Air conditioning load regulation methods, devices, electronic equipment and storage media

Abstract

This invention discloses an air conditioning load regulation method, apparatus, electronic device, and storage medium, relating to the power grid field. The method includes: determining the air conditioning load power based on collected air conditioning operating data; predicting the room temperature based on the air conditioning load power to obtain a predicted temperature; determining an air conditioning load regulation strategy based on the predicted temperature and load power; and transmitting the load regulation strategy to a virtual power plant controller via protocol data transmission rules, wherein the load regulation strategy is used to control the virtual power plant controller to regulate the air conditioning load. This invention solves the technical problem of low accuracy in air conditioning load regulation.

Description

Technical Field

[0001] This invention relates to the field of power grids, and more specifically, to an air conditioning load regulation method, apparatus, electronic device, and storage medium. Background Technology

[0002] As ambient temperature fluctuates, air conditioning load will generate significant power fluctuations, which may lead to grid load imbalance. This not only increases energy waste but also puts the grid under frequent adjustment pressure, affecting power supply stability. Especially during peak electricity consumption periods, it is more likely to cause risks such as grid overload.

[0003] Air conditioning load regulation directly affects the system's load balance and energy efficiency. However, air conditioning load regulation often relies on experience and lacks scientific basis, resulting in low accuracy of air conditioning load regulation.

[0004] There is currently no effective solution to the above problems. Summary of the Invention

[0005] This invention provides an air conditioning load regulation method, apparatus, electronic device, and storage medium to at least solve the technical problem of low accuracy in air conditioning load regulation.

[0006] According to one aspect of the present invention, an air conditioning load regulation method is provided, comprising: determining the load power of the air conditioner based on collected air conditioner operating data; predicting the temperature in the room where the air conditioner is located based on the load power of the air conditioner to obtain a predicted temperature; determining a load regulation strategy for the air conditioner based on the predicted temperature and the load power; and transmitting the load regulation strategy to a virtual power plant controller through protocol data transmission rules, wherein the load regulation strategy is used to control the virtual power plant controller to regulate the load of the air conditioner.

[0007] In one embodiment of this application, determining an air conditioner load adjustment strategy based on predicted temperature and load power includes: determining an adjustable load based on predicted temperature and load power, wherein the adjustable load is the maximum energy consumption that the air conditioner can reduce while ensuring the basic functions of the air conditioner and user comfort; determining the adjustable load of the air conditioner based on the air conditioner's adjustment demand information and the adjustable load, wherein the adjustable load is the energy consumption that the air conditioner should reduce to meet the adjustment demand information; and determining a load adjustment strategy based on the type of air conditioner and the adjustable load.

[0008] In one embodiment of this application, determining the adjustable load of the air conditioner based on the air conditioner's adjustment demand information and adjustable load includes: decomposing the adjustment demand information based on the adjustable load to obtain the adjustable load.

[0009] In one embodiment of this application, determining a load adjustment strategy based on the type of air conditioner and the load to be adjusted includes: determining a load adjustment method based on the type of air conditioner; and determining a load adjustment strategy based on the load adjustment method and the load to be adjusted.

[0010] In one embodiment of this application, a load adjustment method based on the type of air conditioner includes: when the type of air conditioner is a central air conditioner, the load adjustment method includes adjusting the system operating parameters of the air conditioner and changing the system operating mode of the air conditioner; when the type of air conditioner is a multi-split air conditioner, the load adjustment method includes adjusting the indoor unit operating parameters of the air conditioner and changing the indoor unit operating status of the air conditioner.

[0011] In one embodiment of this application, the protocol data transmission rules are constructed based on the high-speed serial computer extended bus standard protocol, cyclic redundancy check mechanism, sliding window flow control strategy, and chip granularity identification technology.

[0012] In one embodiment of this application, the load power of an air conditioner is determined based on the collected operating data of the air conditioner, including: collecting data from the air conditioner to obtain operating data; and cleaning the operating data using interpolation and moving average methods to obtain the load power of the air conditioner.

[0013] According to another aspect of the present invention, an air conditioning load regulation device is also provided, comprising: a first determining module, configured to determine the load power of the air conditioner based on collected air conditioner operating data; a predicting module, configured to predict the room temperature based on the air conditioner load power to obtain a predicted temperature; a second determining module, configured to determine the air conditioner load regulation strategy according to the predicted temperature and load power; and a transmission module, configured to transmit the load regulation strategy to a virtual power plant controller through protocol data transmission rules, wherein the load regulation strategy is used to control the virtual power plant controller to regulate the air conditioner load.

[0014] According to another aspect of the present invention, an electronic device is also provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the above-described air conditioning load adjustment method during runtime.

[0015] According to another aspect of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is executed, it controls the device where the storage medium is located to perform the above-described air conditioning load adjustment method.

[0016] In this embodiment of the invention, the air conditioner's load power is determined based on collected air conditioner operating data; the room temperature is predicted based on the air conditioner's load power to obtain a predicted temperature; a load adjustment strategy for the air conditioner is determined based on the predicted temperature and load power; and the load adjustment strategy is transmitted to the virtual power plant controller through protocol data transmission rules, wherein the load adjustment strategy is used to control the virtual power plant controller to adjust the air conditioner's load. It is noteworthy that predicting the room temperature based on the air conditioner's load power and determining the air conditioner's load adjustment strategy based on the predicted temperature and load power allows the air conditioner to reserve energy consumption to ensure the preset temperature without affecting the user experience. Based on this, the load that the air conditioner can adjust is determined, completing the formulation of the load adjustment strategy. This achieves the goal of adjusting the air conditioner's load based on the load adjustment strategy, thereby improving the technical effect of improving the accuracy of air conditioner load adjustment and solving the technical problem of low accuracy in air conditioner load adjustment. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0018] Figure 1 This is a flowchart of an air conditioning load adjustment method according to an embodiment of the present invention;

[0019] Figure 2 This is a schematic diagram of the operation mechanism of an optional virtual power plant platform according to an embodiment of the present invention;

[0020] Figure 3 This is a schematic diagram of a communication mechanism for an optional protocol data transmission rule according to an embodiment of the present invention;

[0021] Figure 4 This is a schematic diagram of an optional virtual power plant controller adjusting the load of an air conditioner according to an embodiment of the present invention;

[0022] Figure 5 This is a schematic diagram of an optional load adjustment method for an air conditioner according to an embodiment of the present invention;

[0023] Figure 6 This is a schematic diagram of an air conditioning load regulating device according to an embodiment of the present invention. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] Example 1

[0027] According to an embodiment of the present invention, an embodiment of an air conditioning load adjustment method is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0028] Figure 1 This is a flowchart of an air conditioning load adjustment method according to an embodiment of the present invention, such as... Figure 1 As shown, the method includes the following steps:

[0029] Step S102: Determine the load power of the air conditioner based on the collected air conditioner operating data.

[0030] The air conditioner's operating data in the above steps refers to various data generated during the operation of the air conditioner, including but not limited to current, voltage, power, temperature, operating status, operating mode, fan speed, humidity, etc. The operating status can be cooling, heating, standby, or off, and the operating mode can be fully automatic, timed, or energy-saving.

[0031] The load power of the air conditioner in the above steps is the actual electrical power consumed by the air conditioner, which can measure the working intensity and energy consumption of the air conditioner.

[0032] In one optional embodiment, the current and voltage data of the air conditioner are extracted from the air conditioner's operating data, the product of the current and voltage data is calculated to obtain the real-time power, and the real-time power is used as the load data of the air conditioner.

[0033] Step S104: Based on the load power of the air conditioner, predict the temperature in the room where the air conditioner is located to obtain the predicted temperature.

[0034] The predicted temperature in the above steps is the predicted temperature of the room for a future period.

[0035] In one alternative embodiment, the room temperature can be predicted using an Extreme Learning Machine (ELM) model based on the air conditioner's load power. An ELM model is a model built on a Feedforward Neural Network (FNN). When predicting the room temperature, historical temperature data can be obtained, dividing the day into five time periods: 0:00 to 6:00, 6:00 to 11:00, 11:00 to 14:00, 14:00 to 18:30, and 8:30 to 24:00. Then, one historical temperature data point is extracted from each of the five time periods for each day, and temperature variation data is determined based on the extracted historical temperature data. The temperature variation data and the air conditioner's load power are input into the ELM model, which then predicts the room temperature to obtain the predicted temperature.

[0036] Step S106: Determine the load adjustment strategy for the air conditioner based on the predicted temperature and load power.

[0037] The load adjustment strategy in the above steps is a scheme to adjust the operating status of the air conditioner. This may include, but is not limited to, adjusting the set temperature of the air conditioner, changing the operating mode, controlling the start and stop time of the air conditioner, adjusting the fan speed or air outlet direction, etc., in order to reduce the load of the air conditioner and use the saved load quota for other equipment that urgently needs electricity.

[0038] In one optional embodiment, considering user comfort, a preset allowable indoor temperature range is established. This range can be preset based on reference materials or experience, but the method of setting the allowable indoor temperature range is not limited to this. The predicted temperature is compared with the allowable indoor temperature range. If the predicted temperature is within the preset range, it indicates that the air conditioner has an adjustable load, and the load can be adjusted. If the predicted temperature is not within the preset range, the air conditioner operation needs to be adjusted first to ensure that the indoor temperature returns to the set temperature range, and the load adjustment of the air conditioner is temporarily suspended.

[0039] When regulating the load of air conditioners, the maximum load that the air conditioner can regulate, i.e., the maximum adjustable load, is determined under the premise that the indoor temperature can reach the preset temperature range. The maximum adjustable load of all air conditioners capable of load regulation within the power grid area is statistically analyzed, and each air conditioner shares the load regulation demand based on its maximum adjustable load to determine the load regulation strategy.

[0040] Step S108: The load adjustment strategy is transmitted to the virtual power plant controller through the protocol data transmission rules. The load adjustment strategy is used to control the virtual power plant controller to adjust the load of the air conditioner.

[0041] The protocol data transmission rules in the above steps are communication protocols and technologies that can effectively handle large data transmission demands while ensuring data transmission speed, reliability, and security.

[0042] The virtual power plant controller in the above steps is responsible for receiving the load regulation strategy from the virtual power plant platform and converting it into specific control commands for directly controlling the connected air conditioning equipment.

[0043] In one optional embodiment, during the transmission of the load regulation strategy via protocol data transmission rules, the load regulation strategy can be converted into a data packet format and encapsulated. Then, to protect the data from interception or tampering, the encapsulated load regulation strategy can be encrypted. The encryption algorithm can be a homomorphic encryption algorithm, but is not limited to this. The encrypted load regulation strategy is then transmitted based on a sliding window protocol. The virtual power plant controller receives the encrypted load regulation strategy and decrypts it to obtain the load regulation strategy.

[0044] The virtual power plant controller adjusts the operating status of the air conditioner in real time according to load regulation strategies, such as adjusting the set temperature and changing the operating mode, in order to respond to the grid's dispatching needs and achieve precise control of large-scale air conditioning loads.

[0045] The aforementioned air conditioning load regulation method can be applied to a virtual power plant platform. On the virtual power plant platform, small and medium-sized users can register through their terminal devices. Subsequently, the virtual power plant platform manages the small and medium-sized users and their terminal devices. Then, users interact with the demand-side response platform and trading platform on the virtual power plant platform to complete market transactions. After the transaction is completed, the virtual power plant platform executes control instructions through the source-grid-load-storage control platform. Finally, the system completes settlement management, confirms the transaction, and performs internal settlement and data analysis to ensure a closed-loop process.

[0046] Figure 2 This is a schematic diagram illustrating the operating mechanism of an optional virtual power plant platform according to an embodiment of the present invention, such as... Figure 2As shown, in the registration management module, small and medium-sized users register on the virtual power plant platform and register their terminal devices as resources on the same platform. These terminal devices represent the adjustable resources of the small and medium-sized users. By aggregating the adjustable resources of these users, the virtual power plant platform can participate in ancillary service market transactions. When participating in ancillary service market transactions, the virtual power plant platform needs to register with both the demand-side response platform and the trading platform. In the user management module, the virtual power plant platform signs agency contracts with small and medium-sized users and manages these users and their affiliated terminal devices. In the transaction management module, the virtual power plant platform submits transaction applications to the trading center through the demand-side response platform, receives the transaction clearing results released by the trading center, and completes the signing of transaction contracts. In the control and execution management module, the virtual power plant platform constructs virtual generator units to achieve virtual power generation control. During virtual power generation control, the virtual power plant platform manages the terminal devices, interacts with the demand-side response platform for control, and simultaneously, the source-grid-load-storage control platform manages the load control of the terminal devices. In the settlement management module, the virtual power plant platform performs settlement statistical analysis based on transaction contracts and load control determination results. The calculation results are then fed back to the demand-side response platform, which in turn sends market settlement confirmation to the virtual power plant platform. Finally, the virtual power plant platform allocates internal settlements to small and medium-sized users. The aforementioned air conditioning load regulation method can be applied to the control execution management module of the virtual power plant platform.

[0047] In this embodiment of the invention, the air conditioner's load power is determined based on collected air conditioner operating data; the room temperature is predicted based on the air conditioner's load power to obtain a predicted temperature; a load adjustment strategy for the air conditioner is determined based on the predicted temperature and load power; and the load adjustment strategy is transmitted to the virtual power plant controller through protocol data transmission rules, wherein the load adjustment strategy is used to control the virtual power plant controller to adjust the air conditioner's load. It is noteworthy that predicting the room temperature based on the air conditioner's load power and determining the air conditioner's load adjustment strategy based on the predicted temperature and load power allows the air conditioner to reserve energy consumption to ensure the preset temperature without affecting the user experience. Based on this, the load that the air conditioner can adjust is determined, completing the formulation of the load adjustment strategy. This achieves the goal of adjusting the air conditioner's load based on the load adjustment strategy, thereby improving the technical effect of improving the accuracy of air conditioner load adjustment and solving the technical problem of low accuracy in air conditioner load adjustment.

[0048] In one embodiment of this application, determining an air conditioner load adjustment strategy based on predicted temperature and load power includes: determining an adjustable load based on predicted temperature and load power, wherein the adjustable load is the maximum energy consumption that the air conditioner can reduce while ensuring the basic functions of the air conditioner and user comfort; determining the adjustable load of the air conditioner based on the air conditioner's adjustment demand information and the adjustable load, wherein the adjustable load is the energy consumption that the air conditioner should reduce to meet the adjustment demand information; and determining a load adjustment strategy based on the type of air conditioner and the adjustable load.

[0049] The adjustment demand information in the above steps refers to the information on the capacity consumption adjustment requirements proposed by the air conditioners in the power grid, which can correspond to specific energy consumption values.

[0050] In one optional embodiment, a safe range for room temperature is set to ensure that the indoor temperature remains within a comfortable range for the user, even during load adjustment. The predicted temperature is compared to the safe range. If the predicted temperature is outside the safe range, no load adjustment is considered for the current air conditioner. If the predicted temperature is within the safe range, the temperature difference is calculated by subtracting the predicted temperature from the upper limit of the safe range if the air conditioner is in cooling mode; conversely, it is calculated by subtracting the lower limit of the safe range from the predicted temperature if the air conditioner is in heating mode. This temperature difference is then input into a temperature-energy consumption model, which determines the corresponding energy consumption difference, defining this energy consumption difference as an adjustable load.

[0051] The energy consumption value corresponding to the air conditioner's adjustment demand information is allocated to the air conditioners in the power grid that can perform load adjustment, so as to obtain the adjustable load of each air conditioner. It should be noted that when allocating, it is necessary to ensure that the energy consumption value allocated to each air conditioner is less than the adjustable load of the air conditioner, that is, the adjustable load of each air conditioner is less than the adjustable load.

[0052] Then, based on the type of air conditioner and the load to be adjusted, a load adjustment strategy is determined. After determining the load to be adjusted when the air conditioner is turned on, the type of air conditioner needs to be considered. Different types of air conditioners correspond to different load adjustment methods. The load should be adjusted using a load adjustment method that the air conditioner can accept to complete the load adjustment task.

[0053] In one embodiment of this application, determining the adjustable load of the air conditioner based on the air conditioner's adjustment demand information and adjustable load includes: decomposing the adjustment demand information based on the adjustable load to obtain the adjustable load.

[0054] In one alternative embodiment, the proportion of adjustable load that each air conditioner can bear can be determined based on the adjustable load of multiple air conditioners in the power grid. Then, the energy consumption value corresponding to the adjustment demand information is decomposed according to the proportion to obtain the adjustable load of each air conditioner.

[0055] In another alternative embodiment, the adjustable load and adjustment demand information of multiple air conditioners in the power grid can be input into the allocation model. The allocation model decomposes the energy consumption value corresponding to the adjustment demand information and outputs the adjustable load of each air conditioner.

[0056] In one embodiment of this application, determining a load adjustment strategy based on the type of air conditioner and the load to be adjusted includes: determining a load adjustment method based on the type of air conditioner; and determining a load adjustment strategy based on the load adjustment method and the load to be adjusted.

[0057] In one optional embodiment, a load adjustment method that can reduce the load corresponding to this type of air conditioner is determined based on the air conditioner type, such as lowering the set temperature, switching to energy-saving mode, or reducing the fan speed. Then, the load that can be reduced by each load adjustment method is determined, and a load adjustment strategy is formulated in combination with the load to be adjusted, so that the air conditioner can reduce the energy consumption corresponding to the load to be adjusted through specific adjustment methods.

[0058] In one embodiment of this application, a load adjustment method based on the type of air conditioner includes: when the type of air conditioner is a central air conditioner, the load adjustment method includes adjusting the system operating parameters of the air conditioner and changing the system operating mode of the air conditioner; when the type of air conditioner is a multi-split air conditioner, the load adjustment method includes adjusting the indoor unit operating parameters of the air conditioner and changing the indoor unit operating status of the air conditioner.

[0059] The system operating parameters mentioned above are settings that affect the overall performance and energy consumption of the air conditioning system. When applied to a central air conditioning system, these parameters may include, but are not limited to, the set temperature, chilled water temperature, valve opening, fan speed, and compressor frequency.

[0060] The system operation modes mentioned above are preset operating modes for air conditioning systems under specific conditions. They are applicable to central air conditioning systems and may include, but are not limited to, cooling mode, heating mode, energy-saving mode, and ice storage mode.

[0061] The indoor unit operating parameters mentioned in the above steps refer to the independent control parameters of each indoor unit in a multi-split air conditioner, which may include, but are not limited to: set temperature, air outlet speed, airflow direction control, and indoor unit start / stop control.

[0062] The indoor unit operating status mentioned in the above steps refers to the current operating status of the indoor unit in a multi-split air conditioning system.

[0063] In one optional embodiment, when the air conditioner is a central air conditioning system, the load can be adjusted by changing the operating parameters of the air conditioning system, such as adjusting the chilled water temperature and valve opening limits. The operating mode of the air conditioning system can also be changed, such as performing global temperature control or switching to ice storage mode. When the air conditioner is a multi-split air conditioner, the load can be adjusted by changing the operating parameters of the indoor units, such as adjusting the set temperature, airflow speed, and operating mode of the indoor units. This ensures that the operating load of the air conditioning unit is reduced without shutting down. The operating status of the indoor units can also be changed, such as start / stop operations, or allowing the indoor units to be controlled in groups.

[0064] In one embodiment of this application, the protocol data transmission rules are constructed based on the high-speed serial computer extended bus standard protocol, cyclic redundancy check mechanism, sliding window flow control strategy, and chip granularity identification technology.

[0065] The high-speed serial computer expansion bus standard protocol (Peripheral Component Interconnect Express, or PCIe) mentioned in the above steps is a high-speed serial bus standard used to connect internal computer hardware components. PCIe uses a point-to-point connection method, with each connection having its own communication channel, providing high data transfer speeds and flexibility.

[0066] The Cyclic Redundancy Check (CRC) mechanism mentioned above is a verification algorithm used to detect data errors during data transmission and storage.

[0067] The sliding window flow control strategy described above is a mechanism used in network communication to control the data flow rate. It allows the sender to send multiple data packets before receiving an acknowledgment, while the receiver receives and acknowledges the data packets within the limits of the sliding window. The sliding window flow control strategy can effectively utilize network bandwidth, reduce data transmission latency, and prevent network congestion.

[0068] The chip granularity identification technology (ChipletIdentity Document, or Chiplet ID for short) in the above steps can decompose complex chip functions into multiple small chips and assign a unique identifier to each small chip to enable precise data addressing and management in a multi-chip system.

[0069] In one optional embodiment, when designing the protocol data transmission rules, the data transmission protocol is designed using the PCIe packet format, specifically comprising a PCIe header, a data segment, and a CRC checksum segment. The information carried by each component can be represented as follows:

[0070] Pl = {qs, qn, qm};

[0071] Here, Pl represents the information carried in the PCIe header; qs represents the specific data transmission request type; qn represents the data transmission command information; and qm represents the size of the data transmission message body. The data segment is the valid data portion, encapsulated according to the actual data transmission requirements. The CRC check segment is used to verify the validity of the transmitted data packet.

[0072] Considering the fluctuations in transmission demands and volumes under different conditions, a sliding window protocol is used to control traffic for better adaptability. The sizes of the sending and receiving windows are adjusted according to actual needs to ensure corresponding transmission efficiency. The specific settings can be represented as follows:

[0073]

[0074] Where D represents the size of the protocol data transmission sliding window; λ represents the network congestion coefficient; x represents the total data transmission volume, i.e., the data transmission demand; e represents the unit window transmission capacity, i.e., the data transmission throughput that can be performed per unit window size; and Δt represents the maximum allowable transmission delay.

[0075] In flow control strategies, the sliding window size needs to be adjusted based on network congestion and data transmission demands. The window size must balance throughput and latency to ensure data transmission stability and efficiency. When the sending window size reaches its limit, the sender stops sending data and waits for the receiver's confirmation; when the receiving window size reaches its limit, the receiver stops sending reception confirmations and waits for the sender to retransmit data.

[0076] When designing the data transmission adaptation layer, Chiplet ID technology is used to embed a unique identification number in each small module. Accurate identification of a single object under large-scale air conditioning user deployment is achieved by reading the Chiplet ID. Based on this, a unified interface mapping table is established to map the interfaces of different chips, enabling correct addressing and routing. The mapping rules in the interface mapping table need to be defined according to the interface characteristics and data transmission requirements of different chips. These rules are loaded and obtained during system initialization. For transmission environments with frequent or large fluctuations in transmission status, adaptive dynamic updates can be performed to adapt to different interface configurations and data transmission modes.

[0077] Figure 3 This is a schematic diagram of a communication mechanism for an optional protocol data transmission rule according to an embodiment of the present invention, such as... Figure 3Therefore, data transmission between Module 1 and Module 2 uses the protocol data transmission rules. Both Module 1 and Module 2 contain interface modules, which include sending and receiving components. When Module 1 and Module 2 communicate using the protocol data transmission rules, data transmission uses an IPSec adaptation protocol to ensure data confidentiality and integrity. The data width is 64 bits, and the clock width is 16 bits. The sending component encapsulates valid data according to the interface mapping table, including the Chiplet ID, data segment, and checksum information. The Chiplet ID, as a unique identifier, is mainly used to distinguish different Chiplets and is stored in the Chiplet's non-volatile memory. The receiving component can decapsulate the data according to the interface mapping table to extract the valid data.

[0078] In one embodiment of this application, the load power of an air conditioner is determined based on the collected operating data of the air conditioner, including: collecting data from the air conditioner to obtain operating data; and cleaning the operating data using interpolation and moving average methods to obtain the load power of the air conditioner.

[0079] The interpolation method described above is a technique for estimating missing data points, inferring the value of missing points based on existing data points.

[0080] In one optional embodiment, the operating status of the air conditioner can be monitored in real time using smart meters and sensors to acquire operating data. Then, interpolation methods are used to clean the operating data. If current or power data is missing at a certain point in time, the missing value can be estimated using linear interpolation, polynomial interpolation, or spline interpolation methods from preceding and following data points. The estimated missing value is then used to fill in the missing position, ensuring the continuity and integrity of the data.

[0081] The operating data was then cleaned using a moving average method. During this process, a window size was determined, and the average load power of all data points within that window was calculated. As the data was updated, the window moved, and new average values ​​were calculated. Using a moving average to process the operating data reduced random noise, resulting in smoother data. Current and voltage data were then extracted from the cleaned data, and the air conditioner load power was determined based on this data.

[0082] The following description uses a preferred embodiment. Figure 4 This is a schematic diagram of an optional virtual power plant controller adjusting the load of an air conditioner according to an embodiment of the present invention, as shown below. Figure 4As shown, the virtual power plant platform transmits the load regulation strategy to the virtual power plant controller through the protocol data transmission rules. Then, the virtual power plant controller controls the air conditioning through the air conditioning intelligent control interactive terminal. On the one hand, the air conditioning intelligent control interactive terminal controls the air conditioning building automation system through the network cable. On the other hand, the air conditioning intelligent control interactive terminal controls multiple air conditioning units, including air conditioning unit No. 1, air conditioning unit No. 2, air conditioning unit No. 3, etc., through the serial communication protocol.

[0083] Figure 5 This is a schematic diagram of an optional load adjustment method for an air conditioner according to an embodiment of the present invention, such as... Figure 5 As shown:

[0084] Step S502: Data acquisition is performed using smart meters, current and voltage sensors, etc., to obtain real-time air conditioner load data.

[0085] Step S504: Large-scale air conditioning data cleaning based on elastic network regression model and data type conversion.

[0086] Step S506: Based on the prediction of the user's room temperature using a long short-term memory network, calculate the adjustable load capacity that the air conditioning energy management device can control.

[0087] The adjustable load capacity refers to the adjustable load mentioned above.

[0088] Step S508: Use homomorphic encryption algorithm to encrypt and transmit air conditioning load data, and report the controllable capacity of each household's equipment to the air conditioning load control device.

[0089] In step S510, the air conditioning energy load control device receives controllable capacity information, calculates the capacity to be adjusted, and adjusts the air conditioning load based on the capacity to be adjusted.

[0090] Among them, the capacity that needs to be adjusted is the load that should be adjusted mentioned above.

[0091] Example 2

[0092] According to an embodiment of the present invention, an embodiment of an air conditioning load regulating device is provided. This device can perform the air conditioning load regulating method provided in Embodiment 1 above. The specific implementation method and preferred application scenario are the same as those in Embodiment 1 above, and will not be repeated here.

[0093] Figure 6 This is a schematic diagram of an air conditioning load regulating device according to an embodiment of the present invention, such as... Figure 6 As shown, the air conditioning load regulating device includes:

[0094] The first determining module 60 is used to determine the load power of the air conditioner based on the collected operating data of the air conditioner;

[0095] The prediction module 62 is used to predict the temperature in the room where the air conditioner is located based on the load power of the air conditioner, and obtain the predicted temperature.

[0096] The second determining module 64 is used to determine the load adjustment strategy of the air conditioner based on the predicted temperature and load power.

[0097] The transmission module 66 is used to transmit the load regulation strategy to the virtual power plant controller through the protocol data transmission rules. The load regulation strategy is used to control the virtual power plant controller to regulate the load of the air conditioner.

[0098] The second determining module includes: a first determining unit, used to determine the adjustable load based on the predicted temperature and load power, wherein the adjustable load is the maximum energy consumption that the air conditioner can reduce while ensuring the basic functions of the air conditioner and user comfort; a second determining unit, used to determine the adjustable load of the air conditioner based on the air conditioner's adjustment demand information and the adjustable load, wherein the adjustable load is the energy consumption that the air conditioner should reduce to meet the adjustment demand information; and a third determining unit, used to determine the load adjustment strategy based on the type of air conditioner and the adjustable load.

[0099] The second determining unit is also used to decompose the adjustment demand information based on the adjustable load to obtain the load to be adjusted.

[0100] The third determining unit is also used to determine the load adjustment method based on the type of air conditioner; and to determine the load adjustment strategy based on the load adjustment method and the load to be adjusted.

[0101] The third determining unit is also used to determine the load adjustment method, including adjusting the system operating parameters of the air conditioner and changing the system operating mode of the air conditioner, when the type of air conditioner is a central air conditioner; and to determine the load adjustment method, including adjusting the indoor unit operating parameters of the air conditioner and changing the indoor unit operating status of the air conditioner, when the type of air conditioner is a multi-split air conditioner.

[0102] The protocol data transmission rules in the transmission module are constructed based on the high-speed serial computer extended bus standard protocol, cyclic redundancy check mechanism, sliding window flow control strategy and chip granularity identification technology.

[0103] The first determining module includes: a data acquisition unit for acquiring data from the air conditioner to obtain operating data; and a data cleaning unit for cleaning the operating data using interpolation and moving average methods to obtain the load power of the air conditioner.

[0104] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0105] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0106] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0107] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0108] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0109] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0110] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. An air conditioning load adjustment method characterized by, The application is applied to a virtual power plant platform, and comprises the following steps: determining a load power of the air conditioner based on collected operation data of the air conditioner; predicting a temperature in a room where the air conditioner is located based on the load power of the air conditioner to obtain a predicted temperature; determining a load adjustment strategy of the air conditioner according to the predicted temperature and the load power; transmitting the load adjustment strategy to a virtual power plant controller through a protocol data transmission rule, wherein the load adjustment strategy is used to control the virtual power plant controller to perform load adjustment on the air conditioner; the determining of the load adjustment strategy of the air conditioner according to the predicted temperature and the load power comprises the following steps: determining an adjustable load according to the predicted temperature and the load power, wherein the adjustable load is a maximum value of energy consumption that can be reduced by the air conditioner on the basis of guaranteeing basic functions of the air conditioner and user comfort; determining an adjusted load of the air conditioner according to adjustment demand information of the air conditioner and the adjustable load, wherein the adjusted load is energy consumption that should be reduced by the air conditioner to meet the adjustment demand information; determining the load adjustment strategy based on a type of the air conditioner and the adjusted load.

2. The air conditioning load regulation method of claim 1, wherein, the determining of the adjusted load of the air conditioner according to the adjustment demand information of the air conditioner and the adjustable load comprises the following step: decomposing the adjustment demand information based on the adjustable load to obtain the adjusted load.

3. The air conditioning load regulation method of claim 1, wherein, the determining of the load adjustment strategy based on the type of the air conditioner and the adjusted load comprises the following steps: determining a load adjustment method based on the type of the air conditioner; determining the load adjustment strategy according to the load adjustment method and the adjusted load.

4. The air conditioning load regulating method according to claim 3, wherein the determining of the load adjustment method based on the type of the air conditioner comprises the following steps: in a case where the type of the air conditioner is a central air conditioner, the load adjustment method comprises adjusting system operation parameters of the air conditioner and changing a system operation mode of the air conditioner; in a case where the type of the air conditioner is a multi-split air conditioner, the load adjustment method comprises adjusting indoor unit operation parameters of the air conditioner and changing an indoor unit operation state of the air conditioner.

5. The air conditioning load regulation method of claim 1, wherein, the protocol data transmission rule is constructed based on a high-speed serial computer expansion bus standard protocol, a cyclic redundancy check mechanism, a sliding window flow control strategy and a chip granularity identification technology.

6. The air conditioning load regulation method of claim 1, wherein, the determining of the load power of the air conditioner based on the collected operation data of the air conditioner comprises the following steps: performing data collection on the air conditioner to obtain the operation data; performing data cleaning processing on the operation data by using an interpolation method and a moving average method to obtain the load power of the air conditioner.

7. An air conditioning load regulating device characterized by comprising: comprise the following steps: a first determining module is configured to determine a load power of the air conditioner based on collected operation data of the air conditioner; a prediction module is configured to predict a temperature in a room based on the load power of the air conditioner to obtain a predicted temperature; a second determining module is configured to determine a load adjustment strategy of the air conditioner according to the predicted temperature and the load power; a transmission module is configured to transmit the load adjustment strategy to a virtual power plant controller through a protocol data transmission rule, wherein the load adjustment strategy is used to control the virtual power plant controller to perform load adjustment on the air conditioner; The second determining module comprises: A first determining unit configured to determine an adjustable load according to the predicted temperature and the load power, wherein the adjustable load is a maximum value of energy consumption that can be reduced by the air conditioner on the basis of ensuring basic functions of the air conditioner and user comfort; A second determining unit configured to determine an adjustable load of the air conditioner according to the adjustment demand information of the air conditioner and the adjustable load, wherein the adjustable load of the air conditioner is energy consumption that should be reduced by the air conditioner to meet the adjustment demand information; A third determining unit configured to determine the load adjustment strategy based on a type of the air conditioner and the adjustable load.

8. An electronic device, comprising: The program is run by a processor, and the program, when run, performs the air conditioner load adjustment method of any one of claims 1 to 6. The computer readable storage medium comprises a stored executable program, wherein the executable program, when run, controls a device where the storage medium is located to perform the air conditioner load adjustment method of any one of claims 1 to 6. ​ 9. A computer-readable storage medium, characterized in that, ​

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