CN105654239A - Method, device and system for identifying extreme wind condition of wind generating set - Google Patents
Method, device and system for identifying extreme wind condition of wind generating set Download PDFInfo
- Publication number
- CN105654239A CN105654239A CN201511021277.3A CN201511021277A CN105654239A CN 105654239 A CN105654239 A CN 105654239A CN 201511021277 A CN201511021277 A CN 201511021277A CN 105654239 A CN105654239 A CN 105654239A
- Authority
- CN
- China
- Prior art keywords
- wind
- generating set
- power generating
- wind power
- regime
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 45
- 238000011217 control strategy Methods 0.000 claims abstract description 15
- 238000012806 monitoring device Methods 0.000 claims description 8
- 238000001914 filtration Methods 0.000 claims description 7
- 238000012545 processing Methods 0.000 claims description 6
- 238000009499 grossing Methods 0.000 claims description 4
- 238000012360 testing method Methods 0.000 abstract description 6
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 12
- 238000010586 diagram Methods 0.000 description 12
- 230000006870 function Effects 0.000 description 9
- 229910052742 iron Inorganic materials 0.000 description 6
- 230000000875 corresponding effect Effects 0.000 description 5
- 238000004364 calculation method Methods 0.000 description 3
- 238000012887 quadratic function Methods 0.000 description 3
- 238000013461 design Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 238000012546 transfer Methods 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 210000003127 knee Anatomy 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
- 230000001052 transient effect Effects 0.000 description 1
- 230000003245 working effect Effects 0.000 description 1
Classifications
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Educational Administration (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Development Economics (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Wind Motors (AREA)
Abstract
The embodiment of the invention provides a method, a device and a system for identifying extreme wind conditions of a wind generating set, wherein the method comprises the following steps: acquiring the external real-time wind speed of the wind generating set; and determining whether the wind generating set is in an extreme wind condition or not according to the change of the real-time wind speed in the preset time and a change threshold value. According to the method, the device and the system for identifying the extreme wind condition of the wind generating set, provided by the embodiment of the invention, whether the wind generating set is in the extreme wind condition or not is determined according to the change and the change threshold of the external real-time wind speed within the preset time, no expensive test equipment is required to be added, the algorithm is simple, and the real-time performance is high; whether the wind generating set is in an extreme wind condition or not can be effectively identified, and sufficient time is provided for adjusting the control strategy of the wind generating set.
Description
Technical field
The present invention relates to the wind regime processing technology field of wind power generating set, particularly relate to a kind of recognition methods for the extreme wind regime of wind power generating set, Apparatus and system.
Background technology
Wind power generating set likely experiences the harm of extreme wind regime, extreme wind regime includes but not limited to extremely run fitful wind (ExtremeOperatingGust, EOG), the limit continues fitful wind (ExtremeCoherentGust, ECG) or typhoon etc. Protecting or making wind power generating set continue normal operation under the prerequisite ensureing wind power generating set safety wind power generating set under extreme wind regime; depending on and to identify extreme wind regime how effectively and timely, this is the key of the control strategy of adjustment wind power generating set.
The extreme wind regime identification mentioned in existing patent or non-patent literature or appraisal procedure mostly are and adopt expensive testing apparatus such as laser radar apparatus, or use complicated statistical variable and carry out characteristic matching such as average statistic and covariance statistic etc. Therefore, add the design cost of unit or algorithm too complexity cause unit allocation device computational load to strengthen.
Summary of the invention
It is an object of the invention to provide a kind of recognition methods for the extreme wind regime of wind power generating set, Apparatus and system, algorithm is simple, real-time height.
According to an aspect of the present invention, the present invention provides a kind of recognition methods for the extreme wind regime of wind power generating set, and described method comprises: the outside wind speed in real time obtaining described wind power generating set; According to the change of described real-time wind speed within the default time and change threshold, it is determined that whether described wind power generating set is in extreme wind regime.
Further, described according to the change of described real-time wind speed within the default time and change threshold, it is determined that whether described wind power generating set is in extreme wind regime comprises: the sum of squares sequence obtaining described real-time wind speed in the first statistics cycle; Obtain the increase multiple of described sum of squares sequence in the 2nd statistics cycle; When described increase multiple is greater than multiple threshold value, it is determined that described wind power generating set is in the first extreme wind regime.
Further, according to:
Calculate described multiple threshold value f (vwind_speed), wherein, vwind_speedFor the outside wind speed in real time of described wind power generating set, a, b, c, d, e, xlowAnd xhighFor constant, xhighIt is greater than xlow, a is greater than e;And/or, according to:
Calculate described multiple threshold value f (vwind_speed), wherein, vwind_speedFor the outside wind speed in real time of described wind power generating set, f, g, h, i, xlowAnd xhighFor constant, xhighIt is greater than xlow, f is greater than i.
Further, described according to the change of described real-time wind speed within the default time and change threshold, it is determined that whether described wind power generating set is in extreme wind regime comprises: the rate of change obtaining described real-time wind speed in the 3rd statistics cycle; When described rate of change is greater than rate variation threshold value, it is determined that described wind power generating set is in the 2nd extreme wind regime.
Further, described rate variation threshold value is 1.5m/s2��
Further, described method also comprises: when determining that described wind power generating set is in extreme wind regime, according to the initial wind speed in the described default time and the control strategy terminating wind power generating set described in air rate adjustment.
Further, described method also comprises: the record being in extreme wind regime according to described wind power generating set, it is determined that the assessment report of the described wind power generating set place extreme wind regime of wind energy turbine set.
According to a further aspect in the invention, the present invention also provides a kind of means of identification for the extreme wind regime of wind power generating set, and described device comprises: wind speed acquiring unit, for obtaining the outside wind speed in real time of described wind power generating set; Wind regime determining unit, for according to the change of described real-time wind speed within the default time and change threshold, it is determined that whether described wind power generating set is in extreme wind regime.
Further, described wind regime determining unit comprises: sum of squares retrieval subelement, for obtaining the sum of squares sequence of described real-time wind speed in the first statistics cycle; Multiple obtains subelement, for obtaining the increase multiple of described sum of squares sequence in the 2nd statistics cycle; First wind regime determines subelement, for when described increase multiple is greater than multiple threshold value, it is determined that described wind power generating set is in the first extreme wind regime.
Further, described wind regime determining unit also comprises:
First multiple threshold value obtains subelement, for basis:
Calculate described multiple threshold value f (vwind_speed), wherein, vwind_speedFor the outside wind speed in real time of described wind power generating set, a, b, c, d, e, xlowAnd xhighFor constant, xhighIt is greater than xlow, a is greater than e;
2nd multiple threshold value obtains subelement, for basis:
Calculate described multiple threshold value f (vwind_speed), wherein, vwind_speedFor the outside wind speed in real time of described wind power generating set, f, g, h, i, xlowAnd xhighFor constant, xhighIt is greater than xlow, f is greater than i.
Further, described wind regime determining unit comprises: rate of change obtains subelement, for obtaining the rate of change of described real-time wind speed in the 3rd statistics cycle; 2nd wind regime determines subelement, for when described rate of change is greater than rate variation threshold value, it is determined that described wind power generating set is in the 2nd extreme wind regime.
Further, described rate variation threshold value is 1.5m/s2��
Further, described device also comprises: policy control unit, for when determining that described wind power generating set is in extreme wind regime, according to the initial wind speed in the described default time and the control strategy terminating wind power generating set described in air rate adjustment.
Further, described device also comprises: extreme wind regime assessment unit, for being in the record of extreme wind regime according to described wind power generating set, it is determined that the assessment report of the described wind power generating set place extreme wind regime of wind energy turbine set.
Further, the described means of identification for the extreme wind regime of wind power generating set is integrated in the principal controller of described wind power generating set, and/or, the described control device for wind power generating set is integrated in the main control PLC of described wind power generating set.
According to another aspect of the invention, the present invention also provides a kind of recognition system for the extreme wind regime of wind power generating set, the foregoing means of identification for the extreme wind regime of wind power generating set that described system comprises wind speed measuring device and is connected with described wind speed measuring device, described means of identification obtains the outside wind speed in real time of described wind power generating set by described wind speed measuring device.
Further, described wind speed measuring device comprises: instantaneous air monitoring device, Filter and Filltering data buffer storage; Described instantaneous air monitoring device is for measuring the extraneous instantaneous wind velocity signal of described wind power generating set; Described wave filter is for carrying out smoothing processing to the instantaneous wind velocity signal in the described external world; Described filtering data buffer storage is used for the instantaneous wind velocity signal in the filtered external world of buffer memory.
The recognition methods for the extreme wind regime of wind power generating set of embodiment of the present invention offer, Apparatus and system, according to the change of the real-time wind speed in outside within the default time and change threshold, determine whether described wind power generating set is in extreme wind regime, without the need to adding expensive testing apparatus, and algorithm is simple, real-time height; Can effectively identify whether wind power generating set is in extreme wind regime, and the time of the control strategy adjustment offer abundance for wind power generating set.
Accompanying drawing explanation
Fig. 1 is a kind of recognition methods schema for the extreme wind regime of wind power generating set illustrating exemplary embodiment of the present one;
Fig. 2 is the structure iron of the wind speed measuring device illustrated in exemplary embodiment of the present one;
Fig. 3 is the instantaneous wind velocity signal filter curve schematic diagram illustrating in exemplary embodiment of the present one;
Fig. 4 is the schematic diagram illustrating EOG wind regime;
Fig. 5 is the schematic diagram illustrating ECG wind regime;
Fig. 6 is a kind of recognition methods schema for the extreme wind regime of wind power generating set illustrating exemplary embodiment of the present two;
Fig. 7 is a kind of function curve schematic diagram illustrating and identifying EOG wind regime step medium multiple threshold value and wind speed in exemplary embodiment of the present two;
Fig. 8 is another kind of function curve schematic diagram illustrating and identifying EOG wind regime step medium multiple threshold value and wind speed in exemplary embodiment of the present two;
Fig. 9 is another the function curve schematic diagram illustrating and identifying EOG wind regime step medium multiple threshold value and wind speed in exemplary embodiment of the present two;
Figure 10 is a kind of means of identification structure iron one for the extreme wind regime of wind power generating set illustrating exemplary embodiment of the present three;
Figure 11 is a kind of means of identification structure iron two for the extreme wind regime of wind power generating set illustrating exemplary embodiment of the present three.
Embodiment
Below in conjunction with accompanying drawing, the recognition methods for the extreme wind regime of wind power generating set, the Apparatus and system of exemplary embodiment of the present are described in detail.
Embodiment one
Fig. 1 is a kind of recognition methods schema for the extreme wind regime of wind power generating set illustrating exemplary embodiment of the present one.
With reference to Fig. 1, the recognition methods for the extreme wind regime of wind power generating set of exemplary embodiment one comprises step S110 and step S120.
In step S110, obtain the outside wind speed in real time of wind power generating set.
Fig. 2 is the structure iron of the wind speed measuring device illustrated in exemplary embodiment of the present one.
In the present embodiment, it is possible to obtained the outside wind speed in real time of wind power generating set by the wind speed measuring device shown in Fig. 2. With reference to Fig. 2, wind speed measuring device can include but not limited to instantaneous air monitoring device 201 and wave filter 202, wherein, instantaneous air monitoring device 201 can comprise anemoscope and data gathering and transfer equipment, except anemoscope can also adopt other can the device of measuring wind;The parameter of wave filter can be different according to the outside atmosphere difference of concrete wind power generating set, such as, wind power generating set is in mountain valley or is in lakeside etc., the principle that wave filter is chosen is that instantaneous wind velocity signal carries out smoothing processing to external world, but can not significantly change the fluctuation of extraneous instantaneous wind velocity signal, in the present embodiment, time constant is adopted to be the low-pass first order filter of 16.
Fig. 3 is the instantaneous wind velocity signal filter curve schematic diagram illustrating in exemplary embodiment of the present one. In the present embodiment, anemoscope is sent to wave filter 202 after the extraneous instantaneous wind speed measured is carried out signal processing by data gathering and transfer equipment. With reference to Fig. 3, owing to the extraneous instantaneous wind velocity signal 301 obtained often exists trickle burr, therefore optionally, adopt in the present embodiment time constant be 16 low-pass first order filter to external world instantaneous wind velocity signal 301 carry out filtering and obtain real-time wind velocity signal 302.
Optionally, wind speed measuring device can also comprise filtering data buffer storage 203, and filtered real-time wind speed is sent to filtering data buffer storage 203 by wave filter 202. Filtering data buffer storage 203 adopts efficient data buffer memory mechanism to complete the buffer memory of K number of seconds certificate, for step S120 determines whether wind power generating set is in extreme wind regime and provides data encasement.
In step S120, according to the change of real-time wind speed within the default time and change threshold, it is determined that whether wind power generating set is in extreme wind regime.
Wind regime residing for wind power generating set comprises normal wind regime and extreme wind regime, and extreme wind regime is divided into 1 year reoccurrence period and 50 year reoccurrence period. Wind regime is often referred to an average constant air flow rate merged. The extreme wind regime referred in the present embodiment includes but not limited to Germany Lloyd's (GermanischerLoyd, GL) the extreme wind regime of regulation, International Electrotechnical Commission (InternationalElectrotechnicalCommission in the GL2010 standard that renewable energy resources authentication department issues, IEC) the extreme wind regime etc. of regulation in the wind power generating set specification that the extreme wind regime specified in standard or China Classification Society issue, also comprises wind speed rapid increase and energy continues to increase the wind regime that wind power generating set operation may cause damage. Fig. 4 is the schematic diagram illustrating EOG wind regime, and Fig. 5 is the schematic diagram illustrating ECG wind regime. Such as, the EOG wind regime (see Fig. 4) met for 50 years one and ECG wind regime (see Fig. 5), or the limit of wind vector continues fitful wind (ExtremeCoherentgustwithDirectionchange, and extreme wind vector (ExtremeDirectionChange, EDC) wind etc. ECD).
The recognition methods for the extreme wind regime of wind power generating set that the embodiment of the present invention provides, according to the change of the real-time wind speed in outside within the default time and change threshold, determine whether this wind power generating set is in extreme wind regime, it is not necessary to add expensive testing apparatus, and algorithm is simple, real-time height; Can effectively identify whether wind power generating set is in extreme wind regime, and the time of the control strategy adjustment offer abundance for wind power generating set.
Embodiment two
Fig. 6 is a kind of recognition methods schema for the extreme wind regime of wind power generating set illustrating exemplary embodiment of the present two.
The recognition methods for the extreme wind regime of wind power generating set disclosed in the present embodiment comprises the step S110 in the corresponding embodiment one of step S610, step S620, step S630 and step S640 are corresponding to the step S120 in embodiment one, or, step S650 and step S660 is corresponding to the step S120 in embodiment one.
Can for the different characteristics of the extreme wind regime of difference, design the method whether different determination wind power generating set is in this extreme wind regime, the present embodiment is only to identify that EOG and ECG is described, for identifying other extreme wind regime, it is possible to being changed by calculation of wind speed under different time (or time period) and different variable quantity, to determine whether wind power generating set is in the principle of extreme wind regime identical.
In step S610, obtain the outside wind speed in real time of described wind power generating set.
In the present embodiment, step S620, step S630 and step S640 can be used for determining whether wind power generating set is in EOG wind regime, and step S650 and step S660 can be used for determining whether wind power generating set (calling unit in the following text) is in ECG wind regime.
In the present embodiment, for the recognition methods of EOG wind regime, by the formula T of aerodynamic momenta=0.5 �� Cq��R3V2It will be seen that aerodynamic moment TaTo square being directly proportional of wind speed V, wherein, �� represents the density of air of unit place external environment, CqRepresenting the torque coefficient of unit, R represents impeller radius, and unit can realize the control to each blade pitch angle by pitch-controlled system, limits wind wheel with this and absorbs distinguished and admirable energy, and then reduces aerodynamic moment. And generator is while completing electric energy conversion, it is possible to the electromagnetism torque T of control generatore. By �� T=Ta-Te, d ��=�� T/J is it will be seen that rotating speed differential and aerodynamic moment TaWith electromagnetic torque TeDifference be correlated with. Whole unit is exactly regulate aerodynamic moment T by becoming oar mechanisma, generator regulate electromagnetic torque TeRealize the rotating speed control of unit. In the present embodiment, it is possible to according to Ta=0.5 �� Cq��R3V2, �� T=Ta-Te, the formulas Extraction such as d ��=�� T/J go out the objective law of rotating speed differential and wind speed square positive correlation and propose extremely to run the recognition methods of fitful wind (ExtremeOperatingGust, EOG) wind regime as follows:
In step S620, obtain the sum of squares sequence of wind speed in real time in the first statistics cycle (being the K second in the present embodiment). This sum of squares sequence can be the vector of certain length.
Such as, the operating frequency of the main control PLC of wind power generating set is 50HZ, 50 data of namely can sampling for every second (sampling in 0.02 second data). The numerical value of 50 real-time wind speed can be obtained for every second, the numerical value of K*50 real-time wind speed can be obtained in the K second, by the numerical value of the real-time wind speed of jth��K*50+j-1 (j is natural number) respectively square after again summation obtain the sum of squares of the real-time wind speed in corresponding j moment, the sum of squares sequence of wind speed in real time in the sum of squares composition K second of the real-time wind speed that each moment is corresponding in the K second.
In step S630, obtaining the increase multiple of this sum of squares sequence in the 2nd statistics cycle (being the T second in the present embodiment), K second and T second are the numerical value of the same order of magnitude.
In the present embodiment, in the 2nd statistics cycle (in the present embodiment for T second), the increase multiple of this sum of squares sequence refers to that the numerical value of last sum of squares of sum of squares sequence in the T second subtracts after the numerical value of first sum of squares again divided by the numerical value of first sum of squares.
In step S640, when this increase multiple is greater than multiple threshold value, it is determined that wind power generating set is in the first extreme wind regime (i.e. EOG wind regime). Multiple threshold value can according to the wind regime feature reasonable adjusting of different wind district, the wind-resources characteristic of different wind energy turbine set, different type of machines, the different wheel hub height of same type, the different impeller diameter of same type, different seats in the plane point.
Fig. 7 is a kind of function curve schematic diagram illustrating and identifying EOG wind regime step medium multiple threshold value and wind speed in exemplary embodiment of the present two.
Optionally, in the present embodiment, see Fig. 7, it is possible to by the multiple threshold value in following formula (1) calculation procedure S640. According to:
Calculate described multiple threshold value f (vwind_speed), wherein, vwind_speedFor the outside wind speed in real time of described wind power generating set, a, b, c, d, e, xlowAnd xhighFor constant, xhighIt is greater than xlow, a is greater than e.
f(vwind_speed) it is a piecewise function, wherein, xlowAnd xhighRepresent segmentation knee value. When wind speed is less than xlowDuring m/s, threshold value is a; When wind speed is greater than xhighDuring m/s, threshold value is e; When wind speed is at xlowM/s and xhighMeeting quadratic function relation time between m/s, in quadratic function, b, c and d are concrete parameter value.
Fig. 8 is another kind of function curve schematic diagram illustrating and identifying EOG wind regime step medium multiple threshold value and wind speed in exemplary embodiment of the present two.
Optionally, when wind speed is at xlowM/s and xhighCan be quadratic function relation time between m/s can also be linear relationship, such as, in the present embodiment, see Fig. 8, it is also possible to by the multiple threshold value in following formula (2) calculation procedure S640. According to:
Calculate described multiple threshold value f (vwind_speed), wherein, vwind_speedFor the outside wind speed in real time of described wind power generating set, f, g, h, i, xlowAnd xhighFor constant, xhighIt is greater than xlow, f is greater than i.
Fig. 9 is another the function curve schematic diagram illustrating and identifying EOG wind regime step medium multiple threshold value and wind speed in exemplary embodiment of the present two.
Optionally, f (vwind_speed) can also be the function expression obtained by any fitting of a curve mode, such as exponential function as shown in Figure 9 etc.
In the present embodiment, the limit being continued to the recognition methods of fitful wind (ExtremeCoherentGust, ECG) wind regime, the feature of ECG wind regime is wind speed change 15m in 10 seconds, and wind speed rate of change is 15/10=1.5m/s2, therefore, in the present embodiment, setting rate variation threshold value is 1.5m/s2And the recognition methods proposing ECG wind regime is as follows:
In step S650, obtain the rate of change of such as, in the 3rd statistics cycle (this statistics cycle can specify in advance, is K second etc.) wind speed in real time.
In step S660, when described rate of change is greater than rate variation threshold value, it is determined that wind power generating set is in the 2nd extreme wind regime (i.e. ECG wind regime).
Rate variation threshold value in the step of the multiple threshold value in the step of above-mentioned identification EOG wind regime and identification ECG wind regime can according to the wind-resources characteristic reasonable adjusting of different wind district, different wind energy turbine set to obtain optimum recognition effect. Optionally, it is also possible to divide according to wind rating, the multiple threshold value/rate variation threshold value of below wind rating and multiple threshold value/rate variation threshold value more than wind rating is set respectively.
In the present embodiment, recognition methods for the extreme wind regime of wind power generating set can also comprise step S670 and step S680.
In step S670, when determining that described wind power generating set is in extreme wind regime, according to the initial wind speed in the described default time and the control strategy terminating wind power generating set described in air rate adjustment.
Wind power generating set occurs that under the initial wind regime that wind speed is less extreme wind regime can cause set engine room acceleration excessive, and pylon and generator all can by damage and fractures to a certain extent. Wind power generating set occurs that under the initial wind regime that wind speed is bigger extreme wind regime can cause the generator of wind power generating set to overrun, thus affects the work-ing life of generator, and reduces the availability of wind power generating set.Therefore, determine wind power generating set when being in extreme wind regime, can according to the initial wind speed in the described default time and the control strategy terminating wind power generating set described in air rate adjustment, how to ensure wind power generating set safety under extreme wind regime or how to maintain wind power generating set to continue generating.
Optionally, it is possible to pre-set, step S640 exports the boolean's amount characterizing wind power generating set and whether being in the determination result of EOG wind regime, for example, it is determined that when wind power generating set is in EOG wind regime, exports high level and represent; If not determining that wind power generating set is in EOG wind regime, exporting lower level and representing.
Optionally, it is possible to pre-set, step S660 exports the boolean's amount characterizing wind power generating set and whether being in the determination result of ECG wind regime, for example, it is determined that when wind power generating set is in ECG wind regime, exports high level and represent; If not determining that wind power generating set is in ECG wind regime, exporting lower level and representing.
By step S640 export characterize wind power generating set whether be in EOG wind regime determination result boolean amount with step S660 export characterize wind power generating set whether be in ECG wind regime determination result boolean amount carry out or logical operation, and the result of logical operation is as the enable signal of the control strategy of the described wind power generating set of adjustment, step S670 is in conjunction with the control strategy of wind power generating set described in this enable signal and the initial wind speed in the default time and termination air rate adjustment, it is achieved to the optimal adjustment of wind power generating set.
In step S680, it is in the record of extreme wind regime according to described wind power generating set, it is determined that the assessment report of the described wind power generating set place extreme wind regime of wind energy turbine set.
When determining that unit is in extreme wind regime, triggering and generate extreme wind regime document data record, such as, record file can record 30s data after triggering before the moment 90s data and triggering the moment. Needing the regular hour owing to generating extreme wind regime document data record, therefore, generating extreme wind regime document data record can perform side by side with step S670, or performs after step S670.
Frequency statistics and the probability analysis of extreme wind regime can be carried out according to the record that wind power generating set is in extreme wind regime, include but not limited to that adding up each seat in the plane point the frequency that the extreme wind regime of which kind of extreme wind regime, each seat in the plane point occurs and probability etc. easily occurs, and determine the assessment report of the extreme wind regime of whole wind energy turbine set according to statistics.
The present embodiment is the enable signal that unit provides the extreme wind regime of reply, unit allocation strategy is changed before making unit have the sufficient time not to be accumulated to the degree being enough to cause harm to unit at extreme wind regime energy, effectively ensure the safety of unit, it is to increase unit adapts to the ability of complicated wind regime.
Embodiment three
Figure 10 is a kind of means of identification structure iron one for the extreme wind regime of wind power generating set illustrating exemplary embodiment of the present three;
Figure 11 is a kind of means of identification structure iron two for the extreme wind regime of wind power generating set illustrating exemplary embodiment of the present three.
The recognition methods for wind power generating set extreme wind regime of a kind of means of identification for the extreme wind regime of wind power generating set disclosed in the present embodiment for performing in embodiment one and embodiment two.
See Figure 10, a kind of means of identification for the extreme wind regime of wind power generating set comprises wind speed acquiring unit 101 and wind regime determining unit 102.
Wind speed acquiring unit 101, for obtaining the outside wind speed in real time of wind power generating set.
Wind regime determining unit 102, for according to the change of real-time wind speed within the default time and change threshold, it is determined that whether wind power generating set is in extreme wind regime.
Further, described wind regime determining unit 102 comprises sum of squares retrieval subelement 1021, multiple obtains subelement 1022 and the first wind regime determines subelement 1023.
Sum of squares retrieval subelement 1021, for obtaining the sum of squares sequence of described real-time wind speed in the first statistics cycle.
Multiple obtains subelement 1022, for obtaining the increase multiple of described sum of squares sequence in the 2nd statistics cycle.
First wind regime determines subelement 1023, for when described increase multiple is greater than multiple threshold value, it is determined that this wind power generating set is in the first extreme wind regime.
Further, wind regime determining unit also comprises the first multiple threshold value and obtains subelement 1024 and the 2nd multiple threshold value acquisition subelement 1025.
First multiple threshold value obtains subelement 1024, for basis:
Calculate described multiple threshold value f (vwind_speed), wherein, vwind_speedFor the outside wind speed in real time of wind power generating set, a, b, c, d, e, xlowAnd xhighFor constant, xhighIt is greater than xlow, a is greater than e;
2nd multiple threshold value obtains subelement 1025, for basis:
Calculate described multiple threshold value f (vwind_speed), wherein, vwind_speedFor the outside wind speed in real time of described wind power generating set, f, g, h, i, xlowAnd xhighFor constant, xhighIt is greater than xlow, f is greater than i.
See Figure 11, optionally, wind regime determining unit 102 can comprise rate of change and obtains subelement 1026 and the 2nd wind regime and determine subelement 1027.
Rate of change obtains subelement 1026, for obtaining the rate of change of described real-time wind speed in the 3rd statistics cycle;
2nd wind regime determines subelement 1027, for when described rate of change is greater than rate variation threshold value, it is determined that wind power generating set is in the 2nd extreme wind regime.
Optionally, described rate variation threshold value is 1.5m/S2��
See Figure 10, further, this device can also comprise policy control unit 103.
Policy control unit 103, for when determining that wind power generating set is in extreme wind regime, according to the initial wind speed in the default time and the control strategy terminating this wind power generating set of air rate adjustment.
See Figure 10, further, this device can also comprise extreme wind regime assessment unit 104.
Extreme wind regime assessment unit 104, for being in the record of extreme wind regime according to wind power generating set, it is determined that the assessment report of this wind power generating set place extreme wind regime of wind energy turbine set.
Optionally, this means of identification being used for the extreme wind regime of wind power generating set is integrated in the principal controller of described wind power generating set.
Optionally, the described control device for wind power generating set is integrated in the main control PLC of described wind power generating set.
The means of identification for the extreme wind regime of wind power generating set that the embodiment of the present invention provides, according to the change of the real-time wind speed in outside within the default time and change threshold, determine whether described wind power generating set is in extreme wind regime, without the need to adding expensive testing apparatus, and algorithm is simple, real-time height; Can effectively identify whether wind power generating set is in extreme wind regime, and the time of the control strategy adjustment offer abundance for wind power generating set.
Embodiment four
A kind of recognition system for the extreme wind regime of wind power generating set that the present embodiment provides, the means of identification for the extreme wind regime of wind power generating set that described system comprises wind speed measuring device and is connected with wind speed measuring device, this means of identification obtains the outside wind speed in real time of wind power generating set by described wind speed measuring device.
Wherein, the wind speed measuring device in the present embodiment is the wind speed measuring device described in embodiment one.
The means of identification for the extreme wind regime of wind power generating set in the present embodiment is the means of identification for the extreme wind regime of wind power generating set described in embodiment three.
Optionally, described wind speed measuring device comprises: instantaneous air monitoring device, Filter and Filltering data buffer storage; Described instantaneous air monitoring device is for measuring the extraneous instantaneous wind velocity signal of described wind power generating set; Described wave filter is for carrying out smoothing processing to the instantaneous wind velocity signal in the described external world; Described filtering data buffer storage is used for the instantaneous wind velocity signal in the filtered external world of buffer memory.
The recognition system for the extreme wind regime of wind power generating set that the embodiment of the present invention provides, according to the change of the real-time wind speed in outside within the default time and change threshold, determine whether described wind power generating set is in extreme wind regime, without the need to adding expensive testing apparatus, and algorithm is simple, real-time height; Can effectively identify whether wind power generating set is in extreme wind regime, and the time of the control strategy adjustment offer abundance for wind power generating set.
The above-mentioned method according to the present invention can at hardware, firmware realizes, or it is implemented as and can be stored in recording medium (such as CDROM, RAM, floppy disk, hard disk or magneto-optic disk) in software or computer code, or be implemented by the original storage of web download in long-range recording medium or non-temporary transient machine computer-readable recording medium and the computer code that will be stored in local recording medium, thus method described here can be stored in use multi-purpose computer, such software processes on the recording medium of application specific processor or able to programme or specialized hardware (such as ASIC or FPGA). it is appreciated that, computer, treater, microprocessor controller or programmable hardware comprise can store or receive software or computer code storage assembly (such as, RAM, ROM, flash memory etc.), when described software or computer code are by computer, treater or hardware access and execution, it is achieved treatment process described here. in addition, when the code for realizing the process shown in this accessed by multi-purpose computer, multi-purpose computer is converted to the special purpose computer for performing the process shown in this by the execution of code.
The above; it is only the specific embodiment of the present invention, but protection scope of the present invention is not limited thereto, any it is familiar with those skilled in the art in the technical scope that the present invention discloses; change can be expected easily or replace, all should be encompassed within protection scope of the present invention. Therefore, protection scope of the present invention should be as the criterion with the protection domain of described claim.
Claims (17)
1. the recognition methods for the extreme wind regime of wind power generating set, it is characterised in that, described method comprises:
Obtain the outside wind speed in real time of described wind power generating set;
According to the change of described real-time wind speed within the default time and change threshold, it is determined that whether described wind power generating set is in extreme wind regime.
2. recognition methods according to claim 1, it is characterised in that, described according to the change of described real-time wind speed within the default time and change threshold, it is determined that whether described wind power generating set is in extreme wind regime comprises:
Obtain the sum of squares sequence of described real-time wind speed in the first statistics cycle;
Obtain the increase multiple of described sum of squares sequence in the 2nd statistics cycle;
When described increase multiple is greater than multiple threshold value, it is determined that described wind power generating set is in the first extreme wind regime.
3. recognition methods according to claim 2, it is characterised in that, according to:
Calculate described multiple threshold value f (vwind_speed), wherein, vwind_speedFor the outside wind speed in real time of described wind power generating set, a, b, c, d, e, xlowAnd xhighFor constant, xhighIt is greater than xlow, a is greater than e;
And/or, according to:
Calculate described multiple threshold value f (vwind_speed), wherein, vwind_speedFor the outside wind speed in real time of described wind power generating set, f, g, h, i, xlowAnd xhighFor constant, xhighIt is greater than xlow, f is greater than i.
4. recognition methods according to claim 1, it is characterised in that, described according to the change of described real-time wind speed within the default time and change threshold, it is determined that whether described wind power generating set is in extreme wind regime comprises:
Obtain the rate of change of described real-time wind speed in the 3rd statistics cycle;
When described rate of change is greater than rate variation threshold value, it is determined that described wind power generating set is in the 2nd extreme wind regime.
5. recognition methods according to claim 4, it is characterised in that, described rate variation threshold value is 1.5m/s2��
6. recognition methods according to the arbitrary item of claim 1 to 5, it is characterised in that, described method also comprises:
When determining that described wind power generating set is in extreme wind regime, according to the initial wind speed in the described default time and the control strategy terminating wind power generating set described in air rate adjustment.
7. recognition methods according to claim 6, it is characterised in that, described method also comprises:
The record of extreme wind regime it is in, it is determined that the assessment report of the described wind power generating set place extreme wind regime of wind energy turbine set according to described wind power generating set.
8. the means of identification for the extreme wind regime of wind power generating set, it is characterised in that, described device comprises:
Wind speed acquiring unit, for obtaining the outside wind speed in real time of described wind power generating set;
Wind regime determining unit, for according to the change of described real-time wind speed within the default time and change threshold, it is determined that whether described wind power generating set is in extreme wind regime.
9. means of identification according to claim 8, it is characterised in that, described wind regime determining unit comprises:
Sum of squares retrieval subelement, for obtaining the sum of squares sequence of described real-time wind speed in the first statistics cycle;
Multiple obtains subelement, for obtaining the increase multiple of described sum of squares sequence in the 2nd statistics cycle;
First wind regime determines subelement, for when described increase multiple is greater than multiple threshold value, it is determined that described wind power generating set is in the first extreme wind regime.
10. means of identification according to claim 9, it is characterised in that, described wind regime determining unit also comprises:
First multiple threshold value obtains subelement, for basis:
Calculate described multiple threshold value f (vwind_speed), wherein, vwind_speedFor the outside wind speed in real time of described wind power generating set, a, b, c, d, e, xlowAnd xhighFor constant, xhighIt is greater than xlow, a is greater than e;
2nd multiple threshold value obtains subelement, for basis:
Calculate described multiple threshold value f (vwind_speed), wherein, vwind_speedFor the outside wind speed in real time of described wind power generating set, f, g, h, i, xlowAnd xhighFor constant, xhighIt is greater than xlow, f is greater than i.
11. means of identification according to claim 8, it is characterised in that, described wind regime determining unit comprises:
Rate of change obtains subelement, for obtaining the rate of change of described real-time wind speed in the 3rd statistics cycle;
2nd wind regime determines subelement, for when described rate of change is greater than rate variation threshold value, it is determined that described wind power generating set is in the 2nd extreme wind regime.
12. means of identification according to claim 11, it is characterised in that, described rate variation threshold value is 1.5m/s2��
13. means of identification according to claim 8, it is characterised in that, described device also comprises:
Policy control unit, for when determining that described wind power generating set is in extreme wind regime, according to the initial wind speed in the described default time and the control strategy terminating wind power generating set described in air rate adjustment.
14. means of identification according to claim 8, it is characterised in that, described device also comprises:
Extreme wind regime assessment unit, for being in the record of extreme wind regime according to described wind power generating set, it is determined that the assessment report of the described wind power generating set place extreme wind regime of wind energy turbine set.
15. means of identification according to the arbitrary item of claim 8 to 14, it is characterized in that, the described means of identification for the extreme wind regime of wind power generating set is integrated in the principal controller of described wind power generating set, and/or, the described control device for wind power generating set is integrated in the main control PLC of described wind power generating set.
16. 1 kinds of recognition systems for the extreme wind regime of wind power generating set, it is characterized in that, the means of identification for the extreme wind regime of wind power generating set as described in item as arbitrary in claim 8 to 15 that described system comprises wind speed measuring device and is connected with described wind speed measuring device, described means of identification obtains the outside wind speed in real time of described wind power generating set by described wind speed measuring device.
17. recognition systems according to claim 16, it is characterised in that, described wind speed measuring device comprises: instantaneous air monitoring device, Filter and Filltering data buffer storage; Described instantaneous air monitoring device is for measuring the extraneous instantaneous wind velocity signal of described wind power generating set; Described wave filter is for carrying out smoothing processing to the instantaneous wind velocity signal in the described external world; Described filtering data buffer storage is used for the instantaneous wind velocity signal in the filtered external world of buffer memory.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201511021277.3A CN105654239B (en) | 2015-12-30 | 2015-12-30 | Method, device and system for identifying extreme wind condition of wind generating set |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201511021277.3A CN105654239B (en) | 2015-12-30 | 2015-12-30 | Method, device and system for identifying extreme wind condition of wind generating set |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105654239A true CN105654239A (en) | 2016-06-08 |
| CN105654239B CN105654239B (en) | 2021-07-20 |
Family
ID=56490099
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201511021277.3A Active CN105654239B (en) | 2015-12-30 | 2015-12-30 | Method, device and system for identifying extreme wind condition of wind generating set |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105654239B (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107944632A (en) * | 2017-12-06 | 2018-04-20 | 北京天润新能投资有限公司 | A kind of wind farm siting system and site selecting method based on exploitation map |
| CN108152528A (en) * | 2016-12-02 | 2018-06-12 | 北京金风科创风电设备有限公司 | Wind measurement method and device |
| CN109813929A (en) * | 2017-11-21 | 2019-05-28 | 北京金风科创风电设备有限公司 | Wind speed measuring method and system of wind driven generator |
| CN112761868A (en) * | 2019-11-05 | 2021-05-07 | 北京金风科创风电设备有限公司 | Wind condition identification method and device, controller and wind generating set |
| CN112943528A (en) * | 2019-11-26 | 2021-06-11 | 新疆金风科技股份有限公司 | Control method and device of wind generating set |
| CN113090455A (en) * | 2021-04-25 | 2021-07-09 | 中国华能集团清洁能源技术研究院有限公司 | Method, system and equipment for controlling pitch angle of wind turbine generator set under condition of power failure of power grid |
| CN113848346A (en) * | 2020-06-28 | 2021-12-28 | 新疆金风科技股份有限公司 | Method, device and equipment for predicting extreme wind condition conditions of wind turbine generator |
| WO2022001251A1 (en) * | 2020-06-29 | 2022-01-06 | 新疆金风科技股份有限公司 | Wind turbine generator system, and control method, controller and control system therefor |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101776695A (en) * | 2010-03-08 | 2010-07-14 | 江苏省电力试验研究院有限公司 | Wind speed and wind direction measuring method for wind power generation system |
| CN103061980A (en) * | 2012-12-28 | 2013-04-24 | 东方电气集团东方汽轮机有限公司 | Feed-forward control system and feed-forward control method for wind generating set based on laser wind finding radar |
| CN103502637A (en) * | 2011-01-18 | 2014-01-08 | 维斯塔斯风力系统集团公司 | Method and apparatus for protecting wind turbines from extreme events |
| CN103597206A (en) * | 2011-05-06 | 2014-02-19 | 维斯塔斯风力系统集团公司 | Method and apparatus for protecting wind turbines from extreme events |
| CN104832368A (en) * | 2015-04-08 | 2015-08-12 | 华北电力大学 | Concentrated wind energy type wind turbine set variable-pitch control method based on power multiplication characteristic |
| CN104915729A (en) * | 2015-05-26 | 2015-09-16 | 中国科学院深圳先进技术研究院 | Method and system for carrying out processing on environment prediction factor data of typhoon intensity |
-
2015
- 2015-12-30 CN CN201511021277.3A patent/CN105654239B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101776695A (en) * | 2010-03-08 | 2010-07-14 | 江苏省电力试验研究院有限公司 | Wind speed and wind direction measuring method for wind power generation system |
| CN103502637A (en) * | 2011-01-18 | 2014-01-08 | 维斯塔斯风力系统集团公司 | Method and apparatus for protecting wind turbines from extreme events |
| CN103597206A (en) * | 2011-05-06 | 2014-02-19 | 维斯塔斯风力系统集团公司 | Method and apparatus for protecting wind turbines from extreme events |
| CN103061980A (en) * | 2012-12-28 | 2013-04-24 | 东方电气集团东方汽轮机有限公司 | Feed-forward control system and feed-forward control method for wind generating set based on laser wind finding radar |
| CN104832368A (en) * | 2015-04-08 | 2015-08-12 | 华北电力大学 | Concentrated wind energy type wind turbine set variable-pitch control method based on power multiplication characteristic |
| CN104915729A (en) * | 2015-05-26 | 2015-09-16 | 中国科学院深圳先进技术研究院 | Method and system for carrying out processing on environment prediction factor data of typhoon intensity |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108152528A (en) * | 2016-12-02 | 2018-06-12 | 北京金风科创风电设备有限公司 | Wind measurement method and device |
| CN108152528B (en) * | 2016-12-02 | 2020-02-14 | 北京金风科创风电设备有限公司 | Wind speed measuring method and device |
| CN109813929A (en) * | 2017-11-21 | 2019-05-28 | 北京金风科创风电设备有限公司 | Wind speed measuring method and system of wind driven generator |
| CN107944632A (en) * | 2017-12-06 | 2018-04-20 | 北京天润新能投资有限公司 | A kind of wind farm siting system and site selecting method based on exploitation map |
| CN112761868A (en) * | 2019-11-05 | 2021-05-07 | 北京金风科创风电设备有限公司 | Wind condition identification method and device, controller and wind generating set |
| CN112943528A (en) * | 2019-11-26 | 2021-06-11 | 新疆金风科技股份有限公司 | Control method and device of wind generating set |
| CN113848346A (en) * | 2020-06-28 | 2021-12-28 | 新疆金风科技股份有限公司 | Method, device and equipment for predicting extreme wind condition conditions of wind turbine generator |
| CN113848346B (en) * | 2020-06-28 | 2024-04-19 | 金风科技股份有限公司 | Method, device and equipment for predicting extreme wind condition of wind turbine |
| WO2022001251A1 (en) * | 2020-06-29 | 2022-01-06 | 新疆金风科技股份有限公司 | Wind turbine generator system, and control method, controller and control system therefor |
| CN113090455A (en) * | 2021-04-25 | 2021-07-09 | 中国华能集团清洁能源技术研究院有限公司 | Method, system and equipment for controlling pitch angle of wind turbine generator set under condition of power failure of power grid |
| CN113090455B (en) * | 2021-04-25 | 2022-05-24 | 中国华能集团清洁能源技术研究院有限公司 | Method, system and equipment for controlling pitch angle of wind turbine generator set under condition of power failure of power grid |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105654239B (en) | 2021-07-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105654239A (en) | Method, device and system for identifying extreme wind condition of wind generating set | |
| CN111306008B (en) | Fan blade detection method, device, equipment and storage medium | |
| CN109447441B (en) | Transient stability risk assessment method considering uncertainty of new energy unit | |
| CN107728059B (en) | Pitch system state evaluation method | |
| CN110905732B (en) | Method and system for identifying unbalance of wind wheel of wind turbine generator and storage medium | |
| CN113285471B (en) | Offshore wind farm subsynchronous oscillation source sensing and positioning method, device and equipment | |
| CN108075437A (en) | A kind of voltage sag source identification method based on wavelet transformation | |
| CN103925155A (en) | Self-adaptive detection method for abnormal wind turbine output power | |
| CN104504285A (en) | Doubly-fed wind power farm equivalent modeling method for crowbar protection | |
| CN111639583A (en) | Method and system for identifying power quality disturbance of power grid | |
| CN105550450B (en) | Electric energy quality interference source characteristic harmonic modeling method | |
| CN110222393A (en) | The fan blade icing method for monitoring abnormality divided based on fine granularity wind-powered electricity generation generating state | |
| CN113689053A (en) | Strong convection weather overhead line power failure prediction method based on random forest | |
| WO2024041409A1 (en) | Method and apparatus for determining representative wind generating set, and control method and apparatus | |
| CN112855458B (en) | Anemometer fault diagnosis method, system and medium for wind generating set | |
| CN113009337A (en) | Interturn short circuit fault identification method for offshore wind power permanent magnet direct drive motor | |
| CN111400959B (en) | Blade fault diagnosis method and device for wind generating set | |
| CN116298509A (en) | Online identification method for harmonic resonance of power system | |
| Zárate et al. | Analysis and detection of erosion in wind turbine blades | |
| CN116975723A (en) | Electrical fire intelligent early warning system based on residual current waveform characteristic quantity | |
| Ma | Novel early warning fault detection for wind-turbine-based DG systems | |
| Ezzaidi et al. | Evaluation of the Energy Performance of the Amougdoul Wind Farm, Morocco. | |
| CN113090471B (en) | Tower clearance audio monitoring system, method and device of wind generating set | |
| CN113848347A (en) | Health state detection method for wind meter of wind driven generator | |
| CN109944749B (en) | Extreme turbulence identification method, device, equipment and computer readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |