Multi-energy complementation strategy evaluation method and device, equipment and storage medium

Abstract

The invention relates to a multi-energy complementation strategy evaluation method, device and equipment and a storage medium, and the method comprises the steps: obtaining a to-be-evaluated multi-energy complementation strategy for a target new energy and a hydroelectric generating set, and building a corresponding multi-energy complementation system scheduling model, a plurality of energy types related to the multi-energy complementary system scheduling model comprise target new energy, hydroelectric power generation and external energy; solving the external output level of the external energy based on the preset output guarantee probability of the target new energy, wherein the preset output guarantee probability is used for representing the probability that the output level reaches the target output level; calculating the sensitivity of the external output level of the external energy to the output guarantee probability of the target new energy based on a model solving result; and determining an evaluation result of the multi-energy complementation strategy based on the sensitivity. By calculating the sensitivity of the external output level of the external energy to the output guarantee probability, the dependency of the multi-energy complementary strategy on the external energy can be evaluated, and subsequent strategy optimization is facilitated.

Description

Technical Field

[0001] The present disclosure relates to the field of renewable energy power generation technology, and in particular to a multi-energy complementary strategy evaluation method, device, equipment and storage medium. Background Art

[0002] In recent years, with the continuous intensification of the global energy crisis, the demand for efficient and sustainable energy utilization has been increasing. The multi-energy complementary system formed by aggregating multiple clean energy sources such as wind, light, and water has been widely promoted and applied due to its significant advantage of high energy utilization rate. In order to give full play to the advantages of the multi-energy complementary system and ensure its stable operation, it is necessary to formulate an operation strategy for the multi-energy complementary system and reasonably evaluate the formulated strategy. The existing evaluation methods of multi-energy complementary systems often focus on the economy, environmental protection, and technical aspects of the system, and do not consider the degree of dependence of the system on external energy. Since the output of new energy is affected by many factors such as weather conditions, geographical location, and equipment status, it has great uncertainty. If the system operation strategy has a strong dependence on external energy, the regular fluctuation of new energy output may cause a large adjustment of external energy, which not only increases the operating pressure of external energy, but also may have a serious impact on the stable operation of the system. Therefore, how to evaluate the degree of dependence of the multi-energy complementary system on external energy in the operation strategy is a technical problem that needs to be solved urgently. Summary of the invention

[0003] In order to solve the above technical problems, the present disclosure provides a multi-energy complementary strategy evaluation method, device, equipment and storage medium.

[0004] A first aspect of an embodiment of the present disclosure provides a multi-energy complementary strategy evaluation method, the method comprising:

[0005] Obtaining a multi-energy complementary strategy for a target new energy unit and a hydropower unit to be evaluated, and establishing a multi-energy complementary system scheduling model corresponding to the multi-energy complementary strategy, wherein the multi-energy complementary system scheduling model includes constraint conditions corresponding to multiple energy types and an objective function corresponding to the multi-energy complementary strategy, wherein the multiple energy types include target new energy, hydropower generation, and external energy;

[0006] Solving the external output level of the external energy in the multi-energy complementary system scheduling model based on the preset output guarantee probability of the target new energy and the unit change of the output guarantee probability, wherein the preset output guarantee probability is used to characterize the probability that the output level reaches the target output level;

[0007] Calculate the sensitivity of the external output level of the external energy source to the output guarantee probability of the target new energy source based on the model solution result;

[0008] An evaluation result of the multi-energy complementation strategy is determined based on the sensitivity.

[0009] A second aspect of an embodiment of the present disclosure provides a multi-energy complementary strategy evaluation device, the device comprising:

[0010] A model building module, used to obtain the multi-energy complementary strategy for the target new energy units and hydropower units to be evaluated, and to establish a multi-energy complementary system scheduling model corresponding to the multi-energy complementary strategy, wherein the multi-energy complementary system scheduling model includes constraint conditions corresponding to multiple energy types and an objective function corresponding to the multi-energy complementary strategy, wherein the multiple energy types include target new energy, hydropower generation and external energy;

[0011] A model solving module, used to solve the external output level of the external energy in the multi-energy complementary system scheduling model based on the preset output guarantee probability of the target new energy and the unit change of the output guarantee probability, wherein the preset output guarantee probability is used to characterize the probability that the output level reaches the target output level;

[0012] A calculation module, used for calculating the sensitivity of the external output level of the external energy source to the output guarantee probability of the target new energy source based on the model solution result;

[0013] An evaluation module is used to determine an evaluation result of the multi-energy complementary strategy based on the sensitivity.

[0014] A third aspect of an embodiment of the present disclosure provides a computer device, including a memory and a processor, and a computer program, wherein the computer program is stored in the memory, and when the computer program is executed by the processor, the multi-energy complementary strategy evaluation method as described in the first aspect above is implemented.

[0015] A fourth aspect of an embodiment of the present disclosure provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the multi-energy complementary strategy evaluation method as described in the first aspect above is implemented.

[0016] Compared with the prior art, the technical solution provided by the embodiments of the present disclosure has the following advantages:

[0017] In the multi-energy complementary strategy evaluation method, device, equipment and storage medium provided in the embodiments of the present disclosure, by obtaining the multi-energy complementary strategy for the target new energy unit and the hydropower unit to be evaluated, and establishing a multi-energy complementary system scheduling model corresponding to the multi-energy complementary strategy, the multi-energy complementary system scheduling model includes constraints corresponding to multiple energy types and objective functions corresponding to the multi-energy complementary strategy, and the multiple energy types include target new energy, hydropower generation and external energy. Based on the preset output guarantee probability of the target new energy and the unit change of the output guarantee probability, the external output level of the external energy in the multi-energy complementary system scheduling model is solved. The preset output guarantee probability is used to characterize the probability that the output level reaches the target output level. The sensitivity of the external output level of the external energy to the output guarantee probability of the target new energy is calculated based on the model solution result. Based on the sensitivity, the evaluation result of the multi-energy complementary strategy is determined, the sensitivity of the external output level of the external energy to the output guarantee probability can be determined, and the dependence of the multi-energy complementary strategy on the external energy is evaluated according to the sensitivity calculation result, so as to facilitate the subsequent screening of multi-energy complementary strategies with low dependence on external energy based on the evaluation results, thereby improving the stability of the operation of the multi-energy complementary system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0019] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0020] Figure 1 is a flow chart of a multi-energy complementary strategy evaluation method provided by an embodiment of the present disclosure;

[0021] Figure 2 is a flow chart of a method for solving a multi-energy complementary system scheduling model provided by an embodiment of the present disclosure;

[0022] Figure 3 is a flow chart of another method for solving a multi-energy complementary system scheduling model provided by an embodiment of the present disclosure;

[0023] Figure 4 It is a structural schematic diagram of a multi-energy complementary strategy evaluation device provided by an embodiment of the present disclosure;

[0024] Figure 5 It is a structural diagram of a computer device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0025] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0026] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0027] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0028] Figure 1 This is a flow chart of a multi-energy complementary strategy evaluation method provided by an embodiment of the present disclosure. The method can be executed by a multi-energy complementary strategy evaluation device. The multi-energy complementary strategy evaluation device can be implemented in software and / or hardware. The multi-energy complementary strategy evaluation device can be configured in an electronic device, such as a server or a terminal, wherein the terminal specifically includes a mobile phone, a computer or a tablet computer, etc. Figure 1 As shown, the multi-energy complementary strategy evaluation method provided in this embodiment includes the following steps:

[0029] S101. Obtain the multi-energy complementary strategy for the target new energy units and hydropower units to be evaluated, and establish a multi-energy complementary system scheduling model corresponding to the multi-energy complementary strategy. The multi-energy complementary system scheduling model includes constraints corresponding to multiple energy types and objective functions corresponding to the multi-energy complementary strategy. The multiple energy types include target new energy, hydropower and external energy.

[0030] The multi-energy complementary strategy in the embodiments of the present disclosure can be understood as a pre-established operating strategy of a wind, solar and hydropower multi-energy complementary system. For example, the multi-energy complementary strategy may include a hydropower leveling strategy to suppress new energy fluctuations, a wind, solar and hydropower output tracking load strategy, etc., which are not limited here.

[0031] The target new energy in the disclosed embodiments can be understood as a new energy source whose output is easily affected by multiple factors such as weather conditions, geographical location, equipment status, etc., such as wind power generation, photovoltaic power generation, etc. The external energy can be understood as an energy that can be quickly started and stopped or accurately adjust its output level, such as thermal power generation energy, external power supply, etc., which is not limited here.

[0032] In the disclosed embodiment, the multi-energy complementary strategy evaluation device can obtain the multi-energy complementary strategy for the target new energy unit and the hydropower unit to be evaluated, extract the energy type involved in the strategy from the multi-energy complementary strategy, and determine the constraints corresponding to the energy type and the external energy type involved in the strategy, as well as the objective function corresponding to the multi-energy complementary strategy, and combine the constraints corresponding to the energy type and the external energy type involved in the strategy and the objective function corresponding to the multi-energy complementary strategy to obtain a multi-energy complementary system scheduling model corresponding to the multi-energy complementary strategy, wherein the energy types involved in the strategy include the target new energy and hydropower generation, and the multiple energy types for which constraints need to be established in the multi-energy complementary system scheduling model include the target new energy, hydropower generation and external energy.

[0033] In an exemplary implementation of the disclosed embodiment, the multi-energy complementary strategy evaluation device can, after determining the multi-energy complementary strategy to be evaluated, extract the energy type involved in the multi-energy complementary strategy to be evaluated and the objective function corresponding to the multi-energy complementary strategy from a preset database, and then search for the constraint conditions corresponding to each energy type according to the energy type involved in the strategy, and integrate the constraint conditions corresponding to the energy type involved in the strategy, the objective function corresponding to the multi-energy complementary strategy, and the constraint conditions corresponding to the preset external energy type to obtain a multi-energy complementary system scheduling model.

[0034] Optionally, the target new energy may include wind power generation and / or photovoltaic power generation, and the constraints include a first output constraint corresponding to the target new energy, a second output constraint and a climbing constraint corresponding to the external energy, and a third output constraint corresponding to hydropower generation, a flow constraint, a reservoir capacity constraint, an outflow constraint, and at least one of a water level constraint. The multi-energy complementary system scheduling model also includes a dynamic balance relationship between the operating parameters of the hydropower station.

[0035] Specifically, the first output constraint condition corresponding to the target new energy can be expressed as follows:

[0036]

[0037] Among them, i∈[1,N W ],j∈[1,N S ],t∈[1,T],N W 、N S , T are the number of wind farms, the number of photovoltaic power stations and the total number of time periods considered, are the outputs of the i-th wind farm and the j-th photovoltaic power station at time t, and are the output coefficients of the i-th wind farm and the j-th photovoltaic power station at time t when the output guarantee probability is C%, and are the installed capacities of the i-th wind farm and the j-th photovoltaic power station respectively.

[0038] The second output constraint corresponding to the external energy can be expressed as follows:

[0039]

[0040] The climbing constraint corresponding to the external energy can be expressed as follows:

[0041]

[0042] Among them, the positive integer n∈[1,N g ],N g is the number of external power supplies, and are the lower and upper output limits of the nth external power supply, respectively. is the output of the nth external power source at time t, is the output of the nth external power source at time t-1, and are the maximum downward climbing rate and the maximum upward climbing rate of the nth external power supply respectively, and Δt is the time period step.

[0043] The third output constraint corresponding to hydropower generation can be expressed as follows:

[0044]

[0045] The flow constraint corresponding to hydropower generation can be expressed as follows:

[0046]

[0047] The storage capacity constraints corresponding to hydropower generation can be expressed as follows:

[0048]

[0049] The outflow constraints corresponding to hydropower generation can be expressed as follows:

[0050]

[0051] The water level constraints corresponding to hydropower generation can be expressed as follows:

[0052]

[0053] Among them, the positive integer k∈[1,N h ],N h is the total number of hydropower stations. The smaller k is, the higher the altitude of the basin is. k = 1 represents the most upstream hydropower station. are the output, power generation flow, reservoir capacity, outflow flow, and upper water level of the kth hydropower station at time t, They are respectively the minimum and maximum values ​​of the unit output, power generation flow, reservoir capacity, outflow flow, and upper water level of the kth hydropower station.

[0054] The dynamic balance relationship between the operating parameters of a hydropower station can be expressed as follows:

[0055]

[0056] Among them, η k is the comprehensive output coefficient of the kth hydropower station, are the net water head, tail water level, abandoned water volume, and natural water inflow of the kth hydropower station at time t, where the natural water inflow is calculated by combining rainfall and the geographical features near the reservoir. is the head loss of the kth hydropower station, σ k,0 , σ k,1 , σ k,2 , σ k,3 , σ k,4 are the coefficients of various orders in the upper water level-reservoir capacity relationship of the kth hydropower station, μ k,0 , μ k,1 , μ k,2 , μ k,3 , μ k,4 are the order coefficients in the tailwater level-discharge relationship of the kth hydropower station, is the initial storage capacity of the kth hydropower station.

[0057] Optionally, for the strategy of suppressing new energy fluctuations by water level, the corresponding objective function can be expressed as follows:

[0058]

[0059] For the wind, solar and hydro output tracking load strategy, the corresponding objective function can be expressed as follows:

[0060]

[0061] Among them, N W 、N S 、N h , T are the number of wind farms, photovoltaic power stations, hydropower stations and the total number of time periods considered, respectively. are the output levels of the i-th wind farm, the j-th photovoltaic power station, and the k-th hydropower station at the t-th moment, is the load power at moment t.

[0062] S102. Solving the external output level of external energy in the multi-energy complementary system scheduling model based on the preset output guarantee probability of the target new energy and the unit change of the output guarantee probability. The preset output guarantee probability is used to characterize the probability that the output level reaches the target output level.

[0063] The output guarantee probability in the embodiment of the present disclosure can be understood as the probability that the output level of the target new energy reaches the set output level at a certain moment. There is a correlation between the output guarantee probability and the target output level. When other conditions do not change, the greater the output guarantee probability, the lower the set output level. The preset output guarantee probability is used to characterize the probability that the output level reaches the target output level. The preset output guarantee probability and the unit change of the output guarantee probability can be pre-set.

[0064] In the embodiment of the present disclosure, after the multi-energy complementary system scheduling model is constructed, the multi-energy complementary strategy evaluation device can solve the external output level of the external energy in the multi-energy complementary system scheduling model based on the preset output guarantee probability of the target new energy and the unit change of the output guarantee probability. Specifically, the preset output guarantee probability and the unit change of the output guarantee probability can be substituted into the multi-energy complementary system scheduling model, and the external output level (i.e., the variable in S101) can be solved according to the objective function. ) to find the optimal solution.

[0065] S103. Calculate the sensitivity of the external output level of the external energy source to the output guarantee probability of the target new energy source based on the model solution result.

[0066] In the disclosed embodiment, the sensitivity of the external output level of the external energy source to the output guarantee probability of the target new energy source can be understood as the degree to which the external output level of the external energy source changes when the output guarantee probability of the target new energy source changes, and is used to evaluate the impact of the uncertainty of the target new energy source output on the external energy demand. If the sensitivity is high, it means that a small change in the target new energy source output guarantee probability will lead to a large change in the external energy source output, and the multi-energy complementary system is more dependent on the external energy source. On the contrary, if the sensitivity is low, it means that the uncertainty of the target new energy source output has little impact on the external energy demand, and the multi-energy complementary system is less dependent on the external power source.

[0067] In the disclosed embodiment, the multi-energy complementary strategy evaluation device can calculate the sensitivity of the external output level in the model solution result to the output guarantee probability of the target new energy after obtaining the model solution result of the multi-energy complementary system scheduling model.

[0068] In an exemplary implementation of the embodiment of the present disclosure, the multi-energy complementary strategy evaluation device can obtain the partial derivative of the external output level in the model solution result with respect to the output guarantee probability, which can be specifically expressed as follows:

[0069]

[0070] in, represents the lth complementary strategy F l The external output level of the next n-th external energy source is specifically the external output level trajectory corresponding to multiple sampling points at multiple sampling times, a is the time sampling point variable, and ΔC% is the unit change of the output guarantee probability.

[0071] S104. Determine the evaluation result of the multi-energy complementation strategy based on sensitivity.

[0072] In the disclosed embodiment, the multi-energy complementary strategy evaluation device can determine the sensitivity of the external output level of the external energy to the output guarantee probability of the target new energy, and then determine the evaluation result of the corresponding multi-energy complementary strategy according to the sensitivity. Specifically, according to the conversion relationship between the sensitivity and the strategy score, the sensitivity can be converted into the corresponding strategy score to obtain the evaluation result of the multi-energy complementary strategy.

[0073] The disclosed embodiment obtains a multi-energy complementary strategy for a target new energy unit and a hydropower unit to be evaluated, and establishes a multi-energy complementary system scheduling model corresponding to the multi-energy complementary strategy. The multi-energy complementary system scheduling model includes constraints corresponding to a plurality of energy types and an objective function corresponding to the multi-energy complementary strategy. The plurality of energy types include target new energy, hydropower generation and external energy. The external output level of the external energy in the multi-energy complementary system scheduling model is solved based on a preset output guarantee probability of the target new energy and a unit change in the output guarantee probability. The preset output guarantee probability is used to characterize the probability that the output level reaches the target output level. The sensitivity of the external output level of the external energy to the output guarantee probability of the target new energy is calculated based on the model solution result. The evaluation result of the multi-energy complementary strategy is determined based on the sensitivity. The sensitivity of the external output level of the external energy to the output guarantee probability can be determined. The dependence of the multi-energy complementary strategy on the external energy is evaluated according to the sensitivity calculation result, so as to facilitate the subsequent screening of multi-energy complementary strategies with a low degree of dependence on external energy based on the evaluation result, thereby improving the stability of the operation of the multi-energy complementary system.

[0074] Figure 2 is a flow chart of a method for solving a multi-energy complementary system scheduling model provided by an embodiment of the present disclosure, such as Figure 2 As shown, based on the above embodiment, the multi-energy complementary system scheduling model can be solved by the following method, wherein the external output level includes a reference external output level, a first external output level and a second external output level.

[0075] S201. Determine an upper limit output guarantee probability and a lower limit output guarantee probability based on a preset output guarantee probability and a unit change amount of the output guarantee probability.

[0076] In the disclosed embodiment, the multi-energy complementary strategy evaluation device can perform summation and difference processing based on the preset output guarantee probability and the unit change of the output guarantee probability to obtain the upper limit output guarantee probability and the lower limit output guarantee probability.

[0077] S202. Solve the external output level of external energy in the multi-energy complementary system scheduling model based on the preset output guarantee probability, the upper limit output guarantee probability and the lower limit output guarantee probability, and obtain a benchmark external output level corresponding to the preset output guarantee probability, a first external output level corresponding to the upper limit output guarantee probability and a second external output level corresponding to the lower limit output guarantee probability.

[0078] In the disclosed embodiment, the multi-energy complementary strategy evaluation device can substitute the preset output guarantee probability, the upper limit output guarantee probability and the lower limit output guarantee probability into the multi-energy complementary system scheduling model respectively, solve the external output level of the external energy in the model, and determine the external output level obtained after substituting the preset output guarantee probability as the benchmark external output level, determine the external output level obtained after substituting the upper limit output guarantee probability as the first external output level, and determine the external output level obtained after substituting the lower limit output guarantee probability as the second external output level.

[0079] The disclosed embodiment determines the upper limit output guarantee probability and the lower limit output guarantee probability based on the preset output guarantee probability and the unit change of the output guarantee probability, and solves the external output level of the external energy in the multi-energy complementary system scheduling model based on the preset output guarantee probability, the upper limit output guarantee probability and the lower limit output guarantee probability respectively, and obtains the benchmark external output level corresponding to the preset output guarantee probability, the first external output level corresponding to the upper limit output guarantee probability and the second external output level corresponding to the lower limit output guarantee probability. It is possible to construct multiple output guarantee probabilities, which is convenient for the subsequent solution of multiple external output levels corresponding to the multiple output guarantee probabilities, and then obtain the sensitivity of the external output level to the output guarantee probability.

[0080] Figure 3 is a flow chart of another method for solving a multi-energy complementary system scheduling model provided by an embodiment of the present disclosure. Figure 3 As shown, based on the above embodiment, the multi-energy complementary system scheduling model can be solved by the following method, wherein the target output level includes a reference target output level, a first target output level and a second target output level.

[0081] S301. Obtain historical output data of target new energy.

[0082] The historical output data in the embodiment of the present disclosure may be understood as pre-collected output level data of the target renewable energy source over a period of time in the past, and may specifically be power generation data.

[0083] In the disclosed embodiment, the multi-energy complementary strategy evaluation device may obtain pre-collected historical output data of the target new energy in the multi-energy complementary system from a database.

[0084] S302: Based on historical output data, determine a reference target output level corresponding to a preset output guarantee probability, a first target output level corresponding to an upper limit output guarantee probability, and a second target output level corresponding to a lower limit output guarantee probability.

[0085] In the disclosed embodiment, the multi-energy complementary strategy evaluation device can analyze the historical output data after determining the preset output guarantee probability, the upper limit output guarantee probability and the lower limit output guarantee probability, to determine the baseline target output level corresponding to the preset output guarantee probability, the first target output level corresponding to the upper limit output guarantee probability and the second target output level corresponding to the lower limit output guarantee probability. Specifically, the multi-energy complementary strategy evaluation device can sort the historical output data in order from small to large, and determine the data quantile numbers corresponding to the preset output guarantee probability, the upper limit output guarantee probability and the lower limit output guarantee probability respectively according to the number of historical output data, locate a target output data in the sorted historical output data according to the data quantile number, and determine the baseline target output level, the first target output level and the second target output level according to the target output data.

[0086] Optionally, for the historical output data of the target new energy source with a statistical period of d days, the multi-energy complementary strategy evaluation device can extract the output value at the tth moment of each day from the historical output data, and arrange them in order from small to large to obtain the historical output data sequence at the tth moment in is the mth historical output data, The data quantile number N of the preset output guarantee probability C% C％ The calculation method can be expressed as follows:

[0087] N C％ =max{floor[d×(1-C%)],1}

[0088] Among them, N C％ is an integer satisfying 1≤N C％ ≤d, floor means round down, for example, floor(0.95)=0, floor(1.95)=1. Determine the data quantile number N C％ Then, from the historical output data series Find the data quantile number N in C％ The corresponding output data is the benchmark target output level corresponding to the preset output guarantee probability C% at the tth moment. It is expressed as follows:

[0089]

[0090] The method for the multi-energy complementary strategy evaluation device to determine the first target output level corresponding to the upper limit output guarantee probability and the second target output level corresponding to the lower limit output guarantee probability is similar to the method for determining the reference target output level corresponding to the preset output guarantee probability, which will not be repeated here.

[0091] S303: Determine the benchmark output constraint parameter, the first output constraint parameter, and the second output constraint parameter corresponding to the target new energy based on the benchmark target output level, the first target output level, the second target output level, and the pre-acquired installed capacity of the target new energy.

[0092] The output constraint parameter in the embodiment of the present disclosure may be understood as the output coefficient in S102.

[0093] In the disclosed embodiment, the multi-energy complementary strategy evaluation device can, after determining the baseline target output level, the first target output level, and the second target output level, combine the pre-acquired installed capacity of the target new energy to calculate the baseline output constraint parameter, the first output constraint parameter, and the second output constraint parameter corresponding to the target new energy. Specifically, the ratio of the baseline target output level, the first target output level, the second target output level to the installed capacity of the target new energy can be calculated respectively to obtain the baseline output constraint parameter, the first output constraint parameter, and the second output constraint parameter.

[0094] S304. Substitute the baseline output constraint parameter, the first output constraint parameter and the second output constraint parameter into the constraint conditions corresponding to the target new energy respectively, and solve the external output level of the external energy in the multi-energy complementary system scheduling model to obtain the baseline external output level corresponding to the preset output guarantee probability, the first external output level corresponding to the upper limit output guarantee probability and the second external output level corresponding to the lower limit output guarantee probability.

[0095] In the disclosed embodiment, the multi-energy complementary strategy evaluation device can substitute the baseline output constraint parameter into the constraint condition corresponding to the target new energy after calculating the baseline output constraint parameter, the first output constraint parameter and the second output constraint parameter, and solve the external output level of the external energy in the multi-energy complementary system scheduling model to obtain the baseline external output level corresponding to the preset output guarantee probability, substitute the first output constraint parameter into the constraint condition corresponding to the target new energy, and solve the external output level to obtain the first external output level corresponding to the upper limit output guarantee probability, and then substitute the second output constraint parameter into the constraint condition corresponding to the target new energy, and solve the external output level to obtain the second external output level corresponding to the lower limit output guarantee probability.

[0096] Optionally, the historical output data includes output data corresponding to the target new energy at different times within the target period, the target output level is the sequence data of the output level of the target new energy at different times within the target period, and the external output level is the sequence data of the output level of the external energy at different times within the target period.

[0097] Specifically, the multi-energy complementary strategy evaluation device can determine the target output levels at different times corresponding to the same output guarantee probability based on the output data of the target new energy at different times within the target period, and then determine the output constraint parameters at different times based on the target output levels at different times, substitute them into the multi-energy complementary system scheduling model to solve the external output level, and obtain the sequence data of the output level of the external energy at different times.

[0098] The disclosed embodiment obtains historical output data of the target new energy, and determines, based on the historical output data, a benchmark target output level corresponding to a preset output guarantee probability, a first target output level corresponding to an upper limit output guarantee probability, and a second target output level corresponding to a lower limit output guarantee probability; determines a benchmark output constraint parameter, a first output constraint parameter, and a second output constraint parameter corresponding to the target new energy based on the benchmark target output level, the first target output level, the second target output level, and the pre-acquired installed capacity of the target new energy; and substitutes the benchmark output constraint parameter, the first output constraint parameter, and the second output constraint parameter into the target new energy. The constraints corresponding to the source are calculated, and the external output level of the external energy in the multi-energy complementary system scheduling model is solved to obtain the benchmark external output level corresponding to the preset output guarantee probability, the first external output level corresponding to the upper limit output guarantee probability and the second external output level corresponding to the lower limit output guarantee probability. By capturing the intraday changes in the target new energy output reliability, the output guarantee probability of new energy can be extended to the scenario of dynamic intraday changes. The target output level and the external output level also change dynamically, which is closer to the actual operation process of the multi-energy complementary system, further improving the accuracy of the sensitivity calculation, thereby improving the reliability of the strategy evaluation results.

[0099] Optionally, when the multi-energy complementary strategy evaluation device calculates the sensitivity of the external output level of the external energy to the output guarantee probability of the target new energy based on the model solution results, it can calculate the sensitivity of the external output level of the external energy to the output guarantee probability of the target new energy based on the baseline external output level, the first external output level, the second external output level, the preset output guarantee probability and the unit change of the output guarantee probability.

[0100] Specifically, when determining the sensitivity of the external output level to the output guarantee probability, the multi-energy complementary strategy evaluation device can use the perturbation method to calculate the sensitivity of each external energy output level under a given output guarantee probability, and use the median to improve the calculation accuracy. The specific calculation process can be expressed as follows:

[0101]

[0102] Among them, C 0 % is the preset output guarantee probability, ΔC% is the unit change of output guarantee probability, is the lth complementary strategy F l The benchmark external output level of the next nth external energy source under the preset output guarantee probability, is the lth complementary strategy F l The first external output level of the next nth external energy source under the upper limit output guarantee probability, is the lth complementary strategy F l The second external output level of the next nth external energy source under the lower limit output guarantee probability, s n (C 0 %,a,F l ) is the first complementary strategy F l The sensitivity of the external output level of the next n-th external energy source under the preset output guarantee probability.

[0103] After determining the sensitivity of the external output level of the nth external energy source under the preset output guarantee probability to the output guarantee probability, the complementary strategy F l and the preset output guarantee probability C 0 The sensitivity of the external output level of external energy to the output guarantee probability of the target new energy under the condition of % (C 0 %,F l ) is calculated as follows:

[0104]

[0105] Among them, N a is the total number of time sampling points, N g is the amount of external energy.

[0106] Figure 4Schematic diagram of a multi-energy complementary strategy evaluation device provided by an embodiment of the present disclosure. Figure 4 As shown, the multi-energy complementary strategy evaluation device 400 includes: a model building module 410, a model solving module 420, a calculation module 430, and an evaluation module 440, wherein the model building module 410 is used to obtain the multi-energy complementary strategy for the target new energy unit and the hydropower unit to be evaluated, and establish a multi-energy complementary system scheduling model corresponding to the multi-energy complementary strategy, the multi-energy complementary system scheduling model includes constraints corresponding to multiple energy types and an objective function corresponding to the multi-energy complementary strategy, the multiple energy types include target new energy, hydropower generation and external energy; the model solving module 420 is used to solve the external output level of the external energy in the multi-energy complementary system scheduling model based on the preset output guarantee probability of the target new energy and the unit change of the output guarantee probability, the preset output guarantee probability is used to characterize the probability that the output level reaches the target output level; the calculation module 430 is used to calculate the sensitivity of the external output level of the external energy to the output guarantee probability of the target new energy based on the model solution result; the evaluation module 440 is used to determine the evaluation result of the multi-energy complementary strategy based on the sensitivity.

[0107] Optionally, the external output level includes a baseline external output level, a first external output level and a second external output level, and the model solving module 420 includes: a first determination unit, used to determine the upper limit output guarantee probability and the lower limit output guarantee probability based on the preset output guarantee probability and the unit change of the output guarantee probability; a solving unit, used to solve the external output level of the external energy in the multi-energy complementary system scheduling model based on the preset output guarantee probability, the upper limit output guarantee probability and the lower limit output guarantee probability, respectively, to obtain the baseline external output level corresponding to the preset output guarantee probability, the first external output level corresponding to the upper limit output guarantee probability and the second external output level corresponding to the lower limit output guarantee probability.

[0108] Optionally, the target output level includes a baseline target output level, a first target output level and a second target output level, and the model solving module 420 also includes: an acquisition unit for acquiring historical output data of the target new energy; a second determination unit for determining, based on the historical output data, the baseline target output level corresponding to the preset output guarantee probability, the first target output level corresponding to the upper limit output guarantee probability, and the second target output level corresponding to the lower limit output guarantee probability; and a third determination unit for determining the baseline output constraint parameter, the first output constraint parameter and the second output constraint parameter corresponding to the target new energy based on the baseline target output level, the first target output level, the second target output level and the pre-acquired installed capacity of the target new energy.

[0109] Optionally, the solving unit is specifically used to substitute the benchmark output constraint parameter, the first output constraint parameter and the second output constraint parameter into the constraint conditions corresponding to the target new energy, and solve the external output level of the external energy in the multi-energy complementary system scheduling model to obtain the benchmark external output level corresponding to the preset output guarantee probability, the first external output level corresponding to the upper limit output guarantee probability and the second external output level corresponding to the lower limit output guarantee probability.

[0110] Optionally, the historical output data includes output data corresponding to the target new energy at different times within the target time period, the target output level is sequence data of the output level of the target new energy at different times within the target time period, and the external output level is sequence data of the output level of the external energy at different times within the target time period.

[0111] Optionally, the calculation module 430 is specifically used to calculate the sensitivity of the external output level of the external energy to the output guarantee probability of the target new energy based on the benchmark external output level, the first external output level, the second external output level, the preset output guarantee probability and the unit change of the output guarantee probability.

[0112] Optionally, the target new energy includes wind power generation and / or photovoltaic power generation, and the constraints include a first output constraint corresponding to the target new energy, a second output constraint and a climbing constraint corresponding to the external energy, and a third output constraint corresponding to the hydropower generation, a flow constraint, a reservoir capacity constraint, an outflow flow constraint, and at least one of a water level constraint; the multi-energy complementary system scheduling model also includes a dynamic balance relationship between the operating parameters of the hydropower station.

[0113] The multi-energy complementary strategy evaluation device provided in this embodiment can execute the method described in any of the above embodiments, and its execution method and beneficial effects are similar and will not be repeated here.

[0114] Figure 5 It is a structural diagram of a computer device provided in an embodiment of the present disclosure.

[0115] like Figure 5 As shown, the computer device may include a processor 510 and a memory 520 storing computer program instructions.

[0116] Specifically, the processor 510 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0117] The memory 520 may include a large capacity memory for information or instructions. By way of example and not limitation, the memory 520 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 520 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 520 may be inside or outside the integrated gateway device. In a particular embodiment, the memory 520 is a non-volatile solid-state memory. In a particular embodiment, the memory 520 includes a read-only memory (ROM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (Electrically Erasable Programmable ROM, EEPROM), an electrically rewritable ROM (EAROM), or a flash memory, or a combination of two or more of these.

[0118] The processor 510 reads and executes the computer program instructions stored in the memory 520 to perform the steps of the multi-energy complementary strategy evaluation method provided in the embodiment of the present disclosure.

[0119] In one example, the computer device may further include a transceiver 530 and a bus 540. Figure 5As shown, the processor 510, the memory 520 and the transceiver 530 are connected via a bus 540 and communicate with each other.

[0120] The bus 540 includes hardware, software, or both. For example, but not limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industrial Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low Pin Count (LPC) bus, a Memory bus, a MicroChannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses or a combination of two or more of these. Where appropriate, the bus 540 may include one or more buses. Although embodiments of the present application describe and illustrate a particular bus, the present application contemplates any suitable bus or interconnect.

[0121] The embodiments of the present disclosure also provide a computer-readable storage medium, which may store a computer program. When the computer program is executed by a processor, the processor implements the multi-energy complementary strategy evaluation method provided by the embodiments of the present disclosure.

[0122] The above-mentioned storage medium may, for example, include a memory 520 of computer program instructions, and the above-mentioned instructions may be executed by the processor 510 of the multi-energy complementary strategy evaluation device to complete the multi-energy complementary strategy evaluation method provided by the embodiment of the present disclosure. Optionally, the storage medium may be a non-temporary computer-readable storage medium, for example, the non-temporary computer-readable storage medium may be a ROM, a random access memory (Random Access Memory, RAM), a compact disc read-only memory (Compact Disc ROM, CD-ROM), a magnetic tape, a floppy disk, and an optical data storage device, etc. The above-mentioned computer program may be written in any combination of one or more programming languages ​​to perform the program code of the operation of the embodiment of the present disclosure, and the programming language includes an object-oriented programming language, such as Java, C++, etc., and also includes a conventional procedural programming language, such as "C" language or similar programming language. The program code may be executed entirely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device, partially on the remote computing device, or completely on the remote computing device or server.

[0123] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0124] The above description is only a specific embodiment of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A multi-energy complementary strategy evaluation method, characterized in that: The method comprises: Obtaining a multi-energy complementary strategy for a target new energy unit and a hydropower unit to be evaluated, and establishing a multi-energy complementary system scheduling model corresponding to the multi-energy complementary strategy, wherein the multi-energy complementary system scheduling model includes constraint conditions corresponding to multiple energy types and an objective function corresponding to the multi-energy complementary strategy, wherein the multiple energy types include target new energy, hydropower generation, and external energy; Solving the external output level of the external energy in the multi-energy complementary system scheduling model based on the preset output guarantee probability of the target new energy and the unit change of the output guarantee probability, wherein the preset output guarantee probability is used to characterize the probability that the output level reaches the target output level; Calculate the sensitivity of the external output level of the external energy source to the output guarantee probability of the target new energy source based on the model solution result; An evaluation result of the multi-energy complementation strategy is determined based on the sensitivity.

2. The method according to claim 1, characterized in that The external output level includes a reference external output level, a first external output level, and a second external output level. The external output level of the external energy in the multi-energy complementary system scheduling model is solved based on the preset output guarantee probability of the target new energy and the unit change of the output guarantee probability, including: Determining an upper limit output guarantee probability and a lower limit output guarantee probability based on the preset output guarantee probability and a unit change amount of the output guarantee probability; The external output level of the external energy in the multi-energy complementary system scheduling model is solved based on the preset output guarantee probability, the upper limit output guarantee probability and the lower limit output guarantee probability, respectively, to obtain a benchmark external output level corresponding to the preset output guarantee probability, a first external output level corresponding to the upper limit output guarantee probability and a second external output level corresponding to the lower limit output guarantee probability.

3. The method according to claim 2, characterized in that The target output level includes a reference target output level, a first target output level, and a second target output level. Before solving the external output level of the external energy in the multi-energy complementary system scheduling model based on the preset output guarantee probability, the upper limit output guarantee probability, and the lower limit output guarantee probability, respectively, to obtain the reference external output level corresponding to the preset output guarantee probability, the first external output level corresponding to the upper limit output guarantee probability, and the second external output level corresponding to the lower limit output guarantee probability, the method further includes: Obtaining historical output data of the target new energy source; Determine, based on the historical output data, a reference target output level corresponding to the preset output guarantee probability, a first target output level corresponding to the upper limit output guarantee probability, and a second target output level corresponding to the lower limit output guarantee probability; The benchmark output constraint parameter, the first output constraint parameter and the second output constraint parameter corresponding to the target new energy are determined based on the benchmark target output level, the first target output level, the second target output level and the pre-acquired installed capacity of the target new energy.

4. The method according to claim 3, characterized in that The solving of the external output level of the external energy in the multi-energy complementary system scheduling model based on the preset output guarantee probability, the upper limit output guarantee probability and the lower limit output guarantee probability respectively, to obtain a reference external output level corresponding to the preset output guarantee probability, a first external output level corresponding to the upper limit output guarantee probability and a second external output level corresponding to the lower limit output guarantee probability, includes: The benchmark output constraint parameter, the first output constraint parameter and the second output constraint parameter are respectively substituted into the constraint conditions corresponding to the target new energy, and the external output level of the external energy in the multi-energy complementary system scheduling model is solved to obtain the benchmark external output level corresponding to the preset output guarantee probability, the first external output level corresponding to the upper limit output guarantee probability and the second external output level corresponding to the lower limit output guarantee probability.

5. The method according to claim 3, characterized in that: The historical output data includes the output data corresponding to the target new energy at different times within the target period, the target output level is the sequence data of the output level of the target new energy at different times within the target period, and the external output level is the sequence data of the output level of the external energy at different times within the target period.

6. The method according to claim 2, characterized in that The calculating, based on the model solution result, the sensitivity of the external output level of the external energy source to the output guarantee probability of the target new energy source comprises: The sensitivity of the external output level of the external energy source to the output guarantee probability of the target new energy source is calculated based on the reference external output level, the first external output level, the second external output level, the preset output guarantee probability, and a unit change in the output guarantee probability.

7. The method according to any one of claims 1 to 6, characterized in that The target new energy includes wind power generation and / or photovoltaic power generation, the constraints include a first output constraint corresponding to the target new energy, a second output constraint and a climbing constraint corresponding to the external energy, and a third output constraint corresponding to the hydropower generation, a flow constraint, a reservoir capacity constraint, an outflow flow constraint, and at least one of a water level constraint. The multi-energy complementary system scheduling model also includes a dynamic balance relationship between the operating parameters of the hydropower station.

8. A multi-energy complementary strategy evaluation device, characterized in that: The device comprises: A model building module, used to obtain the multi-energy complementary strategy for the target new energy units and hydropower units to be evaluated, and to establish a multi-energy complementary system scheduling model corresponding to the multi-energy complementary strategy, wherein the multi-energy complementary system scheduling model includes constraint conditions corresponding to multiple energy types and an objective function corresponding to the multi-energy complementary strategy, wherein the multiple energy types include target new energy, hydropower generation and external energy; A model solving module, used to solve the external output level of the external energy in the multi-energy complementary system scheduling model based on the preset output guarantee probability of the target new energy and the unit change of the output guarantee probability, wherein the preset output guarantee probability is used to characterize the probability that the output level reaches the target output level; A calculation module, used for calculating the sensitivity of the external output level of the external energy source to the output guarantee probability of the target new energy source based on the model solution result; An evaluation module is used to determine an evaluation result of the multi-energy complementary strategy based on the sensitivity.

9. A computer device, characterized in that: include: Memory; processor; And a computer program; wherein the computer program is stored in the memory and is configured to be executed by the processor to implement the multi-energy complementary strategy evaluation method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by the processor, the multi-energy complementary strategy evaluation method according to any one of claims 1 to 7 is implemented.

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