A method and system for optimizing household power energy efficiency

Abstract

The present invention provides a method and system for optimizing household power energy efficiency, the method comprising: comprehensively evaluating each household power energy efficiency index system based on the power consumption information of each household user using a pre-built energy efficiency evaluation model; obtaining the power consumption of all controllable loads in household power equipment within a set period based on the evaluation results of each household user, the operating parameters of each controllable load in the household user's power equipment and the pre-built controllable load model; optimizing household power consumption behavior with the goal of minimizing the load peak-to-valley difference based on the power consumption of all controllable loads in household power equipment within a set period. The present invention can accurately evaluate household energy efficiency and provide a power optimization solution for users with low power energy efficiency.

Description

Technical Field

[0001] The present invention relates to the field of power demand side management, and in particular to a method and system for optimizing household power energy efficiency. Background Art

[0002] With the continuous development of social economy, the proportion of residential electricity consumption in the total electricity consumption of the whole society has gradually increased, but the comprehensive utilization efficiency of electricity is still very low, and the energy conservation and emission reduction work of household users has received more and more attention. At the same time, the development of smart household electrical equipment and load monitoring technology has enabled power grid companies to obtain a large amount of household electricity consumption information. These user-side power data provide data support for the implementation of power demand side management methods. How to use this information to evaluate the power energy efficiency of household users and formulate personalized solutions for users with low energy efficiency, so as to improve the power efficiency of household users, is of great significance to optimizing the resource allocation of the power industry. Summary of the invention

[0003] In order to solve the above-mentioned deficiencies in the prior art, the present invention provides a method for optimizing household power energy efficiency, comprising:

[0004] Based on the electricity consumption information of each household user, a pre-built energy efficiency evaluation model is used to comprehensively evaluate the electricity energy efficiency index system of each household;

[0005] Based on the evaluation results of each household user, the operating parameters of each controllable load in the household user's electrical equipment and the pre-built controllable load model, the power consumption of all controllable loads in the household electrical equipment within a set period is obtained;

[0006] Based on the power consumption of all controllable loads in household electrical equipment within a set period, the household electricity consumption behavior is optimized with the goal of minimizing the load peak-to-valley difference.

[0007] Preferably, the construction of the energy efficiency evaluation model includes:

[0008] Establish a multi-level household electricity energy efficiency indicator system;

[0009] Performing dimensionless preprocessing on the indicators in the household power energy efficiency indicator system;

[0010] The weight vectors of indicators at each level in the household electricity energy efficiency indicator system are calculated in turn;

[0011] Based on the weight vectors of all upper-level indicators in the multi-level household electricity energy efficiency index system and the weight vectors of lower-level indicators corresponding to each upper-level indicator, an energy efficiency evaluation model is established using a hierarchical comprehensive evaluation method.

[0012] Preferably, the indicators in the household power energy efficiency indicator system are dimensionlessly preprocessed according to the following formula:

[0013]

[0014] Where: x * represents the dimensionless index value, x i represents the value of the i-th index before dimensionless conversion, represents the minimum value of the i-th index, It represents the maximum value of the ith indicator, and n represents the total number of indicators.

[0015] Preferably, the step of calculating the index weight vectors of each level in the household power energy efficiency index system in sequence includes:

[0016] Evaluate the primary indicators in the household electricity energy efficiency index system based on the analytic hierarchy process or the G1 group method to obtain a weight vector for each primary indicator;

[0017] The entropy weight method is used to obtain the weight vector of the secondary index under each primary index in the household power energy efficiency index system;

[0018] The household electricity energy efficiency index system is a secondary index system.

[0019] Preferably, the first level of the household power energy efficiency index system includes household user information, power consumption information of electrical equipment, and household power consumption information at different power consumption periods;

[0020] The second level indicators of the household user information include: annual household electricity consumption per capita and annual household electricity consumption per unit area;

[0021] The second level indicators of the power consumption information of the power-consuming equipment include: annual power consumption of transferable power-consuming equipment, annual power consumption of air-conditioning system, and annual power consumption of lighting and entertainment equipment;

[0022] The second-level indicators of the household electricity consumption information in different electricity consumption periods include: household electricity consumption during the annual low electricity consumption period, household electricity consumption during the annual peak electricity consumption period, and household electricity consumption during the annual flat electricity consumption period.

[0023] Preferably, the evaluating of the primary indicators in the household power energy efficiency index system based on the analytic hierarchy process or the G1 group method to obtain the weight vector of each primary indicator includes:

[0024] Compare the primary indicators in the household electricity energy efficiency index system in pairs and establish a judgment matrix;

[0025] When the consistency index of the judgment matrix meets the requirements, the first-level index in the household power energy efficiency index system is evaluated based on the hierarchical analysis method to obtain the weight vector of each first-level index;

[0026] Otherwise, the first-level indicators in the household electricity energy efficiency indicator system are evaluated based on the G1 group method to obtain the weight vector of each first-level indicator.

[0027] Preferably, the energy efficiency evaluation model is as shown below:

[0028]

[0029] Where: e is the electricity efficiency of household users; λ i represents the weight of the i-th first-level indicator; n is the number of first-level indicators; η ij represents the vector weight of the secondary indicator under the i-th primary indicator; m is the number of secondary indicators under the i-th primary indicator; z ij is the jth secondary indicator under the i-th primary indicator.

[0030] Preferably, the construction of the controllable load model includes:

[0031] The objective function is to obtain the state of the controllable load corresponding to each time interval within the set period;

[0032] The constraints are that the state adjustment of the controllable load needs to be within the working time interval allowed by the user, the allowed working time interval of the controllable load needs to be greater than the time required to complete the task, and the sum of the working states of the controllable load within the working time interval allowed by the user must be equal to the total working time required to complete the task;

[0033] When the controllable load is an electric vehicle, the constraints must also be met:

[0034] The charging power of the electric vehicle is less than its maximum charging power and the state of charge of the electric vehicle is maintained between the minimum state of charge and the maximum state of charge;

[0035] Among them, the controllable loads include washing machines, air conditioners, water heaters and electric vehicles.

[0036] Preferably, the obtaining of the power consumption of all controllable loads in the household electrical equipment within a set period based on the evaluation results of each household user, the operating parameters of each controllable load in the household user's electrical equipment and the pre-built controllable load model includes:

[0037] Based on the evaluation results of each household user, the household users whose electricity energy efficiency evaluation scores in the evaluation results are lower than the threshold;

[0038] Based on the time that the household user is allowed to arrange the controllable load electricity consumption and the pre-built controllable load model, the state of all controllable loads in the household electrical equipment at each time interval within the set period is obtained;

[0039] Based on the states of all controllable loads in household electrical equipment at each time interval within a set period and the power of the controllable loads, the power consumption of all controllable loads in household electrical equipment at each time interval within the set period is obtained.

[0040] Preferably, the household electricity consumption behavior is optimized according to the following formula:

[0041] min D=max(T new )-min(T new )

[0042] Where: D is the peak-to-valley difference of load, T new It is the load value vector within the set period after optimization, which is composed of the power consumption of the controllable load in each time interval.

[0043] Based on the same inventive concept, the present invention also provides a household power energy efficiency optimization system, comprising:

[0044] An evaluation module is used to comprehensively evaluate the power energy efficiency index system of each household based on the acquired power consumption information of each household user using a pre-built energy efficiency evaluation model;

[0045] A calculation module, for obtaining the power consumption of all controllable loads in household electrical equipment within a set period based on the evaluation results of each household user, the operating parameters of each controllable load in the household user's electrical equipment and a pre-built controllable load model;

[0046] The optimization module is used to optimize household electricity consumption behavior based on the power consumption of all controllable loads in household electrical equipment within a set period, with the goal of minimizing the load peak-to-valley difference.

[0047] Preferably, the system further comprises a construction module for constructing an energy efficiency evaluation model; the construction module is specifically used for:

[0048] Establish a multi-level household electricity energy efficiency indicator system;

[0049] Performing dimensionless preprocessing on the indicators in the household power energy efficiency indicator system;

[0050] The weight vectors of indicators at each level in the household electricity energy efficiency indicator system are calculated in turn;

[0051] Based on the weight vectors of all upper-level indicators in the multi-level household electricity energy efficiency index system and the weight vectors of lower-level indicators corresponding to each upper-level indicator, an energy efficiency evaluation model is established using a hierarchical comprehensive evaluation method.

[0052] The technical solution provided by the present invention has the following beneficial effects:

[0053] The technical solution provided by the present invention uses a pre-constructed energy efficiency evaluation model to comprehensively evaluate the power energy efficiency index system of each household based on the power consumption information of each household user; based on the evaluation results of each household user, the operating parameters of each controllable load in the household user's power equipment and the pre-constructed controllable load model, the power consumption of all controllable loads in the household power equipment within a set period is obtained; based on the power consumption of all controllable loads in the household power equipment within a set period, the household power consumption behavior is optimized with the goal of minimizing the load peak-to-valley difference. This technical solution uses the constructed energy efficiency evaluation model to comprehensively and comprehensively evaluate the household energy efficiency evaluation index system, which not only takes into account subjective and objective evaluation information, but also can accurately obtain the evaluation results of household energy efficiency. At the same time, it provides a power optimization plan for users with low power efficiency, which provides a basis for evaluating the power efficiency of power customers, formulating user energy-saving plans, and tapping users' energy-saving potential. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 A flow chart of a household power energy efficiency optimization method provided by the present invention;

[0055] Figure 2 is a detailed flow chart of a household power energy efficiency optimization method in an embodiment of the present invention;

[0056] Figure 3 A two-level household energy efficiency evaluation index system is established for the present invention. DETAILED DESCRIPTION

[0057] In order to better understand the present invention, the content of the present invention is further described below in conjunction with the accompanying drawings and examples.

[0058] Example 1: Figure 1 As shown, the present invention provides a method for optimizing household power energy efficiency, comprising:

[0059] S1 uses the pre-built energy efficiency evaluation model to comprehensively evaluate the power energy efficiency index system of each household based on the electricity consumption information of each household user;

[0060] S2 obtains the power consumption of all controllable loads in household electrical equipment within a set period based on the evaluation results of each household user, the operating parameters of each controllable load in the household user's electrical equipment and the pre-built controllable load model;

[0061] S3 optimizes household electricity consumption based on the power consumption of all controllable loads in household electrical equipment within a set period, with the goal of minimizing the load peak-to-valley difference.

[0062] use Figure 2 right Figure 1 The technical solution shown is specifically introduced:

[0063] Step 1) Create an entry Figure 3 The household electricity energy efficiency evaluation index system shown in the figure includes household user information, electricity consumption information of electrical equipment, and household electricity consumption information at different electricity consumption periods at the first level. In the second level indicators, household user information includes: annual per capita household electricity consumption, annual per capita household electricity consumption per unit area, the annual per capita household electricity consumption is the total household electricity consumption in a year divided by the number of family members, and the annual per capita household electricity consumption per unit area is the total household electricity consumption in a year divided by the area of ​​the family; electricity consumption information of electrical equipment includes: annual electricity consumption of transferable electrical equipment, annual electricity consumption of air-conditioning system, annual electricity consumption of lighting and entertainment equipment. Transferable electrical equipment refers to electrical equipment whose electricity consumption time can be flexibly selected, including washing machines, water heaters, electric vehicles, and entertainment equipment includes computers and televisions. The household electricity consumption information at different periods includes the household electricity consumption during the annual off-peak period, the household electricity consumption during the annual peak period, and the household electricity consumption during the annual flat-rate period. With reference to China's time-of-use electricity price information, the peak periods are: 9:00-11:59, 15:00-21:59; the normal periods are: 6:00-8:59, 12:00-14:59, 22:00-23:59; the off-peak period is: 0:00-5:59.

[0064] Step 2) In order to make the indicator data of different units or magnitudes weighted comparison possible, the indicator is dimensionless processed by the dimensionless processing formula, the formula is as follows:

[0065]

[0066] where x * represents the dimensionless index value, x i represents the value of the i-th index before dimensionless conversion, represents the minimum value of the i-th index, Indicates the maximum value of the i-th indicator.

[0067] Step 3) Use the analytic hierarchy process and G1 group method to determine the weight value of the first-level index, including:

[0068] First, the energy efficiency indicators of the first level are compared pairwise to establish the judgment matrix B.

[0069]

[0070] In the formula, ω ij It is the importance of the i-th indicator relative to the j-th indicator in the first-level evaluation index system.

[0071] The eigenvector γ of equation (2) is determined by using the matrix product square root method. i .

[0072]

[0073]

[0074] According to the determined eigenvector γ i , find the maximum eigenvalue λ max .

[0075]

[0076] According to λ max Calculate the consistency index β of the judgment matrix B.

[0077]

[0078] According to the ratio of the consistency index β of matrix B to the average random consistency index of the same order, if the ratio is less than 0.1, it is considered that the judgment matrix B meets the consistency, and the eigenvector γ i is the weight of the first-level indicator. Otherwise, the weight of the first-level indicator is determined according to the G1 group method.

[0079] Among them, the G1 group method is an improved method of determining the indicator weights of the hierarchical analysis method without the need for consistency testing. It is a subjective experience judgment method that does not require the construction of a judgment matrix, has a small amount of calculation, and does not limit the number of indicators at the same level.

[0080] The steps of the G1 group method in this embodiment are as follows:

[0081] First, determine the order relationship between indicators: if an indicator x in the energy efficiency evaluation of household users i The importance of x is greater than j , then record it as x i >x j If the indices x1, x2, ..., x m With respect to the evaluation index set X = {x1, x2, ..., x m}, their sequence relationship can be determined by the following steps: First, select the most important indicator among the m indicators in the indicator set X, marked as x i ; Then select the most important indicator from the remaining indicators and mark it as x j ; And so on; in this way, the unique index order relationship can be determined.

[0082] Then judge the importance between the two indicators, assuming that the two evaluation indicators x k-1 and x k The importance ratio is κ k-1 / κk , denoted as r k , see formula:

[0083] r k =κ k-1 / κ k (7)

[0084] Among them, k=m,m-1,m-2,...,3,2,κ k Represents the weight corresponding to the kth indicator in the indicator set.

[0085] ω ij and r i The reference table of values ​​is as follows:

[0086] Table 1ω ij and r i Reference table for values

[0087] <![CDATA[ω ij or i ]]> describe 1.0 Both indicators are equally important 1.2 The former indicator is slightly more important than the latter indicator 1.4 The former indicator is obviously more important than the latter indicator 1.6 The former indicator is more important than the latter indicator 1.8 The former indicator is extremely important than the latter indicator 1.1，1.3，1.5，1.7 Corresponding to the middle case of the above two adjacent judgments

[0088] At the same time there is the formula:

[0089]

[0090] Recursion can be obtained:

[0091] κ k-1 =κ k r k (9)

[0092] Among them, k = m, m-1, m-2, ..., 3, 2.

[0093] Step 4), suppose there are m secondary indicators y1, y2, ..., y under the i-th primary indicator m , the entropy weight method is used to configure the weights of these m secondary indicators, including:

[0094] Calculate the information entropy of each indicator, assuming that the information entropy of each indicator is E j , the calculation formula is as follows:

[0095]

[0096]

[0097] Finally, the weight of each indicator is calculated using the following formula:

[0098]

[0099] Step 5) Assume that the weight vectors of the three primary energy efficiency indicators of household users are λ = [λ1,λ2,...,λ n], the weight of the secondary energy efficiency index vector under the i-th primary energy efficiency index is η i =[η i1 ,η i2 ,...,η im ], the household electricity energy efficiency evaluation model based on the hierarchical comprehensive evaluation method is:

[0100]

[0101] In the formula, e is the electricity efficiency of household users; λ i represents the weight of the i-th first-level indicator; n is the number of first-level indicators; η ij represents the vector weight of the secondary indicator under the i-th primary indicator; m is the number of secondary indicators under the i-th primary indicator; z ij It is the jth secondary indicator under the i-th primary indicator.

[0102] Step 6) Model the controllable loads in the home. The common feature of this type of load is that its electricity consumption time can be flexibly arranged within the time range allowed by the user. Its electricity consumption mathematical model is as follows:

[0103] α h ≤t≤β h h∈H (14)

[0104] In the formula, H represents the set of controllable electrical equipment, h represents a certain controllable electrical equipment; [α h ,β h ] represents the allowed working time of h users of the controllable load;

[0105] The allowed working time interval of the controllable load h needs to be greater than the time required to complete the task, as shown in the following formula:

[0106] β h -α h ≥d h (15)

[0107] Where, d h It indicates the working time required for the controllable equipment to complete the required task;

[0108] The state adjustment of controllable electrical equipment needs to be within the working time interval allowed by the user [α h ,β h ], as shown below:

[0109]

[0110] In the formula, s h,t is the working state variable of the controllable load. When it is 1, it means that the controllable electrical equipment is in working state, and when it is 0, it means that the controllable electrical equipment is in off state;

[0111] The sum of the working states of the controllable electrical equipment within the working time interval allowed by the user must be equal to the total working time required to complete the task, as shown in the following formula:

[0112]

[0113] In addition, for charging equipment such as electric vehicles, their operating characteristics also need to meet the following constraints:

[0114]

[0115] The charging power of the electric vehicle is less than its maximum charging power As shown below:

[0116]

[0117] The state of charge of electric vehicles should be maintained at the minimum state of charge S min and maximum state of charge S max Between, as shown below:

[0118] S min ≤S(t)≤S max (20)

[0119] Where S(t+1) and S(t) are the state of charge of the electric vehicle at time t+1 and time t respectively; P ch is the charging power of the electric vehicle; E is the rated capacity of the electric vehicle battery.

[0120] For users with low electricity energy efficiency evaluation scores, their electricity consumption is optimized with the load peak-valley difference as the target to improve their electricity energy efficiency. The optimization target formula is shown as follows:

[0121] min D=max(T new )-min(T new ) (twenty one)

[0122] Where D is the peak-to-valley difference of load, T new To optimize the load value vector for the next 24 hours, the power consumption is calculated from the status of the controllable load and the power of the controllable load every hour.

[0123] The controllable load usage time in the home is optimized with equation (21) as the goal, and the state variable s of the controllable load is h,t As a variable, controllable loads can be transferred from peak hours to off-peak hours as much as possible to reduce users' electricity costs and reduce the peak-to-valley difference in electricity consumption.

[0124] The technical solution provided by the present invention is as follows: first, according to the electricity consumption information of household users, a two-level household power energy efficiency index system is established, and the indicators in the user's energy efficiency index system are dimensionlessly preprocessed, and then the first-level indicators are evaluated by using the analytic hierarchy process or the G1 group method, and the second-level indicators are evaluated by using the entropy weight method, and finally an energy efficiency evaluation model based on the hierarchical comprehensive evaluation method is constructed to comprehensively evaluate the household's power energy efficiency; according to the evaluation results, the controllable loads in household electrical equipment are mathematically modeled, and for users with low energy efficiency evaluation, the peak-to-valley difference of the load is minimized, and their electricity consumption is optimized to improve their electricity efficiency. The technical solution establishes a comprehensive household energy efficiency evaluation index system, and the established comprehensive evaluation model comprehensively considers the subjective and objective evaluation information, can accurately evaluate household energy efficiency, and provides a basis for power companies to formulate energy-saving plans for users and fully tap the energy-saving potential of users.

[0125] Embodiment 2: Based on the same inventive concept, the embodiment of the present invention further provides a household power energy efficiency optimization system, including:

[0126] An evaluation module is used to comprehensively evaluate the power energy efficiency index system of each household based on the acquired power consumption information of each household user using a pre-built energy efficiency evaluation model;

[0127] A calculation module, for obtaining the power consumption of all controllable loads in household electrical equipment within a set period based on the evaluation results of each household user, the operating parameters of each controllable load in the household user's electrical equipment and a pre-built controllable load model;

[0128] The optimization module is used to optimize household electricity consumption behavior based on the power consumption of all controllable loads in household electrical equipment within a set period, with the goal of minimizing the load peak-to-valley difference.

[0129] In an embodiment, the system further includes a construction module for constructing an energy efficiency evaluation model; the construction module is specifically used for:

[0130] Establish a multi-level household electricity energy efficiency indicator system;

[0131] Performing dimensionless preprocessing on the indicators in the household power energy efficiency indicator system;

[0132] The weight vectors of indicators at each level in the household electricity energy efficiency indicator system are calculated in turn;

[0133] Based on the weight vectors of all upper-level indicators in the multi-level household electricity energy efficiency index system and the weight vectors of lower-level indicators corresponding to each upper-level indicator, an energy efficiency evaluation model is established using a hierarchical comprehensive evaluation method.

[0134] In the embodiment, the calculation of the index weight vectors of each level in the household power energy efficiency index system in sequence specifically includes:

[0135] Evaluate the primary indicators in the household electricity energy efficiency index system based on the analytic hierarchy process or the G1 group method to obtain a weight vector for each primary indicator;

[0136] The entropy weight method is used to obtain the weight vector of the secondary index under each primary index in the household power energy efficiency index system;

[0137] The household electricity energy efficiency index system is a secondary index system.

[0138] In the embodiment, the first level of the household power energy efficiency index system includes household user information, power consumption information of electrical equipment, and household power consumption information at different power consumption periods;

[0139] The second level indicators of the household user information include: annual household electricity consumption per capita and annual household electricity consumption per unit area;

[0140] The second level indicators of the power consumption information of the power-consuming equipment include: annual power consumption of transferable power-consuming equipment, annual power consumption of air-conditioning system, and annual power consumption of lighting and entertainment equipment;

[0141] The second-level indicators of the household electricity consumption information in different electricity consumption periods include: household electricity consumption during the annual low electricity consumption period, household electricity consumption during the annual peak electricity consumption period, and household electricity consumption during the annual flat electricity consumption period.

[0142] In the embodiment, the first-level indicators in the household power energy efficiency index system are evaluated based on the hierarchical analysis method or the G1 group method to obtain the weight vector of each first-level indicator, including:

[0143] Compare the primary indicators in the household electricity energy efficiency index system in pairs and establish a judgment matrix;

[0144] When the consistency index of the judgment matrix meets the requirements, the first-level index in the household power energy efficiency index system is evaluated based on the hierarchical analysis method to obtain the weight vector of each first-level index;

[0145] Otherwise, the first-level indicators in the household electricity energy efficiency indicator system are evaluated based on the G1 group method to obtain the weight vector of each first-level indicator.

[0146] In the embodiment, the construction of the controllable load model includes:

[0147] The objective function is to obtain the state of the controllable load corresponding to each time interval within the set period;

[0148] The constraints are that the state adjustment of the controllable load needs to be within the working time interval allowed by the user, the allowed working time interval of the controllable load needs to be greater than the time required to complete the task, and the sum of the working states of the controllable load within the working time interval allowed by the user must be equal to the total working time required to complete the task;

[0149] When the controllable load is an electric vehicle, the constraints must also be met:

[0150] The charging power of the electric vehicle is less than its maximum charging power and the state of charge of the electric vehicle is maintained between the minimum state of charge and the maximum state of charge;

[0151] Among them, the controllable loads include washing machines, air conditioners, water heaters and electric vehicles.

[0152] In an embodiment, the computing module comprises:

[0153] A selection unit is used to select household users whose electricity energy efficiency evaluation scores are lower than a threshold value in the evaluation results obtained based on the evaluation results of each household user;

[0154] A first calculation unit is used to obtain the status of all controllable loads in the household electrical equipment at each time interval within a set period based on the time allowed by the household user to arrange the controllable load power consumption and the pre-built controllable load model;

[0155] The second calculation unit is used to obtain the power consumption of all controllable loads in the household electrical equipment at each time interval within the set period based on the state of all controllable loads in the household electrical equipment at each time interval within the set period and the power of the controllable loads.

[0156] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0157] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes 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 generate 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.

[0158] 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.

[0159] 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 A step that specifies a function in one or more boxes.

[0160] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are included in the scope of the claims of the present invention to be approved.

Claims

1. A method for optimizing household power energy efficiency, characterized in that: include: Based on the electricity consumption information of each household user, a pre-built energy efficiency evaluation model is used to comprehensively evaluate the electricity energy efficiency index system of each household; Based on the evaluation results of each household user, the operating parameters of each controllable load in the household user's electrical equipment and the pre-built controllable load model, the power consumption of all controllable loads in the household electrical equipment within a set period is obtained; Based on the power consumption of all controllable loads in household electrical equipment within a set period, the household electricity consumption behavior is optimized with the goal of minimizing the load peak-to-valley difference; The construction of the energy efficiency evaluation model includes: Establish a multi-level household electricity energy efficiency indicator system; Performing dimensionless preprocessing on the indicators in the household power energy efficiency indicator system; The weight vectors of indicators at each level in the household electricity energy efficiency indicator system are calculated in turn; Based on the weight vectors of all upper-level indicators in the multi-level household electricity energy efficiency index system and the weight vectors of lower-level indicators corresponding to each upper-level indicator, an energy efficiency evaluation model is established using a hierarchical comprehensive evaluation method. The first level of the household power energy efficiency index system includes household user information, power consumption information of electrical equipment, and household power consumption information at different power consumption periods; The second level indicators of the household user information include: annual household electricity consumption per capita and annual household electricity consumption per unit area; The second level indicators of the power consumption information of the power-consuming equipment include: annual power consumption of transferable power-consuming equipment, annual power consumption of air-conditioning system, and annual power consumption of lighting and entertainment equipment; The second-level indicators of household electricity consumption information at different electricity consumption periods include: household electricity consumption during the annual low electricity consumption period, household electricity consumption during the annual peak electricity consumption period, and household electricity consumption during the annual flat electricity consumption period; The construction of the controllable load model includes: The objective function is to obtain the state of the controllable load corresponding to each time interval within the set period; The constraints are that the state adjustment of the controllable load needs to be within the working time interval allowed by the user, the allowed working time interval of the controllable load needs to be greater than the time required to complete the task, and the sum of the working states of the controllable load within the working time interval allowed by the user must be equal to the total working time required to complete the task; When the controllable load is an electric vehicle, the constraints must also be met: The charging power of the electric vehicle is less than its maximum charging power and the state of charge of the electric vehicle is maintained between the minimum state of charge and the maximum state of charge; Among them, the controllable loads include washing machines, air conditioners, water heaters and electric vehicles.

2. The method according to claim 1, characterized in that The indicators in the household electricity energy efficiency indicator system are dimensionlessly preprocessed as follows: Where: x * represents the dimensionless index value, x i represents the value of the i-th index before dimensionless conversion, represents the minimum value of the i-th index, It represents the maximum value of the ith indicator, and n represents the total number of indicators.

3. The method according to claim 1, characterized in that The calculation of the index weight vectors of each level in the household power energy efficiency index system in turn includes: Evaluate the primary indicators in the household electricity energy efficiency index system based on the analytic hierarchy process or the G1 group method to obtain a weight vector for each primary indicator; The entropy weight method is used to obtain the weight vector of the secondary index under each primary index in the household power energy efficiency index system; The household electricity energy efficiency index system is a secondary index system.

4. The method according to claim 3, characterized in that The method of evaluating the primary indicators in the household power energy efficiency index system based on the analytic hierarchy process or the G1 group method to obtain the weight vector of each primary indicator includes: Compare the primary indicators in the household electricity energy efficiency index system in pairs and establish a judgment matrix; When the consistency index of the judgment matrix meets the requirements, the first-level index in the household power energy efficiency index system is evaluated based on the hierarchical analysis method to obtain the weight vector of each first-level index; Otherwise, the first-level indicators in the household electricity energy efficiency indicator system are evaluated based on the G1 group method to obtain the weight vector of each first-level indicator.

5. The method according to claim 1, characterized in that The energy efficiency evaluation model is shown in the following formula: Where: e is the electricity efficiency of household users; represents the weight of the i-th first-level indicator; n is the number of first-level indicators; Represents the vector weight of the secondary indicators under the i-th primary indicator; m is the number of secondary indicators under the i-th primary indicator; Z ij is the jth secondary indicator under the i-th primary indicator.

6. The method according to claim 1, characterized in that The method of obtaining the power consumption of all controllable loads in household electrical equipment within a set period based on the evaluation results of each household user, the operating parameters of each controllable load in the household user's electrical equipment and the pre-built controllable load model includes: Based on the evaluation results of each household user, the household users whose electricity energy efficiency evaluation scores in the evaluation results are lower than the threshold; Based on the time that the household user is allowed to arrange the controllable load electricity consumption and the pre-built controllable load model, the state of all controllable loads in the household electrical equipment at each time interval within the set period is obtained; Based on the states of all controllable loads in household electrical equipment at each time interval within a set period and the power of the controllable loads, the power consumption of all controllable loads in household electrical equipment at each time interval within the set period is obtained.

7. The method according to claim 6, characterized in that Optimize household electricity consumption behavior according to the following formula: Where: D is the peak-to-valley difference of load, T new It is the load value vector within the set period after optimization, which is composed of the power consumption of the controllable load in each time interval.

8. A household power energy efficiency optimization system, characterized in that: include: An evaluation module is used to comprehensively evaluate the power energy efficiency index system of each household based on the acquired power consumption information of each household user using a pre-built energy efficiency evaluation model; A calculation module, for obtaining the power consumption of all controllable loads in household electrical equipment within a set period based on the evaluation results of each household user, the operating parameters of each controllable load in the household user's electrical equipment and a pre-built controllable load model; An optimization module is used to optimize household electricity consumption behavior based on the power consumption of all controllable loads in household electrical equipment within a set period, with the goal of minimizing the load peak-to-valley difference; The system further includes a building module for building an energy efficiency evaluation model; the building module is specifically used for: Establish a multi-level household electricity energy efficiency indicator system; Performing dimensionless preprocessing on the indicators in the household power energy efficiency indicator system; The weight vectors of indicators at each level in the household electricity energy efficiency indicator system are calculated in turn; Based on the weight vectors of all upper-level indicators in the multi-level household electricity energy efficiency index system and the weight vectors of lower-level indicators corresponding to each upper-level indicator, an energy efficiency evaluation model is established using a hierarchical comprehensive evaluation method. The first level of the household power energy efficiency index system includes household user information, power consumption information of electrical equipment, and household power consumption information at different power consumption periods; The second level indicators of the household user information include: annual household electricity consumption per capita and annual household electricity consumption per unit area; The second level indicators of the power consumption information of the power-consuming equipment include: annual power consumption of transferable power-consuming equipment, annual power consumption of air-conditioning system, and annual power consumption of lighting and entertainment equipment; The second-level indicators of household electricity consumption information at different electricity consumption periods include: household electricity consumption during the annual low electricity consumption period, household electricity consumption during the annual peak electricity consumption period, and household electricity consumption during the annual flat electricity consumption period; The construction of the controllable load model includes: The objective function is to obtain the state of the controllable load corresponding to each time interval within the set period; The constraints are that the state adjustment of the controllable load needs to be within the working time interval allowed by the user, the allowed working time interval of the controllable load needs to be greater than the time required to complete the task, and the sum of the working states of the controllable load within the working time interval allowed by the user must be equal to the total working time required to complete the task; When the controllable load is an electric vehicle, the constraints must also be met: The charging power of the electric vehicle is less than its maximum charging power and the state of charge of the electric vehicle is maintained between the minimum state of charge and the maximum state of charge; Among them, the controllable loads include washing machines, air conditioners, water heaters and electric vehicles.

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