Refrigerator and control method thereof

Abstract

The invention provides a refrigerator and a control method thereof. The controller is designed to receive the time-of-use electricity price data and extract the target time period, the control parameter set capable of being dynamically adjusted is generated, and fine control over the running state of the compressor is achieved. Specifically, the control parameters are dynamically adjusted along with the time change in the target time period, so that the operation state of the compressor can flexibly respond to the electricity price change and the power grid load demand in different time periods. Compared with a method that the control parameters are fixed or the adjustment granularity is large in the prior art, the method has the advantages that the load can be adjusted more finely and dynamically in the target time period, the load trough is effectively filled, and the load peak is reduced, so that the smooth effect of a load curve is remarkably improved, the operation energy efficiency of the refrigerator is optimized, and the power utilization cost of a user is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of refrigerators, and in particular to a refrigerator and a control method thereof. Background Art

[0002] In the prior art, in the process of controlling refrigerators based on time-of-use electricity prices, the load regulation is not precise enough, resulting in a technical problem of poor load curve smoothing effect. Summary of the invention

[0003] The purpose of the present invention is to overcome the above technical deficiencies and provide a refrigerator and a control method thereof to solve the technical problem in the related art that the load regulation is not precise enough, resulting in poor load curve smoothing effect.

[0004] In order to achieve the above technical objectives, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a refrigerator, comprising: Refrigerator and / or freezer; A compressor, which is used to generate cold energy and input it into the refrigerating chamber and / or freezing chamber; A controller, which is used to receive time-of-use electricity price data, parse the time-of-use electricity price data to extract at least one target time period, and then generate a control parameter set corresponding to the target time period based on the at least one target time period; wherein the control parameter set includes multiple control parameters, and the control parameters are at least used to control the operating state of the compressor; wherein the control parameters are dynamically adjusted as time changes within the target time period; according to the control parameter set, at least the operating state of the compressor is controlled within the target time period.

[0005] In a second aspect, the present invention provides a method for controlling a refrigerator, wherein the refrigerator includes a compressor, and the method includes: Receive time-of-use electricity price data; Parsing the time-of-use electricity price data to extract at least one target time period; Based on the at least one target period, a control parameter set corresponding to the target period is generated; wherein the control parameter set includes a plurality of control parameters, and the control parameters are at least used to control the operating state of the compressor; wherein the control parameters are dynamically adjusted as time changes within the target period; According to the control parameter set, at least the operating state of the compressor is controlled within the target time period.

[0006] Beneficial effects: The present invention realizes refined control of the operating state of the compressor by designing a controller to receive time-of-use electricity price data and extract the target time period, generating a set of control parameters that can be dynamically adjusted. Specifically, the control parameters are dynamically adjusted as the time changes within the target time period, so that the operating state of the compressor can flexibly respond to changes in electricity prices and grid load demands in different time periods. Compared with the methods in the prior art in which the control parameters are fixed or the adjustment granularity is large, the present invention can perform more refined dynamic adjustment of the load within the target time period, effectively fill the load troughs and reduce the load peaks, thereby significantly improving the smoothing effect of the load curve, optimizing the operating energy efficiency of the refrigerator, and reducing the user's electricity costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 is a block diagram of a refrigerator provided by an embodiment of the present invention; Figure 2 is a block diagram of a refrigerator provided by an embodiment of the present invention; Figure 3 is a flow chart of a refrigerator control method provided by an embodiment of the present invention; Figure 4 is a flow chart of a refrigerator control method provided by an embodiment of the present invention; Figure 5 is a flow chart of a refrigerator control method provided by an embodiment of the present invention; In the attached figure: Refrigerator or freezer: 100; Compressor: 200; Controller: 300; Positioning device: 400; Cloud: 500. DETAILED DESCRIPTION

[0008] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0009] In the related technology, refrigerators are a necessity in modern household appliances, and their operating status has a direct impact on household electricity costs and electricity load (grid load and household electricity load). With the continuous optimization of energy price mechanisms, many regions have implemented time-of-use electricity price policies, dividing a day into multiple electricity price periods, and setting different electricity price levels according to the level of grid load during the period, in order to guide users to use electricity during periods with lower electricity prices and reduce load pressure during peak hours.

[0010] In the related art, refrigerator control methods based on time-of-use electricity prices usually use fixed control parameters. For example, the compressor is stopped during peak hours and started at a constant operating state during off-peak hours to reduce electricity costs. However, this extensive control method has significant defects: due to the complex and diverse internal load change trends in different time periods of time-of-use electricity prices, fixed control parameters cannot accurately adapt to the dynamic changes of the load, resulting in insufficient load regulation and poor smoothing of the load curve, which is not conducive to achieving the goal of peak shaving and valley filling. In addition, this control method may also cause the equipment to operate inefficiently in certain specific periods, increasing electricity costs and equipment wear.

[0011] Through the description of the above related technologies, it can be known that the core reason why load regulation is not fine enough is that the existing control method ignores the dynamic characteristics of the load curve changing over time during the target period, resulting in the adjustment of control parameters unable to accurately match the actual load demand. The changes in the load curve of the power grid during the day usually show stage characteristics. For example, the trough period may experience a dynamic change process in which the load gradually decreases, the lowest point stabilizes, and gradually rises. Therefore, the control parameters only rely on static settings or fixed strategies, which are difficult to adapt to the trend of load curves changing over time, and thus miss the opportunity to fine-tune load regulation by dynamically adjusting control parameters.

[0012] Therefore, in the prior art, in the process of controlling the refrigerator based on the time-of-use electricity price, the load regulation is not precise enough, resulting in a technical problem of poor load curve smoothing effect.

[0013] like Figure 1 As shown, this embodiment provides a refrigerator, comprising: The refrigerating chamber 100 and / or the freezing chamber 100 .

[0014] It is understandable that the refrigerator may include a refrigerating chamber 100. It may also include a freezing chamber 100. It may also include a refrigerating chamber 100 and a freezing chamber 100 at the same time.

[0015] The compressor 200 is used to generate cold energy and input the cold energy into the refrigerating chamber 100 and / or the freezing chamber 100 .

[0016] A controller 300 is used to receive time-of-use electricity price data, parse the time-of-use electricity price data to extract at least one target time period, and then generate a control parameter set corresponding to the target time period based on the at least one target time period; wherein the control parameter set includes multiple control parameters, and the control parameters are at least used to control the operating state of the compressor 200; wherein the control parameters are dynamically adjusted as time changes within the target time period; according to the control parameter set, at least the operating state of the compressor 200 is controlled within the target time period.

[0017] This embodiment realizes refined control of the operating state of the compressor 200 by designing the controller 300 to receive time-of-use electricity price data and extract the target time period, and generate a set of control parameters that can be dynamically adjusted. Specifically, the control parameters are dynamically adjusted as the time changes within the target time period, so that the operating state of the compressor 200 can flexibly respond to changes in electricity prices and grid load demands in different time periods. Compared with the methods in the prior art in which the control parameters are fixed or the adjustment granularity is large, this solution can perform more refined dynamic adjustment of the load within the target time period, effectively fill the grid load troughs and reduce load peaks, thereby significantly improving the smoothing effect of the load curve, optimizing the refrigerator operation energy efficiency, and reducing the user's electricity cost. This method is highly intelligent and can better adapt to the electricity demand under the time-of-use electricity price strategy, and realize the coordinated optimization of refrigerator operation and load.

[0018] like Figure 2 As shown, in some embodiments, the refrigerator further includes: The positioning device 400 is used to obtain the positioning information of the refrigerator; wherein the positioning information is used to provide to the controller 300, and the controller 300 sends a request to the cloud 500 based on the positioning information to obtain time-of-use electricity price data.

[0019] In this embodiment, the positioning device 400 may be a GPS positioning module.

[0020] In this embodiment, the positioning device 400 may be a Wi-Fi positioning module. Specifically, the controller 300 may determine the geographical location of the refrigerator using a Wi-Fi location database based on the signal strength and access point information of the surrounding Wi-Fi network.

[0021] In this embodiment, the positioning device 400 may be a Bluetooth positioning module. Specifically, the controller 300 may determine the position by calculating the distance relationship of the Bluetooth signal based on the signal strength of the nearby Bluetooth beacon.

[0022] In this embodiment, the positioning device 400 is provided to obtain the positioning information of the refrigerator, and the positioning information is provided to the controller 300. The controller 300 can send a request to the cloud 500 based on the positioning information to obtain the time-sharing electricity price data. This design enables the refrigerator to automatically adapt to the electricity price policies of different regions and realize the acquisition of accurate electricity price data for a specific region without the need for manual input or adjustment by the user.

[0023] In some embodiments, the refrigerator further comprises: A cold storage device is used to store the cold energy generated by the compressor.

[0024] In this embodiment, the cold storage device can be arranged in the refrigerator compartment 100 of the refrigerator, can be arranged in the freezer compartment 100 of the refrigerator, can be arranged in both the refrigerator compartment 100 and the freezer compartment 100, or can be arranged between the refrigerator compartment 100 and the freezer compartment 100. For example, the cold storage device is placed in the interlayer or passage between the refrigerator compartment 100 and the freezer compartment 100, and the cold energy can be flexibly distributed to the refrigerator compartment 100 or the freezer compartment 100.

[0025] In this embodiment, the cold storage device may include a shell, that is, an external structure that wraps the cold storage device to provide physical protection. The interior of the shell may be filled with a phase change material. The phase change material can store and release a large amount of cold through phase change. The phase change material may be a water-based material, a salt solution, or a low-temperature organic substance.

[0026] The inner and outer surfaces of the shell may be further provided with heat exchange components. The heat exchange components provided inside can store the cold energy generated by the compressor refrigeration in the cold storage medium through heat exchange. The heat exchange components provided on the outer surface can improve the heat exchange efficiency between the cold storage device and the surrounding air.

[0027] In this embodiment, by providing a cold storage device in the refrigerator, the cold energy generated by the compressor can be effectively stored to support the cold energy demand of the refrigerator in different time periods. The introduction of the cold storage device enables the refrigerator to store cold energy in priority during the target time period when the electricity price is low or the grid load is low, and reduce the operation of the compressor during the time period when the electricity price is high or the grid load is high, and use the stored cold energy to maintain the normal operation of the refrigerator. This design not only reduces the operating cost of the refrigerator, but also effectively alleviates the load pressure of the grid during the peak period of electricity consumption, further achieving the goal of peak shaving and valley filling, while improving the energy efficiency of the refrigerator operation.

[0028] In some embodiments, the refrigerator further comprises: The defrost heater is used to perform a defrost operation within a target period according to a control parameter set generated by the controller 300 .

[0029] In this embodiment, by setting a defrost heater and combining the control parameter set generated by the controller 300, the defrost operation can be performed intelligently within the target period. This design not only effectively reduces the user's electricity cost, but also reduces the impact on the grid load, while ensuring the defrost efficiency of the refrigerator, further improving the overall intelligence level and energy saving effect.

[0030] like Figure 3 As shown, this embodiment provides a control method for a refrigerator, the refrigerator at least includes a compressor, the execution subject of the method may be a controller, and the method may include: Step S12: Receive time-of-use electricity price data.

[0031] In this embodiment, the receiving action can be represented as the controller first determines the current location information of the refrigerator through the positioning device (GPS positioning module) preset in the refrigerator. Then, the controller sends a request to the cloud to obtain the time-sharing electricity price data according to the positioning information. Finally, the controller receives the time-sharing electricity price data sent by the cloud.

[0032] In this embodiment, the receiving action can be represented by the controller receiving time-of-use electricity price data published by the power company or grid operator through a built-in wireless communication module (for example, a Wi-Fi module, a 5G module or an Internet of Things communication module).

[0033] In this embodiment, the receiving action can be represented as the controller receiving the time-sharing electricity price data from the home gateway or the smart home system. It is understandable that the controller can be connected to the home gateway or the smart home system, and the home gateway or the smart home platform uniformly receives and distributes the time-sharing electricity price data. For example, the electricity price data can be obtained by the home gateway from the power grid server and then sent to the refrigerator controller.

[0034] In this embodiment, the time-of-use electricity price data may be time-of-use electricity price data representing five time periods, time-of-use electricity price data representing four time periods, or time-of-use electricity price data representing three time periods.

[0035] In this implementation, the time-of-use electricity price data may be a data table representing the time-of-use electricity price data.

[0036] In this implementation, the time-of-use electricity price data may be an array or a time series, in which each element represents the electricity price for a certain time period.

[0037] In this implementation, the time-of-use electricity price data may be a piecewise function, and different time periods correspond to different electricity prices.

[0038] In this embodiment, the time-sharing electricity price data may also be a graphical data. For example, the time-sharing electricity price data may exist in a graphical form, such as an electricity price curve chart, and the controller extracts the electricity price information through image recognition or curve fitting technology.

[0039] In this implementation, the time-of-use electricity price data may also be JSON or XML data, etc.

[0040] Step S14: parse the time-of-use electricity price data to extract at least one target time period.

[0041] In this implementation, the parsing action may be represented as the controller identifying key fields and corresponding time intervals in the time-of-use electricity price data to extract the target time period.

[0042] The key field may be "valley period", "low valley period", "normal period" or a key field with the same or similar semantics as "valley period, low valley period and normal period", for example, "lowest electricity price period" or "highest electricity price period".

[0043] In this embodiment, the target time period may be a time period with a relatively low or lowest electricity price, such as a valley period, a low valley period, or a normal period.

[0044] In this embodiment, the target time period may include the type of time period and the corresponding specific time interval. The target time period may be a dictionary type of data. For example, the target time period may be a key-value pair structure.

[0045] The target period may also be tuple type data.

[0046] The target period may also be data of a custom object or class.

[0047] In this embodiment, the time-of-use electricity price data is parsed to extract at least one target period, which may be to extract only the period with the lowest electricity price, for example, the valley period.

[0048] In this embodiment, the time-of-use electricity price data is parsed to extract at least one target time period, which may be to extract all time periods with lower and lowest electricity prices. Specifically, when the time-of-use electricity price data is five-time period time-of-use electricity price data, the deep valley period, the low valley period and the normal period may be extracted as the target period. When the time-of-use electricity price data is four-time period or three-time period time-of-use electricity price data, the low valley period and the normal period may be extracted as the target period.

[0049] In this embodiment, the step of parsing the time-of-use electricity price data to extract at least one target period may include: When the time-of-use electricity price data is a data table, the controller can read the rows and columns of the data table and parse the fields "time period category" and "time range". Identify the time range (for example, "00:00-06:00") corresponding to the time period category field (for example, "deep valley", "low valley", "normal period"). Finally, output the target time period, including the category information and the specific time period.

[0050] When the time-of-use electricity price data is an array or a time series, the controller can traverse the electricity value in the array to find the minimum value, the second minimum value and their corresponding indexes. The controller then maps the time interval according to the index and marks the category (such as "deep valley" and "low valley"). Finally, the category information and specific time period of the target time period are output.

[0051] When the time-of-use electricity price data is in JSON or XML format, the controller may parse the key-value pairs in the JSON or XML file and locate the “category field” (type) and the “time range field” (time_interval).

[0052] Step S16: Based on the at least one target time period, generate a control parameter set corresponding to the target time period; wherein the control parameter set includes multiple control parameters, and the control parameters are at least used to control the operating state of the compressor; wherein the control parameters are dynamically adjusted as the time within the target time period changes.

[0053] In this embodiment, a control parameter set corresponding to the target period can be generated based on the target period. It is understandable that if only one target period is extracted in step S14, only one control parameter set is generated. Only the valley period can be used as the target period. Accordingly, if multiple target periods are extracted in step S14, multiple control parameter sets can be generated. In other words, the control parameter set corresponds to the target period.

[0054] In this embodiment, the control parameter set may include one or more types of control parameters. Each type of control parameter may include multiple control parameters. Specifically, one type of control parameter may be used to control the operating state of an electrical component in the air conditioner within a target time period. The electrical component may be a compressor or a defrost heater. For example, in a specific embodiment, only one target time period (e.g., a deep valley time period) may be extracted in step S14, and in step S16, a control parameter set may be generated based on the target time period of the deep valley time period. The control parameter set includes two types of control parameters, one type of control parameter is used to control the operating state of the compressor. The other type of control parameter is used to control the operating state of the defrost heater.

[0055] In this embodiment, the control parameter may be the compressor speed.

[0056] In this embodiment, the control parameter may be the compressor output power.

[0057] In this embodiment, the control parameter may be the operating frequency of the compressor.

[0058] In this implementation, the control parameter may be the compressor output voltage.

[0059] In this embodiment, the control parameter may be the heating temperature of the defrost heater.

[0060] In this embodiment, the control parameter may be the output power of the defrost heater.

[0061] In this embodiment, the control parameter may also be the defrost heater output voltage.

[0062] In this embodiment, the control parameter is dynamically adjusted as the time in the target period changes. It can be expressed as, within the target period, when the time in the target period increases gradually, the control parameter increases gradually. For example, the speed of the compressor increases from 1000RPM to 1500RPM. Alternatively, when the time in the target period increases gradually, the control parameter can be gradually reduced. For example, the power of the compressor decreases from 500W to 300W.

[0063] In this implementation, the target period may be divided into a plurality of time windows, and the value of the control parameter in each time window varies according to a fixed step size.

[0064] In this embodiment, the control parameters within the target period can be dynamically adjusted based on a function fitting method. For example, the controller can fit a function (e.g., a linear function, a polynomial function, or a piecewise function) according to the start and end time of the target period, and use this function as a basis for dynamically adjusting the control parameters. Accordingly, the value of the control parameter can change according to the function within the target period.

[0065] In this embodiment, the control parameters within the target time period can be dynamically adjusted based on event triggering. For example, the controller can dynamically adjust the control parameters by monitoring the triggering events of time or other conditions. When a triggering event occurs (for example, a time point is reached or the device status changes), the value of the control parameter is changed. Specifically, multiple key trigger points (the beginning, middle and end of the time period) can be set within the target time period, and the control parameters can be adjusted at each triggering point. At the start time, the speed is set to 1000RPM, at the middle time, the speed is set to 1200RPM, and at the end time, the speed is set to 1500RPM.

[0066] In this embodiment, the control parameters within the target period can be dynamically adjusted based on the proportional allocation method. For example, the controller can divide the target period into several proportional intervals and dynamically adjust the control parameters within each interval. Specifically, the target period (00:00-06:00) is divided into two intervals: the first 50% and the second 50%. In the first 50% interval, the control parameters are gradually increased, and in the second 50% interval, the control parameters remain unchanged or gradually decrease.

[0067] In this implementation, the above-mentioned multiple dynamic adjustment methods can be combined to dynamically adjust the control parameters within the target time period.

[0068] In one possible and specific implementation, the controller may generate the following control parameters: Target period: deep valley period (00:00-06:00); The speed increases over time, from 1000RPM to 1500RPM; the power increases over time, from 400W to 600W.

[0069] Target period: trough period (06:00-12:00); The speed decreases over time, from 1500RPM to 1000RPM; the power decreases over time, from 600W to 400W.

[0070] Step S18: According to the control parameter set, at least the operating state of the compressor is controlled within the target time period.

[0071] In this embodiment, the controller can control the operating state of the compressor within the target time period according to the control parameter set.

[0072] In this embodiment, the controller can control the operating states of the compressor and the defrost heater simultaneously within the target time period according to the control parameter set.

[0073] In this embodiment, the controller may read the control parameter values ​​of the compressor from the control parameter set, and perform control operations according to the control parameters within the target period.

[0074] Specifically, in a possible and specific implementation, the step of controlling at least the operating state of the compressor within the target period according to the control parameter set may be: First, when the target period starts, the controller reads the compressor control parameters related to the current target period from the control parameter set.

[0075] For example, for the target period 00:00-06:00, the control parameter set may include the following compressor control parameters: Speed: 1100RPM (00:00) Speed: 1200RPM (01:00) Speed: 1300RPM (02:00) Speed: 1400RPM (03:00) Speed: 1500RPM (04:00) Speed: 1600RPM (05:00) Speed: 1700RPM (06:00) Then, the controller directly reads the control parameter value at the current moment at each moment, generates a corresponding control signal and sends it to the compressor execution module (eg, inverter) to implement control.

[0076] In this embodiment, the control signal can be a PWM signal, which can be used to adjust the speed of the compressor, the output voltage of the compressor, the output power of the compressor, the operating frequency of the compressor, and so on.

[0077] It is understandable that the PWM signal can be rectified and filtered by the inverter of the compressor to adjust the output voltage. For example, when the duty cycle is high, the output voltage is high, and the compressor operating power and speed increase. Correspondingly, when the duty cycle is low, the output voltage is low, and the compressor operating power and speed decrease.

[0078] It can be understood that the PWM signal can control the frequency of the AC power output by the inverter. When the frequency is high, the speed is also high, and the compressor runs fast. Correspondingly, when the frequency is low, the speed is also low, and the compressor runs slowly.

[0079] Therefore, the controller can generate a corresponding control signal by reading the control parameters in the control parameter set. In other words, the controller can adjust the duty cycle and frequency in the control signal according to the control parameters in the control parameter set. For example, the control parameter (speed) at a certain point in time in the control parameter set is 1400RPM. The controller will calculate the corresponding operating frequency (for example, 50Hz), and generate a PWM signal with a matching duty cycle and frequency, and send it to the inverter. The inverter adjusts the input voltage and frequency of the compressor according to the PWM signal, and finally achieves the target speed.

[0080] Specifically, in a possible and specific implementation, the controller may read the control parameter values ​​of the compressor from the control parameter set, and perform the steps of controlling the operation according to the control parameters within the target period, which may be: First, when the target period starts, the controller reads the control parameters of the compressor and the defrost heater related to the current target period from the control parameter set.

[0081] For example, for the target time period 00:00-06:00, the control parameter set may include the following control parameters: Compressor control parameters: Speed: 1100RPM (00:00) Speed: 1200RPM (01:00) Speed: 1300RPM (02:00) Speed: 1400RPM (03:00) Speed: 1500RPM (04:00) Speed: 1600RPM (05:00) Speed: 1700RPM (06:00) Control parameters of defrost heater: Heating power: 500W (00:00) Heating power: 550W (02:00) Heating power: 600W (04:00) Heating power: 650W (06:00) Then, the controller can directly read the control parameter value at each moment, generate corresponding control signals and send them to the compressor and defrost heater.

[0082] More specifically, the controller may read the compressor control parameters in the control parameter set according to the current moment.

[0083] For example, the current time is 02:00, and the control parameter read is 1300RPM. The controller calculates the corresponding operating frequency and output power according to the target speed (1300RPM), and then generates a PWM signal that matches the speed and operating frequency. For example, when the speed is 1300RPM, the controller can calculate the corresponding operating frequency to be 50Hz. The controller generates a PWM signal that matches the speed and operating frequency. The controller sends the generated PWM signal to the inverter of the compressor. The inverter adjusts the input voltage and frequency according to the PWM signal, and finally makes the compressor reach the target speed and output power.

[0084] More specifically, the controller may read the defrost heater control parameter in the control parameter set at the current moment.

[0085] For example, the current time is 02:00, and the control parameter read is 550W. The controller generates a PWM signal that matches the target heating power based on the control parameter. The output power is 550W, and the input voltage is set to 220V, then the controller calculates the operating current to be 2.5A. Based on the operating current of 2.5A, the controller can determine the duty cycle to be 80%. Finally, the controller sends the generated PWM signal to the defrost heater drive module. The drive module adjusts the input current and voltage according to the PWM signal, and finally enables the defrost heater to reach the target power and heating temperature.

[0086] The refrigerator control method provided in this embodiment realizes refined control of the operating state of the refrigerator compressor by dynamically generating a set of control parameters that match the target time period, and dynamically adjusting the control parameters according to the time changes within the target time period. Compared with the method of using fixed control parameters or simple start-stop strategies in the prior art, this method can more accurately respond to the load change trend reflected by the time-of-use electricity price data, gradually adjust the operating state of the compressor within the target time period, and optimize the operating efficiency. Through the above-mentioned control logic, this method effectively solves the problem of insufficient fineness of load regulation in the prior art, and significantly improves the smoothing effect of the load curve, thereby better realizing peak shaving and valley filling, reducing user electricity bills, and alleviating peak-period pressure on the power grid.

[0087] In some embodiments, the refrigerator further includes a positioning device; the step of receiving time-of-use electricity price data includes: Step S122: Based on the positioning device, determine the current positioning information of the refrigerator.

[0088] In this implementation, the positioning device may be a GPS positioning module.

[0089] In this embodiment, the positioning device may be a Wi-Fi positioning module. Specifically, the controller may determine the geographical location of the refrigerator using a Wi-Fi location database based on the signal strength and access point information of the surrounding Wi-Fi network.

[0090] In this embodiment, the positioning device may be a Bluetooth positioning module. Specifically, the controller may determine the position by calculating the distance relationship of the Bluetooth signal based on the signal strength of the nearby Bluetooth beacon.

[0091] Step S124: Send a request to the cloud to obtain time-of-use electricity price data based on the positioning information.

[0092] Step S126: Receive time-of-use electricity price data sent by the cloud.

[0093] In this embodiment, after obtaining the location information of the current refrigerator (such as latitude and longitude coordinates, administrative area code, etc.), the controller will assemble a data request packet. The controller can send the request to the server in the cloud through a network interface (for example, Wi-Fi, cellular network, etc.). The target address of the request can be the API endpoint of the cloud service. The request can be in the format of a RESTful API. After sending the request, the controller enters a waiting state and listens for a response from the cloud. The response can be a successful return of time-of-use electricity price data, or it can be a failure message (such as the server is busy or the request is illegal). The controller can receive a response data packet sent by the server through a network interface. The content of the response can be in JSON or XML format, containing relevant information about the time-of-use electricity price.

[0094] In this embodiment, by introducing a positioning device, the latest time-of-use electricity price data can be dynamically obtained according to the geographical location of the refrigerator, thereby improving the flexibility of the refrigerator to adapt to electricity price policies in different regions. Specifically, after the controller uses the positioning device to determine the real-time location of the refrigerator, it can request the time-of-use electricity price table corresponding to the location from the cloud. This information interaction method based on real-time positioning enables the refrigerator to update electricity price data in a timely manner without the need for manual input or update by the user, greatly improving the convenience of use. At the same time, this automated data acquisition method also ensures the universality and accuracy of the refrigerator in different regions or when electricity price policies change, so that the operation control logic of the refrigerator can always optimize the control strategy based on the latest time-of-use electricity price data, further achieving the goal of peak shaving and valley filling and reducing electricity costs.

[0095] like Figure 4 As shown, in this embodiment, the step of parsing the time-of-use electricity price data to extract at least one target period may include: Step S142: Determine whether the time-of-use electricity price data represents five-period time-of-use electricity price data, four-period time-of-use electricity price data, or three-period time-of-use electricity price data.

[0096] In this embodiment, the step of determining whether the time-of-use electricity price data represents five-period time-of-use electricity price data, four-period time-of-use electricity price data, or three-period time-of-use electricity price data may include: First, the controller can identify the target field of the time-sharing electricity price data and count the time period categories contained therein. Specifically, the time-sharing electricity price data can be a file in a structured format (for example, JSON, XML or other). The controller can read the file and identify the corresponding fields therefrom. If the time-sharing electricity price data includes five fields: deep_valley, valley, flat, peak and super_peak, it represents five time periods. If the time-sharing electricity price data contains four fields: valley, flat, peak and super_peak, it represents four time periods. If the time-sharing electricity price data only contains three fields: valley, flat and peak, it represents three time periods.

[0097] The controller can also determine whether the time-of-use electricity price data represents five-period time-of-use electricity price data, four-period time-of-use electricity price data, or three-period time-of-use electricity price data by the semantics of the field name. It is understandable that five-period time can contain deep_valley, valley, flat, peak, and super_peak. Four-period time lacks deep_valley and only contains valley, flat, peak, and super_peak; three-period time only contains valley, flat, and peak.

[0098] Then, the controller can verify the integrity of the time period. Specifically, the controller can verify the time period range in the time-sharing electricity price data to determine whether the data complies with the time period division rules. If the time period covers a complete 24 hours (such as from 00:00 to 24:00) and there is no overlap of time periods, the data is valid. If the time period does not cover a full day, or there is overlap of time periods, it may indicate that the data is incorrect.

[0099] Step S144: When the time-of-use electricity price data is five-time period time-of-use electricity price data, the deep valley period, the low valley period and the normal period are extracted as the target period.

[0100] In this embodiment, the deep valley period may be the period of time when the electricity price is the lowest. During this period, the power demand is extremely low and the power grid has sufficient power supply, so the electricity price is set to the lowest in the day. The controller may identify the deep_valley field or an equivalent field (such as lowest_price) from the time-of-use electricity price data.

[0101] In this embodiment, the valley period may be a period of time when the electricity price is lower but higher than the valley period. The controller may identify the valley field or an equivalent field (such as low_price) from the time-of-use electricity price data.

[0102] In this embodiment, the flat period may be a period of time when the electricity price is at a medium level. The controller may identify a flat field or an equivalent field (such as normal_price) from the time-of-use electricity price data.

[0103] Step S146: When the time-of-use electricity price data is four-time period or three-time period time-of-use electricity price data, the off-peak period and the normal period are extracted as the target period.

[0104] In this embodiment, by parsing the time-of-use electricity price data and determining whether it is five-time, four-time or three-time electricity price data, it is possible to flexibly adapt to a variety of time-of-use electricity price structures in different regions or different electricity price policies. By dynamically extracting target time periods such as deep valleys, low valleys and flat periods, it is ensured that the control logic of the refrigerator can operate efficiently under various electricity price structures without the need for users to manually adjust the electricity price period configuration. This mechanism greatly improves the universality and automation of the control strategy, enabling the refrigerator to adapt to changes in different regions and power grid policies, thereby optimizing the operation strategy and further achieving the goal of peak shaving and valley filling and reducing electricity costs.

[0105] In some embodiments, when the time-of-use electricity price data is time-of-use electricity price data representing five time periods, the step of generating a control parameter set corresponding to the target time period based on the at least one target time period includes: A first control parameter set is generated for a target period representing a valley period; wherein the first control parameter set is a parameter set that enables the compressor to operate in a first operating state at least.

[0106] In this embodiment, the first control parameter set is a set of control parameters generated by the controller when the target time period is a valley period, and is used to guide the compressor to operate in a high-power, high-load state.

[0107] For example, the first control parameter set may enable the compressor to operate in a high-power, high-load operating state to store energy for the energy storage device.

[0108] In this implementation, the first control parameter set may include: The compressor speed, for example, is set to 1400RPM-1700RPM (higher than the speed at other times).

[0109] The operating frequency, for example, is set to 50 Hz-60 Hz, ensuring that the compressor operates in a high power mode.

[0110] Output power, for example, the output power is set to 500W-700W to achieve high efficiency cold storage.

[0111] In this embodiment, the first control parameter set can be refined to different time points within the valley period to dynamically adjust the control parameters.

[0112] For example, the target period is 00:00-06:00 (deep valley period), which is divided into multiple time windows, and specific parameters are adjusted in each window: 00:00-02:00: Speed ​​1400RPM, power 500W; 02:00-04:00: speed 1600RPM, power 600W; 04:00-06:00: Speed ​​1700RPM, power 700W.

[0113] In this embodiment, the first operating state refers to a high-power, high-load mode in which the compressor operates during off-peak hours, the purpose of which is to maximize the use of low electricity prices for high-efficiency refrigeration.

[0114] A second control parameter set is generated for a target period representing a low period or a normal period; wherein the second control parameter set is a parameter set that can enable the compressor to operate in a second operating state at most; wherein, when the compressor operates in the first operating state, its power consumption is greater than the power consumption when operating in the second operating state.

[0115] In this embodiment, the second control parameter set is a set of control parameters generated by the controller when the target time period is a low-peak period or a normal period, which is used to guide the compressor to operate in a low-power, low-load state to reduce power consumption while maintaining the normal refrigeration requirements of the refrigerator.

[0116] In this implementation, the second control parameter set may include: The compressor speed, for example, is set to 800RPM-1200RPM (significantly lower than the speed in the first operating state) The operating frequency, for example, is set to 30 Hz-45 Hz to ensure that the compressor operates in a low power mode.

[0117] Output power, for example, the output power is set to 200W-400W.

[0118] In this embodiment, the second control parameter set can be refined to different time points during low or normal periods to further optimize the operating state.

[0119] For example, the target period is 06:00-12:00 (low period), or 12:00-18:00 (normal period), which is divided into multiple time windows: 06:00-08:00: speed 800RPM, power 200W; 08:00-10:00: speed 1000RPM, power 300W; 10:00-12:00: Speed ​​1200RPM, power 400W.

[0120] In this embodiment, the second operating state refers to a low-power, low-load mode in which the compressor operates during off-peak or normal periods, with the goal of maintaining the basic refrigeration needs of the refrigerator while minimizing power consumption.

[0121] In this embodiment, by generating corresponding control parameter sets for different target time periods (such as valley period, off-peak period and normal period), it is possible to achieve fine adjustment of the compressor operation state. Specifically, by generating a first control parameter set during the valley period, the compressor operates at a higher power, making full use of the time period with the lowest electricity price for cold storage, thereby maximizing electricity cost savings. At the same time, a second control parameter set is generated during the off-peak period or normal period, so that the compressor operates at a lower power to meet the needs of the period with higher electricity prices, further optimizing the operating energy consumption. This method effectively balances the load and the user's electricity cost, can not only reduce the peak and fill the valley, support the stable operation of the power grid, but also significantly improve the operating efficiency and intelligence level of the refrigerator by dynamically adjusting the operating strategies of different target time periods.

[0122] In some embodiments, when the time-of-use electricity price data is time-of-use electricity price data representing four time periods or three time periods, the step of generating a control parameter set corresponding to the target time period based on the at least one target time period includes: For a target period representing a valley period, generating the first control parameter set; The second control parameter set is generated for a target period representing a normal period.

[0123] In this embodiment, by generating a control parameter set corresponding to the target period for the four-period or three-period time-of-use electricity price data, it is possible to effectively adapt to regional or policy changes in different electricity price structures. Specifically, by generating a first control parameter set during the off-peak period, the compressor is operated in a first operating state of high load and high power, making full use of the time period of low electricity prices for cold storage and maximizing electricity cost savings; at the same time, by generating a second control parameter set during the normal period, the compressor is operated in a second operating state of low load and low power, only meeting basic cooling needs, and further optimizing energy consumption.

[0124] In some embodiments, the refrigerator further comprises a cold storage device; The step of controlling at least the operating state of the compressor within the target period according to the control parameter set comprises: Step S182: When the time-of-use electricity price data represents five time periods, and when the current time is a target time period representing a valley period, the compressor is controlled to operate based on a first control parameter set to perform cold storage on the cold storage device; when the current time is a target time period representing a valley period or a normal period, the compressor is controlled to operate based on a second control parameter set to perform supplementary cooling on the cold storage device.

[0125] In this embodiment, the cold storage device can be arranged in the refrigerator compartment, or in the freezer compartment of the refrigerator, or in both the refrigerator compartment and the freezer compartment, or between the refrigerator compartment and the freezer compartment. For example, the cold storage device is placed in a partition or passage between the refrigerator compartment and the freezer compartment, and the cold energy can be flexibly distributed to the refrigerator compartment or the freezer compartment.

[0126] In this embodiment, the cold storage device may include a shell, that is, an external structure that wraps the cold storage device to provide physical protection. The interior of the shell may be filled with a phase change material. The phase change material can store and release a large amount of cold through phase change. The phase change material can be a water-based material, a salt solution, or a low-temperature organic substance.

[0127] The inner and outer surfaces of the shell may be further provided with heat exchange components. The heat exchange components provided inside can store the cold energy generated by the compressor refrigeration in the cold storage medium through heat exchange. The heat exchange components provided on the outer surface can improve the heat exchange efficiency between the cold storage device and the surrounding air.

[0128] It is understandable that during the valley period, the compressor operates at high power based on the first control parameter set, and transfers the cold energy generated by refrigeration to the cold storage device. The phase change material in the cold storage device absorbs and stores the cold energy. During the valley or normal period, the compressor operates at low power based on the second control parameter set to perform supplementary cooling. During the high electricity price period, the cold storage device is used to release the cold energy and reduce the frequency of compressor operation.

[0129] In this embodiment, the controller controls the compressor to operate based on the first control parameter set to perform cold storage on the cold storage device, which may include: First, when the current time is determined to be a valley period, the controller loads controller parameters from the first control parameter set: In a specific and possible implementation, the first control parameter set may include the following control parameters: Compressor speed: for example, 1400RPM-1700RPM; Operating frequency: for example, 50Hz-60Hz; Output power: for example, 500W-700W; Voltage / current: For example, voltage 220V-240V, current 3.5A-4.0A.

[0130] The controller then confirms the current status of the cold storage device.

[0131] Specifically, the controller can detect the current temperature or cooling capacity of the cold storage device through the temperature control sensor. If the current temperature of the cold storage device is higher than the target temperature (for example, -5°C), the cold storage mode is entered. If the current temperature of the cold storage device is close to the minimum temperature threshold (for example, -18°C), the cold storage operation is skipped or the operating power is reduced.

[0132] Finally, when the controller confirms to enter the cold storage mode, specifically, according to the first control parameter set, the controller can generate a corresponding control signal and send the control signal to the compressor (inverter) to make it run at high power.

[0133] It is understandable that after the compressor is started, the refrigerant begins to circulate, and the cold energy is transferred to the cold storage device through the evaporator. The phase change material in the cold storage device absorbs the cold energy and starts to cool down, and at the same time, a phase change occurs (for example, from liquid to solid). When the temperature of the cold storage device reaches the set minimum temperature threshold (for example, -18°C), the controller stops the high-power operation of the compressor.

[0134] In this embodiment, the controller controls the compressor to operate based on the second control parameter set to perform supplementary cooling for the cold storage device, which may include: First, when the current time is judged to be a valley or a normal period, the controller loads the controller parameters from the second control parameter set: In a specific and possible implementation, the first control parameter set may include the following control parameters: Compressor speed: for example, 800RPM-1200RPM; Operating frequency: for example, 30Hz-45Hz; Output power: for example, 200W-400W; Voltage / current: For example, voltage 200V-220V, current 1.5A-2.5A.

[0135] The controller then confirms the current status of the cold storage device.

[0136] Specifically, the controller can detect the current temperature or cooling state of the cold storage device through a temperature control sensor.

[0137] If the temperature of the cold storage device exceeds the supplementary cooling start threshold (for example, -10°C), the supplementary cooling operation is started; if the temperature of the cold storage device is still within the ideal range (for example ≤-15°C), the supplementary cooling operation is skipped or postponed.

[0138] Step S184: When the time-of-use electricity price data represents four-time periods or three-time periods, and when the current time is the target time period representing the off-peak period, the compressor is controlled to operate based on the first control parameter set to perform cold storage on the cold storage device; when the current time is the target time period representing the normal period, the compressor is controlled to operate based on the second control parameter set to perform supplementary cooling on the cold storage device.

[0139] In this embodiment, by combining the type of time-of-use electricity price data and the current target period, the operating state of the compressor is accurately controlled to match the needs of deep valley, low valley or normal period, further improving the intelligent operation and energy-saving effect of the refrigerator. Specifically, under the five-period time-of-use electricity price, the compressor performs cold storage in the first operating state with high power during the deep valley period, making full use of the storage of cold capacity during the period with the lowest electricity price; in the low valley period or normal period, the compressor performs supplementary cooling in the second operating state with low power, maintaining the temperature of the refrigerator stable while significantly reducing energy consumption. Under the four-period or three-period time-of-use electricity price, the compressor performs cold storage during the low valley period and performs supplementary cooling in a more energy-saving manner during the normal period, simplifying the control logic while maintaining efficient operation. By utilizing the energy storage capacity of the cold storage device, this embodiment realizes an intelligent response to electricity price fluctuations under different time-of-use electricity price structures, further optimizes the user's electricity cost, and at the same time plays a positive role in peak shaving and valley filling of the power grid, providing effective support for energy conservation, environmental protection and smart electricity use.

[0140] In some embodiments, the step of controlling the compressor to operate based on a first set of control parameters to perform cold storage on the cold storage device includes: Detect the current temperature of the cold storage device.

[0141] In this embodiment, a temperature control sensor may be built into the cold storage device to measure the temperature of the cold storage device in real time. The controller may read the electrical signal of the sensor through an ADC (analog-to-digital converter) interface and convert it into a specific temperature value.

[0142] It is determined whether the current temperature is greater than or equal to a first temperature threshold.

[0143] In this embodiment, the first temperature threshold is a critical temperature preset in the system for triggering the cold storage operation. For example, the first temperature threshold can be set to -5°C.

[0144] When the current temperature is greater than or equal to the first temperature threshold, the compressor is controlled to operate based on a first control parameter set to perform cold storage on the cold storage device.

[0145] The step of controlling the compressor to operate based on a second control parameter set to provide supplementary cooling to the cold storage device comprises: Detecting the current temperature of the cold storage device; Determining whether the current temperature is greater than or equal to a second temperature threshold; When the current temperature is greater than or equal to a second temperature threshold, the compressor is controlled to operate based on a second control parameter set to perform cold storage on the cold storage device; wherein the second temperature threshold is greater than the first temperature threshold.

[0146] In this embodiment, the second temperature threshold is a critical temperature value for triggering the supplementary cooling operation. This threshold is higher than the first temperature threshold, ensuring that the triggering condition for the supplementary cooling is relatively loose.

[0147] In this embodiment, by setting the first temperature threshold and the second temperature threshold, the compressor is controlled to operate with the first control parameter set and the second control parameter set respectively, so as to realize the precise control of the cold storage and cold supplement operations. Specifically, during the cold storage process, when the current temperature of the cold storage device is greater than or equal to the first temperature threshold, the compressor operates in a high-power mode to quickly complete the cold storage task; and during the cold supplement process, when the current temperature is greater than or equal to the second temperature threshold, the compressor operates in a low-power mode to meet the cold supplement demand. By setting the first temperature threshold lower than the second temperature threshold, it is ensured that the cold storage operation is completed first, and the cold supplement operation is more energy-efficient, thereby realizing efficient management of cold capacity. This logic not only improves the flexibility and energy efficiency of the compressor operation, but also reduces unnecessary energy consumption, while ensuring the stability of the cold storage device under different load conditions, effectively optimizing the electricity cost and operating efficiency of the refrigerator, and further supporting the goal of peak shaving and valley filling.

[0148] In some implementations, the step of generating a set of control parameters corresponding to a target period based on the at least one target period includes: Step S162: Obtain load curve data.

[0149] In this embodiment, the load curve data may be the load curve data of the power grid. Specifically, the controller may obtain the overall load curve data from the power grid to understand the change trend of the current power grid load and respond.

[0150] For example, the controller is connected to the cloud platform of the power grid or energy service provider through a network interface (e.g., Wi-Fi, cellular network). The controller then sends a request for load profile data and receives a response data.

[0151] In this embodiment, the load curve data may be the load curve data of the household where the refrigerator is located. Specifically, the controller may obtain the real-time household power load data through the smart meter interface. Accordingly, if the household has an energy management system (HEMS) installed, the controller may obtain the household load curve through the HEMS platform.

[0152] In some embodiments, the refrigerator may have a built-in power detection module to generate its own load curve by measuring its own operating power and periodic power consumption.

[0153] Step S164: Based on the changing trend of the load curve data within the target time period, generate the control parameter set corresponding to the target time period; wherein, when the load curve data shows a downward trend, the control parameters are gradually adjusted over time to increase the operating status output of the compressor, and when the load curve data shows an upward trend, the control parameters are gradually adjusted over time to reduce the operating status output of the compressor.

[0154] In this embodiment, the controller can analyze the load curve data to identify the load change trend within the target period. Specifically, the controller extracts the load curve data according to the time range of the target period. For the extracted load curve data, the load change rate at adjacent time points is calculated. If the load value decreases, it means that the load curve is on a downward trend; if the load value increases, it means that the load curve is on an upward trend. The controller can divide the target period into multiple sub-intervals according to the load change rate.

[0155] When the load curve drops (such as the first half of the target period), the controller gradually increases the compressor's operating status output (the controller gradually increases the speed, power and other control parameters over time) to actively increase the load and fill the load trough. When the load curve rises (such as the second half of the target period), the controller gradually reduces the compressor's operating status output (the controller gradually reduces the speed, power and other control parameters over time) to reduce the load and avoid excessive power consumption during peak hours.

[0156] In this embodiment, in order to avoid the compressor from running unstably due to the parameter changes being too drastic, the controller can perform smooth optimization on the generated control parameter set. Specifically, the controller can smooth the parameters such as the rotation speed and power based on the moving average method or the weighted average method.

[0157] In this embodiment, the controller may also generate a set of control parameters based on a function curve, which is preset and can fit the load variation trend.

[0158] In this embodiment, the controller may also use a time window of a fixed size and take the mean or weighted mean of the control parameter within the window as the parameter value at the midpoint of the window.

[0159] In this embodiment, the controller can also limit the parameter change speed by setting a dynamic step size so that the parameter adjustment amplitude at each time point does not exceed a preset threshold.

[0160] In this embodiment, by acquiring the load curve data and analyzing its changing trend within the target period, the control parameter set is dynamically adjusted to achieve refined control of the compressor operating state. When the load curve shows a downward trend, the compressor operating state output is gradually enhanced to actively increase the load; and when the load curve shows an upward trend, the compressor operating state output is gradually weakened to reduce the load. This control logic can dynamically respond to real-time changes in the load curve, further optimize the operating efficiency of the refrigerator, and support peak shaving and valley filling needs. Through dynamic adjustment driven by load curve data, this method significantly improves the intelligence level of refrigerator operation, not only saving users' electricity costs, but also improving the balance and stability of the load.

[0161] In some embodiments, the step of generating the control parameter set corresponding to the target period based on the change trend of the load curve data within the target period includes: Step S1642: Determine the upper limit and lower limit of the control parameter and divide the target time period into multiple time windows.

[0162] In this embodiment, the upper limit value of the control parameter may represent the maximum operating state output of the compressor within the target period. The upper limit value does not exceed the maximum operating capacity of the compressor. For example, if the maximum speed is 2000RPM, the upper limit value is set to 1800RPM to avoid the device running in the extreme state for a long time.

[0163] In this embodiment, the lower limit value of the control parameter represents the minimum operating state output of the compressor within the target period. The lower limit value cannot be lower than the minimum value for normal operation of the equipment. For example, the minimum safe speed of the compressor is 800RPM, and the lower limit value cannot be lower than this value.

[0164] In this embodiment, the target period can be divided into multiple time windows. The size of the time window can be determined according to the total duration of the target period and the frequency of change of the load curve. If the load curve changes drastically, the window duration can be further shortened and the adjustment frequency can be increased; if the load curve changes smoothly, the window duration can be extended and the adjustment frequency can be reduced.

[0165] Step S1644: For each time window, dynamically adjust the control parameters according to the changing trend of the load curve to generate the control parameter set corresponding to the target time period; wherein, when the changing trend is a downward trend, the initial value of the control parameter is set to the lower limit value in the order of the time window from front to back, and the control parameter is gradually increased in each subsequent time window until the upper limit value is reached; when the changing trend is an upward trend, the initial value of the control parameter is set to the upper limit value in the order of the time window from front to back, and the control parameter is gradually reduced in each subsequent time window until the lower limit value is reached.

[0166] In this embodiment, when the load curve shows a downward trend, the control parameter is gradually increased from the lower limit value in the order of the time window from the front to the back until the upper limit value is reached. The initial value can be set as the lower limit value, and the incremental step length of each time window can be calculated. For example, step length = (upper limit value - lower limit value) / number of time windows. Then, the control parameters of each time window are generated based on the incremental step length.

[0167] In a possible and specific implementation, the control parameter is the rotation speed, the upper limit is 1600RPM, and the lower limit is 1000RPM. Then the initial value is set to the lower limit of 1000RPM.

[0168] Specific generated control parameters: Time window 1: speed 1000RPM; Time window 2: speed 1100RPM; Time window 3: speed 1200RPM; Time window 4: speed 1300RPM; Time window 5: speed 1400RPM; Time window 6: speed 1500RPM.

[0169] In this embodiment, by dividing the target time period into multiple time windows and dynamically adjusting the control parameters based on the changing trend of the load curve, the refined control of the compressor operation state is effectively achieved. Specifically, when the load curve shows a downward trend, the controller gradually increases the control parameters from the lower limit value, actively increases the load, and fills the load trough; when the load curve shows an upward trend, the control parameters are gradually reduced from the upper limit value to effectively reduce the load pressure. By dynamically adjusting the range and change speed of the control parameters, this method can not only avoid unstable operation caused by sudden changes in parameters, but also respond flexibly according to demand and load change trends, further improving the intelligent level of refrigerator operation and energy-saving effects. At the same time, this time-sharing window adjustment strategy can ensure smoother and more accurate load regulation, which plays a significant role in supporting peak shaving and valley filling and optimizing electricity costs.

[0170] In some embodiments, the refrigerator further includes a defrost heater; the step of controlling at least the operating state of the compressor within the target period according to the control parameter set includes: According to the control parameter set, the operating states of the compressor and the defrost heater are simultaneously controlled within the target time period.

[0171] In this embodiment, by controlling the operating states of the compressor and the defrost heater simultaneously during the target period according to the control parameter set, the intelligent coordination of the refrigerator operation can be achieved. Compared with the traditional method of controlling the compressor or the defrost heater separately, this method allows the dynamic adjustment of the operating parameters of the two according to the electricity price and grid load during the target period, such as starting the compressor and the defrost heater at the same time during the period of low load or low electricity price to optimize energy consumption; and giving priority to limiting the operation of high-energy-consuming equipment during peak hours to reduce the pressure on the grid. This joint control strategy not only significantly improves the energy efficiency of refrigerator operation and reduces the user's electricity cost, but also further supports the peak-shaving and valley-filling needs of the grid load, ensuring the efficiency, stability and energy saving of refrigerators in different operating scenarios.

[0172] like Figure 5 As shown, in a specific technical solution, a refrigerator based on multi-period time-of-use electricity prices is provided. It includes a refrigerator compartment, a freezer compartment and a cold storage compartment. The refrigerator body includes a load, a GPS positioning module, a control module, a display module, and a time-of-use electricity price control logic update module.

[0173] Phase 1: After the refrigerator is powered on, the GPS positioning module starts positioning and sends the positioning results to the control logic update module. The control logic update module obtains the latest local time-of-use electricity price list from the cloud based on the location, and updates the control logic of the refrigerator and sends it to the control module. The control module controls the entire refrigerator according to the updated control logic.

[0174] The second stage: if the time-of-use electricity price at this time includes five stages, namely peak, high, flat section, trough and deep valley, then the cold storage room will store cold in the deep valley stage, and supplementary cooling can be provided in the trough and flat sections; the cold storage capacity of the cold storage room is measured by temperature. When the temperature exceeds a certain value, supplementary cooling can be provided in the flat section, but no supplementary cooling will be provided in the peak and peak sections; if the time-of-use electricity price at this time includes four stages, namely peak, high, flat section and trough, then cold storage will be carried out in the trough stage, supplementary cooling can be provided in the flat section, no cold storage will be carried out, and supplementary cooling can be provided in the flat section; if it includes three stages, namely peak, flat section and trough, then cold storage will be carried out in the trough stage, and supplementary cooling can be provided in the flat section.

[0175] The third stage: The refrigerator determines the control actions to be performed by the cold storage chamber based on the current cold storage capacity and the time-of-use electricity price period it is in. Specifically, when it is in the deep valley period, the cold storage chamber will refrigerate until the cold storage capacity reaches the set value under this condition (T (temperature of the cold storage chamber) < T1 (the lowest temperature corresponding to the maximum cold storage capacity)); in the low valley and flat periods, it is judged whether (T >= T2 (the set cold replenishment temperature of the cold storage chamber)). If it is satisfied, cold replenishment will be carried out, otherwise, no cold replenishment will be done; in the peak and high peak periods, the cold storage chamber is used to supply cold to the refrigerating chamber. For the other two cases in the second stage, the control logic is similar to the previous one.

[0176] The fourth stage: Under the designed control logic, during the peak and high peak periods of the power grid, such refrigerators will not refrigerate, which can reduce the peak load of the power grid. During the low valley period, the electricity load can be increased through cold storage, realizing complementary operation with the power grid, thereby achieving the purpose of smoothing the electricity consumption curve and realizing peak shaving and valley filling.

[0177] According to an embodiment of the present invention, there is provided a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a computer, the computer executes the method described in any one of the above embodiments.

[0178] According to an embodiment of the present invention, there is also provided a computer program product containing instructions. When the instructions are executed by a computer, the computer executes a method in any one of the above embodiments.

[0179] It should be noted that the terms "first", "second", etc. in the description, claims and the above drawings of the present application are used to distinguish similar objects, and do not necessarily need to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0180] Optionally, the specific examples in this embodiment can refer to the examples described in the above embodiments, and will not be elaborated here.

[0181] The serial numbers of the above embodiments of the present application are only for description and do not represent the superiority or inferiority of the embodiments.

[0182] In the above embodiments of the present application, the descriptions of the respective embodiments have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0183] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A refrigerator, characterized in that: include: Refrigerator and / or freezer; A compressor, which is used to generate cold energy and input it into the refrigerating chamber and / or freezing chamber; A controller, which is used to receive time-of-use electricity price data, parse the time-of-use electricity price data to extract at least one target time period, and then generate a control parameter set corresponding to the target time period based on the at least one target time period; wherein the control parameter set includes multiple control parameters, and the control parameters are at least used to control the operating state of the compressor; wherein the control parameters are dynamically adjusted as time changes within the target time period; according to the control parameter set, at least the operating state of the compressor is controlled within the target time period.

2. The refrigerator according to claim 1, characterized in that: The refrigerator further comprises: A positioning device is used to obtain the positioning information of the refrigerator; wherein the positioning information is used to provide to the controller, and the controller sends a request to the cloud based on the positioning information to obtain time-of-use electricity price data.

3. The refrigerator according to claim 1, characterized in that: The refrigerator further comprises: A cold storage device is used to store the cold energy generated by the compressor.

4. The refrigerator according to claim 1, characterized in that: The refrigerator further comprises: The defrost heater is used to perform a defrost operation within a target period according to a set of control parameters generated by a controller.

5. A method for controlling a refrigerator, the refrigerator comprising a compressor, characterized in that: The method comprises: Receive time-of-use electricity price data; Parsing the time-of-use electricity price data to extract at least one target time period; Based on the at least one target period, a control parameter set corresponding to the target period is generated; wherein the control parameter set includes a plurality of control parameters, and the control parameters are at least used to control the operating state of the compressor; wherein the control parameters are dynamically adjusted as time changes within the target period; According to the control parameter set, at least the operating state of the compressor is controlled within the target time period.

6. The method according to claim 5, wherein the refrigerator further comprises a positioning device; and the step of receiving time-of-use electricity price data comprises: Based on the positioning device, determining the current positioning information of the refrigerator; According to the positioning information, a request for obtaining time-of-use electricity price data is sent to the cloud; Receive time-of-use electricity price data sent from the cloud.

7. The method according to claim 5, wherein the step of parsing the time-of-use electricity price data to extract at least one target period comprises: Determining whether the time-of-use electricity price data represents five-period time-of-use electricity price data, four-period time-of-use electricity price data, or three-period time-of-use electricity price data; When the time-of-use electricity price data is five-time time-of-use electricity price data, the deep valley time period, the low valley time period and the normal time period are extracted as the target time period; When the time-of-use electricity price data is four-time period or three-time period time-of-use electricity price data, the off-peak period and the normal period are extracted as the target period.

8. The method according to claim 7, characterized in that In the case where the time-of-use electricity price data is time-of-use electricity price data representing five time periods, the step of generating a control parameter set corresponding to the target time period based on the at least one target time period includes: For a target period representing a valley period, a first control parameter set is generated; wherein the first control parameter set is a parameter set capable of causing the compressor to operate in a first operating state at least; A second control parameter set is generated for a target period representing a low period or a normal period; wherein the second control parameter set is a parameter set that can enable the compressor to operate in a second operating state at most; wherein, when the compressor operates in the first operating state, its power consumption is greater than the power consumption when operating in the second operating state.

9. The method according to claim 8, characterized in that In the case where the time-of-use electricity price data is time-of-use electricity price data representing four time periods or three time periods, the step of generating a control parameter set corresponding to the target time period based on the at least one target time period includes: For a target period representing a valley period, generating the first control parameter set; The second control parameter set is generated for a target period representing a normal period.

10. The method according to claim 8 or 9, characterized in that: The refrigerator also includes a cold storage device; The step of controlling at least the operating state of the compressor within the target period according to the control parameter set comprises: In the case where the time-of-use electricity price data is the time-of-use electricity price data representing five time periods, and when the current time is the target time period representing the deep valley time period, the compressor is controlled to operate based on the first control parameter set to perform cold storage on the cold storage device, and when the current time is the target time period representing the low valley time period or the normal time period, the compressor is controlled to operate based on the second control parameter set to perform supplementary cooling on the cold storage device; When the time-of-use electricity price data represents four time periods or three time periods, and when the current time is a target time period representing a off-peak period, the compressor is controlled to operate based on a first control parameter set to perform cold storage on the cold storage device; and when the current time is a target time period representing a normal period, the compressor is controlled to operate based on a second control parameter set to perform supplementary cooling on the cold storage device.

11. The method according to claim 10, characterized in that The step of controlling the compressor to operate based on a first control parameter set to perform cold storage on the cold storage device includes: Detecting the current temperature of the cold storage device; Determining whether the current temperature is greater than or equal to a first temperature threshold; When the current temperature is greater than or equal to a first temperature threshold, controlling the compressor to operate based on a first control parameter set to perform cold storage on the cold storage device; The step of controlling the compressor to operate based on a second control parameter set to provide supplementary cooling to the cold storage device comprises: Detecting the current temperature of the cold storage device; Determining whether the current temperature is greater than or equal to a second temperature threshold; When the current temperature is greater than or equal to a second temperature threshold, the compressor is controlled to operate based on a second control parameter set to perform cold storage on the cold storage device; wherein the second temperature threshold is greater than the first temperature threshold.

12. The method according to claim 5, characterized in that The step of generating a control parameter set corresponding to a target period based on the at least one target period comprises: Obtain load curve data; Based on the changing trend of the load curve data within the target time period, the control parameter set corresponding to the target time period is generated; wherein, when the load curve data shows a downward trend, the control parameters are gradually adjusted over time to increase the operating status output of the compressor, and when the load curve data shows an upward trend, the control parameters are gradually adjusted over time to reduce the operating status output of the compressor.

13. The method according to claim 12, characterized in that The step of generating the control parameter set corresponding to the target period based on the change trend of the load curve data within the target period comprises: Determining an upper limit value and a lower limit value of the control parameter and dividing the target period into a plurality of time windows; For each time window, the control parameters are dynamically adjusted according to the changing trend of the load curve to generate the control parameter set corresponding to the target time period; wherein, when the changing trend is a downward trend, the initial value of the control parameter is set to the lower limit value in the order of the time window from front to back, and the control parameter is gradually increased in each subsequent time window until the upper limit value is reached; when the changing trend is an upward trend, the initial value of the control parameter is set to the upper limit value in the order of the time window from front to back, and the control parameter is gradually reduced in each subsequent time window until the lower limit value is reached.

14. The method according to claim 5, characterized in that The refrigerator further includes a defrost heater; and the step of controlling at least the operating state of the compressor within the target period according to the control parameter set includes: According to the control parameter set, the operating states of the compressor and the defrost heater are simultaneously controlled within the target time period.

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