CN116523349B - Wind power station reliability analysis method and system - Google Patents

Wind power station reliability analysis method and system Download PDF

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CN116523349B
CN116523349B CN202310569587.7A CN202310569587A CN116523349B CN 116523349 B CN116523349 B CN 116523349B CN 202310569587 A CN202310569587 A CN 202310569587A CN 116523349 B CN116523349 B CN 116523349B
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wind turbine
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CN116523349A (en
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陆一川
刘瑞华
陈振华
马书龙
李晶晶
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Beijing Xiehe Operation And Maintenance Wind Power Technology Co ltd
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Beijing Xiehe Operation And Maintenance Wind Power Technology Co ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
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    • G06Q50/06—Energy or water supply
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
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    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications

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Abstract

The invention provides a wind power station reliability analysis method and a system, wherein the method comprises the following steps: acquiring state data of each wind turbine generator; calculating the availability coefficient of each wind turbine based on the state data of each wind turbine; based on the parameters of the wind power plant and the available coefficient of each wind turbine generator, calculating the available coefficient of the wind power plant and the output power of the wind power plant; based on the availability coefficient of the wind power plant and the output power of the wind power plant, selecting a reliability index and carrying out reliability analysis on the wind power plant to obtain a reliability analysis result. According to the invention, through reliability analysis on the layering level of the wind power station, fault detection and maintenance are carried out according to the reliability analysis result, and the stability of the future output power of the wind power station is maintained by using the power grid energy storage equipment, so that the service lives of the wind power station and the power grid energy storage equipment are prolonged.

Description

Wind power station reliability analysis method and system
Technical Field
The invention relates to the technical field of wind power generation, in particular to a wind power station reliability analysis method and system.
Background
The traditional energy source is fossil energy source. The large-scale exploitation and utilization of fossil energy sources are easy to cause specific harm to the environment, such as acid rain, greenhouse effect and the like. Thus, developed countries are increasingly paying attention to new clean energy sources. Wind energy is one of novel clean energy sources, and is increasingly favored by people. However, the fluctuation of wind energy is relatively large, so that the output power of the wind power station is in an unstable state, and the reliability analysis is needed by artificial intelligence, and intelligent control is performed according to the reliability analysis result.
The prior art CN110084465B provides a wind power generation system cost/power supply reliability evaluation method based on energy storage, and the power failure compensation expense is used as an evaluation object of the system reliability, and the charging and discharging power of the AA-CAES energy storage power station is optimized by using a dynamic programming algorithm so as to balance the randomness of wind power generation. However, in the prior art CN110084465B, energy is stored by compressed air, only the reliability of the whole wind power station is analyzed, the layered reliability analysis of the wind power station is not performed, fault detection and maintenance are not performed according to the reliability analysis result, the compressed air is used for energy storage, and the reaction time of the energy storage equipment of a power grid is short, and the charging speed is high. But if the SOC threshold value is not set and the SOC charging current is controlled, the power grid energy storage equipment is easy to influence the service life of the power grid energy storage equipment because the charging current is too large and the SOC threshold value is too low.
Disclosure of Invention
The invention aims to provide a reliability analysis method for a wind power station, which is characterized in that reliability analysis is carried out on the layering level of the wind power station, fault detection and maintenance are carried out according to the reliability analysis result, the stability of the future output power of the wind power station is maintained by utilizing power grid energy storage equipment, and the service lives of the wind power station and the power grid energy storage equipment are prolonged.
The invention provides a wind power station reliability analysis method which is applied to a wind power station, wherein the wind power station comprises a plurality of wind power stations, any wind power station comprises a plurality of wind power units, and the method comprises the following steps:
acquiring state data of each wind turbine generator;
calculating the availability coefficient of each wind turbine based on the state data of each wind turbine;
based on the parameters of the wind power plant and the available coefficient of each wind turbine generator, calculating the available coefficient of the wind power plant and the output power of the wind power plant;
based on the availability coefficient of the wind power plant and the output power of the wind power plant, selecting a reliability index and carrying out reliability analysis on the wind power plant to obtain a reliability analysis result.
Preferably, calculating the availability factor of each wind turbine based on the state data of each wind turbine includes:
acquiring state data of each wind turbine generator;
constructing a power-wind speed prediction model based on historical data of each wind turbine;
predicting the future output power of each wind turbine based on the power-wind speed prediction model and the wind speed of the future weather forecast;
and obtaining the availability coefficient of each wind turbine based on the predicted future output power of each wind turbine.
Preferably, based on the availability coefficient of the wind power plant and the output power of the wind power plant, selecting a reliability index and performing reliability analysis on the wind power plant to obtain a reliability analysis result, including:
Obtaining the output power of each wind power station, and calculating the total power of the wind power station;
calculating the availability coefficient of the wind power station based on the availability coefficient of each wind power station;
selecting a reliability index, wherein the reliability index comprises shutdown time, failure time and failure rate;
and acquiring the availability coefficient and the historical maintenance record of the wind power station and selecting the reliability index, calculating the value corresponding to the reliability index based on the selected reliability index, and summarizing to obtain a reliability analysis data table of the wind power station.
Preferably, the wind power plant reliability analysis method further comprises:
acquiring current state data of any wind power plant, detecting whether wind turbines in the wind power plant are abnormal or not according to the current state data, and determining maintenance sequence;
the method for acquiring the current state data of any wind power plant, detecting whether the wind power generation set in the wind power plant is abnormal or not according to the current state data and determining the maintenance sequence comprises the following steps:
acquiring historical data of any wind power plant, and constructing an available coefficient database of any wind power plant;
acquiring wind speed data of a future preset time period, and predicting an available coefficient predicted value of the future preset time period of any wind power plant based on the wind speed data of the future preset time period and an available coefficient database of any wind power unit;
When any wind farm operates to a future preset time period, acquiring a true value of an available coefficient of the future preset time period of any wind farm;
calculating the deviation rate of the available coefficient based on the actual value of the available coefficient and the predicted value of the available coefficient in the future preset time period of any wind power plant;
judging whether the deviation rate of the available coefficient is higher than a preset first threshold value, if so, judging that any wind power plant fails, and if not, judging that any wind power plant is normal;
if any wind power plant is judged to have faults, collecting the output power of all wind power units in any wind power plant, predicting the output power of all wind power units in any wind power plant, and calculating the deviation rate of the output power of each wind power unit;
judging whether the output power deviation rate is higher than a preset second threshold value, if so, judging that any wind turbine generator fails, and if not, judging that any wind turbine generator is normal;
collecting voiceprint data of any wind turbine generator to identify a fault type;
And determining the maintenance sequence of any fault wind turbine generator based on the reliability analysis result of the wind power station.
Preferably, the wind power plant reliability analysis method further comprises:
if the fault type is that the lubricating oil is aged, lubricating oil is supplied to any wind turbine generator;
if the fault type is that the lubricating oil is aged, lubricating oil is supplied to any wind turbine generator, and the method comprises the following steps:
when the abnormal type is judged to belong to the aging of the lubricating oil, determining an abnormal part of any wind turbine generator;
cleaning abnormal parts of any wind turbine generator;
acquiring historical data of any wind turbine generator, and fitting a relation between the lubricant dosage and the power of the wind turbine generator;
calculating the lubricant dosage corresponding to the rated power based on the rated power, and adding lubricant based on the lubricant dosage corresponding to the rated power;
and obtaining the first real-time power of any wind turbine generator, predicting the first predicted power of any wind turbine generator based on the relation between the wind speed and the output power of any wind turbine generator, and adding a difference value between the lubricant dosage corresponding to the first predicted power and the lubricant dosage corresponding to the first real-time power based on the relation between the lubricant dosage and the power of the wind turbine generator if the first real-time power is less than the first predicted power according to judgment on whether the first real-time power is less than the first predicted power, or not adding the lubricant dosage if the first real-time power is not less than the rated power.
Preferably, the wind power plant reliability analysis method further comprises:
predicting a future reliability analysis result of the wind power station according to the wind speed of the future weather forecast, and adjusting the wind power station according to the future reliability analysis result of the wind power station;
wherein, the wind power station is adjusted according to the wind speed forecast of the weather forecast and the future reliability analysis result of the wind power station, comprising:
acquiring a real-time reliability analysis result of a wind power station, obtaining real-time output power of each wind turbine generator, and forming a real-time output power matrix;
the future reliability analysis result of the wind power station is predicted by combining the future weather forecast and the real-time output power matrix to obtain the future output power of each wind turbine unit, and a future output power matrix is formed;
correcting a future output power matrix by combining the failure rate and the repair rate in the reliability analysis;
calculating the sum of all matrix elements in a future output power matrix to obtain the future total power of the wind power station;
judging that the future total power of the wind power station is in a set threshold value interval of the wind power station, if the future total power of the wind power station is in the upper limit of the set threshold value interval of the wind power station, calculating an adjustment pitch angle of each wind turbine unit according to a future output power matrix, so that the future total power of the wind power station is in a power generation capacity threshold value interval of the wind power station, if the future total power of the wind power station is in the lower limit of the set threshold value interval of the wind power station, providing differential power for the wind power station through a power grid energy storage device, and if the future total power of the wind power station is in the power generation capacity threshold value interval of the wind power station, not adjusting; if the wind speed is less than the cut-in wind speed or greater than the cut-out wind speed, the wind power station stops generating electricity.
Preferably, if the future total power of the wind power plant is at the upper limit of the set threshold interval of the wind power plant, the adjustment angle of each wind turbine is calculated according to the future output power matrix, so that the future total power of the wind power plant is within the power generation capacity threshold interval of the wind power plant, including:
acquiring an adjusted future output power matrix and a pitch angle of each wind turbine;
acquiring the upper limit of a set threshold interval of a wind power station and the maximum power of each wind turbine generator, and determining a future upper limit matrix of the wind power station;
according to the future output power matrix and the future upper limit matrix, determining an adjustment value of each wind turbine, wherein the adjustment value of each wind turbine forms an adjustment matrix;
and controlling the pitch angle of each wind turbine according to the relation between the power of each wind turbine and the pitch angle of the wind direction, so that the adjustment matrix is a non-positive matrix.
Preferably, if the future total power of the wind power plant is at the lower limit of the set threshold interval of the wind power plant, providing differential power to the wind power plant by the grid energy storage device comprises:
acquiring historical data of wind power station power generation, and calculating the average value of the output power and the maximum value of the output power of the wind power station;
calculating the storage capacity and the SOC threshold value of the power grid energy storage equipment based on the maximum value and the mean value of the power generation of the wind power station and the reliability analysis result;
When the total power of the wind power station is in the lower limit of the set threshold interval of the wind power station, a first difference value between the total power in the future and the lower limit of the set threshold interval is calculated, and based on the first difference value, the power grid energy storage equipment provides differential power for the wind power station;
when the SOC value of the power grid energy storage equipment is lower than a set SOC threshold value, controlling to disconnect the power connection of the wind power station and the power grid energy storage equipment based on the first difference value;
and stopping providing the differential power for the wind power station and charging the power grid energy storage device to store electric energy of the set power grid energy storage device according to the maximum charging current calculated by the state of the SOC when the future total power of the wind power station is recovered to be greater than the lower limit of the set threshold interval of the wind power station.
The invention also provides a wind power station reliability analysis system, which is applied to a wind power station, wherein the wind power station comprises a plurality of wind power stations, any wind power station comprises a plurality of wind power units, and the system comprises:
the acquisition module is used for acquiring the state data of each wind turbine generator;
the unit analysis module is used for calculating the availability coefficient of each wind turbine based on the state data of each wind turbine;
the wind power plant analysis module is used for calculating the availability coefficient of the wind power plant and the output power of the wind power plant based on the parameters of the wind power plant and the availability coefficient of each wind turbine generator;
The power station analysis module is used for selecting a reliability index based on the availability coefficient of the wind power plant and the output power of the wind power plant, and carrying out reliability analysis on the wind power station to obtain a reliability analysis result.
Preferably, the wind power plant reliability analysis system further comprises:
the fault detection module is used for acquiring current state data of any wind turbine generator, detecting whether any wind turbine generator is abnormal or not according to the current state data and determining maintenance sequence;
the lubricating oil supply module is used for supplying lubricating oil to any wind turbine generator if the fault type is lubricating oil aging;
the wind power adjustment module is used for predicting a future reliability analysis result of the wind power station according to the wind speed of the future weather forecast and adjusting the wind power station according to the future reliability analysis result of the wind power station.
The beneficial effects of the invention are as follows:
according to the invention, the wind power station comprises a plurality of wind power stations, each wind power station comprises a plurality of wind power units, and influence factors of the wind power units are considered in multiple aspects, so that the output power and the availability coefficient of the wind power stations and the wind power station are more accurate, and the result is more close to reality.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of a reliability analysis method for a wind turbine power station according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a reliability analysis system for a wind turbine power station according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The embodiment of the invention provides a wind power station reliability analysis method, which is shown in figure 1 and comprises the following steps:
and step 1, acquiring state data of each wind turbine generator.
And 2, calculating the availability coefficient of each wind turbine based on the state data of each wind turbine.
And 3, calculating the availability coefficient of the wind power plant and the output power of the wind power plant based on the parameters of the wind power plant and the availability coefficient of each wind turbine.
And 4, selecting a reliability index based on the availability coefficient of the wind power plant and the output power of the wind power plant, and carrying out reliability analysis on the wind power plant to obtain a reliability analysis result.
The working principle and the beneficial effects of the technical scheme are as follows:
the state data of each wind turbine includes captured wind speed, air pressure and temperature of the wind turbine, wind energy conversion efficiency and failure time of the wind turbine. Because wind speed has certain influence on the power generation of the wind turbine generator. The wind speed is smaller than the cut-in wind speed of the wind turbine generator or larger than the cut-out wind speed of the wind turbine generator, and the wind turbine generator stops running.
When the working temperature of the wind turbine is not in the set range, the output power of the wind turbine is 0, and the wind turbine is in a shutdown state. Because the temperature is too high and too low, the wind turbine generator is easy to overheat or overcooled, and the motor is easy to damage.
When wind speedv a Is cut-in wind speed v b The wind speed is cut off, the output power of the wind turbine generator is 0, and the wind turbine generator is in a shutdown state. Because of wind velocity v<v a When the wind speed is too small, the wind turbine generator set cannot be started to rotate, and the wind speed v>v b During the time, because the wind speed is too big, damage to the wind turbine can appear if the wind turbine is started, even the tower collapse, impeller galloping and other safety accidents are caused.
And calculating the availability coefficient of the wind turbine according to the number of the outage hours in one year of the wind turbine.
Based on the parameters of the wind power plant and the output power of each wind turbine generator, the output power and the availability coefficient of the wind power plant are calculated. The parameters of the wind power plant comprise wind power distribution conditions of the wind power plant, temperature distribution conditions of the wind power plant and distribution conditions of wind power units, the output power of each wind power unit in the wind power plant is calculated according to the parameters of the wind power plant, and the output power of the wind power plant is calculated according to the output power of each wind power unit in the wind power plant.
Therefore, the availability coefficient of each wind power plant can be calculated according to the availability coefficient of each wind power generation set.
The total power of the wind power stations can be obtained by summing the output power of each wind power station, and similarly, the availability coefficient of the wind power stations can be calculated according to the availability coefficient of each wind power station.
And selecting reliability indexes, wherein the reliability indexes comprise shutdown time, failure rate and the like. And finally outputting a reliability analysis result.
According to the embodiment of the invention, the wind power station comprises a plurality of wind power stations, each wind power station comprises a plurality of wind power units, and influence factors of the wind power units are considered in multiple aspects, so that the output power and the availability coefficient of the wind power station and the wind power station are more accurate, and the result is more close to reality.
In one embodiment, step 2 comprises the steps of:
and 2.1, acquiring state data of each wind turbine.
And 2.2, constructing a power-wind speed prediction model based on the historical data of each wind turbine.
And 2.3, predicting the future output power of each wind turbine based on the power-wind speed prediction model and the wind speed of the future weather forecast.
And 2.4, obtaining the availability coefficient of each wind turbine based on the predicted future output power of each wind turbine.
The working principle and the beneficial effects of the technical scheme are as follows:
since the variation of the output power varies with the variation of the wind speed. When the wind speed v<v a When the wind speed is too small, the wind turbine generator set cannot be started to rotate, v a ≤v<v e V when (v) e The rated wind speed is the wind speed, and the output power increases as the wind speed v increases. While when v e ≤v≤v b When the output power reaches a fixed value, the maximum value is also the rated power. When v>v b When the wind speed is too high, the output power is 0.
And because wind speed is time-of-day, wind speed includes base wind speed, gust wind speed, progressive wind speed, and random wind speed.
The uncertainty of wind speed affects the output power. The wind speed probability distribution thus determines the probability distribution of the output power. And predicting the output power of each wind turbine according to the probability distribution of the output power. Meanwhile, when the output power is zero, the corresponding wind turbine generator is in a shutdown state, and the shutdown hours of the wind turbine generator can be obtained, so that the availability coefficient of each wind turbine generator is obtained. The availability factor for each wind turbine is thus related to the probability that the output power is zero.
Therefore, a annual wind speed record of the single wind turbine is acquired, and the basic wind speed is according to the geographical environment of the single wind turbine, such as subtropical climate of the single wind turbine in Jiangsu region of China, and according to the monsoon climate of the Pacific plate and the America continental plate. And the value of the basic wind speed can be obtained according to the local weather forecast corresponding to any specific day, so the basic wind speed can be approximately regarded as a constant. The gust speed is the speed of the wind that occurs instantaneously and may be approximated as a continuous normal distribution. The progressive wind speed is a wind speed at which the wind speed gradually stabilizes. Whereas the random wind speed has randomness, it can be calculated from the random function random ().
Therefore, the basic wind speed, the gust wind speed, the progressive wind speed and the random wind speed are overlapped, a wind speed simulation model is built, and then the output power of each wind turbine generator can be predicted according to the relation between the power and the wind speed. And then according to the time that the output power of each wind turbine is zero in one year, the availability coefficient of each wind turbine is obtained.
According to the wind speed simulation method, the output power and the availability coefficient of each wind turbine generator are obtained by constructing the wind speed simulation model and the relation between the power and the wind speed, and the prediction accuracy of the output power and the availability coefficient is improved.
In one embodiment, step 4 comprises:
and 4.1, obtaining the output power of each wind power station, and calculating the total power of the wind power station.
And 4.2, calculating the availability coefficient of the wind power station based on the availability coefficient of each wind power station.
And 4.3, selecting a reliability index, wherein the reliability index comprises the outage time, the fault time and the fault rate.
And 4.4, acquiring the availability coefficient and the historical maintenance record of the wind power station and selecting the reliability index, calculating the value corresponding to the reliability index based on the selected reliability index, and summarizing to obtain a reliability analysis data table of the wind power station.
The working principle and the beneficial effects of the technical scheme are as follows:
according to a wind power plant comprising m wind farms, each wind farm comprising n wind turbines, an output power matrix of the wind power plant is constructed.
The total power of the wind power plant thus corresponds to the sum of the matrix elements of the output power matrix.
Similarly, the availability factor for the wind power plant may be calculated.
And selecting a reliability index, wherein the reliability index comprises a shutdown time, a fault time and a fault rate.
And calculating a numerical value corresponding to the reliability index based on the selected reliability index to acquire the historical maintenance record of the wind power station. The time to failure and the failure rate may be calculated from historical maintenance records of the power units, wind farms and wind power plants. And calculating the corresponding numerical value of each reliability index and summarizing to obtain a reliability analysis data table of the wind power station.
In one embodiment, further comprising:
and 5, acquiring current state data of any wind power plant, detecting whether the wind turbine generator in the wind power plant is abnormal or not according to the current state data, and determining the maintenance sequence. The step 5 specifically comprises the following steps:
and 5.1, acquiring historical data of any wind power plant, and constructing an available coefficient database of any wind power plant.
And 5.2, acquiring wind speed data of a future preset time period, and predicting an available coefficient predicted value of the future preset time period of any wind power plant based on the wind speed data of the future preset time period and an available coefficient database of any wind turbine generator.
And 5.3, collecting the actual value of the available coefficient of any wind farm in the future preset time period when any wind farm is operated in the future preset time period.
And 5.4, calculating the deviation rate of the available coefficient based on the actual value of the available coefficient and the predicted value of the available coefficient in the future preset time period of any wind power plant.
And 5.5, judging whether the deviation rate of the available coefficient is higher than a preset first threshold value, if so, judging that any wind power plant fails, and if not, judging that any wind power plant is normal.
And 5.6, if any wind power plant is judged to be faulty, collecting the output power of all the wind power units in any wind power plant, predicting the output power of all the wind power units in any wind power plant, and calculating the deviation rate of the output power of each wind power unit.
And 5.7, judging whether the output power deviation rate is higher than a preset second threshold value, if so, judging that any wind turbine generator fails, and if not, judging that any wind turbine generator is normal.
And 5.8, collecting voiceprint data of any wind turbine generator to identify the fault type.
And 5.9, determining the maintenance sequence of any faulty wind turbine generator based on the reliability analysis result of the wind power station.
The working principle and the beneficial effects of the technical scheme are as follows:
and acquiring state data of any wind power plant, and constructing an available coefficient database of any wind power plant. The state data of any wind farm comprises the temperature, the pitch angle, the air pressure and the sea wave height of each wind turbine of the wind farm. Based on a change in wind speed of 11 months. And predicting the predicted value of the available coefficient of the future preset time period of any wind power plant based on the wind speed data of the future preset time period and the available coefficient database of any wind turbine. The future time period, such as 11 months, is preset, and the available coefficient prediction value of 11 months is predicted. At 11 months, the true value of the available coefficient of any wind farm is collected. And calculating the available coefficient deviation rate= (available coefficient predicted value-available coefficient true value)/available coefficient true value according to the available coefficient predicted value and the available coefficient true value.
And setting a first threshold value of the deviation rate of the available coefficients, such as 0.2, and judging that any wind farm fails when the deviation rate of the available coefficients is higher than a preset first threshold value.
And if any wind power plant is judged to be faulty, collecting the output power of each wind turbine in any wind power plant, predicting the output power of each wind turbine in any wind power plant, and calculating the deviation rate of the output power of each wind turbine. The output power of each wind turbine generator is predicted, and the predicted value of the output power of each wind turbine generator can be calculated according to the relation between the wind speed and the output power. And similarly, the output power deviation rate of each wind turbine generator can be calculated.
Setting a second threshold value, judging whether the output power deviation rate is higher than a preset second threshold value, if so, judging that any wind turbine generator fails, and if not, judging that any wind turbine generator is normal. And collecting voiceprint data of the wind turbine generators, and identifying the fault type according to the voiceprint data of any wind turbine generator. The fault type database is constructed according to the historical voiceprint data of the fault types, the voiceprint data of the fault wind turbine generator is collected, the overlap ratio is calculated with the fault type database, the overlap ratio is arranged from large to small, and the fault types contained in the overlap ratio exceeding the set overlap ratio threshold are the fault types corresponding to the fault wind turbine generator. And then observing the shutdown time and the maintenance times according to the reliability analysis result of the wind power station, and preferentially arranging and maintaining the wind turbine generators with long shutdown time and more maintenance times.
According to the embodiment of the invention, the wind power plant and the wind turbine generator set under the wind power station are subjected to fault investigation respectively through the available coefficient deviation rate and the output power deviation rate, the difficulty of fault investigation is reduced, the fault type corresponding to the wind turbine generator set is judged according to voiceprint data, and the overhaul is arranged in combination with the reliability analysis result of the wind power station.
In one embodiment, further comprising:
and 6, if the fault type is that the lubricating oil is aged, lubricating oil is supplied to any wind turbine. The method specifically comprises the following steps:
and 6.1, determining an abnormal part of any wind turbine generator when the abnormal type is judged to belong to the aging of the lubricating oil.
And 6.2, cleaning the abnormal part of any wind turbine generator.
And 6.3, acquiring historical data of any wind turbine generator, and fitting a relation between the lubricant dosage and the power of the wind turbine generator.
And 6.4, calculating the lubricant dosage corresponding to the rated power based on the rated power, and adding lubricant based on the lubricant dosage corresponding to the rated power.
And 6.5, obtaining the first real-time power of any wind turbine, predicting the first predicted power of any wind turbine based on the relation between the wind speed and the output power of any wind turbine, and adding a difference between the lubricant dosage corresponding to the first predicted power and the lubricant dosage corresponding to the first real-time power based on the relation between the lubricant dosage and the power of the wind turbine if the first real-time power is less than the first predicted power and the first predicted power, if the first real-time power is not less than the first predicted power, not adding the lubricant dosage.
The working principle and the beneficial effects of the technical scheme are as follows:
and when the abnormal type is judged to belong to the aging of the lubricating oil, determining an abnormal part of any wind turbine generator, such as a bearing of any wind turbine generator. And cleaning the abnormal part of any wind turbine generator to remove aged lubricating oil. And acquiring historical data of any wind turbine generator, and fitting a relation between the lubricant dosage and the power of the wind turbine generator. And calculating the lubricant dosage corresponding to the rated power and adding lubricant. And checking whether the lubricant dosage accords with the relation between the lubricant dosage and the power of the wind turbine generator according to the real-time power, if not, indicating that the lubricant dosage is less, continuing to add the lubricant, and calculating the lubricant dosage according to the relation between the lubricant dosage and the power of the wind turbine generator.
According to the embodiment of the invention, the dosage of the lubricating oil is controlled to be added according to the relation between the dosage of the lubricating oil and the power of the wind turbine generator, so that the waste of the lubricating oil is reduced.
In one embodiment, further comprising:
and 7, predicting a future reliability analysis result of the wind power station according to the wind speed of the future weather forecast, and adjusting the wind power station according to the future reliability analysis result of the wind power station. The method specifically comprises the following steps:
And 7.1, collecting the real-time output power of each wind turbine generator to form a real-time output power matrix.
And 7.2, predicting the future output power of each wind turbine by combining the future weather forecast, and forming a future output power matrix.
And 7.3, correcting the future output power matrix by combining the failure rate and the repair rate in the reliability analysis.
And 7.4, calculating the sum of all matrix elements in the corrected future output power matrix to obtain the future total power of the wind power station.
And 7.5, judging that the future total power of the wind power station is within a set threshold value interval of the wind power station. If the future total power of the wind power station is at the upper limit of the set threshold interval of the wind power station, calculating an adjustment pitch angle of each wind turbine generator according to the future output power matrix, so that the future total power of the wind power station is within the set threshold interval of the wind power station, if the future total power of the wind power station is at the lower limit of the set threshold interval of the wind power station, providing differential power for the wind power station through the power grid energy storage equipment, and if the future total power of the wind power station is within the power generation capacity threshold interval of the wind power station, not adjusting; if the wind speed is less than the cut-in wind speed or greater than the cut-out wind speed, the wind power station stops generating electricity.
The working principle and the beneficial effects of the technical scheme are as follows:
and forming an output power matrix by the output power of each wind turbine. And collecting the real-time output power of each wind turbine generator to form a real-time output power matrix. And predicting the future output power of each wind turbine unit by combining the future weather forecast according to the wind speed simulation model and the relation between the output power and the wind speed, and forming a future output power matrix. And combining the failure rate and the repair rate in the reliability analysis, such as the failure rate in the reliability analysis, predicting the shutdown of the future wind turbine, predicting the operation of the future wind turbine by the repair rate, and correcting the future output power matrix to obtain a corrected future output power matrix. And carrying out matrix summation on the corrected future output power matrix to obtain the future total power of the wind power station.
The maximum power load limit of the power system of the wind power station determines the upper limit of the set threshold interval of the wind power station, and meanwhile, the minimum power generation power required by the basic operation of the wind power station, the resident power utilization system and the wind power station determines the lower limit of the set threshold interval of the wind power station. Meanwhile, in order to maintain the stability of the output power of the wind power station, when the lower limit of the set threshold interval of the wind power station is set, the power grid energy storage equipment is provided for providing differential power for the wind power station, the power supply of the wind power station is maintained stable, and the power grid energy storage equipment is charged when the electricity consumption of the resident electricity utilization system is low. For example, in the daytime or in the winter and summer, the power consumption of residents is high, and the residents can discharge through the power grid energy storage equipment for the purpose of balancing the wind power station and the resident power consumption system to a certain extent. And night or spring and autumn, the resident has small electricity consumption, and the wind power station is used for charging the power grid energy storage equipment, so that the wind power station can stabilize external power supply in time.
When the future total power of the wind power station is in the upper limit of the set threshold interval of the wind power station, the fact that the total power of the power supply exceeds the maximum load of the power system of the wind power station is indicated, the adjustment pitch angle of each wind turbine is calculated according to the future output power matrix, the wind energy conversion efficiency of each wind turbine is adjusted, the output power of each wind turbine is reduced according to a certain proportion, and when the future total power of the wind power station is in the set threshold interval of the wind power station, the output power is prevented from being excessively large, and the power system is prevented from being damaged. When the wind speed is smaller than the cut-in wind speed or larger than the cut-out wind speed, the wind power station stops generating power for maintaining the safety of the power station.
In one embodiment, if the future total power of the wind power plant is at the upper limit of the set threshold interval of the wind power plant in step 7.5, the adjustment pitch angle of each wind turbine is calculated according to the future output power matrix, such that the future total power of the wind power plant is within the set threshold interval of the wind power plant. The method comprises the following steps:
and firstly, acquiring an adjusted future output power matrix and a pitch angle of each wind turbine.
And secondly, obtaining the upper limit of a set threshold interval of the wind power station and the maximum power of each wind turbine generator, and determining a future upper limit matrix of the wind power station.
And thirdly, determining an adjustment value of each wind turbine according to the future output power matrix and the future upper limit matrix, wherein the adjustment value of each wind turbine forms an adjustment matrix.
And fourthly, controlling the pitch angle of each wind turbine according to the relation between the power of each wind turbine and the pitch angle of the wind direction, so that the adjustment matrix is a non-positive matrix.
The working principle and the beneficial effects of the technical scheme are as follows:
and acquiring the adjusted future output power matrix and the pitch angle of each wind turbine. Obtaining the upper limit of a set threshold interval of the wind power station and the maximum power of each wind turbine, namely rated power, summing the maximum power of each wind turbine, comparing the maximum power with the upper limit of the set threshold interval of the wind power station according to the sum of the maximum powers, and if the sum of the maximum powers is larger than the upper limit of the set threshold interval of the wind power station, reasonably distributing the maximum power of each wind turbine according to the set threshold interval of the wind power station and the maximum power of each wind turbine, and determining a future upper limit matrix of the wind power station. For example, if the upper limit of the set threshold interval of the wind power plant is 60w and the sum of the maximum power is 120w, the proportionality coefficient of the upper limit of the set threshold interval and the sum of the maximum power of the wind power plant can be 1/2, and the upper limit of the set threshold interval of the wind power plant is allocated according to the rated power of each wind turbine. For example, there are 2 wind farms in total, each wind farm has 2 wind turbines, the rated power of each wind turbine in the first wind farm is 20w, the rated power of each wind turbine in the second wind farm is 40w, and the future upper limit matrix of the wind farms is formed according to the upper limit of the set threshold interval of the wind farms If the sum ratio of maximum powerThe maximum power of each wind turbine generator set forms the future upper limit matrix of the wind turbine generator set if the upper limit of the set threshold interval of the wind turbine generator set is small, for example, the upper limit of the set threshold interval of the wind turbine generator set is 180 kilowatts, the sum of the maximum powers is 120 kilowatts, the wind turbine generator set has 2 wind power stations in total, each wind power station has 2 wind turbine generator sets, the rated power of each wind turbine generator set of the first wind power station is 20 kilowatts, the rated power of each wind turbine generator set of the second wind power station is 40 kilowatts, and the future upper limit matrix of the wind turbine generator set is%>
And constructing a difference matrix, namely, performing difference between each matrix element in the future output power matrix and the matrix element corresponding to the future upper limit matrix, and taking the obtained difference matrix as an adjustment matrix. For example, the future upper limit matrix of a wind power plant isAnd the future output power matrix is +.>Therefore, the difference matrix is constructed as follows:thereby adjusting the matrix to +.>
The wind turbine generator comprises a wind wheel, a transmission system and a generator. Wherein, the wind wheel includes blade and wheel hub. The wind wheel faces the wind direction and receives wind energy, and the mechanical energy is transmitted to the rotating shaft of the generator through the transmission system, so that the magnetic force lines of the generator are cut, and wind power generation is performed. One end of the blade is rotatably connected to the hub and forms a certain included angle with the plane of the wind wheel, and the included angle is the blade pitch angle. Factors that affect the rated power of a wind turbine include blade pitch angle and blade size. Thus, in the case of a certain blade size, the change in pitch angle corresponds to the forehead The magnitude of the fixed power varies. The blades are rotated clockwise towards the wind direction to be connected to one end of the hub, so that the blade pitch angle is changed, and the rated power of the wind turbine generator is changed. Thus adjusting the matrixAnd adjusting the blade angle of each wind turbine generator according to the relation between the output power and the blade angle. Each wind turbine of the first wind farm is thus connected by a rotating blade at a blade pitch angle of 15 ° at the end of the rotating blade connected to the hub, clockwise towards the wind direction Fang Xiangshun. Each wind turbine generator in the first wind farm is connected to a blade pitch angle of 7.5 degrees at one end of the hub, which is connected to the rotating blades in the direction Fang Xiangshun by rotating blades. Again a new adjustment matrix is calculated, the new adjustment matrix being +.>So that the matrix elements of the new adjustment matrix are not positive numbers.
According to the embodiment of the invention, the pitch angle of each wind turbine is adjusted through the adjustment matrix, so that the pitch angle is adjusted quickly, the total power of the wind power station in the future is within the set threshold interval of the wind power station, each wind turbine is controlled conveniently and collectively, the safety of the wind power station is improved, and the failure rate of the wind power station is reduced.
In one embodiment, if the future total power of the wind power plant is at the lower limit of the set threshold interval of the wind power plant in step 7.5, providing differential power to the wind power plant through the grid energy storage device, comprising the steps of:
And step one, acquiring historical data of power generation of the wind power station, and calculating the average value and the maximum value of the output power of the wind power station.
And secondly, calculating the storage capacity and the SOC threshold value of the power grid energy storage equipment based on the maximum value and the average value of the power generation of the wind power station and the reliability analysis result.
And thirdly, when the total power of the wind power station is in the lower limit of the set threshold interval of the wind power station, calculating a first difference value between the total power in the future and the lower limit of the set threshold interval, and providing differential power for the wind power station by the power grid energy storage equipment based on the first difference value.
And fourthly, when the SOC value of the power grid energy storage equipment is lower than a set SOC threshold value, controlling to disconnect the power connection of the wind power station and the power grid energy storage equipment based on the first difference value.
And fifthly, stopping providing the differential power for the wind power station and charging the power grid energy storage device to store electric energy of the power grid energy storage device according to the maximum charging current calculated by the state of the SOC when the future total power of the wind power station is recovered to be greater than the lower limit of the set threshold interval of the wind power station.
The working principle and the beneficial effects of the technical scheme are as follows:
and acquiring historical data of wind power station power generation, and calculating the average value, the maximum value and the minimum value of the output power of the wind power station.
And meanwhile, calculating the average outage time of the wind power station according to the reliability analysis result.
And calculating the storage capacity and the SOC threshold value of the power grid energy storage equipment according to the maximum value and the average value of the power generation of the wind power station and the reliability analysis result.
When the total power of the wind power station is in the lower limit of the set threshold interval of the wind power station, a first difference value between the total power in the future and the lower limit of the set threshold interval is calculated, and based on the first difference value, the power grid energy storage equipment provides differential power for the wind power station.
And when the SOC value of the power grid energy storage equipment is lower than the set SOC threshold value, controlling to disconnect the power connection of the wind power station and the power grid energy storage equipment based on the first difference value.
When the future total power of the wind power station is recovered to be greater than the lower limit of the set threshold interval of the wind power station, the supply of differential power to the wind power station is stopped, the power grid energy storage equipment is charged to the stored electric energy of the set power grid energy storage equipment, and in order to prevent the current from coming, the ion state in the battery of the power grid energy storage equipment is separated out, so that the maximum charging current can be obtained according to the state of the SOC.
According to the embodiment of the invention, the power grid energy storage equipment is added to provide differential power for the wind power generation system, so that the persistence and the stability of the wind power station are ensured, the failure rate of the wind power station is reduced, meanwhile, the maximum charging current is obtained according to the state of the SOC, and the service life of the power grid energy storage equipment is prolonged.
The embodiment of the invention also provides a wind power station reliability analysis system, as shown in fig. 2, comprising:
the acquisition module 1 is used for acquiring the state data of each wind turbine.
And the unit analysis module 2 is used for calculating the availability coefficient of each wind turbine based on the state data of each wind turbine.
The wind farm analysis module 3 is configured to calculate an availability coefficient of the wind farm and output power of the wind farm based on parameters of the wind farm and the availability coefficient of each wind turbine.
And the power station analysis module 4 is used for selecting a reliability index based on the availability coefficient of the wind power plant and the output power of the wind power plant, and carrying out reliability analysis on the wind power station to obtain a reliability analysis result.
The working principle and the beneficial effects of the technical scheme are as follows:
according to the embodiment of the invention, the output power and the availability coefficient are calculated in a layering manner on the wind power station, and the reliability index is selected and evaluated. And the influence factors of the wind turbine generator are considered in multiple aspects, so that the reliability analysis result is more accurate.
In one embodiment, the method further comprises the following modules:
the fault detection module 5 is used for acquiring current state data of any wind turbine, detecting whether any wind turbine is abnormal or not according to the current state data, and determining maintenance sequence.
And the lubricating oil replenishing module 6 is used for replenishing lubricating oil to any wind turbine generator if the fault type is lubricating oil aging.
The wind power adjustment module 7 is used for predicting a future reliability analysis result of the wind power station according to the wind speed of the future weather forecast and adjusting the wind power station according to the future reliability analysis result of the wind power station.
The working principle and the beneficial effects of the technical scheme are as follows:
according to the reliability analysis result, the fault detection module 5 is used for detecting faults of the wind turbine generator, and if the fault type is lubricating oil aging, the lubricating oil supply module 6 is used for supplying lubricating oil. The wind power adjusting module 7 predicts the future reliability analysis result of the wind power station according to the wind speed of the future weather forecast, meets the requirement of the upper limit of the set threshold interval by adjusting the pitch angle respectively, and provides difference power to meet the lower limit of the set threshold interval by the power grid energy storage equipment.
According to the embodiment of the invention, the wind power station is regulated and maintained according to the reliability analysis result of the wind power station, so that the normal operation of the wind power station is satisfied.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.

Claims (8)

1. The wind power station reliability analysis method is applied to a wind power station, wherein the wind power station comprises a plurality of wind power stations, and any wind power station comprises a plurality of wind power units, and is characterized by comprising the following steps:
acquiring state data of each wind turbine generator;
calculating the availability coefficient of each wind turbine based on the state data of each wind turbine;
based on the parameters of the wind power plant and the available coefficient of each wind turbine generator, calculating the available coefficient of the wind power plant and the output power of the wind power plant;
based on the availability coefficient of the wind power plant and the output power of the wind power plant, selecting a reliability index and carrying out reliability analysis on the wind power plant to obtain a reliability analysis result;
further comprises:
acquiring current state data of any wind power plant, detecting whether wind turbines in the wind power plant are abnormal or not according to the current state data, and determining maintenance sequence;
the method for acquiring the current state data of any wind power plant, detecting whether the wind power generation set in the wind power plant is abnormal or not according to the current state data and determining the maintenance sequence comprises the following steps:
acquiring historical data of any wind power plant, and constructing an available coefficient database of any wind power plant;
acquiring wind speed data of a future preset time period, and predicting an available coefficient predicted value of the future preset time period of any wind power plant based on the wind speed data of the future preset time period and an available coefficient database of any wind power unit;
When any wind farm operates to a future preset time period, acquiring a true value of an available coefficient of the future preset time period of any wind farm;
calculating the deviation rate of the available coefficient based on the actual value of the available coefficient and the predicted value of the available coefficient in the future preset time period of any wind power plant;
judging whether the deviation rate of the available coefficient is higher than a preset first threshold value, if so, judging that any wind power plant fails, and if not, judging that any wind power plant is normal;
if any wind power plant is judged to have faults, collecting the output power of all wind power units in any wind power plant, predicting the output power of all wind power units in any wind power plant, and calculating the deviation rate of the output power of each wind power unit;
judging whether the output power deviation rate is higher than a preset second threshold value, if so, judging that any wind turbine generator fails, and if not, judging that any wind turbine generator is normal;
collecting voiceprint data of any wind turbine generator to identify a fault type;
And determining the maintenance sequence of any fault wind turbine generator based on the reliability analysis result of the wind power station.
2. The wind power plant reliability analysis method of claim 1, wherein calculating availability factors for each wind turbine based on the status data for each wind turbine comprises:
acquiring state data of each wind turbine generator;
constructing a power-wind speed prediction model based on historical data of each wind turbine;
predicting the future output power of each wind turbine based on the power-wind speed prediction model and the wind speed of the future weather forecast;
and obtaining the availability coefficient of each wind turbine based on the predicted future output power of each wind turbine.
3. The method for analyzing the reliability of a wind power plant according to claim 1, wherein the steps of selecting a reliability index based on the availability factor of the wind power plant and the output power of the wind power plant and performing the reliability analysis on the wind power plant to obtain the reliability analysis result include:
obtaining the output power of each wind power station, and calculating the total power of the wind power station;
calculating the availability coefficient of the wind power station based on the availability coefficient of each wind power station;
selecting a reliability index, wherein the reliability index comprises shutdown time, failure time and failure rate;
And acquiring the availability coefficient and the historical maintenance record of the wind power station and selecting the reliability index, calculating the value corresponding to the reliability index based on the selected reliability index, and summarizing to obtain a reliability analysis data table of the wind power station.
4. The wind power plant reliability analysis method of claim 1, further comprising:
if the fault type is that the lubricating oil is aged, lubricating oil is supplied to any wind turbine generator;
if the fault type is that the lubricating oil is aged, lubricating oil is supplied to any wind turbine generator, and the method comprises the following steps:
when the abnormal type is judged to belong to the aging of the lubricating oil, determining an abnormal part of any wind turbine generator;
cleaning abnormal parts of any wind turbine generator;
acquiring historical data of any wind turbine generator, and fitting a relation between the lubricant dosage and the power of the wind turbine generator;
calculating the lubricant dosage corresponding to the rated power based on the rated power, and adding lubricant based on the lubricant dosage corresponding to the rated power;
and obtaining the first real-time power of any wind turbine generator, predicting the first predicted power of any wind turbine generator based on the relation between the wind speed and the output power of any wind turbine generator, and adding a difference value between the lubricant dosage corresponding to the first predicted power and the lubricant dosage corresponding to the first real-time power based on the relation between the lubricant dosage and the power of the wind turbine generator if the first real-time power is less than the first predicted power according to judgment on whether the first real-time power is less than the first predicted power, or not adding the lubricant dosage if the first real-time power is not less than the rated power.
5. The wind power plant reliability analysis method of claim 1, further comprising:
predicting a future reliability analysis result of the wind power station according to the wind speed of the future weather forecast, and adjusting the wind power station according to the future reliability analysis result of the wind power station;
wherein, the wind power station is adjusted according to the wind speed forecast of the weather forecast and the future reliability analysis result of the wind power station, comprising:
acquiring a real-time reliability analysis result of a wind power station, obtaining real-time output power of each wind turbine generator, and forming a real-time output power matrix;
the future reliability analysis result of the wind power station is predicted by combining the future weather forecast and the real-time output power matrix to obtain the future output power of each wind turbine unit, and a future output power matrix is formed;
correcting a future output power matrix by combining the failure rate and the repair rate in the reliability analysis;
calculating the sum of all matrix elements in a future output power matrix to obtain the future total power of the wind power station;
judging that the future total power of the wind power station is in a set threshold value interval of the wind power station, if the future total power of the wind power station is in the upper limit of the set threshold value interval of the wind power station, calculating an adjustment pitch angle of each wind turbine unit according to a future output power matrix, so that the future total power of the wind power station is in a power generation capacity threshold value interval of the wind power station, if the future total power of the wind power station is in the lower limit of the set threshold value interval of the wind power station, providing differential power for the wind power station through a power grid energy storage device, and if the future total power of the wind power station is in the power generation capacity threshold value interval of the wind power station, not adjusting; if the wind speed is less than the cut-in wind speed or greater than the cut-out wind speed, the wind power station stops generating electricity.
6. The wind power plant reliability analysis method of claim 5, wherein if the future total power of the wind power plant is at an upper limit of a set threshold interval of the wind power plant, calculating an adjustment angle of each wind turbine based on the future output power matrix such that the future total power of the wind power plant is within the power generation capacity threshold interval of the wind power plant comprises:
acquiring an adjusted future output power matrix and a pitch angle of each wind turbine;
acquiring the upper limit of a set threshold interval of a wind power station and the maximum power of each wind turbine generator, and determining a future upper limit matrix of the wind power station;
according to the future output power matrix and the future upper limit matrix, determining an adjustment value of each wind turbine, wherein the adjustment value of each wind turbine forms an adjustment matrix;
and controlling the pitch angle of each wind turbine according to the relation between the power of each wind turbine and the pitch angle of the wind direction, so that the adjustment matrix is a non-positive matrix.
7. The method of claim 5, wherein providing differential power to the wind power plant via the grid energy storage device if the future total power of the wind power plant is at a lower limit of a set threshold interval of the wind power plant, comprising:
Acquiring historical data of wind power station power generation, and calculating the average value of the output power and the maximum value of the output power of the wind power station;
calculating the storage capacity and the SOC threshold value of the power grid energy storage equipment based on the maximum value and the mean value of the power generation of the wind power station and the reliability analysis result;
when the total power of the wind power station is in the lower limit of the set threshold interval of the wind power station, a first difference value between the total power in the future and the lower limit of the set threshold interval is calculated, and based on the first difference value, the power grid energy storage equipment provides differential power for the wind power station;
when the SOC value of the power grid energy storage equipment is lower than a set SOC threshold value, controlling to disconnect the power connection of the wind power station and the power grid energy storage equipment based on the first difference value;
and stopping providing the differential power for the wind power station and charging the power grid energy storage device to store electric energy of the set power grid energy storage device according to the maximum charging current calculated by the state of the SOC when the future total power of the wind power station is recovered to be greater than the lower limit of the set threshold interval of the wind power station.
8. The utility model provides a wind power plant reliability analysis system, is applied to the wind power plant, and the wind power plant includes a plurality of wind power plants, and any wind power plant includes a plurality of wind turbine generator systems, its characterized in that includes:
The acquisition module is used for acquiring the state data of each wind turbine generator;
the unit analysis module is used for calculating the availability coefficient of each wind turbine based on the state data of each wind turbine;
the wind power plant analysis module is used for calculating the availability coefficient of the wind power plant and the output power of the wind power plant based on the parameters of the wind power plant and the availability coefficient of each wind turbine generator;
the power station analysis module is used for selecting a reliability index based on the availability coefficient of the wind power plant and the output power of the wind power plant, and carrying out reliability analysis on the wind power station to obtain a reliability analysis result;
further comprises:
the fault detection module is used for acquiring current state data of any wind turbine generator, detecting whether any wind turbine generator is abnormal or not according to the current state data and determining maintenance sequence;
comprising the following steps:
acquiring historical data of any wind power plant, and constructing an available coefficient database of any wind power plant;
acquiring wind speed data of a future preset time period, and predicting an available coefficient predicted value of the future preset time period of any wind power plant based on the wind speed data of the future preset time period and an available coefficient database of any wind power unit;
when any wind farm operates to a future preset time period, acquiring a true value of an available coefficient of the future preset time period of any wind farm;
Calculating the deviation rate of the available coefficient based on the actual value of the available coefficient and the predicted value of the available coefficient in the future preset time period of any wind power plant;
judging whether the deviation rate of the available coefficient is higher than a preset first threshold value, if so, judging that any wind power plant fails, and if not, judging that any wind power plant is normal;
if any wind power plant is judged to have faults, collecting the output power of all wind power units in any wind power plant, predicting the output power of all wind power units in any wind power plant, and calculating the deviation rate of the output power of each wind power unit;
judging whether the output power deviation rate is higher than a preset second threshold value, if so, judging that any wind turbine generator fails, and if not, judging that any wind turbine generator is normal;
collecting voiceprint data of any wind turbine generator to identify a fault type;
determining the maintenance sequence of any fault wind turbine generator based on the reliability analysis result of the wind power station;
the lubricating oil supply module is used for supplying lubricating oil to any wind turbine generator if the fault type is lubricating oil aging;
The wind power adjustment module is used for predicting a future reliability analysis result of the wind power station according to the wind speed of the future weather forecast and adjusting the wind power station according to the future reliability analysis result of the wind power station.
CN202310569587.7A 2023-05-19 2023-05-19 Wind power station reliability analysis method and system Active CN116523349B (en)

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