Power system frequency modulation capacity estimation method, system, equipment and medium

Abstract

The invention relates to the technical field of power system scheduling and control, and discloses a power system frequency modulation capacity estimation method, system, device and medium, and the method comprises the steps: carrying out the first processing of the historical operation data of a new energy station, and obtaining a two-dimensional fluctuation quantity sample set; based on the fluctuation quantity sample set, obtaining a two-dimensional fluctuation threshold table of the generated power of the new energy station; in the actual operation stage, according to the operation capacity of the new energy station in the next day and the two-dimensional fluctuation threshold table, the fluctuation quantity of the total generated power of the new energy station in the system is evaluated; and obtaining a frequency modulation capacity demand time sequence of the system in combination with load prediction data and an evaluation result. The method can adapt to the change and development of the installed capacity of new energy, can be applied under the background of rapid development of new energy, and meets the frequency modulation management requirements of a novel power system.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power system dispatching and control technology, and particularly relates to a power system frequency modulation capacity estimation method, system, device and medium. BACKGROUND

[0002] With the acceleration of global energy transformation, the installed capacity of new energy power generation such as wind power and photovoltaic power in the power system is continuously increasing, and is gradually becoming the largest power source. New energy power generation has significant intermittency, volatility and uncertainty, which is manifested as the up and down fluctuation amplitude of power generation power in minutes to tens of minutes being much higher than the load fluctuation, which brings great challenges to the frequency modulation control of the power system.

[0003] The power system mainly relies on conventional power sources such as water-fire-nuclear power for frequency modulation control to maintain the system frequency within the qualified range. In particular, the upward frequency modulation that needs to increase the power generation power still relies on conventional power sources at present. However, the frequency modulation reserve capacity reserved by each unit usually only considers the load level, and the typical requirement is that the generator reserves 2%-6% of the rated capacity as the primary frequency modulation capacity, and the system reserves 1%-2.5% of the total load power as the secondary frequency modulation capacity. When the penetration rate of new energy power is high, the starting capacity of conventional power sources is low, and the primary frequency modulation capacity is greatly reduced. Moreover, the new energy power fluctuation is often much higher than the level of 1%-2%, resulting in insufficient reservation of secondary frequency modulation capacity.

[0004] Therefore, under the condition of high proportion of new energy access, the reservation of frequency modulation capacity must consider the fluctuation level of new energy power, and there is still a lack of mature and effective estimation method. SUMMARY

[0005] In view of the above existing problems, the present application is proposed.

[0006] Therefore, the present application provides a power system frequency modulation capacity estimation method, system, device and medium to solve the problem that in a power system with high proportion of new energy access, the traditional frequency modulation capacity reservation method only considers the load fluctuation, and does not fully consider the volatility and uncertainty of new energy power, resulting in insufficient or redundant frequency modulation capacity estimation and reservation, and it is difficult to guarantee the stability and economy of the system frequency.

[0007] To solve the above technical problems, the present application provides the following technical solutions:

[0008] In a first aspect, the present application provides a power system frequency modulation capacity estimation method, comprising:

[0009] performing first processing on the historical operation data of the new energy station to obtain a two-dimensional fluctuation sample set;

[0010] Based on the fluctuation sample set, a two-dimensional fluctuation threshold table of power generation of the new energy station is obtained;

[0011] In the actual operation stage, the fluctuation of the total power generation of the new energy station in the system is evaluated according to the operation capacity of the new energy station of the next day and the two-dimensional fluctuation threshold table.

[0012] Combined with the load prediction data and the evaluation result, a system frequency modulation capacity demand time sequence is obtained.

[0013] As a preferred scheme of the power system frequency modulation capacity estimation method, the two-dimensional fluctuation threshold table of power generation of the new energy station comprises:

[0014] The number of elements in the fluctuation sample set is counted.

[0015] All elements in the fluctuation sample set are sorted in a first order to obtain a new sequence.

[0016] A significance level is set, the number of selected samples is determined according to the significance level, and the two-dimensional fluctuation threshold of the power generation of the new energy station is calculated.

[0017] The beneficial effects of the preferred technical scheme are that the month-hour two-dimensional power fluctuation threshold table of the new energy station is constructed, and the time sequence fluctuation characteristics of the new energy generation can be finely characterized.

[0018] As a preferred scheme of the power system frequency modulation capacity estimation method, the evaluation of the fluctuation of the total power generation of the new energy station in the system comprises:

[0019] The actual operation capacity of each new energy station of the next day is obtained.

[0020] According to the month and hour of the operation date, the fluctuation threshold of each station is extracted from the two-dimensional fluctuation threshold table.

[0021] The actual operation capacity and the fluctuation threshold of each station are calculated to obtain the fluctuation of the total power generation of the new energy station in the system.

[0022] As a preferred scheme of the power system frequency modulation capacity estimation method, the obtaining of the system frequency modulation capacity demand time sequence comprises:

[0023] The load prediction data of the next day is obtained.

[0024] The frequency modulation capacity demand caused by the load fluctuation is calculated according to the load prediction data.

[0025] The frequency modulation capacity demand caused by load fluctuation is added to the total power fluctuation of new energy to obtain a time sequence of system frequency modulation capacity demand.

[0026] The beneficial effect of the preferred technical solution is that the temporal and spatial complementary effects of fluctuation characteristics of different stations can be considered, and the fluctuation level of total new energy output of a provincial power grid can be accurately estimated.

[0027] As a preferred scheme of the power system frequency modulation capacity estimation method, the actual operation capacity of each new energy station on the next day is obtained by:

[0028] In the actual operation stage, the completed next-day load time sequence prediction is obtained according to the time node of developing frequency modulation capacity demand evaluation;

[0029] The actual operation capacity of each new energy station on the next day is obtained according to the station maintenance and production plan.

[0030] As a preferred scheme of the power system frequency modulation capacity estimation method, the first processing of the historical operation data of the new energy station includes:

[0031] The rated capacity and actual power generation data of the new energy station are obtained;

[0032] The power difference value of adjacent time points in the actual power generation data is calculated, and the power difference value is divided by the rated capacity to obtain a fluctuation index.

[0033] As a preferred scheme of the power system frequency modulation capacity estimation method, the first processing of the historical operation data of the new energy station includes:

[0034] The annual fluctuation data of a single station is grouped according to months and hours, and then the fluctuation sample set of the station k in the month m and the hour h is obtained.

[0035] In a second aspect, the present application provides a power system frequency modulation capacity estimation system, comprising:

[0036] The sample processing module is configured to perform first processing on the historical operation data of the new energy station to obtain a two-dimensional fluctuation sample set;

[0037] The threshold table calculation module is configured to obtain a two-dimensional fluctuation threshold table of the power generation of the new energy station based on the fluctuation sample set;

[0038] The fluctuation evaluation module is configured to evaluate the fluctuation of the total power generation of the new energy station in the system according to the operation capacity of the new energy station on the next day and the two-dimensional fluctuation threshold table in the actual operation stage.

[0039] A frequency modulation capacity demand calculation module is configured to obtain a system frequency modulation capacity demand time sequence in combination with load prediction data and the result of the evaluation.

[0040] In a third aspect, the present application provides an electronic device comprising a memory and a processor; the memory is configured to store computer executable instructions, and the processor is configured to implement the steps of the power system frequency modulation capacity estimation method when executing the computer executable instructions.

[0041] In a fourth aspect, the present application provides a computer readable storage medium storing computer executable instructions, and the computer executable instructions are configured to implement the steps of the power system frequency modulation capacity estimation method when executed by a processor.

[0042] Compared with the prior art, the present application has the following beneficial effects: the present application provides a power system frequency modulation capacity estimation method, system, device and medium, and by establishing a month-hour double-dimensional power fluctuation threshold parameter table of a new energy station, fine modeling of the fluctuation characteristics of wind and light and other new energy power generation is realized, and the power fluctuation characteristics in different seasons and different time periods can be accurately reflected. Based on this, the proposed provincial grid new energy total power fluctuation calculation method fully considers the time-space complementary effect between stations, and can more accurately evaluate the power system frequency modulation capacity demand. Compared with the traditional method which only considers load fluctuation, the present application not only avoids the risk of insufficient frequency modulation capacity reservation, but also prevents resource waste caused by excessive capacity configuration, and improves the economy of frequency modulation resource utilization while ensuring the stability of the power grid frequency. In addition, the modeling process of the present application is stable and reliable, the physical meaning of the parameters is clear, and it can flexibly cope with changes in new energy installed capacity and development needs of new power systems, and provides reliable technical support for provincial grid dispatching. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiment description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without any creative effort.

[0044] Figure 1 The overall flow logic diagram of the power system frequency modulation capacity estimation method described in an embodiment of the present application.

[0045] Figure 2 The power system frequency modulation capacity estimation input and output schematic diagram of the power system frequency modulation capacity estimation method described in an embodiment of the present application.

[0046] Figure 3 The 7-month photovoltaic power station S1 power fluctuation scatter plot of the power system frequency modulation capacity estimation method described in an embodiment of the present application.

[0047] Figure 4 The power system frequency modulation capacity estimation method for an embodiment of the application, system 7, net load fluctuation on July 1, and frequency modulation capacity schematic diagram considering new energy fluctuation. DETAILED DESCRIPTION

[0048] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the protection scope of the present application.

[0049] Embodiment 1, refer to Figures 1-2 For an embodiment of the present application, a power system frequency modulation capacity estimation method is provided, which has strong modeling stability and model interpretability based on historical data, and has good adaptability to the changes of the number and on-line capacity of new energy stations in the provincial power grid operation stage. Using the modeling method of the present application, the provincial power grid containing high proportion of wind and light stations can realize the rapid estimation of the power system frequency modulation capacity, guide the dispatching operation and assist the demand analysis of the auxiliary service market. As shown in Figure 1 The specific steps include the following steps:

[0050] S100: first processing the historical operation data of the new energy station to obtain a double-dimensional fluctuation sample set;

[0051] S200: based on the fluctuation sample set, obtaining a double-dimensional fluctuation threshold table of the power generation of the new energy station;

[0052] S300: in the actual operation stage, according to the operation capacity of the new energy station of the next day and the double-dimensional fluctuation threshold table, the fluctuation of the total power generation of the new energy station in the system is evaluated;

[0053] S400: combining the load prediction data and the evaluation result, obtaining the system frequency modulation capacity demand time sequence.

[0054] It should be noted that the present application provides a power system frequency modulation capacity estimation method, system, device and medium, by establishing a month-hour double dimension power fluctuation threshold parameter table of new energy station, the fine modeling of wind and light and other new energy power generation fluctuation characteristics is realized, the power fluctuation characteristics of different seasons and different time periods can be accurately reflected. Based on this, the provincial power grid new energy total power fluctuation calculation method is put forward, which fully considers the time and space complementary effect between stations, and can more accurately evaluate the power system frequency modulation capacity demand. Compared with the traditional method of only considering load fluctuation, the present application not only avoids the risk of insufficient frequency modulation capacity reservation, but also prevents the waste of resources caused by excessive capacity configuration, while ensuring the stability of power grid frequency, improves the economy of frequency modulation resource utilization. In addition, the modeling process of the present application is stable and reliable, the physical meaning of the parameters is clear, and it can flexibly cope with the change of new energy installed capacity and the development demand of new type power system, and provides reliable technical support for provincial power grid dispatching.

[0055] As Figure 2 shown is an input and output schematic diagram of power system frequency modulation capacity estimation, the process is divided into two stages: ① modeling stage: based on historical power generation data, the power fluctuation characteristics of each new energy station are modeled; ② application stage, the system frequency modulation capacity demand time sequence of the provincial power grid is calculated for the operation day. The specific implementation of the power system frequency modulation capacity estimation method provided by the embodiment will be described below in combination with Figure 1 and Figure 2 .

[0056] In the embodiments of the present application, the above step S100 performs first processing on the historical operation data of the new energy station to obtain a double-dimensional fluctuation sample set, including:

[0057] Specifically, the rated capacity and the actual power generation data of the new energy station are obtained; the power difference between adjacent time points in the actual power generation data is calculated, and the power difference is divided by the rated capacity to obtain the fluctuation unit value, which is expressed by the formula:

[0058]

[0059] Where, B i (t) represents the rated capacity of station i, P i (t) represents the actual power generation of station i at time t.

[0060] Specifically, the annual fluctuation data of a single station is grouped according to month and hour, and then the double-dimensional fluctuation sample set of station k in month m and hour h is obtained :

[0061]

[0062] Exemplarily, taking January and 9 o'clock as an example, the fluctuation amount samples belonging to January and the time period of 9:00 to 9:55 in a day in all samples of a certain new energy station k are divided into a subset where x k (1,9) is each fluctuation amount sample.

[0063] In an optional embodiment, the step of the first processing can also be to process the historical operation data by using a statistical method of a sliding time window, first set an appropriate time window length, calculate the maximum value, minimum value and standard deviation of the power and other statistical characteristics in each window, and then divide the statistical quantities by the rated capacity to obtain the normalized fluctuation characteristics.

[0064] In another optional embodiment, the step of the first processing can also be to introduce a wavelet transform or other time-frequency analysis method to process the original power data. By performing multi-scale decomposition on the historical power generation sequence, the power fluctuation components at different time scales are extracted, and the fluctuation characteristic values of each component are calculated.

[0065] It should be noted that the step S100 realizes the standardized processing of the original power generation data by preprocessing the historical operation data of the new energy station, and eliminates the influence of the capacity difference between different stations. At the same time, the month-hour double-dimensional grouping method is adopted, which fully retains the seasonal and time period characteristics of new energy power generation, so that the subsequent modeling can more accurately reflect the actual fluctuation law.

[0066] In the embodiment of the present application, the step S200 of obtaining the double-dimensional fluctuation threshold table of the power generation of the new energy station based on the fluctuation amount sample set includes:

[0067] Count the number N of elements of the fluctuation amount sample set;

[0068] Sort all elements in the fluctuation amount sample set in a first order (from large to small) to obtain a new sequence A={a1, a2,..., a N};

[0069] Set a significance level a, determine the number of selected samples I=int(N x a) according to the significance level, and calculate the double-dimensional fluctuation threshold of the power generation of the new energy station, where int(·) represents the upward rounding function.

[0070] Specifically, the month-hour double-dimensional fluctuation threshold v k (m,h) of the power generation of the station k in the mth month and hth hour is calculated, and the calculation formula is:

[0071]

[0072] It should be noted that the monthly-hour fluctuation threshold table of all new energy stations will be used as the basic model parameter for the system frequency modulation capacity demand evaluation calculation in the running stage.

[0073] It should be noted that the step S200 innovatively determines the fluctuation threshold of each period by using the ranking statistical method, and realizes reasonable capture of extreme fluctuation by setting the significance level. Compared with the traditional method of using fixed proportion or simple statistics, this refined modeling significantly improves the accuracy of fluctuation characteristic representation, and provides reliable basic parameters for system-level evaluation.

[0074] In the embodiment of the present application, the step S300 in the actual running stage evaluates the fluctuation of the total power generation of the new energy stations in the system according to the running capacity of the new energy stations on the next day and the double-dimensional fluctuation threshold table, which includes:

[0075] Specifically, in the actual running stage, the time node for carrying out the frequency modulation capacity demand evaluation is y year m month d day, it is known that: the load time series prediction L(y, m, d) = [l1, l2,..., ln] of the next day has been completed, and the actual running capacity S 24 (y, m, d) of each new energy station k on the next day is obtained according to the station maintenance and production plan. k

[0076] Specifically, the fluctuation of the total power generation of the new energy stations in the system is evaluated, which includes:

[0077] The number of new energy stations running in the system is K, and the actual running capacity of each new energy station on the next day is obtained.

[0078] According to the month and hour of the running date, the fluctuation threshold of each station is extracted from the double-dimensional fluctuation threshold table, and the fluctuation threshold of m month h hour in the table is v k (m, h);

[0079] The actual running capacity and the fluctuation threshold of each station are calculated to obtain the fluctuation of the total power generation of the new energy stations in the system, which is expressed by the formula:

[0080]

[0081] It should be noted that the step S300 realizes dynamic evaluation of the total power fluctuation of the system by combining the running capacity plan of the new energy stations on the next day and the established fluctuation threshold table, fully considers the time and space complementary effect of the fluctuation characteristics of different stations, and can more accurately predict the overall fluctuation level of the system caused by the new energy grid connection.

[0082] In the embodiment of the present application, the step S400 combines the load prediction data and the evaluation result to obtain the system frequency modulation capacity demand time series, which includes:​

[0083] obtaining next-day load forecasting data;

[0084] calculating frequency modulation capacity demand caused by load fluctuation according to the load forecasting data;

[0085] adding the frequency modulation capacity demand caused by load fluctuation to the total power fluctuation of new energy to obtain a system frequency modulation capacity demand time sequence.

[0086] Specifically, the 24-hour system frequency modulation capacity demand time sequence is denoted as F(y, m, d) = [f1, f2,..., fn], and the calculation formula is as follows: 24 ], the calculation formula is as follows:

[0087]

[0088] wherein p is a system frequency modulation capacity coefficient required by load uncertainty, and is usually taken as 2% according to the grid regulation; and λ is a system frequency modulation margin coefficient considering new energy power fluctuation, and the recommended value is 1.1.

[0089] It should be noted that the step S400 realizes comprehensive consideration of the system frequency modulation capacity demand by combining the new energy fluctuation evaluation result with the load forecasting data, which not only avoids the problem of insufficient capacity reservation caused by ignoring new energy fluctuation in the traditional method, but also prevents resource waste caused by excessive conservative configuration. The finally generated frequency modulation capacity demand time sequence can be directly used to guide grid dispatching operation and auxiliary service market transaction, which improves the operation economy while ensuring the system safety.

[0090] Embodiment 2, referring to Figure 3 and Figure 4 Based on the previous embodiment, the present embodiment provides an application example of a power system frequency modulation capacity estimation method, system, device and medium, which verifies and illustrates the technical effects adopted in the method.

[0091] This embodiment illustrates the calculation process of the method provided by the present application by a simple example. It is assumed that a research area R has 4 new energy stations, including 2 wind power stations (W1, W2) and 2 photovoltaic power stations (S1, S2);

[0092] The modeling process is illustrated by taking the photovoltaic power station S1 as an example. The historical data sampling interval is 5 minutes per record point, and there are 105,120 power sampling points in a year. First, the data preprocessing process is performed: the power difference between adjacent two record points is calculated, and divided by the actual operating installed capacity of the power station in the month to form a power fluctuation feature sample set without dimension influence. Taking July as an example, the power fluctuation sample scatter plot with the clock in the day as the horizontal axis is shown in Figure 3 It can be seen that the power fluctuation is located in the interval [-0.6, 0.6] and is symmetrically distributed.

[0093] As above, the sample set of the power fluctuation of photovoltaic power station S1 in each month is established. In the above example, the total number of samples N=372 is obtained for each hour in July. Taking the sample set at 11:00 as an example The calculation is performed as follows: taking the significance level a=0.05, the corresponding critical sample number is selected according to the ranking rule:

[0094] I=int[Nx a]=int[372x 0.05]=19

[0095] The samples in the sample set are ranked from large to small, and the first 19 samples are as follows:

[0096] [0.58240834, 0.54699613, 0.52567825, 0.51523962, 0.43424071, 0.42591614, 0.39076813, 0.36883364, 0.36667549, 0.35879143, 0.35293337, 0.35266915, 0.3456219, 0.34077696, 0.33919132, 0.33082276, 0.32426001, 0.32285058, 0.32016388]

[0097] The average value of the above 19 samples is taken, and the fluctuation threshold of photovoltaic power station S1 in the period of 11:00-12:00 on any day in July is obtained as follows

[0098] The above calculation process is repeated, and all months m e [1, 12] and hours h e [1, 24] are traversed, and a complete month-hour fluctuation threshold table of photovoltaic power station S1 is constructed as shown in Table 1.

[0099] Table 1: Month-hour fluctuation threshold table of photovoltaic power station S1.

[0100]

[0101]

[0102] The same method is used to calculate the power fluctuation threshold table of all new energy power stations (including all wind farms and photovoltaic power stations), and the statistical modeling is completed. Table 2 shows the calculated 24-hour fluctuation threshold table of four new energy power stations in July.

[0103] Table 2: 24-hour fluctuation threshold table of each new energy power station in July.

[0104] ​

[0105]

[0106] Take July 1 as an example to illustrate the calculation process of the frequency modulation capacity requirement of the system. The operating capacity of the wind farms (W1, W2) and photovoltaic power stations (S1, S2) in the system on that day is shown in Table 3. Among them, the wind farm W2 is shut down after 11:00 due to maintenance. Take 11:00 and 12:00 as examples to illustrate the frequency modulation capacity stage process. According to Table 1, the fluctuation threshold of the four fields at 11:00 on July 1 is shown in Table 4.

[0107] Table 3: Installed capacity and operating state of each new energy field on July 1.

[0108] New energy station Installed capacity (MW) Operating state [CD AT W1] 140 Full opening [CDATAW2] 67 After 11 o'clock, close

[00100] S1 23 Full opening [S2] 68 Full opening

[0109] Table 4: Fluctuation threshold of each new energy field at 11:00 on July 1.

[0110] New energy station Fluctuation threshold [CD AT W1] 0.0729 [CD AT W2] 0.0664 <S1> 0.3971 [S2] 0.2688

[0111] According to the formula: new energy fluctuation required frequency modulation capacity requirement The frequency modulation capacity of the system under the influence of new energy fluctuation at 11:00 is:

[0112]

[0113] Similarly, the fluctuation threshold at 12:00 on July 1 is shown in Table 5, where the wind farm W2 is shut down due to maintenance.

[0114] Table 5: Fluctuation threshold of each new energy field at 12:00 on July 1.

[0115] New energy station Fluctuation threshold [CD AT W1] 0.0640 <S1> 0.4668 [S2] 0.3101

[0116] According to the formula, the frequency modulation capacity required by the system under the influence of new energy fluctuation at 12:00 on July 1 is:

[0117]

[0118] The load prediction value of the system for 24 hours on that day is: L(y, m, d) = [l1, l2,..., l 24 ] = [130, 126, 124, 122, 130, 144, 170, 200, 230, 250, 240, 220, 210, 200, 204, 216, 230, 260, 300, 330, 340, 310, 260, 200]. According to the formula Calculate the total frequency modulation capacity requirement of the system, and get f i=[38, 36, 37, 34, 36, 38, 43, 50, 61, 69, 73, 69, 69, 69, 75, 72, 67, 67, 75, 76, 78, 74, 65, 52].

[0119] According to the actual measured net load of the power grid on July 1 (the algebraic sum of the measured load and the measured new energy output), the 5-minute fluctuation amount is calculated, and compared with the predicted frequency modulation capacity as shown in the following table. Figure 4 It can be seen from Figure 4 that the proposed frequency modulation capacity estimation method well meets the regulation demand of the system net load fluctuation, effectively avoids the capacity redundancy problem, and significantly improves the economy of the frequency modulation resource.

[0120] In embodiment 3, a power system frequency modulation capacity estimation system is provided, comprising:

[0121] A sample processing module is configured to perform first processing on historical operation data of the new energy station to obtain a two-dimensional fluctuation sample set.

[0122] A threshold table calculation module is configured to obtain a two-dimensional fluctuation threshold table of the power generation capacity of the new energy station based on the fluctuation sample set.

[0123] A fluctuation amount evaluation module is configured to evaluate the fluctuation amount of the total power generation capacity of the new energy station in the system according to the operation capacity of the new energy station on the next day and the two-dimensional fluctuation threshold table in the actual operation stage.

[0124] A frequency modulation capacity demand calculation module is configured to obtain a time sequence of the frequency modulation capacity demand of the system in combination with the load prediction data and the evaluation result.

[0125] It should be noted that the technical scheme of the power system frequency modulation capacity estimation system belongs to the same concept as the technical scheme of the power system frequency modulation capacity estimation method described above. The technical scheme of the power system frequency modulation capacity estimation system in this embodiment is not described in detail, and the description of the technical scheme of the power system frequency modulation capacity estimation method can be referred to.

[0126] The above-mentioned unit modules can be embedded in or independent of the processor in the electronic device in hardware form, or can be stored in the memory in the electronic device in software form, so as to be called and executed by the processor to perform the operations corresponding to the above-mentioned modules.

[0127] The embodiment also provides an electronic device including a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. The processor of the electronic device is configured to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The communication interface of the electronic device is configured to perform wired or wireless communication with an external terminal. The wireless communication can be achieved through WIFI, a carrier network, NFC (Near Field Communication) or other technologies. The computer program is executed by the processor to implement a power system frequency modulation capacity estimation method. The display screen of the electronic device can be a liquid crystal display screen or an electronic ink display screen. The input device of the electronic device can be a touch layer overlaid on the display screen, or a key, trackball or touchpad arranged on the shell of the electronic device, or an external keyboard, touchpad or mouse, etc.

[0128] The embodiment also provides a computer readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the method proposed in the above embodiment.

[0129] The storage medium proposed in the embodiment belongs to the same inventive concept as the method proposed in the above embodiment. The technical details not described in the embodiment can be referred to the above embodiment, and the embodiment has the same beneficial effects as the above embodiment.

[0130] From the above description about the embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software and necessary universal hardware, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a floppy disk, a ROM, a RAM, a FLASH, a hard disk or an optical disc, etc., and includes a number of instructions to make an electronic device (which can be a personal computer, a server or a network device, etc.) execute the method of the embodiments of the present application.

[0131] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present application but not limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the present application, and all of them should be covered in the scope of the claims of the present application.

[0132] Those skilled in the art will appreciate that embodiments of the application can be situated in the form of a method, a system or a computer program product. Accordingly, the application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the application can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) having computer-usable program code embodied in the medium. The aspects of the embodiments of the application can be implemented in various computer languages.

[0133] The application is described with reference to the flowchart and / or block diagram illustrations of the methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart and / or block diagrams, and combinations of blocks in the flowchart and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks.

[0134] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks.

[0135] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks. Figure 1 one or more functions specified in the flowchart and / or block diagram block or blocks.

[0136] While preferred embodiments of the application have been described, modifications and alterations thereto will occur to those skilled in the art upon reading the preceding description. It is intended to include all such modifications and alterations insofar as they come within the scope of the basic inventive concepts disclosed herein. Accordingly, the following claims are intended to embrace all such alterations and modifications as fall within the scope of the application.

[0137] Obviously, many modifications and variations of the present application are possible in light of the above teachings. It is, therefore, to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

Claims

1. A method for estimating frequency regulation capacity of a power system, characterized in that: include: The historical operation data of new energy stations are first processed to obtain a two-dimensional fluctuation sample set; Based on the fluctuation amount sample set, obtaining a two-dimensional fluctuation threshold table of the power generation power of the new energy station; During the actual operation phase, the fluctuation of the total power generation of the new energy stations in the system is evaluated based on the operating capacity of the new energy stations on the next day and the two-dimensional fluctuation threshold table; Combining the load forecast data with the evaluation results, a time series of system frequency regulation capacity demand is obtained.

2. A method for estimating frequency regulation capacity of a power system according to claim 1, characterized in that: The dual-dimensional fluctuation threshold table for obtaining the power generation power of the new energy station includes: Counting the number of elements in the fluctuation sample set; Sorting all elements in the fluctuation sample set in the first order to obtain a new sequence; A significance level is set, the number of samples to be selected is determined based on the significance level, and the two-dimensional fluctuation threshold of the power generation power of the new energy station is calculated.

3. A method for estimating frequency regulation capacity of a power system according to claim 2, characterized in that: The evaluation of the fluctuation of the total power generation of the new energy stations in the system includes: Obtain the actual operating capacity of each new energy station on the next day; Extracting the fluctuation threshold value of each station from the dual-dimensional fluctuation threshold value table according to the month and hour of the operation date; A first calculation is performed on the actual operating capacity and the fluctuation threshold of each station to obtain the fluctuation amount of the total generated power of the new energy stations in the system.

4. A method for estimating frequency regulation capacity of a power system according to claim 3, characterized in that: The obtaining of the system frequency modulation capacity demand time series includes: Obtain next day's load forecast data; Calculate frequency regulation capacity requirements caused by load fluctuations based on load forecast data; The frequency regulation capacity demand caused by load fluctuation is added to the total power fluctuation of renewable energy to obtain the system frequency regulation capacity demand time series.

5. The method for estimating the frequency regulation capacity of a power system according to claim 3, wherein: The actual operating capacity of each new energy station on the next day is obtained as follows: During the actual operation phase, the completed next-day load time series forecast is obtained based on the time node of the frequency regulation capacity demand assessment; The actual operating capacity of each new energy station the next day is obtained based on the station maintenance and commissioning plan.

6. A method for estimating frequency regulation capacity of a power system according to claim 1, characterized in that: The first processing of the historical operation data of the new energy station includes: Obtain the rated capacity and actual power generation data of new energy stations; The power difference between adjacent time points in the actual generated power data is calculated, and the power difference is divided by the rated capacity to obtain a per-unit value of the fluctuation amount.

7. A method for estimating frequency regulation capacity of a power system according to claim 6, characterized in that: The first processing of the historical operation data of the new energy station further includes: The annual fluctuation data of a single station are grouped by month and hour, and then a set of fluctuation samples of station k in two dimensions of month m and hour h is obtained.

8. A power system frequency regulation capacity estimation system, applying a power system frequency regulation capacity estimation method according to any one of claims 1 to 7, characterized in that: include: A sample processing module is used to perform a first processing on the historical operation data of the new energy station to obtain a two-dimensional fluctuation quantity sample set; A threshold table calculation module is used to obtain a two-dimensional fluctuation threshold table of the power generation power of the new energy station based on the fluctuation amount sample set; A fluctuation assessment module is used to assess the fluctuation of the total power generation of the new energy stations in the system according to the operating capacity of the new energy stations on the next day and the two-dimensional fluctuation threshold table during the actual operation phase; The frequency regulation capacity demand calculation module is used to combine the load forecast data and the evaluation results to obtain the system frequency regulation capacity demand time series.

9. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store computer-executable instructions, and the processor implements the steps of the method for estimating the frequency regulation capacity of a power system according to any one of claims 1 to 7 when executing the computer-executable instructions.

10. A computer-readable storage medium having computer-executable instructions stored thereon, characterized in that: When the computer executable instructions are executed by a processor, the steps of the method for estimating the frequency regulation capacity of a power system according to any one of claims 1 to 7 are implemented.

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