Method and system for evaluating regulation and control flexibility of high-energy-consumption industrial user

Abstract

The invention discloses a high-energy-consumption industrial user regulation and control flexibility evaluation method and system, and the method comprises the steps: obtaining an index, used for evaluating the regulation and control flexibility, of a high-energy-consumption industrial user; wherein the indexes comprise response capacity, response rate, response duration, response precision and response willingness; determining objective weight and subjective weight of each index: based on the objective weight and the subjective weight, performing comprehensive weighting on each index to obtain the weight of each index; and based on the weight of each index, comprehensively scoring the regulation and control flexibility of each high-energy-consumption industrial user. According to the method, parameters such as user response capacity, response duration, response rate, response precision and response intention are adopted, a subjective and objective combined parameter weighting method and a TOPSIS comprehensive evaluation method are adopted to quantitatively evaluate the response capability of the high-energy-consumption industrial load, and the regulation and control flexibility of the high-energy-consumption industrial user can be evaluated more finely.

Description

Technical Field

[0001] The present invention belongs to the field of regulation flexibility evaluation of high-energy-consuming industrial users participating in demand response, and in particular relates to a regulation flexibility evaluation method and system for high-energy-consuming industrial users. Background Art

[0002] The flexibility of industrial load regulation refers to the ability of industrial users to adjust their electricity consumption behavior according to the needs of power system operation. This ability is crucial to the power system because it can provide necessary adjustments when there is an imbalance between supply and demand, helping to maintain the stability and reliability of the power grid. As the penetration rate of renewable energy increases, the fluctuations and uncertainties in supply and demand faced by the power system are also increasing, so the role of demand-side flexibility in the power system is becoming increasingly prominent.

[0003] Patent document CN116739306B discloses a heat pump load flexibility quantification method, system and device, in which the flexibility supply capacity of cluster heat pumps mainly considers the upward and downward flexibility supply of heat pump load aggregators, which is related to factors such as charging and discharging reference power and energy. However, this flexibility assessment method is closely related to the physical modeling of the load itself and is not applicable to other industrial loads.

[0004] Patent document CN115438969A discloses a method for evaluating the adjustable potential of high-energy industrial loads and demand response scheduling, in which the load adjustment rate and load fluctuation rate indicators are used to evaluate the load adjustable potential. However, this method only considers the power size of the load, and does not consider factors such as the speed and accuracy of the load in the actual response process, making it difficult to comprehensively evaluate the flexibility of industrial load regulation.

[0005] Patent document CN116384798A discloses a method for evaluating the peak-shaving potential of industrial users. It uses the improved entropy weight method - CRITIC to evaluate the peak-shaving potential of industrial users. However, this is only a method to determine weights from an objective level, which relies on the degree of variation of the data itself, lacks expert experience and necessary subjectivity, and the final comprehensive scoring method uses a simple data weighted calculation, which cannot fully explore the internal connection of the original data.

[0006] As large electricity users, high-energy-consuming industrial users have great demand response potential. At present, there is an obvious problem in the interaction between power grids and high-energy-consuming industrial users: lack of accurate assessment of load controllability. This situation makes it difficult for power grids to accurately match the actual operating status of loads when planning energy use, power management and load control strategies for high-energy-consuming industrial users, making these strategies poor in terms of economy and feasibility. Summary of the invention

[0007] The purpose of the present invention is to provide a method and system for evaluating the regulatory flexibility of high-energy-consuming industrial users, which can more finely evaluate the regulatory flexibility of high-energy-consuming industrial users.

[0008] In order to achieve the above object, the solution of the present invention is:

[0009] A method for evaluating the flexibility of regulation of high energy consumption industrial users, comprising:

[0010] Obtaining indicators used by high-energy-consuming industrial users to evaluate control flexibility; wherein the indicators include response capacity, response rate, response duration, response accuracy, and response willingness;

[0011] Determine the objective and subjective weights of each indicator:

[0012] Based on the objective weight and subjective weight, each indicator is comprehensively weighted to obtain the weight of each indicator;

[0013] Based on the weights of the various indicators, a comprehensive score is given to the regulatory flexibility of each high-energy-consuming industrial user.

[0014] Among them, obtaining the response capacity of high-energy-consuming industrial users includes:

[0015] Obtain the baseline load of electricity consumption of industrial users participating in demand response each time during the statistical period, and obtain the actual average load of industrial users during the response period;

[0016] Based on the power baseline load and the actual average load, the demand response capacity of industrial users is calculated.

[0017]

[0018] Among them, P base,i is the baseline load of electricity for the i-th participation in demand response (KW), P actual,i is the actual average load of the user in the i-th response period, N R is the number of actual participation in demand response during the statistical period, N D is the typical number of days taken when calculating the baseline load; P pre,j is the historical load in a typical day, P response It is the average response capacity of industrial users during the historical statistical period.

[0019] Among them, obtaining the response rate of high-energy-consuming industrial users includes calculating according to the following formula:

[0020]

[0021] Where V r Represents the response rate of industrial load, NR is the number of actual participation in demand response during the statistical period; t goal,i It represents the time it takes for the industrial load power to climb to the target power during the i-th adjustment; t start,i It represents the time when the industrial load starts to respond to the instruction during the i-th adjustment, P goal,i represents the target power of industrial load participating in the i-th response, P init,i Represents the power of industrial load before participating in the i-th response.

[0022] Among them, obtaining the response duration of high-energy-consuming industrial users includes:

[0023] Get the time t when the industrial load response ends off and the time t when the industrial load just begins to meet the response requirements on ;

[0024] according to

[0025] T d =t off -t on

[0026] Calculate the response duration T d .

[0027] Among them, obtaining the response accuracy of high-energy-consuming industrial users includes calculating according to the following formula:

[0028]

[0029] Among them, ε represents the response accuracy, N R is the number of actual participation in demand response during the statistical period; t goal,i It represents the time it takes for the industrial load power to climb to the target power during the i-th adjustment, t end,i represents the time when the industrial load participates in the i-th regulation and ends, P goal,i represents the target power of industrial load participating in the i-th regulation, P i (t) represents the power value at time t during the i-th adjustment process.

[0030] Among them, obtaining the response willingness of high-energy-consuming industrial users includes calculating according to the following formula:

[0031]

[0032] Where W represents the user's willingness to respond after receiving an invitation in the historical demand response process, and N T is the number of historical demand response invitations, k i represents the participation of the industrial user in the i-th historical demand response. i =1, otherwise k i=0;P max,i is the maximum demand power predicted to occur during the response period before the user participates in the i-th demand response; P i It is the declared response quantity before the user participates in the i-th demand response, representing the response decision made by the industrial user after comprehensively considering its own production conditions.

[0033] Among them, the objective weight of each indicator is obtained, including:

[0034] Get all indicators of each evaluation object;

[0035] All indicators of each evaluation object are positively and standardized to obtain standardized values;

[0036] Based on the standardized value, the proportion of each indicator under each evaluation object is obtained;

[0037] Based on the weights, the information entropy of each indicator is obtained;

[0038] Based on the information entropy, the entropy weight of each indicator, that is, the objective weight of each indicator, is obtained.

[0039] Among them, the subjective weight of each indicator is obtained, including:

[0040] According to the importance of each indicator, obtain the indicator order relationship;

[0041] Determine the weight relationship between adjacent indicators in the order relationship;

[0042] According to the weight relationship, the subjective weight of each indicator is obtained.

[0043] Among them, based on the weight of each indicator, the regulation flexibility of each high-energy-consuming industrial user is comprehensively scored, including:

[0044] The weights of each indicator are positively processed and standardized to obtain standardized values;

[0045] Obtain the distance between each indicator and the maximum value of each evaluation object;

[0046] The distances are normalized to obtain scores for each evaluation object.

[0047] A high energy consumption industrial user regulation flexibility evaluation system, comprising:

[0048] An indicator acquisition module is configured to acquire indicators used by high-energy-consuming industrial users to evaluate control flexibility; wherein the indicators include response capacity, response rate, response duration, response accuracy, and response willingness;

[0049] An objective weight determination module, configured to determine the objective weight of each indicator;

[0050] The subjective weight determination module is configured to determine the subjective weight of each indicator:

[0051] A weight determination module is configured to comprehensively weight each indicator based on the objective weight and the subjective weight to obtain the weight of each indicator; and

[0052] The comprehensive scoring module is configured to comprehensively score the control flexibility of each high-energy-consuming industrial user based on the weights of the various indicators.

[0053] After adopting the above scheme, the present invention is based on the parameters such as user response capacity, response duration, response rate, response accuracy, response willingness, etc. that have an impact on the evaluation of the flexibility of load regulation of high-energy-consuming industrial users. It comprehensively uses the entropy weight method, the ordinal relationship analysis method and the TOPSIS method, and adopts a parameter weighting method combining subjective and objective factors and the TOPSIS comprehensive evaluation method to quantitatively evaluate the response capacity of high-energy-consuming industrial loads. It can more finely evaluate the regulation flexibility of high-energy-consuming industrial users, and can provide valuable reference for the power network when conducting comprehensive demand management, helping to more accurately evaluate and utilize the flexibility of industrial loads. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0055] The present invention provides a method for evaluating the control flexibility of high-energy-consuming industrial users, comprising:

[0056] Obtaining indicators used by high-energy-consuming industrial users to evaluate control flexibility; wherein the indicators include response capacity, response rate, response duration, response accuracy, and response willingness;

[0057] Determine the objective and subjective weights of each indicator:

[0058] Based on the objective weight and subjective weight, each indicator is comprehensively weighted to obtain the weight of each indicator;

[0059] Based on the weights of the various indicators, a comprehensive score is given to the regulatory flexibility of each high-energy-consuming industrial user.

[0060] Among them, obtaining the response capacity of high-energy-consuming industrial users includes:

[0061] Obtain the baseline load of electricity consumption of industrial users participating in demand response each time during the statistical period, and obtain the actual average load of industrial users during the response period;

[0062] Based on the power baseline load and the actual average load, the demand response capacity of industrial users is calculated.

[0063]

[0064] Among them, P base,i is the baseline load of electricity for the i-th participation in demand response (KW), P actual,i is the actual average load of the user in the i-th response period, N R is the number of actual participation in demand response during the statistical period, N D is the typical number of days taken when calculating the baseline load; P pre,j is the historical load in a typical day, P response It is the average response capacity of industrial users during the historical statistical period.

[0065] Among them, obtaining the response rate of high-energy-consuming industrial users includes calculating according to the following formula:

[0066]

[0067] Where V r Represents the response rate of industrial load, t goal,i It represents the time it takes for the industrial load power to climb to the target power during the i-th adjustment; t start,i It represents the time when the industrial load starts to respond to the instruction during the i-th adjustment, P goal,i represents the target power of industrial load participating in the i-th response, P init,i Represents the power of industrial load before participating in the i-th response.

[0068] Among them, obtaining the response duration of high-energy-consuming industrial users includes:

[0069] Get the time t when the industrial load response ends off and the time t when the industrial load just begins to meet the response requirements on ;

[0070] according to

[0071] T d =t off -t on

[0072] Calculate the response duration T d .

[0073] Among them, obtaining the response accuracy of high-energy-consuming industrial users includes calculating according to the following formula:

[0074]

[0075] Among them, ε represents the response accuracy, tgoal,i It represents the time it takes for the industrial load power to climb to the target power during the i-th adjustment. In practical applications, when the deviation is always less than 5%, it is considered that the industrial load power has climbed to the target power; t end,i represents the time when the industrial load participates in the i-th regulation and ends, P goal,i represents the target power of industrial load participating in the i-th regulation, P i (t) represents the power value at time t during the i-th adjustment process.

[0076] Among them, obtaining the response willingness of high-energy-consuming industrial users includes calculating according to the following formula:

[0077]

[0078] Where W represents the user's willingness to respond after receiving an invitation in the historical demand response process, and N T is the number of historical demand response invitations, k i represents the participation of the industrial user in the i-th historical demand response. i =1, otherwise k i =0;P max,i is the maximum demand power predicted to occur during the response period before the user participates in the i-th demand response; P i It is the declared response quantity before the user participates in the i-th demand response, representing the response decision made by the industrial user after comprehensively considering its own production conditions.

[0079] Among them, the objective weight of each indicator is obtained, including:

[0080] Get all indicators of each evaluation object;

[0081] All indicators of each evaluation object are positively and standardized to obtain standardized values;

[0082] Based on the standardized value, the proportion of each indicator under each evaluation object is obtained;

[0083] Based on the weights, the information entropy of each indicator is obtained;

[0084] Based on the information entropy, the entropy weight of each indicator, that is, the objective weight of each indicator, is obtained.

[0085] Among them, the subjective weight of each indicator is obtained, including:

[0086] According to the importance of each indicator, obtain the indicator order relationship;

[0087] Determine the weight relationship between adjacent indicators in the order relationship;

[0088] According to the weight relationship, the subjective weight of each indicator is obtained.

[0089] Among them, based on the weight of each indicator, the regulation flexibility of each high-energy-consuming industrial user is comprehensively scored, including:

[0090] The weights of each indicator are positively processed and standardized to obtain standardized values;

[0091] Obtain the distance between each indicator and the maximum value of each evaluation object;

[0092] The distances are normalized to obtain scores for each evaluation object.

[0093] As a preferred embodiment of the method for evaluating the flexibility of regulation of high energy-consuming industrial users of the present invention, the method comprises:

[0094] 1. After investigating the operating characteristics of high-energy-consuming industrial users (such as steel, cement, electrolytic aluminum, etc.) and their historical participation in grid demand response, five indicators are proposed to quantitatively evaluate their control flexibility: response capacity, response rate, response duration, response accuracy, and response willingness. The calculation method of each indicator is described in detail below:

[0095] (1) Response capacity: The response capacity calculation when industrial load participates in peak load regulation mainly involves the baseline load and actual load of industrial users. For industrial users participating in demand response, the determination of the baseline load is usually based on their historical electricity consumption data and specific rules. In the peak-shaving power demand response, when the demand response event (i.e., the event that requires peak load regulation) occurs on a working day, the historical load of the corresponding period of 5 days before the demand response date should be selected as the typical day for calculating the baseline load. When the event occurs on a non-working day, the three non-working days closest to the demand response date should be selected as typical days. According to the selected daily load data, the load average value of the event period is calculated, which is the baseline load of the user during the event period (this embodiment selects the working day load as the typical day for calculating the baseline load). The demand response capacity calculation formula for industrial users is:

[0096]

[0097] Among them, P base,i is the baseline load of electricity for the i-th participation in demand response (KW), P actual,i is the actual average load (KW) of the user in the i-th response period, N R is the number of actual participation in demand response during the statistical period, N D To calculate the number of typical days used for baseline load calculation, N is taken in this embodiment. D =5;P pre,jis the historical load in a typical day, P response It is the average response capacity of industrial users during the historical statistical period.

[0098] (2) Response rate: The response rate of industrial loads in the process of demand response can be defined as the power change per unit time, which represents the speed of response:

[0099]

[0100] Where V r Represents the response rate of industrial load, t goal,i It represents the time it takes for the industrial load power to climb to the target power during the i-th adjustment; t start,i It represents the time when the industrial load starts to respond to the instruction during the i-th adjustment, P goal,i represents the target power of industrial load participating in the i-th response, P init,i Represents the power of industrial load before participating in the i-th response.

[0101] (3) Response duration: refers to the maximum time that the state can be maintained after the regulation requirements are fully met.

[0102] T d =t off -t on

[0103] Where, T d represents the response duration, t off Indicates the time when industrial load response ends, t on Indicates the time when the industrial load just begins to meet the response requirements.

[0104] (4) Response accuracy: The industrial load response deviation can be used to characterize the error between the actual load control power and the target power during the historical response process:

[0105]

[0106] Among them, ε represents the response accuracy, t goal,i It represents the time it takes for the industrial load power to climb to the target power and the deviation is always less than 5% during the i-th adjustment, t end,i represents the time when the industrial load participates in the i-th regulation and ends, P goal,i represents the target power of industrial load participating in the i-th regulation, P i (t) represents the power value at time t during the i-th adjustment process.

[0107] (5) Response willingness: The response willingness of industrial users is mainly related to the number of historical responses and the capacity requested before the response date.

[0108]

[0109] Where: W represents the user's willingness to respond after receiving an invitation in the historical demand response process, N T is the number of historical demand response invitations, k i represents the participation of the industrial user in the i-th historical demand response. i =1, otherwise k i =0;P max,i is the maximum demand power predicted to occur during the response period before the user participates in the i-th demand response; P i It is the declared response quantity before the user participates in the i-th demand response, representing the response decision made by the industrial user after comprehensively considering its own production conditions.

[0110] 2. The entropy weight method determines the objective weight of each indicator:

[0111] (1) Data normalization and standardization: Assume that there are n evaluation objects and m evaluation indicators, which constitute an evaluation matrix X (as shown below), x ij Represents the j-th evaluation index value of the i-th evaluation object.

[0112]

[0113] First, the indicators are divided into very large indicators (the larger the value, the better) and very small indicators (the smaller the value, the better). The jth indicator is marked as X j ={x 1j ,x 2j, …x nj}, positive processing of very small indicators:

[0114] x i ' j =max(X j )-x ij

[0115] Then standardize each indicator, assuming that the standardized value is z ij , then the calculation formula is:

[0116]

[0117] (2) Calculate the proportion of each indicator in each evaluation object: Under the same evaluation indicator, calculate the proportion of each evaluation object value in the total value, and regard it as the probability used in the relative entropy calculation. The formula is as follows:

[0118]

[0119] (3) Information entropy calculation: For the jth evaluation index, the information entropy calculation formula is:

[0120]

[0121] (4) Information utility value and entropy weight calculation: Define the information utility value of the jth evaluation index as d j , the larger the value, the greater the amount of information it carries. Then the information utility value is normalized to obtain the entropy weight ω of each indicator. e,j :

[0122] d j =1-e j

[0123]

[0124] 3. Determine the subjective weight of each indicator by using the ordinal relationship analysis method:

[0125] (1) Determine the order relationship between evaluation indicators: Assuming there are m evaluation indicators in total, the decision maker sorts these indicators from high to low according to their own judgment, and obtains the order relationship of the indicators:

[0126] X 1 >X 2 >…>X m

[0127] (2) Determine the weights between adjacent indicators in the ordinal relationship: For two adjacent indicators X j With X j-1 , the weight between them is given by the decision maker as μ j and μ j-1 , then the weight ratio is:

[0128]

[0129] γ j The larger the X j-1 Relative to X j The greater the importance of γ j The value of can be found in the following table:

[0130] Table 1

[0131]

[0132] (3) Calculate the weight of each indicator:

[0133]

[0134] ω β-1 =ω β ×γ β (β=2,…,n-1,m)

[0135] From this, we can get the weight ω of the order relationship analysis method G1,j (j=1,2,…,m).

[0136] 4. The combined weighting method allocates subjective and objective comprehensive weights to each indicator. This embodiment adopts the multiplication combined weighting method to comprehensively weight the evaluation indicators:

[0137]

[0138] 5. Based on the weights of the above indicators, the TOPSIS method is used to comprehensively score the control flexibility of each high-energy-consuming industrial user:

[0139] (1) Data positive and normalization processing: This step is consistent with the processing method used in the previous entropy weight method to determine the indicator weights.

[0140] (2) Calculate the distance to the maximum value: Take n industrial users as evaluation objects and assume that there are m evaluation indicators, which constitute an evaluation matrix X, x ij It represents the jth evaluation index value of the i-th evaluation object. First, we need to calculate the maximum value Z of each index. + and the minimum value Z - , which is calculated as follows:

[0141]

[0142] (j=1,2,…,m)

[0143] in, and Indicates the maximum and minimum values ​​of the same indicator in each evaluation object.

[0144] Secondly, calculate the distance between the i-th evaluation object (i=1,2,…,n) and the maximum value Distance from minimum

[0145]

[0146] Among them, ω j It is the weight coefficient of each indicator calculated in the combined weighting method.

[0147] (3) Calculate the final score of each evaluation object and normalize it:

[0148]

[0149] The embodiment of the present invention also provides a high-energy-consuming industrial user control flexibility evaluation system, comprising:

[0150] An indicator acquisition module is configured to acquire indicators used by high-energy-consuming industrial users to evaluate control flexibility; wherein the indicators include response capacity, response rate, response duration, response accuracy, and response willingness;

[0151] An objective weight determination module, configured to determine the objective weight of each indicator;

[0152] The subjective weight determination module is configured to determine the subjective weight of each indicator:

[0153] A weight determination module is configured to comprehensively weight each indicator based on the objective weight and the subjective weight to obtain the weight of each indicator; and

[0154] The comprehensive scoring module is configured to comprehensively score the control flexibility of each high-energy-consuming industrial user based on the weights of the various indicators.

[0155] Among them, the indicator acquisition module obtains the response capacity of high-energy-consuming industrial users, including:

[0156] Obtain the baseline load of electricity consumption of industrial users participating in demand response each time during the statistical period, and obtain the actual average load of industrial users during the response period;

[0157] Based on the power baseline load and the actual average load, the demand response capacity of industrial users is calculated.

[0158]

[0159] Among them, P base,i is the baseline load of electricity for the i-th participation in demand response (KW), P actual,i is the actual average load of the user in the i-th response period, N R is the number of actual participation in demand response during the statistical period, N D is the typical number of days taken when calculating the baseline load; P pre,j is the historical load in a typical day, P response It is the average response capacity of industrial users during the historical statistical period.

[0160] Among them, the indicator acquisition module obtains the response rate of high-energy-consuming industrial users, including, according to the following formula:

[0161]

[0162] Where V r Represents the response rate of industrial load, t goal,i It represents the time it takes for the industrial load power to climb to the target power during the i-th adjustment; t start,i It represents the time when the industrial load starts to respond to the instruction during the i-th adjustment, Pgoal,i represents the target power of industrial load participating in the i-th response, P init,i Represents the power of industrial load before participating in the i-th response.

[0163] Among them, the indicator acquisition module obtains the response duration of high-energy-consuming industrial users, including:

[0164] Get the time t when the industrial load response ends off and the time t when the industrial load just begins to meet the response requirements on ;

[0165] according to

[0166] T d =t off -t on

[0167] Calculate the response duration T d .

[0168] Among them, the indicator acquisition module obtains the response accuracy of high-energy-consuming industrial users, including, according to the following formula:

[0169]

[0170] Among them, ε represents the response accuracy, t goal,i It represents the time it takes for the industrial load power to climb to the target power and the deviation is always less than 5% during the i-th adjustment, t end,i represents the time when the industrial load participates in the i-th regulation and ends, P goal,i represents the target power of industrial load participating in the i-th regulation, P i (t) represents the power value at time t during the i-th adjustment process.

[0171] Among them, the indicator acquisition module obtains the response willingness of high-energy-consuming industrial users, including, according to the following formula:

[0172]

[0173] Where W represents the user's willingness to respond after receiving an invitation in the historical demand response process, and N T is the number of historical demand response invitations, k i represents the participation of the industrial user in the i-th historical demand response. i =1, otherwise k i =0;P max,i is the maximum demand power predicted to occur during the response period before the user participates in the i-th demand response; P i It is the declared response quantity before the user participates in the i-th demand response, representing the response decision made by the industrial user after comprehensively considering its own production conditions.

[0174] Among them, the objective weight determination module determines the objective weight of each indicator, including:

[0175] Get all indicators of each evaluation object;

[0176] All indicators of each evaluation object are positively and standardized to obtain standardized values;

[0177] Based on the standardized value, the proportion of each indicator under each evaluation object is obtained;

[0178] Based on the weights, the information entropy of each indicator is obtained;

[0179] Based on the information entropy, the entropy weight of each indicator, that is, the objective weight of each indicator, is obtained.

[0180] Among them, the subjective weight determination module determines the subjective weight of each indicator, including:

[0181] According to the importance of each indicator, obtain the indicator order relationship;

[0182] Determine the weight relationship between adjacent indicators in the order relationship;

[0183] According to the weight relationship, the subjective weight of each indicator is obtained.

[0184] Among them, the comprehensive scoring module comprehensively scores the control flexibility of each high-energy-consuming industrial user based on the weight of each indicator, including:

[0185] The weights of each indicator are positively processed and standardized to obtain standardized values;

[0186] Obtain the distance between each indicator and the maximum value of each evaluation object;

[0187] The distances are normalized to obtain scores for each evaluation object.

[0188] An embodiment of the present invention further provides another computer device, including a processor and a memory configured to store a computer program that can be run on the processor; wherein, when the processor is configured to run the computer program, the method steps in the aforementioned embodiment are executed.

[0189] In practical applications, the processor includes a field programmable gate array (FPGA), and the processor may be a central processing unit (CPU) or a digital signal processor (DSP). It is understandable that for different devices, the electronic device used to implement the function of the processor may be other, and the embodiment of the present invention does not specifically limit it.

[0190] The above-mentioned memory can be a volatile memory (volatile memory), such as a random access memory (RAM); or a non-volatile memory (non-volatile memory), such as a read-only memory (ROM), a flash memory, a hard disk (HDD) or a solid-state drive (SSD); or a combination of the above-mentioned types of memory, and provide instructions and data to the processor.

[0191] In an exemplary embodiment, an embodiment of the present invention further provides a computer-readable storage medium for storing a computer program.

[0192] Optionally, the computer-readable storage medium can be applied to any one of the methods in the embodiments of the present invention, and the computer program enables the computer to execute the corresponding processes implemented by the processor in each method in the embodiments of the present invention. For the sake of brevity, they are not described here.

[0193] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0194] It should be understood that although this embodiment calculates the control flexibility scores of several high-energy-consuming industrial loads, this cannot be directly used as a reference for actual control priority, because the industrial load power consumption characteristics and response conditions in different regions are different. It is necessary to recalculate in combination with the actual load conditions to obtain the control flexibility of the local high-energy-consuming industrial loads, and then make subsequent control decisions based on this. The control flexibility calculation process of this embodiment is provided to make the present invention more thorough and complete, and to fully convey the scope of the present invention to technicians in this field.

[0195] Several high-energy-consuming industrial users in an industrial park are selected as examples, including electrolytic aluminum, steel, cement, and metal product processing loads. According to the data of these loads participating in the historical demand response process, combined with the calculation method of each response parameter in the present invention, their response capacity, response rate, response duration, response willingness, response accuracy and other data can be obtained, as shown in the following table:

[0196] Table 2

[0197]

[0198] The following steps were used to quantify their regulatory flexibility:

[0199] (1) The subjective weights were determined using the ordinal relationship analysis method (G1 method). Decision makers ranked the response capacity, response rate, response duration, response willingness, and response accuracy from high to low in terms of importance based on their own judgment. The ordinal relationship of the indicators was: response capacity, response duration, response rate, response accuracy, and response willingness. The weight ratios between two adjacent indicators were 1.4, 1.4, 1.2, and 1.2, respectively. Their weights were calculated using the ordinal relationship analysis method.

[0200] (2) Determine the objective weight through the entropy weight method.

[0201] (3) The subjective and objective comprehensive weights of these indicators are calculated using the multiplication integrated combined weighting method formula. The weight coefficients determined by the above method are shown in the following table:

[0202] Table 3

[0203]

[0204] (4) Based on the weights of each indicator obtained by the combined weighting method, the TOPSIS method is used to calculate the comprehensive score of the control flexibility of each load. The results are shown in the following table:

[0205] Table 4

[0206]

[0207] Based on the above analysis process and calculation results, it can be seen that under the load demand response background provided by this embodiment, the regulation flexibility of each high-energy-consuming industrial load is ranked as follows: steel users, electrolytic aluminum users, metal product processing users, and cement users. This can provide a certain reference basis for subsequent load regulation of the power grid.

[0208] 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 codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0209] 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.

[0210] 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 including 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.

[0211] 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 1The steps for the functions specified in one or more boxes.

[0212] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0213] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for evaluating the flexibility of regulation of high energy-consuming industrial users, characterized by: include, Obtaining indicators used by high-energy-consuming industrial users to evaluate control flexibility; wherein the indicators include response capacity, response rate, response duration, response accuracy, and response willingness; Determine the objective and subjective weights of each indicator: Based on the objective weight and subjective weight, each indicator is comprehensively weighted to obtain the weight of each indicator; Based on the weights of the various indicators, a comprehensive score is given to the regulatory flexibility of each high-energy-consuming industrial user.

2. The method according to claim 1, characterized in that: Obtain the response capacity of high energy consuming industrial users, include, Obtain the baseline load of electricity consumption of industrial users participating in demand response each time during the statistical period, and obtain the actual average load of industrial users during the response period; Based on the power baseline load and the actual average load, the demand response capacity of industrial users is calculated. Among them, P base，i is the baseline load of electricity for the i-th participation in demand response (KW), P actual，i is the actual average load of the user in the i-th response period, N R is the number of actual participation in demand response during the statistical period, N D is the typical number of days taken when calculating the baseline load; P pre，j is the historical load in a typical day, P response It is the average response capacity of industrial users during the historical statistical period.

3. The method according to claim 1, characterized in that: Obtain the response rate of high-energy-consuming industrial users, including, according to the following formula, Where Vr represents the response rate of industrial load, N R is the number of actual participation in demand response during the statistical period; t goal，i It represents the time it takes for the industrial load power to climb to the target power during the i-th adjustment; t start，i It represents the time when the industrial load starts to respond to the instruction during the i-th adjustment, P goal，i represents the target power of industrial load participating in the i-th response, P init，i Represents the power of industrial load before participating in the i-th response.

4. The method according to claim 1, characterized in that: Obtain response duration of high energy consuming industrial users, including, Get the time t when the industrial load response ends off and the time t when the industrial load just begins to meet the response requirements on ; according to T d =t off -t on Calculate the response duration T d .

5. The method according to claim 1, characterized in that: Obtaining the response accuracy of high-energy-consuming industrial users includes, according to the following formula, Among them, ε represents the response accuracy, N R is the number of actual participation in demand response during the statistical period; t goal，i It represents the time it takes for the industrial load power to climb to the target power during the i-th adjustment, t end，i represents the time when the industrial load participates in the i-th regulation and ends, P goal，i represents the target power of industrial load participating in the i-th regulation, P i (t) represents the power value at time t during the i-th adjustment process.

6. The method according to claim 1, characterized in that: Obtain the response willingness of high-energy-consuming industrial users, including, according to the following formula: Where W represents the user's willingness to respond after receiving an invitation in the historical demand response process, and N T is the number of historical demand response invitations, k i represents the participation of the industrial user in the i-th historical demand response. i =1, otherwise k i =0;P max，i It is the maximum demand power predicted to occur during the response period before the user participates in the i-th demand response; Pi is the declared response quantity before the user participates in the i-th demand response, which represents the response decision made by the industrial user after comprehensively considering its own production conditions.

7. The method according to claim 1, characterized in that: Obtain objective weights for each indicator, including, Get all indicators of each evaluation object; All indicators of each evaluation object are positively and standardized to obtain standardized values; Based on the standardized value, the proportion of each indicator under each evaluation object is obtained; Based on the weights, the information entropy of each indicator is obtained; Based on the information entropy, the entropy weight of each indicator, that is, the objective weight of each indicator, is obtained.

8. The method according to claim 1, characterized in that: Obtain the subjective weight of each indicator, including, According to the importance of each indicator, obtain the indicator order relationship; Determine the weight relationship between adjacent indicators in the order relationship; According to the weight relationship, the subjective weight of each indicator is obtained.

9. The method according to claim 1, characterized in that: Based on the weight of each indicator, the regulation flexibility of each high-energy-consuming industrial user is comprehensively scored, including: The weights of each indicator are positively processed and standardized to obtain standardized values; Obtain the distance between each indicator and the maximum value of each evaluation object; The distances are normalized to obtain scores for each evaluation object.

10. A high energy consumption industrial user control flexibility evaluation system, characterized by: include, An indicator acquisition module is configured to acquire indicators used by high-energy-consuming industrial users to evaluate control flexibility; wherein the indicators include response capacity, response rate, response duration, response accuracy, and response willingness; An objective weight determination module, configured to determine the objective weight of each indicator; The subjective weight determination module is configured to determine the subjective weight of each indicator: A weight determination module is configured to comprehensively weight each indicator based on the objective weight and the subjective weight to obtain the weight of each indicator; and The comprehensive scoring module is configured to comprehensively score the control flexibility of each high-energy-consuming industrial user based on the weights of the various indicators.

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