Investment limit measuring and calculating method and system for power grid fixed assets, and storage medium

Abstract

The invention discloses a power grid fixed asset investment limit calculation method and system and a storage medium, and relates to the technical field of power grid decision making. Historical electricity selling data and first historical power grid supply and demand data are acquired; adopting a correlation coefficient method to screen out second historical power grid supply and demand data from the first historical power grid supply and demand data; inputting the second historical power grid supply and demand data and the historical electricity selling data into a pre-constructed electricity selling quantity prediction model, and solving to obtain a current electricity selling quantity prediction value; and calculating the investment limit of the fixed assets of the power grid according to the current electricity sale quantity predicted value, the historical electricity sale data and the second historical power grid supply and demand data. By adopting the embodiment of the invention, the investment limit can be obtained by analyzing the main factors influencing the power grid fixed asset investment on the basis of the influence and effect of the power demand increase and the power price change, the optimization of investment management of a power grid enterprise is facilitated, the power grid investment and cost can be effectively controlled, and the power grid investment benefit is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid decision-making, and in particular to a method, system and storage medium for calculating investment limits of power grid fixed assets. Background Art

[0002] The electricity consumption structure has undergone profound changes. Emerging industries and future industries such as artificial intelligence and green electricity hydrogen production are "high-power-consuming" industries, and the total electricity demand of the whole society will continue to maintain rapid growth.

[0003] In the existing technology, investment limits are calculated by manually selecting certain fixed power grid supply and demand indicators of traditional industries. However, the current power supply and demand situation is facing major changes and challenges. The use of traditional methods for calculation will result in the calculated asset limits being inconsistent with actual development, resulting in the inability to achieve optimal resource planning and utilization of the power grid. Summary of the invention

[0004] The embodiments of the present invention provide a method, system and storage medium for calculating the investment limit of power grid fixed assets. The method can start from efficiency and benefit, based on the influence and effect of electricity demand growth and electricity price changes, and obtain the investment limit by analyzing the main factors affecting the investment in power grid fixed assets. This helps power grid enterprises optimize investment management, effectively control power grid investment and costs, and improve power grid investment efficiency.

[0005] In order to solve the above technical problems, an embodiment of the present invention provides a method for calculating the investment limit of power grid fixed assets, comprising:

[0006] Obtain historical electricity sales data and the first historical power grid supply and demand data;

[0007] Using the correlation coefficient method, the key influencing data of the historical power sales data is screened from the first historical power grid supply and demand data to obtain the key influencing data as the second historical power grid supply and demand data;

[0008] Inputting the second historical power grid supply and demand data and the historical power sales data into a pre-built power sales forecasting model to obtain a current power sales forecast value;

[0009] The current investment limit is reversely constrained by the current electricity sales forecast value, the historical electricity sales data and the second historical power grid supply and demand data, and the investment limit of the power grid fixed assets is calculated.

[0010] As an improvement of the above solution, the correlation coefficient method is used to screen the key influencing data of the historical power sales data from the first historical power grid supply and demand data as the second historical power grid supply and demand data, including:

[0011] According to the historical electricity sales data, a historical electricity sales change amount is obtained;

[0012] Using the Pearson correlation coefficient method, calculating the first correlation strength between the first historical power grid supply and demand data and the historical power sales change;

[0013] The first historical power grid supply and demand data whose first correlation strength is greater than a preset threshold is screened, and a significance check is performed on the screened data to obtain the second historical power grid supply and demand data.

[0014] As an improvement of the above solution, the second historical power grid supply and demand data and the historical power sales data are input into a pre-built power sales forecasting model to obtain a current power sales forecast value, including:

[0015] Inputting the second historical power grid supply and demand data and the historical power sales data into a pre-built power sales amount prediction model;

[0016] Calculating the historical growth rates of the second historical power grid supply and demand data and the historical power sales data;

[0017] Calculate the index weight value of the historical growth rate by using the entropy weight method;

[0018] According to the weight value of the indicator, weighted operation is performed on the historical growth rate to calculate the current electricity sales growth rate;

[0019] The current electricity sales forecast value is calculated based on the current electricity sales growth rate.

[0020] As an improvement of the above solution, the calculating of the historical growth rates of the second historical power grid supply and demand data and the historical power sales data includes:

[0021] Calculating a first change amount according to the second historical power grid supply and demand data;

[0022] Calculating a second change amount according to the historical electricity sales data;

[0023] The second historical power grid supply and demand data and the historical growth rate of the historical power sales data are obtained according to the first change amount and the second change amount.

[0024] As an improvement of the above solution, the calculation of the index weight value of the historical growth rate by the entropy weight method includes:

[0025] Constructing a data matrix; the elements of the data matrix are obtained according to the second historical power grid supply and demand data and the historical power sales data of each period;

[0026] Performing standardization processing on the data matrix to obtain a standardized data matrix;

[0027] According to the standardized data matrix, obtaining the contrast intensity of the element;

[0028] Calculating the second correlation strength of each element in the standardized data matrix, and obtaining the conflict of the element according to the second correlation strength;

[0029] The indicator weight value of the historical growth rate is calculated according to the comparison intensity and the conflict.

[0030] As an improvement of the above solution, obtaining the contrast intensity of the element according to the standardized data matrix includes:

[0031] pass Calculating the comparison strength of the jth indicator in the standardized data matrix; the indicator includes the second historical power grid supply and demand data and the historical power sales data;

[0032] Wherein, m is the number of cycles covered by the second historical power grid supply and demand data; x i ′ j is the data of the jth indicator in the ith period in the standardized data matrix; It is the data average of the jth indicator of all periods in the standardized data matrix.

[0033] As an improvement of the above solution, the calculation of the indicator weight value of the historical growth rate according to the comparison intensity and the conflict includes:

[0034] pass C j =σ j f j Calculate the indicator weight value of the historical growth rate;

[0035] Among them, σ j is the comparison strength of the jth indicator; f j is the conflict of the jth indicator; n is the total number of indicators.

[0036] As an improvement of the above scheme, the calculation of the current electricity sales forecast value according to the current electricity sales growth rate includes:

[0037] Obtaining the electricity sales value of the previous cycle from the second historical power grid supply and demand data;

[0038] The current electricity sales growth rate and the electricity sales value of the previous cycle are multiplied to obtain the current electricity sales forecast value.

[0039] As an improvement of the above solution, the current investment limit is reversely constrained by the current electricity sales forecast value, the historical electricity sales data and the second historical power grid supply and demand data to calculate the investment limit of power grid fixed assets, including:

[0040] According to the historical electricity sales data, a base period electricity sales volume is obtained;

[0041] Obtaining base period fixed assets from the second historical power grid supply and demand data;

[0042] Calculate the fixed assets per unit of electricity in the base period based on the base period electricity sales and base period fixed assets;

[0043] According to the preset maximum capital conversion rate and the preset transmission and distribution price pricing supervision constraints, the base period unit electricity fixed assets and the current electricity sales forecast value are used to reversely constrain the current investment limit to obtain the investment limit of the power grid fixed assets.

[0044] The embodiment of the present invention further provides a system for calculating the investment limit of fixed assets of a power grid, comprising:

[0045] A data acquisition module, used to acquire historical electricity sales data and first historical power grid supply and demand data;

[0046] A data screening module, configured to use a Pearson correlation coefficient method to screen the key influencing data of the historical power sales data from the first historical power grid supply and demand data to obtain the key influencing data as the second historical power grid supply and demand data;

[0047] A model prediction module, used for inputting the second historical power grid supply and demand data and the historical power sales data into a pre-built power sales forecasting model to solve and obtain a current power sales forecast value;

[0048] The investment limit calculation module is used to reversely constrain the current investment limit through the current electricity sales forecast value, the historical electricity sales data and the second historical power grid supply and demand data, and calculate the investment limit of the power grid fixed assets.

[0049] As an improvement of the above solution, the data screening module includes:

[0050] A historical electricity sales change calculation unit, used to obtain the historical electricity sales change according to the historical electricity sales data;

[0051] A first correlation strength calculation unit, configured to calculate a first correlation strength between the first historical power grid supply and demand data and the historical power sales change amount by using a Pearson correlation coefficient method;

[0052] The second historical power grid supply and demand data screening unit is used to screen the first historical power grid supply and demand data whose first correlation strength is greater than a preset threshold, and perform significance verification on the screened data to obtain the second historical power grid supply and demand data.

[0053] As an improvement of the above solution, the model prediction module includes:

[0054] A model data input unit, used to input the second historical power grid supply and demand data and the historical power sales data into a pre-built power sales amount prediction model;

[0055] A historical growth rate calculation unit, used to calculate the historical growth rates of the second historical power grid supply and demand data and the historical power sales data;

[0056] An indicator weight value calculation unit, used to calculate the indicator weight value of the historical growth rate by using an entropy weight method;

[0057] A current electricity sales growth rate calculation unit, configured to perform a weighted operation on the historical growth rate according to the indicator weight value to calculate the current electricity sales growth rate;

[0058] The current electricity sales forecast value calculation unit is used to calculate the current electricity sales forecast value according to the current electricity sales growth rate.

[0059] As an improvement of the above solution, the historical growth rate calculation unit is specifically used for:

[0060] Calculating a first change amount according to the second historical power grid supply and demand data;

[0061] Calculating a second change amount according to the historical electricity sales data;

[0062] The second historical power grid supply and demand data and the historical growth rate of the historical power sales data are obtained according to the first change amount and the second change amount.

[0063] As an improvement of the above solution, the indicator weight value calculation unit is specifically used to:

[0064] Constructing a data matrix; the elements of the data matrix are obtained according to the second historical power grid supply and demand data and the historical power sales data of each period;

[0065] Performing standardization processing on the data matrix to obtain a standardized data matrix;

[0066] According to the standardized data matrix, obtaining the contrast intensity of the element;

[0067] Calculating the second correlation strength of each element in the standardized data matrix, and obtaining the conflict of the element according to the second correlation strength;

[0068] The indicator weight value of the historical growth rate is calculated according to the comparison intensity and the conflict.

[0069] As an improvement of the above solution, obtaining the contrast intensity of the element according to the standardized data matrix includes:

[0070] pass Calculating the comparison strength of the jth indicator in the standardized data matrix; the indicator includes the second historical power grid supply and demand data and the historical power sales data;

[0071] Wherein, m is the number of cycles covered by the second historical power grid supply and demand data; x i ′ j is the data of the jth indicator in the ith period in the standardized data matrix; It is the data average of the jth indicator of all periods in the standardized data matrix.

[0072] As an improvement of the above solution, the calculation of the indicator weight value of the historical growth rate according to the comparison intensity and the conflict includes:

[0073] pass C j =σ j f j Calculate the indicator weight value of the historical growth rate;

[0074] Among them, σ j is the comparison strength of the jth indicator; f j is the conflict of the jth indicator; n is the total number of indicators.

[0075] As an improvement of the above solution, the current electricity sales forecast value calculation unit is specifically used to:

[0076] Obtaining the electricity sales value of the previous cycle from the second historical power grid supply and demand data;

[0077] The current electricity sales growth rate and the electricity sales value of the previous cycle are multiplied to obtain the current electricity sales forecast value.

[0078] As an improvement of the above solution, the investment limit calculation module includes:

[0079] A base period electricity sales amount acquisition unit, used to obtain a base period electricity sales amount according to the historical electricity sales data;

[0080] A base period fixed assets acquisition unit, used to acquire base period fixed assets from the second historical power grid supply and demand data;

[0081] A base period unit electricity fixed assets calculation unit, used to calculate the base period unit electricity fixed assets according to the base period electricity sales and base period fixed assets;

[0082] The investment limit calculation unit is used to reversely constrain the current investment limit using the base period unit electricity fixed assets and the current electricity sales forecast value according to the preset maximum capital conversion rate and the preset transmission and distribution price pricing supervision constraints, so as to obtain the investment limit of the power grid fixed assets.

[0083] An embodiment of the present invention also provides a computer-readable storage medium, comprising a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute a method for calculating the investment limit of power grid fixed assets as described in any one of the above.

[0084] Compared with the prior art, the present invention discloses a method, system and storage medium for calculating the investment limit of power grid fixed assets, which obtains historical power sales data and first historical power grid supply and demand data; uses the correlation coefficient method to screen the key influencing data of the historical power sales data from the first historical power grid supply and demand data as the second historical power grid supply and demand data; inputs the second historical power grid supply and demand data and the historical power sales data into a pre-built power sales forecast model to solve and obtain the current power sales forecast value; and reversely constrains the current investment limit through the current power sales forecast value, the historical power sales data and the second historical power grid supply and demand data to calculate the investment limit of power grid fixed assets. By adopting the embodiments of the present invention, it is possible to start from efficiency and benefit, based on the influence and role of power demand growth and power price changes, and to obtain the investment limit obtained by analyzing the main factors affecting the investment in power grid fixed assets, which is helpful for power grid enterprises to optimize investment management, effectively control power grid investment and costs, and improve power grid investment benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0085] Figure 1 It is a schematic diagram of the steps of a method for calculating the investment limit of power grid fixed assets provided by an embodiment of the present invention;

[0086] Figure 2 It is a structural schematic diagram of an investment limit calculation system for power grid fixed assets provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0087] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0088] In the description of the specification and claims, it is to be understood that the terms first, second, etc. in the specification and claims are only used for the purpose of describing the same technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated, nor necessarily describing the order or time sequence. The terms are interchangeable where appropriate. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features.

[0089] The embodiment of the present invention provides a method for calculating the investment limit of power grid fixed assets. Figure 1 In this embodiment, the method for calculating the investment limit of power grid fixed assets is specifically performed through steps S1 to S4:

[0090] S1. Obtain historical electricity sales data and first historical power grid supply and demand data.

[0091] In some embodiments, the first historical power grid supply and demand data includes power supply data, power demand data and economic data. More specifically, the power supply data includes maximum load and installed capacity; the power demand data includes social power consumption and industry power consumption indicators; and the economic data includes GDP and economic growth value.

[0092] It should be noted that as social electricity demand will continue to maintain a high growth rate, historical power grid operation data will also change with each passing day. The above-mentioned historical power grid operation data is the data for more effective investment limits under current application scenarios. It is only used as an example. The specific historical power grid operation data does not affect the beneficial effects achieved by the present invention.

[0093] It should also be noted that, in the embodiment of the present invention, one year is taken as a cycle, and the acquisition of historical electricity sales data and first historical power grid supply and demand data is to acquire electricity sales data and power grid supply and demand data of several historical cycles.

[0094] S2. Using the correlation coefficient method, key influencing data of the historical power sales data are screened from the first historical power grid supply and demand data to obtain the key influencing data as the second historical power grid supply and demand data.

[0095] In the example of the present invention, the strong correlation factors between the first historical power grid supply and demand data and the historical power sales data, that is, the key influencing data, are determined and used as the second historical power grid supply and demand data. This allows the factors that have the greatest impact on power sales to be fully considered during calculations, and reduces the amount of calculations.

[0096] S3. Input the second historical power grid supply and demand data and the historical power sales data into a pre-built power sales forecasting model to obtain a current power sales forecast value.

[0097] It should be noted that the pre-built electricity sales forecasting model is used to forecast the current electricity sales based on the historical electricity consumption trend. The current electricity sales forecast value obtained by the embodiment of the present invention can fit the actual development and further achieve the optimal resource planning and utilization of the power grid.

[0098] S4. Reversely constrain the current investment limit through the current electricity sales forecast value, the historical electricity sales data and the second historical power grid supply and demand data, and calculate the investment limit of the power grid fixed assets.

[0099] Compared with the prior art, the embodiment of the present invention, by adopting the reverse constraint control method, can further analyze the factors that form reverse constraints on the scale of grid investment by fixed assets per unit of electricity in the base period, and can gather the efficiency and benefits of grid investment when testing the investment limit of grid fixed assets, which is helpful for grid enterprises to optimize investment management, effectively control grid investment and costs, and improve grid investment benefits.

[0100] Exemplarily, in the embodiment of the present invention, the Pearson correlation coefficient method and significance check are used to obtain the strongly correlated power grid operation data.

[0101] As a preferred implementation, step S2, using a correlation coefficient method, screens out key influencing data of the historical power sales data from the first historical power grid supply and demand data as the second historical power grid supply and demand data, including:

[0102] According to the historical electricity sales data, a historical electricity sales change amount is obtained;

[0103] Using the Pearson correlation coefficient method, calculating the first correlation strength between the first historical power grid supply and demand data and the historical power sales change;

[0104] The first historical power grid supply and demand data whose first correlation strength is greater than a preset threshold is screened, and a significance check is performed on the screened data to obtain the second historical power grid supply and demand data.

[0105] As a preferred implementation, in step S3, the second historical power grid supply and demand data and the historical power sales data are input into a pre-built power sales forecasting model to obtain a current power sales forecast value, and steps S31-S35 are performed:

[0106] S31. Inputting the second historical power grid supply and demand data and the historical electricity sales data into a pre-built electricity sales amount prediction model.

[0107] S32: Calculate the historical growth rates of the second historical power grid supply and demand data and the historical electricity sales data.

[0108] Preferably, the step S32 includes:

[0109] Calculating a first change amount according to the second historical power grid supply and demand data;

[0110] Calculating a second change amount according to the historical electricity sales data;

[0111] The second historical power grid supply and demand data and the historical growth rate of the historical power sales data are obtained according to the first change amount and the second change amount.

[0112] S33. Calculate the index weight value of the historical growth rate by using the entropy weight method.

[0113] S34. Perform a weighted operation on the historical growth rate according to the indicator weight value to calculate the current electricity sales growth rate.

[0114] In the embodiment of the present invention, one year is taken as a cycle, and all years covered by the second historical power grid supply and demand data are taken as the base period. It should be noted that the base period unit electricity fixed assets are based on the average value of the unit electricity fixed assets of each year in the second historical power grid supply and demand data. Of course, in other embodiments, it can also be the weighted average value of the unit electricity fixed assets of each year.

[0115] It should be noted that the electricity sales growth rate in each cycle will be different. The current electricity sales growth rate is the electricity sales growth rate in the current cycle predicted based on the second historical power grid supply and demand data and the historical electricity sales data. It combines the electricity sales growth rate in historical cycles, and the calculated value can fit the actual development.

[0116] Exemplarily, in one embodiment, the strongly correlated power grid operation data include GDP, installed capacity and social electricity consumption, and the calculated historical growth rate and the indicator weight value are shown in Table 1.

[0117] Table 1

[0118] index Historical growth rate (%) Weight (%) Social electricity consumption 4.5 18 GDP 5.5 21 Installed capacity 9.1 29 Electricity Sales 4.8 32

[0119] In the embodiment of the present invention, the current electricity sales growth rate is Eg=4.5%×18%+5.5%×21%+9.1%×29%+4.8%×32%=6.14%.

[0120] S35. Calculate the current electricity sales forecast value based on the current electricity sales growth rate.

[0121] Preferably, step S35 includes:

[0122] Obtaining the electricity sales value of the previous cycle from the second historical power grid supply and demand data;

[0123] The current electricity sales growth rate and the electricity sales value of the previous cycle are multiplied to obtain the current electricity sales forecast value.

[0124] In some embodiments, by E n =E n-1 ×(1+E g ) calculates the current electricity sales value, where E n-1 The electricity sales value of the previous cycle.

[0125] In the above scheme, the second historical power grid supply and demand data with the greatest impact on power sales is selected from the first historical power grid supply and demand data, and a weighted calculation is performed on the second historical power grid supply and demand data and the growth rate of power sales to obtain the current power sales growth rate, which can be used to predict the current power sales value and is conducive to fully planning the maximum limit of power grid fixed asset investment.

[0126] As a preferred implementation, step S33, calculating the index weight value of the historical growth rate by entropy weight method, includes:

[0127] Constructing a data matrix; the elements of the data matrix are obtained according to the second historical power grid supply and demand data and the historical power sales data of each period;

[0128] Performing standardization processing on the data matrix to obtain a standardized data matrix;

[0129] According to the standardized data matrix, obtaining the contrast intensity of the element;

[0130] Calculating the second correlation strength of each element in the standardized data matrix, and obtaining the conflict of the element according to the second correlation strength;

[0131] The indicator weight value of the historical growth rate is calculated according to the comparison intensity and the conflict.

[0132] Exemplarily, the constructed data matrix is ​​X=(x ij ) m×n ; Wherein, m is the number of cycles, and n is the sum of the second historical power grid supply and demand data and the historical power grid electricity sales; x ij is the data of the jth indicator in the ith period in the data matrix.

[0133] It should be noted that, in some embodiments, the second historical grid supply and demand data and the historical electricity sales data are used as indicators. In other embodiments, the historical electricity sales growth rate is calculated based on the historical electricity sales data, and the second historical grid supply and demand data and the historical electricity sales growth rate are used as indicators.

[0134] pass Normalize positive indicators by Normalize the negative indicators, where x j is the data value of the j-th indicator.

[0135] Furthermore, preferably, obtaining the contrast intensity of the element according to the standardized data matrix comprises:

[0136] pass Calculating the comparison strength of the jth indicator in the standardized data matrix; the indicator includes the second historical power grid supply and demand data and the historical power sales data;

[0137] Wherein, m is the number of cycles covered by the second historical power grid supply and demand data; x i ′ j is the data of the jth indicator in the ith period in the standardized data matrix; It is the data average of the jth indicator of all periods in the standardized data matrix.

[0138] Preferably, the calculating the indicator weight value of the historical growth rate according to the comparison strength and the conflict includes:

[0139] pass C j =σ j f j Calculate the indicator weight value of the historical growth rate;

[0140] Among them, σ j is the comparison strength of the jth indicator; f j is the conflict of the jth indicator; n is the total number of indicators.

[0141] As a preferred implementation, step S4, through the current electricity sales forecast value, the historical electricity sales data and the second historical power grid supply and demand data, the current investment limit is reversely constrained to calculate the investment limit of the power grid fixed assets, including:

[0142] According to the historical electricity sales data, a base period electricity sales volume is obtained;

[0143] Obtaining base period fixed assets from the second historical power grid supply and demand data;

[0144] Calculate the fixed assets per unit of electricity in the base period based on the base period electricity sales and base period fixed assets;

[0145] According to the preset maximum capital conversion rate and the preset transmission and distribution price pricing supervision constraints, the base period unit electricity fixed assets and the current electricity sales forecast value are used to reversely constrain the current investment limit to obtain the investment limit of the power grid fixed assets.

[0146] Exemplarily, the average data of all periods covered by the historical electricity sales data is used as the base period electricity sales amount, and the average data of all periods covered by the second historical power grid supply and demand data is used as the base period fixed assets, and the period covered by the historical electricity sales data is consistent with the period covered by the second historical power grid supply and demand data. By dividing the base period electricity sales amount and the base period fixed assets, the calculated value is used as the base period unit electricity fixed assets.

[0147] It should be noted that, in the embodiment of the present invention, the transmission and distribution price pricing supervision constraints are obtained according to the published provincial power grid transmission and distribution price pricing method. Specifically, the estimated new transmission and distribution fixed assets are based on the requirement to improve investment efficiency and are determined in accordance with the principle of not being higher than the historical unit electricity fixed assets. If it is lower than the historical unit electricity fixed assets, it shall be determined according to the estimated number.

[0148] In the above scheme, the introduction of transmission and distribution price pricing regulatory constraints can make the generated investment limit more in line with actual production activities.

[0149] It should also be noted that in the embodiments of the present invention, the maximum conversion rate is obtained based on the published "Provincial Power Grid Transmission and Distribution Price Pricing Method". According to the Provincial Power Grid Transmission and Distribution Price Pricing Method, the ratio of the estimated new investment included in the fixed assets refers to the ratio of the estimated new transmission and distribution fixed asset investment amount that can be included in the current estimated new transmission and distribution fixed asset original value. In principle, it shall not exceed the ratio of the new investment included in the fixed assets in the previous regulatory cycle, and shall not exceed 75% at most. In some embodiments, the maximum conversion rate is 75%; in other embodiments, the maximum conversion rate is adjusted to 75% according to actual conditions. The maximum conversion rate is determined by economic means, and the specific values ​​do not affect the beneficial effects achieved by the present invention.

[0150] In some embodiments, the inverse constraint control method is adopted, by Fa=(Fe×E n ) / Cr to calculate the investment limit of grid fixed assets;

[0151] Among them, Fe is the fixed assets per unit of electricity in the base period, E n is the current electricity sales value, and Cr is the maximum capital conversion rate.

[0152] By adopting the embodiments of the present invention, it is possible to start from efficiency and benefit, based on the influence and effect of electricity demand growth and electricity price changes, and obtain investment limits by analyzing the main factors affecting the fixed asset investment of the power grid, which helps power grid companies optimize investment management, effectively control power grid investment and costs, and improve power grid investment efficiency.

[0153] See also Figure 2The embodiment of the present invention provides a system for calculating the investment limit of power grid fixed assets, including a data acquisition module 11, a data screening module 12, a model prediction module 13 and an investment limit calculation module 14, wherein:

[0154] A data acquisition module 11 is used to acquire historical electricity sales data and first historical power grid supply and demand data;

[0155] A data screening module 12 is used to screen the key influencing data of the historical power sales data from the first historical power grid supply and demand data using the Pearson correlation coefficient method as the second historical power grid supply and demand data;

[0156] A model prediction module 13, used for inputting the second historical power grid supply and demand data and the historical power sales data into a pre-built power sales forecasting model to obtain a current power sales forecast value;

[0157] The investment limit calculation module 14 is used to reversely constrain the current investment limit through the current electricity sales forecast value, the historical electricity sales data and the second historical power grid supply and demand data, and calculate the investment limit of the power grid fixed assets.

[0158] As a preferred implementation, the data screening module 12 includes:

[0159] A historical electricity sales change calculation unit, used to obtain the historical electricity sales change according to the historical electricity sales data;

[0160] A first correlation strength calculation unit, configured to calculate a first correlation strength between the first historical power grid supply and demand data and the historical power sales change amount by using a Pearson correlation coefficient method;

[0161] The second historical power grid supply and demand data screening unit is used to screen the first historical power grid supply and demand data whose first correlation strength is greater than a preset threshold, and perform significance verification on the screened data to obtain the second historical power grid supply and demand data.

[0162] As a preferred implementation, the model prediction module 13 includes:

[0163] A model data input unit, used to input the second historical power grid supply and demand data and the historical power sales data into a pre-built power sales amount prediction model;

[0164] A historical growth rate calculation unit, used to calculate the historical growth rates of the second historical power grid supply and demand data and the historical power sales data;

[0165] An indicator weight value calculation unit, used to calculate the indicator weight value of the historical growth rate by using an entropy weight method;

[0166] A current electricity sales growth rate calculation unit, configured to perform a weighted operation on the historical growth rate according to the indicator weight value to calculate the current electricity sales growth rate;

[0167] The current electricity sales forecast value calculation unit is used to calculate the current electricity sales forecast value according to the current electricity sales growth rate.

[0168] Furthermore, the historical growth rate calculation unit is specifically used to:

[0169] Calculating a first change amount according to the second historical power grid supply and demand data;

[0170] Calculating a second change amount according to the historical electricity sales data;

[0171] The second historical power grid supply and demand data and the historical growth rate of the historical power sales data are obtained according to the first change amount and the second change amount.

[0172] As a preferred implementation, the indicator weight value calculation unit is specifically used to:

[0173] Constructing a data matrix; the elements of the data matrix are obtained according to the second historical power grid supply and demand data and the historical power sales data of each period;

[0174] Performing standardization processing on the data matrix to obtain a standardized data matrix;

[0175] According to the standardized data matrix, obtaining the contrast intensity of the element;

[0176] Calculating the second correlation strength of each element in the standardized data matrix, and obtaining the conflict of the element according to the second correlation strength;

[0177] The indicator weight value of the historical growth rate is calculated according to the comparison intensity and the conflict.

[0178] Furthermore, preferably, obtaining the contrast intensity of the element according to the standardized data matrix comprises:

[0179] pass Calculating the comparison strength of the jth indicator in the standardized data matrix; the indicator includes the second historical power grid supply and demand data and the historical power sales data;

[0180] Wherein, m is the number of cycles covered by the second historical power grid supply and demand data; x i ′ j is the data of the jth indicator in the ith period in the standardized data matrix; It is the data average of the jth indicator of all periods in the standardized data matrix.

[0181] Preferably, the calculating the indicator weight value of the historical growth rate according to the comparison strength and the conflict includes:

[0182] pass C j =σ j f j Calculate the indicator weight value of the historical growth rate;

[0183] Among them, σ j is the comparison strength of the jth indicator; f j is the conflict of the jth indicator; n is the total number of indicators.

[0184] As a preferred implementation, the current electricity sales forecast value calculation unit is specifically used to:

[0185] Obtaining the electricity sales value of the previous cycle from the second historical power grid supply and demand data;

[0186] The current electricity sales growth rate and the electricity sales value of the previous cycle are multiplied to obtain the current electricity sales forecast value.

[0187] As a preferred implementation, the investment limit calculation module 14 includes:

[0188] A base period electricity sales amount acquisition unit, used to obtain a base period electricity sales amount according to the historical electricity sales data;

[0189] A base period fixed assets acquisition unit, used to acquire base period fixed assets from the second historical power grid supply and demand data;

[0190] A base period unit electricity fixed assets calculation unit, used to calculate the base period unit electricity fixed assets according to the base period electricity sales and base period fixed assets;

[0191] The investment limit calculation unit is used to reversely constrain the current investment limit using the base period unit electricity fixed assets and the current electricity sales forecast value according to the preset maximum capital conversion rate and the preset transmission and distribution price pricing supervision constraints, so as to obtain the investment limit of the power grid fixed assets.

[0192] An investment limit calculation system for power grid fixed assets provided by an embodiment of the present invention can be used to calculate the investment limit based on efficiency and benefits, based on the influence and effect of electricity demand growth and electricity price changes, by analyzing the main factors affecting power grid fixed asset investment. This helps power grid companies optimize investment management, effectively control power grid investment and costs, and improve power grid investment efficiency.

[0193] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0194] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for calculating the investment limit of power grid fixed assets, characterized in that: include: Obtain historical electricity sales data and the first historical power grid supply and demand data; Using the correlation coefficient method, the key influencing data of the historical power sales data is screened from the first historical power grid supply and demand data to obtain the key influencing data as the second historical power grid supply and demand data; Inputting the second historical power grid supply and demand data and the historical power sales data into a pre-built power sales forecasting model to obtain a current power sales forecast value; The current investment limit is reversely constrained by the current electricity sales forecast value, the historical electricity sales data and the second historical power grid supply and demand data, and the investment limit of the power grid fixed assets is calculated.

2. A method for calculating the investment limit of power grid fixed assets according to claim 1, characterized in that: The method of using the correlation coefficient method to screen the key influencing data of the historical power sales data from the first historical power grid supply and demand data as the second historical power grid supply and demand data includes: According to the historical electricity sales data, a historical electricity sales change amount is obtained; Using the Pearson correlation coefficient method, calculating the first correlation strength between the first historical power grid supply and demand data and the historical power sales change; The first historical power grid supply and demand data whose first correlation strength is greater than a preset threshold is screened, and a significance check is performed on the screened data to obtain the second historical power grid supply and demand data.

3. A method for calculating the investment limit of power grid fixed assets according to claim 1, characterized in that: The step of inputting the second historical power grid supply and demand data and the historical power sales data into a pre-built power sales forecasting model to obtain a current power sales forecast value includes: Inputting the second historical power grid supply and demand data and the historical power sales data into a pre-built power sales amount prediction model; Calculating the historical growth rates of the second historical power grid supply and demand data and the historical power sales data; Calculate the index weight value of the historical growth rate by using the entropy weight method; According to the weight value of the indicator, weighted operation is performed on the historical growth rate to calculate the current electricity sales growth rate; The current electricity sales forecast value is calculated based on the current electricity sales growth rate.

4. A method for calculating the investment limit of power grid fixed assets as claimed in claim 3, characterized in that: The calculating the historical growth rate of the second historical power grid supply and demand data and the historical power sales data includes: Calculating a first change amount according to the second historical power grid supply and demand data; Calculating a second change amount according to the historical electricity sales data; The second historical power grid supply and demand data and the historical growth rate of the historical power sales data are obtained according to the first change amount and the second change amount.

5. A method for calculating the investment limit of power grid fixed assets as claimed in claim 3, characterized in that: The calculation of the index weight value of the historical growth rate by the entropy weight method includes: Constructing a data matrix; the elements of the data matrix are obtained according to the second historical power grid supply and demand data and the historical power sales data of each period; Performing standardization processing on the data matrix to obtain a standardized data matrix; According to the standardized data matrix, obtaining the contrast intensity of the element; Calculating the second correlation strength of each element in the standardized data matrix, and obtaining the conflict of the element according to the second correlation strength; The indicator weight value of the historical growth rate is calculated according to the comparison intensity and the conflict.

6. A method for calculating the investment limit of power grid fixed assets as claimed in claim 5, characterized in that: The step of obtaining the contrast intensity of the element according to the standardized data matrix comprises: pass Calculating the comparison strength of the jth indicator in the standardized data matrix; the indicator includes the second historical power grid supply and demand data and the historical power sales data; Wherein, m is the number of cycles covered by the second historical power grid supply and demand data; x i ′ j is the data of the jth indicator in the ith period in the standardized data matrix; It is the data average of the jth indicator of all periods in the standardized data matrix.

7. A method for calculating the investment limit of power grid fixed assets as claimed in claim 5, characterized in that: The calculating the index weight value of the historical growth rate according to the comparison intensity and the conflict includes: pass C j =σ j f j Calculate the indicator weight value of the historical growth rate; Among them, σ j is the comparison strength of the jth indicator; f j is the conflict of the jth indicator; n is the total number of indicators.

8. A method for calculating the investment limit of power grid fixed assets as claimed in claim 3, characterized in that: The calculation of the current electricity sales forecast value according to the current electricity sales growth rate includes: Obtaining the electricity sales value of the previous cycle from the second historical power grid supply and demand data; The current electricity sales growth rate and the electricity sales value of the previous cycle are multiplied to obtain the current electricity sales forecast value.

9. A method for calculating the investment limit of power grid fixed assets according to claim 1, characterized in that: The reverse constraint on the current investment limit is performed by using the current electricity sales forecast value, the historical electricity sales data and the second historical power grid supply and demand data to calculate the investment limit of the power grid fixed assets, including: According to the historical electricity sales data, a base period electricity sales volume is obtained; Obtaining base period fixed assets from the second historical power grid supply and demand data; Calculate the fixed assets per unit of electricity in the base period based on the base period electricity sales and base period fixed assets; According to the preset maximum capital conversion rate and the preset transmission and distribution price pricing supervision constraints, the base period unit electricity fixed assets and the current electricity sales forecast value are used to reversely constrain the current investment limit to obtain the investment limit of the power grid fixed assets.

10. A system for calculating the investment limit of power grid fixed assets, characterized in that: include: A data acquisition module, used to acquire historical electricity sales data and first historical power grid supply and demand data; A data screening module, configured to use a Pearson correlation coefficient method to screen the key influencing data of the historical power sales data from the first historical power grid supply and demand data to obtain the key influencing data as the second historical power grid supply and demand data; A model prediction module, used for inputting the second historical power grid supply and demand data and the historical power sales data into a pre-built power sales forecasting model to solve and obtain a current power sales forecast value; The investment limit calculation module is used to reversely constrain the current investment limit through the current electricity sales forecast value, the historical electricity sales data and the second historical power grid supply and demand data, and calculate the investment limit of the power grid fixed assets.

11. A power grid fixed asset investment limit calculation system as claimed in claim 10, characterized in that: The data screening module comprises: A historical electricity sales change calculation unit, used to obtain the historical electricity sales change according to the historical electricity sales data; A first correlation strength calculation unit, configured to calculate a first correlation strength between the first historical power grid supply and demand data and the historical power sales change amount by using a Pearson correlation coefficient method; The second historical power grid supply and demand data screening unit is used to screen the first historical power grid supply and demand data whose first correlation strength is greater than a preset threshold, and perform significance verification on the screened data to obtain the second historical power grid supply and demand data.

12. The system for calculating the investment limit of power grid fixed assets according to claim 10, characterized in that: The model prediction module comprises: A model data input unit, used to input the second historical power grid supply and demand data and the historical power sales data into a pre-built power sales amount prediction model; A historical growth rate calculation unit, used to calculate the historical growth rates of the second historical power grid supply and demand data and the historical power sales data; An indicator weight value calculation unit, used to calculate the indicator weight value of the historical growth rate by using an entropy weight method; A current electricity sales growth rate calculation unit, configured to perform a weighted operation on the historical growth rate according to the indicator weight value to calculate the current electricity sales growth rate; The current electricity sales forecast value calculation unit is used to calculate the current electricity sales forecast value according to the current electricity sales growth rate.

13. A power grid fixed asset investment limit calculation system as claimed in claim 12, characterized in that: The historical growth rate calculation unit is specifically used for: Calculating a first change amount according to the second historical power grid supply and demand data; Calculating a second change amount according to the historical electricity sales data; The second historical power grid supply and demand data and the historical growth rate of the historical power sales data are obtained according to the first change amount and the second change amount.

14. A power grid fixed asset investment limit calculation system as claimed in claim 12, characterized in that: The indicator weight value calculation unit is specifically used to: Constructing a data matrix; the elements of the data matrix are obtained according to the second historical power grid supply and demand data and the historical power sales data of each period; Performing standardization processing on the data matrix to obtain a standardized data matrix; According to the standardized data matrix, obtaining the contrast intensity of the element; Calculating the second correlation strength of each element in the standardized data matrix, and obtaining the conflict of the element according to the second correlation strength; The indicator weight value of the historical growth rate is calculated according to the comparison intensity and the conflict.

15. A power grid fixed asset investment limit calculation system as claimed in claim 14, characterized in that: The step of obtaining the contrast intensity of the element according to the standardized data matrix comprises: pass Calculating the comparison strength of the jth indicator in the standardized data matrix; the indicator includes the second historical power grid supply and demand data and the historical power sales data; Wherein, m is the number of cycles covered by the second historical power grid supply and demand data; x i ′ j is the data of the jth indicator in the ith period in the standardized data matrix; It is the data average of the jth indicator of all periods in the standardized data matrix.

16. A power grid fixed asset investment limit calculation system as claimed in claim 14, characterized in that: The calculating the index weight value of the historical growth rate according to the comparison intensity and the conflict includes: pass C j =σ j f j Calculate the indicator weight value of the historical growth rate; Among them, σ j is the comparison strength of the jth indicator; f j is the conflict of the jth indicator; n is the total number of indicators.

17. A power grid fixed asset investment limit calculation system as claimed in claim 12, characterized in that: The current electricity sales forecast value calculation unit is specifically used for: Obtaining the electricity sales value of the previous cycle from the second historical power grid supply and demand data; The current electricity sales growth rate and the electricity sales value of the previous cycle are multiplied to obtain the current electricity sales forecast value.

18. The system for calculating the investment limit of power grid fixed assets according to claim 10, characterized in that: The investment limit calculation module includes: A base period electricity sales amount acquisition unit, used to obtain a base period electricity sales amount according to the historical electricity sales data; A base period fixed assets acquisition unit, used to acquire base period fixed assets from the second historical power grid supply and demand data; A base period unit electricity fixed assets calculation unit, used to calculate the base period unit electricity fixed assets according to the base period electricity sales and base period fixed assets; The investment limit calculation unit is used to reversely constrain the current investment limit using the base period unit electricity fixed assets and the current electricity sales forecast value according to the preset maximum capital conversion rate and the preset transmission and distribution price pricing supervision constraints, so as to obtain the investment limit of the power grid fixed assets.

19. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the method for calculating the investment limit of power grid fixed assets as described in any one of claims 1 to 9.

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