CN103758696A - SCADA (supervisory control and data acquisition) temperature parameter based wind turbine set security evaluation method - Google Patents

Abstract

The invention discloses an SCADA (supervisory control and data acquisition) temperature parameter based wind turbine set security evaluation method and belongs to the technical field of equipment security evaluation. The wind turbine set security evaluation method includes: firstly, deciding on an SCADA temperature parameter; then analyzing temperature parameters related to system faults of a wind turbine set, structuring relatedness between operating conditions of the environment temperature as well as wind speed and the SCADA temperature parameter, determining a standard for division of wind turbine set operating conditions, and establishing a standard Gaussian model serving as a reference model for evaluation of the wind turbine set operating conditions; calculating degree of deviation between a curve and the standard model through comparing the standard model with the Gaussian model, and measuring the operating condition of the wind turbine set. By the application of the wind turbine set security evaluation method, monitoring level upon the wind turbine set can be improved, utilization rate of the wind turbine set can be increased, and operation cost can be effectively lowered; a reliable and effective wind turbine set security evaluation mechanism is established, so that deterioration of hidden trouble of the wind turbine set towards faults and accidents is avoided, and an operation circumstance which is secure, stable and efficient is formed for the wind turbine set.

Description

Aerogenerator unit safe status evaluation method based on SCADA temperature parameter

Technical field

The invention belongs to device security status evaluation technical field, be particularly related to a kind of based on SCADA (Supervisory Control And Data Acquisition, data capture and supervisor control) the aerogenerator unit safe status evaluation method of temperature parameter, be processing and the calculating of the temperature data by wind-powered electricity generation unit SCADA is collected specifically, wind-powered electricity generation unit device security situation is evaluated.

Background technique

Wind generating technology is because the feature of its low pollution, environmental protection and sustainable development becomes the main flow energy in world today's new energy development tide.Along with the future development of wind-powered electricity generation unit to large single-machine capacity, the 26S Proteasome Structure and Function of wind-powered electricity generation unit equipment is day by day complicated, wind-powered electricity generation enterprise for normal, the safety of equipment, the requirement of smooth running is more and more higher.The operation and maintenance level that wind-powered electricity generation enterprise must constantly promote unit guarantees that the highly effective and safe of wind-powered electricity generation unit turns round.

Because the cost of wind-powered electricity generation unit is higher, and mounting point is all the area remote, environment is severe, has inconvenient traffic and brought great difficulty to operation and maintenance, and these factors become the obstacle that wind-powered electricity generation industry is pursued the efficient output value.The larger cost of single-machine capacity of wind-powered electricity generation unit is higher, higher to the operation stability requirement of unit, when wind energy turbine set spare part is not enough, once there is the shutdown that unit fault tends to cause unit, causes certain economic loss.Under this background, how to utilize the evaluation of effective monitoring of equipment technology, signal processing technology and data mining technology implementation wind-powered electricity generation unit equipment health status, scenting a hidden danger early, prevent that hidden danger from developing into fault and accident, and adjust operation and arrangement maintenance in advance, become focus and technological difficulties that wind-powered electricity generation industry is paid close attention to.

The condition monitoring and fault diagnosis that develops into wind-powered electricity generation unit of vibration monitoring and acoustic monitoring technology provides effective technical basis, but vibration monitoring often need to install vibration monitoring measuring point additional on wind-powered electricity generation unit, virtually increased the O&M cost of wind-powered electricity generation unit, and the method for off-line monitoring is often used in acoustic monitoring, be difficult to realize the on-line operation state evaluation of wind-powered electricity generation unit.Under this background, numerous research institutions and scholar start to focus on the research of SCADA data, by the deep research SCADA data of data digging method and the relevance between operating states of the units, thereby the stable degree that reflects unit by SCADA data mining Output rusults, wherein temperature parameter is often closely bound up with the operation conditions of unit typical components as most important performance parameter in SCADA data, pitch motor temperature for example, gear case oil liquid temp, the parameters such as bearing temperature are often with pitch motor, the running state of gear-box and each bearing of unit is closely related.The present invention intends analyzing by unique SCADA data probability statistics and data digging method the abnormal conditions of SCADA data, thus the operation conditions of each parts of reflection wind-powered electricity generation unit.What the present invention built whereby is a kind of evaluating method of the wind-powered electricity generation unit on-line operation situation based on SCADA data digging method, and advantage is additionally not increase under the prerequisite of monitoring equipment, realizes the on-line operation safety evaluation of unit.

Summary of the invention

The object of the invention is to propose a kind of aerogenerator unit safe status evaluation method based on SCADA temperature parameter, it is characterized in that, comprise the steps:

1) carry out the selected of SCADA temperature parameter;

2) analyze the temperature parameter being associated with each system failure of wind-powered electricity generation unit, build and comprise the duty parameter of ambient temperature and wind speed and the relevance between SCADA temperature parameter, determine the standard that unit operation operating mode is divided;

3) according to above-mentioned steps 2) duty parameter and the relevance between SCADA temperature parameter, the invariance curve between matching duty parameter and SCADA temperature parameter, and reject " abnormity point ";

4) according to above-mentioned steps 3) in the invariance curve characteristic of matching, based on intending analysis temperature parameter, formulate rational operating conditions interval division criterion;

5) the SCADA temperature data when training at least one annual unit normally to move, carries out probability density curve matching to the temperature parameter in divided working status interval, and the Gauss model of Criterion, as the reference model of evaluating unit operation situation;

6) for what evaluate SCADA temperature data in the period, carry out probability density matching, the temperature parameter distribution curve constructing, by contrasting with standard Gauss model, the degree of deviation of calculated curve and weinberg salam model, thereby the operation conditions of measurement unit.

The temperature parameter that described step 1) is selected, requires selected temperature parameter to want to reflect the running state of equipment, responsive to the misoperation of equipment; By analysis, specifically choose the gentle box bearing temperature of gear box lubricating oil; Choose generator drive side bearing temperature, generator non-drive side bearing temperature and generator windings temperature, pitch-controlled system is chosen pitch motor temperature.

Described step 2), 3) be that operating conditions based on wind-powered electricity generation unit is different, the temperature parameter of each subtense angle is also different, operating mode is corresponding with temperature; Ambient temperature can affect the basal temperature of equipment; Heat radiation can affect the operating temperature of equipment; And for mechanically operated wind-powered electricity generation unit, the rotating speed of air speed influence unit, and rotating speed height has determined the operating temperature of equipment.Selected temperature parameter and wind speed and ambient temperature are closely related, so selected wind speed and ambient temperature are as the parameter of dividing operating mode.

Described step 4) based on intending analysis temperature parameter, formulate rational operating conditions interval division criterion; According to ambient temperature and two parameters of wind speed, the operating conditions of wind-powered electricity generation unit is segmented:

(1) historical data of ambient temperature is added up, determine maximum temperature T _maxand T _min, according to being not less than T _maxthe multiple of minimum 5 get the upper bound, be not more than T _minthe multiple of maximum 5 take off boundary.Take 5 degrees Celsius as interval, operating conditions is carried out to first step division, establish and be divided into m section;

(2) by ambient temperature, undertaken after operating mode division, then according to wind speed, operating conditions is carried out to second step division.Incision wind speed V with wind-powered electricity generation unit _infor lower bound, with the cut-out wind speed V of wind-powered electricity generation unit _outfor the upper bound, according to IEC standard, can be divided into n traffic coverage,

$n=\frac{V_{\mathrm{out}}-V_{\mathrm{in}}}{0.5}---\left(1\right)$

In formula, n is integer;

Ready-portioned traffic coverage is labeled as to O _ij, i=1 wherein, 2,3 ... m; J=1,2,3 ... n; By above-mentioned operating mode division method, put the sample data under accidental conditions under corresponding operating mode space, each interval censored data is carried out to probability density statistics, meet normal distribution; Its distribution is carried out to matching by Gaussian function, obtain fitting function

$F_{\mathrm{ij}}\left(x\right)=\frac{1}{\sqrt{2\mathrm{\π}}{\mathrm{\σ}}_{\mathrm{ij}}}{e}^{\frac{{(x-{\mathrm{\μ}}_{\mathrm{ij}})}^2}{2{{\mathrm{\σ}}_{\mathrm{ij}}}^2}}---\left(2\right)$

μ in formula _ijand σ _ijfor average and the standard deviation of the interval temperature parameter of corresponding operating mode, as reference value.

The invention has the beneficial effects as follows: wind-powered electricity generation unit device security situation is evaluated, instruct operation and maintenance work, the initial data that the monitored data of the SCADA system that wind-powered electricity generation unit is carried is evaluated as safe condition, the utilization ratio of lifting to wind-powered electricity generation unit monitoring level, raising equipment, effectively reduces operating cost.Foundation is reliable, effectively wind-powered electricity generation unit device security status evaluation is machine-processed, has avoided the deterioration of unit hidden danger to fault and accident, has formed aerogenerator unit safe, stable, efficient operating environment.

Accompanying drawing explanation

Fig. 1 divides and the aerogenerator unit safe situation of temperature parameter probability density curve fitness bias degree calculating and the association analysis result between parameter based on operating conditions;

Fig. 2 is the flow chart for the running of wind generating set the evaluation of the safe status method of calculating based on temperature parameter probability density curve fitness bias degree.

Embodiment

Selecting of step 1 SCADA temperature parameter

The aerogenerator unit safe status evaluation method of analyzing based on temperature parameter, requires selected temperature parameter to want to reflect the running state of equipment, responsive to the misoperation of equipment; By analysis, choose the gentle box bearing temperature of gear box lubricating oil; Choose generator drive side bearing temperature, generator non-drive side bearing temperature and generator windings temperature, pitch-controlled system is chosen pitch motor temperature (as shown in Figure 1).

The duty parameter that step 2 analysis is associated with selected SCADA temperature parameter

The operating conditions of wind-powered electricity generation unit is different, and the temperature parameter of each subtense angle is also different, and operating mode is corresponding with temperature; Ambient temperature can affect the basal temperature of equipment; Heat radiation can affect the operating temperature of equipment; And for mechanically operated wind-powered electricity generation unit, the rotating speed of air speed influence unit, and rotating speed height has determined the operating temperature of equipment.Selected temperature parameter and wind speed and ambient temperature are closely related, so selected wind speed and ambient temperature are as the parameter of dividing operating mode.

Step 3 is removed zero power point and singular point, sets up normal operating condition sample

In the service data of wind-powered electricity generation unit; comprising that unit is not worked, cancel closedown and singular value data point; these data are not the data of unit while normally moving; can exert an influence to the reliability of result; during sample data under setting up wind-powered electricity generation unit normal running (operation) conditions, reject above-mentioned data.

The determination methods of the idle data point of unit is to be greater than incision during wind speed when wind speed, and output power is still 0 or the point of negative value; Wind-powered electricity generation unit more than incision wind speed, the following power of cut-out wind speed from normal value be reduced to 0 or the point of negative value be the cancel closedown point of wind-powered electricity generation unit; delete the point (in wind-powered electricity generation unit historical data base, data are the mean value of 10 minute datas, delete three points and are about the data of 30 minutes) of these points and first three stopping process.In like manner, more than incision wind speed, wind-powered electricity generation unit output power by 0 or negative value cumulative be added on the occasion of process be startup more than wind-powered electricity generation unit incision wind speed, delete the point of these points and rear three start-up courses; Abnormal data in singular point index strong point in data, may be because the reasons such as sensor fault, communication abnormality produce, and should be removed.With reference to the Bin method in IEC standard, wind speed range is divided into some intervals (Bin), the integral multiple that the central value of each Bin is 0.5m/s according to 0.5m/s interval.Calculate average value mu and the standard deviation sigma of each interval temperature data, for being less than μ-3 σ, can be used as singular point removal with the data point that is greater than μ+3 σ.By these processing, substantially deleted the data point larger to analyzing influence, can think that remaining data are the historical data under wind-powered electricity generation unit normal running (operation) conditions.

Collect every typhoon group of motors 1 year or above SCADA service data, reject that unit is not worked, cancel closedown and singular value data point, foundation can reflect the sample of normal operating condition of unit.

Step 4 subdividing running operating mode

As shown in Figure 2, because selected temperature parameter is relevant with two duty parameters of ambient temperature to wind speed, so the present invention segments the operating conditions of wind-powered electricity generation unit according to ambient temperature and two parameters of wind speed:

(1) historical data of ambient temperature is added up, determine maximum temperature T _maxand T _min, according to being not less than T _maxthe multiple of minimum 5 get the upper bound, be not more than T _minthe multiple of maximum 5 take off boundary.Take 5 degrees Celsius as interval, operating conditions is carried out to first step division, establish and be divided into m section.

(2) by ambient temperature, undertaken after operating mode division, then according to wind speed, operating conditions is carried out to second step division.Incision wind speed V with wind-powered electricity generation unit _infor lower bound, with the cut-out wind speed V of wind-powered electricity generation unit _outfor the upper bound, according to IEC standard, can be divided into n traffic coverage.

$n=\frac{V_{\mathrm{out}}-V_{\mathrm{in}}}{0.5}---\left(1\right)$

In formula, n is integer.

Ready-portioned traffic coverage is labeled as to O _ij, (i=1,2,3 ... m; J=1,2,3 ... n) by above-mentioned operating mode division method, put the sample data under accidental conditions under corresponding operating mode space, each interval censored data is carried out to probability density statistics, meet normal distribution.Its distribution is carried out to matching by Gaussian function, obtain fitting function

$F_{\mathrm{ij}}\left(x\right)=\frac{1}{\sqrt{2\mathrm{\π}}{\mathrm{\σ}}_{\mathrm{ij}}}{e}^{\frac{{(x-{\mathrm{\μ}}_{\mathrm{ij}})}^2}{2{{\mathrm{\σ}}_{\mathrm{ij}}}^2}}---\left(2\right)$

μ in formula _ijand σ _ijfor average and the standard deviation of the interval temperature parameter of corresponding operating mode, as reference value.

The corresponding relation of setting up according to SCADA temperature parameter and machine set system, utilize good operating unit 1 year or above SCADA temperature data respectively each system representation temperature ginseng to be carried out to probability density statistical analysis, set up the Gaussian distribution model of SCADA temperature parameter by stages in each correlation model, and simulate standard Gaussian distribution curve, as weighing the whether well reference value of operation of machine set system, can set up respectively the standard evaluation curve of pitch-controlled system, gearbox system, generator system.

Step 5 is calculated total deviation degree C

Unit actual operating data (at least one month or more than) is divided into corresponding operating mode by step 4 interval, draw probability density distribution figure and the probability density curve of each interval early warning temperature data, and calculate the Gauss model fitting function G of each interval probability density profile _ij(x).Define this interval fitting degree of deviation C _ij

$G_{\mathrm{ij}}=\underset{-\∞}{\overset{+\∞}{\∫}}|G_{\mathrm{ij}}\left(x\right)-F_{\mathrm{ij}}\left(x\right)|\mathrm{dx}---\left(3\right)$

Calculate the actual operating data distribution of all traffic coverages and the degree of deviation of weinberg salam model, then for all traffic coverages, calculate total deviation degree C

$C=\underset{i=1,j=1}{\overset{i=m,j=n}{\mathrm{\Σ}}}{P}_{\mathrm{ij}}{C}_{\mathrm{ij}}---\left(4\right)$

In formula, Pij is the percentage of data point in interval Oij, by following formula, is tried to achieve

$P_{\mathrm{ij}}=\frac{N_{\mathrm{ij}}}{N}---\left(5\right)$

N in formula _ijfor dropping on interval O _ijinterior data point number, N is data point sum.

From equation (3), can show that wind-powered electricity generation unit is healthy when C ≈ 0, when C>0, wind turbine is departing from normal running state, and health status is degenerated.And health status is degenerated more serious, the value of C trends towards larger.Can judge intuitively by the size of C value the safe condition of wind-powered electricity generation unit equipment.

According to the scheme proposing in step 5, each machine set system model is carried out to unit operation evaluation, evaluation cycle data are at least the data of month, be every month the temperature parameter in the pitch-controlled system of wind-powered electricity generation unit, gearbox system and generator system to be carried out to evaluation analysis, each monthly matching total deviation to pitch-controlled system, gearbox system and generator system is evaluated, the security of operation state of each system of judgement wind-powered electricity generation unit.

Claims (4)

1. the aerogenerator unit safe status evaluation method based on SCADA temperature parameter, is characterized in that, comprises the steps:

1) carry out the selected of SCADA temperature parameter;

2) analyze the temperature parameter being associated with each system failure of wind-powered electricity generation unit, build and comprise the duty parameter of ambient temperature and wind speed and the relevance between SCADA temperature parameter, determine the standard that unit operation operating mode is divided;

3) according to above-mentioned steps 2) duty parameter and the relevance between SCADA temperature parameter, the invariance curve between matching duty parameter and SCADA temperature parameter, and reject " abnormity point ";

4) according to above-mentioned steps 3) in the invariance curve characteristic of matching, based on intending analysis temperature parameter, formulate rational operating conditions interval division criterion;

5) the SCADA temperature data when training at least one annual unit normally to move, carries out probability density curve matching to the temperature parameter in divided working status interval, and the Gauss model of Criterion, as the reference model of evaluating unit operation situation;

6) for what evaluate SCADA temperature data in the period, carry out probability density matching, the temperature parameter distribution curve constructing, by contrasting with standard Gauss model, the degree of deviation of calculated curve and weinberg salam model, thereby the operation conditions of measurement unit.

2. the aerogenerator unit safe status evaluation method based on SCADA temperature parameter according to claim 1, it is characterized in that, the temperature parameter that described step 1) is selected, requires selected temperature parameter to want to reflect the running state of equipment, responsive to the misoperation of equipment; By analysis, specifically choose the gentle box bearing temperature of gear box lubricating oil; Choose generator drive side bearing temperature, generator non-drive side bearing temperature and generator windings temperature, pitch-controlled system is chosen pitch motor temperature.

3. the aerogenerator unit safe status evaluation method based on SCADA temperature parameter according to claim 1, it is characterized in that, described step 2), 3) be that operating conditions based on wind-powered electricity generation unit is different, the temperature parameter of each subtense angle is also different, operating mode is corresponding with temperature; Ambient temperature can affect the basal temperature of equipment; Heat radiation can affect the operating temperature of equipment; And for mechanically operated wind-powered electricity generation unit, the rotating speed of air speed influence unit, and rotating speed height has determined the operating temperature of equipment.Selected temperature parameter and wind speed and ambient temperature are closely related, so selected wind speed and ambient temperature are as the parameter of dividing operating mode.

4. the aerogenerator unit safe status evaluation method based on SCADA temperature parameter according to claim 1, is characterized in that, described step 4) based on intending analysis temperature parameter, formulate rational operating conditions interval division criterion; According to ambient temperature and two parameters of wind speed, the operating conditions of wind-powered electricity generation unit is segmented:

(1) historical data of ambient temperature is added up, determine maximum temperature T _maxand T _min, according to being not less than T _maxthe multiple of minimum 5 get the upper bound, be not more than T _minthe multiple of maximum 5 take off boundary.Take 5 degrees Celsius as interval, operating conditions is carried out to first step division, establish and be divided into m section;

(2) by ambient temperature, undertaken after operating mode division, then according to wind speed, operating conditions is carried out to second step division.Incision wind speed V with wind-powered electricity generation unit _infor lower bound, with the cut-out wind speed V of wind-powered electricity generation unit _outfor the upper bound, according to IEC standard, can be divided into n traffic coverage,

$n=\frac{V_{\mathrm{out}}-V_{\mathrm{in}}}{0.5}---\left(1\right)$

In formula, n is integer;

Ready-portioned traffic coverage is labeled as to O _ij, i=1 wherein, 2,3 ... m; J=1,2,3 ... n; By above-mentioned operating mode division method, put the sample data under accidental conditions under corresponding operating mode space, each interval censored data is carried out to probability density statistics, meet normal distribution; Its distribution is carried out to matching by Gaussian function, obtain fitting function

$F_{\mathrm{ij}}\left(x\right)=\frac{1}{\sqrt{2\mathrm{\π}}{\mathrm{\σ}}_{\mathrm{ij}}}{e}^{\frac{{(x-{\mathrm{\μ}}_{\mathrm{ij}})}^2}{2{{\mathrm{\σ}}_{\mathrm{ij}}}^2}}---\left(2\right)$

μ in formula _ijand σ _ijfor average and the standard deviation of the interval temperature parameter of corresponding operating mode, as reference value.

Images