Generation method and system for typical daily output curve of wind power reverse peak regulation

Abstract

The invention relates to the field of power system planning, and discloses a wind power reverse peak regulation typical daily output curve generation method and system, and the method comprises the steps: carrying out the statistics of the historical year-by-year electric quantity characteristics of a wind power supply in an effective sample space, selecting the confidence probability of the daily guarantee power generation of the wind power supply, and calculating the daily guarantee power generation of the wind power supply under the confidence probability; calculating the guaranteed output rate of the historical output characteristics of the wind power supply in the time period under the confidence probability; calculating the effective capacity under the historical output characteristic accumulated electric quantity ratio of the wind power supply; and according to the peak load time period, the base load time period, the guaranteed output rate of the wind power supply, the effective capacity, the daily guaranteed generating capacity and the reference curve, calculating a typical output curve of the typical daily wind power supply in power balance. By adopting the method, a reasonable wind power supply output curve suitable for typical daily power balance analysis of a resource depletion scene under a novel power system can be provided, and the power supply planning accuracy of the power system is improved.

Description

Technical Field

[0001] The present invention relates to the field of power system planning, and in particular to a method and system for generating a typical daily output curve of wind power anti-peak regulation. Background Art

[0002] With the access of large-scale new energy and energy storage power sources, the balance and safety of the new power system has evolved into two major issues: supply guarantee and consumption. The typical moment power balance method of the traditional power system dominated by hydropower and thermal power is no longer able to meet the needs of power planning. In order to solve the problem of supply guarantee, the typical daily power balance method based on the scenario of new energy resource depletion can be used for analysis, and then reasonable power planning suggestions can be given.

[0003] However, the existing technology does not provide a feasible solution for power supply planning suggestions. In particular, how to improve the rationality of power balance calculation results and improve the accuracy of power system power supply planning in a typical daily power balance is an urgent problem that needs to be solved. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for generating a typical daily output curve for wind power reverse peak regulation. The present invention is based on a typical daily power balance method for a scenario of exhaustion of new energy resources, and provides an important reference for the planning and operation of the power system by deeply analyzing the typical daily output curve for reverse peak regulation of wind power sources.

[0005] In order to achieve the above object, the present invention adopts the following technical solution: In a first aspect, the present invention provides a method for generating a typical daily output curve of wind power reverse peak regulation, comprising the following steps: Collect historical output characteristics of wind power sources in the area to be analyzed; Determine the effective sample space in the annual continuous load curve; Statistically collect the historical year-by-year electricity characteristics of wind power sources in the effective sample space, select the confidence probability of the daily guaranteed power generation of wind power sources, and calculate the daily guaranteed power generation of wind power sources under the confidence probability; From the historical output characteristics of wind power sources, a typical day with poor wind power output is selected as a benchmark curve; Collect the daily characteristics of the power load in the area to be analyzed, and determine the peak load period and base load period based on the daily characteristics of the power load, and the rest is mid-load; Select the confidence probability of wind power source guaranteed output, and calculate the guaranteed output rate of the historical output characteristics of the wind power source in the peak load period in the effective sample space under the confidence probability; Select the cumulative electricity proportion of the effective capacity of the wind power source, and calculate the effective capacity under the cumulative electricity proportion of the historical output characteristics of the wind power source during the base load period in the effective sample space; According to the peak load period, base load period, guaranteed output rate of wind power source, effective capacity, guaranteed daily power generation and benchmark curve, the typical output curve of wind power source on a typical day of power balance is calculated.

[0006] As a further improvement of the present invention, the collecting of historical output characteristics of wind power sources in the area to be analyzed includes: Determine the area to be analyzed, collect the historical 8760-hour output characteristics of the wind power source in the area, and standardize them. The year number is recorded as Y and the sample space is recorded as .

[0007] As a further improvement of the present invention, the effective sample space in the annual continuous load curve is determined by determining the effective sample space in the 8760 curve of year Y; specifically including: calculate The average monthly wind power output is obtained , ,by The month corresponding to the minimum value is the base month, and the effective months are extended 0 to 3 months forward and backward respectively, which is generally between 3 and 4 months. The data in valid months form a valid sample space.

[0008] As a further improvement of the present invention, the typical day with poor wind power output is selected from the historical output characteristics of the wind power source as the reference curve, including: From the 8760-hour output characteristics of wind power sources in history, a typical day with poor wind power output is selected as the benchmark curve. , ; Typical day benchmark curve for poor wind power output There are three selection methods: The first method is to select the daily output characteristic curve with the minimum daily power generation as the reference curve in the effective sample space of wind power output; The second method is to select the daily output characteristic curve with the minimum daily power generation in the effective months of the year in the effective sample space of wind power output year by year, and average or weighted average them to form a benchmark curve; The third method is to combine the hourly historical average output of 24 hours from 0 to 23 in the effective sample space of wind power output into a benchmark curve.

[0009] As a further improvement of the present invention, the daily characteristics of the power load in the area to be analyzed are collected, and the peak load period and the base load period are determined based on the daily characteristics of the power load, and the others are mid-load, including: Collect the daily characteristics of the power load in the area to be analyzed, specifically the hourly per unit value for 24 hours, and determine the peak load period , base load period , the rest are waist load; determine the peak load period , base load period The principles are: Peak load period The maximum value of the daily characteristics of power load is taken as the reference time, and the period is extended 0 to 3 hours forward and backward respectively, and the overall period is between 2 and 4 hours; the base load period Taking the minimum value in the daily characteristics of power load as the reference moment, extend it forward and backward by 0 to 7 hours respectively. It is necessary to avoid the peak load period for at least 1 hour, and the overall time is between 4 and 8 hours.

[0010] As a further improvement of the present invention, the typical output curve of the wind power source on a typical day of power balance is calculated based on the peak load period, the base load period, the guaranteed output rate of the wind power source, the effective capacity, the daily guaranteed power generation and the reference curve, including: remember Peak load period Length of time, Base load period The duration of hour,

[0011] when hour,

[0012] In the formula, peak load period , base load period , the guaranteed output rate of wind power , effective capacity , daily guaranteed power generation , the benchmark curve , Typical output curve of wind power source on a typical day of power balance , .

[0013] In a second aspect, the present invention provides a typical daily output curve generation system for wind power reverse peak regulation, comprising: A collection module, used to collect historical output characteristics of wind power sources in the area to be analyzed; A first determination module is used to determine the effective sample space in the annual continuous load curve; The first calculation module is used to count the historical year-by-year electricity characteristics of wind power sources in the effective sample space, select the confidence probability of the daily guaranteed power generation of the wind power source, and calculate the daily guaranteed power generation of the wind power source under the confidence probability; A selection module is used to select a typical day with poor wind power output from the historical output characteristics of the wind power source as a reference curve; The second determination module is used to collect the daily characteristics of the power load in the area to be analyzed, and determine the peak load period and the base load period based on the daily characteristics of the power load, and the rest is the mid-load period; The second calculation module is used to select the confidence probability of the wind power source to guarantee the output, and calculate the guaranteed output rate of the historical output characteristics of the wind power source during the peak load period in the effective sample space under the confidence probability; The third calculation module is used to select the cumulative electricity proportion of the effective capacity of the wind power source, and calculate the effective capacity under the cumulative electricity proportion of the historical output characteristics of the wind power source during the base load period in the effective sample space; The fourth calculation module is used to calculate and obtain the typical output curve of the wind power source on a typical day of power balance according to the peak load period, base load period, guaranteed output rate of the wind power source, effective capacity, daily guaranteed power generation and reference curve.

[0014] In a third aspect, the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for generating a typical daily output curve for wind power reverse peak regulation when executing the computer program.

[0015] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for generating a typical daily output curve for wind power reverse peak regulation is implemented.

[0016] In a fifth aspect, the present invention provides a computer program product, which includes computer instructions, characterized in that the computer instructions instruct a computer to execute the method for generating a typical daily output curve for wind power reverse peak regulation.

[0017] Compared with the prior art, the beneficial effects of the present invention are: The present invention responds to the demand for typical output curves of wind power reverse peak regulation in the typical daily power balance method based on the scenario of exhaustion of new energy resources. The method collects the historical year-by-year output characteristics of wind power in the area to be analyzed, determines the effective sample space, and counts the daily guaranteed power generation of wind power. The typical characteristics of poor wind power output are selected as the reference curve, and the guaranteed output rate of wind power is counted in the peak load period based on the load characteristics, and the effective capacity of wind power is counted in the base load period. Finally, the typical daily output curve of wind power peak regulation is obtained by calculation. The method has the advantages of data-driven accuracy, representativeness of typical scenarios, flexibility of power balance strategy, and practical application value, which is helpful to promote the green transformation and sustainable development of the power system. The method of the present invention can improve the rationality of the typical daily power balance analysis results based on the scenario of exhaustion of new energy resources, improve the accuracy of power system power planning, and is of great significance to the realization of the "dual carbon" goal. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a strategy flow chart of the present invention; Figure 2 Typical daily load characteristics for power balance. DETAILED DESCRIPTION

[0019] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other without conflict.

[0020] The following detailed description is an exemplary description, which is intended to provide further detailed description of the present invention. Unless otherwise specified, all technical terms used in the present invention have the same meaning as those generally understood by those skilled in the art to which the present application belongs. The terms used in the present invention are only for describing specific embodiments, and are not intended to limit exemplary embodiments according to the present invention.

[0021] In the typical daily power balance, determining a reasonable typical daily output curve for wind power source peak regulation is of great significance for improving the rationality of power balance calculation results, improving the accuracy of power system power planning, and even achieving the "dual carbon" goals.

[0022] Combination Figure 1 As shown, the present invention provides a method for generating a typical daily output curve of wind power reverse peak regulation, comprising the following steps: S1, determine the area to be analyzed, collect the historical 8760-hour output characteristics of the wind power source in the area, and standardize them. The year number is recorded as Y and the sample space is recorded as ; S2, determine the effective sample space in the 8760 curve in year Y; S3: Statistical analysis of the historical 365-day electricity characteristics of wind power sources in the effective sample space, and select the confidence probability of wind power sources to guarantee daily power generation , calculate the confidence probability Daily guaranteed power generation of wind power under .

[0023] S4, from the historical 8760-hour output characteristics of wind power sources, select the typical day with poor wind power output as the benchmark curve .

[0024] S5, collect the daily characteristics of the power load in the area to be analyzed, specifically the hourly per unit value for 24 hours; determine the peak load period , base load period , the others are waist loads.

[0025] S6, confidence probability of selecting wind power source to ensure output , in the peak load period in the effective sample space, calculate the historical output characteristics of the wind power source in this period at the confidence probability Guaranteed output rate under .

[0026] S7, select the cumulative electricity proportion of the effective capacity of wind power sources , in the base load period in the effective sample space, calculate the historical output characteristics of wind power in this period in the cumulative power ratio The effective capacity of .

[0027] S8, according to the peak load period , base load period , Guaranteed output rate of wind power source , Effective Capacity , Daily guaranteed power generation And the benchmark curve , calculate and obtain the typical output curve of wind power source on a typical day of power balance .

[0028] The method for generating a typical daily output curve of wind power reverse peak regulation for wind power sources under resource depletion scenarios proposed in the present invention provides a more refined decision support for the planning and operation of wind power sources through data processing and analysis steps. First, by collecting the historical output data of wind power sources in the study area and performing standardization processing to eliminate the influence of factors such as different years and different installed capacities, the data are made comparable. Filter out the effective sample space from a large amount of historical data to provide a reliable data basis for subsequent statistical analysis. By statistically analyzing the historical power characteristics of wind power sources in the effective sample space, selecting an appropriate confidence probability, and calculating the daily guaranteed power generation of the wind power source, which is an important indicator for evaluating the power supply capacity of the wind power source. Selecting a typical day with poor wind power output as a benchmark curve helps to consider the output of the wind power source under the most unfavorable conditions in subsequent analysis. Collect the daily characteristics of the power load in the study area, determine the peak load, base load and waist load periods, and provide a basis for the matching analysis of wind power sources and power loads. During the peak load period and base load period, the guaranteed output rate and effective capacity of wind power sources are calculated respectively, which are key indicators for evaluating the power supply capacity of wind power sources in different periods. Based on the above analysis, combined with the daily guaranteed power generation, guaranteed output rate, effective capacity and benchmark curve, the typical output curve of wind power sources on a typical day of power balance is calculated.

[0029] In response to the demand for typical output curves of wind power reverse peak regulation in typical daily power balance methods based on scenarios of new energy resource depletion, the method of the present invention collects the historical annual 8760-hour output characteristics of wind power in the area to be analyzed, determines the effective sample space, and counts the daily guaranteed power generation of wind power. The typical characteristics of poor wind power output are selected as the reference curve, and the guaranteed output rate of wind power is counted during the peak load period based on the load characteristics, and the effective capacity of wind power is counted during the base load period, and finally the typical daily output curve of wind power peak regulation is obtained by calculation. The method of the present invention can improve the rationality of the typical daily power balance analysis results based on scenarios of new energy resource depletion, improve the accuracy of power system power planning, and is of great significance to the realization of the "dual carbon" goals.

[0030] The present invention ensures the scientificity and accuracy of the generated typical output curve of wind power sources through a large amount of historical data analysis and statistics. By considering the output characteristics and power load characteristics of wind power sources in different time periods, more refined decision support is provided for the planning and operation of wind power sources. It is suitable for wind power sources in different regions and with different installed capacities, and has strong adaptability and versatility. Through the generated typical output curve of wind power sources, the power supply capacity of wind power sources can be better evaluated, providing strong support for the optimal allocation of power resources. It helps to plan and utilize wind power resources more scientifically and promote the development and application of renewable energy.

[0031] As a further improvement of the present invention, in S2, the method for determining the effective sample space is: calculate The average monthly wind power output is obtained ,by The month corresponding to the minimum value is the base month, and the effective months are extended 0 to 3 months forward and backward respectively, which is generally between 3 and 4 months. The data in valid months form a valid sample space.

[0032] As a further improvement of the present invention, in S4, the typical day benchmark curve of the wind power output is poor There are three selection methods: The first method is to select the daily output characteristic curve with the smallest daily power generation as the benchmark curve in the effective sample space of wind power source output; the second method is to select the daily output characteristic curve with the smallest daily power generation in the effective months of the year year by year in the effective sample space of wind power source output, and average or weighted average them to form a benchmark curve; the third method is to combine the hourly historical average output of 24 hours from 0 to 23 in the effective sample space of wind power source output into a benchmark curve.

[0033] As a further improvement of the present invention, in S5, the peak load period is determined , base load period The principles are: Peak load period The maximum value of the daily characteristics of power load is used as the reference time, and the period is extended 0 to 3 hours forward and backward respectively, with an overall period of 2 to 4 hours. Taking the minimum value in the daily characteristics of power load as the reference moment, extend it forward and backward by 0 to 7 hours respectively. It is necessary to avoid the peak load period for at least 1 hour, and the overall time is between 4 and 8 hours.

[0034] As a further improvement of the present invention, in S8, the typical output curve of the wind power source on a typical day of power balance is The calculation method is: remember Peak load period Length of time, Base load period The duration of hour,

[0035] when hour,

[0036] This method provides an important reference for the planning and operation of the power system. By deeply analyzing the anti-peaking characteristics of wind power sources, it is possible to plan the power structure, configure energy storage and peaking power sources more scientifically and reasonably. By optimizing the power balance strategy, the system operating cost can be reduced and the economic benefits can be improved. For example, reducing the output of other types of power sources during periods of high wind power output can reduce fuel consumption and operation and maintenance costs. This method helps to promote the consumption and utilization of new energy. By reasonably arranging the output sequence and time of various types of power sources, it can ensure that new energy power generation is fully utilized and reduce the occurrence of wind and solar power abandonment.

[0037] The following is a detailed description of a research example of a regional power grid. It should be emphasized that the following description is only exemplary and is not intended to limit the scope and application of the present invention.

[0038] Combination Figure 1 As shown, the present invention provides a method for generating a typical daily output curve of wind power reverse peak regulation of a wind power source under a resource depletion scenario, comprising the following steps: 1) Determine the area to be analyzed, collect the historical 8760-hour output characteristics of the wind power source in the area, and standardize them. The year is recorded as Y and the sample space is recorded as ; 2) Determine the effective sample space in the 8760 curve in year Y; 3) Calculate the historical 365-day electricity characteristics of wind power sources in the effective sample space and select the confidence probability of wind power sources to guarantee daily power generation , calculate the confidence probability Daily guaranteed power generation of wind power under .

[0039] As an example, calculate the daily guaranteed power generation Specifically include: Sort the daily power generation data in each year from large to small. Then, according to the selected confidence probability Φ, intercept the corresponding proportion of data points from the sorted data. For example, if the confidence probability Φ is 95%, intercept the first 95% of the data points.

[0040] The minimum value among the intercepted data points is the daily guaranteed power generation E_Φ under the confidence probability Φ of that year. For data from many years, the daily guaranteed power generation of each year can be calculated , and then take the average or median as the final daily guaranteed power generation .

[0041] 4) From the historical 8760-hour output characteristics of wind power sources, select the typical day with poor wind power output as the benchmark curve .

[0042] 5) Collect the daily characteristics of the power load in the area to be analyzed, specifically the hourly per unit value for 24 hours, and determine the peak load period , base load period , the others are waist loads.

[0043] 6) Select wind power sources to ensure the confidence probability of output , in the peak load period in the effective sample space, calculate the historical output characteristics of the wind power source in this period at the confidence probability Guaranteed output rate under .

[0044] As an example, calculate the guaranteed output rate Specifically include: The filtered wind power output characteristic data are sorted in descending order. According to the selected confidence probability φ, the corresponding proportion of data points are intercepted from the sorted data. For example, if the confidence probability φ is 95%, the first 95% of the data points are intercepted.

[0045] The minimum value among the intercepted data points is the guaranteed output under the confidence probability φ. It is the ratio between the guaranteed output and the rated installed capacity of wind power source, and the calculation formula is: = (guaranteed output / rated installed capacity) × 100% Calculated guaranteed output rate It should be consistent with the actual wind power output characteristics and meet the requirements of the selected confidence probability φ. If there is a large deviation between the calculated results and the actual situation, it may be necessary to adjust the confidence probability φ or re-screen the data to ensure the accuracy and reliability of the calculated results.

[0046] 7) Select the cumulative electricity proportion of the effective capacity of wind power sources , in the base load period in the effective sample space, calculate the cumulative power proportion of the historical output characteristics of wind power in this period The effective capacity of .

[0047] As an example, the effective capacity The calculation method is as follows: Set a cumulative power variable with an initial value of 0. Traverse the sorted data hour by hour or minute by minute, and add the output value at each time point to the cumulative power variable. During the traversal process, calculate the proportion of the current cumulative power to the total power and record it.

[0048] Determine effective capacity , find the time point when the cumulative power ratio reaches or exceeds δ (such as 90%) for the first time in the recorded cumulative power ratio. The output value at this time point is the effective capacity under the cumulative power ratio δ If the output value changes continuously, the output value at that time point can be calculated by interpolation or other methods.

[0049] Calculated effective capacity It should be consistent with the actual output characteristics of the wind power source and meet the requirements of the cumulative power proportion δ. If there is a large deviation between the calculated result and the actual situation, it may be necessary to adjust the cumulative power proportion δ or re-collect and process the data to ensure the accuracy and reliability of the calculated result.

[0050] 8) According to the peak load period , base load period , Guaranteed output rate of wind power source , Effective Capacity , Daily guaranteed power generation And the benchmark curve , calculate and obtain the typical output curve of wind power source on a typical day of power balance .

[0051] Peak load period T PL : The period of time when electricity demand is the highest, usually the wind power output also needs to be correspondingly higher. T VL: During periods when electricity demand is relatively stable, wind power output may be relatively stable. Guaranteed output rate P φ : The probability that wind power can reach or exceed the output level during peak load or a specific period of time. P δ : The output level when the cumulative electricity consumption reaches a certain proportion during the base load period. E Φ :The amount of electricity that wind power can generate in one day. Baseline curve { P Bn}: The benchmark or predicted value of power demand in each period of a day. The typical output curve of wind power source on a typical day of power balance is obtained through the above formula { P n}.

[0052] Example Under the background of "dual carbon", a certain region predicts that the load will exceed 200 million kilowatts in 2030. In order to meet the requirements of the renewable electricity quota system, the installed capacity of renewable energy will exceed 500 million kilowatts. It is now necessary to carry out power supply planning and adopt a power balance method based on a typical day of renewable energy resource depletion scenario to determine the system's supply capacity and arrange an appropriate amount of thermal power and energy storage power. In the resource depletion scenario, the typical daily output curve of the wind power source's anti-peak regulation can be obtained by using the method of the present invention.

[0053] The specific steps of this method are as follows: 1) Collect the historical output characteristics of wind power sources in the regional power system for 8760 hours each year, and standardize them to obtain a total of 52560 point samples in the past 6 years (one leap year, February 29, was merged through technical methods and not considered separately); 2) Calculate the monthly average wind power output in the 8760 curve for 6 years, take January as the minimum month as the base month, and combine the load peak month to determine the effective months as November, December and January. These three months in 6 years have a total of 13,248 points to form an effective sample space; Table 1 Average wind power output per month

[0054] The historical 365-day electricity characteristics of wind power sources in the effective sample space are statistically analyzed, the confidence probability of the daily guaranteed power generation of wind power sources is selected, and the daily guaranteed power generation of wind power sources under the confidence probability is calculated.

[0055] 3) The historical 365-day electricity characteristics of wind power sources in the effective sample space are statistically analyzed, and a total of 552 point samples are obtained for 6 years and 552 days in history, of which the maximum value is 11.02, the minimum value is 0.47, and the average value is 4.95. Based on the situation that the region is reserved for new energy, the confidence probability of the daily guaranteed power generation of wind power sources is 92.9%, and the daily guaranteed power generation of wind power sources under the confidence probability of 92.9% is calculated to be 1.86 hours.

[0056] 4) From the historical output characteristic samples of wind power sources, the second selection method is adopted, that is, the daily output characteristic curve with the smallest daily power generation in the effective month of each year in the six years is selected from the effective sample space of wind power source output, and the average is taken to form the benchmark curve , see Table 1; Table 1 Baseline curve for days with poor wind power resources

[0057]

[0058] 5) Collect the daily characteristics of the power load in the area to be analyzed, specifically the per-unit value for 24 hours, see Figure 1 ; This curve is the net load curve after considering the photovoltaic output. After analysis, the 4-hour period from 17:00 to 20:00 in the evening is the peak load period, and the 4-hour period from 12:00 to 15:00 in the afternoon is the base load period. Figure 2 Typical daily load characteristics for power balance.

[0059] 6) Based on the situation that the region reserves backup for new energy, the confidence probability of wind power generation to guarantee output is 95%. The historical output characteristics of wind power generation between 17:00 and 20:00 have a guaranteed output rate of 0.057 at a confidence probability of 95%.

[0060] 7) Based on the level of new energy consumption in the region, the effective capacity of the wind power source is selected to account for 90% of the cumulative electricity. The historical output characteristics of the wind power source at 12:00-15:00 show that the effective capacity is 0.32 when the cumulative electricity accounts for 90%.

[0061] 8) According to the peak load period, base load period, guaranteed output rate of wind power source, effective capacity, guaranteed daily power generation and benchmark curve, the typical daily output curve of wind power source for reverse peak regulation under resource depletion scenario is obtained as shown in Table 2. The specific calculation steps are as follows: Considering

[0062]

[0063]

[0064] Table 2 Typical daily output curve of wind power generation in the resource depletion scenario

[0065] The typical daily output curve of wind power source anti-peak regulation provides crucial reference information for the planning and operation of the power system. It can be used for power system planning and power system operation, for example: Wind farm site selection and layout: The anti-peaking characteristics of wind power sources indicate that in certain periods (especially during low load periods), wind power output may be large, which is not completely synchronized with the system load demand. Therefore, in power system planning, it is necessary to fully consider this characteristic of wind power output and reasonably select the site selection and layout of wind farms to maximize the utilization efficiency of wind power resources.

[0066] Power structure optimization: By analyzing the output curve of a typical day of wind power reverse peak regulation, we can understand the changing rules of wind power output in different periods, thus providing a basis for optimizing the power structure. For example, during periods of high wind power output, the output of other types of power sources can be appropriately reduced to reduce system operating costs.

[0067] Energy storage and peak-shaving power configuration: The anti-peaking characteristics of wind power increase the difficulty of system peaking. Therefore, in the planning of the power system, it is necessary to reasonably configure the energy storage system and peak-shaving power to cope with the challenges brought by the fluctuation of wind power output. The energy storage system can store electricity when the wind power output is excessive and release electricity when the wind power output is insufficient, thereby smoothing the fluctuation of wind power output; while the peak-shaving power can provide additional power support when the wind power output cannot meet the system demand.

[0068] Power balance: The typical daily output curve of wind power source anti-peak regulation is an important basis for formulating power balance plan. By analyzing the changing rules of wind power output in different periods, the output of other types of power sources can be reasonably arranged to ensure the balance of system power.

[0069] Dispatching and operation control: During the operation of the power system, dispatchers need to formulate dispatch plans based on the typical daily output curve of wind power sources for reverse peak regulation, and reasonably arrange the output sequence and time of various power sources. At the same time, it is also necessary to monitor and adjust the wind power output in real time through the operation control system to ensure the stability and safety of the system operation.

[0070] Economic and environmental assessment: The typical daily output curve of wind power reverse peak regulation can also be used to evaluate the economic and environmental performance of the power system. By analyzing the changing patterns of wind power output in different periods, the contribution of wind power to system operating costs and environmental impact can be calculated, thus providing decision support for the optimal operation of the power system.

[0071] In summary, the typical daily output curve of wind power reverse peak load regulation provides comprehensive reference information for the planning and operation of the power system. Through in-depth analysis of this curve, it is possible to more scientifically and reasonably plan the power structure, configure energy storage and peak load regulation, formulate power balance plans, and perform dispatching and operation control, thereby ensuring the safe, stable, economical and environmentally friendly operation of the power system.

[0072] In summary, the method for generating a typical daily output curve of wind power counter-peak regulation of wind power sources under resource depletion scenarios proposed in the present invention is not only scientific and accurate, but also provides powerful decision-making support for the planning and operation of wind power sources, and helps promote the sustainable development of renewable energy.

[0073] The second object of the present invention is to provide a typical daily output curve generation system for wind power reverse peak regulation, comprising: A collection module, used to collect historical output characteristics of wind power sources in the area to be analyzed; A first determination module is used to determine the effective sample space in the annual continuous load curve; The first calculation module is used to count the historical year-by-year electricity characteristics of wind power sources in the effective sample space, select the confidence probability of the daily guaranteed power generation of the wind power source, and calculate the daily guaranteed power generation of the wind power source under the confidence probability; A selection module is used to select a typical day with poor wind power output from the historical output characteristics of the wind power source as a reference curve; The second determination module is used to collect the daily characteristics of the power load in the area to be analyzed, and determine the peak load period and the base load period based on the daily characteristics of the power load, and the rest is the mid-load period; The second calculation module is used to select the confidence probability of the wind power source to guarantee the output, and calculate the guaranteed output rate of the historical output characteristics of the wind power source during the peak load period in the effective sample space under the confidence probability; The third calculation module is used to select the cumulative electricity proportion of the effective capacity of the wind power source, and calculate the effective capacity under the cumulative electricity proportion of the historical output characteristics of the wind power source during the base load period in the effective sample space; The fourth calculation module is used to calculate and obtain the typical output curve of the wind power source on a typical day of power balance according to the peak load period, base load period, guaranteed output rate of the wind power source, effective capacity, daily guaranteed power generation and reference curve.

[0074] The wind power reverse peak load typical day output curve generation system proposed in the present invention aims to realize the refined analysis of wind power output characteristics through systematic module design, and then generate a typical day output curve that meets the power balance requirements. The collection module is responsible for collecting the historical output characteristic data of wind power sources in the area to be analyzed, which is the basis of the entire analysis. The data is preprocessed, such as cleaning and standardization, to ensure the accuracy of subsequent analysis. The first determination module determines the effective sample space in the annual continuous load curve based on the collected data. This step is to eliminate abnormal data and retain representative output characteristic samples. The first calculation module counts the historical year-by-year electricity characteristics of wind power sources in the effective sample space, and selects an appropriate confidence probability to calculate the daily guaranteed power generation of the wind power source. This indicator reflects the daily power supply capacity of the wind power source at a specific confidence level. The selection module selects a typical day with poor output from the historical output characteristics of the wind power source as a reference curve. This helps to consider the output of the wind power source under the most unfavorable conditions in subsequent analysis. The second determination module collects the daily characteristic data of the power load in the area to be analyzed, and determines the peak load period, base load period and waist load period based on these data. This step provides a basis for the matching analysis of wind power sources and power loads. The second calculation module calculates the guaranteed output rate of wind power sources according to the selected confidence probability during the peak load period. This indicator reflects the power supply reliability of wind power sources during the peak load period. The third calculation module calculates the effective capacity of wind power sources according to the selected cumulative power proportion during the base load period. This indicator reflects the continuous power supply capacity of wind power sources during the base load period. Generation of typical output curve: The fourth calculation module combines the above analysis, combined with the peak load period, base load period, guaranteed output rate of wind power sources, effective capacity, daily guaranteed power generation and benchmark curve, to calculate the typical output curve of wind power sources on a typical day of power balance. This curve provides an important reference for the planning and operation of the power system.

[0075] The system adopts a modular design, and each module is responsible for a specific task, making the entire analysis process clearer and more orderly. This design facilitates the expansion and upgrading of the system, as well as adaptive adjustment for different regions and different wind power characteristics. By collecting a large amount of historical data and conducting refined analysis and processing, the system can more accurately reflect the output characteristics and power load characteristics of wind power sources. This helps to generate a typical daily output curve that is more in line with the actual situation and improve the planning and operation efficiency of the power system. The generated typical daily output curve provides important decision-making support for the planning and operation of the power system. By comparing the typical output curves of different wind power sources, the layout and configuration of wind power sources can be optimized, and the overall power supply capacity and reliability of the power system can be improved. The present invention helps to plan and utilize wind power resources more scientifically and promote the development and application of renewable energy. By improving the power supply capacity and reliability of wind power sources, the competitiveness of renewable energy in the power system can be enhanced, and the optimization and transformation of the energy structure can be promoted.

[0076] The third object of the embodiment of the present invention is to provide an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for generating a typical daily output curve of wind power reverse peak regulation when executing the computer program. It also includes a communication interface and a bus.

[0077] A fourth objective of an embodiment of the present invention is to provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for generating a typical daily output curve of wind power reverse peak regulation is implemented.

[0078] A fifth objective of an embodiment of the present invention is to provide a computer program product, which includes computer instructions, wherein the computer instructions instruct a computer to execute the method for generating a typical daily output curve of wind power anti-peak regulation.

[0079] 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.

[0080] 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 1A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0081] The present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, readable storage media, optical storage, etc.) containing computer-usable program codes.

[0082] 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.

[0083] Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0084] 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 method for generating a typical daily output curve of wind power reverse peak regulation, characterized in that: The following steps are involved: Collect historical output characteristics of wind power sources in the area to be analyzed; Determine the effective sample space in the annual continuous load curve; Statistically collect the historical year-by-year electricity characteristics of wind power sources in the effective sample space, select the confidence probability of the daily guaranteed power generation of wind power sources, and calculate the daily guaranteed power generation of wind power sources under the confidence probability; From the historical output characteristics of wind power sources, a typical day with poor wind power output is selected as a benchmark curve; Collect the daily characteristics of the power load in the area to be analyzed, and determine the peak load period and base load period based on the daily characteristics of the power load, and the rest is mid-load; Select the confidence probability of wind power source guaranteed output, and calculate the guaranteed output rate of the historical output characteristics of the wind power source in the peak load period in the effective sample space under the confidence probability; Select the cumulative electricity proportion of the effective capacity of the wind power source, and calculate the effective capacity under the cumulative electricity proportion of the historical output characteristics of the wind power source during the base load period in the effective sample space; According to the peak load period, base load period, guaranteed output rate of wind power source, effective capacity, guaranteed daily power generation and benchmark curve, the typical output curve of wind power source on a typical day of power balance is calculated.

2. The method for generating a typical daily output curve of wind power reverse peak regulation according to claim 1, characterized in that: The collecting of historical output characteristics of wind power sources in the area to be analyzed includes: Determine the area to be analyzed, collect the historical 8760-hour output characteristics of the wind power source in the area, and standardize them. The year number is recorded as Y and the sample space is recorded as .

3. The method for generating a typical daily output curve of wind power reverse peak regulation according to claim 2, characterized in that: The effective sample space in the determined annual continuous load curve is the effective sample space in the 8760 curve of year Y; specifically, it includes: calculate The average monthly wind power output is obtained , ,by The month corresponding to the minimum value is the base month, and the effective months are extended 0 to 3 months forward and backward respectively, which is generally between 3 and 4 months. The data in valid months form a valid sample space.

4. The method for generating a typical daily output curve of wind power reverse peak regulation according to claim 1, characterized in that: The method of selecting a typical day with poor wind power output from the historical output characteristics of the wind power source as a reference curve includes: From the 8760-hour output characteristics of wind power sources in history, a typical day with poor wind power output is selected as the benchmark curve. , ; Typical day benchmark curve for poor wind power output There are three selection methods: The first method is to select the daily output characteristic curve with the minimum daily power generation as the reference curve in the effective sample space of wind power output; The second method is to select the daily output characteristic curve with the minimum daily power generation in the effective months of the year in the effective sample space of wind power output year by year, and average or weighted average them to form a benchmark curve; The third method is to combine the hourly historical average output of 24 hours from 0 to 23 in the effective sample space of wind power output into a benchmark curve.

5. The method for generating a typical daily output curve of wind power reverse peak regulation according to claim 1, characterized in that: Collect the daily characteristics of the power load in the area to be analyzed, and determine the peak load period and base load period based on the daily characteristics of the power load. The rest are mid-load, including: Collect the daily characteristics of the power load in the area to be analyzed, specifically the hourly per unit value for 24 hours, and determine the peak load period , base load period , the rest are waist load; determine the peak load period , base load period The principles are: Peak load period The maximum value of the daily characteristics of power load is taken as the reference time, and the period is extended 0 to 3 hours forward and backward respectively, and the overall period is between 2 and 4 hours; the base load period Taking the minimum value in the daily characteristics of power load as the reference moment, extend it forward and backward by 0 to 7 hours respectively. It is necessary to avoid the peak load period for at least 1 hour, and the overall time is between 4 and 8 hours.

6. The method for generating a typical daily output curve of wind power reverse peak regulation according to claim 1, characterized in that: The typical output curve of the wind power source on a typical day of power balance is calculated based on the peak load period, the base load period, the guaranteed output rate of the wind power source, the effective capacity, the daily guaranteed power generation and the benchmark curve, including: remember Peak load period Length of time, Base load period The duration of hour, when hour, In the formula, peak load period , base load period , the guaranteed output rate of wind power , effective capacity , daily guaranteed power generation , the benchmark curve , Typical output curve of wind power source on a typical day of power balance , .

7. A typical daily output curve generation system for wind power reverse peak regulation, characterized in that: include: A collection module, used to collect historical output characteristics of wind power sources in the area to be analyzed; A first determination module is used to determine the effective sample space in the annual continuous load curve; The first calculation module is used to count the historical year-by-year electricity characteristics of wind power sources in the effective sample space, select the confidence probability of the daily guaranteed power generation of the wind power source, and calculate the daily guaranteed power generation of the wind power source under the confidence probability; A selection module is used to select a typical day with poor wind power output from the historical output characteristics of the wind power source as a reference curve; The second determination module is used to collect the daily characteristics of the power load in the area to be analyzed, and determine the peak load period and the base load period based on the daily characteristics of the power load, and the rest is the mid-load period; The second calculation module is used to select the confidence probability of the wind power source to guarantee the output, and calculate the guaranteed output rate of the historical output characteristics of the wind power source during the peak load period in the effective sample space under the confidence probability; The third calculation module is used to select the cumulative electricity proportion of the effective capacity of the wind power source, and calculate the effective capacity under the cumulative electricity proportion of the historical output characteristics of the wind power source during the base load period in the effective sample space; The fourth calculation module is used to calculate and obtain the typical output curve of the wind power source on a typical day of power balance according to the peak load period, base load period, guaranteed output rate of the wind power source, effective capacity, daily guaranteed power generation and reference curve.

8. An electronic device, characterized in that: It comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for generating a typical daily output curve of wind power reverse peak regulation as claimed in any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for generating a typical daily output curve of wind power reverse peak regulation according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising computer instructions, characterized in that: The computer instructions instruct the computer to execute the method for generating a typical daily output curve of wind power reverse peak regulation as described in any one of claims 1-6.

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