Wind power output sequence simulation method and system considering typical extreme weather process

Abstract

The invention relates to a wind power output sequence simulation method and system considering a typical extreme weather process. The method comprises the following steps: acquiring a wind speed sample containing the extreme weather process and related parameters of a wind power plant; obtaining a wind turbine generator output characteristic function based on the obtained related parameters of the wind power plant; in combination with wind speed sample data, the influence of extreme weather conditions on the fan failure rate is especially considered, and a time-varying failure rate formula of a single wind turbine generator set is obtained; a wind turbine generator output characteristic function and a time-varying failure rate are considered, and a Monte Carlo simulation method is used to solve a wind power output probability distribution sequence considering a typical extreme weather process. The system comprises a data acquisition module, a data processing module and a solving module. According to the method, the problem of difficulty in renewable energy extreme output simulation in traditional power system planning can be solved, and a certain guiding significance is provided for planning of a novel power system containing high-proportion new energy.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system planning and operation, and specifically relates to a wind power output sequence simulation method and system taking into account typical extreme weather processes. Background Art

[0002] As the proportion of new energy continues to increase, the power supply structure of the new power system will change from being dominated by certain and controllable conventional power generation capacity to being dominated by new energy generation capacity with strong uncertainty and weak controllability. This will also bring a series of new problems accordingly. The existing power system balance mode and regulation technology will be difficult to support the power and electricity balance of the new power system.

[0003] Extreme weather is one of the issues that need to be focused on during the construction of new power systems. The length of time that electricity load has been running at a high level, the magnitude of the decline in hydropower generation capacity, and the difficulty of balancing electricity and power are unprecedented. The frequent occurrence of extreme weather events such as high temperature droughts, typhoons, and large-scale cold waves will greatly affect the output of new energy, and may lead to a serious imbalance in the supply and demand of electricity in new power systems with a high proportion of new energy. The superposition of system structure transformation and intensified climate risks has brought double pressure to the safe supply of electricity in new power systems. Therefore, it is necessary to find a method for simulating wind power output sequences that takes into account extreme weather processes to provide a calculation and planning basis for the construction of new power systems. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for simulating wind power output sequence taking into account typical extreme weather processes, so as to make up for the deficiency of traditional power system planning that less consideration is given to the output of new energy under extreme weather conditions.

[0005] In order to achieve the above object, the present invention adopts the following technical solution: The wind power output sequence simulation method considering typical extreme weather processes includes the following steps: Step 1: Obtain wind speed samples and wind farm related parameters including extreme weather processes; Step 2: Based on the wind farm related parameters obtained in step 1, the output characteristic function of the wind turbine is obtained; Step 3: Combine the wind speed sample data in step 1, consider the impact of extreme weather conditions on the wind turbine failure rate, and derive the time-varying failure rate of a single wind turbine; Step 4: Considering the output characteristic function of the wind turbine and the time-varying failure rate, the Monte Carlo simulation method is used to solve the probability distribution sequence of wind power output taking into account typical extreme weather processes.

[0006] A further improvement of the present invention is that, in step 2, the operating principle of the wind turbine generator set is taken into consideration, and based on the relevant parameters of the wind turbine generator set, the output characteristic function of the wind turbine generator set is obtained as follows: (1) In the formula, is the active output of a single wind turbine, MW; are the cut-in wind speed, cut-out wind speed and rated wind speed of the fan, m / s; is the rated power of a single wind turbine, MW.

[0007] A further improvement of the present invention is that, in step 3, combined with the wind speed sample data in step 1, the influence of extreme weather conditions on the wind turbine failure rate is considered, and the time-varying failure rate expression of a single wind turbine is obtained as follows: (2) In the formula, for t Unit failure rate during the period; is the average hourly failure rate of fans under normal weather conditions; b A coefficient greater than 0 represents the vulnerability of the wind turbine in strong wind weather. b The larger the value, the more obvious the impact of wind speed changes on the fan failure rate.

[0008] A further improvement of the present invention is that in step 4, based on the existing wind turbine failure rate and output characteristic function, a Monte Carlo simulation method is used to establish a wind farm output probability model, and through multiple experiments, the wind farm output probability distribution sequence at each moment is obtained, which is the desired wind power output probability distribution sequence taking into account typical extreme weather processes.

[0009] The wind power output sequence simulation system taking into account typical extreme weather processes includes: Data acquisition module, which obtains wind speed samples and wind farm related parameters including extreme weather processes; A first data processing module, based on the wind farm related parameters obtained by the data acquisition module, obtains the wind turbine output characteristic function; The second data processing module combines the wind speed sample data from the data acquisition module, considers the impact of extreme weather conditions on the wind turbine failure rate, and derives the time-varying failure rate of a single wind turbine; The solution module considers the output characteristic function of the wind turbine and the time-varying failure rate, and uses the Monte Carlo simulation method to solve the probability distribution sequence of wind power output taking into account typical extreme weather processes.

[0010] A further improvement of the present invention is that, in the first data processing module, the operating principle of the wind turbine generator set is taken into consideration, and based on the relevant parameters of the wind turbine generator set, the output characteristic function of the wind turbine generator set is obtained as follows: (1) In the formula, is the active output of a single wind turbine, MW; are the cut-in wind speed, cut-out wind speed and rated wind speed of the fan, m / s; is the rated power of a single wind turbine, MW.

[0011] A further improvement of the present invention is that, in the second data processing module, combined with the wind speed sample data in the data acquisition module, the influence of extreme weather conditions on the wind turbine failure rate is considered, and the time-varying failure rate expression of a single wind turbine is obtained as follows: (2) In the formula, for t Unit failure rate during the period; is the average hourly failure rate of fans under normal weather conditions; b A coefficient greater than 0 represents the vulnerability of the wind turbine in strong wind weather. b The larger the value, the more obvious the impact of wind speed changes on the fan failure rate.

[0012] A further improvement of the present invention is that, in the solution module, based on the existing wind turbine failure rate and output characteristic function, a Monte Carlo simulation method is used to establish a wind farm output probability model, and through multiple experiments, the wind farm output probability distribution sequence at each moment is obtained, which is the wind power output probability distribution sequence taking into account typical extreme weather processes.

[0013] An electronic device comprises: a processor and a memory coupled to the processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the steps of the method for simulating a wind power output sequence taking into account typical extreme weather processes are implemented.

[0014] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the wind power output sequence simulation method taking into account typical extreme weather processes.

[0015] Compared with the prior art, the present invention has at least the following beneficial technical effects: The present invention provides a method and system for simulating a wind power output sequence taking into account typical extreme weather processes. The present invention fully considers the operating characteristics of the wind farm, obtains the output characteristic function of the wind turbine, and obtains the time-varying failure rate formula from the wind speed captured by each unit to highlight the impact of extreme weather conditions on the wind farm. The present invention more accurately considers the impact of extreme weather conditions on the operation of the wind farm, and at the same time nests the output characteristic function of the wind turbine and the time-varying failure rate matrix under extreme weather conditions to obtain a wind power output probability distribution sequence taking into account typical extreme weather processes, providing a powerful tool for solving the planning problems of new power systems facing extreme weather conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] 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.

[0017] Figure 1 It is the overall flow chart of the present invention.

[0018] Figure 2 It is the output characteristic function curve of a single wind turbine.

[0019] Figure 3 It is the probability distribution curve of wind power output under normal weather conditions.

[0020] Figure 4 It is the probability distribution curve of wind power output under extreme weather conditions (typhoon).

[0021] Figure 5 This is a structural block diagram of the wind power output sequence simulation system taking into account typical extreme weather processes of the present invention. DETAILED DESCRIPTION

[0022] In the following, only some exemplary embodiments are briefly described. As those skilled in the art will appreciate, the described embodiments may be modified in various ways without departing from the spirit or scope of the present invention. Therefore, the drawings and descriptions are considered to be exemplary and non-restrictive in nature.

[0023] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0024] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0025] It should be further understood that the term "and / or" used in the present description and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0026] Various structural schematic diagrams of the embodiments disclosed in the present invention are shown in the accompanying drawings. These figures are not drawn to scale, and some details are magnified and some details may be omitted for the purpose of clear expression. The shapes of various regions and layers shown in the figures and the relative sizes and positional relationships therebetween are only exemplary, and may deviate in practice due to manufacturing tolerances or technical limitations, and those skilled in the art may additionally design regions / layers with different shapes, sizes, and relative positions according to actual needs.

[0027] The embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0028] Example 1 The method for simulating wind power output sequence taking into account typical extreme weather processes provided by the present invention comprises the following steps: Step 1: Obtain wind speed samples and wind farm related parameters including extreme weather processes; Step 2: Based on the wind farm related parameters obtained in step 1, the output characteristic function of the wind turbine is obtained; Step 3: Combine the wind speed sample data in step 1, consider the impact of extreme weather conditions on the wind turbine failure rate, and derive the time-varying failure rate of a single wind turbine; Step 4: Considering the output characteristic function of the wind turbine and the time-varying failure rate, the Monte Carlo simulation method is used to solve the probability distribution sequence of wind power output taking into account typical extreme weather processes.

[0029] In this embodiment, in step 2, considering the operating principle of the wind turbine generator set, based on the relevant parameters of the wind turbine generator set, the output characteristic function of the wind turbine generator set is obtained as follows: (1) In the formula, is the active output of a single wind turbine, MW; are the cut-in wind speed, cut-out wind speed and rated wind speed of the fan, m / s; is the rated power of a single wind turbine, MW.

[0030] In this embodiment, in step 3, combined with the wind speed sample data in step 1, the influence of extreme weather conditions on the wind turbine failure rate is considered, and the time-varying failure rate expression of a single wind turbine is obtained as follows: (2) In the formula, for t Unit failure rate during the period; is the average hourly failure rate of fans under normal weather conditions; b A coefficient greater than 0 represents the vulnerability of the wind turbine in strong wind weather. bThe larger the value, the more obvious the impact of wind speed changes on the fan failure rate.

[0031] In this embodiment, in step 4, based on the existing wind turbine failure rate and output characteristic function, a Monte Carlo simulation method is used to establish a wind farm output probability model. Through multiple experiments, the wind farm output probability distribution sequence at each moment is obtained, which is the desired wind power output probability distribution sequence taking into account typical extreme weather processes.

[0032] Example 2 like Figure 1 As shown, the present invention provides a method for simulating a wind power output sequence taking into account a typical extreme weather process, comprising the following steps: Step 1: Obtain wind speed samples and wind farm related parameters including extreme weather processes.

[0033] This example is based on 15 days of wind speed sample data from a southern province, and typhoon weather is selected as a typical extreme weather process. The sample wind farm contains 40 wind turbines with a rated power of 6MW.

[0034] Step 2: Based on the wind farm related parameters obtained in step 1, the wind turbine output characteristic function and the wind speed attenuation coefficient matrix of the wind farm considering the wake effect are obtained.

[0035] Combined with relevant parameters of wind farms and based on the operating principle of wind turbines, the output characteristic function of a single wind turbine is obtained.

[0036] Step 3: Combine the wind speed sample data in step 1, especially consider the impact of extreme weather conditions on wind turbine failure rate, and derive the time-varying failure rate formula for a single wind turbine.

[0037] In order to consider the impact of extreme weather on the output sequence of wind turbines, it is believed that the failure rate of wind turbines will increase accordingly when the wind speed is high in typhoon weather. Combined with the actual wind speed sample data of each wind turbine obtained above, the impact of extreme weather on the working status of wind turbines is quantitatively characterized.

[0038] Step 4: Considering the output characteristic function of the wind turbine and the time-varying failure rate, the Monte Carlo simulation method is used to solve the probability distribution sequence of wind power output taking into account typical extreme weather processes.

[0039] On the basis of the output characteristic function and time-varying failure rate obtained above, an operation model of the wind farm at each moment is established, and the Monte Carlo simulation method is used to solve the probability distribution sequence of the units working normally at each moment, and then the probability distribution sequence of the wind farm output at each moment is obtained, which is the wind power output probability distribution sequence taking into account typical extreme weather processes.

[0040] The output characteristic function curve of a single wind turbine is as follows: Figure 2 As shown, the unit cut-in wind speed is set to 5m / s, the rated wind speed is 20m / s, the cut-out wind speed is 25m / s, and the rated power is 6MW.

[0041] Finally, the probability distribution sequence of wind power output is obtained. The sequence under normal weather conditions is as follows: Figure 3 As shown, the sequence under extreme weather conditions is as follows Figure 4 shown.

[0042] Example 3 like Figure 5 As shown, the wind power output sequence simulation system taking into account typical extreme weather processes provided by the present invention comprises: Data acquisition module, which obtains wind speed samples and wind farm related parameters including extreme weather processes; A first data processing module, based on the wind farm related parameters obtained by the data acquisition module, obtains the wind turbine output characteristic function; The second data processing module combines the wind speed sample data from the data acquisition module, considers the impact of extreme weather conditions on the wind turbine failure rate, and derives the time-varying failure rate of a single wind turbine; The solution module considers the output characteristic function of the wind turbine and the time-varying failure rate, and uses the Monte Carlo simulation method to solve the probability distribution sequence of wind power output taking into account typical extreme weather processes.

[0043] Example 4 The present invention provides an electronic device, comprising: a processor and a memory coupled to the processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the steps of the method for simulating a wind power output sequence taking into account typical extreme weather processes described in any one of claims 1 to 4 are implemented.

[0044] The electronic device may also include one or more of a multimedia component, an input / output (I / O) interface, and a communication component.

[0045] The processor is used to control the overall operation of the electronic device to complete all or part of the steps in the above-mentioned storage medium sharing method. The memory is used to store various types of data to support the operation of the electronic device, and these data may include, for example, instructions for any application or method used to operate on the electronic device, and application-related data, such as contact data, messages sent and received, pictures, audio, video, etc. The memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, magnetic disk or optical disk. The multimedia component may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in a memory or sent through a communication component. The audio component also includes at least one speaker for outputting audio signals. The I / O interface provides an interface between the processor and other interface modules, and the other interface modules may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component is used for wired or wireless communication between the electronic device and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component may include: a Wi-Fi module, a Bluetooth module, an NFC module.

[0046] In an exemplary embodiment, the electronic device may be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned storage medium sharing method.

[0047] Example 5 The present invention provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the wind power output sequence simulation method taking into account typical extreme weather processes are implemented.

[0048] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0049] The present application is described with reference to the flowcharts and / or block diagrams of the methods, systems and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A system that specifies the functions of a box or boxes.

[0050] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0051] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0052] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It is obvious to those skilled in the art that the present invention is not limited to the details of the above exemplary embodiments, and the present invention can be implemented in other specific forms without departing from the spirit or basic features of the present invention. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the attached claims rather than the above description, and it is intended that all changes falling within the meaning and scope of the equivalent elements of the claims are included in the present invention. Any figure mark in the claims should not be regarded as limiting the claims involved.

[0053] In addition, it should be understood that although this specification is described in accordance with the implementation modes, not every implementation mode contains only one independent technical solution. This description of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation modes that can be understood by those skilled in the art. The above content is only to illustrate the technical idea of ​​the present invention, and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution according to the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. A wind power output sequence simulation method taking into account typical extreme weather processes, characterized in that: The following steps are involved: Step 1: Obtain wind speed samples and wind farm related parameters including extreme weather processes; Step 2: Based on the wind farm related parameters obtained in step 1, the output characteristic function of the wind turbine is obtained; Step 3: Combine the wind speed sample data in step 1, consider the impact of extreme weather conditions on the wind turbine failure rate, and derive the time-varying failure rate of a single wind turbine; Step 4: Considering the output characteristic function of the wind turbine and the time-varying failure rate, the Monte Carlo simulation method is used to solve the probability distribution sequence of wind power output taking into account typical extreme weather processes.

2. The method for simulating wind power output sequence taking into account typical extreme weather processes according to claim 1, characterized in that: In step 2, considering the operating principle of the wind turbine generator set, based on the relevant parameters of the wind turbine generator set, the output characteristic function of the wind turbine generator set is obtained as follows: (1) In the formula, is the active output of a single wind turbine, MW; are the cut-in wind speed, cut-out wind speed and rated wind speed of the fan, m / s; is the rated power of a single wind turbine, MW.

3. The method for simulating wind power output sequence taking into account typical extreme weather processes according to claim 2, characterized in that: In step 3, combined with the wind speed sample data in step 1, considering the impact of extreme weather conditions on the wind turbine failure rate, the time-varying failure rate expression of a single wind turbine is obtained as follows: (2) In the formula, for t Unit failure rate during the period; is the average hourly failure rate of fans under normal weather conditions; b A coefficient greater than 0 represents the vulnerability of the wind turbine in strong wind weather. b The larger the value, the more obvious the impact of wind speed changes on the fan failure rate.

4. The method for simulating wind power output sequence taking into account typical extreme weather processes according to claim 3 is characterized in that: In step 4, based on the existing wind turbine failure rate and output characteristic function, the Monte Carlo simulation method is used to establish a wind farm output probability model. Through multiple experiments, the wind farm output probability distribution sequence at each moment is obtained, which is the required wind power output probability distribution sequence taking into account typical extreme weather processes.

5. A wind power output sequence simulation system taking into account typical extreme weather processes, characterized in that: include: Data acquisition module, which obtains wind speed samples and wind farm related parameters including extreme weather processes; A first data processing module, based on the wind farm related parameters obtained by the data acquisition module, obtains the wind turbine output characteristic function; The second data processing module combines the wind speed sample data from the data acquisition module, considers the impact of extreme weather conditions on the wind turbine failure rate, and derives the time-varying failure rate of a single wind turbine; The solution module considers the output characteristic function of the wind turbine and the time-varying failure rate, and uses the Monte Carlo simulation method to solve the probability distribution sequence of wind power output taking into account typical extreme weather processes.

6. The wind power output sequence simulation system taking into account typical extreme weather processes according to claim 5 is characterized in that: In the first data processing module, considering the operating principle of the wind turbine generator set and based on the relevant parameters of the wind turbine generator set, the output characteristic function of the wind turbine generator set is obtained as follows: (1) In the formula, is the active output of a single wind turbine, MW; are the cut-in wind speed, cut-out wind speed and rated wind speed of the fan, m / s; is the rated power of a single wind turbine, MW.

7. The wind power output sequence simulation system taking into account typical extreme weather processes according to claim 5, characterized in that: In the second data processing module, combined with the wind speed sample data in the data acquisition module, considering the impact of extreme weather conditions on the wind turbine failure rate, the time-varying failure rate expression of a single wind turbine is obtained as follows: (2) In the formula, for t Unit failure rate during the period; is the average hourly failure rate of fans under normal weather conditions; b A coefficient greater than 0 represents the vulnerability of the wind turbine in strong wind weather. b The larger the value, the more obvious the impact of wind speed changes on the fan failure rate.

8. The wind power output sequence simulation system taking into account typical extreme weather processes according to claim 5, characterized in that: In the solution module, based on the existing wind turbine failure rate and output characteristic functions, the Monte Carlo simulation method is used to establish a wind farm output probability model. Through multiple experiments, the wind farm output probability distribution sequence at each moment is obtained, which is the required wind power output probability distribution sequence taking into account typical extreme weather processes.

9. An electronic device, characterized in that: include: A processor and a memory coupled to the processor, the memory storing a computer program, wherein the computer program, when executed by the processor, implements the steps of the method for simulating wind power output sequence taking into account typical extreme weather processes as described in any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method for simulating wind power output sequence taking into account typical extreme weather processes according to any one of claims 1 to 4.

Images