Energy real-time monitoring method applied to smart home system
By conducting continuous and stable energy supply assessment and time-dividing energy consumption temperature analysis of smart home energy supply, the problems of fluctuations and excessive consumption of smart home energy supply have been solved, stability monitoring and rational management have been achieved, and smart homes have been promoted to sustainable development.
Patent Information
- Application Number
- CN202510986270.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-17
- Publication Date
- 2025-08-26
AI Technical Summary
The existing technology is difficult to conduct a continuous and stable analysis of the energy supply of smart homes, resulting in an increase in the risk of energy supply fluctuations, reducing management efficiency, and difficulty in conducting status monitoring and reasonable management, resulting in excessive energy consumption.
By conducting continuous and stable energy supply assessment and analysis of the energy supply of smart homes, combining time-divided energy consumption and time-divided temperature analysis, information management is carried out, necessary and non-essential homes are divided, targeted management is carried out, and the risk of abnormal energy consumption is reduced.
It improves the operating monitoring stability of smart homes, reduces energy interference, realizes rational management of energy, and promotes the sustainable development of smart homes.
Smart Images
Figure CN120540112A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of energy monitoring technology, and in particular to a real-time energy monitoring method applied to a smart home system. Background Art
[0002] With the rapid development of information technology, people's work, life, communication and information are becoming increasingly closely related. While the information society is changing people's lifestyles and work habits, it is also challenging traditional housing. Social, technological and economic progress has also led to a significant change in people's concepts. People's requirements for homes are no longer just physical space, but more concerned with a safe, convenient and comfortable home environment. However, in existing technologies, it is difficult to analyze the continuous and stable energy supply performance of smart homes, which increases the risk of energy supply fluctuation interference in smart homes, thereby reducing the management efficiency of smart homes. At the same time, it is difficult to monitor the standby and operation status of smart homes, which is not conducive to timely management of smart homes. It is also difficult to divide and manage smart homes, resulting in excessive and useless consumption of smart homes. In view of the above technical defects, a solution is now proposed. Summary of the Invention
[0003] The purpose of the present invention is to provide a real-time energy monitoring method for a smart home system to solve the technical defects mentioned above. The present invention initially conducts a continuous and stable energy supply evaluation and analysis from the perspective of the energy supply of the smart home, so as to intuitively understand the energy supply stability of the smart home, help reduce the interference of the energy supply on the operation of the smart home, and thus improve the continuous stability of the operation monitoring of the smart home. By means of information progression, analysis is performed from two points of the time period energy consumption and time period temperature of the smart home, so as to carry out targeted management of abnormal smart homes, so as to reduce the risk of abnormal energy consumption of smart homes, and at the same time facilitate the rational disconnection management of the energy of the smart home. The smart home is divided and analyzed from the perspective of daily use, and the smart home is managed in a targeted manner according to the division results of the smart home, so as to reduce the excessive and useless consumption of energy by the smart home, so as to promote the development of the smart home towards sustainability.
[0004] The purpose of the present invention can be achieved by the following technical solution: A method for real-time energy monitoring applied to a smart home system comprises the following steps: Step 1: Initially conduct a continuous and stable energy supply evaluation and analysis from the perspective of smart home energy supply, and perform discrimination processing on the obtained voltage fluctuation rate. If a normal signal is obtained, proceed to steps 2 and 3. If a risk signal is obtained, output feedback; Step 2: Based on the time-segment energy consumption monitoring and analysis under normal signals, the obtained total standby energy consumption value and dynamic energy evaluation value are judged and processed. If a maintenance signal is obtained, the process proceeds to step 4. If an early warning signal is obtained, feedback is output; Step 3: Based on the time period temperature matching division and discrimination operation under the normal signal, the obtained standby temperature range and working temperature range are discriminated and processed, and the obtained stable signal or deviation signal is output; Step 4: Based on the smart home energy division management analysis under information progression, the obtained standby performance value is discriminated and processed to obtain essential homes and non-essential homes, and output management is performed on non-essential homes; Step 5: Based on the in-depth division management analysis of essential homes, the obtained energy consumption values per unit time are judged and processed to obtain high-consumption essential homes and low-consumption essential homes, and output management is performed on high-consumption essential homes.
[0005] Preferably, the continuous and stable energy supply evaluation and analysis process is as follows: The monitoring period of the smart home is collected and set as a time threshold, and the energy supply data of the smart home within the time threshold is obtained. The energy supply data includes the voltage fluctuation rate and the voltage effective value; The process of obtaining the effective voltage value is as follows: the power supply voltage of the smart home is collected once every t1 period, where t1 is a natural number greater than zero. Then, a set A of power supply voltages is constructed, the root mean square deviation of set A is obtained, and the root mean square deviation of set A is set as the effective voltage value.
[0006] Preferably, the process of obtaining the voltage fluctuation rate is as follows: obtaining the mean of the effective voltage values within the time threshold, and setting the mean of the effective voltage values as the effective voltage mean VP, and at the same time obtaining the effective voltage values Vi of the time threshold i, i = 1, 2, 3, ..., k, k is a natural number greater than zero, and at the same time obtaining the rated voltage VE of the smart home line within the time threshold, and then obtaining the voltage fluctuation rate by calculation, and performing discrimination processing on the voltage fluctuation rate to obtain a normal signal or a risk signal.
[0007] Preferably, the time-divided energy consumption monitoring and analysis process is as follows: the standby period and the operating period of the smart home within the time threshold are obtained, and the operating period represents the length of time between the start-up time and the stop-operation time of the smart home; the standby current and the standby resistance of the smart home within the standby period are obtained, and the total standby energy consumption of the smart home within the standby period is obtained based on the standby current and the standby resistance, and the total standby energy consumption is judged and processed to obtain a normal signal or an abnormal signal.
[0008] Preferably, actual energy data of the smart home during the operation period is obtained, the actual energy data including the operation power characteristic curve and the operation energy consumption characteristic curve, standard energy data of the smart home during the operation period is retrieved, the actual energy data is compared and analyzed with the standard energy data one by one, the matching degree of corresponding parameters in the actual energy data and the standard energy data is obtained, and the matching degree is set as the dynamic matching value, the number of parameters corresponding to the dynamic matching value being greater than or equal to the preset dynamic matching value threshold is obtained, and the matching degree is set as the dynamic energy evaluation value, and the dynamic energy evaluation value is discriminated and processed to obtain a stable signal or a dynamic signal; The normal signal and the stable signal are discriminated and processed. If the normal signal and the stable signal are generated, a maintenance signal is obtained. If the normal signal and the stable signal are not generated, an early warning signal is generated.
[0009] Preferably, the time period temperature matching division and judgment operation process is as follows: Obtaining an operating temperature characteristic curve of the smart home within a time threshold, obtaining portions of the operating temperature characteristic curve corresponding to a standby period and an operating period of the smart home in the operating temperature characteristic curve, and setting the portions of the operating temperature characteristic curve corresponding to the standby period and the operating period of the smart home as a standby temperature curve and an operating temperature curve, respectively; The maximum and minimum values in the standby temperature curve and the working temperature curve are obtained, and the standby temperature range and the working temperature range are constructed based on the maximum and minimum values in the standby temperature curve and the working temperature curve respectively. At the same time, the standard standby temperature range and the standard working temperature range of the smart home are obtained, and the standby temperature range and the working temperature range are compared and analyzed with the standard standby temperature range and the standard working temperature range to obtain a stable signal or a deviation signal.
[0010] Preferably, the smart home energy division management analysis process is as follows: The average daily standby time of each smart home in the standby period is obtained, and the average daily standby time of each smart home within the historical m time thresholds is obtained, where m is a natural number greater than zero. A set RB of daily standby time averages is constructed, and after removing the maximum and minimum values in the set RB, the average of the set RB is obtained, and the average of the set RB is set as the standby performance value, and the standby performance value is judged: if the standby performance value is less than the preset standby performance value threshold, the corresponding smart home is judged to be a necessary home; if the standby performance value is greater than or equal to the preset standby performance value threshold, the corresponding smart home is judged to be a non-essential home.
[0011] Preferably, the in-depth division management analysis process is as follows: the energy consumption value of each necessary home in the standby period is obtained, and then the unit time energy consumption value of each necessary home in the standby period is obtained, and the unit time energy consumption value is judged and processed. If the unit time energy consumption value is greater than the preset unit time energy consumption value threshold, the corresponding necessary home is judged to be a high-consumption necessary home; if the unit time energy consumption value is less than or equal to the preset unit time energy consumption value threshold, the corresponding smart home is judged to be a low-consumption necessary home.
[0012] The beneficial effects of the present invention are as follows: (1) The present invention initially conducts a continuous and stable energy supply evaluation and analysis from the perspective of smart home energy supply, so as to intuitively understand the energy supply stability of smart home, help reduce the interference of energy supply on the operation of smart home, and thus improve the continuous stability of smart home operation monitoring. By analyzing the smart home's energy consumption and temperature in different time periods in a progressive manner, the present invention can carry out targeted management of abnormal smart home, reduce the risk of abnormal energy consumption in smart home, and facilitate the rational disconnection management of smart home energy. (2) Carry out segmentation analysis from the perspective of daily use of smart homes, and carry out targeted management of smart homes based on the segmentation results, so as to reduce the excessive and useless consumption of energy by smart homes and promote the development of smart homes in a sustainable direction. BRIEF DESCRIPTION OF THE DRAWINGS
[0013] The present invention will be further described below with reference to the accompanying drawings; Figure 1 It is a reference analysis diagram of the method of the present invention; Figure 2 This is a local analysis diagram of Example 2 of the present invention. DETAILED DESCRIPTION
[0014] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.
[0015] References to "embodiments" herein mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments; Example 1: See also Figures 1 to 2 As shown, the present invention is a real-time energy monitoring method applied to a smart home system, comprising the following steps: Step 1: Initially conduct a continuous and stable energy supply evaluation and analysis from the perspective of smart home energy supply, and perform discrimination processing on the obtained voltage fluctuation rate. If a normal signal is obtained, proceed to steps 2 and 3. If a risk signal is obtained, output feedback; Step 2: Based on the time-segment energy consumption monitoring and analysis under normal signals, the obtained total standby energy consumption value and dynamic energy evaluation value are judged and processed. If a maintenance signal is obtained, the process proceeds to step 4. If an early warning signal is obtained, feedback is output; Step 3: Based on the time period temperature matching division and discrimination operation under the normal signal, the obtained standby temperature range and working temperature range are discriminated and processed, and the obtained stable signal or deviation signal is output; Step 4: Based on the smart home energy division management analysis under information progression, the obtained standby performance value is discriminated and processed to obtain essential homes and non-essential homes, and output management is performed on non-essential homes; Step 5: Based on the in-depth classification and management analysis of essential homes, the obtained energy consumption values per unit time are distinguished and processed to obtain high-consumption essential homes and low-consumption essential homes, and output management for high-consumption essential homes; The specific continuous and stable energy supply evaluation and analysis process is as follows: The monitoring period of the smart home is collected and set as a time threshold, and the energy supply data of the smart home within the time threshold is obtained. The energy supply data includes the voltage fluctuation rate and the voltage effective value; The process of obtaining the effective voltage value is as follows: the power supply voltage of the smart home is collected every time t1, where t1 is a natural number greater than zero. Then, a set A of power supply voltages is constructed, the root mean square deviation of set A is obtained, and the root mean square deviation of set A is set as the effective voltage value. The process of obtaining the voltage fluctuation rate is as follows: the mean of the voltage effective values within the time threshold is obtained, and the mean of the voltage effective values is set as the voltage effective mean value VP. At the same time, the voltage effective values Vi of the time threshold i are obtained, where i = 1, 2, 3, ..., k, and k is a natural number greater than zero. At the same time, the rated voltage VE of the smart home circuit within the time threshold is obtained, and the voltage fluctuation rate is obtained by calculation. in, ; And the voltage fluctuation rate is judged: If the voltage fluctuation rate is less than the preset voltage fluctuation rate threshold, a normal signal is generated; If the voltage fluctuation rate is greater than or equal to the preset voltage fluctuation rate threshold, a risk signal is generated. When a normal signal or a risk signal is generated, the system immediately responds to the normal signal or the risk signal and performs the preset warning operation corresponding to the normal signal or the risk signal, so as to intuitively understand the energy supply stability of the smart home, help reduce the interference of energy supply on the operation of the smart home, and thus improve the continuous stability of the operation monitoring of the smart home; Based on the time-based energy consumption monitoring and analysis under normal signals, the specific time-based energy consumption monitoring and analysis process is as follows: Obtain the standby period and operating period of the smart home within the time threshold. The operating period represents the duration between the start time and the stop time of the smart home. The smart home includes the TV, air conditioner, etc. Obtaining the standby current and standby resistance of the smart home during the standby period, obtaining the total standby energy consumption of the smart home during the standby period based on the standby current and the standby resistance, and performing judgment processing on the total standby energy consumption: if the total standby energy consumption is less than a preset total standby energy consumption threshold, generating a normal signal; if the total standby energy consumption is greater than or equal to the preset total standby energy consumption threshold, generating an abnormal signal; Acquire actual energy data of the smart home during the operation period, the actual energy data including an operation power characteristic curve, an operation energy consumption characteristic curve, etc., retrieve standard energy data of the smart home during the operation period, perform one-to-one comparison and analysis on the actual energy data and the standard energy data, obtain the matching degree of corresponding parameters between the actual energy data and the standard energy data, set the matching degree of corresponding parameters between the actual energy data and the standard energy data as a dynamic matching value, obtain the number of parameters corresponding to the dynamic matching value greater than or equal to a preset dynamic matching value threshold, set the number of parameters corresponding to the dynamic matching value greater than or equal to the preset dynamic matching value threshold as a dynamic energy evaluation value, and perform discrimination processing on the dynamic energy evaluation value: if the dynamic energy evaluation value is equal to the total number of parameters in the actual energy data, generate a stable signal; if the dynamic energy evaluation value is not equal to the total number of parameters in the actual energy data, generate a dynamic signal; And the normal signal and the stable signal are distinguished and processed. If the normal signal and the stable signal are generated, the maintenance signal is obtained. If the normal signal and the stable signal are not generated, the warning signal is generated. The maintenance signal or the warning signal is responded immediately, and the smart home corresponding to the warning signal is marked in red, so that the abnormal smart home can be managed in a targeted manner to reduce the risk of abnormal energy consumption of the smart home. At the same time, the analysis from the perspective of standby and operation is helpful to improve the accuracy and reliability of the analysis results, and it is convenient for the visual management of abnormal smart homes.
[0016] Example 2: Based on the time period temperature matching division and discrimination operation under normal signals, the specific time period temperature matching division and discrimination operation process is as follows: Obtaining an operating temperature characteristic curve of the smart home within a time threshold, obtaining portions of the operating temperature characteristic curve corresponding to a standby period and an operating period of the smart home in the operating temperature characteristic curve, and setting the portions of the operating temperature characteristic curve corresponding to the standby period and the operating period of the smart home as a standby temperature curve and an operating temperature curve, respectively; The maximum and minimum values of the standby temperature curve and the operating temperature curve are obtained. The standby temperature range and the operating temperature range are constructed based on the maximum and minimum values of the standby temperature curve and the operating temperature curve, respectively. At the same time, the standard standby temperature range and the standard operating temperature range of the smart home are obtained, and the standby temperature range and the operating temperature range are compared and analyzed with the standard standby temperature range and the standard operating temperature range: If the standby temperature range is included in the standard standby temperature range, and the operating temperature range is included in the standard operating temperature range, a stable signal is generated; If the standby temperature range is not included in the standard standby temperature range, or the operating temperature range is not included in the standard operating temperature range, a deviation signal is generated, and the stable signal or deviation signal is immediately responded to, and the smart home corresponding to the deviation signal is marked as "fault" with text, and the smart home corresponding to the stable signal is marked as "stable" with text, so as to intuitively understand the standby and operating status of each smart home, and then perform reasonable on-off management of the energy of the smart home; Based on the maintenance signal and stable signal, the smart home energy partition management analysis is carried out. The specific smart home energy partition management analysis process is as follows: The average daily standby time of each smart home in the standby period is obtained, and the average daily standby time of each smart home within the historical m time thresholds is obtained, where m is a natural number greater than zero. A set RB of daily standby time averages is constructed, and after removing the maximum and minimum values in the set RB, the average value of the set RB is obtained, and the average value of the set RB is set as the standby performance value. The standby performance value is then judged: if the standby performance value is less than the preset standby performance value threshold, the corresponding smart home is judged to be a necessary home; if the standby performance value is greater than or equal to the preset standby performance value threshold, the corresponding smart home is judged to be a non-essential home, and targeted management is performed on the necessary homes and non-essential homes based on the classification results of the smart homes, such as shutting down the non-essential homes and continuing to maintain the necessary homes in standby state, so as to reduce the energy consumption of the non-essential homes; The specific in-depth segmentation management analysis process is as follows: The energy consumption value of each essential home appliance during the standby period is obtained, and then the unit time energy consumption value of each essential home appliance during the standby period is obtained. The unit time energy consumption value is judged and processed. If the unit time energy consumption value is greater than a preset unit time energy consumption value threshold, the corresponding essential home appliance is judged to be a high-consumption essential home appliance. If the unit time energy consumption value is less than or equal to the preset unit time energy consumption value threshold, the corresponding smart home is judged to be a low-consumption essential home appliance. The high-consumption essential home appliance is then powered off, which helps to reduce the overall energy consumption of the smart home, so as to achieve a balance between energy consumption reduction and functional experience, and promote the development of smart homes in a sustainable direction. To sum up, the present invention preliminarily conducts a continuous and stable energy supply evaluation and analysis from the perspective of energy supply of smart homes, so as to intuitively understand the energy supply stability of smart homes, help reduce the interference of energy supply on the operation of smart homes, and thus improve the continuous stability of smart home operation monitoring. Through information progression, analysis is conducted from two points of time-divided energy consumption and time-divided temperature of smart homes, so as to carry out targeted management of abnormal smart homes, so as to reduce the risk of abnormal energy consumption of smart homes, and at the same time facilitate rational disconnection management of energy of smart homes. Division and analysis are carried out from the perspective of daily use of smart homes, and targeted management of smart homes is carried out according to the division results of smart homes, so as to reduce excessive and useless consumption of energy by smart homes, so as to promote the development of smart homes in a sustainable direction.
[0017] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each set of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.
[0018] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.
Claims
1. A real-time energy monitoring method for a smart home system, characterized in that: The following steps are involved: Step 1: Initially conduct a continuous and stable energy supply evaluation and analysis from the perspective of smart home energy supply, and perform discrimination processing on the obtained voltage fluctuation rate. If a normal signal is obtained, proceed to Steps 2 and 3. If a risk signal is obtained, output feedback; Step 2: Based on the time-segment energy consumption monitoring and analysis under normal signals, the obtained total standby energy consumption value and dynamic energy evaluation value are judged and processed. If a maintenance signal is obtained, the process proceeds to step 4. If an early warning signal is obtained, feedback is output; Step 3: Based on the time period temperature matching division and discrimination operation under the normal signal, the obtained standby temperature range and working temperature range are discriminated and processed, and the obtained stable signal or deviation signal is output; Step 4: Based on the smart home energy division management analysis under information progression, the obtained standby performance value is discriminated and processed to obtain essential homes and non-essential homes, and output management is performed on non-essential homes; Step 5: Based on the in-depth division management analysis of essential homes, the obtained energy consumption values per unit time are judged and processed to obtain high-consumption essential homes and low-consumption essential homes, and output management is performed on high-consumption essential homes.
2. The method for real-time energy monitoring applied to a smart home system according to claim 1, characterized in that: The continuous and stable energy supply evaluation and analysis process is as follows: The monitoring period of the smart home is collected and set as a time threshold, and the energy supply data of the smart home within the time threshold is obtained. The energy supply data includes the voltage fluctuation rate and the voltage effective value; The process of obtaining the effective value of voltage is as follows: the power supply voltage of the smart home is collected once every time interval t1, where t1 is a natural number greater than zero. Then, a set A of power supply voltages is constructed, the root mean square deviation of set A is obtained, and the root mean square deviation of set A is set as the effective value of voltage.
3. The method for real-time energy monitoring applied to a smart home system according to claim 2, characterized in that: The process of obtaining the voltage fluctuation rate is as follows: the mean of the effective voltage values within the time threshold is obtained, and the mean of the effective voltage values is set as the effective voltage mean VP. At the same time, the effective voltage values Vi of the time threshold i are obtained, i = 1, 2, 3, ..., k, k is a natural number greater than zero, and the rated voltage VE of the smart home line within the time threshold is obtained. Then, the voltage fluctuation rate is obtained by calculation, and the voltage fluctuation rate is discriminated and processed to obtain a normal signal or a risk signal.
4. The method for real-time energy monitoring applied to a smart home system according to claim 1, characterized in that: The time-based energy consumption monitoring and analysis process is as follows: obtaining the standby period and the running period of the smart home within the time threshold, the running period representing the length of time from the start time to the stop time of the smart home; The standby current and standby resistance of the smart home during the standby period are obtained, the total standby energy consumption of the smart home during the standby period is obtained based on the standby current and standby resistance, and the total standby energy consumption is judged and processed to obtain a normal signal or an abnormal signal.
5. The method for real-time energy monitoring applied to a smart home system according to claim 4, characterized in that: Acquire actual energy data of the smart home during the operation period, the actual energy data including the operation power characteristic curve and the operation energy consumption characteristic curve, retrieve standard energy data of the smart home during the operation period, perform one-to-one comparison and analysis on the actual energy data and the standard energy data, obtain the matching degree of corresponding parameters in the actual energy data and the standard energy data, and set it as the dynamic matching value, obtain the number of parameters corresponding to the dynamic matching value greater than or equal to the preset dynamic matching value threshold, and set it as the dynamic energy evaluation value, and perform discrimination processing on the dynamic energy evaluation value to obtain a stable signal or a dynamic signal; The normal signal and the stable signal are discriminated and processed. If the normal signal and the stable signal are generated, a maintenance signal is obtained. If the normal signal and the stable signal are not generated, an early warning signal is generated.
6. The method for real-time energy monitoring applied to a smart home system according to claim 1, characterized in that: The temperature matching and division determination operation process of the time period is as follows: Obtaining an operating temperature characteristic curve of the smart home within a time threshold, obtaining portions of the operating temperature characteristic curve corresponding to a standby period and an operating period of the smart home in the operating temperature characteristic curve, and setting the portions of the operating temperature characteristic curve corresponding to the standby period and the operating period of the smart home as a standby temperature curve and an operating temperature curve, respectively; The maximum and minimum values in the standby temperature curve and the working temperature curve are obtained, and the standby temperature range and the working temperature range are constructed based on the maximum and minimum values in the standby temperature curve and the working temperature curve respectively. At the same time, the standard standby temperature range and the standard working temperature range of the smart home are obtained, and the standby temperature range and the working temperature range are compared and analyzed with the standard standby temperature range and the standard working temperature range to obtain a stable signal or a deviation signal.
7. The method for real-time energy monitoring applied to a smart home system according to claim 1, characterized in that: The smart home energy partitioning management analysis process is as follows: The average daily standby time of each smart home in the standby period is obtained, and the average daily standby time of each smart home within the historical m time thresholds is obtained, where m is a natural number greater than zero. A set RB of daily standby time averages is constructed, and after removing the maximum and minimum values in the set RB, the average of the set RB is obtained, and the average of the set RB is set as the standby performance value, and the standby performance value is judged: if the standby performance value is less than the preset standby performance value threshold, the corresponding smart home is judged to be a necessary home; if the standby performance value is greater than or equal to the preset standby performance value threshold, the corresponding smart home is judged to be a non-essential home.
8. The method for real-time energy monitoring applied to a smart home system according to claim 7, characterized in that: The in-depth division management analysis process is as follows: the energy consumption value of each necessary home during the standby period is obtained, and then the unit time energy consumption value of each necessary home during the standby period is obtained, and the unit time energy consumption value is judged and processed. If the unit time energy consumption value is greater than the preset unit time energy consumption value threshold, the corresponding necessary home is judged to be a high-consumption necessary home; if the unit time energy consumption value is less than or equal to the preset unit time energy consumption value threshold, the corresponding smart home is judged to be a low-consumption necessary home.