CN102044872A - Medium-long term forecasting method for wind power - Google Patents

Abstract

The invention relates to a medium-long term forecasting method for wind power, which is characterized by comprising the following steps of: (1) collecting global large-scale meteorology forecasting field data, and providing an initial field and side boundary condition of 7 days for a WRF (Weather Research Forecast) mode; collecting topography, vegetation and sea temperature data for providing underlying surface information for the WRF mode; (2) building the WRF mode to calculate meteorology field information; (3) inputting the large-scale meteorology forecasting field data collected in the step (1) and the underlying surface information into the WRF model to obtain the wind direction and the wind speed forecasting data within the wind field range; and (4) solving the output power of each fan according to the forecasted wind speed by a fan power curve, and accumulating to obtain the total output power of the wind field. The medium-long term forecasting method can accurately forecast the wind power in future 7 days in the WRF mode, has long forecasting time, operation stability, flexible forecasting scheme and few limitation conditions, and does not need the historical operation data of the wind field.

Description

The medium-term and long-term forecasting procedure of a kind of wind power

[technical field]

The present invention relates to the wind generator system field, relate in particular to the medium-term and long-term forecasting procedure of wind power, the wind energy turbine set wind power forecasting procedure of specifically utilizing the high-resolution numerical model to carry out in conjunction with the power of fan curve 7 days by a definite date.

[background technology]

Energy problem has the strategic position of particular importance in the sustainable development of China's economic society.Chinese present energy supply and demand contradiction is sharp-pointed, and efficiency of energy utilization is low, consumes based on the primary energy of coal and has caused the serious environmental pollution.China has become the second-biggest-in-the-world CO2 emission state that is only second to the U.S., constantly increases from the reduction of greenhouse gas discharge pressure of international community.China's " severe power shortage, coal shortage, oil is waste, natural gas is waste " of taking place on a large scale highlighted the sternness of current China's energy supply conditions in recent years.

Wind power generation is that present technology clean reproducible energy the most ripe, that have large-scale development and commercialized development prospect most utilizes mode, develop very rapid over past ten years, become important energy resource supply mode in some countries, the large-scale commercial applications of regenerative resources such as Chinese Government's great attention wind energy melts to be sent out and the sustainability utilization." People's Republic of China's regenerative resource method " that on January 1st, 2006 is formally effective, the renewable energy utilization that comprises wind energy brought up to be increased energy supply, improve energy resource structure, ensures energy security, the protection environment, realize the strategic height of the sustainable development of socio-economy.The Central Committee of the Communist Party of China explicitly calls for clean energy technologies such as greatly developing wind energy, solar energy about in the suggestion of formulating the national economy and social development 11th Five-Year Plan.

Under these circumstances, the wind power generation cause of China has presented good growth momentum, large-scalely is incorporated into the power networks wind power generation development rapidly, country in succession in Jiuquan, Xinjiang, Jiangsu, Meng Dong, Meng Xi, Jilin, Hebei planned seven ten million multikilowatt wind-powered electricity generation bases.Wherein construction plan has been finished in ten million multikilowatt wind-powered electricity generation base, Jiuquan, and the part wind energy turbine set is generated electricity by way of merging two or more grid systems.

The characteristics of electric power system maximum are real-time dynamic equilibrium, just will guarantee just balance of electricity that each is sent constantly and the electricity that is consumed, and could guarantee the stable and safety of electric power system.Before wind power generation inserted electric power system, what electric power system was faced was foreseeable load and the power supply that can control, on the basis of load prediction, guarantees the real-time dynamic equilibrium of electric power system by the scheduling controlling to generating.

When wind-powered electricity generation is linked into electric power system as a kind of power supply, its intermittence and fluctuation have increased the peak regulation difficulty of electric power system, if wind-powered electricity generation is not given a forecast and dispatching management, just require in the middle of electric power system, to leave the reserve capacity that equates with the wind-powered electricity generation capacity, the fluctuation of balance wind-powered electricity generation.Along with the increase of wind-powered electricity generation ratio in power supply, it is big that the peak-valley difference of electric power system further becomes, and this just need carry out peak regulation by a larger margin, if still adopt electric power system to stay the standby mode of whole wind-powered electricity generation capacity, electric power system can't normally move.

Power Output for Wind Power Field is predicted, wind power is included in the operation plan of electrical network, can make power scheduling department according to predicting the outcome, electrical production and scheduling are made more reasonable, effective plan, for the generation schedule of scheduling schedule system, guarantee electric power system safe and stable operation, reduce reserve capacity and operating cost and electricity market effectively managed etc. all significant, be to solve large-scale wind power to insert one of effective measures of dispatching of power netwoks problem behind the electrical network.

For guarantee large-scale wind power be incorporated into the power networks the back power network safety operation, electrical network need be according to wind-powered electricity generation definite peak of exerting oneself in real time, and peak is the network optimization operating scheme of determining under known reserve capacity, but contain wind-powered electricity generation the reserve capacity of interior electric power system really rule need predicting the outcome of wind power midium or long term as foundation.Especially for the higher Northwest Grid of water power ratio, how determine the storage capacity of hydroelectric plant to need wind power medium-and long-term forecasting result more as foundation according to reservoir regulation and peak load regulation network needs in Various Seasonal.Insert the increase of ratio in addition along with wind-powered electricity generation, also need to consider the variation of exerting oneself of wind-powered electricity generation midium or long term in the maintenance arrangement principle of grid equipment.

Erik L., Frank, scholars such as Bailey are at document 1. " Wind Power Meteorology.Part II:Siting and Models. " (Wind Energy.1998,1:55-72.) 2. " Modelling the Wind Climate of Ireland. " (Boundary-Layer Meteorology, 1997,85:359-378.) 3. " Short-Term Wind Forecasting. " (Proceedings of the European Wind Energy Conference, Nice, Frace, 1-5March 1999, PP.1062-1065, ISBN1902916X.) pointing out in that the integrated system that adopts numerical forecast pattern and wind power statistical forecast model to combine forecasts, is the effective ways of wind energy turbine set wind power short-period forecast.Its juche idea is to utilize numerical value sky forecast that the forecast informations such as wind speed, wind direction of axial fan hub height are provided, and utilizes the forecast data of wind speed and direction and the wind energy turbine set wind power record material of the same period to set up wind power forecast statistics model then and carries out the wind power forecast.

External wind power prediction research work starting is morning, and more representational method mainly contains: Denmark

The Ewind of the Prediktor forecast system of National Laboratory, Hispanic LocalPred forecast system and the U.S. etc.The Prediktor forecast system at first utilizes numerical weather prediction model HIRLAM that the wind speed profile of wind energy turbine set region is provided, and utilizes WA then ^sP further takes all factors into consideration factors such as near the barrier of wind energy turbine set, roughness variation provides resolution higher wind speed forecast, at last by the energy output computing module

Park calculates the wind energy turbine set wind power on the wind speed basis of forecast.The LocalPred forecast system at first utilizes high-resolution mesoscale model MM5 or NWP pattern in conjunction with weather forecast fields such as fluid mechanics computed in software wind speed, by statistical module (MOS) the forecast wind speed is corrected again, gone out force data by history at last and carry out power with power output model that the same period, meteorological field such as wind speed was set up and forecast.The Previento forecast system is corrected wind speed in conjunction with the influence of wind energy turbine set surrounding terrain, roughness of ground surface and thermal stratification on the basis that utilizes numerical model forecast axial fan hub place height wind speed, carries out the power forecast by power forecast module at last.

The existing wind power forecast system of China is mainly short-term wind-electricity power forecast and ultrashort phase wind power forecast system.The forecast timeliness is shorter, be primarily aimed at the solution of wind-electricity integration under the known peak situation, but 7 ten million multikilowatt wind-powered electricity generation bases such as the Jiuquan that starts in succession along with country, Hami, wind-powered electricity generation installation proportion in system is more and more higher, if the mode of taking all standby units to be in hot stand-by duty can make other fired power generating unit average load rate, average output descend, thereby make thermal power plant's decrease in efficiency, coal consumption rise, can reduce the economical of power system operation greatly, coal consumption is risen equally also can increase greenhouse gas emissions.Therefore carry out the medium-term and long-term forecast of wind power to the large-scale wind power crucial effects that has been incorporated into the power networks.

[summary of the invention]

The purpose of this invention is to provide the medium-term and long-term forecasting procedure of a kind of wind power, this forecasting procedure can forecast that effectively the wind-powered electricity generation in its following 7 days exerts oneself at put into operation wind energy turbine set and newly-built wind energy turbine set, for the formulation of the reserve capacity and the production schedule thereof provides rational data support.

To achieve these goals, the present invention adopts following technical scheme:

The medium-term and long-term forecasting procedure of a kind of wind power is characterized in that, may further comprise the steps:

(1) gathers global large scale weather forecast field data and provide initial field and 7 days lateral boundary conditions by a definite date for the WRF pattern; Collection landform, vegetation, extra large temperature data provide underlying surface information for the WRF pattern;

(2) set up WRF mode computation meteorological field information; Described WRF pattern utilizes following equation group to carry out the calculating of wind speed, temperature, air pressure forecast fields;

The Eulerian equation of flux form:

${\∂}_{t}U+(\▿\·V_u)-{\∂}_x\left(p{\∂}_{\mathrm{\η}}\mathrm{\φ}\right)+{\∂}_{\mathrm{\η}}\left(p{\∂}_x\mathrm{\φ}\right)=F_U$

${\∂}_{t}V+(\▿\·\mathrm{Vv})-{\∂}_y\left(p{\∂}_{\mathrm{\η}}\mathrm{\φ}\right)+{\∂}_{\mathrm{\η}}\left(p{\∂}_y\mathrm{\φ}\right)=F_V$

${\∂}_{t}W+(\▿\·\mathrm{Vw})-g({\∂}_{\mathrm{\η}}p-\mathrm{\μ})=F_w$

${\∂}_t\mathrm{\Θ}+(\▿\·\mathrm{V\θ})=F_{\mathrm{\Θ}}$

${\∂}_t\mathrm{\μ}+(\▿\·V)=0$

${\∂}_t\mathrm{\φ}+{\mathrm{\μ}}^{-1}[(V\·\▿\mathrm{\φ})-\mathrm{gW}]=0$

The density equation:

${\∂}_{\mathrm{\η}}\mathrm{\φ}=-\mathrm{\α\μ}$

Wherein, η=(p _h-p _Ht)/μ, μ=(p _Hs-p _Ht), p _hBe the air pressure of gas place layer, p _HsBe surface pressure, p _HtBe mode layer top air pressure; V=μ v=(U, V, W),

Θ=μ θ, (u, v w), are the component of speed air quantity in two horizontal directions and a vertical direction to v=, and θ is a megadyne temperature, and φ=gz, g are acceleration of gravity, and α=1/ ρ, ρ are atmospheric density;

(3) large scale weather forecast field data that step (1) is gathered and the WRF model in the underlying surface information input step (2) obtain wind direction, the wind speed forecast data in the wind energy turbine set scope;

(4) utilize the power of fan curve to obtain each blower fan above-mentioned forecast wind speed and exert oneself, adding up obtains the wind energy turbine set gross capability.

Compared with prior art, the present invention has the following advantages: the medium-term and long-term forecasting procedure of a kind of wind power of the present invention, using the WRF pattern can following 7 days wind power of accurate forecast, and that the inventive method calls time in advance is long, stable, do not need the wind energy turbine set history data, the forecast scheme is flexible, restrictive condition is less; The inventive method only needs the wind electric field blower type information, just can accurately forecast wind power, is applicable to all kinds of the operation or newly-built wind energy turbine set.

[description of drawings]

Fig. 1 is a WRF pattern vertical coordinate schematic diagram;

Fig. 2 is a wind power long range forecasting system schematic diagram;

Fig. 3 is that 70 meters height of certain anemometer tower on August 19th, 2010 are observed wind speed and the comparison diagram that forecasts wind speed;

Fig. 4 is the actual wind power of certain electric field on August 19 in 2010 and forecasts the wind power comparison diagram.

[embodiment]

Below in conjunction with accompanying drawing the present invention is done and to describe in further detail.

See also shown in Figure 2ly, the medium-term and long-term forecasting procedure of wind power of the present invention comprises meteorological and underlying surface data module, WRF mode computation module, power computation module, user's display interface with forecast system.Weather station data, large scale forecast fields data are converted into the needed data format of WRF through the pre-treatment process, for the calculating of WRF pattern provides initial gas image field information; Landform, vegetation, extra large temperature data provide underlying surface information for the WRF pattern; Utilize the power of fan curve will forecast that wind speed is converted into wind-powered electricity generation and exerts oneself, at last the result is shown to user terminal.

The WRF pattern of carrying out weather forecast calculating will be under the parallel high-performance computer environment, this computer environment comprises 12 computing nodes, each node contains 4 CPU, each CPU has two nuclears, can realize mutual communication, file-sharing and concurrent operation between the computing node, and be furnished with certain data space.

WRF mode computation flow process mainly comprises three parts: (1) prepares meteorological data, prepares the meteorological field data on required forecast date for mode computation; (2) formulate pattern framework, according to wind energy turbine set position and the central point of area deterministic model, the nested number of plies, every layer of nested area that surrounds etc.; (3) the WRF pattern utilizes above-mentioned information to carry out the calculating of weather forecast field.

Forecast example below in conjunction with certain wind energy turbine set is elaborated, and this wind energy turbine set area is about 30 square kilometres, and the forecast date is on August 19th, 2010, and calling time in advance is 7 days.

(1) prepares meteorological data

The WRF pattern needs the meteorological field data as its initial condition and lateral boundary conditions, for pattern provides initial gas image field information and boundary information, and the result of calculation of restriction mode itself.

The meteorological field data adopts NCEP lattice point data, horizontal resolution is 1 ° * 1 °, vertical direction comprises 1000hPa, 975hPa, 950hPa, 925hPa, 850hPa, 800hPa, 750hPa, 700hPa, 650hPa, 600hPa, 550hPa, 500hPa, 450hPa, 400hPa, 350hPa 300hPa, 250hPa, 200hPa, 150hPa, 100hPa, 70hPa, 50hPa, 30hPa, 10hPa, 24 barospheres.By the pre-treatment process WPS of WRF pattern, extract the data such as wind speed, temperature, pressure, humidity, geopotential unit of lattice point in the NCEP data and be converted into the required form of WRF pattern.

In addition, need to prepare wind energy turbine set in-scope interior landform, the vegetation data in corresponding month and water surface temperature data.

(2) formulate pattern framework

This wind energy turbine set area is 30 square kilometres, and innermost layer nested region area should be greater than 30 square kilometres, so that wind energy turbine set is all included.Stablize needs and pattern restriction operation time according to mode computation, determine that the innermost layer horizontal resolution is 1km, the horizontal direction lattice point number is 37 * 37.Because NCEP forecast fields resolution is 110km, need to fall yardstick the 110km resolution data is reduced to innermost layer 1km resolution data through power, therefore adopt 4 to repoint the cover zone, each layer resolution is respectively 27km, 9km, 3km, 1km.

(3) WRF mode computation

The WRF pattern utilizes following equation group to carry out the calculating of forecast fieldses such as wind speed, temperature, air pressure.The Eulerian equation of flux form:

${\∂}_{t}U+(\▿\·V_u)-{\∂}_x\left(p{\∂}_{\mathrm{\η}}\mathrm{\φ}\right)+{\∂}_{\mathrm{\η}}\left(p{\∂}_x\mathrm{\φ}\right)=F_U$

${\∂}_{t}V+(\▿\·\mathrm{Vv})-{\∂}_y\left(p{\∂}_{\mathrm{\η}}\mathrm{\φ}\right)+{\∂}_{\mathrm{\η}}\left(p{\∂}_y\mathrm{\φ}\right)=F_V$

${\∂}_{t}W+(\▿\·\mathrm{Vw})-g({\∂}_{\mathrm{\η}}p-\mathrm{\μ})=F_w$

${\∂}_t\mathrm{\Θ}+(\▿\·\mathrm{V\θ})=F_{\mathrm{\Θ}}$

${\∂}_t\mathrm{\μ}+(\▿\·V)=0$

${\∂}_t\mathrm{\φ}+{\mathrm{\μ}}^{-1}[(V\·\▿\mathrm{\φ})-\mathrm{gW}]=0$

The density equation:

${\∂}_{\mathrm{\η}}\mathrm{\φ}=-\mathrm{\α\μ}$

Wherein, η=(p _h-p _Ht)/μ, μ=(p _Hs-p _Ht), p _hBe the air pressure of gas place layer, p _HsBe surface pressure, p _HtBe mode layer top air pressure, as shown in Figure 1.V=μ v=(U, V, W),

Θ=μ θ, (u, v w), are the component of speed air quantity in two horizontal directions and a vertical direction to v=, and θ is a megadyne temperature, and φ=gz, g are acceleration of gravity, and α=1/ ρ, ρ are atmospheric density;

Calculate the data that generate through above-mentioned equation group, utilize the post-processing module of WRF pattern at last, export needed forecast wind speed, wind direction data according to blower fan position and blower fan height; Fig. 3 is the comparison diagram that 70 meters height of certain anemometer tower on August 19th, 2010 are observed wind speed and this method forecast wind speed, and as can be seen from the figure, the inventive method forecast wind speed and actual value are approaching, the forecast precision height;

(4) wind power calculates

Utilize the power of fan curve to obtain each blower fan the wind speed of step (3) forecast and exert oneself, adding up obtains the wind energy turbine set gross capability.As Fig. 4 is in August, 2010 19-25 day wind energy turbine set power forecast result, forecasts the dry straight record result that coincide.Traffic department can arrange reserve capacity start mode according to this, optimizes the peak regulation means.

User's display interface among the present invention can to inquiring about on the same day and historical data, can be realized the dynamic change demonstration of wind power and one day generating calculation of total at different wind energy turbine set.

Above content is to further describing that the present invention did in conjunction with concrete preferred implementation; can not assert that the specific embodiment of the present invention only limits to this; for the general technical staff of the technical field of the invention; without departing from the inventive concept of the premise; can also make some simple deduction or replace, all should be considered as belonging to the present invention and determine scope of patent protection by claims of being submitted to.

Claims (1)

1. the medium-term and long-term forecasting procedure of wind power is characterized in that, may further comprise the steps:

(1) gathers global large scale weather forecast field data and provide initial field and 7 days lateral boundary conditions by a definite date for the WRF pattern; Collection landform, vegetation, extra large temperature data provide underlying surface information for the WRF pattern;

(2) set up WRF mode computation meteorological field information; Described WRF pattern utilizes following equation group to carry out the calculating of wind speed, temperature, air pressure forecast fields;

The Eulerian equation of flux form:

${\∂}_{t}U+(\▿\·V_u)-{\∂}_x\left(p{\∂}_{\mathrm{\η}}\mathrm{\φ}\right)+{\∂}_{\mathrm{\η}}\left(p{\∂}_x\mathrm{\φ}\right)=F_U$

${\∂}_{t}V+(\▿\·\mathrm{Vv})-{\∂}_y\left(p{\∂}_{\mathrm{\η}}\mathrm{\φ}\right)+{\∂}_{\mathrm{\η}}\left(p{\∂}_y\mathrm{\φ}\right)=F_V$

${\∂}_{t}W+(\▿\·\mathrm{Vw})-g({\∂}_{\mathrm{\η}}p-\mathrm{\μ})=F_w$

${\∂}_t\mathrm{\Θ}+(\▿\·\mathrm{V\θ})=F_{\mathrm{\Θ}}$

${\∂}_t\mathrm{\μ}+(\▿\·V)=0$

${\∂}_t\mathrm{\φ}+{\mathrm{\μ}}^{-1}[(V\·\▿\mathrm{\φ})-\mathrm{gW}]=0$

The density equation:

${\∂}_{\mathrm{\η}}\mathrm{\φ}=-\mathrm{\α\μ}$

Wherein, η=(p _h-p _Ht)/μ, μ=(p _Hs-p _Ht), p _hBe the air pressure of gas place layer, p _HsBe surface pressure, p _HtBe mode layer top air pressure; V=μ v=(U, V, W),

Θ=μ θ, (u, v w), are the component of speed air quantity in two horizontal directions and a vertical direction to v=, and θ is a megadyne temperature, and φ=gz, g are acceleration of gravity, and α=1/ ρ, ρ are atmospheric density;

(3) large scale weather forecast field data that step (1) is gathered and the WRF model in the underlying surface information input step (2) obtain wind direction, the wind speed forecast data in the wind energy turbine set scope;

(4) utilize the power of fan curve to obtain each blower fan above-mentioned forecast wind speed and exert oneself, adding up obtains the wind energy turbine set gross capability.

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