Method, system and readable medium for predicting electric boiler electric energy replacement load

Abstract

The present invention belongs to the technical field of power grid load forecasting and relates to a method, system, and readable medium for forecasting load replacement by electric boilers. The method comprises the following steps: generating a steam tonnage frequency distribution function and a thermal effect frequency distribution function based on the steam tonnage and thermal efficiency of coal-fired or oil-fired boilers, respectively; generating a steam tonnage cloud model and a thermal effect cloud model based on the steam tonnage frequency distribution function and the thermal effect frequency distribution function, and generating qualitative language for steam tonnage and qualitative language for thermal effect; converting the qualitative language for steam tonnage and thermal effect into qualitative language for the probability of electric boiler replacement; converting the qualitative language for the probability of electric boiler replacement into a quantitative value for the probability of electric boiler replacement; and, based on the quantitative value for the probability of electric boiler replacement, predicting the power load that would result from the replacement of a coal-fired or oil-fired boiler with an electric boiler in a time series. The method can accurately define the numerical values of steam tonnage and thermal efficiency, resolving the problem of different definition methods in different regions.

Description

Technical Field

[0001] The present invention relates to a method, system and readable medium for predicting electric boiler electric energy replacement load, and belongs to the technical field of power grid load prediction. Background Art

[0002] Electric energy substitution can replace scattered coal burning and fuel consumption in the terminal energy consumption link and reduce energy intensity, which not only improves the economic benefits of energy utilization, but also reduces the emission of pollutants such as smoke, sulfur dioxide, nitrogen oxides, and improves the living environment.

[0003] Currently, electric boiler electricity substitution is in its early stages of development and lacks historical data accumulation. It is difficult to predict the electric energy substitution load in each area of the distribution network using a method based on the load density development law, just like the spatial load prediction of the distribution network.

[0004] The principle for replacing coal- or oil-fired boilers with electric boilers is to first replace those with smaller steam capacity and lower thermal efficiency, and then gradually replace those with larger steam capacity and higher thermal efficiency. However, it is difficult to define steam capacity and thermal efficiency with precise numerical values. Different regions use different definitions based on local conditions, resulting in considerable ambiguity. Summary of the Invention

[0005] In response to the above problems, the purpose of the present invention is to provide a method, system and readable medium for predicting electric boiler electric energy replacement load, which can accurately define the values of steam tonnage and thermal efficiency and solve the problem of different definition methods in different regions.

[0006] To achieve the above-mentioned objectives, the present invention proposes the following technical solutions: a method for predicting electric boiler electric energy replacement load, comprising the following steps: generating a steam tonnage frequency distribution function and a thermal effect frequency distribution function according to the steam tonnage and thermal efficiency of a coal-fired or oil-fired boiler, respectively; generating a steam tonnage cloud model and a thermal effect cloud model according to the steam tonnage frequency distribution function and the thermal effect frequency distribution function, and generating qualitative language of steam tonnage and qualitative language of thermal effect; converting the qualitative language of steam tonnage and qualitative language of thermal effect into qualitative language of electric boiler replacement probability; converting the qualitative language of electric boiler replacement probability into a quantitative value of electric boiler replacement probability; and predicting the power load of a coal-fired or oil-fired boiler replaced by an electric boiler according to a time series based on the quantitative value of the electric boiler replacement probability.

[0007] Furthermore, the method for generating the qualitative language of steam tonnage and the qualitative language of thermal effect is: taking the peak values of the steam tonnage frequency distribution function and the thermal effect frequency distribution function as the expected values of the cloud model to generate the steam tonnage cloud model and the thermal effect cloud model; calculating the digital characteristics of each section of the steam tonnage cloud model and the thermal effect cloud model; and generating the qualitative language of the steam tonnage and the qualitative language of the thermal effect of each coal-fired or oil-fired boiler based on the digital characteristics of the steam tonnage cloud model and the thermal effect cloud model.

[0008] Furthermore, the digital features include expectation, entropy and super entropy, and the expectation, entropy and super entropy are obtained through a reverse cloud algorithm.

[0009] Furthermore, the expectation E x The calculation formula is:

[0010]

[0011] The entropy E n The calculation formula is:

[0012]

[0013] The super entropy H e The calculation formula is:

[0014] Wherein, S is the variance; the calculation formula of the variance is:

[0015]

[0016] Where n is the total number of coal-fired or oil-fired boilers, x i represents the i-th sample value, which in the present invention refers to the steam tonnage or thermal efficiency of the i-th coal-fired or oil-fired boiler.

[0017] Furthermore, the method of converting the qualitative language of the steam tonnage and the qualitative language of the thermal effect into the qualitative language of the probability of electric boiler replacement is: if the qualitative language of the steam tonnage and the qualitative language of the thermal effect are high, the qualitative language of the probability of electric boiler replacement is low; if the qualitative language of the steam tonnage and the qualitative language of the thermal effect are relatively high, the qualitative language of the probability of electric boiler replacement is relatively low; if the qualitative language of the steam tonnage and the qualitative language of the thermal effect are average, the qualitative language of the probability of electric boiler replacement is average; if the qualitative language of the steam tonnage and the qualitative language of the thermal effect are relatively low, the qualitative language of the probability of electric boiler replacement is relatively high; if the qualitative language of the steam tonnage and the qualitative language of the thermal effect are low, the qualitative language of the probability of electric boiler replacement is high.

[0018] Furthermore, the calculation formula for the probability of replacing the coal-fired or oil-fired boiler with an electric boiler based on steam tonnage is:

[0019] ρ bz,j =C T (x z,j )

[0020] Among them, ρ bz,j is the probability of electric boiler replacement based on steam tonnage, C T (x z,j ) is the steam tons input to the electric boiler x z,j Calculated membership degree;

[0021] Among them, E n =normrnd(E n ,H e ), generating E n is the expected value, H e is a normal random number with standard deviation;

[0022] The calculation formula for the probability of replacing the coal-fired or oil-fired boiler with an electric boiler based on the thermal effect is:

[0023] ρ br,j =C T (x r,j )

[0024] Among them, ρ br,j is the probability of electric boiler replacement based on thermal effect, C T (x r,j ) is the thermal effect x input to the electric boiler r,j Calculated membership degree;

[0025] Among them, E n ′ =normrnd(E n ,H e ), generating E n is the expected value, H e is a normal random number with a standard deviation.

[0026] Furthermore, the calculation formula for the probability that the j-th coal-fired or oil-fired boiler is replaced by an electric boiler is as follows:

[0027] ρ b,j =ρ br,j ×ρ bz,j

[0028] If the probability of the coal-fired or oil-fired boiler being replaced by the electric boiler is greater than a preset value, the coal-fired or oil-fired boiler is replaced by the electric boiler; otherwise, the coal-fired or oil-fired boiler is not replaced by the electric boiler.

[0029] Furthermore, the number of coal-fired or oil-fired boilers replaced in year k is predicted, and the calculation formula for the power load replaced by electric boilers in year k is:

[0030]

[0031] Where β is a fixed coefficient, is the steaming tons of the jth electric boiler; n b is the total number of coal-fired or oil-fired boilers replaced by electric boilers predicted in year k.

[0032] The present invention also discloses an electric boiler electric energy replacement load prediction system, comprising: a frequency distribution function generation module, used to generate a steam tonnage frequency distribution function and a thermal effect frequency distribution function according to the steam tonnage and thermal efficiency of a coal-fired or oil-fired boiler, respectively; a cloud model calculation module, used to generate a steam tonnage cloud model and a thermal effect cloud model according to the steam tonnage frequency distribution function and the thermal effect frequency distribution function, and to generate a qualitative language of steam tonnage and a qualitative language of thermal effect; an electric boiler replacement module, used to convert the qualitative language of steam tonnage and the qualitative language of thermal effect into a qualitative language of electric boiler replacement probability; a qualitative-quantitative conversion module, used to convert the qualitative language of electric boiler replacement probability into a quantitative numerical value of electric boiler replacement probability; and an electric load generation module, used to predict the electric load of a coal-fired or oil-fired boiler replaced by an electric boiler according to a time series based on the quantitative numerical value of the electric boiler replacement probability.

[0033] The present invention also discloses a computer-readable storage medium having a computer program stored thereon. The computer program is executed by a processor to implement any of the above-mentioned methods for predicting electric boiler electric energy replacement load.

[0034] The load forecasting of electric boiler electricity substitution is different from the traditional method in the following ways:

[0035] 1) Electric boiler power replacement, a new type of load, is in its early stages of development and lacks historical data accumulation, so traditional historical data-based analysis and forecasting methods cannot be used;

[0036] 2) This new type of load emphasizes the use of electricity to replace coal and oil, and has little correlation with land use. Therefore, existing spatial load forecasting methods based on land use characteristics, load density methods, and land use simulation methods are no longer applicable.

[0037] 3) During the promotion process, new loads are affected by various random factors such as population parameters, economic parameters, technical level and government support. The load forecast of electric energy replacing new loads must take the influence of random factors into account.

[0038] The present invention innovatively utilizes cloud theory, which has a strong ability to handle the fuzziness and randomness of things, to predict the electric energy replacement load of electric boilers in time series. It can accurately define the values of steam tonnage and thermal efficiency, and solve the problem of different definition methods in different regions. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a flow chart of a method for predicting electric boiler electric energy replacement load in one embodiment of the present invention;

[0040] Figure 2 1 is a frequency distribution function diagram of steam tonnage in one embodiment of the present invention;

[0041] Figure 31 is a graph of the frequency distribution function of thermal effect in one embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be described in detail through specific embodiments. However, it should be understood that the specific embodiments are provided only for a better understanding of the present invention and should not be construed as limiting the present invention. In the description of the present invention, it should be understood that the terms used are for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0043] In order to solve the problems existing in the prior art, such as the difficulty in defining steam tonnage and thermal efficiency with precise numerical values, different regions have different definition methods according to local actual conditions, and there is a great deal of ambiguity. The present invention proposes a method, system, and readable medium for predicting electric boiler electric energy replacement load. Because cloud theory can better characterize the characteristics of fuzzy things, the present invention adopts cloud theory to achieve "softening" of steam tonnage and thermal efficiency under different qualitative language conditions, and based on cloud uncertainty reasoning, predicts the probability of coal-fired or oil-fired boilers being replaced by electric boilers, and then provides a time-series prediction of electric boiler spatial load. The present invention can accurately define the numerical values of steam tonnage and thermal efficiency, solving the problem of different definition methods in different regions. The following is a detailed description of the present invention through examples in conjunction with the accompanying drawings.

[0044] Example 1:

[0045] This embodiment discloses a method for predicting electric boiler electric energy replacement load. Figure 1 As shown, the following steps are included:

[0046] S1 generates steam tonnage frequency distribution function and thermal effect frequency distribution function according to the steam tonnage and thermal efficiency of coal-fired or oil-fired boilers.

[0047] Taking Y City as an example, the data of coal-fired or oil-fired boilers in Y City in 2020 are used. There are 2517 coal-fired or oil-fired boilers with a total steam tonnage of 5526 tons. The steam tonnage range is [1,70]. The step size is set to 1. The data within the corresponding step size is recorded to obtain the steam tonnage frequency distribution function. The steam tonnage frequency distribution function is as follows: Figure 2 shown.

[0048] The thermal efficiency range of coal-fired or oil-fired boilers in Y City in 2020 is [63%, 94%], the step size is set to 1%, and the data within the corresponding step size is recorded to obtain the thermal effect frequency distribution function. The thermal effect frequency distribution function is as follows: Figure 3 shown.

[0049] S2 generates a steam tonnage cloud model and a thermal effect cloud model according to the steam tonnage frequency distribution function and the thermal effect frequency distribution function, and generates a qualitative language of steam tonnage and a qualitative language of thermal effect.

[0050] The method for generating qualitative language for steam tonnage and thermal effect is:

[0051] S2.1 Take the steam tonnage frequency distribution function as the expected value of the cloud model, such as Figure 2 As shown in Figure 1, the steam tonnage frequency distribution function selects peak values of 4, 10, 20, 39, and 50 tons of steam as the expected values of the cloud model. A total of five steam tonnage cloud models are generated. The qualitative language, numerical characteristics, and steam tonnage range of each of the five steam tonnage cloud models are calculated. The qualitative language, numerical characteristics, and steam tonnage range of each steam tonnage cloud model are shown in Table 1.

[0052] Table 1 Numerical characteristics of each cloud model in terms of steam tonnage

[0053] Qualitative language interval expect entropy Super Entropy high [39,70] 50 8.15 0.027 Higher [20,50] 39 7.51 0.038 generally [10,39] 20 6.28 0.024 Lower [4,20] 10 4.92 0.034 Low [0.1,10] 4 3.21 0.03

[0054] The thermal effect frequency distribution function is used as the expected value of the cloud model, such as Figure 3 As shown in Figure 2, the thermal effect frequency distribution function selected peak values of 69%, 76%, 80%, 87%, and 91% as the expected values of the cloud model. A total of five thermal effect cloud models were generated. The qualitative language, numerical characteristics, and thermal effect interval of each thermal effect cloud model were obtained through calculation. The qualitative language, numerical characteristics, and thermal effect interval of each thermal effect cloud model are shown in Table 2.

[0055] Table 2 Numerical characteristics of thermal efficiency cloud models

[0056] Qualitative language interval expect entropy Super Entropy high [87％,94％] 91％ 2.14％ 0.15％ Higher [80％,91％] 87％ 2.17％ 0.13％ generally [76％,87％] 80％ 3.14％ 0.15％ Lower [69％,80％] 76％ 3.17％ 0.24％ Low [63％,76％] 69％ 2.04％ 0.16％

[0057] S2.2 Calculate the numerical characteristics of each section of the steam tonnage cloud model and the thermal effect cloud model;

[0058] The numerical characteristics include expectation, entropy and super entropy. The steam tonnage interval in the above table reflects the continuity between cloud models. Expectation, entropy and super entropy are obtained through the reverse cloud algorithm and calculated separately in the steam tonnage interval of each cloud model.

[0059] The reverse cloud algorithm that does not require membership information is a mapping from quantitative to qualitative, which expresses a certain amount of data in qualitative language. The calculation formulas for expectation, entropy, and super entropy in Table 1 are as follows:

[0060] Expected E x The calculation formula is:

[0061]

[0062] Entropy E n The calculation formula is:

[0063]

[0064] Super Entropy H e The calculation formula is:

[0065] Where S is the variance; the calculation formula for the variance is:

[0066]

[0067] Where n is the total number of coal-fired or oil-fired boilers, x i represents the i-th sample value, which in the present invention refers to the steam tonnage or thermal efficiency of the i-th coal-fired or oil-fired boiler.

[0068] S2.3 Generate qualitative language of steam tonnage and thermal effect of each coal-fired or oil-fired boiler based on the numerical characteristics and expectations, entropy and super entropy of the steam tonnage cloud model and thermal effect cloud model.

[0069] S3 converts the qualitative language of steam tonnage and thermal effect into the qualitative language of electric boiler substitution probability.

[0070] The method for converting the qualitative language of steam tonnage and thermal effect into the qualitative language of electric boiler replacement probability is:

[0071] If the qualitative language of steam tonnage and thermal effect is high, the qualitative language of the probability of electric boiler substitution is low;

[0072] If the qualitative language of steam tonnage and thermal effect is high, the qualitative language of the probability of electric boiler substitution is low;

[0073] If the qualitative language of steam tonnage and thermal effect is general, then the qualitative language of the probability of electric boiler substitution is general;

[0074] If the qualitative language of steam tonnage and thermal effect is low, the qualitative language of the probability of electric boiler substitution is high;

[0075] If the qualitative language of steam tonnage and thermal effect is low, the qualitative language of the probability of electric boiler substitution is high.

[0076] The numerical characteristics of the probability cloud model of coal-fired or oil-fired boilers being replaced by electric boilers are as follows:

[0077] Table 3 Digital characteristics of standard cloud model

[0078] Qualitative language expect entropy Super Entropy Low 90 5 0.05 Lower 70 5 0.05 generally 50 5 0.05 Higher 30 5 0.05 high 10 5 0.05

[0079] S4 converts the qualitative language of the electric boiler replacement probability into a quantitative value of the electric boiler replacement probability.

[0080] The calculation formula for the probability of replacing coal-fired or oil-fired boilers with electric boilers based on steam tonnage is:

[0081] ρ bz,j =C T (x z,j ) (1)

[0082] Among them, ρ bz,j is the probability of electric boiler replacement based on steam tonnage, C T (x z,j ) is the steam tons input to the electric boiler x z,j Calculated membership degree;

[0083]

[0084] Among them, E n ′ =normrnd(E n ,H e ), generating E n is the expected value, H e is a normal random number with standard deviation;

[0085] The calculation formula for the probability of replacing coal-fired or oil-fired boilers with electric boilers based on thermal effects is:

[0086] ρ br,j =C T (x r,j ) (3)

[0087] Among them, ρ br,j is the probability of electric boiler replacement based on thermal effect, C T (x r,j ) is the heat effect x input to the electric boiler r,j Calculated membership degree;

[0088]

[0089] Among them, E n ′ =normrnd(E n ,H e ), generating E n is the expected value, H e is a normal random number with a standard deviation.

[0090] Combining equations (1) and (3), we can obtain the following formula for calculating the probability that the j-th coal-fired or oil-fired boiler will be replaced by an electric boiler:

[0091] ρ b,j =ρ br,j ×ρ bz,j (5)

[0092] According to formula (5), n is the total number of oil-fired boilers in the region. If the probability of coal-fired or oil-fired boiler j being replaced by an electric boiler is greater than the preset value Then the coal-fired or oil-fired boiler is replaced by an electric boiler, otherwise the coal-fired or oil-fired boiler is not replaced by an electric boiler.

[0093] S5 predicts the power load when coal-fired or oil-fired boilers are replaced by electric boilers according to the quantitative value of the replacement probability of electric boilers.

[0094] According to cloud uncertainty reasoning, the probability threshold for coal-fired or oil-fired boilers to be replaced in year k is greater than the probability of replacement calculated by steam tons / expected thermal efficiency in year k+1. The threshold for coal-fired or oil-fired boilers to be replaced by electric boilers in year k is given below:

[0095]

[0096] Where, ρ br,l (k+1),ρ bz,m (k+1) are the steam tons of electric boiler in the k+1th year, and the thermal efficiency is the expected value x in that year. z,l ,x z,m Calculate the probability.

[0097] After predicting the number of coal-fired or oil-fired boilers replaced in year k, the calculation formula for the power load replaced by electric boilers in year k is:

[0098]

[0099] Among them, β is a fixed coefficient. According to the national standard document "Industrial Steam Boiler Parameter Series", when the boiler industry converts coal-fired or oil-fired boilers to electric boilers, one steam ton is equal to 0.7 megawatts, and this value is equal to 0.7. is the steaming tons of the jth electric boiler; n b is the total number of coal-fired or oil-fired boilers replaced by electric boilers predicted in year k.

[0100] The method in this embodiment is used below to verify and analyze some of the forecast results for 2021 in Y City, and to predict the electric energy replacement load in a certain area from 2021 to 2025.

[0101] The calculation results of the probability of some coal-fired or oil-fired boilers being replaced by electric boilers are shown in Table 4.

[0102] Table 4 Probability of coal-fired or oil-fired boilers being replaced by electric boilers

[0103]

[0104] Table 5 shows the thresholds for coal-fired or oil-fired boilers to be replaced by electric boilers from 2021 to 2025, as determined by government policies.

[0105] Table 5 Thresholds for achieving electric energy substitution

[0106]

[0107] The prediction results and verification of electric energy substitution from 2021 to 2025 are as shown in Table 6.

[0108] Table 6 Electricity replacement load unit MW for each community in a certain region from 2021 to 2025

[0109]

[0110]

[0111] As shown in the table above, as coal- or oil-fired boilers are gradually replaced with electric boilers and electric heating is adopted for industrial sites I1-I4, the annual electricity replacement load increases linearly, reaching a total of 32.01 MW by 2025. Furthermore, the error between the predicted 2021 electric boiler replacement load and the actual load is within 5%. This demonstrates that by establishing a cloud model for these influencing factors and using cloud-based uncertainty reasoning, this embodiment can accurately predict new loads such as electric boilers.

[0112] Example 2

[0113] Based on the same inventive concept, the present invention also discloses an electric boiler electric energy replacement load forecasting system, comprising:

[0114] Frequency distribution function generation module, used to generate steam tonnage frequency distribution function and thermal effect frequency distribution function according to steam tonnage and thermal efficiency of coal-fired or oil-fired boilers;

[0115] A cloud model calculation module is used to generate a steam tonnage cloud model and a thermal effect cloud model according to the steam tonnage frequency distribution function and the thermal effect frequency distribution function, and to generate a qualitative language of steam tonnage and a qualitative language of thermal effect;

[0116] Electric boiler replacement module, used to convert the qualitative language of steam tonnage and thermal effect into the qualitative language of electric boiler replacement probability;

[0117] A qualitative and quantitative conversion module is used to convert the qualitative language of the electric boiler replacement probability into a quantitative value of the electric boiler replacement probability;

[0118] The power load generation module is used to predict the power load when the coal-fired or oil-fired boiler is replaced by the electric boiler according to the quantitative value of the electric boiler replacement probability in a time series manner.

[0119] Example 2

[0120] Based on the same inventive concept, this embodiment discloses a computer-readable storage medium having a computer program stored thereon. The computer program is executed by a processor to implement any of the above-mentioned methods for predicting electric energy replacement load of an electric boiler.

[0121] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to 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 steps in the process. 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.

[0122] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work 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 The function specified in one or more boxes.

[0123] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0124] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the specific embodiments of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be included within the scope of protection of the claims of the present invention. The above content is only a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or replacements within the technical scope disclosed in the present application, which should be included within the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for predicting electric boiler electric energy replacement load, characterized in that: The following steps are involved: According to the steam tonnage and thermal efficiency of coal-fired or oil-fired boilers, the steam tonnage frequency distribution function and thermal effect frequency distribution function are generated respectively; Generate steam tonnage cloud model and thermal effect cloud model according to steam tonnage frequency distribution function and thermal effect frequency distribution function, and generate qualitative language of steam tonnage and qualitative language of thermal effect; Convert the qualitative language of steam tonnage and the qualitative language of thermal effect into the qualitative language of electric boiler replacement probability; Converting the qualitative language of the electric boiler replacement probability into a quantitative value of the electric boiler replacement probability; Based on the quantitative value of the electric boiler replacement probability, predict the power load when the coal-fired or oil-fired boiler is replaced by the electric boiler in a time series manner; The method for generating the qualitative language of steam tonnage and the qualitative language of thermal effect is: The peak values of steam tonnage frequency distribution function and thermal effect frequency distribution function are used as expected values of cloud models to generate steam tonnage cloud model and thermal effect cloud model. Calculating the numerical characteristics of each section of the steam tonnage cloud model and the thermal effect cloud model; The qualitative language of the steam tonnage and the qualitative language of the thermal effect of each coal-fired or oil-fired boiler are generated according to the digital characteristics of the steam tonnage cloud model and the thermal effect cloud model.

2. The electric boiler electric energy replacement load prediction method according to claim 1, characterized in that: The digital features include expectation, entropy and super entropy, which are obtained through a reverse cloud algorithm.

3. The electric boiler electric energy replacement load prediction method according to claim 2, characterized in that: The expectations The calculation formula is: The entropy The calculation formula is: The super entropy The calculation formula is: ; Wherein, S is the variance; the calculation formula of the variance is: Where n is the total number of coal-fired or oil-fired boilers, x i It represents the steam tons or thermal efficiency of the i-th coal-fired or oil-fired boiler.

4. The electric boiler electric energy replacement load prediction method according to any one of claims 1 to 3, characterized in that: The method for converting the qualitative language of steam tonnage and thermal effect into the qualitative language of electric boiler replacement probability is as follows: If the qualitative language of steam tonnage and the qualitative language of thermal effect are high, the qualitative language of the probability of electric boiler substitution is low; if the qualitative language of steam tonnage and the qualitative language of thermal effect are relatively high, the qualitative language of the probability of electric boiler substitution is relatively low; if the qualitative language of steam tonnage and the qualitative language of thermal effect are average, the qualitative language of the probability of electric boiler substitution is average; if the qualitative language of steam tonnage and the qualitative language of thermal effect are relatively low, the qualitative language of the probability of electric boiler substitution is relatively high; if the qualitative language of steam tonnage and the qualitative language of thermal effect are low, the qualitative language of the probability of electric boiler substitution is high.

5. The electric boiler electric energy replacement load prediction method according to any one of claims 1 to 3, characterized in that: The calculation formula for the probability of replacing coal-fired or oil-fired boilers with electric boilers based on steam tonnage is: in, is the probability of electric boiler replacement based on steam tonnage, is the steam tons input to the electric boiler Calculated membership degree; in, ,generate is the expected value, is a normal random number with standard deviation; The calculation formula for the probability of replacing the coal-fired or oil-fired boiler with an electric boiler based on the thermal effect is: in, is the probability of electric boiler replacement based on thermal effect, The thermal effect of the input electric boiler Calculated membership degree; in, ,generate is the expected value, is a normal random number with a standard deviation.

6. The electric boiler electric energy replacement load prediction method according to claim 5, characterized in that: No. The formula for calculating the probability of a coal-fired or oil-fired boiler being replaced by an electric boiler is as follows: If the probability of the coal-fired or oil-fired boiler being replaced by the electric boiler is greater than a preset value, the coal-fired or oil-fired boiler is replaced by the electric boiler; otherwise, the coal-fired or oil-fired boiler is not replaced by the electric boiler.

7. The electric boiler electric energy replacement load prediction method according to claim 6, characterized in that: The number of coal-fired or oil-fired boilers replaced in year k is predicted, and the calculation formula for the power load replaced by electric boilers in year k is: in, is a fixed coefficient, It is j Steaming tons of electric boilers; is the total number of coal-fired or oil-fired boilers replaced by electric boilers predicted in year k.

8. An electric boiler electric energy replacement load forecasting system, characterized in that: include: Frequency distribution function generation module, used to generate steam tonnage frequency distribution function and thermal effect frequency distribution function according to steam tonnage and thermal efficiency of coal-fired or oil-fired boilers; A cloud model calculation module is used to generate a steam tonnage cloud model and a thermal effect cloud model according to the steam tonnage frequency distribution function and the thermal effect frequency distribution function, and to generate a qualitative language of steam tonnage and a qualitative language of thermal effect; An electric boiler replacement module, used for converting the qualitative language of steam tonnage and the qualitative language of thermal effect into the qualitative language of electric boiler replacement probability; A qualitative and quantitative conversion module, used to convert the qualitative language of the electric boiler replacement probability into a quantitative value of the electric boiler replacement probability; An electric load generation module is used to predict the electric load when the coal-fired or oil-fired boiler is replaced by the electric boiler according to the quantitative value of the electric boiler replacement probability in a time series manner; The method for generating the qualitative language of steam tonnage and the qualitative language of thermal effect is: The peak values of steam tonnage frequency distribution function and thermal effect frequency distribution function are used as expected values of cloud models to generate steam tonnage cloud model and thermal effect cloud model. Calculating the numerical characteristics of each section of the steam tonnage cloud model and the thermal effect cloud model; The qualitative language of the steam tonnage and the qualitative language of the thermal effect of each coal-fired or oil-fired boiler are generated according to the digital characteristics of the steam tonnage cloud model and the thermal effect cloud model.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the electric boiler electric energy replacement load prediction method according to any one of claims 1 to 7.

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