CN105354632B - A kind of wind power optimization allocation strategy considering wake effect - Google Patents
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Abstract
The invention discloses a kind of wind powers for considering wake effect to optimize allocation strategy, the program considers the active and idle output for coordinating each Wind turbines under the influence of wake effect, at sea under the various restrictive conditions of wind power plant idle work optimization, it is up to optimization aim with marine wind electric field active power output, using prim al- dual interior point m ethod optimization algorithm, the optimal case of marine wind electric field power distribution is obtained.Compared with current all kinds of wind power allocation plans, consider that the influence of wake effect largely improves the computational accuracy of Power Output for Wind Power Field, furthermore, it proposes that the marine wind electric field power optimization allocation strategy based on wake effect ensures the stable operation of integrated wind plant while improving wind power plant active power output, is of great significance to economy and the stability of the Operation of Electric Systems containing wind power plant.
Description
Technical field
The present invention relates to a kind of wind powers for considering wake effect to optimize allocation strategy, belongs to new energy power generation technology
In wind-power electricity generation control technology.
Background technique
With maintaining sustained and rapid growth for China's economy, energy security has gone up the significant problem as relationship national security.
Greatly develop the important content that new energy has become the adjustment of China's energy strategy, transformation electric power development mode.Wind-power electricity generation with
The advantages that its at low cost, pollution-free and scale and benefit is significant is rapidly developed in recent years.Ended for the end of the year 2013, China is accumulative
Installed capacity 91413MW adds up grid connection capacity 77160MW, is the third-largest power supply after thermoelectricity, water power.China's sea turn
Electric project construction achieves breakthrough, and national offshore wind farm project adds up approval scale about 2220MW, wherein is completed
390MW is distributed mainly on Jiangsu Province and Shanghai City, and Built Projects are grid-connected at present.Compared with land wind power plant, offshore wind farm
Field unit capacity is bigger, and the transport of large-scale wind electricity unit, cost of installation and maintenance are huge, improves marine wind electric field active power output effect
Rate is the important channel that marine wind electric field cuts operating costs.
Current wind power plant generallys use the control program of single machine maximal wind-energy capture to improve the utilization rate of wind energy.However,
Under the influence of wake effect, wind speed can be reduced by upwind Wind turbines.The maximal wind-energy of all Wind turbines of wind power plant
Capture control model cannot be guaranteed that output of wind electric field maximizes.In order to greatly utilize wind energy resources and guarantee that wind power plant is pacified
Full stable operation, it is necessary to establish a kind of wind power optimization allocation strategy for considering wake effect, coordinate each in wind power plant
The active and idle output of Wind turbines, the distribution of wake flow in regulating wind power field.
Power optimization with the continuous expansion of grid-connected marine wind electric field scale, under wind power integration system safe and stable operation
Allocation strategy has expanded extensive research.For different optimization aim and Operation of Wind Power Plant, researcher is proposed
Many wind powers optimize allocation strategies.Current research is often directed to wind power plant, and wind speed is identical in synchronization everywhere
The case where, rarely have and is related to the situation that aerodynamics influences each other under situation.
Summary of the invention
Goal of the invention: consider wake effect not yet to solve current wind generator system power distribution strategies to cause mould
Type is inaccurate, and wind power plant active power output efficiency can be further improved this problem, and the invention proposes a kind of consideration wake flow effects
Answer wind power optimization allocation strategy, the strategy by establish for optimize calculating simplify wake model, to analyze sea
The aerodynamics coupling of each Wind turbines, improves wind-powered electricity generation under the premise of guaranteeing wind power plant safe and stable operation in upper wind power plant
The active power output of field.
Technical solution: to achieve the above object, the technical solution adopted by the present invention are as follows:
A kind of wind power optimization allocation strategy considering wake effect, the strategy consider under the influence of wake effect
Coordinate the active and idle output of each Wind turbines, at sea under the various restrictive conditions of wind power plant idle work optimization, with sea turn
Electric field active power output is up to optimization aim, using prim al- dual interior point m ethod optimization algorithm, obtains marine wind electric field power distribution
Optimal case；The program specifically comprises the following steps:
(1) layout based on wind speed, wind direction and marine wind electric field, the influence of meter and wake effect, establishes offshore wind farm
Amendment Parker's model of field output power analysis；
(2) on the basis of amendment Parker's model that step (1) is established, blower output work is determined by axial inducible factor
Rate, while considering variable bound, establish marine wind electric field power optimization distribution model；
(3) prim al- dual interior point m ethod optimization algorithm is used, the marine wind electric field power optimization distribution model established to step (2)
Calculating is optimized, each typhoon electricity optimal active output and idle output is obtained, is used for system call.
In the step (1), the process of amendment Parker's model of marine wind electric field output power analysis is established are as follows:
(11) it establishes amendment Parker's model: setting in certain time, the constant wind speed of marine wind electric field is v∞And wind direction is vertical
In blower face, the fan blade face diameter of the i-th Fans is Di, the axial inducible factor of the i-th Fans is ai, then the wind of the i-th Fans
Speed distribution Vi(x,r；ai) are as follows:
Vi(x,r；ai)=V∞(1-δVi(x,r；ai)) (1)
Wherein: δ Vi(x,r；ai) be the i-th Fans under wind direction the position (x, r) wind speed, and:
Wherein: with the center (x of the i-th Fansi,ri) it is used as datum mark, x is the wake flow and base that the i-th Fans generate
Distance on wind direction on schedule, r are the wake flow of the i-th Fans generation at a distance from datum mark is on wind direction orthogonal direction；K is thick
Rough coefficient, for characterizing the slope of blower wake flow diffusion, the value of k is 0.04 in marine wind electric field；
(12) meter and wake effect, then the wind speed V of the i-th Fansi(a) are as follows:
Vi(a)=V∞(1-δVi(a)) (3)
Wherein: N is total number of units of blower；AiThe velocity wake region generated for the i-th Fans；For the i-th Fans and
The wake flow overlapping region of j Fans.
In the step (2), the process for establishing marine wind electric field power optimization distribution model is as follows:
(21) by axial inducible factor, the output power P of the i-th Fans is determinedgi(a) are as follows:
Wherein: ρ is atmospheric density, CP(ai) it is power of fan coefficient, CP(ai)=4ai(1-ai)2；
(22) meter and wake effect, establish the maximum objective function of marine wind electric field active power output:
Wherein: PgiIt (a) is the active power output of the i-th Fans；PlossFor the active power loss in marine wind electric field；
(23) variable bound is made of node power equality constraint and operation variable inequality constraints；
1. node power equality constraint are as follows:
Wherein: UiAnd UjThe respectively voltage magnitude of node i and node j；θij=θi-θjFor the voltage of node i and node j
Phase angle difference, θiFor the voltage phase angle of node i, θjFor the voltage phase angle of node j；GijFor the transconductance of node i and node j, BijFor
The mutual susceptance of node i and node j；PiFor the active power injected to node i, QiFor the reactive power injected to node i；In electricity
In Force system, power supply (such as blower) and non-power (such as load) are considered node usually to handle；
2. running variable inequality constraints are as follows:
Ui,min≤Ui≤Ui,max (12)
Wherein:For the active power output of the i-th Fans,For the maximum active power output of the i-th Fans；USFor double-fed wind
The stator voltage of motor group；IRFor the rotor current of double-fed fan motor unit；XMFor the excitation reactance of double-fed fan motor unit；XSIt is double
Present the stator reactance of Wind turbines；S is the revolutional slip of double-fed fan motor unit；For the idle power output of double-fed fan motor unit；Ui,min
For the voltage magnitude lower limit of node i, Ui,maxFor the voltage magnitude upper limit of node i.
The utility model has the advantages that the wind power provided by the invention for considering wake effect optimizes allocation strategy, consider in wake flow
Coordinate the active and idle output of each Wind turbines under the influence of effect, at sea the various restrictive conditions of wind power plant idle work optimization
Under, optimization aim is up to marine wind electric field active power output, using prim al- dual interior point m ethod optimization algorithm, obtains marine wind electric field
The optimal case of power distribution；Compared with current all kinds of wind power allocation plans, this strategy considers the shadow of wake effect
The computational accuracy for largely improving Power Output for Wind Power Field is rung, in addition, proposing the offshore wind farm based on wake effect
Field power optimization allocation strategy ensures the stable operation of integrated wind plant while improving wind power plant active power output, to containing wind-powered electricity generation
The economy of field Operation of Electric Systems is of great significance with stability.
Detailed description of the invention
Fig. 1 is the wind power optimization allocation strategy flow chart for considering wake effect；
Fig. 2 is separate unit blower wake model；
Fig. 3 aerodynamic effects model between Wind turbines；
Fig. 4 is optimization algorithm flow chart.
Specific embodiment
The present invention will be further explained with reference to the accompanying drawing.
Optimize allocation strategy flow chart as shown in Figure 1 for a kind of wind power for considering wake effect, including walks as follows
It is rapid:
(1) layout based on wind speed, wind direction and marine wind electric field, the influence of meter and wake effect, establishes offshore wind farm
Amendment Parker's model of field output power analysis；
(2) on the basis of amendment Parker's model that step (1) is established, blower output work is determined by axial inducible factor
Rate, while considering variable bound, establish marine wind electric field power optimization distribution model；
(3) prim al- dual interior point m ethod optimization algorithm is used, the marine wind electric field power optimization distribution model established to step (2)
Calculating is optimized, each typhoon electricity optimal active output and idle output is obtained, is used for system call.
In the step (1), the process of amendment Parker's model of marine wind electric field output power analysis is established are as follows:
(11) establish amendment Parker's model: separate unit blower wake model is as shown in Fig. 2, set in certain time, offshore wind farm
The constant wind speed of field is v∞And wind direction, perpendicular to blower face, the fan blade face diameter of the i-th Fans is Di, the axial direction of the i-th Fans
Inducible factor is ai, then the wind speed profile V of the i-th Fansi(x,r；ai) are as follows:
Vi(x,r；ai)=V∞(1-δVi(x,r；ai)) (1)
Wherein: δ Vi(x,r；ai) be the i-th Fans under wind direction the position (x, r) wind speed, and:
Wherein: with the center (x of the i-th Fansi,ri) it is used as datum mark, x is the wake flow and base that the i-th Fans generate
Distance on wind direction on schedule, r are the wake flow of the i-th Fans generation at a distance from datum mark is on wind direction orthogonal direction；K is thick
Rough coefficient, for characterizing the slope of blower wake flow diffusion, the value of k is 0.04 in marine wind electric field；
(12) between Wind turbines aerodynamic effects model as shown in figure 3, described by taking 2 Fans as an example wake flow superposition area
Domain, if the wake flow of the 1st Fans all covers the 2nd Fans,Meter and wake effect, then the i-th typhoon
The wind speed V of machinei(a) are as follows:
Vi(a)=V∞(1-δVi(a)) (3)
Wherein: N is total number of units of blower；AiThe velocity wake region generated for the i-th Fans；For the i-th Fans and
The wake flow overlapping region of j Fans.
In the step (2), the process for establishing marine wind electric field power optimization distribution model is as follows:
(21) by axial inducible factor, the output power P of the i-th Fans is determinedgi(a) are as follows:
Wherein: ρ is atmospheric density, CP(ai) it is power of fan coefficient, CP(ai)=4ai(1-ai)2；
(22) meter and wake effect, establish the maximum objective function of marine wind electric field active power output:
Wherein: PgiIt (a) is the active power output of the i-th Fans；PlossFor the active power loss in marine wind electric field；
(23) variable bound is made of node power equality constraint and operation variable inequality constraints；
1. node power equality constraint are as follows:
Wherein: UiAnd UjThe respectively voltage magnitude of node i and node j；θij=θi-θjFor the voltage of node i and node j
Phase angle difference, θiFor the voltage phase angle of node i, θjFor the voltage phase angle of node j；GijFor the transconductance of node i and node j, BijFor
The mutual susceptance of node i and node j；PiFor the active power injected to node i, QiFor the reactive power injected to node i；
2. running variable inequality constraints are as follows:
Ui,min≤Ui≤Ui,max (12)
Wherein:For the active power output of the i-th Fans,For the maximum active power output of the i-th Fans；USFor double-fed wind
The stator voltage of motor group；IRFor the rotor current of double-fed fan motor unit；XMFor the excitation reactance of double-fed fan motor unit；XSIt is double
Present the stator reactance of Wind turbines；S is the revolutional slip of double-fed fan motor unit；For the idle power output of double-fed fan motor unit；Ui,min
For the voltage magnitude lower limit of node i, Ui,maxFor the voltage magnitude upper limit of node i.
Prim al- dual interior point m ethod optimization algorithm flow chart is as shown in figure 4, comprise the following steps that
(a) primitive network parameter is inputted；
(b) data initialization, the number of iterations k=1；
(c) compensation clearance C is calculatedGap=lTz+uTW: if CGap< ε then exports optimal solution, stops calculating；Otherwise, enter
Step (d)；Wherein, z and w is Lagrange multiplier, and l and u are slack variable, and ε is computational accuracy；
(d) the calculation perturbation factorWherein, (0,1) Center Parameter σ ∈, r are the number of inequality constraints；
(e) update equation is solved, △ x, △ y, △ z, △ l, △ u, △ w are obtained；Wherein, Δ x is the amendment of original variable x
Amount, △ y, △ z, △ w are respectively the correction amount of Lagrange multiplier x, y, z, and △ l, △ u are respectively the amendment of slack variable l, u
Amount；
(f) the iteration step length step of original variable and dual variable is determinedpAnd stepd, and update original variable and glug is bright
Day multiplier；
(g) k=k+1 is set: if k < Kmax, then return step (c)；Otherwise, (h) is entered step；Wherein, KmaxFor greatest iteration
Number；
(h) it calculates and does not restrain, exit the program.
The above is only a preferred embodiment of the present invention, it should be pointed out that: for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered
It is considered as protection scope of the present invention.
Claims (1)
1. a kind of wind power for considering wake effect optimizes allocation strategy, characterized by the following steps:
(1) layout based on wind speed, wind direction and marine wind electric field, considers the influence of wake effect, it is defeated to establish marine wind electric field
Amendment Parker's model of power analysis out；Establish the process of amendment Parker's model of marine wind electric field output power analysis are as follows:
(11) it establishes amendment Parker's model: setting in certain time, the constant wind speed of marine wind electric field is v∞And wind direction is perpendicular to wind
Machine side, the fan blade face diameter of the i-th Fans are Di, the axial inducible factor of the i-th Fans is ai, then the wind speed of the i-th Fans divides
Cloth Vi(xi,ri；ai) are as follows:
Vi(xi,ri；ai)=V∞(1-δVi(xi,ri；ai)) (1)
Wherein: δ Vi(xi,ri；ai) be the i-th Fans under wind direction (xi,ri) position wind speed, and:
Wherein: with the center (x of the i-th Fansi,ri) it is used as datum mark, xiThe wake flow and benchmark generated for the i-th Fans
Distance of the point on wind direction, riFor the i-th Fans generate wake flow at a distance from datum mark is on wind direction orthogonal direction；K is thick
Rough coefficient, for characterizing the slope of blower wake flow diffusion, the value of k is 0.04 in marine wind electric field；
(12) consider wake effect, then the wind speed V of the i-th Fansi(ai) are as follows:
Vi(ai)=V∞(1-δVi(ai)) (3)
Wherein: N is total number of units of blower；AiThe velocity wake region generated for the i-th Fans；For the i-th Fans and jth typhoon
The wake flow overlapping region of machine；
(2) on the basis of amendment Parker's model that step (1) is established, blower output power is determined by axial inducible factor, together
When consider variable bound, establish marine wind electric field power optimization distribution model；Establish marine wind electric field power optimization distribution model
Process it is as follows:
(21) by axial inducible factor, the output power P of the i-th Fans is determinedgi(ai) are as follows:
Wherein: ρ is atmospheric density, CP(ai) it is power of fan coefficient, CP(ai)=4ai(1-ai)2；
(22) consider wake effect, establish the maximum objective function of marine wind electric field active power output:
Wherein: PgiIt (a) is the active power output of the i-th Fans；PlossFor the active power loss in marine wind electric field；
(23) variable bound is made of node power equality constraint and operation variable inequality constraints；
1. node power equality constraint are as follows:
Wherein: UiAnd UjThe respectively voltage magnitude of node i and node j；θij=θi-θjFor the voltage phase angle of node i and node j
Difference, θiFor the voltage phase angle of node i, θjFor the voltage phase angle of node j；GijFor the transconductance of node i and node j, BijFor node i
With the mutual susceptance of node j；PiFor the active power injected to node i, QiFor the reactive power injected to node i；
2. running variable inequality constraints are as follows:
Ui,min≤Ui≤Ui,max (12)
Wherein:For the active power output of the i-th Fans,For the maximum active power output of the i-th Fans；USFor double-fed fan motor machine
The stator voltage of group；IRFor the rotor current of double-fed fan motor unit；XMFor the excitation reactance of double-fed fan motor unit；XSFor double-fed wind
The stator reactance of motor group；S is the revolutional slip of double-fed fan motor unit；For the idle power output of double-fed fan motor unit；Ui,minFor section
The voltage magnitude lower limit of point i, Ui,maxFor the voltage magnitude upper limit of node i
(3) prim al- dual interior point m ethod optimization algorithm is used, the marine wind electric field power optimization distribution model that step (2) are established is carried out
Optimization calculates, and obtains each typhoon electricity optimal active output and idle output, is used for system call.
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| CN107784386B (en) * | 2016-08-31 | 2021-12-03 | 中国电力科学研究院 | Wind power plant fan optimal arrangement method and system based on wind speed attenuation factor |
| WO2018050185A1 (en) * | 2016-09-16 | 2018-03-22 | Vestas Wind Systems A/S | Reactive power production of wind turbine generators within wind wake zone |
| CN106960254B (en) * | 2017-03-14 | 2020-09-22 | 华南理工大学 | Optimal configuration method for capacity of electric-to-gas equipment considering wind power consumption |
| CN109946475B (en) * | 2017-12-21 | 2020-04-17 | 新疆金风科技股份有限公司 | Method and device for determining wind speed |
| CN111245008B (en) * | 2020-01-14 | 2021-07-16 | 香港中文大学（深圳） | Wind field cooperative control method and device |
| CN111310972B (en) * | 2020-01-17 | 2022-06-03 | 上海电力大学 | Offshore wind turbine maintenance path random planning method considering wake effect |
| CN111614088B (en) * | 2020-06-09 | 2021-09-21 | 三一重能股份有限公司 | Energy management method considering wake flow influence |
| CN113688581B (en) * | 2021-07-28 | 2024-08-09 | 国网冀北张家口风光储输新能源有限公司 | Method, device, electronic equipment and medium for optimally controlling active output of wind power plant |
| CN115912484B (en) * | 2022-12-08 | 2024-02-20 | 南方电网数字电网研究院有限公司 | Wind power plant power rapid control system providing active supporting capability of power grid |
| CN116357517B (en) * | 2023-04-12 | 2024-10-29 | 中国长江三峡集团有限公司 | Wind farm group cooperative control method and device, computer equipment and medium |
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| CN103886185A (en) * | 2014-03-05 | 2014-06-25 | 中国东方电气集团有限公司 | Annual wind speed generation method for wind resource assessment |
| CN104331621A (en) * | 2014-11-05 | 2015-02-04 | 中国大唐集团新能源股份有限公司 | Wind resource computation method |
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Address after: 210008 No. 251, Gulou District, Jiangsu, Zhongshan Road, Nanjing Co-patentee after: STATE GRID JIANGSU ELECTRIC POWER DESIGN CONSULTATION Co.,Ltd. Patentee after: JIANGSU ELECTRIC POWER COMPANY ECONOMIC Research Institute Co-patentee after: SOUTHEAST University Co-patentee after: State Grid Corporation of China Address before: 210008 No. 251, Gulou District, Jiangsu, Zhongshan Road, Nanjing Co-patentee before: NANJING ELECTRIC POWER ENGINEERING DESIGN Co.,Ltd. Patentee before: JIANGSU ELECTRIC POWER COMPANY ECONOMIC Research Institute Co-patentee before: SOUTHEAST University Co-patentee before: State Grid Corporation of China |