A water and wind scenery complementary system power abandonment simulation method and device and electronic equipment

Abstract

The application discloses a water-wind-solar complementary system power abandonment simulation method and device and electronic equipment, at least one key risk factor is acquired, a multi-dimensional joint distribution function and a conditional distribution function of a water-wind-solar complementary system power abandonment rate are established, further, a multi-dimensional conditional expected risk assessment model and a multi-dimensional conditional most possible risk assessment model are respectively established, and an expected value and a most possible value of the water-wind-solar complementary system power abandonment rate are obtained through the models. The application identifies the influence and degree of the key risk factor on the water-wind-solar complementary scheduling power abandonment rate, establishes the multi-dimensional conditional expected and multi-dimensional conditional most possible risk assessment model, reveals the water-wind-solar complementary system power abandonment evolution law under different resource thresholds, realizes the precise simulation of the multi-energy complementary system daily power abandonment rate, and provides a new way for reasonably evaluating the water-wind-solar complementary system power abandonment risk assessment.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of multi-purpose complementary dispatching risk management, and particularly relates to a water-wind-solar complementary system curtailment simulation method and device and electronic equipment. BACKGROUND

[0002] Based on the complementarity of water, wind and solar and the regulation ability of hydropower, the scale of wind and solar is continuously expanding, and the proportion of renewable energy penetrating into the power grid is increasing, which reduces the consumption of traditional energy. However, the randomness and volatility of wind and solar are also increasing, and under the existing regulation limit of hydropower, the curtailment rate of the water-wind-solar system also increases. Therefore, it is particularly important to explore the curtailment law of the water-wind-solar complementary system. In the long-term complementary operation of the water-wind-solar system, the curtailment law cannot be accurately described, which leads to deviation of the medium and long-term generation plan, and the overall benefit of the complementary system is reduced. Therefore, how to effectively simulate the curtailment law of the water-wind-solar complementary system has become an important scientific problem.

[0003] At present, most of the researches on medium and long-term scheduling curtailment risk assessment of the water-wind-solar system focus on "S-type" curve calculation or nested short-term scheduling model, and there are few researches on curtailment risk under the condition of multiple variables derived from theoretical analysis, and there is also a lack of application analysis of engineering practical cases. SUMMARY

[0004] Therefore, the embodiments of the present application provide a water-wind-solar complementary system curtailment simulation method and device and electronic equipment to solve the technical problems that the curtailment risk of the water-wind-solar complementary system is difficult to depict, and the short-term risk is difficult to consider in medium and long-term scheduling in the prior art.

[0005] The technical solutions provided by the present application are as follows:

[0006] In a first aspect, the embodiments of the present application provide a water-wind-solar complementary system curtailment simulation method, which comprises: acquiring at least one key risk factor, the key risk factor being used to reflect the influence on the curtailment rate of the water-wind-solar complementary system; establishing a multi-dimensional joint distribution function of the curtailment rate of the water-wind-solar complementary system based on each key risk factor, and determining a conditional distribution function of the curtailment rate of the water-wind-solar complementary system based on the multi-dimensional joint distribution function; establishing a multi-dimensional conditional expected risk assessment model and a multi-dimensional conditional most likely risk assessment model based on the conditional distribution function; and obtaining an expected value and a most likely value of the curtailment rate of the water-wind-solar complementary system through the multi-dimensional conditional expected risk assessment model and the multi-dimensional conditional most likely risk assessment model based on the curtailment rate of the water-wind-solar complementary system.

[0007] With reference to the first aspect, in a possible implementation manner of the first aspect, after the at least one key risk factor is acquired, the method further includes: quantitatively processing the curtailment rate of the water-wind-solar complementary system and each key risk factor.

[0008] With reference to the first aspect, in another possible implementation manner of the first aspect, the curtailment rate includes a wind curtailment rate, a solar curtailment rate, and a wind-solar curtailment rate; the quantitatively processing the curtailment rate of the water-wind-solar complementary system includes: acquiring a wind power generation amount, a solar power generation amount, and a wind-solar curtailment amount of the water-wind-solar complementary system; determining a wind curtailment amount and a solar curtailment amount of the water-wind-solar complementary system based on the wind power generation amount, the solar power generation amount, and the wind-solar curtailment amount; quantitatively processing the wind curtailment rate based on the wind curtailment amount and the wind power generation amount; quantitatively processing the solar curtailment rate based on the solar curtailment amount and the solar power generation amount; quantitatively processing the wind-solar curtailment rate based on the wind power generation amount, the solar power generation amount, and the wind-solar curtailment amount.

[0009] With reference to the first aspect, in still another possible implementation manner of the first aspect, the establishing the multi-dimensional joint distribution function of the curtailment rate of the water-wind-solar complementary system based on each key risk factor includes: determining a correlation between each key risk factor and the curtailment rate of the water-wind-solar complementary system; and establishing the multi-dimensional joint distribution function based on the correlation and a preset connection function.

[0010] With reference to the first aspect, in still another possible implementation manner of the first aspect, the method further includes: adjusting an available water amount of the water-wind-solar complementary system based on the expected value and the most likely value.

[0011] The second aspect, the embodiment of the present application provides a water-wind-solar complementary system curtailment simulation device, the water-wind-solar complementary system curtailment simulation device includes: an acquisition module, used for acquiring at least one key risk factor, the key risk factor is used for reflecting the influence on the curtailment rate of water-wind-solar complementary system;First establishment module, for establishing the multi-dimensional joint distribution function of the curtailment rate of the water-wind-solar complementary system based on each key risk factor, and determining the conditional distribution function of the curtailment rate of the water-wind-solar complementary system based on the multi-dimensional joint distribution function;Second establishment module, for establishing a multi-dimensional conditional expected risk assessment model and a multi-dimensional conditional most likely risk assessment model based on the conditional distribution function;Evaluation module, for obtaining the expected value and the most likely value of the curtailment rate of the water-wind-solar complementary system based on the curtailment rate of the water-wind-solar complementary system, through the multi-dimensional conditional expected risk assessment model and the multi-dimensional conditional most likely risk assessment model.

[0012] With reference to the second aspect, in a possible implementation manner of the second aspect, the apparatus further includes a quantization processing module configured to quantize the water-wind-solar complementary system curtailment rate and each of the key risk factors.

[0013] With reference to the second aspect, in another possible implementation manner of the second aspect, the curtailment rate includes a wind curtailment rate, a solar curtailment rate, and a wind-solar curtailment rate; and the quantization processing module includes: an acquisition sub-module configured to acquire a wind power generation amount, a solar power generation amount, and a wind-solar curtailment amount of the water-wind-solar complementary system; a first determination sub-module configured to determine the wind curtailment amount and the solar curtailment amount of the water-wind-solar complementary system based on the wind power generation amount, the solar power generation amount, and the wind-solar curtailment amount; a first quantization processing sub-module configured to quantize the wind curtailment rate based on the wind curtailment amount and the wind power generation amount; a second quantization processing sub-module configured to quantize the solar curtailment rate based on the solar curtailment amount and the solar power generation amount; and a third quantization processing sub-module configured to quantize the wind-solar curtailment rate based on the wind power generation amount, the solar power generation amount, and the wind-solar curtailment amount.

[0014] In a third aspect, an embodiment of the present application provides a computer readable storage medium, which stores computer instructions, and the computer instructions are used to make a computer execute the water-wind-solar complementary system curtailment simulation method according to the first aspect and any one of the implementation manners of the first aspect.

[0015] In a fourth aspect, an embodiment of the present application provides an electronic device, which includes a memory and a processor, the memory and the processor are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to execute the water-wind-solar complementary system curtailment simulation method according to the first aspect and any one of the implementation manners of the first aspect.

[0016] The technical solution provided by the present application has the following effects:

[0017] The water-wind-solar complementary system curtailment simulation method provided by the embodiment of the present application identifies the influence and degree of the key risk factors on the water-wind-solar complementary scheduling curtailment rate, establishes a multi-dimensional conditional expectation and multi-dimensional conditional most likely risk assessment model, reveals the water-wind-solar complementary system curtailment evolution law under different resource thresholds, realizes the accurate simulation of the daily curtailment rate of the multi-energy complementary system, and provides a new way for reasonably evaluating the water-wind-solar complementary system curtailment risk assessment. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the specific embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the specific embodiments or the prior art description. Obviously, the drawings described below are some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0019] Figure 1 is a flow chart of a water, wind and light complementary system abandoned electricity simulation method according to an embodiment of the present application;

[0020] Figure 2 is a flow chart of a water, wind and light complementary system abandoned electricity simulation method considering wind and light fluctuations and water power regulation capacity according to an embodiment of the present application;

[0021] Figure 3A is a schematic diagram of abandoned wind rate evaluation result based on a multi-dimensional condition most likely risk evaluation model according to an embodiment of the present application;

[0022] Figure 3B is a schematic diagram of abandoned wind rate evaluation result based on a multi-dimensional condition expected risk evaluation model according to an embodiment of the present application;

[0023] Figure 3C is a schematic diagram of abandoned wind rate evaluation result based on a linear function according to an embodiment of the present application;

[0024] Figure 4 is a structural block diagram of a water, wind and light complementary system abandoned electricity simulation device according to an embodiment of the present application;

[0025] Figure 5 is a structural schematic diagram of a computer readable storage medium according to an embodiment of the present application;

[0026] Figure 6 is a structural schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the following will combine the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are some 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 are within the protection scope of the present application.

[0028] It is to be understood that the terms "first", "second", and the like, used in the description and the claims of the application, as well as the above-described drawings, are used to distinguish similar objects, and are not necessarily used to describe a particular sequential or chronological order. It should be understood that the data thus used can be interchanged, where appropriate, so that the embodiments of the application described herein can be carried out in other than the order shown or described herein. Furthermore, the terms "comprising" and "having", as well as any variations thereof, are intended to cover non-exclusive inclusion, for example, processes, methods, systems, products, or devices that include a series of steps or units not necessarily limited to those clearly listed, but can include other steps or units not clearly listed or inherent to such processes, methods, products, or devices.

[0029] The embodiment of the application provides a water, wind and light complementary system abandoned power simulation method, as shown in the figure, the method comprises the following steps: Figure 1

[0030] Step 101: Obtain at least one key risk factor.

[0031] The key risk factor is used for reflecting the influence on the abandoned power rate of the water, wind and light complementary system, and can be water power, wind and light output, wind and light fluctuation and water power regulation capacity.

[0032] Specifically, the reasons causing the abandoned power of the water, wind and light complementary system mainly include that the wind and light output fluctuation is large and the water power regulation capacity is insufficient. Therefore, in the embodiment of the application, the key factor causing the abandoned power of the water, wind and light complementary system can be wind and light fluctuation and water power.

[0033] The relationship between the abandoned power rate of the water, wind and light complementary system and the key risk factor is shown in the following relationship formula (1):

[0034] γ=F(x1,x2…,x n ) (1)

[0035] In the formula, γ represents the abandoned power rate; x1, x2, …, x n represent the key risk factor.

[0036] Step 102: Based on each key risk factor, a multi-dimensional joint distribution function of the abandoned power rate of the water, wind and light complementary system is established, and a conditional distribution function of the abandoned power rate of the water, wind and light complementary system is determined based on the multi-dimensional joint distribution function.

[0037] Specifically, after the key risk factor is obtained, firstly, the multi-dimensional joint distribution function of the abandoned power rate of the water, wind and light complementary system can be established, and each key risk factor can be connected through the multi-dimensional joint distribution function; further, based on the conditional factor and the connection relationship, the conditional distribution function of the abandoned power rate of the water, wind and light complementary system under different risk conditions can be determined, as shown in the following relationship formula (2):​

[0038] f(γ|X1=x1,…,X n = x n ) (2)

[0039] Step 103: based on the conditional distribution function, a multi-dimensional conditional expected risk assessment model and a multi-dimensional conditional most likely risk assessment model are established.

[0040] The multi-dimensional conditional expected risk assessment model is used to assess the average level of curtailment of the water-wind-solar complementary system, and the multi-dimensional conditional most likely risk assessment model is used to assess the most likely curtailment rate of the water-wind-solar complementary system.

[0041] Specifically, given the input variable X, the expected level of risk rate γ under short-term complementary scheduling. For example, the expected level of curtailment rate under the condition of wind-solar fluctuation and available water power. The multi-dimensional conditional expected risk assessment model can be expressed as the following relationship (3):

[0042]

[0043] In the formula, u X represents the cumulative probability of variable X; u γ represents the cumulative probability of variable γ; F -1 (u γ ) represents the inverse function of the distribution function of variable γ; c(·) represents the multi-dimensional joint distribution probability density function, i.e. the multi-dimensional joint distribution function established in step 102; E(·) represents the expected value.

[0044] Further, given the input variable X, the most likely value of curtailment risk rate γ under short-term complementary scheduling.

[0045] Specifically, under the condition of wind-solar fluctuation and available water power, the curtailment rate is subject to a certain distribution function, and the highest point of the distribution is the solution. That is, the multi-dimensional conditional most likely risk assessment model is the curtailment rate corresponding to the maximum density probability of the conditional distribution function. That is, by taking the first derivative of the solution function (the above relationship (2)), the following relationship (4) can be obtained:

[0046]

[0047] Further, the expression on the left side of the above relationship (4) is shown in the following relationship (5):

[0048]

[0049] In combination with the relationship (5), the above relationship (4) is simplified to obtain the following relationship (6):

[0050]

[0051] In the formula: f' γ (γ) represents the derivative of the curtailment rate density function with respect to the curtailment rate, as shown in the following relationship (7); represents the derivative of the Copula (connection) density function with respect to the cumulative distribution of the curtailment rate, as shown in the following relationship (8):

[0052]

[0053]

[0054] Step 104: Based on the water, wind and light complementary system curtailment rate, through the multi-dimensional conditional expectation risk assessment model and the multi-dimensional conditional most likely risk assessment model, the expected value and the most likely value of the water, wind and light complementary system curtailment rate are obtained.

[0055] Specifically, according to the description of the multi-dimensional conditional expectation risk assessment model and the multi-dimensional conditional most likely risk assessment model in step 103, the average level of the water, wind and light complementary system curtailment rate can be obtained through the multi-dimensional conditional expectation risk assessment model; The most likely curtailment rate of the water, wind and light complementary system, i.e. the most likely value of the water, wind and light complementary system curtailment rate, can be obtained through the multi-dimensional conditional most likely risk assessment model.

[0056] The water, wind and light complementary system curtailment simulation method provided by the embodiment of the application identifies the influence and degree of the key risk factors on the water, wind and light complementary scheduling curtailment rate, establishes a multi-dimensional conditional expectation and multi-dimensional conditional most likely risk assessment model, reveals the evolution law of the water, wind and light complementary system curtailment under different resource thresholds, and realizes the accurate simulation of the daily curtailment rate of the multi-energy complementary system, thereby providing a new way for reasonably evaluating the curtailment risk assessment of the water, wind and light complementary system.

[0057] As an optional implementation manner of the embodiment of the application, after step 101, the method further includes: quantizing the water, wind and light complementary system curtailment rate and each key risk factor.

[0058] First, according to the description of step 101. Quantize the key risk factors: wind and light fluctuation and water power.

[0059] (1) Wind and light fluctuation

[0060] In the water, wind and light daily complementary scheduling, the main reasons for curtailment include large wind and light output fluctuation or insufficient water power regulation. For the daily fluctuation of wind and light output, the standard deviation is generally used to describe, as shown in the following relationship (9):

[0061]

[0062] In the formula, NW(t) represents the wind power output of the water-wind-solar complementary system at the t period; and NS(t) represents the solar power output of the water-wind-solar complementary system at the t period. represents the average wind-solar output in a day; and T represents the number of periods.

[0063] (2) Water power

[0064] As the main energy of the water-wind-solar complementary system, water power has flexibility to smooth wind-solar fluctuations, reduce curtailment of wind and solar power, and increase system power generation benefits. However, water power also has regulation capacity, which can alleviate the curtailment of water-wind-solar system power under a certain water power, and the expression of water power is shown in the following relationship (10):

[0065] N H (t)=k×H(t)×q(t) (10)

[0066] In the formula, N H (t) represents the water power output at the t period; H(t) represents the net water head of the reservoir at the t period; q(t) represents the water flow of the reservoir at the t period; and k represents the reservoir output coefficient.

[0067] Secondly, the curtailment rate of the water-wind-solar complementary system is quantitatively processed, including: obtaining the wind power, the solar power and the curtailment of wind-solar power of the water-wind-solar complementary system; determining the curtailment of wind power and the curtailment of solar power of the water-wind-solar complementary system based on the wind power, the solar power and the curtailment of wind-solar power; quantitatively processing the curtailment rate of wind power based on the curtailment of wind power and the wind power; quantitatively processing the curtailment rate of solar power based on the curtailment of solar power and the solar power; and quantitatively processing the curtailment rate of wind-solar power based on the wind power, the solar power and the curtailment of wind-solar power.

[0068] Among them, the curtailment rate can include the curtailment rate of wind power, the curtailment rate of solar power and the curtailment rate of wind-solar power.

[0069] For a water-wind-solar complementary system, when curtailment of power occurs inevitably during the operation of the water-wind-solar complementary system, the proportion of curtailment of wind power and curtailment of solar power is allocated according to the proportion of wind-solar output at the period.

[0070] Firstly, the curtailment of wind power and the curtailment of solar power of the water-wind-solar complementary system are determined according to the wind power, the solar power and the curtailment of wind-solar power, as shown in the following relationship (11):

[0071]

[0072] In the formula, P W (t) represents the wind power of the water-wind-solar complementary system at the t period; P S (t) represents the solar power of the water-wind-solar complementary system at the t period; and P pc(t) represents the abandoned wind power of the water-wind-solar complementary system in the t period; P pc,W (t) represents the abandoned wind power of the water-wind-solar complementary system in the t period; P pc,S (t) represents the abandoned wind power of the water-wind-solar complementary system in the t period; P

[0073] Secondly, according to the wind power, the photovoltaic power, the abandoned wind power and the abandoned light power, the abandoned wind rate, the abandoned light rate and the abandoned wind-light rate are quantified respectively. Wherein, the quantified abandoned wind rate, the abandoned light rate and the abandoned wind-light rate are respectively shown in the following relationship (12), (13) and (14):

[0074]

[0075]

[0076]

[0077] In the formula: γ W represents the abandoned wind rate; γ S represents the abandoned light rate; γ WS represents the abandoned wind-light rate.

[0078] As an optional implementation of the embodiment of the application, the multi-dimensional joint distribution function of the abandoned power rate of the water-wind-solar complementary system is established based on each key risk factor, comprising: determining the correlation between each key risk factor and the abandoned power rate of the water-wind-solar complementary system; and establishing the multi-dimensional joint distribution function based on the correlation and a preset connection function.

[0079] Specifically, according to the description of step 101, the correlation between each key risk factor and the abandoned power rate of the water-wind-solar complementary system can be determined, that is, the influence degree of each key risk factor on the abandoned power rate of the water-wind-solar complementary system.

[0080] Further, according to the description in step 102, the corresponding multi-dimensional joint distribution function can be constructed by using the correlation and a preset connection function (Copula function), as shown in the following relationship (15):

[0081] f(γ,x1,...,x n )=c(u γ ,u X )×f(γ)×f(x1)×…×f(x n ) (15)

[0082] As an optional implementation of the embodiment of the application, the method further comprises: adjusting the available water quantity of the water-wind-solar complementary system based on the expected value and the most possible value.

[0083] Specifically, after obtaining the expected value and the most possible value of the water-wind-solar complementary system curtailment rate under the condition of multiple risk variables, the available water amount is further adjusted by the size of the value, thereby providing a theoretical basis for improving the resource utilization rate of the complementary system and reducing the curtailment of wind and light.

[0084] By implementing the present application, the evolution law of the water-wind-solar complementary system curtailment under different resource thresholds is disclosed, and the precise simulation of the daily curtailment rate of the multi-energy complementary system is realized.

[0085] In an example, a water-wind-solar complementary system curtailment simulation method considering wind and light fluctuations and water power regulation capacity is provided, as shown in Figure 2 .

[0086] Taking the Guandi water-wind-solar complementary power station on the Yalong River as an example, the historical wind speed, photovoltaic intensity and inflow process in 2016 are input, the optimization method is used for scheduling, and the daily wind curtailment rate and light curtailment rate are obtained. Based on the wind and light fluctuations of the measured wind power and photovoltaic power and the amount of hydroelectricity, the wind curtailment rate and the light curtailment rate are obtained by a multi-dimensional conditional expected risk evaluation model and a multi-dimensional conditional most possible risk evaluation model. In order to verify the advantages of the conditional model, the fitting effects of the multi-dimensional conditional most possible risk evaluation model, the multi-dimensional conditional expected risk evaluation model and the linear function with the optimization model are compared and analyzed, and the results are shown in Figures 3A-3C . From the fitting results of each month, it can be seen that the linear function underestimates the curtailment rate (including the wind curtailment rate and the light curtailment rate), and can be used to simulate the smaller value of the curtailment rate. The multi-dimensional conditional most possible risk evaluation model effectively simulates the larger value of the curtailment rate, and is prone to overestimate the smaller scenario of the wind curtailment rate. For example: for the wind curtailment rate in January, the multi-dimensional conditional most possible risk evaluation model can better simulate the larger scenario of the wind curtailment rate. On January 26, the optimization wind curtailment rate is 29.70%, the multi-dimensional conditional most possible risk evaluation model calculates the result as 29.96%, while the multi-dimensional conditional expected risk evaluation model and the linear function are 18.38% and 13.55% respectively. From the results in January, it can be seen that the multi-dimensional conditional most possible risk evaluation model overestimates the light curtailment rate, indicating that the model will overestimate the smaller curtailment rate scenario. For the multi-dimensional conditional expected risk evaluation model, although there is some error in the fitting effect, it is basically at the average level, and can effectively simulate the average level of the wind curtailment rate. For example, the average value of the wind curtailment rate in January is 11.27%, the conditional most possible value is 13.23%, the expected value is 10.09%, and the linear function is 8.29%. For the light curtailment rate, the monthly average value is 1.81%, the conditional most possible value is 3.32%, the expected model calculates the result as 2.09%, and the linear function result is 2.13%. The results show that the conditional expected risk evaluation model is suitable for simulating the average level on the monthly scale, and the conditional most possible risk evaluation model is suitable for simulating the daily scale or the scenario with higher risk.

[0087] Through the example, the evolution law of the water-wind-solar complementary system abandoned electricity under different resource thresholds can be revealed, the precise simulation of the daily abandoned electricity rate of the multi-energy complementary system is realized, and a theoretical basis for realizing the medium and long term complementary operation of the energy system is provided.

[0088] The embodiment of the present application also provides a water-wind-solar complementary system abandoned electricity simulation device, as shown in the figure, the device comprises: Figure 4

[0089] The acquisition module 401 is used for acquiring at least one key risk factor, and the key risk factor is used for reflecting the influence on the water-wind-solar complementary system abandoned electricity rate. For details, refer to the related description of step 101 in the above method embodiment.

[0090] The first establishment module 402 is used for establishing the multi-dimensional joint distribution function of the water-wind-solar complementary system abandoned electricity rate based on each key risk factor, and determining the conditional distribution function of the water-wind-solar complementary system abandoned electricity rate based on the multi-dimensional joint distribution function. For details, refer to the related description of step 102 in the above method embodiment.

[0091] The second establishment module 403 is used for establishing the multi-dimensional conditional expected risk assessment model and the multi-dimensional conditional most possible risk assessment model based on the conditional distribution function. For details, refer to the related description of step 103 in the above method embodiment.

[0092] The evaluation module 404 is used for obtaining the expected value and the most possible value of the water-wind-solar complementary system abandoned electricity rate based on the water-wind-solar complementary system abandoned electricity rate, the multi-dimensional conditional expected risk assessment model and the multi-dimensional conditional most possible risk assessment model. For details, refer to the related description of step 104 in the above method embodiment.

[0093] The water-wind-solar complementary system abandoned electricity simulation device provided by the embodiment of the present application identifies the influence and degree of the key risk factor on the water-wind-solar complementary scheduling abandoned electricity rate, establishes the multi-dimensional conditional expected and multi-dimensional conditional most possible risk assessment model, reveals the evolution law of the water-wind-solar complementary system abandoned electricity under different resource thresholds, realizes the precise simulation of the daily abandoned electricity rate of the multi-energy complementary system, and provides a new way for reasonably evaluating the water-wind-solar complementary system abandoned electricity risk assessment.

[0094] As an optional implementation manner of the embodiment of the present application, the device further comprises a quantization processing module used for quantizing the water-wind-solar complementary system abandoned electricity rate and each key risk factor.

[0095] ​As an optional implementation of this invention, the curtailment rate includes wind curtailment rate, solar curtailment rate, and wind-solar curtailment rate; the quantification processing module includes: an acquisition submodule, used to acquire the wind power generation, photovoltaic power generation, and wind-solar curtailment amount of the hydro-wind-solar hybrid system; a first determination submodule, used to determine the wind curtailment amount and solar curtailment amount of the hydro-wind-solar hybrid system based on the wind power generation, photovoltaic power generation, and wind-solar curtailment amount; a first quantification processing submodule, used to quantify the wind curtailment rate based on the wind curtailment amount and wind power generation; a second quantification processing submodule, used to quantify the solar curtailment rate based on the solar curtailment amount and photovoltaic power generation; and a third quantification processing submodule, used to quantify the wind-solar curtailment rate based on the wind power generation, photovoltaic power generation, and wind-solar curtailment amount.

[0096] As an optional implementation of the present invention, the first establishing module includes: a second determining submodule, used to determine the correlation between each of the key risk factors and the curtailment rate of the hydro-wind-solar hybrid system; and an establishing submodule, used to establish the multidimensional joint distribution function based on the correlation and a preset connection function.

[0097] As an optional embodiment of the present invention, the device further includes: an adjustment module for adjusting the available water volume of the water-wind-solar hybrid system based on the expected value and the most likely value.

[0098] For a detailed description of the function of the hydro-wind-solar hybrid system curtailment simulation device provided in this embodiment of the invention, please refer to the description of the hydro-wind-solar hybrid system curtailment simulation method in the above embodiments.

[0099] This invention also provides a storage medium, such as... Figure 5 As shown, a computer program 501 is stored thereon. When executed by a processor, this program implements the steps of the method for simulating power curtailment in the hydro-wind-solar hybrid system described in the above embodiments. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk drive (HDD), or solid-state drive (SSD), etc.; the storage medium may also include combinations of the above types of memory.

[0100] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The program can be stored in a computer readable storage medium. When the program is executed, the processes of the above-mentioned embodiment methods can be included. The storage medium can be a magnetic disc, an optical disc, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD) or a solid-state drive (SSD), etc. The storage medium can also include a combination of the above-mentioned types of memories.

[0101] The embodiment of the present application also provides an electronic device, as shown in the figure, which can include a processor 61 and a memory 62. The processor 61 and the memory 62 can be connected through a bus or other means, Figure 6 The bus connection is taken as an example. Figure 6 The bus connection is taken as an example.

[0102] The processor 61 can be a central processing unit (CPU). The processor 61 can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. chips, or a combination of the above-mentioned chips.

[0103] The memory 62 is a non-transitory computer readable storage medium, which can be used to store non-transitory software programs, non-transitory computer executable programs and modules, such as the corresponding program instructions / modules in the embodiment of the present application. The processor 61 executes various functions of the processor and data processing by running the non-transitory software programs, instructions and modules stored in the memory 62, that is, the water and air scenery complementary system power abandonment simulation method in the above-mentioned method embodiment.

[0104] The memory 62 can include a program storage area and a data storage area, where the program storage area can store application programs required for operating the device, at least one function; the data storage area can store data created by the processor 61, etc. In addition, the memory 62 can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory 62 can optionally include a memory disposed remotely relative to the processor 61, which can be connected to the processor 61 through a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0105] The one or more modules are stored in the memory 62, and when executed by the processor 61, perform the functions as described above. Figures 1-3C The water-wind complementary system power abandonment simulation method in the embodiment shown.

[0106] The above-mentioned electronic device specific details can be referred to in Figures 1 to 3C The corresponding related description and effects in the embodiment shown are understood, and will not be described here.

[0107] Although the embodiments of the present application are described in conjunction with the accompanying drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application, and such modifications and changes fall within the scope defined by the appended claims.

Claims

1. A water-wind complementary system abandoned electricity simulation method, characterized in that, The method includes: At least one key risk factor is obtained, which is used to reflect the impact on the curtailment rate of the hydro-wind-solar hybrid system. The key risk factor is wind and solar power fluctuations and hydropower generation. A multidimensional joint distribution function of the curtailment rate of the hydro-wind-solar hybrid system is established based on each of the key risk factors, and a conditional distribution function of the curtailment rate of the hydro-wind-solar hybrid system is determined based on the multidimensional joint distribution function. Based on the conditional distribution function, a multidimensional conditional expected risk assessment model and a multidimensional conditional most probable risk assessment model are established. Based on the curtailment rate of the hydro-wind-solar hybrid system, the expected value and the most likely value of the curtailment rate of the hydro-wind-solar hybrid system are obtained through the multi-dimensional conditional expected risk assessment model and the multi-dimensional conditional most likely risk assessment model. The conditional distribution function for determining the curtailment rate of the hydro-wind-solar hybrid system based on the multidimensional joint distribution function includes: connecting key risk factors through the multidimensional joint distribution function; and determining the conditional distribution function for the curtailment rate of the hydro-wind-solar hybrid system under different risk conditions based on the conditional factors and the connection relationships, expressed as the following relationship: In the formula: represents a conditional distribution function; represents a key risk factor; The multidimensional conditional expected risk assessment model is used to evaluate the average level of power curtailment in hydro-wind-solar hybrid systems, and is expressed as the following relationship: wherein: denotes the cumulative probability of the variable ; denotes the cumulative probability of the variable ; denotes the inverse function of the distribution function of the variable ; denotes the multidimensional joint distribution probability density function, i.e. the multidimensional joint distribution function; denotes the expected value; denotes the risk of power rejection rate; The multidimensional conditional most probable risk assessment model is used to evaluate the most likely curtailment rate of the hydro-wind-solar hybrid system. It represents the curtailment rate corresponding to the maximum density probability of the conditional distribution function, expressed as the following formula: wherein: denotes the derivative of the spilling rate density function with respect to the spilling rate; denotes the derivative of the Copula linking density function with respect to the cumulative distribution of the spilling rate.

2. The method of claim 1, wherein, After obtaining at least one key risk factor, the method further includes: The curtailment rate of the hydro-wind-solar hybrid system and each of the key risk factors are quantified.

3. The method of claim 2, wherein, The curtailment rate includes wind curtailment rate, solar curtailment rate, and wind-solar curtailment rate; the curtailment rate of the hydro-wind-solar hybrid system is quantified, including: Obtain the wind power generation, photovoltaic power generation, and curtailed wind and solar power of the hydro-wind-solar hybrid system; The amount of wind power curtailed and the amount of solar power curtailed in the hydro-wind-solar hybrid system are determined based on the wind power generation, the photovoltaic power generation, and the amount of wind and solar power curtailed. The wind curtailment rate is quantified based on the amount of wind curtailment and the amount of wind power generation. The curtailment rate is quantified based on the amount of curtailed solar power and the amount of photovoltaic power generated. The wind and solar curtailment rate is quantified based on the wind power generation, the photovoltaic power generation, and the amount of wind and solar power curtailed.

4. The method of claim 1, wherein, A multidimensional joint distribution function for the curtailment rate of the hydro-wind-solar hybrid system is established based on each of the aforementioned key risk factors, including: Determine the correlation between each of the key risk factors and the curtailment rate of the hydro-wind-solar hybrid system; The multidimensional joint distribution function is established based on the correlation and the preset connection function.

5. The method of claim 1, wherein, The method further includes: The available water volume of the water-wind-solar hybrid system is adjusted based on the expected value and the most likely value.

6. A water-wind complementary system abandoned electricity simulation device, characterized in that, The device includes: An acquisition module is used to acquire at least one key risk factor, which is used to reflect the impact on the curtailment rate of the hydro-wind-solar hybrid system. The key risk factor is wind and solar power fluctuations and hydropower generation. The first establishing module is configured to establish a multi-dimensional joint distribution function of the water-wind-solar complementary system curtailment rate based on each key risk factor, and determine a conditional distribution function of the water-wind-solar complementary system curtailment rate based on the multi-dimensional joint distribution function; The second establishing module is configured to establish a multi-dimensional conditional expectation risk assessment model and a multi-dimensional conditional most likely risk assessment model based on the conditional distribution function; The assessment module is configured to obtain an expected value and a most likely value of the water-wind-solar complementary system curtailment rate based on the water-wind-solar complementary system curtailment rate, the multi-dimensional conditional expectation risk assessment model and the multi-dimensional conditional most likely risk assessment model. The conditional distribution function of the water-wind-solar complementary system curtailment rate is determined based on the multi-dimensional joint distribution function, which includes connecting the key risk factors through the multi-dimensional joint distribution function, and determining the conditional distribution function of the water-wind-solar complementary system curtailment rate under different risk conditions based on the conditional factors and the connection relationship, which is represented by the following relationship: In the formula: represents a conditional distribution function; represents a key risk factor; The multi-dimensional conditional expectation risk assessment model is configured to assess the average level of the water-wind-solar complementary system curtailment, which is represented by the following relationship: wherein: denotes the cumulative probability of the variable . denotes the cumulative probability of the variable . denotes the inverse function of the distribution function of the variable . denotes the multidimensional joint distribution probability density function, i.e. the multidimensional joint distribution function denotes the expected value denotes the risk of power rejection rate The multi-dimensional conditional most likely risk assessment model is configured to assess the most likely size of the water-wind-solar complementary system curtailment rate, which is the curtailment rate corresponding to the maximum density probability of the conditional distribution function, and is represented by the following relationship: In the formula: represents the derivative of the spilling rate density function with respect to the spilling rate; represents the derivative of the Copula linking density function with respect to the cumulative distribution of the spilling rate.

7. The apparatus of claim 6, wherein, The device further includes: The quantization processing module is configured to quantize the water-wind-solar complementary system curtailment rate and each key risk factor.

8. The apparatus of claim 7, wherein, The curtailment rate includes a wind curtailment rate, a light curtailment rate and a wind-light curtailment rate; and the quantization processing module includes: The acquisition sub-module is configured to acquire the wind power generation, the light power generation and the wind-light curtailment of the water-wind-solar complementary system; The first determination sub-module is configured to determine the wind curtailment and the light curtailment of the water-wind-solar complementary system based on the wind power generation, the light power generation and the wind-light curtailment; The first quantization processing sub-module is configured to quantize the wind curtailment rate based on the wind curtailment and the wind power generation; The second quantization processing sub-module is configured to quantize the light curtailment rate based on the light curtailment and the light power generation; The third quantization processing sub-module is configured to quantize the wind-light curtailment rate based on the wind power generation, the light power generation and the wind-light curtailment.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions, and the computer instructions are used to make the computer execute the water-wind-solar complementary system curtailment simulation method in any one of claims 1 to 5.

10. An electronic device, comprising: The device includes: The memory and the processor are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to execute the water-wind-solar complementary system curtailment simulation method in any one of claims 1 to 5.

Images