Method and device for determining loss of power generation of a wind farm
By generating failure scenarios and random power generation scenarios for wind farms using the Monte Carlo simulation method, and combining the wind farm topology and component maintenance time, the uncertainty problem in wind farm power generation loss assessment is solved, and more accurate loss rate calculation is achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHANGHAI ELECTRIC WIND POWER GRP CO LTD
- Filing Date
- 2022-05-25
- Publication Date
- 2026-05-12
AI Technical Summary
In existing technologies, deterministic analysis of wind farm power generation loss cannot effectively handle the uncertainty caused by unavailability, resulting in inaccurate assessment of power generation loss.
The Monte Carlo simulation method is used to generate failure scenarios and random power generation scenarios of wind farms at different time periods. Combined with the topology of the wind farm and the maintenance time of components, the power generation loss rate of the wind farm is calculated.
It provides a more comprehensive and accurate assessment of wind farm power generation losses, supports optimized design and maintenance strategies, and improves the effectiveness of the assessment.
Smart Images
Figure CN115483677B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of wind farms, and more particularly to a method and apparatus for determining the power generation loss of a wind farm. Background Technology
[0002] Typically, wind farm power generation loss due to unavailability is calculated using deterministic methods. For example, assuming an unavailability rate of 3%, the annual average power generation (AEP) loss due to unavailability can be calculated using the following formula:
[0003] AEP Loss =3% × AEP
[0004] The unavailability of a power transmission system depends on many factors, such as equipment failure rate and downtime.
[0005] Existing technologies address this issue from a deterministic perspective, assuming that the average annual power generation loss due to unavailability is deterministic. However, in reality, these average annual power generation losses due to unavailability have a significant degree of uncertainty. Summary of the Invention
[0006] This application provides a method and apparatus for determining the power generation loss of a wind farm.
[0007] Specifically, this application is implemented through the following technical solution:
[0008] This application provides a method for determining the power generation loss of a wind farm, the method comprising:
[0009] The failure rate of different components in the power transmission system of the wind farm, the power data of the wind turbine generators deployed in the wind farm, and the wind resource data of the wind farm are obtained.
[0010] The failure rates of the different components, the power data, and the wind resource data are all input into the Monte Carlo simulation module;
[0011] In the scenario generation module of the Monte Carlo simulation module, sample data of failure scenarios of the wind farm at different times in different time periods are generated based on the failure rate of the different components, and first random power generation scenario data without considering component damage is generated based on the power data and the wind resource data in the different time periods. The sample data includes the failure time of the failed components in the failure scenarios.
[0012] In the calculation module of the Monte Carlo simulation module, based on the sample data, the topology of the wind farm, and the preset maintenance time corresponding to the different components, the second random power generation scenario data considering component damage is determined in the different time periods. Based on the first random power generation scenario data, the first expected total power generation of the wind farm without considering component damage is determined in the different time periods. Based on the second random power generation scenario data, the second expected total power generation of the wind farm considering component damage is determined in the different time periods.
[0013] Based on the first expected total power generation and the second expected total power generation, the power generation loss rate of the wind farm in the different time periods is determined.
[0014] Optionally, generating sample data of failure scenarios of the wind farm at different times within different time periods based on the failure rates of the different components includes:
[0015] Based on the failure rates of the different components, sample data of failure scenarios of the wind farm at different times within different time periods are generated using Poisson distribution.
[0016] Optionally, generating the first random power generation scenario data for different time periods without considering component damage, based on the power data and the wind resource data, includes:
[0017] Based on the wind resource data, random wind direction data for the different components in the different time periods are generated through multiple distributions.
[0018] Based on the random wind direction data, random wind speed data for the different components in the different time periods are generated using Weibull distribution;
[0019] Based on the power data and the random wind speed data, determine the first random power generation scenario data for different time periods without considering component damage.
[0020] Optionally, determining the second random power generation scenario data considering component damage within the different time periods based on the sample data, the topology of the wind farm, and the preset maintenance durations corresponding to the different components includes:
[0021] Based on the failure time of the failed component in the sample data, the topology of the wind farm, and the maintenance time corresponding to the failed component, calculate the first power generation of the wind farm in the corresponding failure scenario, and the second power generation of the wind farm when there is no failed component in the different time periods, until the operating time of the wind farm reaches the total time corresponding to the different time periods.
[0022] Based on the first power generation and the second power generation, determine the second random power generation scenario data considering component damage within the different time periods.
[0023] Optionally, calculating the first power generation of the wind farm in the corresponding failure scenario based on the failure time of the failed component in the sample data, the topology of the wind farm, and the maintenance time corresponding to the failed component includes:
[0024] Based on the failure time of the failed component in the sample data, the topology of the wind farm, and the maintenance time corresponding to the failed component, the downtime of the wind turbine generator set where the failed component is located and the associated wind turbine generator sets are determined. The power generation of the associated wind turbine generator sets is affected by the downtime of the wind turbine generator set where the failed component is located.
[0025] Based on the downtime and associated wind turbine generators, calculate the first power generation of the wind farm in the corresponding failure scenario.
[0026] Optionally, when the failed component is a cable, the associated wind turbine generator set is connected to the wind turbine generator set containing the cable via the cable.
[0027] Optionally, determining the power generation loss rate of the wind farm in different time periods based on the first expected total power generation and the second expected total power generation includes:
[0028] The power generation loss rate of the wind farm in different time periods is determined by the ratio of the power generation difference obtained by subtracting the second expected power generation from the first expected total power generation to the first expected total power generation.
[0029] Optionally, the different components include at least two of the following: cables, converters, and transformers.
[0030] Optionally, acquiring the failure rate of different components in the power transmission system of the wind farm, the power data of the wind turbine generators deployed in the wind farm, and the wind resource data of the wind farm includes:
[0031] Based on the current wind farm design scheme, select the failure rate of the corresponding type of component from the failure rate database, and determine the power data of the wind turbine generators deployed in the current wind farm and the wind resource data of the current wind farm.
[0032] The design scheme includes the wind turbine deployment scheme of the current wind farm and the model of the deployed wind turbine generators. The model of the different components is related to the model of the wind turbine generators.
[0033] Optionally, the wind farm is an offshore wind farm.
[0034] This application also provides an apparatus for determining wind farm power generation loss, including one or more processors, for implementing the method for determining wind farm power generation loss as described in any of the above embodiments.
[0035] This application also provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the method for determining the power generation loss of a wind farm as described in any of the above embodiments.
[0036] According to the technical solution provided in the embodiments of this application, considering the failure rate, power data and wind resource data of different components in the power transmission system of the wind farm, the power generation loss of the wind farm can be assessed more comprehensively and effectively, providing a more effective basis for optimizing the design scheme and maintenance strategy.
[0037] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description
[0038] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0039] Figure 1 This is a flowchart illustrating an exemplary embodiment of the present application of a method for determining power generation loss in a wind farm;
[0040] Figure 2 This is an exemplary embodiment of the present application illustrating the process of determining the second random power generation scenario data considering component damage within different time periods based on sample data, the topology of the wind farm, and the preset maintenance time corresponding to different components.
[0041] Figure 3 This is a schematic diagram of a wind farm layout shown in an exemplary embodiment of this application;
[0042] Figure 4 This is a schematic diagram of the structure of a device for determining the power generation loss of a wind farm, as shown in an exemplary embodiment of this application. Detailed Implementation
[0043] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.
[0044] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.
[0045] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."
[0046] The method and apparatus for determining wind farm power generation loss according to this application will be described in detail below with reference to the accompanying drawings. Unless otherwise specified, the features in the following embodiments and implementations can be combined with each other.
[0047] In this embodiment of the application, the power generation of the wind farm refers to the power generation transmitted from the wind farm to the grid. The power transmission system is used to transmit the power generated by the wind farm through wind power generation to the grid.
[0048] The wind farms in this application embodiment can be offshore wind farms or onshore wind farms.
[0049] Figure 1 This is a flowchart illustrating an exemplary embodiment of this application, showing a method for determining wind farm power generation loss. The method for determining wind farm power generation loss in this embodiment can be applied to any device with data processing capabilities, such as a computer. See also... Figure 1 The method for determining the power generation loss of a wind farm provided in this application embodiment may include steps S11 to S15.
[0050] In S11, the failure rate of different components in the power transmission system of the wind farm, the power data of the wind turbine generators deployed in the wind farm, and the wind resource data of the wind farm are obtained.
[0051] It should be noted that in the embodiments of this application, the design of the wind farm has been completed, that is, the wind farm deployment plan and the model of the wind turbine generators to be deployed have been completed.
[0052] The component in S11 refers to the component that, when it fails, can affect the amount of electricity generated by the wind farm and transmitted to the grid.
[0053] Different components may include at least two of cables, converters and transformers; it is understood that different components may also be other components of the wind farm.
[0054] For example, different components include cables, converters, and transformers.
[0055] In this embodiment of the application, when acquiring the failure rates of different components of a wind farm, the power data of the wind turbine generators deployed in the wind farm, and the wind resource data of the wind farm, specifically, based on the current wind farm design scheme, the failure rate of the corresponding model of component is selected from the failure rate database, and the power data of the wind turbine generators deployed in the current wind farm and the wind resource data of the current wind farm are determined. The design scheme includes the current wind farm deployment scheme and the model of the deployed wind turbine generators; the models of different components are related to the models of the wind turbine generators. For example, the failure rate of cables is 100 km / year.
[0056] During the wind farm design process, cable models can be selected from the submarine cable model database, converter models can be selected from the converter model database, and transformer models can be selected from the transformer model database.
[0057] The wind turbine deployment scheme for a wind farm can adopt existing deployment schemes or be designed according to needs.
[0058] The components of a wind farm are interconnected. The failure of one component may lead to the failure of at least some of the other components, and the power generated by at least some wind turbines may not be transmitted. Therefore, the topology of the transmission network will affect the power generation, which cannot be considered in existing deterministic analyses.
[0059] In S12, the failure rate, power data, and wind resource data of different components are all input into the Monte Carlo simulation module.
[0060] In S13, in the scenario generation module of the Monte Carlo simulation module, sample data of failure scenarios of wind farm at different times in different time periods are generated based on the failure rate of different components. In addition, the first random power generation scenario data without considering component damage is generated based on power data and wind resource data in different time periods. The sample data includes the failure time of the failed component in the failure scenario.
[0061] It should be noted that not considering component damage in different time periods means that all components that can affect the power generation transmitted from the wind farm to the grid are working normally in different time periods (i.e., ideal power generation scenario).
[0062] In this way, we can know at what moment within what time period the corresponding component failed, that is, we can know the failure time of the corresponding component.
[0063] Each failure scenario may include at least one failure component, and the types of failure components corresponding to different failure scenarios may be different or the same.
[0064] Different time periods can refer to different years within the expected lifespan of the wind farm. For example, if the expected lifespan is 25 years, the different time periods can be different years within those 25 years, and the time periods can be different months within those different years. Alternatively, the total duration of the different time periods can also be less than the expected lifespan of the wind farm.
[0065] When generating sample data of failure scenarios for wind farms at different times within different time periods based on the failure rates of different components, optionally, sample data of failure scenarios for wind farms at different times within different time periods can be generated using a Poisson distribution based on the failure rates of different components. It is understood that other models can also be used to generate sample data of failure scenarios for wind farms at different times within different time periods.
[0066] When generating scenario data for the first random power generation without considering component damage in different time periods based on power data and wind resource data, optionally, random wind direction data for different components in different time periods can be generated using a multinomial distribution based on wind resource data. Then, random wind speed data for different components in different time periods can be generated using a Weibull distribution based on the random wind direction data for different components in different time periods. Finally, based on the power data and the random wind speed data for different components in different time periods, the scenario data for the first random power generation without considering component damage in different time periods can be determined. It is understood that other models can also be used to generate scenario data for the first random power generation without considering component damage in different time periods.
[0067] In S14, within the calculation module of the Monte Carlo simulation module, based on sample data, the topology of the wind farm, and the preset maintenance durations corresponding to different components, the second random power generation scenario data considering component damage is determined for different time periods. Based on the first random power generation scenario data, the first expected total power generation of the wind farm without considering component damage is determined for different time periods. Based on the second random power generation scenario data, the second expected total power generation of the wind farm considering component damage is determined for different time periods.
[0068] Figure 2 This is a schematic diagram illustrating an exemplary embodiment of the present application, showing the process of determining second random power generation scenario data considering component damage within different time periods based on sample data, the topology of a wind farm, and preset maintenance times corresponding to different components; as shown in the diagram. Figure 2As shown, an implementation process for determining the second random power generation scenario data considering component damage within different time periods, based on sample data, the topology of the wind farm, and the preset maintenance time corresponding to different components, may include the following steps:
[0069] S21. Based on the failure time of the failed components in the sample data, the topology of the wind farm, and the maintenance time corresponding to the failed components, calculate the first power generation of the wind farm in the corresponding failure scenario, and the second power generation of the wind farm when there are no failed components in different time periods, until the operating time of the wind farm reaches the total time corresponding to different time periods.
[0070] The calculation of the first power generation of the wind farm in the corresponding failure scenario, based on the failure time of the failed components in the sample data, the topology of the wind farm, and the maintenance time corresponding to the failed components, may include the following steps:
[0071] (1) Based on the failure time of the failed component in the sample data, the topology of the wind farm and the maintenance time corresponding to the failed component, determine the downtime of the wind turbine generator set where the failed component is located and the associated wind turbine generator set. The power generation of the associated wind turbine generator set is affected by the downtime of the wind turbine generator set where the failed component is located.
[0072] Downtime is the sum of the failure time of the failed component and the corresponding maintenance time for that failed component.
[0073] In this scenario, when the failed component is a cable, the associated wind turbine and the wind turbine containing the cable are connected via the cable. In this failure scenario, the wind turbine containing the failed component shuts down and does not generate electricity. The associated wind turbine may continue operating and generate electricity, but due to the failure of the electricity transmission path, the electricity generated by the associated wind turbine cannot be transmitted to the grid.
[0074] When the failed component is the converter of a wind turbine, and the associated wind turbine is located adjacent to it, the failure of the latter will result in the wind turbine shutting down and generating no electricity. Because the latter wind turbine is shut down, the operation of the associated wind turbines will not be affected by its operation (e.g., wake effect). Therefore, the power generation of the associated wind turbines may change due to the shutdown of the former.
[0075] (2) Calculate the first power generation of the wind farm in the corresponding failure scenario based on the downtime and associated wind turbine generators.
[0076] During the downtime, the power generation of the wind turbine where the failed component is located is 0, and the power generation of the associated wind turbine is 0 or changes. Specifically, step (2) is to determine the first power generation of the wind farm in the corresponding failure scenario based on the power generation of the associated wind turbine and the power generation of the non-associated wind turbine.
[0077] S22. Based on the first power generation and the second power generation, determine the second random power generation scenario data considering component damage in different time periods.
[0078] The second expected total power generation is determined by the sum of all first power generation and all second power generation determined in S21. Optionally, the second expected total power generation is the sum of all first power generation and all second power generation determined in S21, or the second expected total power generation is obtained by modifying the sum of all first power generation and all second power generation determined in S21.
[0079] In S15, the power generation loss rate of the wind farm in different time periods is determined based on the first expected total power generation and the second expected total power generation.
[0080] When determining the power generation loss rate of a wind farm in different time periods based on a first expected total power generation and a second expected total power generation, optionally, the power generation loss rate can be determined by the ratio of the power generation difference (the difference between the first and second expected total power generation) to the first expected total power generation. For example, the power generation loss rate of a wind farm in different time periods can be the ratio of the power generation difference (the difference between the first and second expected total power generation) to the first expected total power generation, or it can be obtained by adjusting the ratio of the power generation difference (the difference between the first and second expected total power generation) to the first expected total power generation.
[0081] The method for determining wind farm power generation loss in this application embodiment can be applied to both offshore and onshore wind farms.
[0082] Figure 3 For a wind farm consisting of 57 wind turbine generators, the method for determining wind farm power generation loss according to the embodiments of this application is used to calculate... Figure 3 The power generation loss of the wind farm shown is calculated using the parameters in Table 1. The power generation loss of the wind farm due to the failure of components in the power transmission system is 6.3%.
[0083] Table 1
[0084] Component type failure rate Repair time (days) cable 0.08 (100km / year) 60 converter 0.12 (units / year) 30 transformer 0.035 (units / year) 76.89
[0085] The method for determining wind farm power generation loss in this application embodiment takes into account the failure rate, power data and wind resource data of different components of the wind farm, and can more comprehensively and effectively assess the power generation loss of the wind farm, providing a more effective basis for optimizing design schemes and maintenance strategies.
[0086] Corresponding to the aforementioned embodiments of the method for determining wind farm power generation loss, this application also provides embodiments of a device for determining wind farm power generation loss.
[0087] This application also provides an apparatus for determining wind farm power generation loss, including one or more processors, for implementing the wind farm power generation loss determination method in the above embodiments.
[0088] The embodiments of the wind farm power generation loss determination device of this application can be applied to any device with data processing capabilities. The device embodiments can be implemented through software, hardware, or a combination of both. Taking software implementation as an example, as a logical device, it is formed by the processor of any data processing device loading the corresponding computer program instructions from non-volatile memory into memory for execution. From a hardware perspective, such as... Figure 4 The diagram shown is a hardware structure diagram of any data processing-capable device containing the wind farm power generation loss determination device of this application, except... Figure 4 In addition to the processor, memory, network interface, and non-volatile memory shown, any data processing device in the embodiment may also include other hardware depending on the actual function of the data processing device, which will not be described in detail here.
[0089] The specific implementation process of the functions and roles of each unit in the above device can be found in the implementation process of the corresponding steps in the above method, and will not be repeated here.
[0090] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.
[0091] This application also provides a computer-readable storage medium storing a program thereon, which, when executed by a processor, implements the method for determining wind farm power generation loss in the above embodiments.
[0092] The computer-readable storage medium can be an internal storage unit of any data processing device as described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device of any data processing device, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc., equipped on the device. Furthermore, the computer-readable storage medium can include both internal storage units and external storage devices of any data processing device. The computer-readable storage medium is used to store the computer program and other programs and data required by the data processing device, and can also be used to temporarily store data that has been output or will be output.
[0093] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.
Claims
1. A method for determining power generation loss in a wind farm, characterized in that, The method includes: The failure rate of different components in the power transmission system of the wind farm, the power data of the wind turbine generators deployed in the wind farm, and the wind resource data of the wind farm are obtained. The failure rates of the different components, the power data, and the wind resource data are all input into the Monte Carlo simulation module; In the scenario generation module of the Monte Carlo simulation module, sample data of failure scenarios of the wind farm at different times in different time periods are generated based on the failure rate of the different components. Also, first random power generation scenario data without considering component damage is generated based on the power data and the wind resource data in the different time periods. The sample data includes the failure time of the failed components in the failure scenarios. Furthermore, based on the wind resource data, random wind direction data of the different components in the different time periods is generated through multiple distributions. Based on the random wind direction data, random wind speed data for the different components in the different time periods are generated using Weibull distribution; Based on the power data and the random wind speed data, determine the first random power generation scenario data for different time periods without considering component damage; In the calculation module of the Monte Carlo simulation module, based on the sample data, the topology of the wind farm, and the preset maintenance time corresponding to different components, the second random power generation scenario data considering component failure is determined in different time periods. Based on the first random power generation scenario data, the first expected total power generation of the wind farm without considering component failure is determined in different time periods. Based on the second random power generation scenario data, the second expected total power generation of the wind farm considering component failure is determined in different time periods. Specifically, based on the failure time of the failed component in the sample data, the topology of the wind farm, and the maintenance time corresponding to the failed component, the first power generation of the wind farm in the corresponding failure scenario and the second power generation when there are no failed components in the wind farm in different time periods are calculated until the operating time of the wind farm reaches the total duration corresponding to the different time periods. Based on the first power generation and the second power generation, the second random power generation scenario data considering component failure is determined in different time periods. Based on the first expected total power generation and the second expected total power generation, the power generation loss rate of the wind farm in the different time periods is determined.
2. The method for determining wind farm power generation loss according to claim 1, characterized in that, The step of generating sample data of failure scenarios of the wind farm at different times within different time periods based on the failure rates of the different components includes: Based on the failure rates of the different components, sample data of failure scenarios of the wind farm at different times within different time periods are generated using Poisson distribution.
3. The method for determining wind farm power generation loss according to claim 1, characterized in that, The step of calculating the first power generation of the wind farm in the corresponding failure scenario based on the failure time of the failed component in the sample data, the topology of the wind farm, and the maintenance time corresponding to the failed component includes: Based on the failure time of the failed component in the sample data, the topology of the wind farm, and the maintenance time corresponding to the failed component, the downtime of the wind turbine generator set where the failed component is located and the associated wind turbine generator sets are determined. The power generation of the associated wind turbine generator sets is affected by the downtime of the wind turbine generator set where the failed component is located. Based on the downtime and associated wind turbine generators, calculate the first power generation of the wind farm in the corresponding failure scenario.
4. The method for determining wind farm power generation loss according to claim 3, characterized in that, When the failed component is a cable, the associated wind turbine generator set is connected to the wind turbine generator set containing the cable through the cable.
5. The method for determining wind farm power generation loss according to claim 1, characterized in that, Determining the power generation loss rate of the wind farm in different time periods based on the first expected total power generation and the second expected total power generation includes: The power generation loss rate of the wind farm in different time periods is determined by the ratio of the power generation difference obtained by subtracting the second expected power generation from the first expected total power generation to the first expected total power generation.
6. The method for determining wind farm power generation loss according to claim 1, characterized in that, The different components include at least two of the following: cables, converters, and transformers.
7. The method for determining wind farm power generation loss according to claim 1, characterized in that, The acquisition of failure rates of different components in the power transmission system of the wind farm, power data of the wind turbine generators deployed in the wind farm, and wind resource data of the wind farm includes: Based on the current wind farm design scheme, select the failure rate of the corresponding type of component from the failure rate database, and determine the power data of the wind turbine generators deployed in the current wind farm and the wind resource data of the current wind farm. The design scheme includes the wind turbine deployment scheme of the current wind farm and the model of the deployed wind turbine generators. The model of the different components is related to the model of the wind turbine generators.
8. The method for determining wind farm power generation loss according to claim 1, characterized in that, The wind farm in question is an offshore wind farm.
9. A device for determining power generation loss in a wind farm, characterized in that, It includes one or more processors for implementing the method for determining the power generation loss of a wind farm as described in any one of claims 1-8.
10. A computer-readable storage medium, characterized in that, It stores a program that, when executed by a processor, implements the method for determining the power generation loss of a wind farm as described in any one of claims 1-8.