User demand response cost evaluation method and device, equipment and storage medium

Abstract

The invention provides a user demand response cost evaluation method, device and equipment and a storage medium, and belongs to the field of electricity markets, and the method comprises the steps: obtaining an interaction willingness and an interaction proportion of a sample user group participating in demand response, and determining a membership degree set according to the interaction willingness and the interaction proportion; a comprehensive membership function under different temperatures and different electricity prices is established according to the membership set, and the comprehensive membership function is adjusted through electricity consumption time; according to the adjusted comprehensive membership function, respectively constructing a reducible load marginal utility function and a translational load marginal utility function of user power consumption; and respectively determining the demand response cost corresponding to the change of the electricity consumption, and further determining the total cost of the user demand response. The calculation method is simple in principle, reliable, efficient, high in practicability and suitable for the residential user demand response cost in different electricity utilization environments, the comprehensive energy system can be effectively helped to participate in market competition, and the operation cost of the comprehensive energy system is reduced.

Description

Technical Field

[0001] The present invention belongs to the field of electric power market, and specifically relates to a user demand response cost evaluation method, device, equipment and storage medium. Background Art

[0002] As an important flexible load resource, the residential load will not be greatly affected by adjusting its electricity consumption behavior, so the cost of residential load participating in demand response is relatively low. The key to formulating demand response electricity prices or incentive mechanisms for residential user groups lies in evaluating their demand response costs. Residential users have various types of electrical equipment, and their electricity utility is closely related to the electricity consumption environment. The residential demand response cost needs to consider the impact of multiple factors such as the user's flexible load adjustment type, electricity consumption time period, and outside temperature. In addition, the willingness of residential users to participate in demand response is also related to the factors of each user themselves, and a detailed survey of users is needed to more accurately evaluate the demand response cost of residential users.

[0003] At present, the research on the participation of integrated energy systems in the electricity market is mainly focused on integrated energy optimization control based on demand response, resulting in the following problems in the participation of residential loads in the demand-side response of the power grid: first, different types of residential loads have different power characteristics, and the residential loads themselves lack power regulation means to participate in responding to the power regulation instructions on the demand side of the power grid; secondly, different ambient temperatures will also have an impact on residential loads. Based on the above two reasons, residents' participation in the demand-side response of the power grid will affect the normal production order of the loads, resulting in unclear costs of power regulation. Summary of the invention

[0004] In order to solve the problem of unclear cost caused by the above-mentioned power regulation, the present invention provides a user demand response cost evaluation method, device, equipment and storage medium.

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

[0006] Firstly, a user demand response cost evaluation method is provided, the method comprising:

[0007] Obtaining the interaction willingness and interaction ratio of the sample user group to participate in demand response, and determining the membership set of the user interaction willingness according to the interaction willingness and interaction ratio;

[0008] Establishing a comprehensive membership function of user interaction willingness under different temperatures and different electricity prices according to the membership set, and adjusting the comprehensive membership function according to electricity consumption time;

[0009] According to the adjusted comprehensive membership function, the marginal utility function of the load that can be cut and the marginal utility function of the load that can be shifted of the user's electricity consumption are respectively constructed;

[0010] The demand response cost corresponding to the change in power consumption is determined respectively according to the marginal utility function of the curtailable load and the marginal utility function of the shiftable load, and then the total cost of the user's demand response is determined.

[0011] Optionally, determining a membership set according to the interaction willingness and the interaction ratio includes:

[0012] Dividing the interaction willingness and interaction ratio into a plurality of different levels, and determining the distribution of the interaction willingness and interaction ratio in each level;

[0013] The membership function of the interaction ratio is determined by fuzzy statistics, and then the membership set of the interaction willingness is determined according to the membership function of the interaction ratio and the distribution of the interaction willingness and the interaction ratio.

[0014] Optionally, establishing a comprehensive membership function under different temperatures and different electricity prices according to the membership set includes:

[0015] Establishing first membership functions at different temperatures and second membership functions at different electricity prices respectively;

[0016] Based on the first membership function and the second membership function, a comprehensive membership function is determined according to a preset weight vector for temperature and electricity price.

[0017] Optionally, the adjusting the comprehensive membership function according to the electricity usage time includes:

[0018] Divide electricity consumption time into multiple time periods and determine the user's preference for electricity consumption in each time period;

[0019] Constructing a third membership function of the preference degree, and then determining the kernel of the preference degree fuzzy set according to the third membership function;

[0020] According to the kernel of the preference degree fuzzy set, the adjustment ratio of the user's interaction amount is determined by defuzzification through the centroid method, and then the comprehensive membership function is adjusted according to the adjustment ratio.

[0021] Optionally, the step of constructing the marginal utility function of the user's electricity consumption of the reducible load and the marginal utility function of the shiftable load according to the adjusted comprehensive membership function includes:

[0022] Determine the user's comprehensive electricity consumption according to the adjusted comprehensive membership function;

[0023] Determine the marginal utility function of the load that can be cut based on the comprehensive power consumption, and then determine the transferred power consumption of the load that can be transferred out based on the comprehensive power consumption and the proportion of each interaction willingness level;

[0024] The marginal utility function of the shiftable load is determined based on the comprehensive power consumption and the transferred power consumption.

[0025] Optionally, determining the demand response cost corresponding to changing the power consumption according to the marginal utility function of the curtailable load and the marginal utility function of the shiftable load respectively includes:

[0026] Determine, according to the marginal utility function of the reducible load, the demand response cost corresponding to the reducible load when the user's electricity consumption changes;

[0027] The demand response cost corresponding to the shiftable load is determined according to the shiftable load marginal utility function when the user's electricity consumption changes.

[0028] Optionally, determining the total cost of user demand response includes:

[0029] The sum of the demand response cost corresponding to the curtailable load and the demand response cost corresponding to the shiftable load is determined as the total cost of the user's demand response.

[0030] Secondly, a user demand response cost evaluation device is also provided, the device comprising:

[0031] An acquisition module, used to acquire the interaction willingness and interaction ratio of the sample user group to participate in the demand response, and determine the membership set of the user interaction willingness according to the interaction willingness and interaction ratio;

[0032] A construction module is used to establish a comprehensive membership function of user interaction willingness under different temperatures and different electricity prices according to the membership set, and adjust the comprehensive membership function according to the electricity consumption time; and construct a marginal utility function of the user's electricity consumption that can be reduced and a marginal utility function of the user's electricity consumption that can be shifted according to the adjusted comprehensive membership function;

[0033] The determination module is used to determine the demand response cost corresponding to the change in power consumption according to the marginal utility function of the curtailable load and the marginal utility function of the shiftable load, and then determine the total cost of the user's demand response.

[0034] In addition, a computer-readable storage medium is provided, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned user demand response cost evaluation method is implemented.

[0035] Finally, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the above-mentioned user demand response cost evaluation method is implemented when the processor executes the program.

[0036] The user demand response cost evaluation method provided by the present invention has the following beneficial effects:

[0037] By combining the user's willingness and proportion of interaction in demand response, and taking into account the impact of multiple factors such as different temperatures, different electricity prices, and different electricity consumption times on user electricity consumption, the electricity consumption utility of various loads is evaluated based on the user's own willingness to use electricity, the outside temperature, and the influence of electricity consumption time, which can more accurately determine the user's participation in demand response. Then, based on the user's participation in demand response, the marginal utility function of the load that can be cut and the load that can be shifted is constructed through the fuzzy algorithm, and the total cost of the user's participation in demand response is determined. This calculation method is simple in principle, reliable and efficient, and highly practical, and is suitable for the demand response cost of residential users under different electricity consumption environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiment of the present invention and its design scheme, the following briefly introduces the drawings required for this embodiment. The drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0039] Figure 1 This is a flow chart of a user demand response cost evaluation method provided in accordance with Example 1 of the present invention.

[0040] Figure 2 This is a flow chart of another user demand response cost evaluation method provided according to Example 2 of the present invention.

[0041] Figure 3 The present invention is a block diagram of a user demand response cost evaluation device provided according to an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to enable those skilled in the art to better understand the technical solution of the present invention and implement it, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the scope of protection of the present invention.

[0043] The technical solutions provided by various embodiments of the present invention are described in detail below in conjunction with the accompanying drawings.

[0044] Example 1

[0045] First, the present invention provides a method for evaluating user demand response costs, specifically: Figure 1 As shown, the following steps are included:

[0046] S101. Obtain the interaction willingness and interaction ratio of the sample user group to participate in demand response, and determine the membership set of the user interaction willingness according to the interaction willingness and interaction ratio.

[0047] In this step, the interaction willingness and interaction ratio can be divided into multiple different levels, and the distribution of interaction willingness and interaction ratio in each level can be determined; the membership function of the interaction ratio can be determined by fuzzy statistics, and then the membership set of interaction willingness can be determined based on the membership function of the interaction ratio and the distribution of interaction willingness and interaction ratio.

[0048] For example, the interaction willingness is divided into five levels: low, lower, medium, higher, and high. The fuzzy sets are SL, L, M, H, and SH, respectively, denoted by U X ={SL,L,M,H,SH}.

[0049] The load interaction ratio is divided into the intervals [0, 0.05], (0.05, 0.15], ..., (0.85, 0.95], (0.95, 1], denoted as A0, A1, ..., A 10 ,A={A0,A1,…,A 10}, through questionnaire survey, the distribution of interaction willingness and interaction ratio is counted, and the membership function of fuzzy set is calculated by fuzzy statistics method. The interaction ratio is A i The number of value samples is N i , where the number of users at each willingness level is N i,X* , X * ∈U X , then the set A i The membership function can be calculated as:

[0050]

[0051] Then take the set A i The fuzzy set of interaction willingness of the domain is expressed as:

[0052]

[0053] User interaction willingness is X * ∈U X When , the load interaction is:

[0054]

[0055] Among them, φ(A i ) is the set A i The middle value of the corresponding interval.

[0056] S102: establishing a comprehensive membership function of user interaction willingness under different temperatures and different electricity prices according to the membership set, and adjusting the comprehensive membership function according to electricity usage time.

[0057] Specifically, a first membership function at different temperatures and a second membership function at different electricity prices are respectively established; based on the first membership function and the second membership function, a comprehensive membership function is determined according to a preset weight vector for temperature and electricity price.

[0058] In one embodiment, the first membership function and the second membership function are first determined according to the temperature and the electricity price, respectively.

[0059] For example, the outside temperature is divided into M temperature segments, denoted as Θ = {T1, T2, ... T M}, and according to the membership function of the set Ai, the first membership function corresponding to the fuzzy set of interaction willingness at different external temperatures is obtained as follows:

[0060]

[0061] in, They are the degrees of membership under different interaction intentions in the corresponding temperature ranges.

[0062] For another example, the electricity price adjustment ratio is divided into N intervals, denoted as P = {p1, p2, ... p N}, and according to the set A i The membership function of the second membership function corresponding to the fuzzy set of interaction willingness under different electricity prices is obtained as follows:

[0063]

[0064] in, is the membership degree under different interaction willingness in the corresponding electricity price range, U * Indicates different levels of willingness to interact.

[0065] In another embodiment, the comprehensive membership function is determined according to a preset weight vector for temperature and electricity price.

[0066] For example, assuming that the user's air conditioning load is at an outside temperature T m and electricity price p n When the weight vector D of the weight distribution of price and temperature is (d, 1-d), the user's interaction willingness fuzzy set and its membership degree

[0067]

[0068] in, The comprehensive membership when considering electricity price and temperature is calculated as follows:

[0069]

[0070] Among them, a * and b * (*∈{SL,L,M,H,SH}) represents the degree of interaction willingness at different temperatures and electricity prices.

[0071] In another embodiment, the electricity usage time is further divided into multiple time periods to determine the user's preference for electricity usage in each time period; a third membership function of the preference degree is constructed, and then the kernel of the preference degree fuzzy set is determined based on the third membership function; based on the kernel of the preference degree fuzzy set, defuzzification is performed through the centroid method to determine the user's interaction adjustment ratio, and then the comprehensive membership function is adjusted according to the adjustment ratio.

[0072] For example, according to the degree of interaction preference for each time period, the preference degree is divided into three levels: "disgust, neutral, preference", denoted as V * ={NP,N,P}. Set the membership function of the preference degree to a triangle, as follows:

[0073]

[0074] in, is the kernel V∈V* of fuzzy sets with different preference levels, σ V is the preference range parameter, where σ NP =σ N =σ P =0.2.

[0075] Obtain the degree of preference of users participating in interaction in each period respectively, and obtain the degree of interaction preference of aggregated user groups in different periods. In a certain period, the proportions of different preferences of users participating in interaction are γ NP , γ N , γ P , then γ NP +γ N +γ P =1. Using the centroid method for defuzzification, the adjustment ratio of user interaction is

[0076] γ=0.2(γ P -γ NP ).

[0077] S103. Constructing the marginal utility function of the user's electricity consumption for the load that can be reduced and the marginal utility function of the load that can be shifted respectively according to the adjusted comprehensive membership function.

[0078] Specifically, the user's comprehensive electricity consumption can be determined according to the adjusted comprehensive membership function; the marginal utility function of the reducible load can be determined based on the comprehensive electricity consumption, and then the transferred electricity consumption of the shiftable load can be determined according to the comprehensive electricity consumption and the proportion of each interaction willingness level; the marginal utility function of the shiftable load can be determined according to the comprehensive electricity consumption and the transferred electricity consumption.

[0079] For example, assuming that the user's electricity price is p0, the predicted power consumption of a certain type of load is Q p0 , when the outside temperature is T and the electricity price is adjusted to p, the proportions of each interaction willingness level are V SL 、V L 、V M 、V H 、V SH , then the user's electricity consumption at this time is:

[0080]

[0081] Among them, V X* is the proportion of each level of interaction willingness, Y X* is the load interaction amount;

[0082] The marginal utility of this type of load is:

[0083] U R,MU (Q) = p.

[0084] Assume that when the electricity price is p0, the predicted power consumption of this type of load is Q p0 When the electricity price rises from p0 to p, the proportions of each interaction willingness level are V SL 、V L 、V M 、V H 、V SH , then the power consumption transferred out by this type of load is

[0085]

[0086] The power consumption can be calculated as Q p0 -Q z The marginal utility when is p-p0, that is

[0087] U S,MU (Q p0 -Q z )=p-p0.

[0089] S104. Determine the demand response cost corresponding to the change in power consumption according to the marginal utility function of the curtailable load and the marginal utility function of the shiftable load, and then determine the total cost of the user's demand response.

[0090] Specifically, the demand response cost corresponding to the curtailable load is determined according to the marginal utility function of the curtailable load when the user's electricity consumption changes; the demand response cost corresponding to the shiftable load is determined according to the marginal utility function of the shiftable load when the user's electricity consumption changes. The sum of the demand response cost corresponding to the curtailable load and the demand response cost corresponding to the shiftable load is determined as the total cost of the user's demand response.

[0091] For example, the corresponding electricity consumption at different rising values ​​of electricity prices is obtained through multiple evaluations, and the marginal utility U of load reduction and load shifting is obtained respectively. R,MU (Q), US, MU (Q). Assume that after the electricity price changes, the load power consumption can be reduced from Q R Change to Q r ;Translable load from Q S Change to Q s , then the demand response cost corresponding to the reduction of electricity consumption by the load that can be cut and the load that can be shifted is calculated using marginal utility:

[0092]

[0093] At this time, the demand response cost of the residential user group is

[0094] C=C R +C S .

[0095] The above method combines the user's willingness to participate in demand response and the proportion of interaction, and comprehensively considers the impact of multiple factors such as different temperatures, different electricity prices and different electricity consumption times on the user's electricity consumption. In this way, based on the user's own willingness to use electricity, the outside temperature, and the influence of the electricity consumption period, the electricity consumption utility of various loads is evaluated, which can more accurately determine the user's participation in demand response. Then, based on the user's participation in demand response, the marginal utility function of the load that can be cut and the load that can be shifted is constructed through the fuzzy algorithm, and then the total cost of the user's participation in demand response is determined. This calculation method is simple in principle, reliable and efficient, and has strong practicality. It is suitable for the demand response cost of residential users under different electricity consumption environments, and can effectively help the integrated energy system participate in market competition and reduce its own operating costs.

[0096] Example 2

[0097] The present invention also provides another possible implementation method of the user demand response cost evaluation method, specifically as follows Figure 2 As shown:

[0098] 1) Through questionnaire surveys, evaluate users' willingness to participate in interaction, set fuzzy sets, calculate their corresponding membership functions, and establish membership sets of interaction willingness;

[0099] 2) Considering the impact of outside temperature on interaction willingness, establish the interaction willingness affiliation under different outside temperature conditions;

[0100] 3) Considering the impact of electricity prices on interaction willingness, establish the degree of interaction willingness under different electricity price conditions;

[0101] 4) According to the influence weights of different types of loads on the outside temperature and electricity price, a weighted comprehensive analysis is performed to obtain the degree of interaction willingness of residential users;

[0102] 5) Consider the impact of electricity consumption time on interaction willingness and modify the user's interaction willingness;

[0103] 6) Establish marginal utility function of load that can be reduced;

[0104] 7) Establish a translatable marginal utility function;

[0105] 8) Evaluate the demand response costs for residential user groups.

[0106] In order to verify the feasibility and correctness of the present invention, the following examples are given:

[0107] In this step 1), through questionnaire survey, evaluate the user's willingness to participate in interaction, set fuzzy sets, calculate the corresponding membership functions, and establish the membership set of interaction willingness. The effective number of people participating in the survey is 2858. The questionnaire survey obtained the fuzzy statistics of interaction willingness level as shown in Table 1, the survey data on the relationship between electricity price increase and air conditioner interaction willingness as shown in Table 2, the survey data on the relationship between electricity price increase and electric water heater interaction willingness as shown in Table 3, the survey data on the relationship between electricity price increase and washing machine, induction cooker, rice cooker, microwave oven interaction willingness as shown in Table 4, the impact of interaction time on interaction willingness as shown in Table 5, the impact of outdoor temperature on air conditioning load interaction willingness as shown in Table 6, and the weight relationship between air conditioning load electricity price and temperature as shown in Table 7:

[0108]

[0109] Table 1

[0110]

[0111] Table 2

[0112]

[0113] Table 3

[0114]

[0115] Table 4

[0116]

[0117] Table 5

[0118]

[0119] Table 6

[0120]

[0121] Table 7 The fuzzy set representation of interaction willingness calculated according to Table 1 is:

[0122]

[0123] Compared with other loads, the use of air conditioning load is more affected by the outside temperature. Calculate the marginal utility of air conditioning load according to steps 2) to 5).

[0124] According to step 2), the interactive willingness fuzzy set and its membership degree at different outside temperatures are obtained using the data in Table 6. According to step 3), the interactive willingness fuzzy set and its membership degree of air conditioning load at different electricity prices are obtained using the data in Table 2. According to step 4), the interactive willingness fuzzy set and its membership degree of air conditioning load considering outside temperature and electricity price are obtained using the data in Table 7. Finally, according to step 5), the interactive time period is corrected to obtain the air conditioning load electricity utility function.

[0125] For portable loads such as microwave ovens, induction cookers, rice cookers, and washing machines, it is assumed that the interactive period is 12:00-13:00, and the original electricity price is the normal residential electricity price of 0.5583 yuan / kWh. At this time, the user's electricity consumption is 147.17 kWh. According to the survey data in Table 4, the corresponding load when the electricity price increases by 5%, 20%, 40%, 60%, and 80% can be calculated using step 7). The marginal utility function during the interactive period is obtained by fitting:

[0126] U MU (Q) = 9.89 × 10 9 Q -5.5743 .

[0127] In the calculation of electricity utility of residential users, the loads that can be shifted include microwave ovens, induction cookers, rice cookers, and washing machines; air conditioners and water heaters are considered to be loads that can be reduced during the interactive period; refrigerators are uncontrollable loads. In addition, this article assumes that the loads that do not participate in the interaction account for 20% of other loads, the loads that can be shifted account for 50%, and the loads that can be reduced account for 30%.

[0128] The utility function and the interactive characteristics contained in the utility function are analyzed in the two time periods of 12:00-12:15 and 22:00-22:15, and the detailed power consumption data of various loads are shown in Tables 8 and 9. At 12:00-12:15 and 22:00-22:15, the outdoor temperature is 34.7℃ and 31.2℃ respectively, and the electricity price is 0.5583 yuan / kWh and 0.3583 yuan / kWh respectively.

[0129]

[0130] Table 8

[0131]

[0132]

[0133] Table 9

[0134] In the two periods of 12:00-12:15 and 22:00-22:15, although the electricity prices are quite different, 0.5583 yuan / kWh and 0.3583 yuan / kWh respectively, the amount of electricity that can be shifted depends mainly on the price difference between the shifting periods, and the range of its marginal utility value will not change significantly due to the difference in electricity prices. Its marginal utility functions are

[0135]

[0136] The marginal utility function of the load that can be reduced is as follows:

[0137]

[0138] Secondly, the present invention also provides a user demand response cost evaluation device, such as Figure 3 As shown, including:

[0139] The acquisition module 301 is used to obtain the interaction willingness and interaction ratio of the sample user group to participate in the demand response, and determine the membership set of the user interaction willingness according to the interaction willingness and interaction ratio.

[0140] Construction module 302 is used to establish a comprehensive membership function of user interaction willingness under different temperatures and different electricity prices based on the membership set, and adjust the comprehensive membership function according to the electricity consumption time; according to the adjusted comprehensive membership function, the marginal utility function of the user's electricity consumption that can be reduced and the marginal utility function of the user's electricity consumption that can be shifted are respectively constructed.

[0141] The determination module 303 is used to determine the demand response cost corresponding to the change in power consumption according to the marginal utility function of the curtailable load and the marginal utility function of the shiftable load, and then determine the total cost of the user's demand response.

[0142] The present invention also provides a computer-readable storage medium, which stores a computer program, which can be used to execute the above Figure 1 The steps of the user demand response cost assessment method are provided.

[0143] The present invention also provides a computer device. At the hardware level, the computer device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory. Of course, it may also include hardware required for other services. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 1 The steps of the user demand response cost assessment method are provided.

[0144] It will be appreciated by those skilled in the art 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.

[0145] The present invention is described with reference to flowcharts and / or block diagrams of methods, apparatus (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 a 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.

[0146] 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.

[0147] 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 in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0148] It should be noted that the above specific implementation methods can enable those skilled in the art to more fully understand the invention, but do not limit the invention in any way. Therefore, although the invention has been described in detail in this specification, those skilled in the art should understand that the invention can still be modified or replaced by equivalents; and all technical solutions and improvements that do not deviate from the spirit and scope of the invention are included in the protection scope of the patent for the invention. Any figure mark in the claims should not be regarded as limiting the claims involved.

Claims

1. A user demand response cost evaluation method, characterized in that: The method comprises: Obtaining the interaction willingness and interaction ratio of the sample user group to participate in demand response, and determining the membership set of the user interaction willingness according to the interaction willingness and interaction ratio; Establishing a comprehensive membership function of user interaction willingness under different temperatures and different electricity prices according to the membership set, and adjusting the comprehensive membership function according to electricity consumption time; According to the adjusted comprehensive membership function, the marginal utility function of the load that can be cut and the marginal utility function of the load that can be shifted of the user's electricity consumption are respectively constructed; The demand response cost corresponding to the change in power consumption is determined respectively according to the marginal utility function of the curtailable load and the marginal utility function of the shiftable load, and then the total cost of the user's demand response is determined.

2. A user demand response cost evaluation method according to claim 1, characterized in that: The membership set for determining the user's interaction willingness according to the interaction willingness and interaction ratio includes: Dividing the interaction willingness and interaction ratio into a plurality of different levels, and determining the distribution of the interaction willingness and interaction ratio in each level; The membership function of the interaction ratio is determined by fuzzy statistics, and then the membership set of the interaction willingness is determined according to the membership function of the interaction ratio and the distribution of the interaction willingness and the interaction ratio.

3. A user demand response cost evaluation method according to claim 1, characterized in that: The comprehensive membership function of user interaction willingness under different temperatures and different electricity prices is established according to the membership set, including: Establishing first membership functions at different temperatures and second membership functions at different electricity prices respectively; Based on the first membership function and the second membership function, a comprehensive membership function is determined according to a preset weight vector for temperature and electricity price.

4. A user demand response cost evaluation method according to claim 1, characterized in that: The adjusting the comprehensive membership function according to the electricity usage time includes: Divide electricity consumption time into multiple time periods and determine the user's preference for electricity consumption in each time period; Constructing a third membership function of the preference degree, and then determining the kernel of the preference degree fuzzy set according to the third membership function; According to the kernel of the preference degree fuzzy set, the adjustment ratio of the user's interaction amount is determined by defuzzification through the centroid method, and then the comprehensive membership function is adjusted according to the adjustment ratio.

5. A user demand response cost evaluation method according to claim 1, characterized in that: The method of constructing the marginal utility function of the user's electricity consumption of the load that can be reduced and the marginal utility function of the load that can be shifted according to the adjusted comprehensive membership function includes: Determine the user's comprehensive electricity consumption according to the adjusted comprehensive membership function; Determine the marginal utility function of the load that can be cut based on the comprehensive power consumption, and then determine the transferred power consumption of the load that can be transferred out based on the comprehensive power consumption and the proportion of each interaction willingness level; The marginal utility function of the shiftable load is determined based on the comprehensive power consumption and the transferred power consumption.

6. A user demand response cost evaluation method according to claim 1, characterized in that: Determining the demand response cost corresponding to changing the power consumption according to the marginal utility function of the curtailable load and the marginal utility function of the shiftable load respectively includes: Determine, according to the marginal utility function of the reducible load, the demand response cost corresponding to the reducible load when the user's electricity consumption changes; The demand response cost corresponding to the shiftable load is determined according to the shiftable load marginal utility function when the user's electricity consumption changes.

7. A user demand response cost evaluation method according to claim 6, characterized in that: The total cost of determining the user demand response includes: The sum of the demand response cost corresponding to the curtailable load and the demand response cost corresponding to the shiftable load is determined as the total cost of the user's demand response.

8. A user demand response cost evaluation device, characterized in that: The device comprises: An acquisition module, used to acquire the interaction willingness and interaction ratio of the sample user group to participate in the demand response, and determine the membership set of the user interaction willingness according to the interaction willingness and interaction ratio; A construction module is used to establish a comprehensive membership function of user interaction willingness under different temperatures and different electricity prices according to the membership set, and adjust the comprehensive membership function according to the electricity consumption time; and construct a marginal utility function of the user's electricity consumption that can be reduced and a marginal utility function of the user's electricity consumption that can be shifted according to the adjusted comprehensive membership function; The determination module is used to determine the demand response cost corresponding to the change in power consumption according to the marginal utility function of the curtailable load and the marginal utility function of the shiftable load, and then determine the total cost of the user's demand response.

9. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

10. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the method according to any one of claims 1 to 7 when executing the program.

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