Fan operation data processing and visualization method, product, medium and system

Abstract

The invention discloses a fan operation data processing and visualization method, a product, a medium and a system, and the method comprises the steps: segmenting a continuous operation data sequence of a measurement point part representing the operation state of a fan into a plurality of data blocks A, and drawing a time sequence color histogram; sequencing the continuous data sequences representing the wind speed and the actual active power of the fan into a sequence B according to a time sequence, and drawing a time sequence curve graph of the theoretical power and the actual active power of the fan; segmenting continuous data representing environmental factors into data blocks C, and drawing a histogram; and combining the histogram of the data block A, the curve graph of the sequence B and the shading graph of the data block C to form a comprehensive graph which takes the horizontal axis as time, color blocks in different colors represent the fan state, the range of the color blocks in the longitudinal axis corresponds to the size of a power curve value, and the shading pattern corresponds to an environment anomaly identifier. The system is standardized, and can visually display the change of each fan in each state, the power generation amount and the specific distribution condition of each lost electric quantity in a wind field.

Description

TECHNICAL FIELD

[0001] The present application mainly relates to the field of wind power technology, in particular to a wind turbine operation data processing and visualization method, product, medium and system. BACKGROUND

[0002] The running state of the wind turbine can be received from the SCADA system, such as power generation, fault shutdown, standby, offline, etc. These states can be displayed in real time in the SCADA system. In addition, these states can be transmitted to the control center or dispatch through the communication protocol, and displayed in real time in the form of the remote control center. However, the running state definitions of different wind turbine manufacturers are different, and the wind turbine state definition and display cannot be unified.

[0003] Moreover, the original state set recorded by the wind turbine may not be the same as the actual state. For example, after the wind turbine fails, the PLC restarts and self-checks, and tries to run again, the wind turbine records the states in turn as: fault, offline, standby, fault, …, but in fact, the entire state should be counted as fault. Similar original state sets and actual logical states are not one-to-one corresponding. This leads to that directly displaying these original state records will be too trivial and inconsistent with the actual logical state, and the actual usability is not high.

[0004] More importantly, these running state data are either used in the SCADA in real-time display mode, or used for statistical wind turbine time availability data, and cannot provide more information support for the energy availability system, which is another index system closely related to the operation benefit of the wind farm and more concerned by the owner. It is impossible to provide intuitive and visible image display for the detailed distribution of energy loss caused by various reasons and the specific situation of each part of the theoretical power.

[0005] In the use of these wind turbine running states, the influence of environmental factors (such as abnormal power grid environment, extreme wind speed, extreme temperature) on the wind turbine state and power generation is often not considered or shown.

[0006] In addition, when using data, it is often difficult to perform regular data processing due to the long-time power-off shutdown of the wind turbine without saving the running data. SUMMARY

[0007] In view of the technical problems existing in the prior art, the present application provides a wind turbine operation data processing and visualization method, product, medium and system which can standardize and draw a wind turbine state and power time sequence diagram of a wind farm.

[0008] To solve the above technical problems, the technical solution provided by the present application is: A wind turbine operation data processing and visualization method, comprising the following steps: The record state of the original operation data of the fan is arranged in time sequence to form a continuous operation data sequence; The continuous operation data sequence of the measuring points representing the operation state of the fan is divided into a plurality of data blocks A, each data block A corresponds to a single standard logic state; the end point of the data block A is dynamically determined for different logic states, and the time sequence color column chart of each fan is drawn according to the data block A, and different colors in the column chart represent different logic states of the fan; The continuous data sequence representing the fan speed and the actual active power is sorted in time sequence as sequence B, and the time sequence curve chart of the theoretical power and the actual active power of the fan is drawn according to the sequence B; The continuous data representing the environmental factors is divided into data block C, the data block with environmental abnormality is found, and the column chart is drawn; for different data blocks with environmental abnormality, the column chart with different shadow underlines is used to represent; The column chart of the fan data block A, the curve chart of the sequence B and the column chart with underlines of the data block C are combined to finally form a comprehensive chart with the horizontal axis as time, the color blocks of the column chart representing the state of the fan, the range of the vertical axis of the column chart corresponding to the size of the power curve value, and the underline pattern of the column chart corresponding to the identification of the environmental abnormality.

[0009] Preferably, the standard logic states include: normal shutdown, command shutdown, pre-maintenance shutdown, fault_unhandled, fault_handing, normal power generation, grid dispatch limit power, dispatch limit power shutdown, fan command limit power, fan self-protection limit power, fan performance reduction power generation, offline; wherein normal shutdown is a fan shutdown due to no fan fault, no dispatch, no human command or operation reason, and other classification states except for it; command shutdown refers to SCADA remote command shutdown, and a state until normal operation; pre-maintenance shutdown refers to a state that the fan is not due to a fault reason, but a person is performing shutdown / service operation at the fan site until the fan resumes operation; fault_unhandled refers to a state that the fan is from reporting a fault to the fan resuming operation or to a person performing shutdown / service operation at the fan site; fault_handing refers to a state that a person performs shutdown / service operation at the fan site until the fan resumes operation after the fan reports a fault; normal power generation refers to normal power generation of the fan, and a power curve during power generation conforms to a design power curve; grid dispatch limit power refers to power generation of the fan, but the power generation power is lower than the corresponding power generation power of the design power curve due to a grid limit power command; dispatch limit power shutdown refers to a state that the wind farm is subjected to a grid limit power command, and the power limit of the fan is lower than the minimum power of the fan and the fan is shutdown; fan command limit power refers to a limit power generation state of the fan subjected to a human limit power command not from the grid dispatch; fan self-protection limit power refers to limit power operation of the fan due to built-in self-protection logic, and the fan resumes normal power generation when the condition is eliminated; and fan performance reduction power generation refers to a case that the fan performance is reduced due to reasons such as aging of fan components and blade pollution, and the power generation power is still lower than the design power curve under non-special circumstances.

[0010] Preferably, the logic state of each data block is determined by the first data point representing the fan operating state, supplemented by the data point representing the active power of the fan at that time, the wind speed data point, the limit power instruction data point, the fault or warning data point, and the design power curve, and the determination logic corresponds to the logic definition of the first logic state; for example, if the first recorded state is power generation, and the power is found to be within the range of the design power curve by comparing the wind speed and active power, then the data block is normal power generation; if the first recorded state is power generation, and the power is lower than the design power curve by comparing the wind speed and active power, and the power is consistent with the received grid dispatch limit power instruction value, then the data block is grid dispatch limit power; if the first recorded state is power generation, and the power is lower than the design power curve by comparing the wind speed and active power, and the power is consistent with the received local instruction limit power instruction value, then the data block is fan instruction limit power; if the first recorded state is shutdown, and the received grid dispatch limit power instruction value is lower than the minimum startup power of the fan, excluding other shutdown judgment logic conditions, then the data block is dispatch limit power shutdown; if the first recorded state is power generation, and the power is lower than the power curve by comparing the wind speed and active power, and the fan is in a self-protection limit power state by a specific warning or other fan measurement points and built-in logic, then the data block is fan self-protection limit power; if the first recorded state is power generation, and the power is found to be lower than the design power curve range by comparing the wind speed and active power, while excluding various other limit power states, then the data block is fan performance reduction power generation. If the first recorded state is an instruction shutdown, then the data block is an instruction shutdown; if the first recorded state is a local shutdown or a service operation, then the data block is preventive maintenance; if the first recorded state is a fan fault, then the data block is a fault; if the first recorded state is a communication interruption or an offline state, then the data block is offline. If the fan state judgment meets multiple limit power conditions, the state selection priority is: fan self-protection limit power > fan instruction limit power > grid dispatch limit power > fan performance reduction power generation; if the fan can meet multiple shutdown state judgment conditions at the same time, the state selection priority is: fault > preventive maintenance > instruction shutdown > dispatch limit power shutdown > normal shutdown.

[0011] Preferably, the specific process of dynamically determining the end point of data block A is as follows: If the data block is normal power generation, then read the states from the start point of the data block in sequence until the first non-power generation state or any limit power state is read, and the previous state of the non-power generation or limit power state is the end point of the data block; if the data block is any limit power state, then read the states from the start point of the data block in sequence until the first non-power generation state or any other limit power state or normal power generation state is read, and the previous state of the state is the end point of the data block. If the data block is offline or communication interruption type, read the state from the starting point of the data block to the end point of the data block in sequence until the first record state indicating recovery from offline is read, and the previous record state of the non-power generation record state is the end point of the data block; The end point of the instruction shutdown, dispatch limit power shutdown is the record state indicating the logical state lasting until the "fan recovery running state" or the preventive maintenance shutdown, fault type or offline; The end point of the preventive maintenance shutdown, fault data block is the record state indicating the logical state lasting until the "fan recovery running state" or offline.

[0012] Preferably, for long offline, manually supplement data; supplement in data block A as actual state type; supplement missing timing wind speed data in sequence B, which is replaced by wind speed of nearby fan or wind tower; If there is a period of offline state in the fault data block or the preventive maintenance data block, calculate the offline data time of the period according to the method of calculating the start point and the end point of the offline data block, if the offline time is less than a preset threshold, it indicates that the offline is caused by fault or local operation, the period of time belongs to the fault or local operation time, the start point and the end point of the data block are correct; if the intermediate offline time is greater than the preset threshold, it indicates that the state is transformed from fault or local operation to real offline state that needs attention, the previous record state of the offline record is the end point of the data block; start from the next offline record to rejudge the data block type and the end point.

[0013] Preferably, the environmental abnormal state includes: power grid abnormality, extreme low temperature, extreme high temperature, extreme wind speed, blade icing and turbulence abnormality; The start point of the power grid abnormality state is the data point at which the grid voltage exceeds the wind turbine running range, and the end point state is the data point at which the grid voltage returns to the wind turbine running range; or indirectly judge the start point: the data point at which all wind turbines of the same time or the same power collection line are powered off or offline at the same time, and the end point is the data point at which the wind turbine recovers power supply; If the wind turbine has a blade icing state judgment measuring point, the start point and the end point of the blade icing state are directly judged according to the measuring point, if there is no such measuring point, the environmental temperature, humidity, wind speed and active power measuring points are indirectly judged; the turbulence abnormality is judged by the data point and the wind speed and direction change before and after it; the extreme high temperature, low temperature and extreme wind speed are directly judged by the environmental temperature and wind speed measuring points; The power grid abnormality can be represented by horizontal bar hatching, the extreme low temperature is represented by left oblique line hatching, the extreme high temperature is represented by right oblique line hatching, the extreme wind speed is represented by short vertical line hatching, and the turbulence abnormality is represented by wave hatching.

[0014] Preferably, the same three data of the wind turbine are combined, the time axis of the horizontal axis is kept synchronous, the columnar chart of the data block A and the data block C is consistent in the vertical direction, the height of the columnar chart in the vertical direction corresponds to the full power of the wind turbine, the lowest point of the columnar chart corresponds to the power of 0, and other power values are linearly and uniformly distributed therebetween, so as to combine the power time sequence chart of the sequence B into the columnar chart; and then, the wind turbines of a line or a wind farm are arranged in sequence in the vertical direction according to the same horizontal axis. The normal generation and normal shutdown are represented by a green color system, the instruction shutdown is represented by a yellow color system, the pre-maintenance shutdown is represented by a blue color system, the fault_untreated and fault_treated are represented by different red color systems, the power limiting of various reasons and the dispatching power limiting shutdown are represented by a purple color system, the wind turbine performance reduction generation is represented by a brown color, the offline is represented by a gray color system, the uncertain state is white or transparent, the actual power time sequence chart is represented by a black solid line, the theoretical power time sequence chart is represented by a green dotted line, the grid environment anomaly is represented by a horizontal line bottom, the extreme temperature is represented by a diagonal line bottom, the extreme wind speed is represented by a vertical line bottom, the turbulence anomaly is represented by a wave bottom, and the blade icing is represented by a block bottom.

[0015] The application further discloses a computer program product, comprising a computer program, which executes the steps of the method when run by a processor.

[0016] The application further discloses a computer readable storage medium, which stores a computer program, which executes the steps of the method when run by a processor.

[0017] The application further discloses a wind turbine state data processing and visualization system, comprising a memory and a processor connected to each other, wherein the memory stores a computer program, which executes the steps of the method when run by the processor.

[0018] Compared with the prior art, the application has the following advantages: The application converts the fragmented wind turbine original record state into continuous and logical actual operation states, and the states are applicable to wind turbines of different manufacturers, can form the same standard, and can draw the wind turbine state time sequence chart of the complete system based on the energy availability of the wind farm, including the power limiting states caused by various reasons, the shutdown caused by the power limiting and the reduced power operation state caused by the performance reduction of the wind turbine, and the completeness and practicability of the states exceed the original state system based on the time availability.

[0019] In another aspect, by superimposing the power time sequence diagram on the state time sequence diagram, the distribution of the theoretical and actual power generation of each fan in each state can be quantitatively displayed, and the specific distribution of energy loss in each state, including the power loss of operation and maintenance of power limitation / performance reduction, can be displayed. In addition, by superimposing the environmental abnormalities represented by different hatchings in the diagram, the fan state abnormalities and power loss caused by environmental abnormalities can be easily identified.

[0020] In addition, in the case of long-time fan power outage and lack of data (long-time offline), the application also provides an approximate data supplement method, and then the power loss display of the application can still be used.

[0021] Through the method, the normal power generation of each fan in the wind farm, various power limitations, maintenance and fault conditions, and the energy loss of each fan in various conditions can be intuitively reviewed, which provides a visual basis for the review, judgment and decision of the operation personnel of the wind farm. In various power loss complex, and power grid power limitation is serious, seasonal or regional fan self-protection power limitation frequently occurs, or old fans face the situation of reduced power operation due to performance decline, the utility of the method in loss power analysis is particularly prominent. BRIEF DESCRIPTION OF DRAWINGS

[0022] Figure 1 The fan state time sequence diagram of the application.

[0023] Figure 2 The typical logical state transition diagram in the application.

[0024] Figure 3 The method flowchart for converting the original record state of the fan into a logical state in the application.

[0025] Figure 4 The flowchart of the fan state data processing and visualization method in the embodiment of the application. DETAILED DESCRIPTION

[0026] The application will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0027] As shown in Figure 4 , the fan operation data processing and visualization method provided by the embodiment of the application includes the following steps: predefined typical logical states, including: normal power generation, normal shutdown, command shutdown, pre-maintenance shutdown, fault_unprocessed, fault_processing, power grid dispatching power limitation, dispatching power limitation shutdown, fan command power limitation, fan self-protection power limitation, fan performance reduction power generation, offline, as shown in Figure 2 , as shown in Figure 3Normal stop is the state of the wind turbine from normal stop to other classification state except for it, such as from the stop caused by too low wind speed to the state during the process of the wind turbine resuming normal power generation after the wind speed reaches the cut-in wind speed. Command stop refers to the state of SCADA remote command stop to normal operation. Pre-maintenance stop refers to the state of the wind turbine non-fault reason, but someone is performing stop / service operation at the local of the wind turbine to the wind turbine resuming operation. Fault_unhandled refers to the state of the wind turbine from reporting a fault to the wind turbine resuming operation or to someone performing stop / service operation at the local of the wind turbine. Fault_handled refers to the state of the wind turbine reporting a fault to someone performing stop / service operation at the local of the wind turbine to the wind turbine resuming operation.

[0028] Normal power generation refers to the state of the wind turbine normal power generation, and the power curve during power generation conforms to the design power curve. Grid dispatch limit power refers to the state of the wind turbine power generation, but the power is lower than the corresponding power of the design power curve due to the grid limit power instruction. Dispatch limit power stop refers to the state of the wind turbine stop due to the wind farm receiving the grid limit power instruction and the power limit of the wind turbine being lower than the minimum power. Wind turbine command limit power refers to the state of the wind turbine limit power generation due to the non-grid dispatch human limit power instruction, such as the manual limit power instruction given by the operator after replacing the gear box. Wind turbine self-protection limit power refers to the state of the wind turbine limit power generation due to the built-in self-protection logic under specific conditions (such as component over-temperature self-protection limit power, blade icing self-protection limit power, abnormal vibration, etc.), and the wind turbine resumes normal power generation when the condition is eliminated. Wind turbine performance reduction power generation refers to the state of the wind turbine performance reduction due to component aging, blade contamination, etc., and the power is still lower than the design power curve under non-specific conditions.

[0029] According to the above typical logical state classification, it can also be slightly modified and combined into a smaller number of logical states, such as combining command stop and pre-maintenance stop into "operation stop" or other names containing the essential connotation of the definition; or combining normal stop, command stop, and pre-maintenance stop into "stop"; or combining fault_unhandled and fault_handled into "fault"; or combining all limit power states and limit power stop into "limit power".

[0030] In addition, the typical logical state can also be split, such as splitting the wind turbine self-protection limit power into over-temperature self-protection limit power and blade icing self-protection limit power.

[0031] Based on the above defined typical logical state, the method of the present application comprises the following steps: S1. Arrange the record state of the original running data of the fan in chronological order to form a continuous running data sequence. These data can be the sampling value of the fan running data, or the aggregated value after averaging or maximum value taking with a certain time granularity (such as 1 minute), provided that the aggregated data can accurately or relatively accurately reflect the state judgment of S2-S3; S2. Divide the continuous running data sequence of the measuring points representing the fan running state into a plurality of data blocks A, and each data block A corresponds to a single standard logic state; Determine which logic state the data block belongs to according to the measuring point representing the fan state in the first running data of each data block, and the judgment logic corresponds to the logic definition of the first logic state. For example, if the first represented state is normal power generation or various types of power limiting state, the data block is normal power generation or various types of power limiting state; if the first represented state is dispatch power limiting shutdown, the data block is dispatch power limiting shutdown state; if the first represented state is instruction shutdown, the data block is instruction shutdown; if the first represented state is local shutdown or service operation, the data block is preventive maintenance; if the first represented state is fan failure, the data block is failure (how to further divide into failure_untreated and failure_treated, see below); if the first represented state is communication interruption or offline, the data block is offline.

[0032] The method for determining that the data block is performance reduction power generation is as follows: compare the actual power generation and the theoretical power generation in the data (which can reuse the data in sequence B), for example, if the actual power generation is lower than the theoretical power generation by a certain value (such as 7%) and lasts for a certain time (such as 45 minutes), and any power limiting state can be excluded, the first state that meets this logic is the starting point of the performance reduction power generation data block.

[0033] If the fan state judgment can meet multiple power limiting conditions at the same time, the state selection priority is: fan self-protection power limiting > fan instruction power limiting > grid dispatch power limiting > fan performance reduction power generation. If the fan state judgment can meet multiple shutdown conditions at the same time, the state selection priority is: failure > preventive maintenance > instruction shutdown > dispatch power limiting shutdown > normal shutdown.

[0034] S3. Dynamically determine the end point of the data block A for different logic states. According to the data block A, a time sequence color column chart of each fan can be drawn, and different colors in the column chart represent different logic states of the fan; If the data block is power generation or normal shutdown, read the data from the starting point of the data block to the end, until the first data representing a state other than the state is read, then the previous data of the data is the end point of the data block.

[0035] If the data block is offline or communication interruption, then read the data from the start of the data block to the end of the data block.

[0036] If the data block is instruction shutdown or dispatch limited power shutdown, then read the data from the start of the data block to the end of the data block.

[0037] If the data block is performance reduction generation, then read the data from the start of the data block to the end of the data block.

[0038] The end of the data block of preventive maintenance shutdown, fault (the state combined by fault_not_handled and fault_handled) is the data of offline or the state of the logic that lasts until the state of "fan recovery operation" is reached. A typical method of determining the state of "fan recovery operation" is as follows: read the data from the start of the data block to the end of the data block.

[0039] The data block of fault (the state combined by fault_not_handled and fault_handled) obtained by the above method is read from the start of the data block to the end of the data block.

[0040] In particular, if there is a short offline state in the calculated fault data block or preventive maintenance data block, the offline data time can be calculated according to the method of calculating the start and end points of the offline data block. If the offline time is less than a certain value (e.g., 1 hour), it indicates that the offline is most likely caused by a fault or local operation, and the offline time actually belongs to the fault or local operation time. The short offline data block can be included in the previous fault or preventive maintenance data block. If the offline time is greater than the specified value, it indicates that the offline state is converted from a fault or local operation state to a real offline state that needs attention. Therefore, the previous data of the offline state is the end point of the data block before the offline, and the offline is regarded as a real offline data block. If the fan is determined to be in a fault shutdown or other shutdown state during the offline time, the data can be manually supplemented to replace the data block with the actual fan state.

[0041] In addition, the first data block of the fan may not be a complete logical state, so special processing is required. The method is to read the first recorded state of the first data block. If it is a power generation state, it can still be regarded as a normal logical state. If it is other recorded states, it is regarded as a special unknown state (because the non-power generation state cannot be determined what caused it), and the end point of the data block is the data found by searching backward until the "fan recovery running state" is found. The determination method of the "fan recovery running state" is the same as above. The end point of the last data block of the fan is the timestamp of the last data of the fan data.

[0042] Through the above steps, a plurality of logical states connected end to end and the start and end times of each logical state (the duration of the state can be calculated by the start time and the end time) can be formed. The start time of each logical state is the timestamp of the original data at the start point of the data block corresponding to each logical state, and the end time of each logical state can be determined as the timestamp of the original data at the start point of the data block corresponding to the next logical state.

[0043] S4. The continuous data sequence representing the fan speed and the actual active power is sorted in time sequence as sequence B, and the theoretical power and the actual power time sequence curve of the fan can be drawn according to sequence B; Select the measuring point in the operation data that can most accurately reflect the fan wind speed and actual active power to form a sequence B sorted in time sequence. According to the sequence B, a time sequence curve diagram of the actual power of the fan can be drawn; according to the wind speed and the theoretical power curve table of the fan model, a time sequence curve diagram of the theoretical power of the fan can be drawn. In order to distinguish the actual power diagram and the theoretical power diagram, different colors of solid lines and dashed lines can be used. Since the method has separated the performance reduction power generation state, during normal power generation, the actual power curve and the theoretical power curve are nearly equivalent, and the area surrounded thereby is the actual power generation of the fan. In various shutdown states, the actual power is 0 and does not need to be drawn, and the energy loss condition can be judged by the area surrounded by the theoretical power time sequence curve. In various power limiting states and performance reduction power generation, when the two curve time sequence diagrams are drawn at the same time, the area surrounded by the actual power curve and the horizontal axis is the actual power generation, and the area between the two intervals is the power limiting loss.

[0044] If there is a large amount of empty data in the sequence (corresponding to a long time offline in data block A), if it can be determined that the fan is in a fault shutdown or other reason for shutdown during the period, the data can be manually supplemented, and the wind speed data of the fan or the anemometer tower near the fan at the same time can be regarded as the reference wind speed. At this time, the actual power of the fan is 0, and the theoretical power curve is the power time sequence diagram corresponding to the supplemented wind speed.

[0045] S5. The continuous data representing environmental factors are divided into data block C, and the data block in which the environmental anomaly (environmental condition exceeding the running range of the fan) is found. For different environmental anomaly data blocks, different hatched columnar graphs can be used to represent them; The calculation of the environmental anomaly data block is independent of data block A and sequence B and is carried out separately. The environmental anomaly includes power grid anomaly, extreme high temperature, extreme low temperature, extreme wind speed, blade icing, and turbulence anomaly.

[0046] The starting point of the extreme high temperature and low temperature is the data in which the environmental temperature measured by multiple different environmental temperature measuring points all exceeds the design range value of the fan, and the end point is the data point in which all the environmental temperature measuring points all return to the design range of the fan. The extreme wind speed is the data in which the wind speed value exceeds the cut-out wind speed or the design range value of the fan, and the end point is the data point in which the wind speed drops below the cut-out wind speed or returns to the design range of the fan.

[0047] The grid abnormality includes grid outage fault, grid abnormal fluctuation or grid voltage abnormality (out of the wind turbine design range). The starting point of the grid outage fault state judgment is that the grid voltage will reach 0, and the starting point of the grid voltage abnormality judgment is that the grid voltage exceeds the data point of the wind turbine design range. The indirect judgment method of the grid abnormality is that when multiple wind turbines or all wind turbines of the same power collection line are simultaneously powered off at the same time, it can be judged as a grid outage fault, when multiple wind turbines or all wind turbines of the same power collection line are simultaneously powered off at the same time, it can be judged as a grid outage fault, when multiple wind turbines or all wind turbines of the same power collection line are simultaneously powered off at the same time, it can be judged as a grid outage fault, or simultaneously enter the high / low transmission state as the grid abnormal fluctuation or grid voltage abnormality. The end point state of the grid abnormality is that the grid voltage returns to the data point within the wind turbine operating range, and when the above indirect judgment method is used, the end point is the data point when the wind turbine resumes standby.

[0048] If the wind turbine has a blade icing state judgment measurement point, the start point and end point of the blade icing state can be directly judged according to the measurement point, and if there is no such measurement point, the blade icing state can be indirectly judged according to the environmental temperature, humidity, wind speed and active power and other measurement points. Turbulence abnormalities can be judged by data points and changes in wind speed and direction before and after them.

[0049] S6. Merge the column chart of the wind turbine data block A, the curve chart of the sequence B, and the bottom chart of the data block C to finally form a comprehensive chart with the horizontal axis as time, the different color blocks of the column chart representing the wind turbine state, the vertical axis color block range of the column chart corresponding to the size of the power curve value, and the bottom chart pattern corresponding to the environmental abnormality identification. Arrange multiple wind turbines in sequence along the horizontal axis for vertical arrangement to facilitate simultaneous viewing of the entire wind farm: When the three data charts of the same wind turbine are merged, the time axis of the horizontal axis is kept synchronous. The vertical heights of the column charts of the data block A and the data block C are consistent, and the vertical height of the column chart corresponds to the full power of the machine type. The lowest point of the column chart corresponds to a power of 0, and other power values are linearly and uniformly distributed therebetween. In this way, the power time sequence chart of the sequence B is merged therein. Then, multiple wind turbines of a line or a wind farm are arranged in sequence along the same horizontal axis for vertical arrangement.

[0050] The change of the operation of each fan over time is represented by the change of the color of the column chart of the state of the corresponding column body over time, the change of the power corresponding curve, and the change of the background of the column chart corresponding to the environment state. A typical color example is that normal power generation and normal shutdown are represented by green, command shutdown is represented by yellow, pre-maintenance shutdown is represented by blue, fault_unhandled and fault_handled are represented by different colors of red, power limiting of various reasons and dispatching power limiting shutdown are represented by purple, power generation of reduced performance of the fan is represented by brown, offline is represented by gray, and the uncertain state is white or transparent. The actual power time sequence diagram is represented by a black solid line, and the theoretical power time sequence diagram is represented by a green dashed line. The grid environment anomaly is represented by a horizontal bar background, the extreme temperature is represented by a diagonal bar background, the extreme wind speed is represented by a vertical line background, the turbulence anomaly is represented by a wave background, and the blade icing is represented by a block background, as shown in Figure 1 Fig. 6. Of course, the colors and backgrounds of the above states can be arbitrarily defined as needed.

[0051] One aspect of the present application converts the fragmented original record state of the fan into continuous and logical actual operation state, and these states are applicable to fans of different manufacturers, can form the same standard, and on this basis, the fan state time sequence diagram of the complete system based on energy availability of the wind farm can be drawn, including the power limiting state caused by various reasons, the shutdown caused by power limiting, and the reduced power operation state caused by performance reduction of the fan. The completeness and practicality of the state exceed the original state system based on time availability.

[0052] Another aspect is that by superimposing the power time sequence diagram in the state time sequence diagram, the distribution of the theoretical power generation and the actual power generation of each fan in each state can be quantitatively displayed, and the specific distribution of energy loss in each state, including the power loss caused by power limiting / operation and maintenance of performance reduction, can be displayed. In addition, by superimposing the environment anomalies represented by different backgrounds in the diagram, the fan state anomaly and power loss caused by environmental anomalies can be easily identified.

[0053] In addition, in the case of long-time power failure of the fan for a long time and lack of data (long-time offline), the present application also provides a method for approximating data supplement, and then the drawing method of the present application can still be used to display the power loss.

[0054] Through the method, the normal power generation, various power limiting, maintenance and fault conditions of each fan of the wind farm, and the energy loss of each fan in various conditions can be intuitively reviewed, judged and decided, providing a visual basis for the review, judgment and decision of the operation personnel of the wind farm. In the case of complex power loss and serious grid power limiting, seasonal or regional fan self-protection power limiting frequently occurs, or old fans face reduced power operation due to performance reduction, the utility of the method in loss power analysis is particularly prominent.

[0055] The present application can also be simplified as a plot only integrating data block A and sequence B, a plot only integrating data block A and data block C, or a plot only integrating sequence B and data block C. In the plot of sequence B, it can be simplified as only drawing a power curve in the state of shutdown or limited power, or only drawing a theoretical power time sequence curve, or only drawing an actual power time sequence curve, or only drawing a difference curve of the theoretical power time sequence and the actual power time sequence. If the classification accuracy of the state time sequence diagram is not high, for example, only a state system based on time availability needs to be drawn, when calculating data block A, only event records or state logs can be selected for simplified calculation, and then the results calculated by selecting running data (sample level data or data aggregated according to a certain time granularity (1 minute, 5 minutes or 10 minutes)) for sequence B or data block C are integrated to draw a schematic diagram.

[0056] The present application also discloses a computer program product comprising a computer program which, when executed by a processor, performs the steps of the method described above. The present application further discloses a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method described above. The present application also discloses a fan running data processing and visualization system comprising a memory and a processor connected to each other, wherein the memory stores a computer program which, when executed by the processor, performs the steps of the method described above. The product, medium and system of the present application correspond to the above-mentioned method, and also have the advantages of the above-mentioned method.

[0057] The present application can realize all or part of the processes in the above-mentioned embodiment methods, and can also be completed by computer program instruction related hardware. The computer program can be stored in a computer readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned method embodiment can be realized. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms, etc. The computer readable storage medium includes any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. The memory is used to store computer programs and / or modules. The processor realizes various functions by running or executing the computer programs and / or modules stored in the memory, and calling the data stored in the memory. The memory can include high-speed random access memory, and can also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage device, etc.

[0058] The above is only the preferred embodiment of the present application, and the protection scope of the present application is not limited to the above-mentioned embodiment. Any technical solution falling within the concept of the present application shall fall within the protection scope of the present application. It should be noted that some improvements and refinements made by ordinary skilled in the art without departing from the principles of the present application shall be considered as the protection scope of the present application.

Claims

1. A method for processing and visualizing wind turbine operation data, characterized in that, The method comprises the following steps: The record state of the original operation data of the fan is arranged in time sequence to form a continuous operation data sequence; The continuous operation data sequence representing the measurement points of the fan operation state is divided into a plurality of data blocks A, each data block A corresponds to a single standard logic state; the end point of the data block A is dynamically determined for different logic states, and a time sequence color column chart of each fan is drawn according to the data block A, and different colors in the column chart represent different logic states of the fan; The continuous data sequence representing the fan wind speed and the actual active power is sorted in time sequence as sequence B, and a time sequence curve chart of the theoretical power and the actual active power of the fan is drawn according to the sequence B; The continuous data representing the environmental factors is divided into data blocks C, the data block with environmental abnormality is found, and a column chart is drawn; for different data blocks with environmental abnormality, a column chart with different shadow underlines is used for representation; The column chart of the fan data block A, the curve chart of the sequence B, and the column chart with underlines of the data block C are combined to finally form a comprehensive chart with the horizontal axis as time, the different color blocks of the column chart representing the fan state, the range of the vertical axis of the column chart corresponding to the size of the power curve value, and the underline pattern of the column chart corresponding to the environmental abnormality identification.

2. The fan operational data processing and visualization method of claim 1, wherein, The standard logic states include: normal shutdown, instruction shutdown, pre-maintenance shutdown, fault_not_handled, fault_handled, normal power generation, grid dispatching limited power, dispatching limited power shutdown, fan instruction limited power, fan self-protection limited power, fan performance reduction power generation, and offline; wherein the normal shutdown is the fan shutdown due to non-fan fault, non-dispatching, non-human instruction or operation reason, and other classification states except the normal shutdown; the instruction shutdown refers to the SCADA remote instruction shutdown, and the state until the normal operation; the pre-maintenance shutdown refers to the fan non-fault reason, but someone is performing the shutdown / service operation at the fan local until the fan resumes operation; the fault_not_handled refers to the fan from reporting the fault to the fan resuming operation or to someone performing the shutdown / service operation at the fan local; the fault_handled refers to the fan from reporting the fault to someone performing the shutdown / service operation at the fan local until the fan resumes operation; the normal power generation refers to the fan normal power generation, and the power curve during the power generation meets the design power curve; the grid dispatching limited power refers to the fan power generation, but the power generation power is lower than the design power curve corresponding to the power generation power due to the grid limited power instruction; the dispatching limited power shutdown refers to the wind farm receiving the grid limited power instruction, and the power limit of the fan is lower than the minimum power of the fan to stop; the fan instruction limited power refers to the limited power generation state of the fan receiving the human limited power instruction not from the grid dispatching; the fan self-protection limited power refers to the limited power operation of the fan due to the built-in self-protection logic, and the fan resumes the normal power generation when the condition is eliminated; and the fan performance reduction power generation refers to the fan performance reduction due to the reasons such as the aging of the fan components and the contamination of the blades, and the power generation power is still lower than the design power curve under the non-special circumstances.

3. The fan operational data processing and visualization method of claim 2, wherein, The logic state of the data block is judged by the first measuring point of each data block representing the running state of the fan, supplemented by the measuring point representing the active power of the fan at this time, the wind speed measuring point, the limiting power instruction measuring point, the fault or warning measuring point and the designed power curve to judge the logic state of this data block, and the judgment logic corresponds to the logic definition of the first logic state; for example, if the first recorded state is power generation, and the power is found to be within the designed power curve range by comparing the wind speed and the active power, the data block is normal power generation; if the first recorded state is power generation, and the power is lower than the designed power curve by comparing the wind speed and the active power, and the power is consistent with the received grid dispatch limiting power instruction value, the data block is grid dispatch limiting power; if the first recorded state is power generation, and the power is lower than the designed power curve by comparing the wind speed and the active power, and the power is consistent with the received local instruction limiting power instruction value, the data block is fan instruction limiting power; if the first recorded state is shutdown, and the received grid dispatch limiting power instruction value is lower than the minimum starting power of the fan, excluding other shutdown judgment logic conditions, the data block is dispatch limiting power shutdown; if the first recorded state is power generation, and the power is lower than the power curve by comparing the wind speed and the active power, and the fan is in a self-protection limiting power state by a specific warning or other fan measuring points and built-in logic, the data block is fan self-protection limiting power; if the first recorded state is power generation, and the power is found to be lower than the designed power curve range by comparing the wind speed and the active power, while excluding various other limiting power states, the data block is fan performance reduction power generation; If the first recorded state is an instruction shutdown type, the data block is an instruction shutdown; if the first recorded state is a local shutdown type or a service operation type, the data block is preventive maintenance; if the first recorded state is a fan fault, the data block is a fault; if the first recorded state is a communication interruption type or an offline type, the data block is offline; If the fan state judgment meets multiple limiting power conditions at the same time, the state selection priority is: fan self-protection limiting power > fan instruction limiting power > grid dispatch limiting power > fan performance reduction power generation; if the fan can meet multiple shutdown state judgment conditions at the same time, the state selection priority is: fault type > preventive maintenance > instruction shutdown > dispatch limiting power shutdown > normal shutdown.

4. The fan operation data processing and visualizing method according to claim 1 or 2 or 3, characterized in that, The specific process of dynamically determining the end point of the data block A is as follows: If the data block is normal power generation, read the states from the recorded state of the start point of the data block in sequence until the first non-power generation type or any limiting power state is read, and the previous recorded state of the non-power generation or limiting power state is the end point of the data block; if the data block is any limiting power state, read the states from the recorded state of the start point of the data block in sequence until the first non-power generation type or any other limiting power state or normal power generation state is read, and the previous recorded state of the state is the end point of the data block; If the data block is offline or communication interruption type, read the states from the recorded state of the start point of the data block in sequence until the first recorded state indicating recovery from offline is read, and the previous recorded state of the non-power generation state is the end point of the data block; The end point of the instruction stop, dispatch limit power stop is the record state that the logical state lasts until the "fan recovery operation state" or the preventive maintenance stop, fault class or offline; The end point of the preventive maintenance stop, fault data block is the record state that the logical state lasts until the "fan recovery operation state" or offline.

5. The fan operational data processing and visualization method of claim 4, wherein, For long offline, manually supplement data; supplement in data block A as actual state type; supplement missing timing wind speed data in sequence B, which is replaced by wind speed of nearby fan or wind tower; If there is a period of offline state in the fault data block or preventive maintenance data block, calculate the offline data time according to the method of calculating the start and end points of the offline data block. If the offline time is less than a certain preset threshold, it indicates that the offline is caused by fault or local operation, and the data block start and end points are correct. If the intermediate offline time is greater than the preset threshold, it indicates that the state is converted from fault or local operation state to real offline state that needs attention, and the previous record state of this offline record state is the data block end point; Start from the next offline record state to rejudge the data block type and end point.

6. The fan operation data processing and visualization method according to claim 1 or 2 or 3, wherein, The environmental abnormal state includes: power grid anomaly, extreme low temperature, extreme high temperature, extreme wind speed, blade icing and turbulence anomaly; The start point of the power grid anomaly state is the data point at which the grid voltage exceeds the wind turbine operating range, and the end point state is the data point at which the grid voltage returns to the wind turbine operating range; or indirectly judge the start point: the data point at which multiple wind turbines or all wind turbines of the same collection line are powered off or offline at the same time, and the end point is the data point at which the wind turbine resumes power supply; If the wind turbine has a blade icing state judgment measuring point, the start and end points of the blade icing state are directly judged according to the measuring point, and if there is no such measuring point, the environmental temperature, humidity, wind speed and active power measuring points are indirectly judged; turbulence anomaly is judged by the data point and the change of wind speed and direction before and after it; extreme high temperature, low temperature, extreme wind speed are directly judged by the environmental temperature and wind speed measuring points; The power grid anomaly can be represented by horizontal bottom lines, the extreme low temperature is represented by left oblique lines, the extreme high temperature is represented by right oblique lines, the extreme wind speed is represented by short vertical lines, and the turbulence anomaly is represented by wave lines.

7. The fan operation data processing and visualizing method according to claim 1 or 2 or 3, characterized in that, When the graphs of three data of the same wind turbine are combined, the time axis of the horizontal axis is kept synchronous; the columnar graphs of data block A and data block C have consistent vertical heights, and the vertical height of the columnar graph corresponds to the full power of the model, the lowest point of the columnar graph corresponds to 0 power, and other power values are linearly and uniformly distributed therebetween, so as to combine the power timing graph of sequence B; Then arrange multiple wind turbines of a line or a wind farm in sequence vertically along the same horizontal axis; Normal generation and normal shutdown are represented by green color, command shutdown by yellow color, pre-maintenance shutdown by blue color, fault_unhandled and fault_handled by different red color, limited power and dispatch limited power shutdown by purple color, fan performance reduced generation by brown color, offline by gray color, and uncertain state by white or transparent color; actual power time series is represented by black solid line, and theoretical power time series is represented by green dotted line; grid environment abnormality is represented by horizontal line hatching, extreme temperature is represented by diagonal line hatching, extreme wind speed is represented by vertical line hatching, turbulence abnormality is represented by wave hatching, and blade icing is represented by block hatching.

8. A computer program product comprising a computer program, characterized in that, The computer program, when executed by the processor, performs the steps of the method of any of claims 1-7.

9. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program, when executed by the processor, performs the steps of the method of any of claims 1-7.

10. A fan condition data processing and visualization system comprising a memory and a processor interconnected, said memory having stored thereon a computer program, characterized in that, The computer program, when executed by the processor, performs the steps of the method of any of claims 1-7. The computer program, when executed by the processor, performs the steps of the method of any of claims 1-7.

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