CN102570453B - Short-term wind power prediction method and system based on multiple numerical weather prediction sources - Google Patents

Short-term wind power prediction method and system based on multiple numerical weather prediction sources Download PDF

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CN102570453B
CN102570453B CN201210003944.5A CN201210003944A CN102570453B CN 102570453 B CN102570453 B CN 102570453B CN 201210003944 A CN201210003944 A CN 201210003944A CN 102570453 B CN102570453 B CN 102570453B
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wind
data
weather forecast
prediction
numerical weather
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CN201210003944.5A
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CN102570453A (en
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汪宁渤
王定美
马彦宏
刘光途
赵龙
路亮
马明
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甘肃省电力公司风电技术中心
国家电网公司
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Abstract

The invention discloses a short-term wind power prediction method and system based on multiple numerical weather prediction sources, and the method and the system can be applied to ten-million-kilowatt wind power bases in Jiuquan. The method comprises the following steps of: establishing prediction models for wind power plants by applying a physical and statistical combined method; acquiring the numerical weather prediction data of the wind power plants and inputting the numerical weather prediction data into the prediction models; and carrying out prediction processing on the short-term and ultra-short-term wind power contributing situations of the wind power plants based on the input numerical weather prediction data by virtue of the predication models so as to acquire predicted results capable of being applied to power dispatching and the establishment of new prediction models. The short-term wind power prediction method and system based on the multiple numerical weather prediction sources, disclosed by the invention, have the advantages that the defect, in the prior art, that the practical requirements cannot be met due to low prediction accuracy and poor safety and stability can be overcome, and the practical operation in power dispatching can be achieved due to high prediction accuracy, safety in operation and good stability.

Description

Based on short-term wind power forecast method and the system in many cover numerical weather forecast sources
Technical field
The present invention relates to technical field of power systems, particularly, relate to the short-term wind power forecast method based on many cover numerical weather forecast sources and system.
Background technology
Under the background of the day by day exhausted and serious environmental problem of the conventional energy resource such as coal, oil; wind power generation as current in regenerative resource the most ripe, the generation technology most with scale exploit condition and commercialized development prospect of technology; day by day obtain the great attention of country and vigorously support, obtaining develop rapidly in recent years.
Along with the fast development of wind-powered electricity generation, being incorporated into the power networks of Large Scale Wind Farm Integration is also more and more significant on the impact of electrical network.China's wind power base is generally in meagrely-populated area, and load is little, and electric network composition is also relatively weak.The feature of the randomness that wind energy has, intermittence and uncontrollability and in actual motion, the anti-peak-shaving capability that most wind-powered electricity generation has, make that prediction is carried out to the trend of exerting oneself of wind energy turbine set and become difficulty, cause operation of power networks to dispatch difficult and complicated, very large impact is caused on the safe and stable operation of electrical network.
In order to when ensureing power network safety operation, improve wind-powered electricity generation electricity volume, it is necessary for setting up wind-powered electricity generation prediction system.
At present, the history of more than 20 year has been had abroad to the research of wind-powered electricity generation prediction, research unit is the earliest the Risoe National Laboratory of Denmark, Germany also conducts in-depth research subsequently, each wind-powered electricity generation power all appreciates the value and significance of wind-powered electricity generation prediction, have developed the commercial prognoses system of oneself one after another and puts into effect.
As the AWPT forecast system etc. of the Prediktor forecast system in Danish National laboratory, Hispanic LocalPred forecast system and Germany.First Prediktor forecast system utilizes numerical weather prediction model HIRLAM to provide the wind speed profile of wind energy turbine set region, then the wind speed that utilizing WASP to consider the factor such as barrier, roughness change near wind energy turbine set further provides resolution higher forecasts, finally on the basis of the wind speed of forecast, calculates wind energy turbine set wind power by energy output computing module RisPark.
First LocalPred forecast system utilizes high-resolution mesoscale numerical model MM5 or NWP pattern in conjunction with weather forecast fields such as fluid mechanics software calculation of wind speed, by statistical module (MOS), forecast wind speed is revised again, go out force data finally by history and power stage model that the same period, the meteorological field such as wind speed was set up carries out that power forecast.Previento forecast system is corrected wind speed in conjunction with the impact of wind energy turbine set surrounding terrain, roughness of ground surface and heating power layer on the basis utilizing numerical model forecast axial fan hub place height wind speed, carries out power forecast finally by power forecast module.
Wind Power In China power prediction forecast system is in the Primary Study stage, the domestic research of wind power prediction that also had many units to carry out.As Jilin Utilities Electric Co., national grid northwest branch, North China Electric Power University, China Meteorological Administration etc. have all built wind power prediction forecast system.
The height of wind power prediction forecast accuracy, directly affect wind energy utilization efficiency and the economic benefit of each wind energy turbine set, also affecting traffic department makes rational generation schedule simultaneously.Although there have been the wind-powered electricity generation prediction system of preliminarily forming in domestic many units, but reason makes the accuracy of power prediction not high because Forecasting Methodology, data source be single etc., do not reach practical requirement, in addition because the wind-resources of China distributes relatively concentrated geographically, cause external ripe prediction system directly can not be applied in the wind energy turbine set of China.Numerical weather forecast affects wind power forecast accuracy vital factor.
Realizing in process of the present invention, inventor finding at least to exist in prior art that precision of prediction is low, safety and poor stability so that do not reach the defects such as practical requirement.
Summary of the invention
The object of the invention is to, for the problems referred to above, propose the short-term wind power forecast method based on many cover numerical weather forecast sources, precision is high to realize surveying, security of operation and good stability so that can in the advantage of the practical operation of power scheduling.
For achieving the above object, the technical solution used in the present invention is: based on the short-term wind power forecast method in many cover numerical weather forecast sources, comprising:
The forecast model of each wind energy turbine set of method establishment that Applied Physics and statistics combine;
Obtain the numerical weather forecast data of each wind energy turbine set, input described forecast model;
Described forecast model, based on the numerical weather forecast data of input, carries out prediction processing to the wind power output situation of each wind energy turbine set short-term and ultra-short term, obtains and can be applied to power scheduling and set up predicting the outcome of new forecast model.
Further, described operation of setting up the forecast model of each wind energy turbine set comprises:
Obtain at least to comprise and overlap the topography and geomorphology in region and the master data of fan operation state residing for numerical weather forecast, wind energy turbine set history survey wind data, Power Output for Wind Power Field historical data, wind energy turbine set more;
By statistical method, or the method that physical method combines with statistical method, gained master data is processed, obtains the forecast model of each wind energy turbine set.
Further, the operation of the numerical weather forecast data of each wind energy turbine set of described acquisition comprises:
From the server of each service provider of numerical weather forecast, download various places numerical weather forecast;
To gained various places numerical weather forecast, carry out data processing and D/A conversion, obtain each wind energy turbine set prediction period numerical weather forecast;
To gained each wind energy turbine set prediction period numerical weather forecast data, carry out analyzing and weighted calculation, obtain the numerical weather forecast data for input prediction model.
Further, described numerical weather forecast data, at least comprise and obtain air speed data, wind direction data, temperature record, barometric information and humidity data from various places numerical weather forecast.
Further, described forecast model is based on the numerical weather forecast data of input, and the operation wind power output situation of each wind energy turbine set short-term and ultra-short term being carried out to prediction processing comprises:
Described numerical weather forecast data, after the process of NWP system, export rough prediction data;
Based on atmospheric boundary layer dynamics and boundary layer meteorology theory, described rough prediction data is carried out process of refinement, obtains the predicted value under wind energy turbine set actual landform, geomorphologic conditions;
By the prediction of wind speed in described predicted value and wind direction, be converted to wind speed and the wind direction of wind-powered machine unit hub height;
In conjunction with wake effect between Wind turbines, by the wind speed of gained wind-powered machine unit hub height and wind direction, be applied to the power curve of Wind turbines, draw the predicted power of Wind turbines;
The predicted power of all Wind turbines is sued for peace, obtains the predicted power of whole wind energy turbine set, namely obtain predicting the outcome of whole wind energy turbine set.
Further, the above-described short-term wind power forecast method based on many cover numerical weather forecast sources, the method also comprises:
To the described operation stored that predicts the outcome, and/or,
To the described operation shown that predicts the outcome.
Meanwhile, another technical scheme that the present invention adopts is: based on the short-term wind-electricity power prognoses system in many cover numerical weather forecast sources, comprise data of weather forecast collecting unit, EMS system and prediction processing unit, wherein:
Described EMS system, for providing the data setting up each wind energy turbine set forecast model;
Described data of weather forecast collecting unit, for obtaining the numerical weather forecast data of each wind energy turbine set, and input prediction model;
Described prediction processing unit, for the data setting up each wind energy turbine set forecast model provided based on EMS system, sets up forecast model; And, for the numerical weather forecast data that described forecast model inputs based on data of weather forecast collecting unit, prediction processing is carried out to the wind power output situation of each wind energy turbine set short-term and ultra-short term, obtains and can be applied to power scheduling and set up predicting the outcome of new forecast model.
Further, described EMS system, comprises wind energy turbine set real-time information collection module, data dispatch module and EMS system data platform, wherein:
Described wind energy turbine set real-time information collection module, for the server from each service provider of numerical weather forecast, downloads various places numerical weather forecast;
Described EMS system data platform, for gained various places numerical weather forecast, carries out data processing and D/A conversion, obtains each wind energy turbine set prediction period numerical weather forecast; And,
For to gained each wind energy turbine set prediction period numerical weather forecast data, carry out analyzing and weighted calculation, obtain the numerical weather forecast data for input prediction model;
Described data dispatch module, for the data interaction between wind energy turbine set real-time information collection module and EMS system data platform.
Further, described prediction processing unit, comprises NWP processing module and prediction and calculation processor, wherein:
Described NWP processing module, after numerical weather forecast data being processed, exports rough prediction data;
Described prediction and calculation processor, for based on atmospheric boundary layer dynamics and boundary layer meteorology theory, carries out process of refinement by described rough prediction data, obtains the predicted value under wind energy turbine set actual landform, geomorphologic conditions;
By the prediction of wind speed in described predicted value and wind direction, be converted to wind speed and the wind direction of wind-powered machine unit hub height;
In conjunction with wake effect between Wind turbines, by the wind speed of gained wind-powered machine unit hub height and wind direction, be applied to the power curve of Wind turbines, draw the predicted power of Wind turbines;
The predicted power of all Wind turbines is sued for peace, obtains the predicted power of whole wind energy turbine set, namely obtain predicting the outcome of whole wind energy turbine set.
Further. the above-described short-term wind-electricity power prognoses system based on many cover numerical weather forecast sources, also comprises prognoses system database, man-machine interaction unit and communication unit, wherein:
Described prognoses system database, as data center, for store, transfer and upgrade from data of weather forecast collecting unit numerical weather forecast data, send out wind power data and predicting the outcome from prediction processing unit from the reality of EMS system;
Described man-machine interaction unit, for user interactions, complete and at least comprise data and curve display and the operation of system management and maintenance;
Described communication unit, for data of weather forecast collecting unit, EMS system, prediction processing unit and man-machine interaction unit data interaction to each other.
The short-term wind power forecast method based on many cover numerical weather forecast sources of the embodiment of various embodiments of the present invention and system, be applied to ten million kilowatt, Jiuquan wind power base, larger.
The short-term wind power forecast method based on many cover numerical weather forecast sources of various embodiments of the present invention and system, because the method comprises: the forecast model of each wind energy turbine set of method establishment that Applied Physics and statistics combine; Obtain the numerical weather forecast data of each wind energy turbine set, input prediction model; Forecast model, based on the numerical weather forecast data of input, carries out prediction processing to the wind power output situation of each wind energy turbine set short-term and ultra-short term, obtains and can be applied to power scheduling and set up predicting the outcome of new forecast model; Wind power prediction in 72 hours can be realized, be conducive to improving the total specified installed capacity of wind power system; Generation schedule is formulated, send out for electric equilibrium, ensure that power network safety operation has important function, during to solve traffic department's mixing system stand-by power supply, only lean on the historical data of installed capacity of wind-driven power and wind-powered electricity generation electricity volume to estimate the problem of wind power; Thus can overcome that precision of prediction in prior art is low, safety and poor stability so that do not reach the defect of practical requirement, to realize surveying, precision is high, security of operation and good stability so that can in the advantage of the practical operation of power scheduling.
Other features and advantages of the present invention will be set forth in the following description, and, partly become apparent from specification, or understand by implementing the present invention.Object of the present invention and other advantages realize by structure specifically noted in write specification, claims and accompanying drawing and obtain.
Below by drawings and Examples, technical scheme of the present invention is described in further detail.
Accompanying drawing explanation
Accompanying drawing is used to provide a further understanding of the present invention, and forms a part for specification, together with embodiments of the present invention for explaining the present invention, is not construed as limiting the invention.In the accompanying drawings:
Fig. 1 is the schematic flow sheet according to the short-term wind power forecast method that the present invention is based on many cover numerical weather forecast sources;
Fig. 2 is the schematic flow sheet according to the short-term wind power forecast method preferred embodiment that the present invention is based on many cover numerical weather forecast sources;
Fig. 3 is the operation principle schematic diagram according to the short-term wind-electricity power prognoses system that the present invention is based on many cover numerical weather forecast sources;
Fig. 4 is the operation principle schematic diagram according to the short-term wind-electricity power prognoses system preferred embodiment that the present invention is based on many cover numerical weather forecast sources.
By reference to the accompanying drawings, in the embodiment of the present invention, Reference numeral is as follows:
1-data of weather forecast collecting unit; 11-internet module; 12-Europe meteorological observatory numerical weather forecast; 13-Lanzhou meteorological observatory numerical weather forecast; 14-China DianKeYuan numerical weather forecast; 2-man-machine interaction unit; 21-graphic user interface; 22-graphical user interface module; 3-prognoses system database; 31-prognoses system database interface; 32-prognoses system database server; 4-EMS system; 41-wind energy turbine set real-time information collection module; 42-data dispatch module; 43-EMS system data platform; 5-prediction processing unit; 51-NWP processing module; 52-prediction and calculation processor; 6-communication unit; 61-Network Security Device; The 62-network switch.
Embodiment
Below in conjunction with accompanying drawing, the preferred embodiments of the present invention are described, should be appreciated that preferred embodiment described herein is only for instruction and explanation of the present invention, is not intended to limit the present invention.
embodiment of the method
According to the embodiment of the present invention, as depicted in figs. 1 and 2, the short-term wind power forecast method based on many cover numerical weather forecast sources is provided.
As shown in Figure 1, the short-term wind power forecast method based on many cover numerical weather forecast sources of the present embodiment, comprising:
Step 100: the forecast model of each wind energy turbine set of method establishment that Applied Physics and statistics combine;
Step 101: the numerical weather forecast data obtaining each wind energy turbine set, input prediction model;
Step 103: described forecast model, based on the numerical weather forecast data of input, carries out prediction processing to the wind power output situation of each wind energy turbine set short-term and ultra-short term, obtains and can be applied to power scheduling and set up predicting the outcome of new forecast model.
Preferably, as shown in Figure 2, the short-term wind power forecast method based on many cover numerical weather forecast sources of above-described embodiment, specifically comprises:
Step 200: obtain at least to comprise and overlap the topography and geomorphology in region and the master data of fan operation state residing for numerical weather forecast, wind energy turbine set history survey wind data, Power Output for Wind Power Field historical data, wind energy turbine set more;
Step 201: by statistical method, or the method that physical method combines with statistical method, process step 200 gained master data, obtain the forecast model of each wind energy turbine set, performs step 205;
Step 202: from the server of each service provider of numerical weather forecast, downloads various places numerical weather forecast;
Step 203: to step 202 gained various places numerical weather forecast, carries out data processing and D/A conversion, obtains each wind energy turbine set prediction period numerical weather forecast;
Step 204: to step 203 gained each wind energy turbine set prediction period numerical weather forecast data, carry out analyzing and weighted calculation, obtain the numerical weather forecast data for input prediction model, performs step 205; In step 204, numerical weather forecast data, at least comprise and obtain air speed data, wind direction data, temperature record, barometric information and humidity data from various places numerical weather forecast;
Step 205: by the numerical weather forecast data of each for step 204 gained wind energy turbine set, input step 202 gained forecast model;
Step 206: the numerical weather forecast data of input prediction model in step 205, after the process of NWP system, export rough prediction data;
Step 207: based on atmospheric boundary layer dynamics and boundary layer meteorology theory, by prediction data rough for step 206 gained, carry out process of refinement, obtain the predicted value under wind energy turbine set actual landform, geomorphologic conditions;
Step 208: by the prediction of wind speed in step 207 gained predicted value and wind direction, is converted to wind speed and the wind direction of wind-powered machine unit hub height;
Step 209: in conjunction with wake effect between Wind turbines, by the wind speed of step 208 gained wind-powered machine unit hub height and wind direction, is applied to the power curve of Wind turbines, draws the predicted power of Wind turbines;
Step 210: the predicted power of all such as step 209 gained Wind turbines is sued for peace, obtains the predicted power of whole wind energy turbine set, namely obtain predicting the outcome of whole wind energy turbine set.
In step 210, can also predict the outcome to gained store, data and curve display and the operation such as system management and maintenance.
In the above-described embodiments, the data such as the topography and geomorphology that numerical weather forecast is overlapped in utilization more, wind energy turbine set history surveys region residing for wind data, Power Output for Wind Power Field historical data, wind energy turbine set and fan operation state, by the method that statistical method or physics combine with statistics, set up the forecast model of each wind energy turbine set; Again using numerical weather forecast data as the input of forecast model, predict each wind energy turbine set and the whole province's wind power output next day situation.
In the above-described embodiments, when obtaining numerical value data of weather forecast, numerical weather forecast model can be passed through.Numerical weather forecast model is very complicated, and needs a large amount of measured datas, is generally responsible for forecast by National Meteorological Bureau.The horizontal resolution of general global models is that 80 × 80km2 is to 40 × 40km2.Global models drive partial model, and resolution is reduced.Determine that the initial condition of prognoses system needs a large amount of data.The responsible collection data such as a large amount of weather stations, buoy, radar, observation vessel, meteorological satellite and aircraft.World Meteorological Organization has formulated the standard of data format and measuring period.
These data are not observed in the same time and being obtained, and the precision of these data is general all poor than conventional data.Therefore, how utilizing these unconventional observational datas, they and conventional data are cooperated, enriches the information of initial fields, is an important problem.Need to adopt four-dimensional assimilate method not in the same time, different regions, meteorological data of different nature constantly input computer, by certain Forecast Mode, make it to coordinate on power and heating power, obtain the initial fields that quality field and wind field reach balance substantially, be supplied to Forecast Mode and use.Four-dimensional assimilate mainly contains three part compositions, and one is Forecast Mode, and two is objective analyses, and three is initialization.The effect of pattern is that previous data is extrapolated to the current analysis moment; Analysis is combined with current observational data the information of model predictions, is inside inserted on lattice point; Initialization is then filtered by the high frequency gravitational wave in analysis field, ensures the stability calculated.
The numerical weather forecast that current American-European countries uses mainly contains several below.Meso-scale meteorology forecasting centre integrated system, Europe (ECMWF), the T170L42 forecast system that U.S. environment forecasting centre integrated system (NCEP) develops, Japan spectral expansion pattern T213L30, Britain More General Form UM, the Lokal modell model that Meteorological Services mechanism of Germany (DWD) develops, the T213L31 etc. of China national weather bureau exploitation.
The raising that the meteorological element fine forecast (as wind speed, wind direction etc.) of high-spatial and temporal resolution only can not rely on numerical model resolution obtains.This is because on the one hand by the restriction of computing power, on the other hand, too high resolution can make the uncertainty of data and pattern itself be amplified, and even can run counter to desire.So in this case, the numerical forecasting product that using forestland exports adds the forecast result that statistics or artificial intelligence technology just can obtain high-resolution.
In the above-described embodiments, the physical method of wind power prediction, mainly based on atmospheric boundary layer dynamics and boundary layer meteorology theory, rough prediction data NWP system exported is meticulous turns to wind energy turbine set actual landform, predicted value under geomorphologic conditions, and by prediction of wind speed, wind direction is converted to the wind speed of wind-powered machine unit hub height, wind direction, between consideration Wind turbines after wake effect, again prediction of wind speed is applied to the power curve of Wind turbines, draw the predicted power of Wind turbines thus, finally, the predicted power of all Wind turbines is sued for peace, obtain the predicted power of whole wind energy turbine set.
The Output rusults of roughness variation model and topography variation model is the speedup factor (relief model also exports the wind deflection relative to upwind) of the not disturbed wind speed of upwind for research range edge (being 10km) herein, therefore, when the application speedup factor calculates the disturbance of wind energy turbine set roughness and topography variation stream field, first need to determine the not disturbed wind speed of upwind, wind direction, and in order to realize the prediction to hub height wind speed, wind direction, NWP wind speed, wind direction and with reference to wind speed, the contacting of wind direction must be set up again.The geostrophic wind Chang Zuowei of reflection large scale variations in flow contacts the bridge of diverse location wind speed, wind direction in boundary layer, and towing law can be turned by ground and set up contacting of geostrophic wind and ground layer characteristic quantity, and ground turns towing law and can also extrapolate to surveying wind data in conjunction with logarithm Wind outline.
The influencing factor of Power Output for Wind Power Field mainly contains wind speed, wind direction, temperature, air pressure, humidity and roughness of ground surface etc.Therefore the data such as wind speed, wind direction, temperature, air pressure, humidity obtained from numerical weather forecast are all necessity inputs of forecast model.But equally also there is certain misdata in numerical weather forecast historical data, need further process just can be applied to Power Output for Wind Power Field prediction.Based on digital map, using numerical weather forecast or survey wind data as the input of model, set up the physical model being used for power prediction.According to wind energy turbine set digital model, consider that between landform, barrier, roughness and blower fan, wake effect is on the impact of Power Output for Wind Power Field, the wind speed of ad-hoc location is extrapolated to the wind speed at every Fans hub height place, in conjunction with the power curve of particular rack, calculate the power output of whole wind energy turbine set.
In the above-described embodiments, wind energy turbine set information gathering comprises historical power data acquisition, historical wind speed data acquisition.Power data can obtain in wind energy turbine set central monitoring system.Central monitoring system gathers the situation of exerting oneself of wind energy turbine set for every 15 minutes and is kept in the file of specifying.The central monitoring system data memory format of different company's exploitation is different, needs it just can open under designated environment.
The collection of air speed data needs to set up anemometer tower in the place that wind energy turbine set is representative.The stable little wind energy turbine set anemometer tower of, wind speed simple in landform just can represent the wind conditions of whole wind energy turbine set substantially.But in wind energy turbine set (such as mountain topography) with a varied topography, then needing to select multiple type locality to set up anemometer tower could go out the wind conditions of this wind field by Correct.
Anemometer tower height is generally at 70 meters, and the needs of system data according to weather report, anemometer tower need the transducer installed have air velocity transducer, wind transducer, temperature sensor, baroceptor and humidity sensor.
Particularly, the installation of each transducer: temperature sensor, barometric pressure humidity transducer can be arranged on 10 meters of eminences, air velocity transducer and wind transducer can 10 meters, 30 meters, 50 meters, the 70 meters each installations in one.
Can adopt the method establishment forecast model that above-mentioned physical method and statistical method combine, this forecast model is mainly wind energy turbine set numerical weather forecast, wind farm wind velocity, wind energy turbine set historical power data etc.Export the power for wind energy turbine set.
Above-described embodiment adopts the Forecasting Methodology of many cover numerical weather forecasts, is conducive to improving precision of prediction, and realizing predicts the outcome can be used in the wind power forecasting system of power scheduling department and wind energy turbine set.
system embodiment
According to the embodiment of the present invention, as shown in Figure 3 and Figure 4, the short-term wind power forecast method based on many cover numerical weather forecast sources is provided.
As shown in Figure 3, the short-term wind-electricity power prognoses system based on many cover numerical weather forecast sources of the present embodiment, comprise data of weather forecast collecting unit 1, EMS system 4 and prediction processing unit 5, wherein: EMS system 4, for providing the data setting up each wind energy turbine set forecast model; Data of weather forecast collecting unit 1, for obtaining the numerical weather forecast data of each wind energy turbine set, and input prediction model; Prediction processing unit 5, based on the data setting up each wind energy turbine set forecast model that EMS system provides, sets up forecast model; And, for the numerical weather forecast data that forecast model inputs based on data of weather forecast collecting unit 1, prediction processing is carried out to the wind power output situation of each wind energy turbine set short-term and ultra-short term, obtains and can be applied to power scheduling and set up predicting the outcome of new forecast model.
Further, the short-term wind-electricity power prognoses system based on many cover numerical weather forecast sources of above-described embodiment, also comprise prognoses system database 3, man-machine interaction unit 2 and communication unit 6, wherein: prognoses system database 3, as data center, for store, transfer and upgrade from data of weather forecast collecting unit 1 numerical weather forecast data, send out wind power data and predicting the outcome from prediction processing unit 5 from the reality of EMS system 4, each software module all completes the mutual of data by system database; Man-machine interaction unit 2, for user interactions, complete and at least comprise data and curve display and the operation of system management and maintenance; Communication unit 6, for data of weather forecast collecting unit 1, EMS system 4, prediction processing unit 5 and man-machine interaction unit 2 data interaction to each other.
In the above-described embodiments, prediction processing unit 5, takes out numerical weather forecast data from prognoses system database 3, calculates predicting the outcome of wind energy turbine set through forecast model, and will predict the outcome and send prognoses system database 3 back to.
Preferably, as shown in Figure 4, the short-term wind-electricity power prognoses system based on many cover numerical weather forecast sources of above-described embodiment, comprise data of weather forecast collecting unit 1, man-machine interaction unit 2, prognoses system database 3, EMS system 4, prediction processing unit 5 and communication unit 6, data of weather forecast collecting unit 1, prediction processing unit 5, communication unit 6, EMS system 4 connect successively, prognoses system database 3 is connected with prediction processing unit 5 and communication unit 6 respectively, and man-machine interaction unit is connected with communication unit 6.
Wherein, above-mentioned data of weather forecast collecting unit 1, comprises internet module 11, European meteorological observatory numerical weather forecast 12, Lanzhou meteorological observatory numerical weather forecast 13 and Chinese DianKeYuan numerical weather forecast 14; Prediction processing unit 5, comprises NWP processing module 51 and prediction and calculation processor 52; Communication unit 6, comprises Network Security Device 61 and the network switch 62; EMS system 4, comprises wind energy turbine set real-time information collection module 41, data dispatch module 42 and EMS system data platform 43; Prognoses system database 3, comprises prognoses system database interface 31 and prognoses system database server 32; Man-machine interaction unit 2, comprises graphic user interface 21 and graphical user interface module 22.
In the above-described embodiments, the data such as the realtime power of each wind energy turbine set, wind speed are sent in prognoses system database 3 by wind energy turbine set real-time information collection module 41, will predict the outcome from prognoses system database 3 simultaneously and take out, and send to EMS system data platform 43.
In the above-described embodiments, internet module 11, respectively after European meteorological observatory numerical weather forecast 12, Lanzhou meteorological observatory numerical weather forecast 13 and Chinese DianKeYuan numerical weather forecast 14, be connected with the network switch 62 with NWP processing module 51, Network Security Device 61 successively; Prognoses system database server 32, prognoses system database interface 31, prediction and calculation processor 52 are connected successively with the network switch 62, and prognoses system database interface 31, graphic user interface 21 and EMS system data platform 43 are all connected with the network switch 62; EMS system data platform 43, data dispatch module 42 are connected successively with wind energy turbine set real-time information collection module 41, and graphic user interface 21 is connected with graphical user interface module 22.
In above-mentioned EMS system 4, wind energy turbine set real-time information collection module 41, for the server from each service provider of numerical weather forecast, downloads various places numerical weather forecast; EMS system data platform 43, for gained various places numerical weather forecast, carries out data processing and D/A conversion, obtains each wind energy turbine set prediction period numerical weather forecast; And, for gained each wind energy turbine set prediction period numerical weather forecast data, carry out analyzing and weighted calculation, obtain the numerical weather forecast data for input prediction model; Data dispatch module 42, for the data interaction between wind energy turbine set real-time information collection module and EMS system data platform.
In above-mentioned prediction processing unit 5, NWP processing module 51, after numerical weather forecast data being processed, exports rough prediction data; Prediction and calculation processor 52, for based on atmospheric boundary layer dynamics and boundary layer meteorology theory, carries out process of refinement by rough prediction data, obtains the predicted value under wind energy turbine set actual landform, geomorphologic conditions; By the prediction of wind speed in predicted value and wind direction, be converted to wind speed and the wind direction of wind-powered machine unit hub height; In conjunction with wake effect between Wind turbines, by the wind speed of gained wind-powered machine unit hub height and wind direction, be applied to the power curve of Wind turbines, draw the predicted power of Wind turbines; The predicted power of all Wind turbines is sued for peace, obtains the predicted power of whole wind energy turbine set, namely obtain predicting the outcome of whole wind energy turbine set.
In the embodiment shown in fig. 4, the high-precision numerical weather forecast of 3 cover is contained in data of weather forecast collecting unit 1, European meteorological observatory numerical weather forecast 12, Lanzhou meteorological observatory numerical weather forecast 13 and Chinese DianKeYuan numerical weather forecast 14 respectively, by NWP processing module 51 to the numerical weather forecast data that 3 cover numerical weather forecasts are analyzed, weighted calculation draws finally prediction wind field.NWP processing module 51 is connected by network with between Network Security Device 61, the network switch 62.Data acquisition equipment in wind energy turbine set real-time information collection module 41, comprises wind farm wind velocity, wind direction, temperature, air pressure collecting equipment and wind electric field blower real-time information collection device.Prognoses system database server 32 is connected with EMS system data platform 43 by the network switch 62, Network Security Device 61 and NWP processing module 51, EMS system data platform 43 is connected with wind energy turbine set real-time data acquisition equipment (i.e. wind energy turbine set real-time information collection module 41) by data dispatch module 42, prognoses system database server 32 adopts PC system, loads Windows XP operating system.
Numerical weather forecast provides the various weather forecast data of wind energy turbine set position surface layer, and once, forecast in a day 2 times, forecasts 72 hours at every turn in forecast in every 12 hours.The data that data of weather forecast collecting unit 1 provides are binary format, through data processing and conversion, convert the input of decimal format as forecast model to.Wind energy turbine set real-time information collection module 41 mainly sets up anemometer tower at wind energy turbine set key position, gathers the data such as wind speed, wind direction, temperature, air pressure.Also as the input data of forecast model after the conversion of these data process.Prediction processing unit 5 is mainly predicted wind speed and power, is the core of the short-term wind-electricity power prognoses system based on many cover numerical weather forecast sources.Because the geographical position of each wind energy turbine set, meteorological condition are not identical, so forecast model will have adjustable, software-implemented module mainly comprises data processing conversion and GUI graphical interfaces.
The short-term wind power forecast method based on many cover numerical weather forecast sources of above-described embodiment and system, can realize wind power prediction in 72 hours, improve the specified installed capacity that system is total; Generation schedule is formulated, send out for electric equilibrium, ensure that power network safety operation has important function; Only lean on the historical data of installed capacity of wind-driven power and wind-powered electricity generation electricity volume to estimate the problem of wind power when being conducive to solving traffic department's mixing system stand-by power supply.
In sum, the short-term wind power forecast method based on many cover numerical weather forecast sources of various embodiments of the present invention and system, because the method comprises: the forecast model of each wind energy turbine set of method establishment that Applied Physics and statistics combine; Obtain the numerical weather forecast data of each wind energy turbine set, input prediction model; Forecast model, based on the numerical weather forecast data of input, carries out prediction processing to the wind power output situation of each wind energy turbine set short-term and ultra-short term, obtains and can be applied to power scheduling and set up predicting the outcome of new forecast model; Wind power prediction in 72 hours can be realized, be conducive to improving the total specified installed capacity of wind power system; Generation schedule is formulated, send out for electric equilibrium, ensure that power network safety operation has important function, during to solve traffic department's mixing system stand-by power supply, only lean on the historical data of installed capacity of wind-driven power and wind-powered electricity generation electricity volume to estimate the problem of wind power; Thus can overcome that precision of prediction in prior art is low, safety and poor stability so that do not reach the defect of practical requirement, to realize that precision of prediction is high, security of operation and good stability so that can in the advantage of the practical operation of power scheduling.
Last it is noted that the foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, although with reference to previous embodiment to invention has been detailed description, for a person skilled in the art, it still can be modified to the technical scheme described in foregoing embodiments, or carries out equivalent replacement to wherein portion of techniques feature.Within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (4)

1., based on the short-term wind power forecast method in many cover numerical weather forecast sources, it is characterized in that, comprising:
The forecast model of each wind energy turbine set of method establishment that Applied Physics and statistics combine;
Obtain the numerical weather forecast data of each wind energy turbine set, input described forecast model;
Described forecast model, based on the numerical weather forecast data of input, carries out prediction processing to the wind power output situation of each wind energy turbine set short-term and ultra-short term, obtains and can be applied to power scheduling and set up predicting the outcome of new forecast model;
Described operation of setting up the forecast model of each wind energy turbine set comprises:
Obtain at least to comprise and overlap the topography and geomorphology in region and the master data of fan operation state residing for numerical weather forecast, wind energy turbine set history survey wind data, Power Output for Wind Power Field historical data, wind energy turbine set more;
By statistical method, or the method that physical method combines with statistical method, gained master data is processed, obtains the forecast model of each wind energy turbine set;
The operation of the numerical weather forecast data of each wind energy turbine set of described acquisition comprises:
From the server of each service provider of numerical weather forecast, download various places numerical weather forecast;
To gained various places numerical weather forecast, carry out data processing and D/A conversion, obtain each wind energy turbine set prediction period numerical weather forecast;
To gained each wind energy turbine set prediction period numerical weather forecast data, carry out analyzing and weighted calculation, obtain the numerical weather forecast data for input prediction model;
Described forecast model is based on the numerical weather forecast data of input, and the operation wind power output situation of each wind energy turbine set short-term and ultra-short term being carried out to prediction processing comprises:
Described numerical weather forecast data, after the process of NWP system, export rough prediction data;
Based on atmospheric boundary layer dynamics and boundary layer meteorology theory, described rough prediction data is carried out process of refinement, obtains the predicted value under wind energy turbine set actual landform, geomorphologic conditions;
By the prediction of wind speed in described predicted value and wind direction, be converted to wind speed and the wind direction of wind-powered machine unit hub height;
In conjunction with wake effect between Wind turbines, by the wind speed of gained wind-powered machine unit hub height and wind direction, be applied to the power curve of Wind turbines, draw the predicted power of Wind turbines;
The predicted power of all Wind turbines is sued for peace, obtains the predicted power of whole wind energy turbine set, namely obtain predicting the outcome of whole wind energy turbine set;
The method also comprises:
To the described operation stored that predicts the outcome, and/or,
To the described operation shown that predicts the outcome.
2. the short-term wind power forecast method based on many cover numerical weather forecast sources according to claim 1, it is characterized in that, described numerical weather forecast data, at least comprise and obtain air speed data, wind direction data, temperature record, barometric information and humidity data from various places numerical weather forecast.
3., based on the short-term wind-electricity power prognoses system in many cover numerical weather forecast sources, it is characterized in that, comprise data of weather forecast collecting unit, EMS system and prediction processing unit, wherein:
Described EMS system, for providing the data setting up each wind energy turbine set forecast model;
Described data of weather forecast collecting unit, for obtaining the numerical weather forecast data of each wind energy turbine set, and input prediction model;
Described prediction processing unit, for the data setting up each wind energy turbine set forecast model provided based on EMS system, sets up forecast model; And, for the numerical weather forecast data that described forecast model inputs based on data of weather forecast collecting unit, prediction processing is carried out to the wind power output situation of each wind energy turbine set short-term and ultra-short term, obtains and can be applied to power scheduling and set up predicting the outcome of new forecast model;
Described EMS system, comprises wind energy turbine set real-time information collection module, data dispatch module and EMS system data platform, wherein:
Described wind energy turbine set real-time information collection module, for the server from each service provider of numerical weather forecast, downloads various places numerical weather forecast;
Described EMS system data platform, for gained various places numerical weather forecast, carries out data processing and D/A conversion, obtains each wind energy turbine set prediction period numerical weather forecast; And,
For to gained each wind energy turbine set prediction period numerical weather forecast data, carry out analyzing and weighted calculation, obtain the numerical weather forecast data for input prediction model;
Described data dispatch module, for the data interaction between wind energy turbine set real-time information collection module and EMS system data platform;
Described prediction processing unit, comprises NWP processing module and prediction and calculation processor, wherein:
Described NWP processing module, after numerical weather forecast data being processed, exports rough prediction data;
Described prediction and calculation processor, for based on atmospheric boundary layer dynamics and boundary layer meteorology theory, carries out process of refinement by described rough prediction data, obtains the predicted value under wind energy turbine set actual landform, geomorphologic conditions;
By the prediction of wind speed in described predicted value and wind direction, be converted to wind speed and the wind direction of wind-powered machine unit hub height;
In conjunction with wake effect between Wind turbines, by the wind speed of gained wind-powered machine unit hub height and wind direction, be applied to the power curve of Wind turbines, draw the predicted power of Wind turbines;
The predicted power of all Wind turbines is sued for peace, obtains the predicted power of whole wind energy turbine set, namely obtain predicting the outcome of whole wind energy turbine set.
4. the short-term wind-electricity power prognoses system based on many cover numerical weather forecast sources according to claim 3, is characterized in that, also comprise prognoses system database, man-machine interaction unit and communication unit, wherein:
Described prognoses system database, as data center, for store, transfer and upgrade from data of weather forecast collecting unit numerical weather forecast data, send out wind power data and predicting the outcome from prediction processing unit from the reality of EMS system;
Described man-machine interaction unit, for user interactions, complete and at least comprise data and curve display and the operation of system management and maintenance;
Described communication unit, for data of weather forecast collecting unit, EMS system, prediction processing unit and man-machine interaction unit data interaction to each other.
CN201210003944.5A 2012-01-06 2012-01-06 Short-term wind power prediction method and system based on multiple numerical weather prediction sources CN102570453B (en)

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