CN105825439A - Method for conservative calculation of short-term abandoned wind power of generating-limited wind power plant - Google Patents

Abstract

The invention relates to a method for conservative calculation of short-term abandoned wind power of a generating-limited wind power plant, and belongs to the technical field of operation and control of a power system. First of all, historical short-term prediction data of the wind power plant in a past year and historical actual active power data under a generating-limited condition are counted, then, a relation between the historical short-term prediction data and the historical actual active power data under the generating-limited condition is obtained, accordingly, the short-term abandoned wind power of the generating-limited wind power plant is conservatively calculated, and the historical short-term prediction data and the historical actual active power data under the generating-limited condition are updated. The method provided by the invention solves the problem of a conventional power system in calculating the abandoned wind power of a generating-limited wind power plant and provides a basis for high-energy-consumption enterprises in participation of consumption of new energy.

Description

The method that the short-term of a kind of Conservative estimation limited wind energy turbine set of generating abandons wind

Technical field

The present invention relates to the method that the short-term of a kind of Conservative estimation limited wind energy turbine set of generating abandons wind, belong to Operation of Electric Systems and control technical field.

Background technology

Constantly increasing and the construction in generation of electricity by new energy base recently as new forms of energy installed capacity, the region serious wind of abandoning of appearance of the generation of electricity by new energy installed capacity affluences such as Gansu abandons optical issue.Under the power system that the most local underload of the origin cause of formation of this problem causes, spinning reserve is not enough.Due to national policy support, high energy industrial zone is had in generation of electricity by new energy installed capacity areas of well-being such as Gansu, use a large amount of electric energy in process of production, and equipment has certain regulating power to the power load of self, the most limited wind-powered electricity generation if participation electric power system dispatching is dissolved, rotation stand by margin under power system can be improved, promote that wind-light-electricity is dissolved.Due to the randomness of wind-powered electricity generation, wind energy turbine set short-term (following 24 hours) pre-power scale has certain deviation compared with actual wind power, and for the wind energy turbine set generated electricity by way of merging two or more grid systems, the accuracy of this deviation value is in the range of power system permission.But owing to Gansu province wind energy turbine set is chronically at more serious production status of rationing the power supply, production of rationing the power supply makes the real output of wind energy turbine set and wind energy turbine set reality can send out and have relatively large deviation between power, and wind-powered electricity generation short-term forecast power cannot truly reflect that the reality of wind energy turbine set can send out power.Therefore, when high energy industry participates in electric power system dispatching, power system is difficult to Accurate Prediction wind energy turbine set short-term can send out power, thus the limited wind power of short-term that wind energy turbine set cannot be calculated.Method proposes the method that the limited wind energy turbine set short-term of a kind of Conservative estimation generating abandons wind, utilize history generated output data base under the prediction of history wind-powered electricity generation and production status of rationing the power supply, rolling amendment short term predicted data and the deviation of real data, so that power system can calculate the limited wind power of short-term of wind energy turbine set.

Summary of the invention

The purpose of the present invention is to propose to the method that the limited wind energy turbine set short-term of a kind of Conservative estimation generating abandons wind, short-term wind power prediction and reality for the limited wind energy turbine set that generates electricity can send out the deviation between power, rolling amendment wind energy turbine set short-term forecast error, for power system computation wind energy turbine set short-term limited power, promote that high energy coordinates wind-powered electricity generation offer basis of dissolving.

The method that the short-term of the Conservative estimation limited wind energy turbine set of generating that the present invention proposes abandons wind, comprises the following steps:

(1) the actual active power of history under the history short term predicted data in the past 1 year of wind energy turbine set and generating limited situation is added up, obtain the relation between the actual active power of history under history short term predicted data and generating limited situation, concretely comprise the following steps:

(1-1) prediction active power F of wind energy turbine set history short term predicted data 1 year in the past is read from wind farm data storehouse_{yy-mm-dd-hour-min}, wherein yy-mm-dd-hour-min is data markers, and this data markers represents that prediction active power realizes the moment, and form is " year-month-day-hours-minutes "；

(1-2) by wind energy turbine set history short term predicted data in step (1-1) according to prediction active power F_{yy-mm-dd-hour-min}Arranging from small to large, the minima in note wind energy turbine set history short term predicted data is F_min, maximum is F_max；

(1-3) by minima F in step (1-2)_minWith maximum F_maxIt is expressed as an interval [F_min,F_max], the prediction active power numerical value F of wind energy turbine set history short term predicted data_{yy-mm-dd-hour-min}All at interval [F_min,F_maxIn], it is 100 sections by interval division, remembers that the expression formula in r section interval is:

$\begin{array}{c}\[F_{\min }+\frac{F_{\max }-F_{\min }}{100}\·(r-1),F_{\min }+\frac{F_{\max }-F_{\min }}{100}\·r\]\\ r=1,2,\mathrm{...},100\end{array},$

(1-4) the actual active-power P of history wind energy turbine set generating limited situation is read from wind farm data storehouse_{yy-mm-dd-hour-min}, wherein yy-mm-dd-hour-min is data markers, and data markers represents the measurement moment of actual active power, and form is " year-month-day-hours-minutes "；

(1-5) according to the interval number in step (1-3), set omega is set up_rWith set Φ_r, r=1,2 ..., 100, when active power F of prediction in wind energy turbine set history short term predicted data_{yy-mm-dd-hour-min}Fall interval at the rTime middle, by this prediction active power F_{yy-mm-dd-hour-min}Put into set omega_rIn, and will be with F_{yy-mm-dd-hour-min}The actual active-power P of history under the wind energy turbine set generating limited situation that markers is corresponding_{yy-mm-dd-hour-min}Put into set Φ_rIn；

(2) according to relation between the actual active power of history under history short term predicted data in step (1) and generating limited situation, the short-term calculating the limited wind energy turbine set that generates electricity abandons wind power, and detailed process is as follows:

(2-1) short term predicted data of arbitrary prediction time in wind farm data storehouse is read following 24 hours, remembers that this numerical value is FP_{yy'-mm'-dd'-hour'-min'}, yy'-mm'-dd'-hour'-min' is data markers, and this data markers represents that prediction active power realizes the moment, and form is " year-month-day-hours-minutes "；

(2-2) according to the interval division method of step (1-3), the FP of step (2-1) is determined_{yy'-mm'-dd'-hour'-min'}Affiliated interval, remember the numbered r' in this interval；

(2-3) according to the set Φ in step (1-5)_r, make r=r', read the actual active power of history under limited situation that generates electricity in this set, calculate mean μ and the standard deviation sigma of the actual active power of all history read；

(2-4) using μ+σ as the power H that substantially rations the power supply realizing the moment corresponding with short term predicted data in step (2-1) of wind energy turbine set_{yy'-mm'-dd'-hour'-min'}；

(2-5) FP is judged_{yy'-mm'-dd'-hour'-min'}With H_{yy'-mm'-dd'-hour'-min'}Between relation, if FP_{yy'-mm'-dd'-hour'-min'}≤H_{yy'-mm'-dd'-hour'-min'}, then judge that, at moment yy'-mm'-dd'-hour'-min', wind energy turbine set short-term limited power is 0, if FP_{yy'-mm'-dd'-hour'-min'}≥H_{yy'-mm'-dd'-hour'-min'}, then P'=FP is calculated_{yy'-mm'-dd'-hour'-min'}-H_{yy'-mm'-dd'-hour'-min'}, α P' is abandoned wind power as the short-term of the limited wind energy turbine set that generates electricity of moment yy'-mm'-dd'-hour'-min', wherein α is the conservative degree coefficient that wind energy turbine set operations staff sets, and this coefficient value is between 0 to 1；

(3) traversal wind energy turbine set all moment, repetition step (2) in following 24 hours, obtains this wind energy turbine set short-term of following 24 hours and abandons wind power.

The method that the short-term of the Conservative estimation limited wind energy turbine set of generating that the present invention proposes abandons wind, its advantage is: the inventive method takes into full account the historical statistical data of wind energy turbine set, provide conservative wind energy turbine set short-term and abandon wind power, thus participate in power system coordinated scheduling for high energy industry and set up basis.

Accompanying drawing explanation

Fig. 1 is the FB(flow block) that the limited wind energy turbine set short-term of Conservative estimation generating that the present invention proposes abandons the method for wind.

Detailed description of the invention

The method that the short-term of the Conservative estimation limited wind energy turbine set of generating that the present invention proposes abandons wind, its FB(flow block) is as it is shown in figure 1, comprise the following steps:

(1) the actual active power of history under the history short term predicted data in the past 1 year of wind energy turbine set and generating limited situation is added up, obtain the relation between the actual active power of history under history short term predicted data and generating limited situation, concretely comprise the following steps:

(1-1) prediction active power F of wind energy turbine set history short term predicted data 1 year in the past is read from wind farm data storehouse_{yy-mm-dd-hour-min}, wherein yy-mm-dd-hour-min is data markers, and this data markers represents that prediction active power realizes the moment, and form is " year-month-day-hours-minutes "；

(1-2) by wind energy turbine set history short term predicted data in step (1-1) according to prediction active power F_{yy-mm-dd-hour-min}Arranging from small to large, the minima in note wind energy turbine set history short term predicted data is F_min, maximum is F_max；

(1-3) by minima F in step (1-2)_minWith maximum F_maxIt is expressed as an interval [F_min,F_max], the prediction active power numerical value F of wind energy turbine set history short term predicted data_{yy-mm-dd-hour-min}All at interval [F_min,F_maxIn], it is 100 sections by interval division, remembers that the expression formula in r section interval is:

$\begin{array}{c}\[F_{\min }+\frac{F_{\max }-F_{\min }}{100}\·(r-1),F_{\min }+\frac{F_{\max }-F_{\min }}{100}\·r\]\\ r=1,2,\mathrm{...},100\end{array},$

(1-4) the actual active-power P of history wind energy turbine set generating limited situation is read from wind farm data storehouse_{yy-mm-dd-hour-min}, wherein yy-mm-dd-hour-min is data markers, and data markers represents the measurement moment of actual active power, and form is " year-month-day-hours-minutes "；

(1-5) according to the interval number in step (1-3), set omega is set up_rWith set φ_r, r=1,2 ..., 100, when active power F of prediction in wind energy turbine set history short term predicted data_{yy-mm-dd-hour-min}Fall interval at the rTime middle, by this prediction active power F_{yy-mm-dd-hour-min}Put into set omega_rIn, and will be with F_{yy-mm-dd-hour-min}The actual active-power P of history under the wind energy turbine set generating limited situation that markers is corresponding_{yy-mm-dd-hour-min}Put into set Φ_rIn；

(2) according to relation between the actual active power of history under history short term predicted data in step (1) and generating limited situation, the short-term calculating the limited wind energy turbine set that generates electricity abandons wind power, and detailed process is as follows:

(2-1) short term predicted data of arbitrary prediction time in wind farm data storehouse is read following 24 hours, remembers that this numerical value is FP_{yy'-mm'-dd'-hour'-min'}, yy'-mm'-dd'-hour'-min' is data markers, and this data markers represents that prediction active power realizes the moment, and form is " year-month-day-hours-minutes "；

(2-2) according to the interval division method of step (1-3), the FP of step (2-1) is determined_{yy'-mm'-dd'-hour'-min'}Affiliated interval, remember the numbered r' in this interval；

(2-3) according to the set φ in step (1-5)_r, make r=r', read the actual active power of history under limited situation that generates electricity in this set, calculate mean μ and the standard deviation sigma of the actual active power of all history read；

(2-4) using μ=σ as the power H that substantially rations the power supply realizing the moment corresponding with short term predicted data in step (2-1) of wind energy turbine set_{yy'-mm'-dd'-hour'-min'}；

(2-5) FP is judged_{yy'-mm'-dd'-hour'-min'}With H_{yy'-mm'-dd'-hour'-min'}Between relation, if FP_{yy'-mm'-dd'-hour'-min'}≤H_{yy'-mm'-dd'-hour'-min'}, then judge that, at moment yy'-mm'-dd'-hour'-min', wind energy turbine set short-term limited power is 0, if FP_{yy'-mm'-dd'-hour'-min'}≥H_{yy'-mm'-dd'-hour'-min'}, then P'=FP is calculated_{yy'-mm'-dd'-hour'-min'}-H_{yy'-mm'-dd'-hour'-min'}, α P' is abandoned wind power as the short-term of the limited wind energy turbine set that generates electricity of moment yy'-mm'-dd'-hour'-min', wherein α is the conservative degree coefficient that wind energy turbine set operations staff sets, and this coefficient value is between 0 to 1；

(3) traversal wind energy turbine set all moment, repetition step (2) in following 24 hours, obtains this wind energy turbine set short-term of following 24 hours and abandons wind power.

Claims (1)

1. the method that the short-term of the Conservative estimation limited wind energy turbine set of generating abandons wind, it is characterised in that the method comprises the following steps:

(1) the actual active power of history under the history short term predicted data in the past 1 year of wind energy turbine set and generating limited situation is added up, obtain the relation between the actual active power of history under history short term predicted data and generating limited situation, concretely comprise the following steps:

(1-1) prediction active power F of wind energy turbine set history short term predicted data 1 year in the past is read from wind farm data storehouse_{yy-mm-dd-hour-min}, wherein yy-mm-dd-hour-min is data markers, and this data markers represents that prediction active power realizes the moment, and form is " year-month-day-hours-minutes "；

(1-2) by wind energy turbine set history short term predicted data in step (1-1) according to prediction active power F_{yy-mm-dd-hour-min}Arranging from small to large, the minima in note wind energy turbine set history short term predicted data is F_min, maximum is F_max；

(1-3) by minima F in step (1-2)_minWith maximum F_maxIt is expressed as an interval [F_min,F_max], the prediction active power numerical value F of wind energy turbine set history short term predicted data_{yy-mm-dd-hour-min}All at interval [F_min,F_maxIn], it is 100 sections by interval division, remembers that the expression formula in r section interval is:

$\begin{array}{c}\[F_{\min }+\frac{F_{\max }-F_{\min }}{100}\·(r-1),F_{\min }+\frac{F_{max}-F_{\min }}{100}\·r\]\\ r=1,2,\mathrm{...},100\end{array},$

(1-4) the actual active-power P of history wind energy turbine set generating limited situation is read from wind farm data storehouse_{yy-mm-dd-hour-min}, wherein yy-mm-dd-hour-min is data markers, and data markers represents the measurement moment of actual active power, and form is " year-month-day-hours-minutes "；

(1-5) according to the interval number in step (1-3), set omega is set up_rWith set Φ_r, r=1,2 ..., 100, when active power F of prediction in wind energy turbine set history short term predicted data_{yy-mm-dd-hour-min}Fall interval at the rTime middle, by this prediction active power F_{yy-mm-dd-hour-min}Put into set omega_rIn, and will be with F_{yy-mm-dd-hour-min}The actual active-power P of history under the wind energy turbine set generating limited situation that markers is corresponding_{yy-mm-dd-hour-min}Put into set Φ_rIn；

(2) according to relation between the actual active power of history under history short term predicted data in step (1) and generating limited situation, the short-term calculating the limited wind energy turbine set that generates electricity abandons wind power, and detailed process is as follows:

(2-1) short term predicted data of arbitrary prediction time in wind farm data storehouse is read following 24 hours, remembers that this numerical value is FP_{yy'-mm'-dd'-hour'-min'}, yy'-mm'-dd'-hour'-min' is data markers, and this data markers represents that prediction active power realizes the moment, and form is " year-month-day-hours-minutes "；

(2-2) according to the interval division method of step (1-3), the FP of step (2-1) is determined_{yy'-mm'-dd'-hour'-min'}Affiliated interval, remember the numbered r' in this interval；

(2-3) according to the set Φ in step (1-5)_r, make r=r', read the actual active power of history under limited situation that generates electricity in this set, calculate mean μ and the standard deviation sigma of the actual active power of all history read；

(2-4) using μ+σ as the power H that substantially rations the power supply realizing the moment corresponding with short term predicted data in step (2-1) of wind energy turbine set_{yy'-mm'-dd'-hour'-min'}；

(2-5) FP is judged_{yy'-mm'-dd'-hour'-min'}With H_{yy'-mm'-dd'-hour'-min'}Between relation, if FP_{yy'-mm'-dd'-hour'-min'}≤H_{yy'-mm'-dd'-hour'-min'}, then judge that, at moment yy'-mm'-dd'-hour'-min', wind energy turbine set short-term limited power is 0, if FP_{yy'-mm'-dd'-hour'-min'}≥H_{yy'-mm'-dd'-hour'-min'}, then P'=FP is calculated_{yy'-mm'-dd'-hour'-min'}-H_{yy'-mm'-dd'-hour'-min'}, α P' is abandoned wind power as the short-term of the limited wind energy turbine set that generates electricity of moment yy'-mm'-dd'-hour'-min', wherein α is the conservative degree coefficient that wind energy turbine set operations staff sets, and this coefficient value is between 0 to 1；

(3) traversal wind energy turbine set all moment, repetition step (2) in following 24 hours, obtains this wind energy turbine set short-term of following 24 hours and abandons wind power.