CN107529587A - Wind light mutual complementing maximum power tracing method based on genetic algorithm - Google Patents

Wind light mutual complementing maximum power tracing method based on genetic algorithm Download PDF

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Publication number
CN107529587A
CN107529587A CN201710579987.0A CN201710579987A CN107529587A CN 107529587 A CN107529587 A CN 107529587A CN 201710579987 A CN201710579987 A CN 201710579987A CN 107529587 A CN107529587 A CN 107529587A
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wind
wind energy
conversion system
energy conversion
power
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王英立
郭晶
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Harbin University of Science and Technology
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Harbin University of Science and Technology
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    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/72—Wind turbines with rotation axis in wind direction
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P70/00—Climate change mitigation technologies in the production process for final industrial or consumer products
    • Y02P70/50—Manufacturing or production processes characterised by the final manufactured product

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Abstract

Wind light mutual complementing maximum power tracing method based on genetic algorithm.Genetic algorithm finds the method for the peak power of mathematical modeling to find Function Optimization solution, but using concussion problem existing for perturbation observation method.The inventive method includes：Obtain power coefficient formula；Power coefficient formula substitution GAs Toolbox is calculated in MATLAB, finds the maximum P of power coefficientmax, tip speed ratio λ value is recorded, obtains wind energy conversion system rotating speed n now；Draw the actual peak power P of wind energy conversion systemmax；According to principle of genetic algorithm, using GAs Toolbox, optimum individual is found；Find optimal wind energy conversion system rotating speed；In controller design circuit, the tachometer value of this wind energy conversion system is tracked, just realizes the maximum power tracing of wind energy.Faster, real-time is stronger for optimal speed of the present invention, and solving precision is higher, overcomes concussion problem existing for perturbation observation method.

Description

Wind light mutual complementing maximum power tracing method based on genetic algorithm
Technical field：
The present invention relates to a kind of wind light mutual complementing maximum power tracing method based on genetic algorithm.
Background technology：
It is well known that Natural Resources in China is very abundant, but have a problem that, be exactly distributed very uneven, water Resource petroleum resources coal resources be so, the distribution of wind energy and solar energy be also it is very uneven, northern China wind energy and Solar energy just forms good complementation, and the place that power network is published at the place at edge, but also needs to electricity consumption.Lose Propagation algorithm finds the method for the peak power of mathematical modeling to find Function Optimization solution, but is shaken using perturbation observation method is existing Problem.
The content of the invention：
It is an object of the invention to provide a kind of wind light mutual complementing maximum power tracing method based on genetic algorithm.
Above-mentioned purpose is realized by following technical scheme：
Wind light mutual complementing maximum power tracing method based on genetic algorithm, described wind light mutual complementing maximum power tracing method Realized by following steps：
Step 1: determine the wind energy conversion system parameter that blower fan manufacturer provides：Radius, threshold wind velocity, rated wind speed, pitch Angle, rated power, peak power, are obtained：
CPRepresent power coefficient；λiRepresent optimum tip-speed ratio；
Step 2: the C of the wind energy conversion system can be obtained by MTALABPGradually increase during the curve increase of (λ), then again can be with The increase for tip speed ratio λ reduces rapidly；Power coefficient formula is substituted into GAs Toolbox in MATLAB to carry out Calculate, find the maximum C of power coefficientPmax, and corresponding tip speed ratio λ value is recorded, substitute into λ and λiPass It is expression formula：
In, wind energy conversion system rotating speed n now can be obtained；
Step 3: the maximum C by the power coefficient obtained in step 2Pmax, wind energy conversion system rotating speed n and current wind Fast v is updated in moment coefficient expression formula：In, it can draw wind energy conversion system reality by calculating Peak power Pmax。
Step 4: according to principle of genetic algorithm, using GAs Toolbox, optimum individual is found；
Step 5: find optimal wind energy conversion system rotating speed；
Step 6: in controller design circuit, the tachometer value of this wind energy conversion system is tracked, just realizes the peak power of wind energy Tracking.
Beneficial effect：
The present invention genetic algorithm require no knowledge about whether object function can lead, if continuously can be quickly find target The optimal solution of function, faster, real-time is stronger for optimal speed compared with other algorithms, and solving precision is higher, and also overcomes Concussion problem existing for perturbation observation method.
Brief description of the drawings：
Accompanying drawing 1 is blower fan CPWith λ relation curves；
Accompanying drawing 2 is wind energy initial individuals distribution situation；
Accompanying drawing 3 is wind energy battery CP- λ curve maps.
Embodiment：
Embodiment one：
Wind light mutual complementing maximum power tracing method based on genetic algorithm, it is characterized in that：Described wind light mutual complementing maximum work Rate method for tracing is realized by following steps：
Step 1: determine the wind energy conversion system parameter that blower fan manufacturer provides：Radius, threshold wind velocity, rated wind speed, pitch Angle, rated power, peak power, are obtained：
CPRepresent power coefficient；λiRepresent optimum tip-speed ratio；
Step 2: the C of the wind energy conversion system can be obtained by MTALABPThe curve of (λ) is as shown in figure 1, power coefficient CP When tip speed ratio λ is smaller, with tip speed ratio increase when gradually increase, then again can be fast with tip speed ratio λ increase Speed reduces；
By the function of genetic algorithm Automatic-searching optimal value, power coefficient formula is substituted into heredity calculation in MATLAB Method tool box is calculated, and can quickly find the maximum C of the i.e. power coefficient of maximum of the curvePmax, and will Corresponding tip speed ratio λ value is recorded, and substitutes into λ and λiRelational expression：
In, wind energy conversion system rotating speed n now can be obtained；
Step 3: the maximum C by the power coefficient obtained in step 2Pmax, wind energy conversion system rotating speed n and current wind Fast v is updated in moment coefficient expression formula：In, it can draw wind energy conversion system reality by calculating Peak power Pmax。
Step 4: according to principle of genetic algorithm, using GAs Toolbox, with reference to the C of wind energyP- λ characteristic curves and wind Can usage factor formula：Altogether containing 20 populations in same design breeding pond Body, with reference to CPThe object function that-λ characteristic curves formula representsIf It is 0.9 to determine generation gap, and genetic recombination probability is 0.7；
Because this object function is unimodal function, searching optimal value is relatively simple with respect to Solving Multimodal Function, is calculated to shorten Time, same setting only produces 20 initial individuals immediately, and as shown in Fig. 2 " * ", each " * " represents one initial Body.Crisscross inheritance is carried out by the use of these initial individuals as parent, finds optimum individual；
Step 5: in the case where wind speed is certain, during wind speed v=12m/s, by experiment repeatedly, as long as finding by 5 The maximum of the function is found in generation heredity, can so be greatly shortened and be calculated the time.In order to be applied in the engineering of reality, by mistake The processing of difference is essential, therefore, being accurate to after decimal point 4 control errors when designing herein 0.01%, this is with regard to big It is big to save the tracking time, the effect of real-time tracking can be reached, while the efficiency of the wind power generation also improved.By 5 generations After heredity tracking, the optimal value for finding object function is λ=7.9789, and maximal wind-energy usage factor is CPmax=0.4832.Profit With the maximum power point that genetic algorithm is found as shown in "○" red in Fig. 3, coordinate of this in figure for (7.9789, 0.4832)。
After finding tip speed ratio λ corresponding with maximal wind-energy usage factor, its value is substituted into tip speed ratio formula：
In, can obtain corresponding to blower fan rotating speed n,
N ≈ 18.36r/s are calculated to obtain by above formula, wind energy conversion system tachometer value i.e. optimal wind energy conversion system rotating speed now；
Step 6: in controller design circuit, the tachometer value of this wind energy conversion system is tracked, just realizes the peak power of wind energy Tracking.
Embodiment two：
Unlike embodiment one, the wind light mutual complementing peak power based on genetic algorithm of present embodiment chases after Track method, described in step 4 according to principle of genetic algorithm, using GAs Toolbox, the process for finding optimum individual is, With reference to the C of wind energyP- λ characteristic curves and power coefficient formula：Together Sample design breeding contains 20 population at individual altogether in pond, with reference to CPThe object function that-λ characteristic curves formula representsGeneration gap is set as 0.9, genetic recombination probability is 0.7；If It is fixed only to produce 20 initial individuals immediately, crisscross inheritance is carried out by the use of these initial individuals as parent, completes to find optimum individual Process.
Embodiment three：
Unlike embodiment one or two, the wind light mutual complementing maximum work based on genetic algorithm of present embodiment Rate method for tracing, the process of the optimal wind energy conversion system rotating speed of searching described in step 5 is, in the case where wind speed is certain, by 5 generations The maximum of the function is found in heredity, and the optimal value for finding object function is λ=7.9789, and maximal wind-energy usage factor is CPmax =0.4832；After finding tip speed ratio λ corresponding with maximal wind-energy usage factor, its value is substituted into tip speed ratio formula：In, can obtain corresponding to blower fan rotating speed n,By Above formula calculates to obtain n ≈ 18.36r/s, wind energy conversion system tachometer value i.e. optimal wind energy conversion system rotating speed now.

Claims (3)

1. the wind light mutual complementing maximum power tracing method based on genetic algorithm, it is characterized in that：Described wind light mutual complementing peak power Method for tracing is realized by following steps：
Step 1: determine the wind energy conversion system parameter that blower fan manufacturer provides：Radius, threshold wind velocity, rated wind speed, propeller pitch angle, volume Determine power, peak power, obtain：
CPRepresent power coefficient；λiRepresent optimum tip-speed ratio；
Step 2: can be obtained gradually increasing during the CP (λ) of wind energy conversion system curve increase by MTALAB, then again can be with leaf Tip-speed ratio λ increase reduces rapidly；Power coefficient formula substitution GAs Toolbox is calculated in MATLAB, The maximum CPmax of power coefficient is found, and corresponding tip speed ratio λ value is recorded, substitutes into λ and λ i relation table Up to formula：
In, wind energy conversion system rotating speed n now can be obtained；
Step 3: by the maximum CPmax of the power coefficient obtained in step 2, wind energy conversion system rotating speed n and current wind speed v It is updated in moment coefficient expression formula：In, by calculating the maximum that can show that wind energy conversion system is actual Power P max；
Step 4: according to principle of genetic algorithm, using GAs Toolbox, optimum individual is found；
Step 5: find optimal wind energy conversion system rotating speed；
Step 6: in controller design circuit, the tachometer value of this wind energy conversion system is tracked, just realizes that the peak power of wind energy chases after Track.
2. the wind light mutual complementing maximum power tracing method according to claim 1 based on genetic algorithm, it is characterized in that：Step Described in four according to principle of genetic algorithm, using GAs Toolbox, the process for finding optimum individual is, with reference to wind energy CP- λ characteristic curves and power coefficient formula：Same design is bred Contain 20 population at individual in pond altogether, with reference to CPThe object function that-λ characteristic curves formula representsGeneration gap is set as 0.9, genetic recombination probability is 0.7；Setting 20 initial individuals are only produced immediately, are carried out crisscross inheritance by the use of these initial individuals as parent, are completed to find optimum individual Process.
3. the wind light mutual complementing maximum power tracing method according to claim 1 or 2 based on genetic algorithm, it is characterized in that： The process of the optimal wind energy conversion system rotating speed of searching described in step 5 is, in the case where wind speed is certain, the letter to be found by the heredity of 5 generations Several maximums, the optimal value for finding object function are λ=7.9789, and maximal wind-energy usage factor is CPmax=0.4832；Look for To after tip speed ratio λ corresponding with maximal wind-energy usage factor, its value is substituted into tip speed ratio formula：In, The rotating speed n of blower fan corresponding to can obtaining,N ≈ 18.36r/ are calculated to obtain by above formula S, wind energy conversion system tachometer value i.e. optimal wind energy conversion system rotating speed now.
CN201710579987.0A 2017-07-17 2017-07-17 Wind light mutual complementing maximum power tracing method based on genetic algorithm Pending CN107529587A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108506163A (en) * 2018-04-25 2018-09-07 华北电力科学研究院有限责任公司 A kind of double-fed fan motor virtual synchronous machine rotating speed restoration methods, apparatus and system
CN109779836A (en) * 2018-12-20 2019-05-21 明阳智慧能源集团股份公司 A kind of wind power generating set generated energy method for improving based on genetic algorithm optimizing

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CN102072083B (en) * 2010-12-27 2012-06-13 西安理工大学 Maximum wind energy tracking method for double-fed wind power generation system
US8949097B2 (en) * 2011-08-12 2015-02-03 California Institute Of Technology Methods and systems for comparing vertical axis turbine arrays and providing configurations thereof
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108506163A (en) * 2018-04-25 2018-09-07 华北电力科学研究院有限责任公司 A kind of double-fed fan motor virtual synchronous machine rotating speed restoration methods, apparatus and system
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CN109779836A (en) * 2018-12-20 2019-05-21 明阳智慧能源集团股份公司 A kind of wind power generating set generated energy method for improving based on genetic algorithm optimizing

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Application publication date: 20180102