Systems, devices, and methods for appliances with integrated energy storage

Abstract

An intelligent energy system includes an electrical appliance that consumes energy, a battery module coupled to the electrical appliance, and a bidirectional converter coupled to the electrical appliance and the battery module through a power bus. The battery module is configured to provide power to the appliance. The bidirectional converter converts between alternating current (AC) and direct current (DC) and engages with a power infrastructure external to the appliance. The system also includes a control unit communicatively coupled to the battery module, the bidirectional converter, and the appliance. The control unit is configured to determine a charge and discharge schedule for the battery module. A battery module coupled with the bi-directional converter provides uninterrupted power to the appliance, extracts the power demand of the appliance from the local power infrastructure, and allows greater appliance peak power consumption than would otherwise be actual or possible.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims the benefit of and priority to U.S. Provisional Patent Application No. 63 / 301,861, filed on January 21, 2022, the entire disclosure of which is hereby incorporated by reference in its entirety for all purposes. Technical Field

[0003] The present disclosure relates generally to energy storage, and more particularly, to systems, apparatus, and methods for optimized charging or discharging of energy storage devices for increasing the availability of peak power and sharing stored energy among multiple electrical or electrically driven units. Background Art

[0004] The distribution, consumption, or conversion of electrical energy in buildings (such as residences, commercial buildings, industrial facilities) and non-building environments (e.g., agriculture, industry, medical, and transportation systems) relies on available input power as a basis for distributing the power. For example, if a user wants to purchase and install an appliance (e.g., a dryer) that is powered by electricity, the appliance may be required to have the necessary electrical infrastructure, such as a dedicated high-current 220V line and / or plug. A significant amount of expense and effort may then be required to install these dedicated lines and / or plugs. In addition, due to these requirements, the locations where such appliances may be located are also limited. Similarly, if a user wishes to charge an electric vehicle, it may be necessary to add a dedicated 220V line and a dedicated plug. A range, stove, or cooktop may face similar problems due to its special power requirements.

[0005] During periods when the grid is unavailable, users of electricity have limited options. For example, users can purchase generators fueled by gasoline or natural gas. Additionally or alternatively, users can also retrofit, reinstall, or upgrade electrical panels to include power storage devices, such as fixed-mount battery systems. However, such approaches require significant expense and dedicated space, and are limited to providing power to units based on available power from the generator or fixed-mount battery system. In addition, backup power options are limited by other factors (e.g., use of other appliances at home, appropriate home / building electrical infrastructure sizing methods), or by conditions such as when the generator runs out of fuel.

[0006] Additional limitations include, but are not limited to, that the heat and / or energy available during times of peak load are typically limited by the available power of the grid connection, and may be further limited by infrastructure. Therefore, the peak available power for appliances is limited by existing shared and private infrastructure. For example, due to branch circuit size setting limitations, it is impractical (or likely impossible based on standards) for a single appliance to pull 20kW. Similarly, it may be impractical to have several appliances in a home that use lower (e.g., 15kW) peak power consumption because there are not only branch circuit limitations, but also certain panel and feed limitations. This may result in performance limitations. For example, users may experience long cooking / boiling times and / or be unable to use stoves or cooktops to cook certain types of food, and users may have to wait for water to be heated for washing clothes or dishes, bathing, etc. All of this may result in additional costs on energy and water and undesirable performance of these appliances.

[0007] Additionally, in the era of decarbonization, with strong interest in technologies and methods that could limit the Earth's warming to more than 1.5°C above pre-industrial levels, most countries, including the United States, have set a goal of achieving net zero by 2050. Net zero means that all greenhouse gas emissions produced are offset by an equal amount of emissions eliminated or captured. Achieving this will require a shift from greenhouse gas emissions produced by fossil fuels, such as through the use of renewable energy. Although renewable energy is abundant under the right conditions, it is intermittent. For example, a solar panel in a residential unit may not produce energy at times when demand is high (e.g., early morning or evening). Therefore, additional goals of decarbonization include improving the efficiency of energy transmission, storage, distribution, and conversion at the point of use.

[0008] Thus, there is an unmet need for effective methods to more efficiently and intelligently distribute power within a particular residential, industrial, or commercial setting. Summary of the invention

[0009] To address the above shortcomings, systems and methods for intelligent energy management are provided. An example method includes an appliance, a battery module coupled to the appliance, and a bidirectional converter coupled to the appliance and the battery module via a power bus. The battery module is configured to provide power to the appliance. The directional converter converts between alternating current (AC) and direct current (DC) and interfaces with a power infrastructure external to the appliance. The system and method also include a control unit communicatively coupled to the battery module, the bidirectional converter, and the appliance. The control unit is configured to determine an optimized charging and discharging schedule for the battery module.

[0010] The above is a summary and therefore necessarily contains simplifications, generalizations and omissions of details; therefore, the summary is only illustrative and not limiting in any way. Other aspects, inventive features and advantages of the systems and / or processes described herein will become apparent in the non-limiting detailed description set forth herein. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] The advantages and features of the disclosed embodiments will be more readily apparent from the detailed description, the appended claims and the accompanying drawings (or drawings accompanying the specification). The following is a brief introduction to the drawings.

[0012] Figure 1 A block diagram illustrating an exemplary system architecture for smart energy management according to some implementations.

[0013] Figure 2 A block diagram illustrating example modules included in a smart energy management application according to some implementations.

[0014] Figure 3 is a graph illustrating example power usage patterns of an appliance, power production patterns of a power supply, and charging and discharging schedules of battery molecules according to some embodiments.

[0015] Figure 4 A block diagram illustrating an exemplary architecture of an appliance equipped with a battery module according to some embodiments.

[0016] Figure 5 A block diagram illustrating an exemplary application scenario for energy sharing between different living units within a building according to some embodiments.

[0017] Figure 6 is a flow chart of an example method for intelligent energy management according to some implementations.

[0018] Figure 7 is a flow chart of another example method for intelligent energy management according to some implementations. DETAILED DESCRIPTION

[0019] In the following detailed description of the embodiments, reference is made to the accompanying drawings which form a part thereof and are shown by way of illustration. It should be understood that the features of the various described embodiments may be combined, other embodiments may be utilized, and structural changes may be made without departing from the spirit and scope of the present disclosure. It should also be understood that the features of the various embodiments and examples herein may be combined, exchanged, or removed without departing from the spirit and scope of the present disclosure. In addition, for clarity, reference numerals between the drawings and descriptions of redundant elements may be omitted.

[0020] According to some embodiments, the methods and functions described herein (such as controlling battery charging or discharging) can be implemented as one or more software programs running on a computer processor (e.g., a control unit or controller). According to some embodiments, the methods and functions described herein can be implemented as one or more software programs or firmware programs running on a stand-alone computing device or embedded device (such as a tablet computer, a smart phone, a personal computer, a server, or any other computing device) or on an appliance or device with a control program. Special hardware - including but not limited to application-specific integrated circuits, programmable logic arrays, and other hardware devices - can also be constructed to implement the methods and functions described herein. In addition, the methods described herein can be implemented as a device such as a non-temporary computer-readable storage medium or a memory device, which includes instructions that, when executed, cause a processor to perform the methods and functions described herein.

[0021] According to some embodiments, the methods, systems, and apparatus described herein may relate to energy storage devices (e.g., battery modules) for single or multiple electrical appliances, devices, or electrically driven units. The energy storage device may be present inside or outside the electrical appliance, device, or electrically driven unit, and may be intelligently charged and discharged to provide appropriate power to the directly coupled (one or more) electrical appliances, (one or more) devices, or (one or more) electrically driven units themselves or to other indirectly connected electrical appliances, devices, or electrically driven units. For example, the methods and functions described herein, when implemented as software or firmware programs, may provide a control mechanism that optimizes the charging or discharging of energy storage devices during periods of peak power consumption, high transient energy pricing, and / or during power outages. According to some embodiments, the methods, systems, and apparatus disclosed herein may be applied in residential, industrial, or commercial environments for electrical appliances or any other system having power as input and optically having various forms of energy as output.

[0022] According to some embodiments, the methods, systems, and devices described herein may provide various benefits and advantages. For example, but not by way of limitation, the embodiments disclosed herein may provide the functional equivalent of a 220V, 50A (or even higher or lower value) socket in the context of an existing 110V electrical infrastructure, without having to install a new 220V power delivery infrastructure (e.g., dedicated wiring and / or plugs). This then saves the cost and effect of installing or modifying the 220V power delivery infrastructure. In addition, the embodiments disclosed herein may also provide energy storage in a battery module that allows for the storage of internal (or external) energy within (or outside) an appliance, device, or electrically driven unit. Therefore, the embodiments disclosed herein may allow for the use of electricity in a manner that avoids the limitations of existing electrical infrastructure (such as branch circuits, circuit breakers, 100A panels, etc.). For example, the embodiments disclosed herein may allow an appliance to be movable or portable. Additionally, embodiments disclosed herein may also allow power stored in a battery module within an appliance (or outside of an appliance) to be redirected during periods of power loss to provide backup power for the appliance itself and for additional appliances (e.g., appliances in the same room, house, facility, building, etc.) For example, if a power outage occurs in the middle of the night, when kitchen appliances are less likely to be used but the house is more likely to need heating, power from the kitchen appliances stored in the battery module can be provided as power to run a space heater or other furnace without interfering with operation of the kitchen appliances.

[0023] It is to be understood that the features, benefits and advantages described herein are not all-inclusive and that many additional features and advantages will be apparent to one of ordinary skill in the art from the drawings and the following description.

[0024] Overview of Intelligent Energy Management System

[0025] As used herein, the terms "energy" and "power" are interpreted according to their broad and ordinary meanings, and may refer to any form of power resource and / or its converted form (e.g., power generated by natural gas, charcoal, hydroelectric or water power, wind, solar, biomass, geothermal, etc.) used to drive an appliance, device, or other electrically powered equipment to operate as intended. The term "battery module" is used herein according to its broad and ordinary meaning, and may refer to any type of battery cell (the smallest unit of a battery) or a module organized in a single package in a series and parallel manner for charging from a resource and for discharging to an appliance, device, or any other electrically powered unit.

[0026] Figure 1A block diagram of an example smart energy management architecture 100 according to some embodiments of the present disclosure is illustrated. As illustrated, the smart energy management system 100 may include distributed appliances 103a-103n (collectively or individually referred to as appliances 103) and a server environment including one or more servers, including but not limited to a smart energy management server 101a and / or one or more third-party servers 101n. One or more appliances 103 may be coupled to a battery module 107a or 107n (collectively or individually referred to as a battery module 107), and may include a smart energy management application 105a-105n (collectively or individually referred to as a smart energy management application 105) for managing the coupled battery module 107. Each battery module 107 may be installed inside or outside the appliance, and may include a coupled bidirectional converter 111a or 111n (collectively or individually referred to as a bidirectional converter 111) for charging or discharging the battery. In some embodiments, the storage battery may not be directly coupled to a specific appliance, but may provide power to multiple different appliances, and may therefore be referred to as an independent battery 117. The smart energy management system 100 also includes a communication network 115 for establishing communication between different components of the system and a power grid / electrical infrastructure 123 for transmitting power between components within the system or with (one or more) external sources. In some embodiments, the smart energy management system 100 may optionally include a user device 119 configured to communicate with one or more appliances 103 and / or the server 101 (e.g., for remotely controlling one or more appliances or a battery module coupled to the appliances).

[0027] It should be noted that the scale of the intelligent energy management system 100 may vary and may include more than Figure 1 , or more or fewer than those illustrated in . In one embodiment, in its basic form, the smart energy management system 100 may include only one appliance 103 without necessarily including a server 101 and / or a client device 119. In another embodiment, additional sensors 109a-109n (collectively or individually referred to as sensors 109) may be included in the smart energy management system 100. In addition, in some embodiments, the engagement between the components of the smart energy management system 100 may occur remotely, for example, where the components of the smart energy management system 100 may be distributed across one or more devices of a distributed network. For example, one user device 119 or server 101 may be configured to manage multiple appliances at a remote location (or via remote control) via a distributed smart energy management application 105.

[0028] The appliance 103 may be specifically configured to include a storage battery module 107 that is directly coupled to the appliance (e.g., by being integrated into, embedded in, or attached to the appliance). Embodiments of such appliances may include, but are not limited to, certain heating, cooling, and climate control equipment (e.g., central air conditioners, window air conditioners, space heaters, electric water heaters, dehumidifiers, fans, air purifiers, etc.), kitchen appliances (e.g., electric ranges, microwave ovens, stoves, ovens, refrigerators, coffee makers, toasters, blenders, dishwashers, stove top burners, hotpots, tea kettles, etc.), lighting, various entertainment electronic devices (e.g., televisions, audio receivers, game consoles, etc.), and other appliances such as clothes dryers, hair dryers, or any other device or electrically powered unit that may have peak power demands for residential, commercial, or industrial applications.

[0029] The battery module 107 is a battery that can be charged, discharged to a load, and recharged multiple times, as opposed to a disposable battery or primary battery. The battery module 107 can be composed of one or more electrochemical cells. Rechargeable batteries can come in many different shapes and sizes, from button cells to megawatt-class systems that are connected to stabilize the power distribution network. In some embodiments, the battery module 107 can be designed to have a size and shape suitable for a specific electrical appliance 103. In some embodiments, different combinations of electrode materials and electrolytes can be used for the battery module 107, including but not limited to lead acid, zinc air, nickel cadmium (NiCd), nickel metal hydride (NiMH), lithium ion (Li-ion), lithium iron phosphate (LiFePO4), and lithium ion polymer (Li-ion polymer). In some embodiments, the battery module 107 disposed inside or outside the electrical appliance 103 is also replaceable. That is, the battery module 107 can be easily replaced (for example, by pulling out / pushing in) without affecting the function of the coupled electrical appliance 103.

[0030] The bidirectional converter 111 can convert alternating current (AC) to direct current (DC) in the direction from the power source (e.g., from the power grid / electrical infrastructure 123) to the battery module 107, and convert direct current to alternating current in the direction from the battery module 107 to the power source or a directly connected load requiring alternating current (e.g., a refrigerator directly connected to a cooktop containing a battery and a bidirectional converter). In some embodiments, the power source is a 110V power supply. In some embodiments, the power source can be a 220V power supply, depending on the power grid structure used by the supplier (e.g., in some Eastern countries). In addition, the DC output provided by the converter can also be at different scales. For example, the output can be 6V, 12V, 24V, or any other appropriate voltage, depending on the appliance to which the bidirectional converter is coupled. In some embodiments, the bidirectional converter 111 includes more than one converter. For example, the bidirectional converter 111 may include a first AC-DC converter for a 110V power supply and a second AC-DC converter for a 220V power supply. For another example, the bidirectional converter 111 may include a first converter that outputs 6V power and a second converter that outputs 12V power. In some embodiments, the bidirectional converter 111 may include a DC-DC converter with or without an AC-DC converter. In some embodiments, the bidirectional converter may automatically configure itself to accept a range of AC and DC voltages.

[0031] The grid / electrical infrastructure 123 can provide power to the battery module 107 through the coupled bidirectional converter 111. The grid / electrical infrastructure 123 can be provided by an existing electrical infrastructure (e.g., a power grid within a building or a group of buildings, also referred to as grid power, fixed power, or fixed AC power). In one embodiment, an existing circuit containing a circuit breaker element with a 20A limit (whether it is on 110V or 220V) can provide power input to the bidirectional converter. In some embodiments, such as in an industrial environment, the existing circuit can include any voltage level or any number of phases, such as a 3-phase 480V configuration. In some embodiments, the power source can alternatively be a DC source, such as current from a solar panel, a local DC generator (e.g., a gas generator), etc.

[0032] The sensors 109 may include any number of sensors and / or any type of sensors configured to collect information from the surrounding environment or system. In one embodiment, the sensors 109 may include, but are not limited to, image sensors, video sensors, audio sensors, temperature sensors, humidity sensors, light detection sensors, different weather sensors (e.g., wind direction sensors, wind direction sensors, rain gauges, UV sensors, sunlight sensors, solar radiation sensors, air pressure sensors, noise sensors, rain / snow sensors, evaporation sensors, etc.), etc. These different sensors may be coupled to the appliance and / or power supply locally (e.g., onboard temperature sensors) or remotely, and may provide certain contextual information to the appliance 103 (e.g., to the smart energy management application 105 of the appliance). In some embodiments, each sensor 109 may also include a signal processing unit configured to process the signals detected by the sensor. For example, based on the configured complexity, an audio sensor may be configured to recognize text from the audio, the possible age of a person (e.g., a baby or an elderly person), the temperament of a person in an audio file, etc. If more than one person is included in the audio file, such information may be recognized for each person. For another example, based on the configured complexity, a video sensor coupled to a cooktop can be configured to monitor the cooking process, including obtaining an image of the food being cooked. In another embodiment, based on the configured complexity, an image sensor coupled to a storage portion of a refrigerator can be configured to detect the type and amount of food stored in the refrigerator (e.g., how many eggs, how many vegetables, what type of vegetables, etc.). In some embodiments, there can be other different sensors, as described later.

[0033] In some embodiments, the smart energy management system 100 may optionally include a client device 119 configured to communicate with one or more appliances 103 and / or the server 101. For example, through an instance of the smart energy management application 105p installed on the client device 119, a user can check the power level of the storage battery and configure certain parameters of the battery, such as preferred charging time, preferred appliances for discharge, etc. In some embodiments, such configuration information can be transmitted directly to the appliance 103, the independent battery 117, or the server 101 via the communication network 115.

[0034] In some embodiments, another instance of the smart energy management application 105p may reside on a single server 101a, or may be distributed across multiple servers (not shown) as desired or practical. The smart energy management server 101a may be implemented based on executable code and / or associated server components used to support computing on the server 101a.

[0035] In some embodiments, the smart energy management server 101a may be a cloud server having greater computing / communication capabilities and computing resources than the appliance 103, and may therefore perform more complex computations or communications than the appliance 103 may perform. For example, a complex decision-making process for automatically determining an ideal daily schedule for charging and / or dynamically adjusting the level of power provided from the battery module 107 to the coupled appliance 103 may be implemented in an instance of the smart energy management application 105p on the smart energy management server 101a, while receiving user input for manually setting a charging or discharging task may be implemented in an instance of the smart energy management application 105a or 105n on the appliance 103. For another example, the smart energy management application 105p may automatically communicate with one or more sensors to collect immediate contextual information in order to determine whether to start, stop, or adjust the power supplied to the appliance in a timely manner. In some embodiments, the smart energy management server 101a and the smart energy management application 105p may include additional functionality and components, such as in Figure 2 In some embodiments, some or all of the functionality of the smart energy management application 105p may be released to a smart energy management application resident in a particular appliance. In some embodiments, the smart energy management application 105p may be provided via a software-as-a-service (SaaS) platform.

[0036] In some embodiments, the additional data storage unit may be locally (e.g., Figure 11) or remotely (not shown) coupled to the server 101a. The data storage device 121 may include one or more non-transitory computer-readable media and may collectively include logical data, executable code, instructions and / or associated components to support storage, data management and retrieval of data related to energy management. The data related to energy management may include appliance data (model, type, manufacture, service date, etc.), stored battery data (e.g., size, power level, number of units, etc.), bidirectional converter data (e.g., input / output type, number of units, etc.), user profiles (e.g., user age, family size, etc.), user preferences about certain appliances (e.g., shower water temperature, shower time, washing machine load cycle, etc.), weather data, recipes for specific cooktops, features (e.g., capturing raw performance and command data to summarize usage over time), or any other data related to smart energy management. In some embodiments, the data related to energy management may also include operational data of components included in the system, including settings, states, levels, etc. related to batteries, loads, etc. In some embodiments, the collected and / or stored data can be transmitted to a server and used by the server for intelligent management. For example, intelligent management based on the data can be applied on the supply side (e.g., to optimize charging for battery life or cost) or on the demand side (e.g., to plan for common usage that has not been explicitly commanded by the user) for performance improvement and optimization.

[0037] The third-party server 101n may provide additional services to the smart energy management server 101a, or the services may be provided directly to the appliance 103. According to some embodiments, the third-party server 101n may be provided using other logical server instances, or included within the smart energy management server 101a. The server features and services provided may relate to intelligent decision-making processes and / or other context-driven services. Examples of other server services may include, but are not limited to, weather forecast services, power outage maps, alert services, instant recipes and other information delivery, etc.

[0038] In some embodiments, the smart energy management server 101a can also be configured to facilitate information communication between the appliances 103, the independent battery 117, the client device 119, and possible (one or more) other third-party servers 101n. For example, the appliances 103 can exchange calendar information via the smart energy management server 101a through the communication network 115, directly between the appliances 103 via the communication network 115, and / or through direct device-to-device information exchange, such as through local pairing or network connection (e.g., Bluetooth, near field communication, infrared, power line network, etc.).

[0039] The communication network 115 can be of a conventional type, wired and / or wireless, and can have a variety of different configurations, including a star configuration, a token ring configuration, or other configurations. For example, the communication network 115 can include one or more local area networks (LANs), wide area networks (WANs) (e.g., the Internet), public networks, private networks, virtual networks, mesh networks, point-to-point networks, and / or other interconnected data paths over which multiple devices can communicate. The communication network 115 can also be coupled to or include a portion of a telecommunications network for sending data with a variety of different communication protocols. In some embodiments, the communication network 115 includes a Bluetooth communication network or a cellular communication network for sending and receiving data, including via a short message service (SMS), a multimedia message service (MMS), a hypertext transfer protocol (HTTP), a direct data connection, a wireless application protocol (WAP), email, etc. In some embodiments, during data transmission, certain security mechanisms can be implemented in the communication network 115 to ensure that no user information is leaked during data transmission between different components of the intelligent management system 100.

[0040] In some embodiments, the smart energy management system 100 may include Figure 1 For example, the smart energy management system 100 may further include a power bus for connecting the different components included in the system.

[0041] Smart Energy Management Application

[0042] Figure 2 The example modules included in the smart energy management application 105 are illustrated, and the application can be an application resident in any of the appliances 103a-103n, the independent battery 117, the user device 119, or the smart energy management server 101a. According to one embodiment, the smart energy management application 105 can include a load and power supply characterization module 201, an energy allocation decision module 203a, a context information collection module 205, and a dynamic adjustment module 207. In some embodiments, when multiple battery modules are shared between different appliances and / or different residential units, the smart energy management application 105 can also include a battery aggregation module 209 and an energy redistribution module 211.

[0043] The load and power supply characterization module 201 can be configured to characterize how the input energy is supplied (e.g., identifying the power supply mode) and how the electrical appliances or related loads consume power (e.g., identifying the power consumption mode). In some embodiments, the intelligent energy management system 100 may optionally include an infrastructure configured to collect data from household loads. For example, there may be one or more sensors for monitoring the power usage of each electrical appliance. Such sensors may include certain current transducer sensors that are configured to monitor the power usage of large loads (such as air conditioners, washing machines, dryers, dishwashers, refrigerators, etc.) wired to dedicated circuits. These sensors can be connected to the in-panel meter and sample the front circuit power usage every second. In some embodiments, these sensors can be configured to be turned on only at a certain time period (e.g., at the data collection phase for pattern recognition) and turned off after the data collection phase ends to save energy.

[0044] In some embodiments, the load and power supply characterization module 201 can be configured to also identify patterns of power usage for each appliance based on the collected data. For example, the load and power supply characterization module 201 can generate a daily usage line for the appliance (e.g., average power usage at any time of the day during the pattern recognition phase) based on data collected over 1 month, 3 months, 6 months, 12 months, etc. Figure 3 An example graph containing three example power usage patterns identified for three appliances is illustrated. The X-axis of the graph indicates a day from 12 am to 12 pm (a full 24 hour period), the upper half of the Y-axis (e.g., +Y) indicates the power generated by the solar panel, and the lower half of the Y-axis (e.g., -Y) indicates the power usage consumed by the different appliances. Note that Figure 3 The electricity production pattern and electricity usage pattern in are not scaled on the Y-axis, but reflect the overall pattern during a typical day. For example, the actual electricity production may be several times (e.g., 5 times, 10 times, 15 times, etc.) the electricity usage of the appliance. In addition, Figure 3 The different patterns illustrated in FIG. 1 are for exemplary purposes, and the actual daily pattern on a particular day may differ from Figure 3 Those modes exemplified in .

[0045] As can be seen, line 301 indicates that the corresponding appliance uses less power during the day and more power during the night. Line 302 indicates that the corresponding appliance uses more power during meal times (such as morning, noon and evening). Line 303 indicates that the corresponding appliance uses more power during the morning hours and evening hours. It can be seen that line 302 is considered to be more peaky than the other two lines 301 and 303, which indicates that one or more short periods of very high demand for power are possible for the corresponding (one or more) appliances. When such high demand for power exceeds the limitations of the power supply during these periods, if there is no battery module disclosed herein, the performance of the corresponding appliance may be limited (e.g., longer cooking time than expected, lower cooking temperature than expected, etc.). However, in the present disclosure, due to the integration of the battery module, the integrated battery actually makes the appliance perform better than it would otherwise be possible. That is, when there is a power demand that exceeds the limitations of the existing power supply provided by the grid / electrical infrastructure, the integrated battery can act as a buffer for peak power to ensure that there is sufficient power supply for the appliance.

[0046] In some embodiments, such patterns can be identified for all connected appliances in a residential unit (e.g., appliances directly coupled to a battery module or indirectly connected to a battery module). Based on such information, it can be predicted which appliance will likely use how much power at any time of the day. In some embodiments, power production patterns (one or more) can be similarly identified. Figure 3 Also illustrated is a pattern of electricity production corresponding to the solar panels, as indicated by line 304. As can be seen from the peaks in line 304, solar energy production peaks around solar noon and decreases during dark periods such as at night or with cloud cover. Figure 3 From the electricity production and electricity usage patterns shown in , it can be seen that the supply of solar energy is very high during the midday period, while the demand for energy is high during the evening and morning periods when users are in their homes.

[0047] In some embodiments, there may be more than one pattern identified for an appliance or power source (such as a solar panel). For example, for an appliance, the power usage pattern may include a weekday pattern, a weekend pattern, a spring pattern, a summer pattern, an autumn pattern, a winter pattern, a winter sunny pattern, a winter snowy pattern, etc. Each pattern may show some changes when compared to other patterns. Similarly, for a power source such as a solar panel, it may also include a sunny pattern, a cloudy pattern, a spring pattern, a summer pattern, a summer pattern, a fall pattern, a winter pattern, a winter sunny pattern, a winter snowy pattern, etc. In some embodiments, not every pattern is generated based on data collection. Instead, a machine learning model can infer a pattern based on other available patterns and by considering additional information. For example, a summer cloudy pattern for a solar mode can be generated based on a summer sunny pattern and further based on how many clouds there are in a cloudy day (which can be obtained based on weather forecast information).

[0048] The energy allocation decision module 205 can be configured to determine the charging or discharging schedule for the battery module within the residential unit based on the identified power production and power usage patterns. For example, the energy allocation decision module 205 can predict the power usage for a day based on the identified pattern, and then manage the charging and discharging of the battery module based on the prediction. For example, the charging and discharging schedule can ensure that energy is purchased for storage when supply exceeds demand or the price is relatively low or negative, which can be reversely fed and used at a time when demand exceeds supply or the price is relatively high or positive. Specifically, the energy allocation decision module 205 can determine to purchase energy to charge the battery module during the peak solar energy availability period (which is also a period of low or negative pricing), and discharge during the peak demand period (which is also a period of peak or positive pricing). During periods of low demand (such as in the middle of the night), additional charging can be performed from the AC grid source.

[0049] It should be noted that while the battery charging or discharging described above may generally work well on most days and / or in most households, in some cases, for a particular household and / or for a particular day, there may be some variation in power usage and / or some variation in power production. For example, if a family is away on vacation, discharging may become unnecessary. Therefore, in some embodiments, the smart energy management application 105 may additionally include a contextual information collection module 205 that is configured to collect contextual information related to power usage of appliances in specific situations (e.g., for a particular household and / or on a particular day) and information related to power production.

[0050] For example, the context information collection module 205 can obtain information from a third-party service (e.g., The dynamic adjustment module 207 may receive calendar and travel information of family members (such as check-in reminders from emails, etc.), and identify that family members will go on vacation within a day. This information can then be forwarded to the dynamic adjustment module 207 to adjust the charging and / or discharging plan of the battery module (one or more) on this day. For another example, the context information collection module 205 may receive a weather forecast indicating that it will be cloudy within a day. This information may cause the dynamic adjustment module 207 to charge from the grid structure rather than from the solar panel during the day. In another embodiment, if the context information collection module 205 obtains information indicating that the family will go out for dinner, the dynamic adjustment module 207 may determine not to charge the battery module embedded in the cooktop. In some embodiments, the dynamic adjustment module 207 may also include dynamically adjusting the charging level of the modular battery. For example, if thick clouds and / or heavy rain are predicted during the day, the dynamic adjustment module 207 may adjust the charging of the battery module for the air conditioner much less than planned, because the air conditioner may not need to be turned on during this day. In addition, there may also be less electricity produced by the solar panel. By minimizing the charging of the battery modules for the air conditioner, the battery modules for other electrical appliances can obtain necessary charging from the solar panels during the day.

[0051] In some embodiments, if there are multiple battery modules connected to form a battery network within a residential unit or between residential units within a building or facility or small community, redistribution of power can also be performed on or between appliances (and other electrically driven units) during periods of low demand in order to synchronize and redistribute the stored power between the storage batteries during the discharge period. For example, consider the case where battery modules used for cooking during the evening become partially discharged after use in the evening. Those battery modules can be embedded in appliances (such as cooktops or ovens). Those battery modules can also be connected to the battery network and can therefore provide power later in the evening for use in other non-kitchen uses, such as water heating for bathing, etc. After the evening demand period ends, the battery modules for kitchen appliances can then be recharged by charging from the grid / electrical infrastructure (e.g., also known as grid power, fixed power, fixed AC, solar or local generation) or by redistribution from other appliances (or independent battery modules) that are idle, so that the battery modules of the kitchen appliances are recharged before there is a demand for use in the morning (e.g., for cooking breakfast). This recharging method can be applied within a residential unit, across residential units, across buildings, and across regions or systems to optimize the charging and discharging of battery modules.

[0052] Therefore, in some embodiments, the smart energy management application 105 may additionally include a battery aggregation module 209 and a stored energy reallocation module 211. The battery aggregation module 209 may be configured to aggregate information about the remaining power level of each battery module in the battery network, and also aggregate the predicted usage of (one or more) appliances coupled to each battery module for the next few hours of the day. By collecting all of this information, the energy reallocation module 211 may then determine whether to reallocate the energy stored in the battery module to another different battery module and / or different appliance within the same residential unit or across different residential units, different buildings, different areas, etc. In this way, since there are a large number of battery modules that can be shared between different appliances, the stability of the battery modules may be further improved and the efficiency of the battery modules in controlling peak power consumption, reducing high transient energy pricing, and / or handling power outages may be improved.

[0053] It should be noted that the modules for the smart energy management application described above are for illustrative purposes. In some embodiments, the smart energy management application may include additional components and / or functions not described above. For example, there may be additional machine learning engines that assist in the decision-making process, particularly when making instant decisions based on the collected contextual information and / or aggregated information. For example, based on contextual information, a machine learning model can predict when a specific user in a household will take a shower, how long the shower will last, and what the temperature of the water to be used in the shower is. Based on this information, the machine learning model can predict how much power should be provided to an electrically driven water heater to ensure that there is appropriate hot water ready for the user to take a shower. The functions and components of the smart energy management application are further described in detail below with reference to a battery module coupled to (one or more) electrical appliances and multiple battery modules within a battery network.

[0054] Intelligent energy management of individual battery modules

[0055] Figure 4 An example appliance equipped with a battery module according to some embodiments is illustrated. As illustrated, the appliance 403 is equipped with a battery module 407, which can be integrated into the appliance. The appliance can be a household appliance, such as a kitchen appliance, or any possible appliance. The battery 407 is coupled to a power source (e.g., a grid / electrical infrastructure 423) and a sink energy (e.g., (one or more) loads 413) via a bidirectional connection by means of a single-phase or multi-phase bidirectional inverter 411. The power source can be provided from the existing electrical infrastructure of a building or a group of buildings.

[0056] A high power bus 410 is provided between the power source / (one or more) loads and a bidirectional converter 411, which converts AC to DC in the direction from the power source 423 to the battery 407, and converts DC to AC in the direction from the battery 407 to the power source 423. The high power bus 410 may also be connected to the battery 407, the bidirectional converter 411, and (one or more) peak loads 413. In addition, the control unit 405 (embodied by the smart energy management application and the hardware associated therein) may be provided with (one or more) sensors 409 and switches, which are located at different locations, such as at the bidirectional converter 411 and the battery module 407, and at (one or more) peak loads 413 or near (one or more) peak loads 413. For example, (one or more) sensors 409 may be located inside or outside the appliance 403. In the case where the sensors are located inside the appliance, these sensors may include built-in sensors (e.g., temperature controllers for built-in stoves or ranges, infrared and / or contact sensors may be built-in to the appliance).

[0057] In some embodiments, the control unit 405 can provide a physical user interface 417 for the user, such as a manual control. Additionally or alternatively, the control unit 405 can automatically control battery charging and discharging to allocate power to (one or more) peak loads 413 by using a deterministic process and / or a predictive model based on machine learning or artificial intelligence. In some embodiments, the control unit 405 can provide peak power or average power, wherein the peak power can provide a fast and high peak of power for (one or more) peak loads 413. In some embodiments, the control unit 405 can also be configured to enhance or improve battery performance through certain existing means. As illustrated, the control unit 405 can communicate with different components (e.g., Figure 4 The components 407, 409, 411, 413 and 417 in the embodiment communicate with each other, wherein the power bus can be a normal power bus (ie, powering the embedded electronic devices with typical voltage and current).

[0058] In some embodiments, the appliance 403 can be coupled to a data storage unit 430. The data storage unit 430 can be a local or remote data storage unit and can be configured to store data generated by the smart energy management application and / or data collected from other sources (e.g., from a third-party service). For example, the data stored in the data storage unit 430 can include, but is not limited to, characterization 431, content 433, AI / ML 435, wireless (OTA) updates 437, and additional services 419.

[0059] Characterization 431 data may include data related to the power usage pattern generated for the appliance 403 or (one or more) loads 413 and the power supply pattern generated for the battery module. Content 433 may include contextual information that may affect the power usage of the appliance and the power supply for the battery module. Such information may include weather information, user schedule information, user preferences, user age or health status, or any other information that may affect the power usage of the appliance and the power supply of the battery module. In some embodiments, content 433 may also include different ways of using the appliance. For example, for a cooker, content 433 may include recipes, cooking instructions, and other types of content related to the type of cooking and / or the cooker being used. For example, for a recipe that requires the use of a wok, the content may include instructions or commands for controlling the power supplied to the wok or limiting the wok accordingly (e.g., limiting peak power to prevent burning food). In some embodiments, content 433 may additionally include information related to the limitations and energy requirements of the power supply of the appliance. It should be noted that the content 433 described above is not all-inclusive, and some other information may also be included in content 433.

[0060] AI / ML 435 may include (one or more) machine learning models that are pre-trained before being deployed to the control unit 405 or the smart energy management application. AI / ML 435 may also include data related to the training of the machine learning model and a partially trained model or a fully trained model that is not deployed to the control unit 405 or the smart energy management application. In some embodiments, AI / ML 435 may additionally include an algorithm or application for training the machine learning model. OTA update 437 may include any information received over the air, which may include instructions received from a user via a mobile device to manually set or adjust the charging or discharging schedule of the battery module at any point in time. OTA update 437 may also include other information received over the air. For example, the user may also provide information about food stored in the refrigerator or recipes used by the user in cooking, washing cycles selected by the user, and the like. In some embodiments, the OTA update may actually include a software or firmware update that changes any of the above modules or the modules described later. Additional services 439 may include certain notification services, alarm services, information display or delivery, and any other services related to energy management.

[0061] It should be noted that in some embodiments, there may be multiple appliances directly coupled to a single battery module. When there are multiple loads within a commercial, industrial, or residential unit or across multiple units, the control unit 405 can provide time transfer and management of resources so that loads or power can be shared within or across the commercial, industrial, or residential unit. In some embodiments, multiple battery modules are shared within these units instead. The application of energy sharing is described in further detail below.

[0062] Storage Energy Sharing

[0063] Figure 5 An example application scenario for sharing stored energy within an apartment building 510 according to some embodiments is illustrated. As illustrated, the example apartment building 510 includes four separate apartment units: unit 101, unit 102, unit 201, and unit 202. Each of the apartment units may have a certain number of appliances (only one appliance is shown in FIG. 1 ). Figure 5 In each apartment unit in the apartment unit, the appliance has a specific peak load. Among the apartment units, at least two apartment units include one or more battery modules coupled to the appliances in each apartment unit. Among the at least two apartment units, at least one apartment unit may include two or more battery modules within the apartment unit. In some embodiments, the battery modules in the apartment units and the appliances connected to the battery modules form a battery network. Therefore, the apartment building 510 can allow sharing of energy stored in the battery among different appliances within the same apartment unit or between different apartment units. As described earlier, the power input for the apartment building can be provided by an electricity service provider (e.g., ) 523 and provided by solar panels 525. The electrical energy may be distributed to each of the apartment units by means of existing circuits and infrastructure, including distribution to connected battery modules (e.g., via bidirectional converters) and / or appliances. At each apartment unit, a unit-level circuit panel may be provided, and on one of the circuits, there may be one or more connected appliances. When there is a coupled battery, the appliance may additionally include a bidirectional converter, a power bus, (one or more) sensors, a control unit, and / or a user interface, as described earlier in Figure 4 Described in .

[0064] In some cases, it may be beneficial to share the energy stored in the battery modules among different appliances or apartment units using a battery network to improve energy usage efficiency. For example, if an apartment unit (e.g., unit 101) is not in use (such as when the occupant of the apartment unit is out of town), the energy stored in the battery modules of the appliance(s) within the apartment unit may be redistributed to other connected units during periods of peak power consumption, high transient energy pricing, and / or during power outages. Thus, short-term redundant emergency use power may be provided at the building level. Similarly, within the apartment unit itself, the battery module may provide backup power to another appliance during periods of peak power consumption, high transient energy pricing, and / or during power outages. Thus, the apartment building may manage the use of power in the context of power pricing or in an emergency.

[0065] In some embodiments, to allow for sharing of stored energy, a control unit for an appliance (also referred to as an appliance-specific control unit) may coordinate (e.g., via communications and / or a power bus) with other control units for other appliances within the same apartment unit or between different apartment units in apartment building 401. In this regard, the appliance-specific control units may be implemented in a master / slave mode, wherein one of the appliance-specific control units functions as a primary control unit, while all other appliance-specific control units function as secondary control units and listen to the primary control unit. Alternatively or in addition, there may be a specially configured central control unit (e.g., resident in a central location) that controls all appliance-specific control units. Figure 5 A control unit in the external first and / or third party service 509).

[0066] In some embodiments, the central control unit or main control unit may be configured to monitor the instantaneous power usage of the connected appliances and the remaining power level of the connected battery modules. The central control unit or main control unit may reallocate the stored energy in the connected battery modules based on demand. For example, if the residents in apartment unit 101 are out of town, the energy stored in the battery module(s) in apartment unit 101 may be reallocated to other apartment units if they lack the power stored in the battery modules for peak loads.

[0067] In some cases, such as when there is a power outage, there is a shortage of stored energy in all appliances and / or apartment units. At this time, the central control unit or main controller can reallocate the stored energy based on priority. Therefore, in some embodiments, the central control unit or main control unit can additionally include a priority determination module configured to determine the power usage priority for appliances within an apartment unit and / or within a building.

[0068] In some embodiments, a priority determination module in a central control unit or a main control unit can determine the priority of each appliance based on the general function of each appliance. For example, the priority determination module can determine that a refrigerator generally has a higher priority because if the refrigerator loses power for too long, the food stored in the refrigerator may become inedible. Similarly, the priority for a water heater may be lower than that of a refrigerator but higher than that of other appliances such as a clothes dryer or a dishwasher. In this way, the priority determination module can sort the appliances included in an apartment unit and / or an entire building based on the determined priority of each appliance.

[0069] In some embodiments, the priority determination module may also determine priorities at the apartment unit level. That is, the priority determination module may determine that some apartment units within an apartment building have higher priorities than other units. For example, if an apartment unit has an elderly person who generally requires more stringent care, the apartment unit may have a higher priority than other apartment units. In the event of a power outage, stored power may be provided to this unit first to ensure that this apartment unit has the necessary power. In one embodiment, if the elderly person in the apartment unit uses an electrically powered medical support device, priority-based energy sharing may be used to ensure that the medical support device will not immediately lose power. In another embodiment, the priority determination module may determine that the apartment unit may have a newborn baby, and therefore determine to increase the priority of the apartment unit to ensure that the room temperature is stable at the apartment unit.

[0070] In some embodiments, the disclosed smart power management system may include one or more sensors configured to monitor apartment units in an apartment building when determining appliance-level and / or apartment-unit-level priorities. In one embodiment, the disclosed smart power management system may include an audio sensor to detect sounds from an apartment unit to determine whether there is a newborn baby (e.g., based on the sound of a baby crying) or an elderly person (e.g., based on frequent coughing). In some embodiments, a machine learning model trained for speech recognition may be included in the audio sensor or the smart power management system to provide the necessary information for determining priorities.

[0071] In some embodiments, the information obtained from the sensor can also allow further adjustment of the priority of certain appliances and / or apartment units. In one embodiment, the intelligent power management system disclosed herein can include a video sensor coupled to a stove to monitor the cooking process and determine whether an enhanced power supply should be provided to the stove in real time based on a recipe (or some other protocol). At this point, the priority for the stove can be instantly increased. In another embodiment, a video sensor coupled to the interior of a refrigerator can determine the type of food stored in the refrigerator. In general, some types of food (such as vegetables) may be more temperature sensitive than other types of food (such as eggs). Therefore, if the video sensor detects that there is hardly any temperature-sensitive food stored inside the refrigerator, the priority of the refrigerator can be downgraded to a much lower level based on the information obtained from the video sensor.

[0072] In some embodiments, based on the determined priorities at the appliance level and / or at the apartment unit level, when multiple appliances and / or apartment units require power supply at about the same time and when there is not enough power supply for all of these needs, the central control unit or the main control unit can determine how to distribute the stored power between different appliances in the same apartment unit or between different apartment units. In general, when many appliances or apartment units require power supply at the same time (e.g., when there is a power outage), higher priority appliances or apartment units get higher priority when power is redistributed. For example, for appliances or devices with extremely high priority (e.g., medical support equipment), the central control unit and the main control unit can reserve energy stored by battery modules in the battery network to ensure that there is enough power to operate the appliance or device for at least a certain period of time (e.g., 1 hour, 2 hours, 4 hours, 8 hours, 16 hours, 24 hours, etc.). This can ensure that a limited amount of stored energy is used appropriately to improve the efficiency of the energy stored by the battery modules.

[0073] Implementation

[0074] The disclosed embodiments additionally include methods for intelligent energy management of electrical appliances equipped with the battery modules. Figure 6 An example method for managing a single battery module according to some embodiments is illustrated, and Figure 7 An example method for managing a plurality of battery modules according to some embodiments is illustrated.

[0075] The example method 600 is illustrated with reference to an application scenario in which a single appliance (or multiple appliances) is connected to a single battery module. In step 612, the power usage of the appliance coupled to the battery module is first monitored. This includes monitoring the power usage of the appliance within a certain period of time (e.g., 1 month, 3 months, 6 months, 12 months, etc.). In step 614, the power usage pattern of the appliance connected to the battery module is identified. The power usage pattern may include a single pattern or may include a group of patterns, such as a weekday pattern, a weekday pattern, a seasonal pattern, etc. The method 600 also monitors the power supply of one or more power sources in step 616. For example, the availability or cost of power from a solar panel or a power grid may fluctuate throughout the day. For another example, the power supply from a solar panel may be peak around noon. In step 618, the power supply pattern of one or more power sources for the battery module is identified. Similar to the power usage pattern, the power supply pattern may also include a group of patterns, such as a seasonal pattern, a cloudy day pattern, a sunny day pattern, etc. In step 620, a power charging and discharging schedule for the battery module is determined based on the identified power usage pattern of the appliance and the power supply pattern of one or more power sources supplying power to the battery module. In one embodiment, if the day is a weekend in summer, the weekend summer pattern of the appliance and / or the power source can be used to determine the schedule for charging and discharging the battery module.

[0076] In some embodiments, the determined charging and discharging schedule for the battery module can be dynamically adjusted for a specific day and time, because not every day is the same. Therefore, method 600 may also include step 622, which collects contextual information related to the power usage of the appliance and the power supply of one or more power sources that may affect the charging and / or discharging of the battery module. For example, due to a busy schedule, a regular dinner is canceled, which then affects the power usage of the cooktop. The discharge of power to the cooktop through the battery module coupled to the cooktop can then be changed. In step 624, the power charging and / or discharging schedule can then be dynamically adjusted based on the contextual information related to the power usage of the appliance and / or the power supply of one or more power sources.

[0077] Despite Figure 6 It is not specifically illustrated in the example, but in some embodiments, it is illustrated in Figure 6The battery module in can be applied to multiple appliances. That is, there are two or more appliances connected to the same battery module, and therefore the battery module can discharge two or more appliances within a certain period of time. For example, based on demand, during the day, the battery module can provide power to the cooktop at 5:45-6:30 pm, and then provide power to the electric water heater at 8:30-9:30 pm. In some embodiments, if there are two connected appliances that need power at the same time and the battery module may not be able to provide power to both appliances at the same time, the battery module can provide power to the appliance with a higher priority. In some embodiments, if the battery module is embedded in an appliance, the appliance can have a higher priority than other appliances connected to the battery module. In some embodiments, the priority can be determined in other different ways as described earlier. For example, if the appliance has a peak power consumption that is so high that it is actually not allowed to run on any kind of existing approved home infrastructure, the appliance can have a higher priority than other appliances. For example, the power usage pattern for the appliance can be determined, and then the power charging and discharging schedule can be determined and / or dynamically adjusted based on the power usage pattern for the appliance to ensure that the appliance operates properly. In this way, the disclosed system can actually unlock appliance requirements to allow certain disallowed appliances to be installed at the home infrastructure (e.g., appliances that are not allowed to operate on existing home infrastructure that does not have the battery modules disclosed herein).

[0078] The example method 700 also illustrates an example scenario of sharing multiple battery modules among different appliances and / or different residential units. The method 700 begins by identifying, in step 712, power usage patterns of two or more appliances connected to a battery network, and identifying, in step 714, power supply patterns of two or more battery modules in the battery network. The battery network includes two or more battery modules that can be charged and / or discharged. In some embodiments, the battery network may refer to all battery modules, all appliances connected to the battery modules, and other ancillary components such as sensors, control units, bidirectional converters, peak loads, etc. The power usage pattern for each appliance and the power supply pattern for each battery module may be determined according to the methods described earlier (e.g., as in Figure 6 In step 716, a charging and discharging schedule for two or more battery modules in the battery network is determined based on the power usage pattern and the power supply pattern. In some embodiments, the determined charging and discharging schedule can also be dynamically adjusted according to contextual information for a specific time point on a specific day related to each specific appliance, as described earlier (e.g., as described in Figure 6 described in ).

[0079] In step 718, method 700 may also determine whether stored power redistribution is required for one or more electrical appliances at a time point in the day. The stored power may refer to the sum of the remaining power stored in all battery modules within the battery network. In some embodiments, the instantaneous charge level for each battery module in the battery network may be determined separately, and the total available power within the battery network may be determined accordingly. In order to determine whether stored power redistribution is required, method 700 may check whether there is still power remaining in the battery network when the battery module directly coupled to the electrical appliance does not have power remaining or does not have enough power to supply the expected power usage of the electrical appliance. Here, the battery module directly coupled to the electrical appliance refers to a battery module that is disposed inside or outside the electrical appliance and is primarily used to provide power to the electrical appliance. In step 720, when it is determined that stored power redistribution is not required, the battery modules included in the battery network may be charged and / or discharged according to the schedule determined in step 716.

[0080] On the other hand, in step 722, when it is determined that reallocation is required for one or more appliances, the method 700 further determines in step 722 whether there are more than one appliances that need power reallocation. If there is only one appliance that needs power reallocation, the power stored in the battery network is reallocated to the appliance that needs power reallocation in step 724. Power can be reallocated from the battery module with the highest power remaining, with or without considering the necessary power supply required to provide power to the (one or more) directly coupled appliances of the battery module before the next scheduled battery charge. In some embodiments, the battery modules are preferably selected from the same residential unit. When it is determined that reallocation is required for more than one appliance at a time point in the day, the method 700 can further determine the priority of the two or more appliances that need power reallocation in step 726. One of the appliances may have a higher priority than the other, and therefore may be more likely to have power reallocated to it. In some embodiments, the priority can also be determined at the residential unit level. If an appliance from one residential unit has a higher priority, that appliance may be more likely to have power reallocated than another appliance with a higher priority but from a residential unit with a lower priority, even though the appliance itself may have a lower priority.

[0081] In some embodiments, machine learning models or other algorithms can be further employed to predict which appliance should have a higher priority at any point in time by taking into account changing conditions, so as to ensure that power is properly redistributed at a single point in time. This then improves the power usage efficiency for the power stored in the battery network.

[0082] Additional Notes

[0083] Throughout this specification, multiple instances may implement components, operations, or structures described as a single instance. Although the individual operations of one or more methods are illustrated and described as separate operations, one or more of the individual operations may be performed simultaneously, and there is no requirement to perform the operations in the order illustrated. Structures and functions presented as separate components in the example configurations may be implemented as combined structures or components.

[0084] Similarly, structures and functionality presented as a single component may be implemented as separate components. These and other variations, modifications, additions, and improvements fall within the scope of the subject matter herein.

[0085] Certain embodiments as described herein include logic or a certain number of components, modules or mechanisms, for example, as illustrated and described above in the accompanying drawings. Modules can constitute software modules (e.g., code embodied on a machine-readable medium) or hardware modules. A hardware module is a tangible unit capable of performing certain operations and can be configured or arranged in a certain manner. In example embodiments, one or more computer systems (e.g., stand-alone, client or server computer systems) or one or more hardware modules of a computer system (e.g., a processor or a group of processors) can be configured by software (e.g., an application or application portion) as a hardware module that operates to perform certain operations as described herein.

[0086] In various embodiments, hardware modules may be implemented mechanically or electronically. For example, a hardware module may include dedicated circuitry or logic that is permanently configured to perform certain operations (e.g., as a dedicated processor such as a field programmable gate array (FPGA) or an application specific integrated circuit (ASIC)). A hardware module may also include programmable logic or circuitry that is temporarily configured to perform certain operations by software (e.g., as contained within a general purpose processor or other programmable processor). It will be understood that the decision to implement a hardware module mechanically, with dedicated and permanently configured circuitry, or with temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations.

[0087] The various operations of the example methods described herein may be performed at least in part by one or more processors, which are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions. In some example embodiments, the modules mentioned herein may include processor-implemented modules.

[0088] One or more processors may also operate in a "cloud computing" environment or as "software as a service" (SaaS) to support the execution of the relevant operations. For example, at least some of the operations may be performed by a group of computers (such as an embodiment of a machine including a processor) that are accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., an application programming interface (API)).

[0089] The execution of certain operations may be distributed among one or more processors, which may reside not only in a single machine but also on a number of machines. In some example embodiments, one or more processors or processor-implemented modules may be located in a single geographic location (e.g., in a home environment, an office environment, or a server farm). In other example embodiments, one or more processors or processor-implemented modules may be distributed across a number of geographic locations.

[0090] Some parts of this specification are presented in the form of algorithms or symbolic representations of data stored as bits or binary digital signals in machine memory (e.g., computer memory) for operation. These algorithms or symbolic representations are embodiments of the technology used by those of ordinary skill in the field of data processing to convey the essence of their work to other technicians in the field. As used herein, an "algorithm" is a series of self-consistent operations or similar processes that lead to a desired result. In this context, algorithms and operations involve physical manipulation of physical quantities. Typically, but not necessarily, such quantities can take the form of electrical, magnetic, or optical signals that can be stored, accessed, transferred, combined, compared, or otherwise manipulated by a machine. Sometimes, mainly for general reasons, it is convenient to use words such as "data," "content," "bit," "value," "element," "symbol," "character," "item," "number," "numerical value," etc. to refer to such signals. However, these words are only convenient labels and are associated with appropriate physical quantities.

[0091] Unless specifically stated otherwise, discussions herein using terms such as "processing," "computing," "calculating," "determining," "presenting," "displaying," and the like may refer to the actions or processes of a machine (e.g., a computer) that manipulates or transfers data represented as physical (e.g., electronic, magnetic, or optical) quantities within one or more memories (e.g., volatile memory, non-volatile memory, or a combination thereof), registers, or other machine components that receive, store, transmit, or display information.

[0092] As used herein, any reference to "one embodiment" or "an embodiment" means that a particular element, feature, structure, or characteristic described in conjunction with the embodiment is included in at least one embodiment. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment.

[0093] Some embodiments may be described using the expressions "coupled" and "connected" and their derivatives. For example, some embodiments may be described using the term "coupled" to indicate that two or more elements are in direct physical or electrical contact. However, the term "coupled" may also mean that two or more elements are not in direct contact with each other, but can still cooperate or interact with each other. In this context, the embodiments are not limited.

[0094] As used herein, the terms "comprises," "comprising," "includes," "including," "has," "having," or any other variation thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, article, or apparatus that includes a list of elements is not necessarily limited to those elements, but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. In addition, unless expressly stated to the contrary, "or" refers to an inclusive or and not an exclusive or. For example, condition A or B is satisfied by any of the following conditions: A is true (or present) and B is false (or absent), A is false (or absent) and B is true (or present), and both A and B are true (or present). In addition, "automatic" can refer to fully automatic or semi-automatic implementations - involving user or operator control of certain aspects of the implementation - depending on the desired implementation of the implementation of the content of the present disclosure by a person of ordinary skill in the art.

[0095] In addition, the use of "a" or "an" is adopted to describe the elements and components of the embodiments herein. This is done only for convenience and to give a general sense of the invention claimed. This specification should be understood to include one or at least one, and the singular also includes the plural, unless it is obvious that there is another meaning.

[0096] In addition, sequential terms (such as "first", "second", "third", etc.) may be used in the description and claims for marking purposes only, and should not be limited to referring to the described actions or items occurring in the described order. The actions or items may be sequenced into a different order or may be performed in parallel or dynamically without departing from the scope of the present disclosure.

[0097] After reading this disclosure, those skilled in the art will appreciate other additional alternative structural and functional designs for the systems described above. Therefore, although specific embodiments and applications have been illustrated and described, it should be understood that the disclosed embodiments are not limited to the precise configurations and components disclosed herein. Various modifications, changes and variations may be made in the arrangement, operation and details of the methods and apparatus disclosed herein - which will be apparent to those skilled in the art without departing from the spirit and scope defined in the appended claims.

Claims

1. A system for intelligent power management, comprising: Electrical appliances; a battery module, the battery module being coupled to the electrical appliance, the battery module being configured to provide power to the electrical appliance; a bidirectional converter coupled to the appliance and the battery module via a power bus, the bidirectional converter converting between alternating current (AC) and direct current (DC) and interfacing with a power infrastructure external to the appliance; as well as A control unit is communicatively coupled to the battery module, the bidirectional converter, and the appliance, the control unit being configured to determine a charging and discharging schedule for the battery module. 2 . The system of claim 1 , wherein the battery module is coupled to the appliance by being integrated into the appliance.

3. The system of claim 1, wherein the battery module provides power to the appliance according to the determined charging and discharging schedule. 4 . The system of claim 1 , wherein the control unit is further configured to determine a power usage pattern of the electrical appliance and a power supply pattern of the power infrastructure for providing power to the battery module. 5 . The system of claim 4 , wherein the control unit is further configured to determine the charging and discharging schedule for the battery module based on the power usage pattern and the power supply pattern.

6. The system of claim 1 , further comprising one or more sensors or third-party services coupled to the control unit and configured to collect contextual information related to the battery module or one or more of the appliances.

7. The system of claim 6, wherein the control unit further comprises a machine learning model trained to predict usage of the appliance at a point in time based on the collected contextual information.

8. The system of claim 6, wherein the control unit is further configured to adjust the determined schedule based on the collected context information.

9. The system of claim 1, further comprising a physical user interface configured to receive user input for manually editing the charging and discharging schedule for the battery module at a point in time.

10. The system according to claim 1, wherein the electrical appliances include two or more electrical appliances, and the battery module includes two or more battery modules, and at least two of the two or more electrical appliances are coupled to the two or more battery modules.

11. The system of claim 10, wherein the control unit is further configured to redistribute power stored in the two or more battery modules by providing power to the appliance from a battery module that is not directly coupled to the appliance.

12. A method for intelligent power management, the method comprising: collecting power usage data of the electrical appliances during a first time period; determining a power usage pattern of the appliance based on the power usage data; collecting power supply data of a battery module during a second time period, the battery module being coupled to the electrical appliance via a bidirectional converter and configured to provide power to the electrical appliance; determining a power supply mode of the battery module based on the power supply data; as well as A charging and discharging schedule of the battery module is determined based on the power usage pattern of the electrical appliance and the power supply pattern of the battery module.

13. The method according to claim 12, further comprising: collecting contextual information related to one or more of power usage of the appliance or power supply for the battery module for a point in time of day; as well as The charging and discharging schedule for the point in time is adjusted based on the collected contextual information.

14. The method of claim 13, wherein the contextual information is collected from one or more sensors coupled to one or more of the appliance or battery module. The method of claim 13 , wherein the context information is collected from one or more third-party services.

16. A method for intelligent power management, the method comprising: Collecting electricity usage data for two or more appliances; determining a power usage pattern of each of the two or more electrical appliances based on the power usage data; collecting power supply data of two or more battery modules, at least two of the two or more electrical appliances being coupled to the two or more battery modules via a set of bidirectional converters; determining a power supply mode of each of two or more battery modules based on the power supply data; as well as A charging and discharging schedule of each of the two or more battery modules is determined based on the power usage pattern of each of the two or more electrical appliances and the power supply pattern of each of the two or more battery modules.

17. The method according to claim 16, further comprising: Based on contextual information related to power usage of at least one appliance, a charging and discharging schedule of at least one of the two or more battery modules is dynamically adjusted.

18. The method according to claim 16, further comprising: determining whether power reallocation is required for one of the two or more appliances; as well as When it is determined that one of the two or more electrical appliances requires the power redistribution, power is redistributed from the uncoupled battery module to the one of the two or more electrical appliances.

19. The method according to claim 16, further comprising: determining whether power reallocation is required for at least two of the two or more electrical appliances; as well as When it is determined that at least two of the two or more electrical appliances require the power redistribution, a priority of each of the at least two of the two or more electrical appliances is determined.

20. The method according to claim 19, further comprising: Power is reallocated to the at least two of the two or more electrical appliances according to the determined priority of each of the at least two electrical appliances.

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