Intelligent energy management and energy saving system and method for fourth-generation residence

Abstract

The invention relates to the technical field of energy management, in particular to a fourth-generation residence intelligent energy management and energy saving system and method, and the system comprises a response feature recognition module, a response gradient calculation module, a task adaptation sorting module, an instruction time sequence regulation and control module and an inertia correction module. In the method, the response fluctuation equipment is dynamically identified and labeled by identifying the response time offset of the equipment in the continuous task, extracting the starting and finishing offset characteristics, finishing response inertia classification in combination with the equipment type and the operation cycle, calculating the frequency change of the offset change and identifying the equipment with an unstable response state; response scheduling priority weights are distributed, control tasks of equipment are ranked, response lag records are extracted in combination with sending of control signals and response time difference, dynamic correction of equipment control precision and ordered adjustment of execution rhythm are achieved, the phenomena of multi-equipment operation conflict and response out-of-control are effectively avoided, and the service life of the equipment is prolonged. And the coordination of equipment regulation and control and the flexibility of system energy efficiency scheduling are improved.

Description

Technical Field

[0001] This invention relates to the field of energy management technology, and in particular to fourth-generation residential intelligent energy management and energy-saving systems and methods. Background Technology

[0002] Energy management technology involves the monitoring, scheduling, optimization, and control of energy in energy-consuming systems such as buildings, industry, and transportation. Core aspects include energy sensing and data collection, load forecasting, energy efficiency assessment, energy system regulation, and the integrated utilization of renewable energy. This technology achieves coordinated management of electricity, heat, and water resources through various methods, aiming to improve energy efficiency and reduce resource waste while ensuring functional requirements are met. Energy management systems consist of sensing devices, control algorithms, and actuators, combining information technology and automation to achieve real-time control, energy-saving strategy formulation, and feedback adjustments for different energy consumption scenarios, which is particularly crucial in the built environment. Traditional residential intelligent energy management and energy-saving systems involve collecting data from residential energy-consuming equipment such as lighting, air conditioning, and hot water supply systems using sensors, combining this data with preset logic to determine energy demand, and adjusting equipment operation through timed control, temperature settings, and load switching to achieve energy savings. Such systems are based on local control logic and manage each device separately in the absence of a unified coordination mechanism. Widely used technical methods include setting the start and stop points of air conditioners through thermostats, using timer switches to control lighting circuits, configuring pressure valves to control the running time of hot water circulation pumps, or using microcontrollers to realize local energy data acquisition and simple logic judgment. The system structure is relatively independent and has weak interactivity and predictability.

[0003] Traditional residential smart energy management systems rely on preset logic to control devices locally, lacking in-depth perception and analysis of the device operation response process. The system triggers device actions with single parameters such as timing, temperature control, or pressure, ignoring the time offset characteristics of the device in the actual response. It is difficult to accurately reflect the dynamic relationship between control signals and device responses. The lack of coordination mechanisms between control tasks leads to startup conflicts and energy consumption superposition when multiple devices are controlled concurrently. At the same time, it cannot identify fluctuations in the device's operating status, resulting in static and lagging control strategies. It lacks the ability to effectively identify and respond to devices with abnormal responses, affecting the accuracy of overall energy efficiency control and system adaptability, and limiting the coordination and dynamic optimization capabilities of energy management in residential scenarios. Summary of the Invention

[0004] To address the shortcomings of existing technologies, such as the lack of in-depth perception and analysis of equipment operation response processes, systems trigger equipment actions based on single parameters like timing, temperature control, or pressure, ignoring the time offset characteristics of the equipment in actual response. This makes it difficult to accurately reflect the dynamic relationship between control signals and equipment responses. Furthermore, the lack of coordination mechanisms between control tasks leads to startup conflicts and energy consumption accumulation issues when multiple devices are controlled concurrently. Additionally, the inability to identify fluctuations in equipment operating status results in static and lagging control strategies, and a lack of effective identification and feedback capabilities for abnormal response devices. These issues affect the accuracy of overall energy efficiency control and system adaptability, limiting the coordination and dynamic optimization capabilities of energy management in residential scenarios. This invention provides a fourth-generation residential intelligent energy management and energy-saving system and method. The technical solution is as follows: On the one hand, it provides a fourth-generation residential smart energy management and energy-saving system, which includes: The response feature recognition module extracts the control signal transmission time, equipment response start time and action completion time from the control tasks of air conditioners, water pumps and water heaters in residential scenarios, calculates the difference between the response start time and the control signal transmission time as the start offset, and generates a residential energy-consuming equipment response inertia classification table. The response gradient calculation module, based on the residential energy equipment response inertia classification table, calls the offset records of the equipment in adjacent control tasks, calculates the difference between two consecutive offset items, labels the equipment with unstable response state for those exceeding the frequency limit, and generates a fluctuating residential equipment identification list. The task adaptation and sorting module uses the unstable device identifier in the fluctuating residential equipment identification list to assign response scheduling priority weight labels to the devices, sorts the air conditioners, water pumps and water heaters in ascending order, and generates a residential energy equipment control task trigger sequence. The instruction timing control module calls the residential energy equipment control task trigger sequence, sends control signals to the target equipment in the residence in sequence, compares the device instruction sending time with the time point required for the synchronous execution of the scheduling task, and generates a residential task timing execution record.

[0005] As a further aspect of the present invention, the residential energy equipment response inertia classification table includes equipment type labels, average start-up offset, average completion offset, extreme start-up offset state, and extreme completion offset state; the fluctuating residential equipment identification list includes response change frequency, response instability state labels, and equipment identification number; the residential energy equipment control task trigger sequence includes response scheduling priority weight labels, air conditioning control sequence, water pump control sequence, and water heater control sequence; and the residential task timing execution record includes equipment control signal transmission time, scheduling task synchronization time point, response lag difference, and task binding identifier.

[0006] As a further aspect of the present invention, the response feature recognition module includes: The control signal detection submodule is based on the control tasks of air conditioners, water pumps and water heaters in residential scenarios. It extracts the control signal transmission time, equipment response start time and action completion time in continuous control tasks. Based on the time sequence record in each control task, it identifies and parses the time nodes of the equipment control signals, records the start response time and action completion time of multiple types of equipment in each round of control tasks, and generates a control response time sequence of residential energy-consuming equipment. The response offset calculation submodule calls the control response time sequence of the residential energy-consuming equipment, calculates the start offset based on the time difference between the control signal sending time and the response start time, and calculates the completion offset based on the time difference between the control signal sending time and the action completion time. It extracts the mean and filters the peak and trough values ​​for the start offset and completion offset of each type of equipment to obtain a set of equipment response offset statistical indicators. The response inertia classification submodule establishes a mapping relationship between the start-up offset and the completion offset based on the set of equipment response offset statistics and the equipment type and operation cycle information. It classifies and labels the response offset characteristics of different equipment, calls the equipment category information and offset periodic trends to classify and summarize the response inertia of similar equipment, and obtains a residential energy equipment response inertia classification table.

[0007] As a further aspect of the present invention, the response gradient calculation module includes: The offset change construction submodule, based on the residential energy equipment response inertia classification table, calls the start offset and completion offset records of the listed equipment in continuous control tasks, calculates the difference between the start offsets in two consecutive control tasks for the same equipment, and simultaneously performs the difference calculation of the completion offsets to generate equipment offset change sequence pairs. The gradient frequency extraction submodule calls the device offset change sequence pair, calculates the number of offset changes within a unit period for the start offset change sequence and the completion offset change sequence of each type of device, extracts the change frequency parameter based on the cumulative number of offset change amplitude and fluctuation period within the time window, and obtains the device response offset change frequency table. The response status labeling submodule sets a response frequency threshold as a response stability benchmark based on the device response offset change frequency table, filters device identification codes whose frequency values ​​exceed the threshold, labels the devices with unstable response status, summarizes the labeled devices and integrates their corresponding attribute information, and generates a fluctuating residential equipment identification list.

[0008] As a further aspect of the present invention, the task adaptation and sorting module includes: The weight tag generation submodule, based on the equipment identification information in the fluctuating residential equipment identification list, calls the response inertia level and response stability level parameters of the unstable equipment, constructs a dual-weight mapping relationship between the response inertia level and the response stability level according to the equipment collaborative start-up control requirements, calculates the equipment scheduling response priority factor through linear combination, and converts the equipment scheduling response priority factor into a tag form and attaches it to the equipment entry to generate a set of residential energy-consuming equipment scheduling priority weight tags. The scheduling sequence construction submodule calls the residential energy equipment scheduling priority weight label set, sorts the air conditioner, water pump and water heater equipment in ascending order according to the weight label values ​​attached to them, adjusts the triggering order in the control task, verifies that the control timing conditions and resource allocation constraints under the collaborative start are met, and generates the residential energy equipment control task triggering sequence.

[0009] As a further aspect of the present invention, the instruction timing control module includes: The control signal sending submodule selects the control task priority information of the target devices in sequence based on the residential energy equipment control task trigger sequence, sends control signals to the air conditioner, water pump and water heater devices one by one in the sorting order, and records the sending time of each control signal to generate a list of residential equipment control command sending times. The timing offset extraction submodule calls the residential equipment control command sending time list, compares the control signal sending time and time point under the same equipment with the synchronous execution requirement time point of each task in the scheduling task, calculates the time difference between the two and records it as the response lag, extracts the lag offset value of each equipment under the control task, and generates a residential equipment control response lag difference table. The task execution record generation submodule calls the residential equipment control response lag difference table, binds the control response lag difference of the equipment with the corresponding control task identifier, and summarizes and archives them according to the scheduling order and equipment category to generate residential task timing execution records.

[0010] As a further aspect of the present invention, the process of sequentially selecting the control task priority information of the target device specifically involves: setting a control task execution priority threshold in each control cycle, wherein the control task execution priority threshold is 3, and prioritizing the selection of control task information within the control task execution priority threshold. The process of sending control signals to the air conditioner, water pump and water heater equipment one by one in the order of sorting is as follows: when there are multiple control task priority information with the same order within the same control cycle, the control signals are sent according to the preset equipment priority of the air conditioner, water pump and water heater. The process of recording the transmission time of each control signal is as follows: the time when the control signal completes the instruction transmission at the transmission interface is recorded with millisecond precision, and written into the residential equipment control instruction transmission time list in the form of a timestamp.

[0011] As a further aspect of the present invention, the system also includes an inertial correction module: The inertia correction module calls the residential task timing execution record, extracts the distribution center and boundary range based on the time distribution range of the response lag record of each type of device in the task, calls the device response lag value and the time distribution range to make difference judgment, if the difference between the real-time lag offset and the distribution center exceeds the threshold, then updates the response inertia level mark of the corresponding device and generates the residential equipment inertia level adjustment result. The results of the residential equipment inertia level adjustment include equipment hysteresis offset value, response inertia level update marker, time distribution center value, and time distribution boundary range.

[0012] As a further aspect of the present invention, the inertial correction module includes: The lag range extraction submodule is based on the response lag difference of each type of equipment recorded in the residential task time sequence execution record. It collects the lag offset value under the control task according to the equipment type, calculates the time distribution center position and boundary value range of the lag value for air conditioner, water pump and water heater respectively, and generates a set of equipment response lag distribution parameters. The grade label update submodule calls the set of device response lag distribution parameters, judges the difference between the device's response lag value and the corresponding device's time distribution center, sets a response inertia correction threshold as the judgment benchmark, and if the difference between the device's lag value and the distribution center exceeds the response inertia correction threshold, then the device's response inertia grade label is numerically corrected, and the record table entries are updated synchronously according to the device type to generate the residential equipment inertia grade adjustment result.

[0013] On the other hand, the fourth-generation residential smart energy management and energy-saving method, which is based on the aforementioned fourth-generation residential smart energy management and energy-saving system, includes the following steps: S1: Based on the control tasks of air conditioners, water pumps and water heaters in residential scenarios, extract the control signal transmission time, equipment response start time and action completion time in the control tasks. Extract the arithmetic mean and offset value of the start offset value and completion offset value for the three types of equipment: air conditioners, water pumps and water heaters. Perform interval mapping classification on the mean and extreme values ​​of the offset values ​​according to the equipment category and operating cycle to generate a residential energy-consuming equipment response inertia classification table. S2: Call the residential energy equipment response inertia classification table, obtain the start offset value and completion offset value of the equipment in two adjacent tasks, construct an offset change sequence based on the difference between adjacent offset values, calculate the frequency of the offset difference in the sequence, determine whether the frequency exceeds the fluctuation frequency benchmark value corresponding to the equipment cycle, and generate a fluctuation residential equipment identification list. S3: Call the fluctuating residential equipment identification list, map the response stability level and response inertia level to intervals respectively, combine the scoring weighting coefficient of the task synchronous start requirement in the equipment collaborative start constraint, calculate the scheduling weight value of air conditioner, water pump and water heater equipment, arrange them in ascending order of scheduling weight value, and generate residential energy equipment control task trigger sequence; S4: Call the residential energy equipment control task trigger sequence, send control commands to the equipment one by one in ascending order, collect the command sending time of each equipment and compare the difference with the corresponding scheduling requirement time point, calculate the equipment response lag time value and bind the corresponding task number and equipment number to generate a residential task timing execution record; S5: Call the residential task time sequence execution record, calculate the lag distribution center value and boundary range based on the mode and range in the time sequence of similar equipment task lag records, calculate the difference between the lag value and the distribution center value of each equipment, and generate the residential equipment inertia level adjustment result.

[0014] The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: By identifying the response time offset of equipment in continuous tasks, its start-up and completion offset features are extracted. Combined with equipment type and operating cycle, response inertia classification is completed, the frequency change of offset changes is calculated, and equipment with unstable response state is identified. This enables dynamic identification and labeling of equipment with fluctuating response. By assigning response scheduling priority weights and sorting control tasks for equipment, and extracting response lag records based on the time difference between control signal transmission and response, the response inertia level is updated according to the distribution changes of lag time. This enables dynamic correction of equipment control accuracy and orderly adjustment of execution rhythm, effectively avoiding multi-device operation conflicts and response loss of control, and improving the coordination of equipment regulation and the flexibility of system energy efficiency scheduling. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the fourth-generation residential intelligent energy management and energy-saving system provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the system framework of the present invention; Figure 3 This is a flowchart of the response feature recognition module in this invention; Figure 4 This is a flowchart of the response gradient calculation module in this invention; Figure 5 This is a flowchart of the task adaptation and sorting module in this invention; Figure 6 This is a flowchart of the instruction timing control module in this invention; Figure 7 This is a flowchart of the inertia correction module in this invention. Detailed Implementation

[0017] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0018] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0019] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0020] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0021] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0022] This invention provides a fourth-generation residential intelligent energy management and energy-saving system, such as... Figure 1-2 The diagram shown illustrates a fourth-generation residential smart energy management and energy-saving system, which includes: The response feature recognition module is based on the control tasks of air conditioners, water pumps and water heaters in residential scenarios. It extracts the control signal transmission time, equipment response start time and action completion time from the control tasks. It calculates the difference between the response start time and the control signal transmission time as the start offset, and the difference between the task completion time and the control signal transmission time as the completion offset. It extracts the mean and judges the extreme values ​​of the start offset and completion offset for each type of equipment. It labels and classifies the deviation features in combination with the equipment type and operating cycle, and generates a residential energy-consuming equipment response inertia classification table. The response gradient calculation module is based on the residential energy equipment response inertia classification table. It calls the offset records of the equipment in adjacent control tasks, calculates the difference between two consecutive offset terms, constructs an offset change sequence and extracts the sequence change frequency. Equipment with frequency exceeding the limit is labeled with an unstable response state label, and a fluctuating residential equipment identification list is generated. The task adaptation and sorting module uses the unstable equipment identifiers in the fluctuating residential equipment identification list, combined with the control requirements for equipment coordinated start-up, to perform weighted mapping and integration of response inertia level and response stability level, assign response scheduling priority weight labels to equipment, sort air conditioners, water pumps and water heaters in ascending order, and generate residential energy equipment control task trigger sequence. The instruction timing control module calls the sorting results in the residential energy equipment control task trigger sequence, sends control signals to the target equipment in the residence in turn, compares the equipment instruction sending time with the synchronous execution requirement time of the scheduling task, extracts the time offset difference to form a response lag record, and binds the corresponding equipment with the control task identifier to generate a residential task timing execution record. The inertia correction module calls the residential task timing execution record, extracts the distribution center and boundary range based on the time distribution range of the response lag record of each type of device in the task, calls the device response lag value and the time distribution range to judge the difference, and if the difference between the real-time lag offset and the distribution center exceeds the threshold, the response inertia level mark of the corresponding device is updated, and the residential equipment inertia level adjustment result is generated. The residential energy equipment response inertia classification table includes equipment type labels, average start-up offset, average completion offset, extreme start-up offset state, and extreme completion offset state. The fluctuating residential equipment identification list includes response change frequency, unstable response state labels, and equipment identification number. The residential energy equipment control task trigger sequence includes response scheduling priority weight labels, air conditioning control sequence, water pump control sequence, and water heater control sequence. The residential task timing execution record includes equipment control signal transmission time, scheduling task synchronization time point, response lag difference, and task binding identifier. The residential equipment inertia level adjustment result includes equipment lag offset value, response inertia level update mark, time distribution center value, and time distribution boundary range.

[0023] Specifically, such as Figure 2 , 3 As shown, the response feature recognition module includes: The control signal detection submodule is based on the control tasks of air conditioners, water pumps and water heaters in residential scenarios. It extracts the control signal transmission time, equipment response start time and action completion time in continuous control tasks. Based on the time sequence record in each control task, it identifies and parses the time nodes of the equipment control signals, records the start response time and action completion time of multiple types of equipment in each round of control tasks, and generates a control response time sequence of residential energy-consuming equipment. This requires access to the data acquisition interface of home smart control devices to extract three key time points from continuous control tasks: the control signal issuance time, the device response start time, and the action completion time. This process is achieved by deploying smart meters, time-series recording modules, and device status feedback modules at the data acquisition end. For air conditioners, the response start time and action completion time can be identified by monitoring the power-on status and compressor start feedback. For water pumps, the start time of pumping is determined by a flow sensor. For water heaters, the start and completion times of heating are determined by a thermistor or water temperature rise rate. Device status information and control signal recordings must be synchronized, using a "controller timestamp" as the basis for recording event occurrence times. During extraction, the data needs to be categorized and sorted according to the control command number of each task round. If a control command number has multiple response start records in the device startup data, the first record is taken as the response start time, and abnormal signals (such as response delay greater than the threshold of 10 seconds) are excluded and marked as abnormal tasks. By statistically analyzing the response start time and action completion time of a device in five consecutive rounds of tasks, a device response time sequence is established. Taking a water heater as an example, if the control signal is issued at 18:00:00, the response start time is at 18:00:03, and the action completion time is at 18:05:00, then the sequence is recorded as a 3-second start delay and a 300-second completion delay, respectively. This is extracted separately for each type of device. The response behaviors of air conditioners, water pumps, and water heaters need to be classified and processed. If the air conditioner involves mode switching, the delay behavior of the heating and cooling modes needs to be recorded separately to generate a residential energy equipment control response time sequence.

[0024] The response offset calculation submodule calls the control response time sequence of residential energy-consuming equipment. It calculates the start offset based on the time difference between the control signal sending time and the response start time for each round, and calculates the completion offset based on the time difference between the control signal sending time and the action completion time. It extracts the mean and filters the peak and trough values ​​for the start offset and completion offset of each type of equipment to obtain a set of equipment response offset statistical indicators. For each round of control tasks, the time difference between the control signal transmission time and the response start time is used to calculate the start offset, i.e., offset Δt1 = t1(start) - t0(signal), where t1 is the response start time and t0 is the control signal transmission time, calculated in seconds. In the water heater task example, the start offset is 3 seconds, and the completion offset Δt2 = t2(finish) - t0(signal), which is 300 seconds. After calculating the time difference for each type of device in the above manner, an offset sequence is formed. The mean of the offset values ​​is extracted using the following formula: Mean(Δt) = (ΣΔt) i ) / N, where N is the number of effective control rounds, Δt i For the i-th control offset, the pandas library in Python is used to perform mean statistics for each type of device. Peak and trough values ​​are filtered using the local extremum method. The offset sequence is scanned by a sliding window of size k=3. If the current value is greater than the adjacent values, it is determined to be a local peak value; if it is less than the adjacent values, it is a trough value. The filtering threshold can be set to the mean of the offset sequence ± 1.5 × standard deviation σ. If a water heater completes an offset of 320 seconds and exceeds the mean + 1.5σ, it is recorded as a peak value. The offset statistics are stored in the form of a DataFrame, with fields including device number, control round, start offset, completion offset, mean, peak value, and trough value, to obtain the set of device response offset statistics.

[0025] The response inertia classification submodule establishes a mapping relationship between the start-up offset and the completion offset based on the set of equipment response offset statistics and the equipment type and operation cycle information. It classifies and labels the response offset characteristics of different equipment, calls the equipment category information and offset periodic trend to classify and summarize the response inertia of similar equipment, and obtains a residential energy equipment response inertia classification table. To establish a mapping relationship between the device's start offset and completion offset, i.e., to establish Δt1 For the corresponding relationship of Δt2, the two-dimensional coordinate method is used to map each set of device responses as a point P(Δt1, Δt2). If the average start offset of an air-conditioning device is 5 seconds and the completion offset is 240 seconds, it is mapped as P(5, 240). According to the distribution trend of the response offset values and combined with the device types, preliminary grouping is carried out. For devices with obvious operation cycles (such as water heaters running at fixed times of 6:00 and 18:00 every day), Fourier transform analysis is performed on the response periodicity. Whether there is a fixed operation cycle is judged through the periodic function F(f). If there is an obvious main frequency component (the main frequency energy is greater than 40% of the total frequency energy), it is classified as a periodic inertia device. If the spectrum distribution is uniform, it is classified as a non-periodic response inertia device. The response inertia index I = (Δt2 - Δt1) / Δt2 is calculated based on the difference between the high and low response offsets to quantify the response delay degree. When I > 0.85, the device is considered to have high response inertia; 0.6 < I ≤ 0.85 is medium response inertia; I ≤ 0.6 is low response inertia. By traversing the I values of the devices for classification and annotation, a classification table of the response inertia of residential energy-consuming devices is obtained.

[0026] Specifically, as Figure 2 , 4 shown, the response gradient calculation module includes: The offset change construction sub-module, based on the classification table of the response inertia of residential energy-consuming devices, calls the start offset and completion offset records of the listed devices in continuous control tasks, calculates the difference in the start offset between two consecutive control tasks for the same device, and synchronously executes the difference calculation of the completion offset to generate a device offset change sequence pair; Extract the identification codes, device types, and response characteristic records of the listed devices, call the control records of the devices at different times from the control task database, and read the start offset and completion offset in continuous control tasks item by item. For each device, select any two consecutive control task records, such as the 5th and 6th round tasks, and calculate the change values between the start offsets and the change values between the completion offsets item by item. The system reads the task timestamps in sequence through an automated script to ensure that the time interval between the two control tasks is within a comparable range, preventing offset judgment errors caused by non-continuous tasks. Taking a water heater as an example, assume that in two consecutive control tasks on a certain day, the start offset of the first time is 5 seconds and the second time is 8 seconds, then the offset change is 3 seconds; if the completion offset of the first time is 240 seconds and the second time is 238 seconds, then the offset change is -2 seconds. The system records these two sets of differences as an offset change pair at the same time, executes it for each type of device one by one, and sorts the results of each round of difference calculation by time and organizes them with unified numbers to generate a device offset change sequence pair.

[0027] The gradient frequency extraction submodule calls the device offset change sequence pair, calculates the number of offset changes per unit period for the start offset change sequence and the completion offset change sequence of each type of device, extracts the change frequency parameter based on the cumulative number of offset change amplitude and fluctuation period within the time window, and obtains the device response offset change frequency table. By traversing the start-up and completion offset change records of various types of devices, the system counts the frequency of offset changes within a certain time period. During the extraction process, the system divides the data into periodic units such as days and hours, and counts the number of start-up offset changes and completion offset changes in each period as the basis for frequency analysis. In order to exclude small and meaningless change records, the system sets a data filtering threshold to remove data with too small fluctuation amplitude, and only counts records with significant numerical changes, such as offset changes exceeding 2 seconds, which are then included in the count. For each type of device, such as water heaters, water pumps, and air conditioners, the system categorizes the number of offset changes that occur for each device within 24 hours, records the daily offset change frequency, and judges whether there is a phenomenon of concentrated changes in a fixed time period based on the records of the device over several consecutive days. In order to identify whether the device has a periodic offset change trend, the system performs time-series traversal of the offset frequency data, records the time points of each high-frequency change, and compares the intervals between time points to determine whether the device's response offset shows periodic fluctuations, and obtains a device response offset change frequency table.

[0028] The response status labeling submodule sets a response frequency threshold as a response stability benchmark based on the device response offset change frequency table, filters device identification codes whose frequency values ​​exceed the threshold, labels the devices with unstable response status, summarizes the labeled devices and integrates their corresponding attribute information, and generates a fluctuating residential equipment identification list. The system analyzes the offset frequency data for each type of equipment, setting a unified response frequency threshold to mark high-frequency equipment states. During actual execution, the system statistically analyzes the frequency changes of different equipment types based on their categories, calculating the frequency range of equipment under normal fluctuations as a reference baseline for response stability assessment. Equipment exceeding the baseline frequency within the same category is filtered, and its identification code is extracted. The status record field is labeled "unstable response." After filtering, the system organizes the marked unstable equipment and retrieves relevant attribute information from the classification table, such as equipment type, control location, and usage cycle, integrating it into a summary table. The list is arranged in order of equipment number and includes fields such as basic equipment information, offset change frequency, whether the frequency exceeds the threshold, and whether the response is stable. For example, if an air conditioning unit's start-up offset change frequency exceeds the set standard for three consecutive days, the unit will be marked, and its number, type, and abnormal characteristics will be displayed in the summary list for easy on-site inspection or maintenance reference, generating a fluctuating residential equipment identification list.

[0029] Specifically, such as Figure 2 , 5 As shown, the task adaptation and sorting module includes: The weight label generation submodule uses the equipment identification information in the fluctuating residential equipment identification list to call the response inertia level and response stability level parameters of unstable equipment. Based on the equipment collaborative start-up control requirements, it constructs a dual-weight mapping relationship between the response inertia level and the response stability level. It calculates the equipment scheduling response priority factor through a linear combination method and converts the equipment scheduling response priority factor into a label form and attaches it to the equipment entry to generate a set of residential energy-consuming equipment scheduling priority weight labels. The system retrieves the response inertia level and response stability level parameters for each device marked as "unstable response." These two levels represent the delay characteristics during device startup or response completion and the fluctuation range of response performance within different control cycles, respectively. The system reads these two level values ​​item by item according to the device number matching method and processes them in conjunction with the logic requirements of multi-device joint control within the residence. It focuses on devices with obvious coordinated startup relationships, such as air conditioners, water pumps, and water heaters. A two-dimensional mapping table is established, with the response inertia level as the horizontal axis and the response stability level as the vertical axis, mapping the corresponding scheduling influence factors. After mapping, the system applies the two level values ​​at a set ratio. Linear combinations are used to form a single scheduling response priority factor. For example, for a water heater with an inertia level of 3 and a stability level of 2, the combination factor can be set to 3×0.6+2×0.4=2.6. After the system calculates the priority factor for the equipment, it converts the value into a discrete label. For example, priority factors less than 2 are labeled as "low priority", those between 2 and 3 are labeled as "medium priority", and those greater than 3 are labeled as "high priority". The generated labels are then appended back to the entry of each equipment in the original list. The label field includes not only the label level itself, but also the source level of the calculated original priority factor value and the constituent weight values ​​to ensure that the labels are traceable, thus generating a set of priority weight labels for residential energy equipment scheduling.

[0030] The scheduling sequence construction submodule calls the residential energy equipment scheduling priority weight label set, sorts the air conditioner, water pump and water heater equipment in ascending order according to the weight label values ​​attached to the equipment, adjusts the triggering order in the control task, verifies that the control timing conditions and resource allocation constraints under the collaborative start are met, and generates the residential energy equipment control task triggering sequence. Each device is sorted according to its scheduling response priority factor label level. The system organizes the device lists for air conditioners, water pumps, and water heaters separately according to the device classification dimension, placing "high priority" devices at the front of the sorted list, "medium priority" devices in the middle, and "low priority" devices at the end. After completing the scheduling priority sorting, the system then performs synchronous verification by combining the control task number to which the device belongs with the pre-set collaborative start strategy requirements. The collaborative start strategy specifies the triggering order relationship between different devices, such as the water heater must be triggered 5 seconds after the air conditioner starts, or the water pump must start simultaneously with the air conditioner, etc. The system compares the sorting results to confirm whether the scheduling order can meet the time interval and resource call conflict restrictions. In the case of scheduling conflicts, the system will attempt to swap tasks within the same priority level to meet the overall coordination conditions without disrupting the overall priority order. For example, the order of two "medium priority" devices can be swapped to adapt to the control logic of air conditioner priority start. When the control logic verification is successful, the system writes the current sorted list into the control task scheduling queue and generates the residential energy equipment control task trigger sequence.

[0031] Specifically, such as Figure 2 , 6 As shown, the instruction timing control module includes: The control signal sending submodule selects the control task priority information of the target device in sequence based on the residential energy equipment control task trigger sequence, sends control signals to the air conditioner, water pump and water heater equipment one by one in the sorting order, and records the sending time of each control signal to generate a list of residential equipment control command sending times. Each control task is retrieved sequentially. The system selects the highest-ranking device task from the scheduling list for the current round, extracts its corresponding device number and task priority, and determines the order of control signal transmission based on this priority. The system categorizes devices such as air conditioners, water pumps, and water heaters, assigning each category an independent signal transmission channel to ensure that the scheduling order does not overlap during parallel operations. The control center generates control signals sequentially according to the scheduling table. During execution, the system writes each signal transmission operation into the control buffer before execution to await system synchronization flag activation. The communication interface (such as a 485 bus, PLC channel, or smart IoT gateway) sends a start command to the target device. Each sending action is recorded with a precise timestamp in the main control system. The system automatically captures the millisecond-level time point when the signal is sent, including fields such as device ID, task number, sequence position, and sending time. For example, if the air conditioner number AC001 is listed first, the control signal sending time is recorded as 08:00:00; the second number is the water pump number P001, and the recording time is 08:00:03, and so on, generating a list of residential equipment control command sending times.

[0032] The timing offset extraction submodule calls the residential equipment control command sending time list, compares the control signal sending time and time point under the same equipment with the synchronous execution requirement time point of each task in the scheduling task, calculates the time difference between the two and records it as the response lag, extracts the lag offset value of each equipment under the control task, and generates a residential equipment control response lag difference table. Based on the synchronous execution requirement time points defined by the scheduling tasks in the system, the actual control signal transmission time of each device is compared, the time difference between the two is calculated, and the time difference is recorded as the response lag. Each scheduling task has a preset theoretical execution time point when it is formulated. For example, the water heater is required to start at 08:00:10 in the collaborative control strategy, while the actual transmission time recorded in the transmission time list is 08:00:13. Then the response lag of the device in this task is 3 seconds. After extracting the device lag, the system generates a set of lag offset value records for each device, including device ID, task number, theoretical time point, actual transmission time, lag difference, etc. During execution, the device type of each round of tasks needs to be classified to ensure that the timing reference is not confused between different types of devices. Records with negative values ​​(early transmission) or excessive lag (lag exceeding the set upper limit value, such as 10 seconds) are specially marked for the reference of adjusting the scheduling strategy and correcting the error tolerance mechanism, and a residential equipment control response lag difference table is generated.

[0033] The task execution record generation submodule calls the residential equipment control response lag difference table, binds the control response lag difference of the equipment with the corresponding control task identifier, and summarizes and archives them according to the scheduling order and equipment category to generate residential task time sequence execution records. Each lag difference is bound to its corresponding scheduling task number to form a complete record of equipment task execution. The system categorizes tasks based on their task numbers, grouping tasks belonging to the same control round together. Items are then further categorized by equipment type, with separate execution record sub-tables created for categories such as air conditioners, water pumps, and water heaters. These sub-tables are then integrated. The recorded content includes not only the equipment number and task number but also key fields such as lag time, theoretical trigger time, and actual trigger time. This helps the management end to review scheduling and locate problematic equipment. The system allows setting record classification conditions, such as automatically archiving daily tasks in chronological order or periodically archiving them to independent log tables by equipment type, ensuring that all control behaviors are traceable. For example, in a certain day's scheduling tasks, the air conditioner AC002 task number is T105, and the lag difference record is 1.5 seconds. This record will be placed in row T105 of the air conditioner classification table and merged into the overall task execution table for that day, forming a task execution data framework based on a three-dimensional intersection of equipment, time, and control characteristics, generating a residential task time-series execution record.

[0034] Specifically, such as Figure 2 , 7 As shown, the inertial correction module includes: The hysteresis range extraction submodule is based on the response hysteresis difference of each type of equipment recorded in the residential task time sequence execution record. It collects the hysteresis offset value under the control task according to the equipment type, calculates the time distribution center position and boundary value range of the hysteresis value for air conditioner, water pump and water heater respectively, and generates the equipment response hysteresis distribution parameter set. The original records are grouped and categorized by equipment type, and the hysteresis offset values ​​of air conditioners, water pumps, and water heaters are summarized separately. Each group of data undergoes preliminary cleaning, removing records marked as abnormal (exceeding limits or premature triggering). A basic statistical set is constructed from the remaining hysteresis data. The system performs central tendency analysis on the hysteresis values ​​of each equipment type to determine the central location of the time distribution. This central location is used as a reference point for the standard response time. For example, if the hysteresis record distribution for a certain week is 2 seconds, 3 seconds, 5 seconds, 4 seconds, 6 seconds, etc., then the central location is set as the median or mode of this distribution, i.e., 4 seconds. The system extracts... The boundary interval of the equipment hysteresis value distribution is defined by the minimum and maximum values ​​of the statistical hysteresis values, and then extended outward by a set buffer range to form an acceptable range for hysteresis behavior. For example, for air conditioning equipment, if the minimum hysteresis value is 1 second and the maximum is 7 seconds, the boundary interval can be set to 0~8 seconds. This allows for the construction of response hysteresis time distribution models for various types of equipment. For water pump equipment, if the response is greatly affected by voltage fluctuations, the hysteresis boundary is relatively loose. The system dynamically sets the upper and lower limit intervals based on the records. The time distribution parameters include the center value, boundary range, standard fluctuation range, etc., generating a set of equipment response hysteresis distribution parameters.

[0035] The grade label update submodule calls the device response lag distribution parameter set, judges the difference between the device's response lag value and the corresponding device's time distribution center, sets the response inertia correction threshold as the judgment benchmark, and if the difference between the device's lag value and the distribution center exceeds the response inertia correction threshold, the device's response inertia grade label is numerically corrected, and the record table entries are updated synchronously according to the device type to generate the residential equipment inertia grade adjustment result. The system determines the latest response lag value for each device within the system. By calculating the difference between the lag value and the time distribution center of the device type, it judges whether the response falls within the normal range. To ensure sensitivity and accuracy, the system sets a response inertia correction threshold. This threshold is a fixed time difference standard for each type of device, set based on response fluctuations. For example, it's set to 2 seconds for air conditioners, 3 seconds for water heaters, and 4 seconds for water pumps. If a water heater's response lag in this round of tasks is 8 seconds, the difference from the water heater distribution center value of 4 seconds is 4 seconds, which exceeds the set threshold of 3 seconds. Therefore, the system... If the system determines that there is a deviation in the response inertia level, the original level will be upgraded by one level. Conversely, if the lag value of a certain device is less than the center value and the absolute value of the difference is greater than the threshold, the level will be downgraded. Each level adjustment operation requires updating the corresponding record in the residential equipment information table at the same time, and retaining the level value before the update for audit tracking. Taking water pump equipment as an example, if the original inertia level of the device with the number WP002 is level 2, the lag in this round is 10 seconds, the distribution center is 5 seconds, and the correction threshold is 4 seconds, then the upgrade operation is triggered because the difference reaches 5 seconds, the new level is set to level 3, and the residential equipment inertia level adjustment result is generated.

[0036] The fourth-generation residential smart energy management and energy-saving method is implemented based on the aforementioned fourth-generation residential smart energy management and energy-saving system, and includes the following steps: S1: Based on the control tasks of air conditioners, water pumps and water heaters in residential scenarios, extract the control signal transmission time, equipment response start time and action completion time in the control tasks. Extract the arithmetic mean and offset value of the start offset value and completion offset value for the three types of equipment: air conditioners, water pumps and water heaters. Perform interval mapping classification on the mean and extreme values ​​of the offset values ​​according to the equipment category and operating cycle to generate a residential energy-consuming equipment response inertia classification table. S2: Call the residential energy equipment response inertia classification table, obtain the start offset value and completion offset value of the equipment in two adjacent tasks, construct an offset change sequence based on the difference between adjacent offset values, calculate the frequency of the offset difference in the sequence, determine whether the frequency exceeds the fluctuation frequency benchmark value corresponding to the equipment cycle, and generate a fluctuation residential equipment identification list. S3: Call the fluctuating residential equipment identification list, map the response stability level and response inertia level to the interval respectively, combine the scoring weighting coefficient of the task synchronous start requirement in the equipment collaborative start constraint, calculate the scheduling weight value of air conditioner, water pump and water heater equipment, arrange them in ascending order of scheduling weight value, and generate residential energy equipment control task trigger sequence; S4: Call the residential energy equipment control task trigger sequence, send control commands to the equipment one by one in ascending order, collect the command sending time of each equipment and compare the difference with the corresponding scheduling requirement time point, calculate the equipment response lag time value and bind the corresponding task number and equipment number to generate a residential task timing execution record; S5: Call the residential task time sequence execution record, calculate the lag distribution center value and boundary range based on the mode and range in the time series of lag records of similar equipment tasks, calculate the difference between the lag value and the distribution center value of each equipment, and generate the residential equipment inertia level adjustment result.

[0037] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A fourth-generation residential intelligent energy management and energy-saving system, characterized in that: The system includes: The response feature recognition module extracts the control signal transmission time, equipment response start time and action completion time from the control tasks of air conditioners, water pumps and water heaters in residential scenarios, calculates the difference between the response start time and the control signal transmission time as the start offset, and generates a residential energy-consuming equipment response inertia classification table. The response gradient calculation module, based on the residential energy equipment response inertia classification table, calls the offset records of the equipment in adjacent control tasks, calculates the difference between two consecutive offset items, labels the equipment with unstable response state for those exceeding the frequency limit, and generates a fluctuating residential equipment identification list. The task adaptation and sorting module uses the unstable device identifier in the fluctuating residential equipment identification list to assign response scheduling priority weight labels to the devices, sorts the air conditioners, water pumps and water heaters in ascending order, and generates a residential energy equipment control task trigger sequence. The instruction timing control module calls the residential energy equipment control task trigger sequence, sends control signals to the target equipment in the residence in sequence, compares the device instruction sending time with the time point required for the synchronous execution of the scheduling task, and generates a residential task timing execution record.

2. The fourth-generation residential intelligent energy management and energy-saving system according to claim 1, characterized in that: The residential energy equipment response inertia classification table includes equipment type labels, average start-up offset, average completion offset, extreme start-up offset state, and extreme completion offset state. The fluctuating residential equipment identification list includes response change frequency, unstable response state labels, and equipment identification number. The residential energy equipment control task trigger sequence includes response scheduling priority weight labels, air conditioner control sequence, water pump control sequence, and water heater control sequence. The residential task timing execution record includes equipment control signal transmission time, scheduling task synchronization time point, response lag difference, and task binding identifier.

3. The fourth-generation residential intelligent energy management and energy-saving system according to claim 1, characterized in that: The response feature recognition module includes: The control signal detection submodule is based on the control tasks of air conditioners, water pumps and water heaters in residential scenarios. It extracts the control signal transmission time, equipment response start time and action completion time in continuous control tasks. Based on the time sequence record in each control task, it identifies and parses the time nodes of the equipment control signals, records the start response time and action completion time of multiple types of equipment in each round of control tasks, and generates a control response time sequence of residential energy-consuming equipment. The response offset calculation submodule calls the control response time sequence of the residential energy-consuming equipment, calculates the start offset based on the time difference between the control signal sending time and the response start time, and calculates the completion offset based on the time difference between the control signal sending time and the action completion time. It extracts the mean and filters the peak and trough values ​​for the start offset and completion offset of each type of equipment to obtain a set of equipment response offset statistical indicators. The response inertia classification submodule establishes a mapping relationship between the start-up offset and the completion offset based on the set of equipment response offset statistics and the equipment type and operation cycle information. It classifies and labels the response offset characteristics of different equipment, calls the equipment category information and offset periodic trends to classify and summarize the response inertia of similar equipment, and obtains a residential energy equipment response inertia classification table.

4. The fourth-generation residential intelligent energy management and energy-saving system according to claim 3, characterized in that: The response gradient calculation module includes: The offset change construction submodule, based on the residential energy equipment response inertia classification table, calls the start offset and completion offset records of the listed equipment in continuous control tasks, calculates the difference between the start offsets in two consecutive control tasks for the same equipment, and simultaneously performs the difference calculation of the completion offsets to generate equipment offset change sequence pairs. The gradient frequency extraction submodule calls the device offset change sequence pair, calculates the number of offset changes within a unit period for the start offset change sequence and the completion offset change sequence of each type of device, extracts the change frequency parameter based on the cumulative number of offset change amplitude and fluctuation period within the time window, and obtains the device response offset change frequency table. The response status labeling submodule sets a response frequency threshold as a response stability benchmark based on the device response offset change frequency table, filters device identification codes whose frequency values ​​exceed the threshold, labels the devices with unstable response status, summarizes the labeled devices and integrates their corresponding attribute information, and generates a fluctuating residential equipment identification list.

5. The fourth-generation residential intelligent energy management and energy-saving system according to claim 4, characterized in that: The task adaptation and sorting module includes: The weight tag generation submodule, based on the equipment identification information in the fluctuating residential equipment identification list, calls the response inertia level and response stability level parameters of the unstable equipment, constructs a dual-weight mapping relationship between the response inertia level and the response stability level according to the equipment collaborative start-up control requirements, calculates the equipment scheduling response priority factor through linear combination, and converts the equipment scheduling response priority factor into a tag form and attaches it to the equipment entry to generate a set of residential energy-consuming equipment scheduling priority weight tags. The scheduling sequence construction submodule calls the residential energy equipment scheduling priority weight label set, sorts the air conditioner, water pump and water heater equipment in ascending order according to the weight label values ​​attached to them, adjusts the triggering order in the control task, verifies that the control timing conditions and resource allocation constraints under the collaborative start are met, and generates the residential energy equipment control task triggering sequence.

6. The fourth-generation residential intelligent energy management and energy-saving system according to claim 5, characterized in that: The instruction timing control module includes: The control signal sending submodule selects the control task priority information of the target devices in sequence based on the residential energy equipment control task trigger sequence, sends control signals to the air conditioner, water pump and water heater devices one by one in the sorting order, and records the sending time of each control signal to generate a list of residential equipment control command sending times. The timing offset extraction submodule calls the residential equipment control command sending time list, compares the control signal sending time and time point under the same equipment with the synchronous execution requirement time point of each task in the scheduling task, calculates the time difference between the two and records it as the response lag, extracts the lag offset value of each equipment under the control task, and generates a residential equipment control response lag difference table. The task execution record generation submodule calls the residential equipment control response lag difference table, binds the control response lag difference of the equipment with the corresponding control task identifier, and summarizes and archives them according to the scheduling order and equipment category to generate residential task timing execution records.

7. The fourth-generation residential intelligent energy management and energy-saving system according to claim 6, characterized in that: The process of sequentially selecting the control task priority information of the target device is as follows: in each control cycle, a control task execution priority threshold is set, the control task execution priority threshold is 3, and control task information within the priority of the control task execution priority threshold is selected first. The process of sending control signals to the air conditioner, water pump and water heater equipment one by one in the order of sorting is as follows: when there are multiple control task priority information with the same order within the same control cycle, the control signals are sent according to the preset equipment priority of the air conditioner, water pump and water heater. The process of recording the transmission time of each control signal is as follows: the time when the control signal completes the instruction transmission at the transmission interface is recorded with millisecond precision, and written into the residential equipment control instruction transmission time list in the form of a timestamp.

8. The fourth-generation residential intelligent energy management and energy-saving system according to claim 1, characterized in that: The system also includes an inertial correction module: The inertia correction module calls the residential task timing execution record, extracts the distribution center and boundary range based on the time distribution range of the response lag record of each type of device in the task, calls the device response lag value and the time distribution range to make difference judgment, if the difference between the real-time lag offset and the distribution center exceeds the threshold, then updates the response inertia level mark of the corresponding device and generates the residential equipment inertia level adjustment result. The results of the residential equipment inertia level adjustment include equipment hysteresis offset value, response inertia level update marker, time distribution center value, and time distribution boundary range.

9. The fourth-generation residential intelligent energy management and energy-saving system according to claim 8, characterized in that: The inertial correction module includes: The lag range extraction submodule is based on the response lag difference of each type of equipment recorded in the residential task time sequence execution record. It collects the lag offset value under the control task according to the equipment type, calculates the time distribution center position and boundary value range of the lag value for air conditioner, water pump and water heater respectively, and generates a set of equipment response lag distribution parameters. The grade label update submodule calls the set of device response lag distribution parameters, judges the difference between the device's response lag value and the corresponding device's time distribution center, sets a response inertia correction threshold as the judgment benchmark, and if the difference between the device's lag value and the distribution center exceeds the response inertia correction threshold, then the device's response inertia grade label is numerically corrected, and the record table entries are updated synchronously according to the device type to generate the residential equipment inertia grade adjustment result.

10. A fourth-generation residential intelligent energy management and energy-saving method, characterized in that, The fourth-generation residential smart energy management and energy-saving system according to any one of claims 1-9 includes the following steps: S1: Based on the control tasks of air conditioners, water pumps and water heaters in residential scenarios, extract the control signal transmission time, equipment response start time and action completion time in the control tasks. Extract the arithmetic mean and offset value of the start offset value and completion offset value for the three types of equipment: air conditioners, water pumps and water heaters. Perform interval mapping classification on the mean and extreme values ​​of the offset values ​​according to the equipment category and operating cycle to generate a residential energy-consuming equipment response inertia classification table. S2: Call the residential energy equipment response inertia classification table, obtain the start offset value and completion offset value of the equipment in two adjacent tasks, construct an offset change sequence based on the difference between adjacent offset values, calculate the frequency of the offset difference in the sequence, determine whether the frequency exceeds the fluctuation frequency benchmark value corresponding to the equipment cycle, and generate a fluctuation residential equipment identification list. S3: Call the fluctuating residential equipment identification list, map the response stability level and response inertia level to intervals respectively, combine the scoring weighting coefficient of the task synchronous start requirement in the equipment collaborative start constraint, calculate the scheduling weight value of air conditioner, water pump and water heater equipment, arrange them in ascending order of scheduling weight value, and generate residential energy equipment control task trigger sequence; S4: Call the residential energy equipment control task trigger sequence, send control commands to the equipment one by one in ascending order, collect the command sending time of each equipment and compare the difference with the corresponding scheduling requirement time point, calculate the equipment response lag time value and bind the corresponding task number and equipment number to generate a residential task timing execution record; S5: Call the residential task time sequence execution record, calculate the lag distribution center value and boundary range based on the mode and range in the time sequence of similar equipment task lag records, calculate the difference between the lag value and the distribution center value of each equipment, and generate the residential equipment inertia level adjustment result.

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