CN105354632B

CN105354632B - A kind of wind power optimization allocation strategy considering wake effect

Info

Publication number: CN105354632B
Application number: CN201510700582.9A
Authority: CN
Inventors: 孙建龙; 薄鑫; 吴倩; 高丙团; 叶飞; 杨志超
Original assignee: NANJING ELECTRIC POWER ENGINEERING DESIGN Co Ltd; State Grid Corp of China SGCC; Southeast University; Economic and Technological Research Institute of State Grid Jiangsu Electric Power Co Ltd
Current assignee: State Grid Jiangsu Electric Power Design Consultation Co ltd; State Grid Corp of China SGCC; Southeast University; Economic and Technological Research Institute of State Grid Jiangsu Electric Power Co Ltd
Priority date: 2015-10-26
Filing date: 2015-10-26
Publication date: 2019-03-19
Anticipated expiration: 2035-10-26
Also published as: CN105354632A

Abstract

The invention discloses a wind farm power optimization distribution strategy considering the wake effect. The scheme considers the coordination of the active and reactive power output of each wind turbine under the influence of the wake effect, and various restrictions on reactive power optimization in offshore wind farms. Under the conditions, taking the maximum active power output of the offshore wind farm as the optimization goal, the optimization algorithm of the original-dual interior point method is used to obtain the optimal scheme of the power distribution of the offshore wind farm. Compared with the current power distribution schemes of various types of wind farms, considering the influence of the wake effect greatly improves the calculation accuracy of the output power of the wind farm. In addition, an optimal power distribution strategy for offshore wind farms based on the wake effect is proposed. Ensuring the stable operation of grid-connected wind farms while improving the active power output of wind farms is of great significance to the economy and stability of the power system operation including wind farms.

Description

A kind of wind power optimization allocation strategy considering wake effect

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 D_i, the axial inducible factor of the i-th Fans is a_i, then the wind of the i-th Fans Speed distribution V_i(x,r；a_i) are as follows:

V_i(x,r；a_i)=V_∞(1-δV_i(x,r；a_i)) (1)

Wherein: δ V_i(x,r；a_i) be the i-th Fans under wind direction the position (x, r) wind speed, and:

Wherein: with the center (x of the i-th Fans_i,r_i) 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 Fans_i(a) are as follows:

V_i(a)=V_∞(1-δV_i(a)) (3)

Wherein: N is total number of units of blower；A_iThe 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 determined_gi(a) are as follows:

Wherein: ρ is atmospheric density, C_P(a_i) it is power of fan coefficient, C_P(a_i)=4a_i(1-a_i)²；

(22) meter and wake effect, establish the maximum objective function of marine wind electric field active power output:

Wherein: P_giIt (a) is the active power output of the i-th Fans；P_lossFor 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: U_iAnd U_jThe respectively voltage magnitude of node i and node j；θ_ij=θ_i-θ_jFor the voltage of node i and node j Phase angle difference, θ_iFor the voltage phase angle of node i, θ_jFor the voltage phase angle of node j；G_ijFor the transconductance of node i and node j, B_ijFor The mutual susceptance of node i and node j；P_iFor the active power injected to node i, Q_iFor 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:

U_i,min≤U_i≤U_i,max (12)

Wherein:For the active power output of the i-th Fans,For the maximum active power output of the i-th Fans；U_SFor double-fed wind The stator voltage of motor group；I_RFor the rotor current of double-fed fan motor unit；X_MFor the excitation reactance of double-fed fan motor unit；X_SIt 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；U_i,min For the voltage magnitude lower limit of node i, U_i,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:

(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 D_i, the axial direction of the i-th Fans Inducible factor is a_i, then the wind speed profile V of the i-th Fans_i(x,r；a_i) are as follows:

V_i(x,r；a_i)=V_∞(1-δV_i(x,r；a_i)) (1)

(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 machine_i(a) are as follows:

V_i(a)=V_∞(1-δV_i(a)) (3)

1. node power equality constraint are as follows:

Wherein: U_iAnd U_jThe respectively voltage magnitude of node i and node j；θ_ij=θ_i-θ_jFor the voltage of node i and node j Phase angle difference, θ_iFor the voltage phase angle of node i, θ_jFor the voltage phase angle of node j；G_ijFor the transconductance of node i and node j, B_ijFor The mutual susceptance of node i and node j；P_iFor the active power injected to node i, Q_iFor the reactive power injected to node i；

2. running variable inequality constraints are as follows:

U_i,min≤U_i≤U_i,max (12)

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 calculated_Gap=l^Tz+u^TW: if C_Gap< 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 determined_pAnd step_d, and update original variable and glug is bright Day multiplier；

(g) k=k+1 is set: if k < K_max, then return step (c)；Otherwise, (h) is entered step；Wherein, K_maxFor 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. A wind farm power optimization allocation strategy considering wake effect, is characterized in that: comprise the steps:

(1) Based on the wind speed, wind direction and the layout of the offshore wind farm, considering the influence of the wake effect, a modified Parker model for the analysis of the output power of the offshore wind farm is established; the process of establishing the modified Parker model for the analysis of the output power of the offshore wind farm is as follows:

(11) Establish a modified Parker model: Assume that the wind speed of the offshore wind farm is constant v _∞ and the wind direction is perpendicular to the fan surface within a certain period of time, the diameter of the wind blade surface of the ith fan is D _i , and the axial direction of the ith fan is D i . The induction factor is a _i , then the wind speed distribution _Vi ( _xi , ri ; a _i ) of the _ith fan is:

V _i ( _xi , _{ri ; a i} ₎ =V _∞ (1-δV _i ( _xi , _{ri ; a i} ₎ ) (1)

Where: δV _i ( _xi , ri ; a _i ) is the wind speed at the position ( _xi , _ri ) in the downwind direction of the _ith fan, and:

Among them: take the center position ( _xi , ri) of the _ith fan as the reference point, _xi is the distance between the wake generated by the ith fan and the reference point in the wind direction, and ri is the wind generated by the _ith fan The distance between the wake and the reference point in the direction orthogonal to the wind direction; k is the roughness coefficient, which is used to characterize the slope of the fan wake diffusion, and the value of k in the offshore wind farm is 0.04;

(12) Considering the wake effect, the wind speed V _i (a _i ) of the i-th fan is:

V _i (a _i )=V _∞ (1-δV _i (a _i )) (3)

Among them: N is the total number of fans; A _i is the wake area generated by the ith fan; is the overlapping area of the wake of the ith fan and the jth fan;

(2) On the basis of the modified Parker model established in step (1), the output power of the wind turbine is determined by the axial induction factor, and the variable constraints are considered to establish the optimal distribution model of the power of the offshore wind farm; the process of establishing the optimal distribution model of the power of the offshore wind farm as follows:

(21) Through the axial induction factor, determine the output power P _gi (a _i ) of the ith fan as:

Wherein: ρ is the air density, C _P (a _i ) is the fan power coefficient, C _P (a _i )=4a _i (1-a _i ) ² ;

(22) Considering the wake effect, establish the objective function of the maximum active power output of the offshore wind farm:

Among them: P _gi (a) is the active power output of the i-th wind turbine; P _loss is the active power loss in the offshore wind farm;

(23) Variable constraints consist of node power equality constraints and operating variable inequality constraints;

①The node power equation constraint is:

Where: U _i and U _j are the voltage amplitudes of node i and node j respectively; θ _ij =θ _i -θ _j is the voltage phase angle difference between node i and node j, θ _i is the voltage phase angle of node i, θ _j is the voltage phase angle at node j; G _ij is the mutual conductance between node i and node j, B _ij is the mutual susceptance between node i and node j; P _i is the active power injected into node i, and Q _i is the active power injected into node i i injected reactive power;

②The running variable inequality constraint is:

U _i,min ≤U _i ≤U _i,max (12)

in: For the active power output of the i-th fan, is the maximum active power output of the i-th wind turbine; U _S is the stator voltage of the DFIG; I _R is the rotor current of the DFIG; X _M is the excitation reactance of the DFIG; X _S is the DFIG is the stator reactance; s is the slip rate of the double-fed wind turbine; is the reactive power output of the doubly-fed wind turbine; U _i,min is the lower limit of the voltage amplitude of the node i, and U _i,max is the upper limit of the voltage amplitude of the node i

(3) Using the original-dual interior point method optimization algorithm, optimize the power distribution model of the offshore wind farm established in step (2), and obtain the optimal active and reactive power output of each wind power for system scheduling.