Comprehensive energy user potential assessment system based on artificial intelligence

Abstract

The present invention relates to the field of artificial intelligence data analysis technology, and in particular to an integrated energy user potential assessment system based on artificial intelligence, including a data acquisition module, an electricity consumption analysis module, an electricity consumption rating management module, and an energy analysis determination module; the data acquisition module collects individual energy user electricity demand information and energy equipment electricity consumption capacity information; the electricity consumption analysis module calculates the electricity demand coefficient and the electricity consumption capacity coefficient; the electricity consumption rating management module determines the electricity consumption evaluation level according to the electricity demand coefficient and the electricity consumption capacity coefficient, and obtains the electricity consumption evaluation result; the energy analysis determination module calculates and analyzes the energy-saving potential value to obtain the energy-saving potential analysis result, calculates the energy-saving evaluation coefficient according to the energy-saving potential analysis result, and analyzes to obtain the best electricity consumption strategy. The present invention is used to solve the technical problem of inaccurate electricity consumption potential monitoring.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence data analysis technology, and in particular to an integrated energy user potential assessment system based on artificial intelligence. Background Art

[0002] Artificial intelligence is the study and development of computer systems that can simulate the capabilities and behaviors of human intelligence. It involves building intelligent systems that can perceive, understand, learn, reason, make decisions, and interact to complete various tasks and solve problems.

[0003] Artificial intelligence aims to develop computer systems that can simulate and execute human intelligent activities, so as to have the ability to understand and solve complex problems and demonstrate intelligence in various fields and tasks. However, the potential problems of comprehensive energy user potential assessment based on artificial intelligence are not easy to be discovered, and it is impossible to provide better monitoring and evaluation strategies for electricity consumption potential. Users with different levels of demand have different electricity consumption and corresponding electricity consumption potential. Traditional user potential assessment is difficult to achieve accurate prediction of electricity consumption potential, which in turn reduces the reliability of electricity consumption strategies. This is an urgent problem to be solved. Summary of the invention

[0004] The purpose of the present invention is to solve the problems in the background technology and to propose an integrated energy user potential assessment system based on artificial intelligence.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] An integrated energy user potential assessment system based on artificial intelligence, including: data collection module, electricity consumption analysis module, electricity consumption rating management module and energy analysis determination module;

[0007] The data collection module is used to collect the power demand information of individual energy users and store it in the power demand database, and at the same time collect the power capacity information of energy equipment and store it in the power capacity database; the data collection module includes a power demand information collection unit and a power capacity information collection unit, the power demand information collection unit is used to obtain the daily historical power consumption and power consumption time of individual energy users, and the power capacity information collection unit is used to obtain the rated power and preset usage time of the equipment;

[0008] The power consumption analysis module includes a power demand analysis unit and a power capacity analysis unit; the power demand analysis unit is used to calculate the power demand coefficient, and the power capacity analysis unit is used to calculate the power capacity coefficient;

[0009] The power rating management module is used to determine the power evaluation level according to the power demand coefficient and the power capacity coefficient, and obtain the power evaluation results;

[0010] The energy analysis determination module includes an energy-saving potential analysis unit and an optimal electricity usage strategy generation unit; the energy-saving potential analysis unit is used to calculate and analyze the energy-saving potential values ​​of demand users of different levels according to the electricity consumption evaluation results, and obtain the energy-saving potential analysis results; the optimal electricity usage strategy generation unit is used to calculate the energy-saving evaluation coefficients of demand users of different levels according to the energy-saving potential analysis results, and perform judgment and analysis to obtain the optimal electricity usage strategy.

[0011] It should be noted that the application object of the comprehensive energy user potential assessment system based on artificial intelligence in the embodiment of the present invention can be data monitoring of the electricity consumption potential of apartment users. Specifically, it can be used to analyze electricity demand and evaluate electricity consumption potential, obtain the best electricity consumption strategy, and effectively improve the accuracy of electricity consumption potential prediction and electricity consumption strategy. Among them, energy equipment includes household appliances such as refrigerators and air conditioners. In addition, the present invention uses one quarter as a monitoring period to make a quarterly forecast of the electricity consumption of a household.

[0012] Furthermore, the process of the electricity demand information collection unit collecting the electricity demand information of individual energy users includes:

[0013] One quarter is used as a monitoring cycle for monitoring;

[0014] The electricity demand information of energy users is obtained on a household basis, including the daily historical electricity consumption and daily electricity consumption duration of individual users, which are marked as ls c and yd c , c=1, 2, 3, ..., m; m is a positive integer;

[0015] The electricity demand information of individual energy users is stored in the electricity demand database.

[0016] Furthermore, the process of collecting the power consumption capacity information of the energy equipment by the power consumption capacity information collection unit includes:

[0017] Collect the power consumption information of different energy equipment used by individual users on a household basis, obtain the rated power of different energy equipment used by individual users, and mark them with numbers gl k , k = 1, 2, 3, ..., o; o is a positive integer;

[0018] Get the preset usage time t of different energy devices of individual users k ;

[0019] Storing the power consumption capacity information of different energy devices in a power consumption capacity database;

[0020] Among them, the preset usage time here is the theoretical usage time obtained by technicians based on the historical power consumption data corresponding to different devices, and the actual usage time will be less than the theoretical value.

[0021] Further, the process of the electricity demand analysis unit calculating the electricity demand coefficient includes:

[0022] Through the formula Calculate the electricity demand yx of the user individual within a monitoring period;

[0023] Set the critical threshold yx0 of the electricity demand of the user individual;

[0024] Calculate the electricity demand coefficient XQ through the calculation formula, where the calculation formula is: In the formula, α is the preset proportional coefficient of the electricity demand coefficient, and 0 < α < 1;

[0025] Among them, the critical threshold of the electricity demand of the user individual is based on the total electricity consumption when the energy equipment used by the user individual is running, and the critical threshold of the electricity demand of the user individual is greater than the total electricity consumption when the energy equipment is running.

[0026] Further, the process of the electricity capacity analysis unit calculating the electricity capacity coefficient includes:

[0027] According to the rated power gl k Calculate the total electricity capacity dr of the equipment used by the user individual, where the calculation formula is

[0028] Set the minimum total electricity capacity dr0 according to the electricity demand of the user individual;

[0029] Calculate the electricity capacity coefficient RL through the calculation formula, where the calculation formula is: In the formula, β is the preset proportional coefficient of the electricity capacity coefficient, and 0 < β < 1.

[0030] Further, the process of the electricity rating management module determining the electricity evaluation level according to the electricity demand coefficient and the electricity capacity coefficient and analyzing to obtain the electricity evaluation result includes:

[0031] Integrate and analyze the electricity demand coefficient and the electricity capacity coefficient, and determine the electricity evaluation level. Among them, the calculation formula of the evaluation level value PD is PD = XQ × θ1 + RL × θ2. In the formula, θ1 and θ2 are respectively preset different proportional coefficients;

[0032] Combined with the evaluation level standard value i, when the evaluation level value PD > 0.8, it is determined as a high-demand user i1; when the evaluation level value 1 < PD ≤ 0.8, it is determined as a general-demand user i2; when the evaluation level value PD ≤ 1, it is determined as a low-demand user i3;

[0033] The electricity consumption evaluation result is formed according to the high-demand user i1, the general-demand user i2, or the low-demand user i3;

[0034] The electricity consumption evaluation results are stored and transmitted to the cloud platform.

[0035] Furthermore, the energy-saving potential analysis unit calculates and analyzes the energy-saving potential value, and determines the process of obtaining the energy-saving potential analysis result, including:

[0036] The energy-saving potential analysis unit obtains the electricity consumption evaluation results;

[0037] The actual power consumption of individual users with different levels of demand is obtained on a household basis. j and actual power consumption time d j , j = 1, 2, 3, ..., n; n is a positive integer;

[0038] By formula Calculate the energy consumption value NH of energy equipment used by individual users of different levels of demand in a monitoring period;

[0039] Take the average of the energy consumption values ​​NH to obtain the median energy consumption NH0;

[0040] By formula Calculate the energy saving potential value QL of individual users with different levels of demand;

[0041] The energy-saving potential values ​​of individual users with different levels of demand are judged and analyzed to obtain the energy-saving potential of users with different levels and obtain the energy-saving potential analysis results, that is, the energy-saving potential value of high-level demand user i1 is QL1; the energy-saving potential value of general demand user i2 is QL2; the energy-saving potential value of low-level demand user i3 is QL3;

[0042] The energy saving potential analysis results are sent to the optimal power utilization strategy generation unit.

[0043] Furthermore, the process of the optimal power usage strategy generation unit calculating and analyzing the energy saving evaluation coefficient and generating the optimal power usage strategy includes:

[0044] Set the electricity energy saving target value K of individual users with different levels of demand; obtain the actual electricity consumption value QD of individual users with different levels of demand from the energy consumption value NH of the energy equipment used by the individual users with different levels of demand;

[0045] According to the energy-saving potential analysis results, the energy-saving evaluation coefficient JN of individual demand users of different levels is calculated, where the calculation formula is: In the formula, γ is the preset energy saving potential proportional coefficient, and C is the constant correction coefficient;

[0046] Obtain the standard range (JNmin, JNmax) of the energy-saving assessment coefficient, and make judgment and analysis on the energy-saving assessment coefficient. When the energy-saving assessment coefficient belongs to (JNmin, JNmax), the demand users of this level meet the standards, and are determined as the best electricity consumption signal. Generate the best electricity consumption strategy, and apply the strategy to other households of the same type. When the energy-saving assessment coefficient does not belong to (JNmin, JNmax), the demand users of this level do not meet the standards, and are determined as signals to be optimized. The signals to be optimized are sent to monitoring analysts for optimization processing.

[0047] Compared with the existing technology, the advantages of the comprehensive energy user potential assessment system based on artificial intelligence provided by the present invention are:

[0048] 1. The present invention obtains the power demand information of individual energy users and the power capacity information of energy equipment through a data acquisition module, and stores the collected information in a power demand database and a power capacity database respectively;

[0049] 2. The present invention obtains the daily historical power consumption and power consumption time of individual energy users and the rated power and preset usage time of the equipment through the power consumption analysis module, and calculates the power demand coefficient and power capacity coefficient;

[0050] 3. The present invention determines the electricity consumption evaluation level according to the electricity demand coefficient and the electricity capacity coefficient through the electricity consumption rating management module, and obtains the electricity consumption evaluation result;

[0051] 4. The present invention calculates and analyzes the energy-saving potential values ​​of different levels of demand users according to the electricity consumption evaluation results through the energy analysis determination module, obtains the energy-saving potential analysis results, calculates the energy-saving evaluation coefficients of different levels of demand users according to the energy-saving potential analysis results, and performs judgment and analysis to obtain the optimal electricity consumption strategy.

[0052] In summary, the present invention can analyze and process the calculation results of the energy-saving evaluation coefficient according to actual conditions to obtain the optimal power consumption signal and the signal to be optimized. The system applies the generated optimal power consumption strategy, which effectively improves the accuracy of power consumption potential prediction and power consumption strategy. Through comprehensive data analysis and processing, the normal operation of the subsequent comprehensive energy user potential evaluation system based on artificial intelligence is ensured. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a module diagram of the comprehensive energy user potential assessment system based on artificial intelligence proposed in the present invention. DETAILED DESCRIPTION

[0054] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the implementation regulations described 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 creative work are within the scope of protection of the present invention.

[0055] Reference Figure 1 , an integrated energy user potential assessment system based on artificial intelligence, the system includes a data acquisition module, an electricity consumption analysis module, an electricity consumption rating management module and an energy analysis determination module;

[0056] The data collection module is used to collect the power demand information of individual energy users and store it in the power demand database, and at the same time collect the power capacity information of energy equipment and store it in the power capacity database; the data collection module includes a power demand information collection unit and a power capacity information collection unit, the power demand information collection unit is used to obtain the daily historical power consumption and power consumption time of individual energy users, and the power capacity information collection unit is used to obtain the rated power and preset usage time of the equipment;

[0057] The power consumption analysis module includes a power demand analysis unit and a power capacity analysis unit; the power demand analysis unit is used to calculate the power demand coefficient, and the power capacity analysis unit is used to calculate the power capacity coefficient;

[0058] The power rating management module is used to determine the power evaluation level according to the power demand coefficient and the power capacity coefficient, and obtain the power evaluation results;

[0059] The energy analysis determination module includes an energy-saving potential analysis unit and an optimal electricity usage strategy generation unit; the energy-saving potential analysis unit is used to calculate and analyze the energy-saving potential values ​​of demand users of different levels according to the electricity consumption evaluation results, and obtain the energy-saving potential analysis results; the optimal electricity usage strategy generation unit is used to calculate the energy-saving evaluation coefficients of demand users of different levels according to the energy-saving potential analysis results, and perform judgment and analysis to obtain the optimal electricity usage strategy.

[0060] It should be noted that the application object of the comprehensive energy user potential assessment system based on artificial intelligence in the embodiment of the present invention can be data monitoring of the electricity consumption potential of apartment users. Specifically, it can be used to analyze electricity demand and evaluate electricity consumption potential, obtain the best electricity consumption strategy, and effectively improve the accuracy of electricity consumption potential prediction and electricity consumption strategy. Among them, energy equipment includes household appliances such as refrigerators and air conditioners. In addition, the present invention uses one quarter as a monitoring period to make a quarterly forecast of the electricity consumption of a household.

[0061] The process of the electricity demand information collection unit collecting the electricity demand information of individual energy users includes:

[0062] S101. Monitor with one quarter as one monitoring cycle;

[0063] S102, obtaining the electricity demand information of energy users on a household basis, including the daily historical electricity consumption and daily electricity consumption duration of individual users, and marking them as ls c and yd c , c=1, 2, 3, ..., m; m is a positive integer;

[0064] S103: storing the electricity demand information of individual energy users in an electricity demand database.

[0065] The process of the power consumption capacity information collection unit collecting the power consumption capacity information of the energy equipment includes:

[0066] S201, collecting the power consumption capacity information of different energy devices used by individual users on a household basis, obtaining the rated power of different energy devices used by individual users, and marking them as gl k , k = 1, 2, 3, ..., o; o is a positive integer;

[0067] S202: Obtaining the preset usage time t of different energy devices of individual users k ;

[0068] S203, storing the power consumption capacity information of different energy devices in a power consumption capacity database;

[0069] Among them, the preset usage time here is the theoretical usage time obtained by technicians based on the historical power consumption data corresponding to different devices, and the actual usage time will be less than the theoretical value.

[0070] The process of calculating the electricity demand coefficient by the electricity demand analysis unit includes:

[0071] S301, through the formula Calculate the electricity demand yx of individual users within a monitoring period;

[0072] S302, setting a critical threshold yx0 of the power demand of an individual user;

[0073] S303, calculate the power demand coefficient XQ through a calculation formula, where the calculation formula is: Where α is the preset proportional coefficient of the electricity demand coefficient, and 0<α<1;

[0074] The critical threshold of the power demand of an individual user is based on the total power consumption of the energy equipment used by the individual user during operation, and the critical threshold of the power demand of the individual user is greater than the total power consumption of the energy equipment during operation.

[0075] The process of calculating the electricity consumption capacity coefficient by the electricity consumption capacity analysis unit includes:

[0076] S401. Calculate the total electricity consumption capacity dr of the equipment used by the user individual according to the rated power gl k where the calculation formula is

[0077] S402. Set the minimum total electricity consumption capacity dr0 according to the electricity consumption demand of the user individual;

[0078] S403. Calculate the electricity consumption capacity coefficient RL through the calculation formula, where the calculation formula is: In the formula, β is the preset proportional coefficient of the electricity consumption capacity coefficient, and 0 < β < 1.

[0079] The process that the electricity consumption rating management module determines the electricity consumption evaluation level according to the electricity consumption demand coefficient and the electricity consumption capacity coefficient and obtains the electricity consumption evaluation result through analysis includes:

[0080] S501. Integrate and analyze the electricity consumption demand coefficient and the electricity consumption capacity coefficient, and determine the electricity consumption evaluation level. Among them, the calculation formula of the evaluation level value PD is PD = XQ × θ1 + RL × θ2. In the formula, θ1 and θ2 are respectively preset different proportional coefficients;

[0081] S502. Combine the evaluation level standard value i. When the evaluation level value PD > 0.8, it is determined as a high-demand user i1; when the evaluation level value 1 < PD ≤ 0.8, it is determined as a general-demand user i2; when the evaluation level value PD ≤ 1, it is determined as a low-demand user i3;

[0082] S503. Form the electricity consumption evaluation result according to the high-demand user i1 or the general-demand user i2 or the low-demand user i3;

[0083] S504. Store the electricity consumption evaluation result and transmit it to the cloud platform.

[0084] The process that the energy-saving potential analysis unit calculates and analyzes the energy-saving potential value and judges to obtain the energy-saving potential analysis result includes:

[0085] S601. The energy-saving potential analysis unit obtains the electricity consumption evaluation result;

[0086] S602. Obtain the actual electricity consumption power s j and the actual electricity consumption duration d j of the demand user individuals at different levels for each household, j = 1, 2, 3,..., n; n is a positive integer;

[0087] S603. Through the formula Calculate the energy consumption value NH of energy equipment used by individual users of different levels of demand in a monitoring period;

[0088] S604, taking the average of the energy consumption values ​​NH to obtain the median energy consumption NH0;

[0089] S605, through the formula Calculate the energy saving potential value QL of individual users with different levels of demand;

[0090] S606, judging and analyzing the energy-saving potential values ​​of individual users with different levels of demand, obtaining the energy-saving potential values ​​of users with different levels, and obtaining energy-saving potential analysis results, that is, the energy-saving potential value of the high-level demand user i1 is QL1; the energy-saving potential value of the general demand user i2 is QL2; the energy-saving potential value of the low-level demand user i3 is QL3;

[0091] S607: Send the energy-saving potential analysis result to the optimal power utilization strategy generation unit.

[0092] The process of the optimal power consumption strategy generation unit calculating and analyzing the energy-saving evaluation coefficient and generating the optimal power consumption strategy includes:

[0093] S701, setting the power consumption energy saving target value K of individual demand users of different levels; obtaining the actual power consumption value QD of individual demand users of different levels from the energy consumption value NH of the energy equipment used by the individual demand users of different levels;

[0094] S702. Calculate the energy-saving evaluation coefficient JN of individual demand users of different levels according to the energy-saving potential analysis results, where the calculation formula is: In the formula, γ is the preset energy saving potential proportional coefficient, and C is the constant correction coefficient;

[0095] S703. Obtain the standard range (JNmin, JNmax) of the energy-saving assessment coefficient, and make judgment and analysis on the energy-saving assessment coefficient. When the energy-saving assessment coefficient belongs to (JNmin, JNmax), the demand users of this level meet the standard, and are determined as the best electricity consumption signal. An optimal electricity consumption strategy is generated, and the strategy is applied to other households of the same type. When the energy-saving assessment coefficient does not belong to (JNmin, JNmax), the demand users of this level do not meet the standard, and are determined as signals to be optimized. The signals to be optimized are sent to monitoring analysts for optimization processing.

[0096] In the embodiment of the present invention, the power demand information of individual energy users and the power capacity information of energy equipment are obtained through the data acquisition module, and the collected information is stored in the power demand database and the power capacity database respectively, the daily historical power consumption and power consumption time of individual energy users and the rated power and preset usage time of the equipment are obtained through the power analysis module, and the power demand coefficient and the power capacity coefficient are calculated, and the power rating management module is used to determine the power evaluation level according to the power demand coefficient and the power capacity coefficient, and obtain the power evaluation result, and the energy analysis determination module calculates and analyzes the energy saving potential values ​​of different levels of demand users according to the power evaluation result, obtains the energy saving potential analysis result, calculates the energy saving evaluation coefficients of different levels of demand users according to the energy saving potential analysis result, and performs judgment analysis to obtain the best power strategy. In summary, the example of the present invention involves data collection and analysis, result generation and decision-making of optimization measures, and solves the problem of inaccurate power potential monitoring in the comprehensive energy user potential evaluation system based on artificial intelligence. In actual situations, more data and context information may be needed to make specific decisions and optimization plans.

[0097] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically based on the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0098] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0099] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0100] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0101] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0102] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0103] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0104] Finally: The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An integrated energy user potential assessment system based on artificial intelligence, characterized by: It includes a data acquisition module, an electricity consumption analysis module, an electricity consumption rating management module, and an energy analysis and determination module; The data acquisition module is used to collect the electricity consumption demand information of individual energy users and store it in the electricity consumption demand database. At the same time, it collects the electricity consumption capacity information of energy equipment and stores it in the electricity consumption capacity database; The data acquisition module includes an electricity consumption demand information acquisition unit and an electricity consumption capacity information acquisition unit. The electricity consumption demand information acquisition unit is used to obtain the historical electricity consumption and electricity consumption time of individual energy users on a daily basis. The electricity consumption capacity information acquisition unit is used to obtain the rated power and preset usage time of the equipment; The process of the electricity consumption demand information acquisition unit collecting the electricity consumption demand information of individual energy users includes: Monitoring with a quarter as a monitoring cycle; The electricity demand information of energy users is obtained on a household basis, including the daily historical electricity consumption and daily electricity consumption duration of individual users, which are marked as ls c and yd c , c=1, 2, 3, ..., m; m is a positive integer; Storing the electricity consumption demand information of individual energy users into the electricity consumption demand database; The process of the electricity consumption capacity information acquisition unit collecting the electricity consumption capacity information of energy equipment includes: Collect the power consumption information of different energy equipment used by individual users on a household basis, obtain the rated power of different energy equipment used by individual users, and mark them with numbers gl k , k=1, 2, 3, ..., o; o is a positive integer; Get the preset usage time t of different energy devices of individual users k ; Storing the electricity consumption capacity information of different energy equipment into the electricity consumption capacity database; The electricity consumption analysis module includes an electricity consumption demand analysis unit and an electricity consumption capacity analysis unit. The electricity consumption demand analysis unit is used to calculate the electricity consumption demand coefficient, and the electricity consumption capacity analysis unit is used to calculate the electricity consumption capacity coefficient; Among them, through the formula yx= Calculate the electricity demand yx of individual users within a monitoring period; Set the critical threshold yx0 of the electricity consumption demand of individual users; The power demand coefficient XQ is calculated by the calculation formula, where the calculation formula is: XQ= ; In the formula, α is the preset proportional coefficient of the electricity demand coefficient, and 0< α <1; According to the rated power k Calculate the total power consumption of the equipment used by the individual user, dr, where the calculation formula is dr= ; Set the minimum total electricity consumption capacity dr0 according to the electricity consumption demand of individual users; The power consumption capacity coefficient RL is calculated by the calculation formula, where the calculation formula is: RL= ; In the formula, β is the preset proportional coefficient of the power consumption capacity coefficient, and 0< β＜ 1; The electricity consumption rating management module is used to determine the electricity consumption evaluation level according to the electricity consumption demand coefficient and the electricity consumption capacity coefficient, and obtain the electricity consumption evaluation result; Among them, the electricity consumption demand coefficient and the electricity consumption capacity coefficient are integrated and analyzed to determine the electricity consumption evaluation level. Among them, the calculation formula of the evaluation level value PD is PD = XQ×θ1+RL×θ2, where θ1 and θ2 are respectively preset different proportionality coefficients; Combined with the evaluation level standard value i, when the evaluation level value PD>1, it is determined as a high-demand user i1; when the evaluation level value 0.8 < PD ≤ 1, it is determined as a general-demand user i2; when the evaluation level value PD ≤ 0.8, it is determined as a low-demand user i3; The electricity consumption evaluation result is formed according to the high-demand user i1 or the general-demand user i2 or the low-demand user i3; Store the electricity consumption evaluation result and transmit it to the cloud platform; The energy analysis and determination module includes an energy-saving potential analysis unit and an optimal electricity consumption strategy generation unit. The energy-saving potential analysis unit is used to calculate and analyze the energy-saving potential values of users with different levels of demand according to the electricity consumption evaluation result and obtain the energy-saving potential analysis result. The optimal electricity consumption strategy generation unit is used to calculate the energy-saving evaluation coefficients of users with different levels of demand according to the energy-saving potential analysis result and make a judgment and analysis to obtain the optimal electricity consumption strategy; Among them, the energy-saving potential analysis unit obtains the electricity consumption evaluation result; The actual power consumption of individual users with different levels of demand is obtained on a household basis. j and actual power consumption time d j , j = 1, 2, 3, ..., n; n is a positive integer; By the formula NH= Calculate the energy consumption value NH of energy equipment used by individual users of different levels of demand in a monitoring period; Take the average value of the energy consumption value NH to obtain the energy consumption median NH0; By the formula QL= Calculate the energy saving potential value QL of individual users with different levels of demand; The energy-saving potential values ​​of individual users with different levels of demand are judged and analyzed to obtain the energy-saving potential of users with different levels and obtain the energy-saving potential analysis results, that is, the energy-saving potential value of high-level demand user i1 is QL1; the energy-saving potential value of general demand user i2 is QL2; the energy-saving potential value of low-level demand user i3 is QL3; Sending the energy saving potential analysis results to the optimal power usage strategy generation unit; Set the electricity energy saving target value K of individual users with different levels of demand; obtain the actual electricity consumption value QD of individual users with different levels of demand from the energy consumption value NH of the energy equipment used by the individual users with different levels of demand; According to the energy-saving potential analysis results, the energy-saving evaluation coefficient JN of individual demand users of different levels is calculated, where the calculation formula is JN= +C, where γ is the preset energy saving potential proportional coefficient and C is the constant correction coefficient; Obtain the standard range (JNmin, JNmax) of the energy-saving assessment coefficient, and make judgment and analysis on the energy-saving assessment coefficient. When the energy-saving assessment coefficient belongs to (JNmin, JNmax), the demand users of this level meet the standard, and are determined as the best electricity consumption signal. Generate the best electricity consumption strategy, and apply the strategy to other households of the same type. When the energy-saving assessment coefficient does not belong to (JNmin, JNmax), the demand users of this level do not meet the standard, and are determined as signals to be optimized. The signals to be optimized are sent to monitoring analysts for optimization processing.

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