Method and device for calculating uncertainty of equivalent hours of actual power generation in wind farms

Abstract

The present invention discloses a method and device for calculating the uncertainty of the equivalent hours of actual power generation of a wind farm, and belongs to the technical field of wind power. The method comprises: obtaining the preliminary design data and operation data of the wind farm; calculating each loss through the numerical calculation relationship between each loss and the reduction coefficient; calculating the total loss through each loss, and calculating the theoretical equivalent hours of the wind farm through the overall theoretical power generation of the wind farm and the installed capacity of the wind farm; calculating the equivalent hours of the wind farm with a probability of exceeding 50% based on the total loss and the theoretical equivalent hours of the wind farm, and calculating the overall uncertainty based on each uncertainty; using the error function method to calculate the uncertainty of the equivalent hours of actual power generation of the wind farm based on the equivalent hours with a probability of exceeding 50% and the overall uncertainty. The technical solution of the present application improves the accuracy of the calculation of the uncertainty value of the wind farm power generation, and optimizes the wind farm power generation evaluation process.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power, and in particular to a method and device for calculating the uncertainty of equivalent hours of actual power generation in a wind farm. Background Art

[0002] With the rapid growth of my country's wind power installed capacity, the wind power industry has made remarkable achievements, but also faced some urgent problems. For example, the equivalent full-power hours of some wind farms after operation did not reach the design expected value, resulting in lower-than-expected asset returns or even losses, which seriously restricted the sustainable development of the wind power industry and became an important hidden danger affecting the healthy development of the industry.

[0003] After analysis, the uncertainty in the early wind resource and power generation assessment leads to a deviation between the design expected value and the actual operation data. At present, the uncertainty of power generation is mainly calculated in China based on the "Probability-based Power Generation Calculation Method" issued by the Renewable Energy Expert Technical Committee. However, in actual projects, the exceedance probability is usually selected for evaluation based on experience, and there is a lack of systematic post-evaluation research on the uncertainty of the calculation results. In addition, there is currently no systematic research on post-evaluation methods, which to a certain extent limits the accuracy of uncertainty evaluation results and the application effect in actual engineering. Compared with the early assessment of the uncertainty of wind farm power generation, for wind farms that have been in operation, when conducting uncertainty calculation review, the loss values ​​and some uncertainty parameters in their actual operation data can be referred to. How to correct the value of wind farm power generation uncertainty based on the analysis method of post-evaluation results has become an urgent issue to be solved in the industry. Summary of the invention

[0004] The present invention provides a method and device for calculating the uncertainty of actual equivalent hours of power generation in a wind farm, which are used to correct loss uncertainty and power curve uncertainty based on post-evaluation of the wind farm and calculate the uncertainty of actual equivalent hours of power generation in the wind farm.

[0005] According to a first aspect of the present invention, a method for calculating the uncertainty of equivalent hours of actual power generation of a wind farm is provided. The method for calculating the uncertainty of equivalent hours of actual power generation of a wind farm comprises: Obtaining preliminary design data and operation data of the wind farm, wherein the preliminary design data includes reduction factors; Calculate the various losses through the numerical calculation relationship between the various losses and the reduction coefficients, wherein the various losses include any one or more of equipment availability, electrical loss, fan performance loss, environmental factor loss, control strategy and other cause loss, and wake loss; Calculate the total loss through the various losses, and calculate the theoretical equivalent hours of the wind farm through the overall theoretical power generation of the wind farm and the installed capacity of the wind farm; Calculate the equivalent hours of the wind farm with a exceedance probability of 50% according to the total loss and the theoretical equivalent hours of the wind farm, and calculate the overall uncertainty according to each uncertainty; According to the equivalent hours with a exceedance probability of 50% and the overall uncertainty of the wind farm, the uncertainty of the equivalent hours of actual power generation of the wind farm is calculated by using an error function method.

[0006] In one embodiment, it further includes: The preliminary design data includes any one or more of the original data of the wind tower, the mesoscale data, the simulation results and the reduction factor, wherein the simulation results include the theoretical power generation and wake loss of each wind turbine; The uncertainty includes any one or more of measurement uncertainty u1, data interpolation uncertainty u2, vertical extrapolation uncertainty u3, long-term correction uncertainty u4, future wind climate uncertainty u5, model uncertainty u6, power curve uncertainty u7 and loss uncertainty u8; The losses include any one or more of equipment availability s1, electrical loss s2, fan performance loss s3, environmental factor loss s4, control strategy and other reasons loss s5 and wake loss s6.

[0007] In one embodiment, it further includes: The wind farm operation period data include any one or more of the wind farm energy availability a1, wind farm power consumption and line loss a2, power curve compliance a3, power restriction rate a4 and statistical wind turbine online equivalent power generation hours a5; The reduction factors include any one or more of wind turbine availability b1, plant power consumption and line loss b2, power curve correction b3, blade pollution reduction b4, climate impact reduction b5, future wind farm impact b6 control and turbulence intensity impact b7, power restriction b8 and wake impact reduction b9.

[0008] In one embodiment, the calculating of the total loss by using the various losses, and the calculating of the theoretical equivalent hours of the wind farm by using the overall theoretical power generation of the wind farm and the installed capacity of the wind farm, include: Total loss total The calculation formula is as follows:

[0009] The calculation formula of theoretical equivalent hours ETH of wind farm is as follows:

[0010] Among them, the sum of the theoretical power generation of each wind turbine is the overall theoretical power generation of the wind farm.

[0011] In one embodiment, the calculating of the equivalent hours for which the probability of exceedance of the wind farm is 50% according to the total loss and the theoretical equivalent hours of the wind farm, and the calculating of the overall uncertainty according to the various uncertainties include: The equivalent number of hours P50Hrs for a wind farm to exceed the probability of 50% is calculated using the following formula: P50Hrs=ETH*(1-s total ) Among them, P50Hrs is the equivalent hours when the probability of wind farm exceedance is 50%, ETH is the theoretical equivalent hours of wind farm, and s total is the total loss; Calculate the overall uncertainty u total , the formula is as follows:

[0012] Among them, u total is the overall uncertainty, u1 is the measurement uncertainty, u2 is the data interpolation uncertainty, u3 is the vertical extrapolation uncertainty, u4 is the long-term correction uncertainty, u5 is the future wind climate uncertainty, u6 is the model uncertainty, u7 is the power curve uncertainty, and u8 is the loss uncertainty; The power curve uncertainty u7 and loss uncertainty u8 are calculated using the estimated loss measurement correction uncertainty calculation method EL-RMCUCM. The power curve uncertainty u7 is obtained by the following formula:

[0013] The loss uncertainty u8 is given by the following formula:

[0014] Measurement uncertainty u1, data interpolation uncertainty u2, vertical extrapolation uncertainty u3, long-term correction uncertainty u4, future wind climate uncertainty u5, and model uncertainty u6 can be calculated through the "Probability-based Power Generation Calculation Method" issued by the Renewable Energy Expert Technical Committee.

[0015] In one embodiment, the uncertainty of the equivalent hours of actual power generation of the wind farm is calculated using an error function method according to the equivalent hours with a exceedance probability of 50% and the overall uncertainty, including: The uncertainty of the actual equivalent hours of power generation in a wind farm follows a normal distribution, and the value of the uncertainty is calculated using the following formula:

[0016]

[0017] Where, σ=P50Hrs*u total / 100, UncertaintyEH is the uncertainty of the equivalent hours of actual power generation of the wind farm, Erf is the error function, P50Hrs is the equivalent hours with a 50% exceedance probability of the wind farm, a5 is the equivalent hours of wind turbines connected to the grid, u total is the overall uncertainty.

[0018] According to a second aspect of the present invention, a method and apparatus for calculating the uncertainty of equivalent hours of actual power generation in a wind farm is provided, comprising: An acquisition module is used to acquire the preliminary design data and the operation data of the wind farm, wherein the preliminary design data includes the reduction factor; A first calculation module is used to calculate each loss through a numerical calculation relationship between each loss and the reduction coefficient, wherein each loss includes any one or more of equipment availability, electrical loss, fan performance loss, environmental factor loss, control strategy and other reasons loss, and wake loss; A second calculation module is used to calculate the total loss through the various losses, and to calculate the theoretical equivalent hours of the wind farm through the overall theoretical power generation of the wind farm and the installed capacity of the wind farm; A third calculation module is used to calculate the equivalent hours of the wind farm with a exceedance probability of 50% according to the total loss and the theoretical equivalent hours of the wind farm, and to calculate the overall uncertainty according to each uncertainty; The fourth calculation module is used to calculate the uncertainty of the equivalent hours of actual power generation of the wind farm by using an error function method according to the equivalent hours with a exceedance probability of 50% and the overall uncertainty of the wind farm.

[0019] According to a third aspect of the present invention, there is provided an electronic device, the electronic device comprising: a communication interface, a processor, and a memory; The memory is used to store program instructions, and when the program instructions are executed by the processor that is communicatively connected to the memory through the communication interface, any of the above-mentioned methods for calculating the uncertainty of the equivalent hours of actual power generation of a wind farm is implemented.

[0020] According to a fourth aspect of the present invention, there is provided a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a computer (e.g., a processor in the computer), implement any of the above-mentioned methods for calculating the uncertainty of the actual equivalent hours of power generation of a wind farm.

[0021] In summary, the present invention provides a method and device for calculating the uncertainty of the actual equivalent hours of power generation of a wind farm, the method comprising: obtaining preliminary design data and period operation data of the wind farm, the preliminary design data comprising a reduction factor; calculating each loss through a numerical calculation relationship between each loss and the reduction factor, the each loss comprising any one or more of equipment availability, electrical loss, wind turbine performance loss, environmental factor loss, control strategy and other cause loss, and wake loss; calculating the total loss through the each loss, and calculating the theoretical equivalent hours of the wind farm through the overall theoretical power generation of the wind farm and the installed capacity of the wind farm; calculating the equivalent hours of the wind farm with a probability of exceeding 50% based on the total loss and the theoretical equivalent hours of the wind farm, and calculating the overall uncertainty based on each uncertainty; and calculating the uncertainty of the actual equivalent hours of power generation of the wind farm using an error function method based on the equivalent hours of the wind farm with a probability of exceeding 50% and the overall uncertainty. The technical solution of the present application calculates the loss value of the preliminary project through the corresponding relationship between the reduction coefficient and the loss, effectively solving the conversion problem when using the reduction coefficient to calculate the power generation in the preliminary power generation assessment, and realizing the function of converting the reduction coefficient into the loss value for uncertainty calculation. By adopting the estimated loss measured correction uncertainty calculation method (EL-RMCUCM), it is possible to obtain more accurate power curve uncertainty and loss uncertainty in combination with the actual operation of the wind farm. The present invention has important guiding significance in the calculation of uncertainty values ​​of wind farm power generation based on post-evaluation, can improve the accuracy of uncertainty calculation, optimize the wind farm power generation assessment process, and provide reliable technical support for engineering practice. It not only has significant industrial application value in actual wind farm projects, but also shows broad application prospects in the engineering field.

[0022] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0023] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 A flow chart of a method for calculating the uncertainty of equivalent hours of actual power generation in a wind farm provided by an embodiment of the present invention; Figure 2 A structural diagram of a method and device for calculating the uncertainty of equivalent hours of actual power generation in a wind farm provided by an embodiment of the present invention; Figure 3 A structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is only to provide a better understanding of the present application by illustrating the examples of the present application.

[0027] It should be noted that, in this article, relational terms such as first and second, etc. 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 statement "include..." do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0028] like Figure 1 As shown, the present invention provides a method for calculating the uncertainty of the equivalent hours of actual power generation of a wind farm, and the method for calculating the uncertainty of the equivalent hours of actual power generation of a wind farm includes: In step S11, the preliminary design data and the operation data of the wind farm are obtained, wherein the preliminary design data includes a reduction factor; In step S12, the various losses are calculated through the numerical calculation relationship between the various losses and the reduction coefficients, wherein the various losses include any one or more of equipment availability, electrical loss, fan performance loss, environmental factor loss, control strategy and other cause loss, and wake loss; In step S13, the total loss is calculated by the various losses, and the theoretical equivalent hours of the wind farm are calculated by the overall theoretical power generation of the wind farm and the installed capacity of the wind farm; In step S14, the equivalent hours for which the wind farm exceedance probability is 50% are calculated according to the total loss and the theoretical equivalent hours of the wind farm, and the overall uncertainty is calculated according to the various uncertainties; In step S15, according to the equivalent hours with a exceedance probability of 50% of the wind farm and the overall uncertainty, the uncertainty of the equivalent hours of actual power generation of the wind farm is calculated using an error function method; In one embodiment, the present invention relates to a method for calculating the uncertainty of the equivalent hours of actual power generation of a wind farm, which is particularly important in the evaluation of the power generation performance, design optimization and technological development of the wind power industry of the wind farm. Wind energy is an important renewable energy source, and the power generation capacity of a wind farm is affected by many factors, including wind speed, wind turbine performance, climate change, equipment utilization, etc. Due to the uncertainty of these factors, the evaluation and prediction of the power generation capacity of a wind farm often face great challenges. Equivalent Full Load Hours (EFLH) is an important indicator for evaluating the power generation capacity of a wind farm. It reflects that within a certain period of time, the power generation of a wind farm is equal to the power generation generated by the continuous operation of its rated power. Accurately calculating the actual equivalent hours of power generation of a wind farm and its uncertainty is of vital importance to the operation management, economic benefit analysis and future planning of the wind farm.

[0029] Traditional wind farm power generation assessment methods often fail to fully consider the impact of various uncertain factors, resulting in large deviations in the assessment results. Therefore, how to scientifically and reasonably calculate the uncertainty of the actual equivalent hours of wind farm power generation has become an urgent problem to be solved in current technology.

[0030] The present invention provides a method for calculating the uncertainty of the equivalent hours of actual power generation of a wind farm. The method obtains the preliminary design data and the operation data of the wind farm, and combines multiple factors (such as reduction coefficient, loss, measurement uncertainty, data interpolation uncertainty, etc.) to perform systematic calculations, thereby obtaining the uncertainty of the equivalent hours of actual power generation of the wind farm. Through the comprehensive calculation of multiple factors such as mathematical models, loss models, reduction coefficients, statistical data, etc., the calculation of the uncertainty of power generation of the wind farm is more accurate and comprehensive.

[0031] Obtain the preliminary design data and operation data of the wind farm. The preliminary design data includes the reduction coefficient of the wind farm, and the operation data includes the energy availability, power curve compliance, plant power consumption and line loss of the wind farm. The reduction coefficient is used to correct the ideal power generation capacity of the wind turbine in the evaluation of the wind farm, so as to more truly reflect the power generation performance of the wind turbine in the actual operating environment. The introduction of the reduction coefficient makes the evaluation result closer to the actual power generation situation. The loss calculation involves multiple factors, such as equipment availability, electrical loss, wind turbine performance loss, environmental factor loss, control strategy loss, wake loss, etc. Through the numerical calculation relationship between each loss and the reduction coefficient, each loss is calculated in turn. Finally, the accumulation of all losses forms the total loss. The calculation of loss factors is very complex and variable. Considering that each loss factor has a different impact on the actual power generation capacity, considering them one by one and summing them up can more accurately describe the power generation capacity of the wind farm. The total loss is the comprehensive result of all loss factors. By calculating the theoretical equivalent hours of the wind farm, the actual equivalent hours of the wind farm can be further calculated. The theoretical equivalent hours of the wind farm are calculated by the ratio of the overall theoretical power generation of the wind farm to the installed capacity of the wind farm. Through the above calculation steps, the theoretical equivalent hours (ETH) under an ideal state is obtained, and then the actual equivalent hours of the wind farm are corrected according to the actual losses.

[0032] The equivalent hours of a wind farm not only rely on the above theoretical calculations, but are also affected by many factors such as measurement errors, data interpolation errors, long-term correction errors, and future wind climate changes. Therefore, the calculation of uncertainty is further introduced. Through the comprehensive calculation of various uncertainties, the uncertainty of the equivalent hours of wind farm power generation is obtained, and various uncertainties are considered, including measurement uncertainty, data interpolation uncertainty, vertical extrapolation uncertainty, long-term correction uncertainty, future wind climate uncertainty, model uncertainty, power curve uncertainty, loss uncertainty, etc. The overall uncertainty is finally obtained by weighted average and other methods. After obtaining the overall uncertainty, the uncertainty of the actual equivalent hours of wind farm power generation is further calculated by using the error function method. This method assumes that the uncertainty of the actual equivalent hours of wind farm power generation follows a normal distribution, and estimates the value of the uncertainty through the error function formula.

[0033] The specific formula is:

[0034] Where, σ=P50Hrsutotal / 100, UncertaintyEH is the uncertainty of the equivalent hours of actual power generation of the wind farm, Erf is the error function, P50Hrs is the equivalent hours of the wind farm with a probability of exceeding 50%, a5 is the equivalent hours of wind turbines connected to the grid, u totalThe overall uncertainty can be used to accurately evaluate the final uncertainty of the actual equivalent hours of power generation in the wind farm, providing an important basis for the operation management and investment decision-making of the wind farm.

[0035] By comprehensively considering the reduction factor, loss factors and various uncertainties, the calculation of the actual equivalent hours of power generation in the wind farm is more comprehensive and accurate. Not only the influence of a single loss or uncertainty factor is considered, but also the complexity of the operation of the wind farm is fully reflected through the combined calculation of multiple factors. Traditional wind farm evaluation methods often ignore the impact of uncertainty on the results, while the present invention can more accurately reflect the impact of uncertainty on the actual equivalent hours of power generation through the introduction of error functions. It is not only suitable for specific wind farm projects, but can also be adjusted and applied in different regions, different wind turbine models and different operating environments, and has strong versatility.

[0036] The post-evaluation-based calculation method for the uncertainty of wind farm power generation is designed to quantify the uncertainty of the actual equivalent hours of wind farm power generation through a comprehensive analysis of the preliminary design data and operation data of the wind farm, combined with the estimated loss measurement correction uncertainty calculation method (EL-RMCUCM). This method can calculate the power curve uncertainty and loss uncertainty based on the actual operation results, thereby correcting and improving the accuracy of wind farm power generation prediction based on probability, assisting decision-making and having high engineering application value.

[0037] The method includes the following steps: collecting preliminary design data and operation data of the wind farm; calculating the theoretical equivalent hours and wake loss of the wind farm according to the preliminary simulation results of the wind farm; making the reduction coefficient correspond to the loss item in the uncertainty calculation process; calculating various losses and uncertainties; using the estimated loss measured correction uncertainty calculation method EL-RMCUCM to calculate the power curve uncertainty and loss uncertainty respectively; calculating the equivalent hours P50Hrs with a probability of exceedance of 50% of the wind farm, and using the sum of squares method to calculate the combined uncertainty; and finally calculating the uncertainty value corresponding to the actual equivalent hours of power generation of the wind farm.

[0038] Collect preliminary design data and operation data of the wind farm. The preliminary design data include: original data of the wind tower, mesoscale data, simulation results (including theoretical power generation and wake loss of each wind turbine), and reduction factor.

[0039] The operation period data include the energy availability rate of the wind farm a1, the power consumption and line loss of the wind farm a2, the power curve compliance a3, the power restriction rate a4, and the statistical equivalent power generation hours of the wind turbines a5.

[0040] Among them, the reduction factor comes from the early stage of wind farm power generation assessment, mainly covering the following contents: Wind turbine availability b1: does not take into account the impact of downtime caused by maintenance and failure of wind turbines, transmission lines and electrical equipment.

[0041] Blade contamination reduction b4: Ice is prone to occur in the low temperature and high humidity in winter. The blades gradually wear and age with use, and the aerodynamic performance decreases, affecting the power generation performance of the wind turbine.

[0042] Control and turbulence intensity impact b7: In actual operation, wind turbines cannot be fully synchronized with changes in wind speed and direction, and there is often a control lag, resulting in power generation loss.

[0043] Auxiliary power consumption and line loss b2: Energy loss caused by transmission lines and wind farm’s own power consumption, which is generally related to the wind farm’s transmission lines and its own design.

[0044] Power curve correction b3: Considering that the actual power curve of the wind turbine may be different from the standard power curve, appropriate corrections need to be made when calculating the power generation.

[0045] Climate impact reduction b5: The site area may have special climate conditions and destructive weather, which deviate from the design standard climate conditions and the uncertainty needs to be considered.

[0046] Reduction of uncertainties: There are certain uncertainties due to factors that have not been fully taken into account, including software calculation errors and map data errors.

[0047] According to the early simulation results of the wind farm, the theoretical equivalent hours of the wind farm and the wake loss s6 are calculated.

[0048] The calculation formula of the theoretical equivalent hours ETH of a wind farm is as follows:

[0049] The calculation formula of wake loss s6 is:

[0050] Where n is the number of fans.

[0051] The reduction factor corresponds to the loss item in the uncertainty calculation. According to the IEC61400-15 standard, the loss should include: equipment availability, electrical loss, fan performance loss, environmental factor loss, control strategy and other reasons. For the convenience of correspondence, the corresponding relationship between each loss and the reduction factor is listed in Table 1 below: Table 1

[0052] Uncertainty values ​​include: measurement uncertainty u1, data interpolation uncertainty u2, vertical extrapolation uncertainty u3, long-term correction uncertainty u4, future wind climate uncertainty u5, model uncertainty u6, power curve uncertainty u7, loss uncertainty u8. Among them, the calculation method of uncertainty values ​​of u1~u6 is calculated in accordance with the "Probability-based Power Generation Calculation Method" issued by the Renewable Energy Expert Technical Committee.

[0053] In the early stage of evaluation, the reduction factor is usually used to approximate the overall loss of the wind farm. By comparing the value of the reduction factor, the following formula can be obtained: Equipment availability s1 = wind turbine availability b1 Electrical loss s2 = factory power, line loss b2 Fan performance loss s3 = power curve correction b3 Environmental factor loss s4 = blade pollution reduction b4 * climate impact reduction b5 * future wind farm impact b6 Control strategy and other reasons loss s5 = control and turbulence intensity impact b7 * power restriction b8 Wake loss s6 = wake effect reduction b9 The power curve uncertainty and loss uncertainty are calculated using the estimated loss measurement correction uncertainty calculation method EL-RMCUCM, which is as follows: When calculating the loss, the previous loss values ​​are used for calculation, as shown in Table 2 below: Table 2

[0054]

[0055] The power curve uncertainty u7 and loss uncertainty u8 are calculated using the estimated loss measurement correction uncertainty calculation method EL-RMCUCM. When calculating the loss specifically, you can first refer to the values ​​of each loss in the previous evaluation and make the following corrections:

[0056] Among them, a3 is the compliance of the wind farm power curve, b3 is the power curve correction coefficient, and b5 is the climate impact reduction coefficient.

[0057]

[0058] Among them, a1 is the energy availability of the wind farm, a5 is the power restriction rate or the statistical equivalent generating hours of wind turbines connected to the grid, a2 is the actual value of the wind farm's plant power consumption and line loss, b1 is the wind turbine availability reduction coefficient, and b2 is the plant power consumption and line loss reduction coefficient.

[0059] Calculate the equivalent hours P50Hrs when the probability of wind farm exceeding is 50%, and use the sum of squares method to calculate the combined uncertainty. After obtaining the total loss and various uncertainties, the equivalent hours P50Hrs when the probability of wind farm exceeding is 50% can be calculated.

[0060]

[0061] Assuming that the uncertainty follows a normal distribution, the error function method is used to calculate the uncertainty value corresponding to the actual equivalent hours of power generation in the wind farm.

[0062]

[0063]

[0064] Assuming that the uncertainty conforms to the normal distribution, the uncertainty range of power generation is quantified by the error function (erf), and the uncertainty value corresponding to the actual equivalent hours of power generation in the wind farm is calculated.

[0065] The uncertainty of the actual equivalent hours of power generation in a wind farm follows a normal distribution, and the value of the uncertainty is calculated using the following formula:

[0066]

[0067] Where, σ=P50Hrs*u total / 100, UncertaintyEH is the uncertainty of the equivalent hours of actual power generation of the wind farm, Erf is the error function, P50Hrs is the equivalent hours with a 50% exceedance probability of the wind farm, a5 is the equivalent hours of wind turbines connected to the grid, u total is the overall uncertainty.

[0068] The sub-items of the reduction coefficients obtained in the previous calculations are mapped to the corresponding loss items, thereby achieving an accurate correspondence between the reduction coefficients and the losses, and providing data support for subsequent loss correction and uncertainty analysis. Based on the actual operating conditions of the wind farm (including the energy availability of the wind farm, plant power and line loss, power curve compliance, and power restriction rate), the actual power curve uncertainty and loss uncertainty can be calculated using the EL-RMCUCM method. This method effectively corrects the previous loss analysis, thereby improving the accuracy of the uncertainty assessment of the actual equivalent hours of power generation in the wind farm.

[0069] The present invention proposes a method for calculating the uncertainty of wind farm power generation based on post-evaluation, which uses the measured results to correct the losses and uncertainties in the previous evaluation, and can more accurately evaluate the uncertainty of the equivalent hours of actual power generation in the wind farm. The power curve uncertainty and loss uncertainty are calculated by the estimated loss measured correction uncertainty calculation method (EL-RMCUCM), and combined with the normal distribution assumption and the error function method, the evaluation system of the uncertainty of wind farm power generation is further improved. According to the calculation results of this method, the key parameters such as power curve uncertainty and loss uncertainty applicable to the wind farm in the preliminary evaluation can be clarified, and the accuracy of probability-based power generation calculation can be improved, thereby providing strong support for the design, operation and scheduling decisions of the wind farm. The present invention has important guiding significance for the calculation of the uncertainty of wind farm power generation based on post-evaluation, and has high industrial value and good application prospects in engineering practice.

[0070] The present invention proposes a method for calculating the uncertainty of the equivalent hours of actual power generation in a wind farm, which overcomes the shortcomings of traditional wind power evaluation methods that cannot fully consider uncertainty factors. Through reasonable mathematical modeling and multi-factor comprehensive calculation, the evaluation of the power generation capacity of the wind farm is made more accurate. It is not only reflected in the loss model and the uncertainty calculation method, but also includes the calculation method of evaluating the final uncertainty through the error function method, which provides strong support for the design, operation, management and economic benefit analysis of the wind farm. The technical solution in this embodiment calculates the loss value of the preliminary project through the corresponding relationship between the reduction coefficient and the loss, effectively solves the conversion problem when the reduction coefficient is used to calculate the power generation in the preliminary power generation evaluation, and realizes the function of converting the reduction coefficient into the loss value for uncertainty calculation. By adopting the estimated loss measured correction uncertainty calculation method (EL-RMCUCM), it is possible to obtain more accurate power curve uncertainty and loss uncertainty in combination with the actual operation of the wind farm. The present invention has important guiding significance in the calculation of uncertainty values ​​of wind farm power generation based on post-evaluation, can improve the accuracy of uncertainty calculation, optimize the wind farm power generation evaluation process, and provide reliable technical support for engineering practice. It not only has significant industrial application value in actual wind farm projects, but also shows broad application prospects in the engineering field.

[0071] In one embodiment, Figure 2 1 is a block diagram of a method for calculating the uncertainty of equivalent hours of actual power generation in a wind farm according to an exemplary embodiment. Figure 2 It is shown that the calculation method and device for the uncertainty of the actual equivalent hours of power generation in the wind farm includes an acquisition module 21, a first calculation module 22, a second calculation module 23, a third calculation module 24 and a fourth calculation module 25.

[0072] The acquisition module 21 is used to acquire the preliminary design data and the operation data of the wind farm, wherein the preliminary design data includes the reduction factor; The first calculation module 22 is used to calculate each loss through the numerical calculation relationship between each loss and the reduction coefficient, wherein each loss includes any one or more of equipment availability, electrical loss, fan performance loss, environmental factor loss, control strategy and other reasons loss, and wake loss; The second calculation module 23 is used to calculate the total loss through the various losses, and to calculate the theoretical equivalent hours of the wind farm through the overall theoretical power generation of the wind farm and the installed capacity of the wind farm; The third calculation module 24 is used to calculate the equivalent hours of the wind farm with a exceedance probability of 50% according to the total loss and the theoretical equivalent hours of the wind farm, and to calculate the overall uncertainty according to each uncertainty; The fourth calculation module 25 is used to calculate the uncertainty of the equivalent hours of actual power generation of the wind farm using an error function method according to the equivalent hours with a exceedance probability of 50% and the overall uncertainty of the wind farm.

[0073] The acquisition module 21, the first calculation module 22, the second calculation module 23, the third calculation module 24 and the fourth calculation module 25 included in the device block diagram of a method for calculating the uncertainty of the actual equivalent hours of power generation in a wind farm are controlled to execute the method for calculating the uncertainty of the actual equivalent hours of power generation in a wind farm described in any of the above embodiments.

[0074] like Figure 3 As shown, the present invention provides an electronic device 300, the electronic device includes: a communication interface, a processor 301, and a memory 302; The memory 302 is used to store program instructions, and when the program instructions are executed by the processor 301 that is communicatively connected to the memory 302 through the communication interface, the preliminary design data and the period operation data of the wind farm are obtained, and the preliminary design data include the reduction coefficient; the various losses are calculated through the numerical calculation relationship between each loss and the reduction coefficient, and the various losses include any one or more of equipment availability, electrical loss, wind turbine performance loss, environmental factor loss, control strategy and other reasons loss, and wake loss; the total loss is calculated through the various losses, and the theoretical equivalent hours of the wind farm are calculated through the overall theoretical power generation of the wind farm and the installed capacity of the wind farm; the equivalent hours of the wind farm with a exceedance probability of 50% are calculated based on the total loss and the theoretical equivalent hours of the wind farm, and the overall uncertainty is calculated based on the various uncertainties; the uncertainty of the actual power generation equivalent hours of the wind farm is calculated using the error function method based on the equivalent hours with a exceedance probability of 50% and the overall uncertainty.

[0075] The present invention provides a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the preliminary design data and the period operation data of a wind farm are obtained, wherein the preliminary design data include a reduction coefficient; each loss is calculated by a numerical calculation relationship between each loss and the reduction coefficient, wherein each loss includes any one or more of equipment availability, electrical loss, wind turbine performance loss, environmental factor loss, control strategy and other cause loss, and wake loss; the total loss is calculated by the various losses, and the theoretical equivalent hours of the wind farm are calculated by the overall theoretical power generation of the wind farm and the installed capacity of the wind farm; the equivalent hours of the wind farm with a exceedance probability of 50% are calculated according to the total loss and the theoretical equivalent hours of the wind farm, and the overall uncertainty is calculated according to each uncertainty; the uncertainty of the actual power generation equivalent hours of the wind farm is calculated by an error function method according to the equivalent hours of the wind farm with a exceedance probability of 50% and the overall uncertainty.

[0076] It should be understood that the specific features, operations and details described hereinabove about the method of the present invention may also be similarly applied to the device and system of the present invention, or, vice versa. In addition, each step of the method of the present invention described above may be performed by the corresponding parts or units of the device or system of the present invention.

[0077] It should be understood that each module / unit of the device of the present invention can be implemented in whole or in part by software, hardware, firmware or a combination thereof. Each module / unit can be embedded in the processor of the computer device in the form of hardware or firmware or independent of the processor, or can be stored in the memory of the computer device in the form of software for the processor to call to perform the operation of each module / unit. Each module / unit can be implemented as an independent component or module, or two or more modules / units can be implemented as a single component or module.

[0078] In one embodiment, a computer device is provided, which includes a memory and a processor, and the memory stores computer instructions executable by the processor, and the computer instructions instruct the processor to execute each step of the method of the embodiment of the present invention when executed by the processor. The computer device can be a server, a terminal, or any other electronic device with necessary computing and / or processing capabilities in a broad sense. In one embodiment, the computer device may include a processor, a memory, a network interface, a communication interface, etc. connected through a system bus. The processor of the computer device can be used to provide necessary computing, processing and / or control capabilities. The memory of the computer device may include a non-volatile storage medium and an internal memory. An operating system, a computer program, etc. may be stored in or on the non-volatile storage medium. The internal memory can provide an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface and the communication interface of the computer device can be used to connect and communicate with external devices through a network. The steps of the method of the present invention are executed by the processor.

[0079] The present invention may be implemented as a computer-readable storage medium having a computer program stored thereon, which causes the steps of the method of an embodiment of the present invention to be executed when executed by a processor. In one embodiment, the computer program is distributed on a plurality of computer devices or processors coupled to a network so that the computer program is stored, accessed, and executed in a distributed manner by one or more computer devices or processors. A single method step / operation, or two or more method steps / operations, may be performed by a single computer device or processor or by two or more computer devices or processors. One or more method steps / operations may be performed by one or more computer devices or processors, and one or more other method steps / operations may be performed by one or more other computer devices or processors. One or more computer devices or processors may perform a single method step / operation, or perform two or more method steps / operations.

[0080] It will be appreciated by those skilled in the art that the method steps of the present invention may be performed by instructing related hardware such as a computer device or a processor through a computer program, and the computer program may be stored in a non-temporary computer-readable storage medium, which causes the steps of the present invention to be performed when the computer program is executed. Depending on the circumstances, any reference to memory, storage, database, or other media herein may include non-volatile and / or volatile memory. Examples of non-volatile memory include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, magnetic tape, floppy disk, magneto-optical data storage device, optical data storage device, hard disk, solid state disk, etc. Examples of volatile memory include random access memory (RAM), external cache memory, etc.

[0081] The various technical features described above can be combined arbitrarily. Although all possible combinations of these technical features are not described, any combination of these technical features should be considered to be covered by this specification as long as there is no contradiction in such combination.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for calculating the uncertainty of equivalent hours of actual power generation in a wind farm, characterized in that: include: Obtaining preliminary design data and operation data of the wind farm, wherein the preliminary design data includes reduction factors; Calculate the various losses through the numerical calculation relationship between the various losses and the reduction coefficients, wherein the various losses include any one or more of equipment availability, electrical loss, fan performance loss, environmental factor loss, control strategy and other cause loss, and wake loss; Calculate the total loss through the various losses, and calculate the theoretical equivalent hours of the wind farm through the overall theoretical power generation of the wind farm and the installed capacity of the wind farm; Calculate the equivalent hours of the wind farm with a exceedance probability of 50% according to the total loss and the theoretical equivalent hours of the wind farm, and calculate the overall uncertainty according to each uncertainty; According to the equivalent hours with a exceedance probability of 50% and the overall uncertainty of the wind farm, the uncertainty of the equivalent hours of actual power generation of the wind farm is calculated by using an error function method.

2. The method for calculating the uncertainty of the equivalent hours of actual power generation of a wind farm according to claim 1, characterized in that: Also includes: The preliminary design data includes any one or more of the original data of the wind tower, the mesoscale data, the simulation results and the reduction factor, wherein the simulation results include the theoretical power generation and wake loss of each wind turbine; The uncertainty includes any one or more of measurement uncertainty u1, data interpolation uncertainty u2, vertical extrapolation uncertainty u3, long-term correction uncertainty u4, future wind climate uncertainty u5, model uncertainty u6, power curve uncertainty u7 and loss uncertainty u8; The losses include any one or more of equipment availability s1, electrical loss s2, fan performance loss s3, environmental factor loss s4, control strategy and other reasons loss s5 and wake loss s6.

3. The method for calculating the uncertainty of the equivalent hours of actual power generation of a wind farm according to claim 1, characterized in that: Also includes: The wind farm operation period data include any one or more of the wind farm energy availability a1, wind farm power consumption and line loss a2, power curve compliance a3, power restriction rate a4 and statistical wind turbine online equivalent power generation hours a5; The reduction factors include any one or more of wind turbine availability b1, plant power consumption and line loss b2, power curve correction b3, blade pollution reduction b4, climate impact reduction b5, future wind farm impact b6 control and turbulence intensity impact b7, power restriction b8 and wake impact reduction b9.

4. The method for calculating the uncertainty of the equivalent hours of actual power generation of a wind farm according to claim 3, characterized in that: The calculation of the total loss through the various losses, and the calculation of the theoretical equivalent hours of the wind farm through the overall theoretical power generation of the wind farm and the installed capacity of the wind farm, include: Total loss total The calculation formula is as follows: The calculation formula of theoretical equivalent hours ETH of wind farm is as follows: Among them, the sum of the theoretical power generation of each wind turbine is the overall theoretical power generation of the wind farm.

5. The method for calculating the uncertainty of the equivalent hours of actual power generation of a wind farm according to claim 4, characterized in that: The calculating of the equivalent hours for which the probability of exceedance of the wind farm is 50% according to the total loss and the theoretical equivalent hours of the wind farm, and the calculating of the overall uncertainty according to each uncertainty, include: The equivalent number of hours P50Hrs for a wind farm to exceed the probability of 50% is calculated using the following formula: P50Hrs=ETH*(1-s total ) Among them, P50Hrs is the equivalent hours when the probability of wind farm exceedance is 50%, ETH is the theoretical equivalent hours of wind farm, and s total is the total loss; Calculate the overall uncertainty u total , the formula is as follows: Among them, u total is the overall uncertainty, u1 is the measurement uncertainty, u2 is the data interpolation uncertainty, u3 is the vertical extrapolation uncertainty, u4 is the long-term correction uncertainty, u5 is the future wind climate uncertainty, u6 is the model uncertainty, u7 is the power curve uncertainty, and u8 is the loss uncertainty; The power curve uncertainty u7 and loss uncertainty u8 are calculated using the estimated loss measurement correction uncertainty calculation method EL-RMCUCM. The power curve uncertainty u7 is obtained by the following formula: The loss uncertainty u8 is given by the following formula: Measurement uncertainty u1, data interpolation uncertainty u2, vertical extrapolation uncertainty u3, long-term correction uncertainty u4, future wind climate uncertainty u5, and model uncertainty u6 can be calculated through the "Probability-based Power Generation Calculation Method" issued by the Renewable Energy Expert Technical Committee.

6. The method for calculating the uncertainty of the equivalent hours of actual power generation of a wind farm according to claim 5, characterized in that: The uncertainty of the actual power generation equivalent hours of the wind farm is calculated by using the error function method according to the equivalent hours with a exceedance probability of 50% and the overall uncertainty, including: The uncertainty of the actual equivalent hours of power generation in a wind farm follows a normal distribution, and the value of the uncertainty is calculated using the following formula: Where, σ=P50Hrs*u total / 100, UncertaintyEH is the uncertainty of the equivalent hours of actual power generation of the wind farm, Erf is the error function, P50Hrs is the equivalent hours with a 50% exceedance probability of the wind farm, a5 is the equivalent hours of wind turbines connected to the grid, u total is the overall uncertainty.

7. A method and device for calculating the uncertainty of equivalent hours of actual power generation in a wind farm, characterized in that: include: An acquisition module is used to acquire the preliminary design data and the operation data of the wind farm, wherein the preliminary design data includes the reduction factor; A first calculation module is used to calculate each loss through a numerical calculation relationship between each loss and the reduction coefficient, wherein each loss includes any one or more of equipment availability, electrical loss, fan performance loss, environmental factor loss, control strategy and other reasons loss, and wake loss; A second calculation module is used to calculate the total loss through the various losses, and to calculate the theoretical equivalent hours of the wind farm through the overall theoretical power generation of the wind farm and the installed capacity of the wind farm; A third calculation module is used to calculate the equivalent hours of the wind farm with a exceedance probability of 50% according to the total loss and the theoretical equivalent hours of the wind farm, and to calculate the overall uncertainty according to each uncertainty; The fourth calculation module is used to calculate the uncertainty of the equivalent hours of actual power generation of the wind farm by using an error function method according to the equivalent hours with a exceedance probability of 50% and the overall uncertainty of the wind farm.

8. The method and device for calculating the uncertainty of equivalent hours of actual power generation in a wind farm according to claim 7, characterized in that: The acquisition module, the first calculation module, the second calculation module, the third calculation module and the fourth calculation module are controlled to execute the method for calculating the uncertainty of the actual equivalent hours of power generation in a wind farm as described in any one of claims 1-6.

9. An electronic device, characterized in that: include: Communication interface, processor, memory; Wherein, the memory is used to store program instructions, and when the program instructions are executed by the processor that is communicatively connected to the memory through the communication interface, the electronic device implements the method for calculating the uncertainty of the actual equivalent hours of power generation of a wind farm as described in any one of claims 1 to 6.

10. A computer-readable storage medium having program instructions stored thereon, characterized in that: When the program instructions are executed by a computer, the computer implements the method for calculating the uncertainty of the actual equivalent hours of power generation of a wind farm as described in any one of claims 1 to 6.

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