Medium and long term load growth analysis method and device considering multi-factor influence
Through a medium- and long-term load growth analysis method that considers the influence of multiple factors, the load increment caused by various factors is obtained and its role is quantified, and the limitations of factor analysis and extreme weather power supply in the existing technology are solved, which improves the accuracy of load prediction. and the difficulty of balance between grid.
Patent Information
- Application Number
- CN202411004456.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-25
- Publication Date
- 2024-12-20
AI Technical Summary
The existing load analysis method only considers a small number of factors, making it difficult to effectively analyze the causes of power load growth, and it is difficult to solve the problem of power supply tightness in extreme weather and other situations.
A medium- and long-term load growth analysis method considering the influence of multiple factors is proposed. By obtaining the load increment caused by various influencing factors in the period to be analyzed, and based on these increments, the quantitative value of load growth of each factor, including meteorological factors and economics Growth factors and related event factors.
A comprehensive analysis of the multi-factor impact of power load growth has been achieved, and the role of various factors is quantified, which improves the accuracy of power system load prediction and the difficulty of grid balance, which is of great market significance.
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Figure CN119168677A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of power system load calculation, and in particular to a medium- and long-term load growth analysis method and device taking into account the influence of multiple factors. Background Art
[0002] With the advancement of the construction of new power systems, power supply shortages in local areas and time periods are common, and the "double highs and double peaks" characteristics of the power system are becoming increasingly prominent. In addition, affected by external factors such as economy, meteorology, and events, the randomness and volatility of both the source and the load are further enhanced, and the difficulty of balancing the power grid is gradually increasing. Although the company has proposed power supply measures such as demand response priority, orderly power consumption guarantee, and power conservation assistance, it is still difficult to solve the power supply shortage caused by extreme weather.
[0003] As one of the important means to understand the operating status of the power grid, power load analysis has important reference value for the planning, design, operation and management of the power system. Due to the influence of multiple factors such as temperature, economy, events, and the mutual coupling between the factors affecting load growth, it is difficult to quantify the causes of power load growth. At the same time, with the advancement of information and digital technology, the data on electricity and related factors continues to grow. How to analyze and utilize these power big data and explore their internal meanings has become a challenging problem.
[0004] At present, there are few methods for load analysis, especially for analyzing and summarizing the causes of load growth. The existing load analysis methods only consider a small number of factors, and the analysis of various influencing factors mostly remains at the qualitative level, which has great limitations. Summary of the invention
[0005] In order to overcome the above-mentioned defects, the present invention proposes a medium- and long-term load growth analysis method and device taking into account the influence of multiple factors.
[0006] In a first aspect, a medium- and long-term load growth analysis method considering the influence of multiple factors is provided, and the medium- and long-term load growth analysis method considering the influence of multiple factors includes: Obtain the load increment caused by each influencing factor in the period to be analyzed; Analyze the quantified value of the load increase caused by each influencing factor in the period to be analyzed based on the load increment caused by each influencing factor in the period to be analyzed; The influencing factors include one of the following: meteorological factors, economic growth factors, and related event factors.
[0007] Preferably, the load increment caused by each influencing factor in the period to be analyzed is as follows: L m =LP In the above formula, L mis the load increment caused by meteorological factors during the period to be analyzed, L is the total load during the period to be analyzed, and P is the basic load during the period to be analyzed.
[0008] Furthermore, the basic load in the period to be analyzed is as follows: P=QP1+JP2 In the above formula, P1 is the basic load of working days in the period to be analyzed, P2 is the basic load of rest days in the period to be analyzed, Q is the number of working days in the period to be analyzed, and J is the number of rest days in the period to be analyzed.
[0009] Furthermore, the basic load of the working day in the period to be analyzed is as follows: P1=(∑ (m∈M) P m ) / M The basic load on rest days in the period to be analyzed is as follows: P2=(∑ (n∈N) P n ) / N In the above formula, P m is the actual load on the mth working day in spring or autumn, M is the total number of working days in spring or autumn, P n is the actual load on the nth rest day in spring or autumn, and N is the total number of rest days in spring or autumn.
[0010] Preferably, the load increment caused by each influencing factor in the period to be analyzed is as follows: P3= aP4 In the above formula, P3 is the load increment caused by economic growth factors in the period to be analyzed, P4 is the average load in the previous period to be analyzed, and a is the natural load growth rate.
[0011] Furthermore, the natural load growth rate is as follows: a=k1w1 / W1+ k2w2 / W2+ k3w3 / W3+ k4y / Y-1 In the above formula, k1, k2, k3 and k4 are the proportion of electricity consumption of the primary industry, secondary industry, tertiary industry and urban and rural residents respectively, w1, w2 and w3 are the industrial added value of the primary industry, secondary industry and tertiary industry in the period to be analyzed respectively, W1, W2 and W3 are the industrial added value of the primary industry, secondary industry and tertiary industry in the previous period to be analyzed respectively, y is the per capita consumption expenditure in the period to be analyzed, and Y is the per capita consumption expenditure in the previous period to be analyzed.
[0012] Preferably, the load increment caused by each influencing factor in the period to be analyzed is as follows: A=∑ (i∈I) P i In the above formula, A is the load increment caused by the relevant event factors in the period to be analyzed, P i is the load increment caused by the i-th related event factor in the period to be analyzed, and I is the number of related events occurring in the period to be analyzed.
[0013] Furthermore, the load increment caused by the i-th related event factor in the period to be analyzed is as follows: P i =L i1 -L i2 In the above formula, L i1 is the load before the occurrence of the ith related event in the period to be analyzed, L i2 is the load after the i-th related event occurs in the period to be analyzed.
[0014] Furthermore, the related event is an event whose correlation with the load exceeds a threshold, wherein the correlation between event x and the load is: the correlation between the all-1 vector at each time point in the period during which event x occurs and the load growth vector at each time point in the period during which event x occurs, wherein the load growth vector at each time point in the period during which event x occurs is (b1, b2…b k …b K ), b k is the load growth coefficient at the kth time point during the period when event x occurs. If the load at the kth time point during the period when event x occurs is greater than the load before event x occurs, then b k =1, otherwise, b k =0, b K is the load growth factor at the Kth time point during the period when event x occurs.
[0015] Preferably, the analyzing the quantified value of the load increase caused by each influencing factor in the period to be analyzed based on the load increment caused by each influencing factor in the period to be analyzed includes: The difference between the load increment caused by each influencing factor in the period to be analyzed and the load increment caused by each influencing factor in the historical period corresponding to the period to be analyzed is used as the increment of the load increment caused by each influencing factor in the period to be analyzed; The difference between the total load in the period to be analyzed and the total load in the historical period corresponding to the period to be analyzed is used as the increment of the total load in the period to be analyzed; The quantified value of the load increase caused by each influencing factor in the period to be analyzed is determined based on the increment of the load increment caused by each influencing factor in the period to be analyzed and the increment of the total load in the period to be analyzed.
[0016] Furthermore, the quantitative values of the load growth of each influencing factor in the period to be analyzed are as follows: η 1=(△L m / △L)×100% η 2=(△P3 / △L)×100% η 3 = (△A / △L) × 100% In the above formula, η 1 is the quantitative value of the load growth caused by meteorological factors during the period to be analyzed, η 2 is the quantitative value of the load growth caused by economic growth factors in the period to be analyzed, η 3 is the quantitative value of the load growth caused by the relevant event factors in the period to be analyzed, △L m is the increment of load increment caused by meteorological factors during the period to be analyzed, △P3 is the increment of load increment caused by economic growth factors during the period to be analyzed, △A is the increment of load increment caused by related event factors during the period to be analyzed, and △L is the increment of total load during the period to be analyzed.
[0017] In a second aspect, a medium- and long-term load growth analysis device considering the influence of multiple factors is provided, and the medium- and long-term load growth analysis device considering the influence of multiple factors includes: An acquisition module is used to obtain the load increment caused by various influencing factors in the period to be analyzed; An analysis module is used to analyze the quantitative value of the load increase caused by each influencing factor in the period to be analyzed based on the load increment caused by each influencing factor in the period to be analyzed; The influencing factors include one of the following: meteorological factors, economic growth factors, and related event factors.
[0018] In a third aspect, a computer device is provided, comprising: one or more processors; The processor is configured to execute one or more programs; When the one or more programs are executed by the one or more processors, the medium- and long-term load growth analysis method considering the influence of multiple factors is implemented.
[0019] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed, the medium- and long-term load growth analysis method considering the influence of multiple factors is implemented.
[0020] The above one or more technical solutions of the present invention have at least one or more of the following beneficial effects: The present invention relates to the technical field of load calculation of power systems, and specifically provides a medium- and long-term load growth analysis method and device that considers the influence of multiple factors, including: obtaining the load increment caused by each influencing factor in the period to be analyzed; analyzing the quantitative value of the load growth of each influencing factor in the period to be analyzed based on the load increment caused by each influencing factor in the period to be analyzed; wherein the influencing factor includes one of the following: meteorological factors, economic growth factors, and related event factors. The technical solution provided by the present invention can comprehensively consider the influence of meteorology, economy, and events on load growth, analyze the degree of effect of each influencing factor on load growth, and quantify the attribution load growth, which is of great significance to the load analysis business in the power sales market. BRIEF DESCRIPTION OF THE DRAWINGS
[0021] Figure 1 This is a flow chart of main steps of a method for analyzing medium- and long-term load growth considering the influence of multiple factors according to an embodiment of the present invention; Figure 2 is the baseline load curve for working days in 2022 according to an embodiment of the present invention; Figure 3 This is the baseline load curve for rest days in 2022 of an embodiment of the present invention. DETAILED DESCRIPTION
[0022] The specific implementation modes of the present invention will be further described in detail below in conjunction with the accompanying drawings.
[0023] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.
[0024] Example 1 See attached Figure 1 , Figure 1 FIG. 1 is a flow chart of the main steps of a method for analyzing medium- and long-term load growth considering the influence of multiple factors according to an embodiment of the present invention. Figure 1 As shown, the medium- and long-term load growth analysis method considering the influence of multiple factors in the embodiment of the present invention mainly includes the following steps: Step S101: Obtaining the load increment caused by each influencing factor in the period to be analyzed; Step S102: Analyze the quantified value of the load increase caused by each influencing factor in the period to be analyzed based on the load increment caused by each influencing factor in the period to be analyzed; The influencing factors include one of the following: meteorological factors, economic growth factors, and related event factors.
[0025] In this embodiment, the load increment caused by each influencing factor in the period to be analyzed is as follows: L m =LP In the above formula, L m is the load increment caused by meteorological factors during the period to be analyzed, L is the total load during the period to be analyzed, and P is the basic load during the period to be analyzed.
[0026] In one embodiment, the base load in the period to be analyzed is as follows: P=QP1+JP2 In the above formula, P1 is the basic load of working days in the period to be analyzed, P2 is the basic load of rest days in the period to be analyzed, Q is the number of working days in the period to be analyzed, and J is the number of rest days in the period to be analyzed.
[0027] In one embodiment, the basic load of the working day in the period to be analyzed is as follows: P1=(∑ (m∈M) P m ) / M The basic load on rest days in the period to be analyzed is as follows: P2=(∑ (n∈N) P n ) / N In the above formula, P m is the actual load on the mth working day in spring or autumn, M is the total number of working days in spring or autumn, P n is the actual load on the nth rest day in spring or autumn, and N is the total number of rest days in spring or autumn.
[0028] In this embodiment, the load increment caused by each influencing factor in the period to be analyzed is as follows: P3= aP4 In the above formula, P3 is the load increment caused by economic growth factors in the period to be analyzed, P4 is the average load in the previous period to be analyzed, and a is the natural load growth rate.
[0029] In one embodiment, the natural load growth rate is as follows: a=k1w1 / W1+ k2w2 / W2+ k3w3 / W3+ k4y / Y-1 In the above formula, k1, k2, k3 and k4 are the proportion of electricity consumption of the primary industry, secondary industry, tertiary industry and urban and rural residents respectively, w1, w2 and w3 are the industrial added value of the primary industry, secondary industry and tertiary industry in the period to be analyzed respectively, W1, W2 and W3 are the industrial added value of the primary industry, secondary industry and tertiary industry in the previous period to be analyzed respectively, y is the per capita consumption expenditure in the period to be analyzed, and Y is the per capita consumption expenditure in the previous period to be analyzed.
[0030] In this embodiment, the load increment caused by each influencing factor in the period to be analyzed is as follows: A=∑ (i∈I) P i In the above formula, A is the load increment caused by the relevant event factors in the period to be analyzed, P i is the load increment caused by the i-th related event factor in the period to be analyzed, and I is the number of related events occurring in the period to be analyzed.
[0031] In one embodiment, the load increment caused by the i-th related event factor in the period to be analyzed is as follows: P i =L i1 -L i2 In the above formula, L i1 is the load before the occurrence of the ith related event in the period to be analyzed, L i2 is the load after the i-th related event occurs in the period to be analyzed.
[0032] In one embodiment, the related event is an event whose correlation with the load exceeds a threshold, wherein the correlation between event x and the load is: the correlation between the all-1 vector at each time point in the period during which event x occurs and the load growth vector at each time point in the period during which event x occurs, wherein the load growth vector at each time point in the period during which event x occurs is (b1, b2…b k …b K ), b k is the load growth coefficient at the kth time point during the period when event x occurs. If the load at the kth time point during the period when event x occurs is greater than the load before event x occurs, then b k =1, otherwise, b k =0, b K is the load growth factor at the Kth time point during the period when event x occurs.
[0033] In this embodiment, the load increment analysis based on the load increment caused by the various influencing factors in the period to be analyzed to obtain the quantitative value of the load increase caused by the various influencing factors in the period to be analyzed includes: The difference between the load increment caused by each influencing factor in the period to be analyzed and the load increment caused by each influencing factor in the historical period corresponding to the period to be analyzed is used as the increment of the load increment caused by each influencing factor in the period to be analyzed; The difference between the total load in the period to be analyzed and the total load in the historical period corresponding to the period to be analyzed is used as the increment of the total load in the period to be analyzed; The quantified value of the load increase caused by each influencing factor in the period to be analyzed is determined based on the increment of the load increment caused by each influencing factor in the period to be analyzed and the increment of the total load in the period to be analyzed.
[0034] In one embodiment, the quantitative value of each influencing factor on the load growth in the period to be analyzed is as follows: η 1=(△L m / △L)×100% η 2=(△P3 / △L)×100% η 3 = (△A / △L) × 100% In the above formula, η 1 is the quantitative value of the load growth caused by meteorological factors during the period to be analyzed, η 2 is the quantitative value of the load growth caused by economic growth factors in the period to be analyzed, η 3 is the quantitative value of the load growth caused by the relevant event factors in the period to be analyzed, △L m is the increment of load increment caused by meteorological factors during the period to be analyzed, △P3 is the increment of load increment caused by economic growth factors during the period to be analyzed, △A is the increment of load increment caused by related event factors during the period to be analyzed, and △L is the increment of total load during the period to be analyzed.
[0035] In a specific implementation, an example analysis is conducted based on the load growth in a certain area, where the load data mainly includes the load data for the whole year of 2022; the meteorological data mainly includes the daily maximum temperature, minimum temperature, average temperature, average wind speed, etc. corresponding to the load data. April to early July is selected as the analysis period, and the example analysis is conducted with the load growth attribution at the time of the maximum load in July as the goal. For ease of reading, the load units in the subsequent part of this chapter have been omitted, so the load units are explained here as 10,000 kilowatts.
[0036] (1) Meteorological factors According to the Pearson correlation coefficient calculation formula, the correlation coefficient between the daily maximum load and meteorological factors in this area is shown in Table 1.
[0037] Table 1 Maximum temperature Minimum temperature Average temperature Wind speed January 0.22 0.21 0.21 0.05 February -0.03 -0.22 -0.13 -0.21 March -0.57 -0.71 -0.73 -0.39 April -0.57 -0.71 -0.73 -0.39 May 0.16 0.24 0.21 0.16 June 0.79 0.82 0.85 -0.16 July 0.36 0.67 0.52 0.27 August 0.45 0.55 0.54 0.34 September 0.36 0.51 0.45 0.25 October -0.87 -0.55 -0.81 0.04 November -0.90 -0.85 -0.88 0.34 December 0.22 0.21 0.21 0.05 According to Table 1, the correlation between wind speed and load in this area is weak and can be ignored; the correlation between temperature and load has obvious time domain characteristics, and the correlation in cross-seasonal months such as March, April, June, July, October and November is more significant than that in other months. The meteorological correlation coefficient in May is low, indicating that the meteorological load value of this month is small, and May can be selected as the baseline load selection date. According to the technical solution provided by the present invention, the total social electricity load, primary industry, secondary industry, tertiary industry and residential electricity baseline load in this area on weekdays in 2022 are calculated as follows Figure 2 The total social power load, primary industry, secondary industry, tertiary industry and residential power load in this area on holidays in 2022 are shown as follows: Figure 3 shown.
[0038] The maximum load moment in this area in April was 20:15 on April 1, and the maximum load moment in July was 16:15 on July 1, with a load increase of 6.1033 million kilowatts. According to the technical solution provided by the present invention and Figure 2 We can get △L at 16:15 on July 1 m It is 5.0476 million kilowatts.
[0039] (2) Economic growth factors Since the analysis period is from April to early July, it can be regarded as the first and second quarters. According to the technical solution provided by the present invention, the natural economic load growth index can be obtained, and the data used are shown in Table 2.
[0040] Table 2 Indicator name Region 1 <![CDATA[w1 / 100 million yuan]]> 473.8 <![CDATA[W1 / 100 million yuan]]> 239.06 <![CDATA[w2 / 100 million yuan]]> 4160.71 <![CDATA[W2 / 100 million yuan]]> 3661.29 <![CDATA[w3 / 100 million yuan]]> 3352.42 <![CDATA[W3 / 100 million yuan]]> 3365.06 y / 100 million yuan 4589 Y / 100 million yuan 4971 The electricity consumption of the primary industry accounts for 2.36%, the electricity consumption of the secondary industry accounts for 52.06%, the electricity consumption of the tertiary industry accounts for 30.43%, and the electricity consumption of urban and rural residents accounts for 15.15%. The natural growth index is 7.86%. Therefore, according to the technical solution provided by the present invention, the △P3 of this area is 103.59.
[0041] (3) Related event factors Since there were no major events or extreme weather during the analysis period, only the impact of rest days was considered. According to the technical solution provided by the present invention, the area ΔA is 0.
[0042] According to the above, the total load increase is 6.1033 million kilowatts, that is, △L=610.33. Therefore, the quantitative values of the impact of various influencing factors on load growth are calculated and shown in Table 3.
[0043] Table 3 variable Load increment increment Quantization value △L 610.33 99.67% <![CDATA[△L m ]]> 504.76 82.70% <![CDATA[△P3]]> 103.59 16.97% △A 0.00 0.00% Although the sum of the quantitative values of the load growth caused by various factors is different from the theoretical value of 100%, the difference is within an acceptable range. This problem is mainly due to the insufficient decoupling of various loads, and there is still a certain overlap, such as the overlap between the load generated by business expansion and meteorological load.
[0044] Example 2 Based on the same inventive concept, the present invention also provides a medium- and long-term load growth analysis device considering the influence of multiple factors, and the medium- and long-term load growth analysis device considering the influence of multiple factors comprises: An acquisition module is used to obtain the load increment caused by various influencing factors in the period to be analyzed; An analysis module is used to analyze the quantitative value of the load increase caused by each influencing factor in the period to be analyzed based on the load increment caused by each influencing factor in the period to be analyzed; The influencing factors include one of the following: meteorological factors, economic growth factors, and related event factors.
[0045] Preferably, the load increment caused by each influencing factor in the period to be analyzed is as follows: L m =LP In the above formula, L m is the load increment caused by meteorological factors during the period to be analyzed, L is the total load during the period to be analyzed, and P is the basic load during the period to be analyzed.
[0046] Furthermore, the basic load in the period to be analyzed is as follows: P=QP1+JP2 In the above formula, P1 is the basic load of working days in the period to be analyzed, P2 is the basic load of rest days in the period to be analyzed, Q is the number of working days in the period to be analyzed, and J is the number of rest days in the period to be analyzed.
[0047] Furthermore, the basic load of the working day in the period to be analyzed is as follows: P1=(∑ (m∈M) P m ) / M The basic load on rest days in the period to be analyzed is as follows: P2=(∑ (n∈N) P n ) / N In the above formula, P m is the actual load on the mth working day in spring or autumn, M is the total number of working days in spring or autumn, P n is the actual load on the nth rest day in spring or autumn, and N is the total number of rest days in spring or autumn.
[0048] Preferably, the load increment caused by each influencing factor in the period to be analyzed is as follows: P3= aP4 In the above formula, P3 is the load increment caused by economic growth factors in the period to be analyzed, P4 is the average load in the previous period to be analyzed, and a is the natural load growth rate.
[0049] Furthermore, the natural load growth rate is as follows: a=k1w1 / W1+ k2w2 / W2+ k3w3 / W3+ k4y / Y-1 In the above formula, k1, k2, k3 and k4 are the proportion of electricity consumption of the primary industry, secondary industry, tertiary industry and urban and rural residents respectively, w1, w2 and w3 are the industrial added value of the primary industry, secondary industry and tertiary industry in the period to be analyzed respectively, W1, W2 and W3 are the industrial added value of the primary industry, secondary industry and tertiary industry in the previous period to be analyzed respectively, y is the per capita consumption expenditure in the period to be analyzed, and Y is the per capita consumption expenditure in the previous period to be analyzed.
[0050] Preferably, the load increment caused by each influencing factor in the period to be analyzed is as follows: A=∑ (i∈I) P i In the above formula, A is the load increment caused by the relevant event factors in the period to be analyzed, P i is the load increment caused by the i-th related event factor in the period to be analyzed, and I is the number of related events occurring in the period to be analyzed.
[0051] Furthermore, the load increment caused by the i-th related event factor in the period to be analyzed is as follows: P i =L i1 -L i2 In the above formula, L i1 is the load before the occurrence of the ith related event in the period to be analyzed, L i2 is the load after the i-th related event occurs in the period to be analyzed.
[0052] Furthermore, the related event is an event whose correlation with the load exceeds a threshold, wherein the correlation between event x and the load is: the correlation between the all-1 vector at each time point in the period during which event x occurs and the load growth vector at each time point in the period during which event x occurs, wherein the load growth vector at each time point in the period during which event x occurs is (b1, b2…b k …b K ), b k is the load growth coefficient at the kth time point during the period when event x occurs. If the load at the kth time point during the period when event x occurs is greater than the load before event x occurs, then b k =1, otherwise, bk =0, b K is the load growth factor at the Kth time point during the period when event x occurs.
[0053] Preferably, the analyzing the quantified value of the load increase caused by each influencing factor in the period to be analyzed based on the load increment caused by each influencing factor in the period to be analyzed includes: The difference between the load increment caused by each influencing factor in the period to be analyzed and the load increment caused by each influencing factor in the historical period corresponding to the period to be analyzed is used as the increment of the load increment caused by each influencing factor in the period to be analyzed; The difference between the total load in the period to be analyzed and the total load in the historical period corresponding to the period to be analyzed is used as the increment of the total load in the period to be analyzed; The quantified value of the load increase caused by each influencing factor in the period to be analyzed is determined based on the increment of the load increment caused by each influencing factor in the period to be analyzed and the increment of the total load in the period to be analyzed.
[0054] Furthermore, the quantitative values of the load growth of each influencing factor in the period to be analyzed are as follows: η 1=(△L m / △L)×100% η 2=(△P3 / △L)×100% η 3 = (△A / △L) × 100% In the above formula, η 1 is the quantitative value of the load growth caused by meteorological factors during the period to be analyzed, η 2 is the quantitative value of the load growth caused by economic growth factors in the period to be analyzed, η 3 is the quantitative value of the load growth caused by the relevant event factors in the period to be analyzed, △L m is the increment of load increment caused by meteorological factors during the period to be analyzed, △P3 is the increment of load increment caused by economic growth factors during the period to be analyzed, △A is the increment of load increment caused by related event factors during the period to be analyzed, and △L is the increment of total load during the period to be analyzed.
[0055] Example 3 Based on the same inventive concept, the present invention also provides a computer device, which includes a processor and a memory, wherein the memory is used to store a computer program, wherein the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function, so as to implement the steps of a medium- and long-term load growth analysis method considering the influence of multiple factors in the above embodiment.
[0056] Example 4 Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It can be understood that the computer-readable storage medium here can include both built-in storage media in a computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of a medium- and long-term load growth analysis method considering the influence of multiple factors in the above embodiment.
[0057] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0058] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.
[0059] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.
[0060] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.
[0061] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.
Claims
1. A medium- and long-term load growth analysis method considering the influence of multiple factors, characterized in that: The method comprises: Obtain the load increment caused by each influencing factor in the period to be analyzed; Analyze the quantified value of the load increase caused by each influencing factor in the period to be analyzed based on the load increment caused by each influencing factor in the period to be analyzed; The influencing factors include one of the following: meteorological factors, economic growth factors, and related event factors.
2. The method according to claim 1, characterized in that The load increment caused by each influencing factor in the period to be analyzed is as follows: L m =L-P In the above formula, L m is the load increment caused by meteorological factors during the period to be analyzed, L is the total load during the period to be analyzed, and P is the basic load during the period to be analyzed.
3. The method according to claim 2, characterized in that The basic load in the period to be analyzed is as follows: P=QP1+JP2 In the above formula, P1 is the basic load of working days in the period to be analyzed, P2 is the basic load of rest days in the period to be analyzed, Q is the number of working days in the period to be analyzed, and J is the number of rest days in the period to be analyzed.
4. The method according to claim 3, characterized in that The basic load of working days in the period to be analyzed is as follows: P1=(∑ (m∈M) P m ) / M The basic load on rest days in the period to be analyzed is as follows: P2=(∑ (n∈N) P n ) / N In the above formula, P m is the actual load on the mth working day in spring or autumn, M is the total number of working days in spring or autumn, P n is the actual load on the nth rest day in spring or autumn, and N is the total number of rest days in spring or autumn.
5. The method according to claim 1, characterized in that The load increment caused by each influencing factor in the period to be analyzed is as follows: P3= aP4 In the above formula, P3 is the load increment caused by economic growth factors in the period to be analyzed, P4 is the average load in the previous period to be analyzed, and a is the natural load growth rate.
6. The method according to claim 5, characterized in that The natural load growth rate is as follows: a=k1w1 / W1+ k2w2 / W2+ k3w3 / W3+ k4y / Y-1 In the above formula, k1, k2, k3 and k4 are the proportion of electricity consumption of the primary industry, secondary industry, tertiary industry and urban and rural residents respectively, w1, w2 and w3 are the industrial added value of the primary industry, secondary industry and tertiary industry in the period to be analyzed respectively, W1, W2 and W3 are the industrial added value of the primary industry, secondary industry and tertiary industry in the previous period to be analyzed respectively, y is the per capita consumption expenditure in the period to be analyzed, and Y is the per capita consumption expenditure in the previous period to be analyzed.
7. The method according to claim 1, characterized in that The load increment caused by each influencing factor in the period to be analyzed is as follows: A=∑ (i∈I) P i In the above formula, A is the load increment caused by the relevant event factors in the period to be analyzed, P i is the load increment caused by the i-th related event factor in the period to be analyzed, and I is the number of related events occurring in the period to be analyzed.
8. The method according to claim 7, characterized in that The load increment caused by the i-th related event factor in the period to be analyzed is as follows: P i =L i1 - L i2 In the above formula, L i1 is the load before the occurrence of the ith related event in the period to be analyzed, L i2 is the load after the i-th related event occurs in the period to be analyzed.
9. The method according to claim 7, characterized in that The related event is an event whose correlation with the load exceeds a threshold, wherein the correlation between event x and the load is: the correlation between the all-1 vector at each time point in the period during which event x occurs and the load growth vector at each time point in the period during which event x occurs, wherein the load growth vector at each time point in the period during which event x occurs is (b1, b2…b k …b K ), b k is the load growth coefficient at the kth time point during the period when event x occurs. If the load at the kth time point during the period when event x occurs is greater than the load before event x occurs, then b k =1, otherwise, b k =0, b K is the load growth factor at the Kth time point during the period when event x occurs.
10. The method according to claim 1, characterized in that The load increment analysis based on the load increment caused by the various influencing factors in the period to be analyzed includes: The difference between the load increment caused by each influencing factor in the period to be analyzed and the load increment caused by each influencing factor in the historical period corresponding to the period to be analyzed is used as the increment of the load increment caused by each influencing factor in the period to be analyzed; The difference between the total load in the period to be analyzed and the total load in the historical period corresponding to the period to be analyzed is used as the increment of the total load in the period to be analyzed; The quantified value of the load increase caused by each influencing factor in the period to be analyzed is determined based on the increment of the load increment caused by each influencing factor in the period to be analyzed and the increment of the total load in the period to be analyzed.
11. The method according to claim 10, characterized in that The quantitative values of the load growth of each influencing factor in the period to be analyzed are as follows: η 1=(△L m / △L)×100% η 2=(△P3 / △L)×100% η 3=(△A / △L)×100% In the above formula, η 1 is the quantitative value of the load growth caused by meteorological factors during the period to be analyzed, η 2 is the quantitative value of the load growth caused by economic growth factors in the period to be analyzed, η 3 is the quantitative value of the load growth caused by the relevant event factors in the period to be analyzed, △L m is the increment of load increment caused by meteorological factors during the period to be analyzed, △P3 is the increment of load increment caused by economic growth factors during the period to be analyzed, △A is the increment of load increment caused by related event factors during the period to be analyzed, and △L is the increment of total load during the period to be analyzed.
12. A device for analyzing medium- and long-term load growth considering multiple factors according to any one of claims 1 to 11, characterized in that: The device comprises: An acquisition module is used to obtain the load increment caused by various influencing factors in the period to be analyzed; An analysis module is used to analyze the quantitative value of the load increase caused by each influencing factor in the period to be analyzed based on the load increment caused by each influencing factor in the period to be analyzed; The influencing factors include one of the following: meteorological factors, economic growth factors, and related event factors.
13. A computer device, characterized in that: include: one or more processors; The processor is configured to execute one or more programs; When the one or more programs are executed by the one or more processors, the medium- and long-term load growth analysis method considering the influence of multiple factors as described in any one of claims 1 to 11 is implemented.
14. A computer-readable storage medium, characterized in that: A computer program is stored thereon, and when the computer program is executed, the medium- and long-term load growth analysis method considering the influence of multiple factors as described in any one of claims 1 to 11 is implemented.