, airflow, etc.), lighting, water heaters, refrigerators, large appliances, and other equipment, and is configured to automatically "tune" these primary energy consuming devices, optimizing their energy efficiency performance, to conserve energy.

In another refinement of this step, if the transactional data indicates significant changes from historical conventions, energy management control center 102 includes analysis and software to identify these changes, and to automatically flag these behaviors to study and adjust scheduling or other declared performance conditions. For example, the ems control center 102 is configured to create "pre-assembly event response primitives" that work in response to specific data stimuli to automatically control the ems 100 to operate in an integrated manner to get specified results or outputs defined by the rules stored in the unified repository 210 of the ems control center 102.

In step 635, the energy management control center 102 generates a sequence of control command signals in response to the data analysis operations and transmits the commands to the energy management computer 302 of the home automation network 300. At step 640, energy management computer 302 receives and converts these signals so that energy management computer 302 can drive a plurality of sensors, devices, mobile clients and/or controllers 304 and 316 and preferably USLCD controller 304 and SSLCD controller 306, while meeting consumer preferences, resulting in optimization of energy consumption, peak energy demand, carbon emissions reduction, reliability, comfort and cost. To accomplish these goals, the energy management computer converts the control instruction signals into control commands (i.e., "remove load," "redirect load," and "reduce/increase load") to be sent to the appropriate USLCD controller 304 and SSLCD controller 306, which USLCD controller 304 and SSLCD controller 306 then perform the specified functions (step 645).

Finally, it should be understood that steps 625 through 645 may be repeated periodically (e.g., every 60 seconds) to periodically "tune" the appliance/energy consuming device to maximize energy consumption efficiency. Through this iterative cycle, the analytics and software implemented at the energy management control center 102 can continuously integrate and synchronously deliver the methods, processes, premise-based assets, equipment, consumer rules, behaviors, portals, communication networks, intelligent processors, sensors, controllers, and services needed to improve consumer comfort, convenience, and reliability, reduce utility and consumer costs, and extend the results in the life cycle of premise-based assets, with reduced carbon emissions and peak demand.

Fig. 7 illustrates a flowchart of an example data analysis performed by the energy management control center 102, according to an example embodiment. It should be appreciated that the flow chart illustrated in FIG. 7 corresponds to the data analysis step (step 630) described above with respect to FIG. 6.

First, at step 705, real-time transaction data is received from energy management computer 302 of dwelling 106 via connection interface 202. Next, at step 710, data store 204 stores the transactional data, and data store 204 stores only the current value of the transactional data. Similarly, at step 710, cloud data storage 206 stores a complete history of values, including current values of transactional data. At step 715, the transaction data is retrieved from the corresponding data store and validation rules engine 208 validates the transaction data. As described above, the validation rules may include one or more of the following: 1) static limiting; 2) a single value threshold; 3) percentage of change in value; 4) a percentage of difference values to related data objects; 5) a range of standard deviations; 6) a slope differential; 7) a numerical threshold; 8) subject completeness (integrity); 9) and others. If a transaction or series of transaction data does not meet the validation requirements, the data is declared invalid, triggering an appropriate response (step 720). In an example embodiment, the triggered event is responded to based on habits, where typical responses include, for example: excluding failed data points, notifying an operator, making a system flag for later use, or alerting an operator. Once all the data passes the required validation rules, energy management control center 102 reinserts the transactional data into cloud data storage 206 and synchronizes it to unified data repository 210 (step 725).

At step 730, new calculation data is created using the validated transaction data as raw data. For example, step 730 includes simple calculations performed by the optimization engine, such as addition and subtraction or complex mathematical calculations using brackets. Preferably, all calculations are performed in the order of p.d.m.a.s. (brackets, division, multiplication, addition, subtraction) operations. However, it should be appreciated that any suitable order of computation may be used. At this point, the data analysis is split into two parallel paths that can be performed serially or simultaneously. Specifically, at step 735, the motion platform 214 scans the unified data warehouse 210 to determine participation in active activities. The current state of the activity is updated with the new valid data and the calculation data. Further, at step 740, the operation rules engine 216 identifies valid business rules (i.e., "If the n Else" logical chain) and executes those business rules in the correct order of operation. Finally, at step 745, the optimization results are generated and appropriate control instructions are sent to all subscriber members connected to the energy management system 100 via the service and delivery platform 218 (see step 535-545 of FIG. 6).

In one example implementation of the energy management system 100, the energy management control center 102 may be used to support a utility demand response program for load control of large appliances (e.g., end-user refrigerators and water heaters). For example, upon receiving the command signal, the appliances may be turned off for short intervals without compromising the safety of the refrigerator inventory.

For example, refrigerator optimization can be achieved using a USLCD controller 304 (such as USLCD 120 or 220 volt plug). The hardware sensors of the sensor array 502 in these USLCD controllers are configured to measure the consumption kW of the outlet to determine the run length of the refrigerator. The measured duty cycle data is then sent to the ems computer 302 and ultimately to the unified data warehouse 210 of the ems control center 102.

The suggested settings for internal refrigerator control are determined by associating the input data stream with model information collected about appliances during the installation process of the home automation network 300. These suggested settings generated by the ems control center 102 are then transmitted to the ems computer 302 of the end user. Due to the significant variety of refrigerator brands and models, end users are required to manually make refrigerator temperature setting adjustments. The correct settings take into account the use of the kitchen as a room, outside climate conditions, HVAC settings, etc.

In addition, the data controlled by USLCD controller 304 allows the user's operational cycle of the particular appliance (i.e., refrigerator, water heater, dishwasher, washing machine, etc.) to which it is connected to be analyzed based on the currently derived data from USLCD controller 304. Thus, the energy management control center 102 is able to see the scheduled and actual operation of the end-user appliances. With this observation and other behavioral data, the energy management control center 102 is configured to make recommendations to the energy management computer 302 regarding the scheduling of appliance operations in the form of control command signals to achieve more efficient conservation and energy optimization.

Since the energy management system 100 is designed to utilize a unified data repository 210 (storing the type and distance of the relationship of one sensor, device, mobile client or controller to another sensor, device, mobile client or controller), the energy management system 100 has a greater range of control over connected (via sensor, device, mobile client or controller) assets. Thus, the decision logic may take into account the status/value of other connected sensors, devices, mobile clients or controllers. This allows for the use of more sophisticated machine intelligence to control assets and to enable control of household or business dwelling assets in a manner that is more reflective of a collaborative asset system than separate assets. The effect of these cooperating assets is lower energy bills, more efficient operation, and lower energy consumption and demand. Furthermore, since the ems 100 is an ongoing system, the efficiency and cost gains achieved by ems 100 can last over time, unlike existing one-time analyses that slowly lose effectiveness over time. Furthermore, because energy management system 100 has the ability to store information over time, it can also be used in this manner as an asset management platform for home or business use. Data from the energy management system 100 can be used to correlate and infer when actual maintenance is required, establishing an "on-demand" maintenance program, rather than the existing scheduled maintenance program.

Further, since the energy management system 100 is designed to utilize the unified data repository 210 (storing the type and distance of the relationship of one sensor, device, mobile client or controller to another sensor, device, mobile client or controller), the energy management system 100 can calculate and determine how the impact of multiple energy saving projects or actions. This is because the energy management system 100 can identify relationships between different assets via the unified data repository 210. Broadly, the calculations for this analysis utilize standard mathematical functions of correlation coefficients.

While the above has been described in connection with example embodiments, it is to be understood that the term "example" is merely representative of an example. Accordingly, the present application is intended to cover alternatives, modifications, and equivalents, which may be included within the spirit and scope of the energy management system and method disclosed herein.

Furthermore, in the previous detailed description, numerous specific details have been set forth in order to provide a thorough understanding of the invention. It will be apparent, however, to one skilled in the art that the energy management system and method may be practiced without these specific details. In other instances, well-known methods, procedures, components, and circuits have not been described in detail as not to unnecessarily obscure aspects of the energy management systems and methods disclosed herein.

Claims (24)

1. An energy management system for efficiently and continuously managing energy consumption, energy demand and operational performance of a dwelling, the system comprising:

an energy consumption controller associated with the dwelling and configured to repeatedly collect current energy consumption data from at least one electrical component associated with the dwelling, the current energy consumption data comprising performance data of the at least one electrical component; and

a control center communicatively coupled to the energy consumption controller and configured to:

continuously receiving current energy consumption data collected by the energy consumption controller;

storing the received current energy consumption data as historical energy consumption data;

performing a data analysis operation using the current energy consumption data, the historical energy consumption data, and data not collected by the energy consumption controller, and

dynamically generating instructions for controlling the at least one electrical component based on the data analysis operations,

wherein the data not collected comprises data not related to energy consumption data.

2. The energy management system of claim 1, further comprising: a server configured to transmit an instruction to the energy consumption controller.

3. The energy management system of claim 2, wherein the energy consumption controller is further configured to control the at least one electrical component based on the instructions.

4. The energy management system of claim 2, wherein the server is further configured to receive energy consumption rules from a user of the at least one electrical component.

5. The energy management system of claim 4, wherein the control center is further configured to generate instructions for controlling the at least one electrical component based on the energy consumption rules.

6. The energy management system of claim 1, wherein the at least one electrical component is an appliance.

7. The energy management system of claim 6, wherein the control center is further configured to dynamically learn energy consumption schedules and performance characteristics of appliances based on performance data of the at least one electrical component.

8. The energy management system of claim 1, wherein the data not collected by the energy consumption controller is selected from the group consisting of: user preferences, energy market conditions, weather conditions, grid infrastructure constraints, manufacturer specifications and standards for the at least one electrical component, and regulatory requirements.

9. The energy management system of claim 1, wherein the energy consumption data further comprises an ambient temperature of a location of the at least one electrical component, and the occupancy of the room in the dwelling in which the at least one electrical component is located is determined based on the energy consumption data.

10. An energy management system for efficiently and continuously managing energy consumption and operational performance of a dwelling, the system comprising:

a server configured to continuously receive current energy consumption data from an energy consumption controller associated with at least one electrical component, the at least one electrical component being associated with the dwelling, the current energy consumption data comprising performance data of the at least one electrical component; and

a computer coupled to the server and configured to

Storing the received current energy consumption data as historical energy consumption data;

performing a data analysis operation using current energy consumption data, historical energy consumption data, and data not from the energy consumption controller; and

dynamically generating instructions for controlling the at least one electrical component based on the data analysis operations.

11. The energy management system of claim 10, wherein the server is further configured to send instructions to the energy consumption controller.

12. The energy management system of claim 11, further comprising: a data repository configured to store the current energy consumption data and the data not from the energy consumption controller.

13. The energy management system of claim 12, wherein the computer is further configured to analyze current and historical energy consumption data and the data not from the at least one energy consumption controller and to generate instructions for control based on the analyzed data to optimize energy consumption and operating performance of the at least one electrical component.

14. The energy management system of claim 10, wherein the computer is further configured to dynamically learn the energy consumption schedule and the performance characteristics of the at least one electrical component based on the performance data of the at least one electrical component.

15. The energy management system of claim 10, wherein the data not from the energy consumption controller is selected from the group consisting of: user preferences, energy market conditions, weather conditions, grid infrastructure constraints, manufacturer specifications and standards for the at least one electrical component, and regulatory requirements.

16. The energy management system of claim 10, wherein the computer is further configured to validate the energy consumption data using at least one of the following criteria: static limiting; a single value threshold; percent change in value; a percentage of difference values to related data objects; a range of standard deviations; a slope differential; a numerical threshold; and object completeness.

17. The energy management system of claim 10, wherein the energy consumption data further comprises an ambient temperature of a location of the at least one electrical component, and the occupancy of the room in the dwelling in which the at least one electrical component is located is determined based on the energy consumption data.

18. An energy management method for efficiently and continuously managing energy consumption and operational performance of a dwelling, the method comprising:

collecting current energy consumption data from an energy consumption controller associated with at least one electrical component at a dwelling, the current energy consumption data including performance data of the at least one electrical component;

storing the received current energy consumption data as historical energy consumption data;

performing a data analysis operation using current energy consumption data, historical energy consumption data, and data not from the energy consumption controller; and

dynamically generating instructions for controlling the at least one electrical component based on the data analysis operations.

19. The energy management method of claim 18, further comprising: and sending an instruction to the energy consumption controller.

20. The energy management method of claim 18, further comprising: storing the historical energy consumption data and the data not from the energy consumption controller in a data warehouse.

21. The energy management method of claim 20, further comprising:

analyzing current and historical energy consumption data and the data not from the at least one energy consumption controller; and

generating instructions for controlling to optimize energy consumption and operational performance of the at least one electrical component based on the analyzed data.

22. The energy management method of claim 21, further comprising: the analyzed data is correlated with other data from the residence to optimize the overall energy consumption of the residence.

23. The energy management method of claim 18, further comprising: dynamically learning an energy consumption schedule and performance characteristics of the at least one electrical component based on the performance data of the at least one electrical component.

24. The energy management method of claim 18, wherein the energy consumption data further comprises an ambient temperature of a location of the at least one electrical component, and the occupancy of the room in the dwelling in which the at least one electrical component is located is determined based on the energy consumption data.