CN114336787B - Method and system for optimizing configuration of active power of wind power plant and computer readable storage medium - Google Patents
Method and system for optimizing configuration of active power of wind power plant and computer readable storage medium Download PDFInfo
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Abstract
The embodiment of the invention provides an optimal configuration method and system for active power of a wind farm and a computer readable storage medium. The method comprises the following steps: establishing an equivalent network of a wind power plant, wherein the equivalent network of the wind power plant comprises a plurality of groups of equivalent fans which are respectively connected to an alternating current bus through power transmission lines; selecting at least one group of equivalent fans from a plurality of groups of equivalent fans as relaxation nodes, and determining the trend distribution of the wind power plant at the static wind speed based on the active scheduling instruction of the wind power plant and the established equivalent network of the wind power plant; establishing a dynamic mathematical model of the wind farm at a dynamic wind speed; establishing an active power instruction optimization model of the wind power plant based on rotor kinetic energy maximization; and carrying out active power configuration based on rotor kinetic energy optimization at dynamic wind speed based on the trend distribution of the wind power plant at static wind speed and the established active power instruction optimization model of the wind power plant and the dynamic mathematical model of the wind power plant. Thereby achieving the goal of active modulation and maximization of stored rotor kinetic energy.
Description
Technical Field
The embodiment of the invention relates to the technical field of wind power generation, in particular to an optimal configuration method and system for active power of a wind farm and a computer readable storage medium.
Background
Along with the gradual exhaustion of energy sources such as coal, petroleum and the like, people pay more attention to the utilization of renewable energy sources. Wind energy is becoming increasingly important worldwide as a clean renewable energy source. With the continuous development of wind power technology, fans are increasingly applied to power systems. Wind farms are built in places where wind energy resources are abundant.
Due to the characteristics of fluctuation, randomness, uncertainty and the like of wind power resources, the frequency of a wind power plant inevitably fluctuates, so that the realization of effective response to the power grid active power scheduling instruction is an effective method for supporting the frequency of the power grid. Meanwhile, active loss is inevitably generated in the power transmission lines in the wind power stations and among the stations, and the influence on the effectiveness, instantaneity and the like of active power control of the wind power stations is further aggravated.
The existing wind power plant generally adopts a maximum power point tracking (Maximum Power Point Tracking, MPPT) control mode, takes the maximization of active power of a fan as a main target, mainly considers the real-time output active power value of the fan when the wind power plant issues a scheduling instruction, and less considers the influence of active loss of a power transmission line of the wind power plant on the overall active power configuration of the wind power plant. Meanwhile, under the influence of wind farm wake effect, wind speed conditions faced by the fans are unbalanced, so that active power adjustment capability borne by each group of fans is not equal, the existing method ignores the characteristic that active power adjustment and frequency support capability of each group of fans on the wind farm are not identical, and therefore an optimization strategy of active power configuration in the wind farm cannot be realized.
Disclosure of Invention
The embodiment of the invention aims to provide an optimal configuration method and system for active power of a wind power plant and a computer readable storage medium, which can ensure the realization of an active regulation target and the maximization of the stored rotor kinetic energy in the wind power plant.
One aspect of the embodiment of the invention provides an optimal configuration method for active power of a wind farm. The method comprises the following steps: establishing an equivalent network of a wind power plant, wherein the equivalent network of the wind power plant comprises a plurality of groups of equivalent fans which are respectively connected to an alternating current bus through power transmission lines; selecting at least one group of equivalent fans from the plurality of groups of equivalent fans as relaxation nodes, and determining the power flow distribution of the wind power plant at the static wind speed based on the active scheduling instruction of the wind power plant and the established equivalent network of the wind power plant; establishing a dynamic mathematical model of the wind power plant at a dynamic wind speed; establishing an active power instruction optimization model of the wind power plant based on rotor kinetic energy maximization; and carrying out active power configuration based on rotor kinetic energy optimization at dynamic wind speed based on the trend distribution of the wind power plant at static wind speed, the established active power instruction optimization model of the wind power plant and the dynamic mathematical model of the wind power plant.
Another aspect of the embodiment of the invention also provides an optimal configuration system for active power of the wind farm. The system comprises one or more processors, and is used for realizing the optimal configuration method of the active power of the wind farm according to the above embodiments.
Yet another aspect of the embodiments of the present invention further provides a computer readable storage medium having a program stored thereon, where the program is executed by a processor to implement the method for optimizing configuration of active power of a wind farm according to the foregoing embodiments.
According to the wind power plant active power optimizing configuration method, the wind power plant active power optimizing configuration system and the wind power plant active power optimizing configuration computer readable storage medium, active power instruction optimizing models of wind power plants based on rotor kinetic energy maximization and dynamic mathematical models of wind power plants under dynamic wind speed are established by comprehensively considering active power loss of power transmission lines in and among the wind power plants and wake effects of the wind power plants, optimal configuration of each group of equivalent wind power plants active power in the wind power plants is achieved, effective response of the wind power plants to power grid active power output requirements is achieved, maximization of rotor storage kinetic energy in the wind power plants is guaranteed, system frequency supporting capacity of high-proportion access wind power plants is fully exerted, and the wind power plant active power optimizing configuration method is well suitable for engineering application of wind power plant active frequency modulation optimizing technology.
Drawings
FIG. 1 is a flowchart of a method for optimizing configuration of active power of a wind farm according to an embodiment of the present invention;
FIG. 2 is an equivalent network of a wind farm according to one embodiment of the present invention;
FIG. 3 is an equivalent circuit diagram of a wind farm performing power flow calculations according to one embodiment of the present invention;
fig. 4 is an equivalent circuit diagram of an inverter according to an embodiment of the present invention;
FIG. 5 is a schematic illustration of a power curve of a fan in a de-load mode;
FIG. 6 shows the scaling factor K of the PI controller according to one embodiment of the invention P An influence curve on the active power P4 of the point of connection;
FIG. 7 shows the integral coefficient K of the PI controller according to one embodiment of the present invention I An influence curve on the active power P4 of the point of connection;
fig. 8 is a schematic block diagram of a wind farm active power optimization configuration system according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Rather, they are merely examples of apparatus consistent with aspects of the invention as detailed in the accompanying claims.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. Unless defined otherwise, technical or scientific terms used in the embodiments of the present invention should be given the ordinary meaning as understood by one of ordinary skill in the art to which the present invention belongs. The terms first, second and the like in the description and in the claims, are not used for any order, quantity or importance, but are used for distinguishing between different elements. Likewise, the terms "a" or "an" and the like do not denote a limitation of quantity, but rather denote the presence of at least one. "plurality" or "plurality" means two or more. Unless otherwise indicated, the terms "front," "rear," "lower," and/or "upper" and the like are merely for convenience of description and are not limited to one location or one spatial orientation. The word "comprising" or "comprises", and the like, means that elements or items appearing before "comprising" or "comprising" are encompassed by the element or item recited after "comprising" or "comprising" and equivalents thereof, and that other elements or items are not excluded. The terms "connected" or "connected," and the like, are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any or all possible combinations of one or more of the associated listed items.
The embodiment of the invention provides an optimal configuration method for active power of a wind farm. Fig. 1 discloses a flowchart of a method for optimizing configuration of active power of a wind farm according to an embodiment of the present invention. As shown in fig. 1, the method for optimizing the active power of a wind farm according to an embodiment of the present invention may include steps S1 to S5.
When the wind farm is in grid-connected operation, the wind farm control executes active power scheduling and reactive power instructions issued by an AGC (Automatic Generation Control, automatic power generation control)/AVC (Automatic Voltage Control ) system, and the active power optimization configuration scheme of the wind farm is designed to meet the requirements of the active power scheduling instructions.
Firstly, in step S1, an equivalent network of a wind farm is established, the equivalent network of the wind farm includes a plurality of groups of equivalent fans connected to an ac bus in series and/or in parallel through power transmission lines, and the equivalent network of the wind farm has a plurality of groups of access points to which the equivalent fans are connected.
In one embodiment, the multiple groups of equivalent fans of the wind farm may include, for example, multiple groups of fans collected in a single wind farm, which may be connected to grid-connected points through power transmission lines, respectively. In another embodiment, the multiple groups of equivalent fans of the wind farm may include multiple sub-wind farms, for example, which may be connected to grid-connected points through power transmission lines, respectively.
In a real worldIn an embodiment, the equivalent network of the wind farm may be established by a radial network. In the following, three groups of equivalent fans are taken as examples to establish an equivalent network of the wind power plant. Figure 2 discloses an equivalent network of a wind farm according to an embodiment of the invention. As shown in fig. 2, three exhaust fans of the wind farm respectively form three groups of equivalent fans, and the three exhaust fans are respectively connected to grid connection points through power transmission lines 1,2 and 3. Wherein each exhaust fan can comprise n fans, and the injected power of the n fans is represented by a group of equivalent fans instead. V (V) 1 ～V 3 For the voltage of each exhaust fan access point, V 4 For the grid-connected point voltage of the wind power plant, and all voltages are reduced to 35kV, all power transmission lines adopt a standard quasi-steady-state RX model, X l1 、R l1 ，X l2 、R l2 ，X l3 、R l3 The equivalent reactance X and the equivalent resistance R of the power transmission lines 1,2 and 3 are obtained.
Considering the wake effect of the wind farm, the wind speed of the wind farm can be calculated according to the formula v 1 >v 2 >v 3 Given.
Fig. 3 discloses an equivalent circuit diagram of a wind farm performing a load flow calculation according to an embodiment of the present invention. As shown in fig. 3, P 1 、Q 1 ，P 2 、Q 2 ，P 3 、Q 3 Active power and reactive power of three groups of equivalent fans respectively; p (P) l1 、Q l1 ，P l2 、Q l2 ，P l3 、Q l3 The injection power from the initial end to the final end in the power transmission lines 1,2 and 3 respectively; p (P) 4 、Q 4 Active and reactive power (i.e., active and reactive power of a grid connection point) is injected into the power grid for the wind farm; i 1 ～I 3 For the current flowing through the transmission lines 1,2, 3; v (V) 1 ～V 4 Is a voltage of 4 nodes.
Referring back to fig. 1, in step S2, at least one set of equivalent fans is selected from the sets of equivalent fans as a relaxation node, and the power flow distribution of the wind farm at the static wind speed is determined based on the active scheduling instruction of the wind farm and the established equivalent network of the wind farm.
Under the static wind speed condition, an active power distribution strategy of the wind farm is designed, so that the power flowing to a power grid (namely the grid connection point shown in fig. 2 and 3) at the outlet of the wind farm meets the requirements of an AGC/AVC instruction.
First, the wind energy received by each set of equivalent fans is different due to the wake effect, and thus the actual maximum active force of each set of fans is different. Secondly, active power loss of the wind farm is also necessarily present, and active power distribution needs to consider the iteration problem of loss. Therefore, to make the active power of the wind farm meet the active scheduling command of the grid-connected point, it is not reasonable to completely and evenly distribute the active power of each group of equivalent fans.
Thus, in an embodiment of the present invention, at least one set of equivalent fans (e.g., an array of equivalent fans) is selected from a plurality of sets of equivalent fans in a wind farm as a relaxation node for balancing the active power loss of the wind farm.
In some embodiments, the active scheduling instructions of the wind farm may be distributed to a plurality of groups of equivalent fans according to a predetermined active power distribution rule, and then the power flow distribution of the wind farm at the static wind speed is determined based on the equivalent network of the wind farm and the predetermined active power distribution rule.
In one embodiment, distributing the active scheduling instructions of the wind farm to the plurality of groups of equivalent fans according to a predetermined active power distribution rule may include: and distributing the active scheduling instructions of the wind power plant to a plurality of groups of equivalent fans according to an equal proportion distribution rule. The equal proportion distribution rule is that the fan utilization rate of each group of equivalent fans is equal, namely the active power emitted by each group of equivalent fans is determined according to the same fan utilization rate.
The three sets of equivalent fans shown in fig. 2 and 3 will be exemplified below. Assume that the maximum operating power of three groups of equivalent fans in the wind power plant is P respectively 1max 、P 2max 、P 3max Namely, the running power of the fans under MPPT control can be obtained according to the following dynamic mathematical model of the wind power plant to be established, and the maximum active output of each group of equivalent fans and the wind power plant overall is respectively as follows:
wherein ρ is the air density coefficient, R is the impeller radius of the fan, C p Is the maximum wind energy utilization coefficient.
The fan utilization is equal to the ratio of the active scheduling instruction of the wind power plant to the sum of the maximum output power emitted by a plurality of groups of equivalent fans, for example, as follows:
wherein eta is the utilization rate of the fan and P 4 ref Instructions are scheduled for the active of the wind farm.
When eta=1, the active force of each group of equivalent fans is the maximum value; when eta <1, the equivalent fans are not fully distributed in each group for load shedding control.
The active power of all three groups of equivalent fans when operating according to the equal proportion distribution rule can be expressed as:
P 1 ＝ηP 1max
P 2 ＝ηP 2max
P 3 ＝ηP 3max (3)
however, consider that inWhen the wind farm actually operates, due to active power loss, if three groups of equivalent fans all perform active output according to the same fan utilization rate, the active power P of the grid-connected point can be caused 4 ＜P 4 ref . Therefore, the embodiment of the invention can ensure that the active power output of the first two groups of equivalent fans always operates according to the given fan utilization rate eta, and the third group of equivalent fans are used as relaxation nodes to balance the active power loss in the wind power plant, thereby being used for meeting the requirements of active scheduling instructions of the wind power plant.
How to let the third set of equivalent fans act as relaxation nodes to balance the active power loss in the wind farm will be described in detail below.
Active and reactive scheduling instructions at a given wind farm grid connection point, i.e. P 4 ref +jQ 4 ref Active power P of three groups of equivalent fans under equal proportion distribution rule 1 、P 2 、P 3 Considering that the wind farm is a radial network, a push-forward substitution method may be employed in some embodiments to determine the tidal current distribution of the wind farm at static wind speeds. Determining a tidal current distribution of the wind farm at static wind speeds may include: active power emitted by an equivalent fan serving as a relaxation node is determined to balance active power loss of the wind power plant so as to meet the requirements of active scheduling instructions. Thus, the active power of the third group of equivalent fans is finally obtained. When the third group of equivalent fans run at the calculated value, the power of the grid-connected point at the outlet of the wind power plant can reach the instruction value P 4 ref +jQ 4 ref . Therefore, the wind farm can realize the active scheduling target under the condition of stable wind speed and comprehensively considering the loss of the power transmission line.
The specific calculation steps for determining the tide distribution of the wind farm at the static wind speed by adopting the forward push back substitution method are as follows:
(A) Forward calculation process:
assume that all nodes are 35 < 0- ° Under the condition of not considering the voltage drop and the loss of the power transmission line, the active power loss of the wind power plant is calculated preliminarily, and the power transmission line 1 can be obtainedThe power and line losses are as follows:
the power and line loss on the transmission line 2 are obtainable by kirchhoff current theorem (KCL) as follows:
when the active power loss of the wind power plant is calculated for the first time, the active power sent by the third group of equivalent fans can be initially determined according to the equal proportion distribution rule, so that the power and the line loss on the power transmission line 3 can be obtained as follows:
wherein P is 4 ＝P l3 ，Q 4 ＝Q l3 . The active power and the reactive power P of the point of connection calculated at the moment l3 And Q l3 Less than the desired P 4 ref +jQ 4 ref And (4) carrying out correction calculation again, and keeping the given voltage value unchanged.
In the second calculation, the power and line loss on transmission line 1 can be obtained as follows:
the power and line losses on the transmission line 2 available from KCL are as follows:
the power and line losses on the transmission line 3 are also available as follows:
the active power of the first two groups of equivalent fans is kept unchanged, and the active power and the reactive power of the grid-connected point can be enabled to be P required by actual active and reactive scheduling instructions by correcting the active power of the third group of equivalent fans 4 ref +jQ 4 ref And are consistent.
The node voltage of the wind farm is corrected as follows:
(B) And (3) a back-substitution calculation process:
and re-performing back-substitution calculation on the loss of the power transmission line 1, the power transmission line 2 and the power transmission line 3.
The power and line losses on the available transmission line 1 are as follows:
the power and line losses on the transmission line 2 available from KCL are as follows:
the power and line losses on the transmission line 3 are also available as follows:
wherein P, Q is added with " . "Hejia" .. "indicates the results obtained by the calculation of different times, respectively.
(C) And (3) after the previous push back process is finished, the updated voltage is used for carrying out the previous push back calculation again in the step (B), the approximate power of the whole network is updated, and the updated approximate power is used for carrying out the next push back calculation.
If the active power P of the point of connection 4 And reactive power Q 4 (i.e. power P l3 And Q l3 ) P required by actual active and reactive scheduling instructions 4 ref +jQ 4 ref If the power flow is inconsistent, repeatedly correcting according to the formula (10), continuously correcting the voltage according to the formula (11), and repeatedly carrying out power flow calculation until the active power P of the grid-connected point is finally obtained 4 And reactive power Q 4 (i.e. power P l3 And Q l3 ) P with actual active and reactive scheduling requirements 4 ref +jQ 4 ref Consistent results. At this time, the back-substitution calculation is stopped, so that the accurate voltage, current and power flow distribution of the wind farm can be obtained, wherein the active power reference value and the reactive power reference value of the third group of equivalent fans serving as the relaxation nodes can be respectively expressed as follows:
wherein,respectively representing an active power reference value and a reactive power reference value of a third group of equivalent fans as relaxation nodes, < ->The active power loss value and the reactive power loss value of the transmission lines 1,2 and 3 obtained by the last calculation are respectively shown.
Therefore, the active power and the reactive power of the three groups of equivalent fans can be respectively given through the calculation, and the following steps are shown:
under the static wind speed condition, when three groups of equivalent fans of the wind power plant respectively run under the above conditions, the output of the wind power plant can meet the requirements of AGC/AVC instructions.
With continued reference to fig. 1, in step S3, a dynamic mathematical model of the wind farm at dynamic wind speeds is established.
The specific establishment process of the dynamic mathematical model of the wind power plant comprises the following aspects:
(1) Dynamic mathematical model of fan
At dynamic wind speed, the formula of the mechanical power of the fan is:
wherein P is wi For the mechanical power of the i-th equivalent fan, C p The wind energy utilization coefficient is lambda, the tip speed ratio, beta, the pitch angle, rho, the air density coefficient, R, the impeller radius of the fan and v, the wind speed.
The equation of motion of the fan rotor is:
wherein P is wi And P ei Wind energy captured by the ith equivalent fan (namely mechanical power of the ith equivalent fan) and output active power H i Is the inertia constant omega of the ith equivalent fan group ri Is the rotation speed of the ith equivalent fan.
Under the Maximum Power Point Tracking (MPPT) working mode, the electromagnetic power reference value of the fanEqual to the maximum mechanical power P of the fan wmax . By fan C p The curve shows that when the pitch angle beta is constant to be 0, the fan reaches the maximum mechanical power P when the rotating speed of the fan changes wmax Time C pmax Is kept unchanged, so that the maximum mechanical power P of the fan is kept constant in the maximum power point tracking working mode wmax The ratio of the electromagnetic power reference value to the third power of the rotating speed is proportional to the third power of the rotating speed, which can be expressed as:
wherein,for the electromagnetic power reference value omega of the ith group of equivalent fans ri The rotation speed of the i-th equivalent fan is set. C under the maximum power point tracking working mode when the pitch angle beta is unchanged pmax The pitch angle beta remains constant, and therefore the tip speed ratio lambda remains constant. From lambda i ＝ω ri R/v i At a fixed wind speed v i With an optimal rotational speed omega opt Corresponding lambda opt Then:
by the above formula, the coefficient C is obtained as:
(2) Dynamic response model of converter
The converters in wind farms are assumed to be typical three-phase two-level converters, which mainly comprise a converter station consisting of IGBTs (Insulated Gate Bipolar Transistor, insulated gate bipolar transistors), a converter reactor and a dc capacitor. Fig. 4 discloses an equivalent circuit diagram of an inverter according to an embodiment of the invention. As shown in fig. 4, the voltage equation of the ac system can be obtained by defining the current direction flowing from the converter station to the ac system as the reference direction:
in the above-mentioned formula(s),the voltage of the alternating current side of the converter station under the abc coordinate system; />Is the system voltage in the abc coordinate system; l (L) c Equivalent inductance of the converter reactor; r is R c Is the equivalent resistance of the converter reactor; i.e abc The current of the alternating current side of the converter station under the abc coordinate system; m is m abc The modulation ratio of the converter under the abc coordinate system; u (u) dc Is the voltage on the dc side of the converter station.
The active power and the reactive power output by the single-group equivalent fans are respectively as follows:
wherein,and->Active power references for i-th group of equivalent fans, respectivelyValue and reactive power reference value, T 1 、T 2 The response times of the active and reactive controllers in the wind farm, respectively.
The dynamic equation of the fan in the time domain can be obtained by carrying out Laplace's inverse transformation on the formula:
wherein P is ei And Q ei Respectively the active power and the reactive power output by the ith group of equivalent fans,and->The active power reference value and the reactive power reference value of the i-th equivalent fan are respectively.
(3) Dynamic mathematical model of wind power plant
In summary, the dynamic mathematical model of the wind farm includes a formula of mechanical power of each set of equivalent fans, a rotor motion equation of each set of equivalent fans, a dynamic equation of each set of equivalent fans in a time domain, and an equation of an electromagnetic power reference value of each set of equivalent fans, as follows:
the dynamic mathematical model of the wind farm comprises three state variables including P ei 、Q ei 、ω ri The method is characterized in that the active power and the reactive power output by each group of equivalent fans are respectively the rotating speed of each group of equivalent fans. The requirements of the AGC/AVC instruction can be met by adjusting the output of fans with different values.
With continued reference to FIG. 1, in step S4, an active power command optimization model of the wind farm based on rotor kinetic energy maximization is established.
Considering that a large power grid requires a wind power plant to have certain frequency modulation capability, when the power grid frequency is reduced, the wind power plant is required to participate in frequency modulation. The most common frequency modulation strategy of the wind power plant is to control the fan to operate in a load shedding mode, so that the fan is required to deviate from an MPPT curve, redundant active power is stored through rotor acceleration, and therefore when the frequency of a power grid is reduced, the active power can be released through the fan to ensure stable support of the frequency.
FIG. 5 discloses a schematic diagram of a power curve of a fan in a de-load mode. As shown in fig. 5, when the fan operates at the point a, the fan adopts MPPT control; when the rotor speed is increased to omega tdel The fan runs at the point B, and the mechanical power at the moment is P wdel Wherein the kinetic energy stored in the rotor per unit time t is as follows:
ΔP＝P wmax -P wdel (18)
wherein DeltaP is kinetic energy stored in the inner rotor in unit time, P wmax For maximum active power of fan operating in MPPT mode, P wdel Is the active power of the fan in the load shedding mode.
When the load is increased and the frequency of the power grid is reduced, the active output of the fan can be increased by reducing the rotating speed to participate in the frequency modulation of the power grid. When the fan works in the load shedding mode, the utilization rate eta of the fan<1, the rotating speeds of the three groups of equivalent fans are higher than the rotating speeds of the MPPTThe rotation speed in the mode can be used for optimally distributing the output of three groups of equivalent fans through an interior point method, and determining the rotation speed omega of the three groups of equivalent fans in the load shedding mode tdel The wind power plant can meet the requirements of AGC/AVC instructions in a load shedding mode, the kinetic energy stored by the rotor can be maximized, and the capacity of the wind power plant for participating in power grid frequency modulation is improved.
Thus, in some embodiments of the invention, building an active power command optimization model of a wind farm based on rotor kinetic energy maximization may include: and solving an optimization problem of an active power instruction of the wind power plant with maximized rotor kinetic energy of each group of equivalent fans by adopting an interior point method to determine the rotating speed of each group of equivalent fans in a load shedding mode.
The optimization problem of the active power command of the wind farm with the maximized rotor kinetic energy of each group of equivalent fans is as follows:
wherein f (x) is the kinetic energy of the rotor, n represents the number of equivalent fans of a plurality of groups, omega topti Is the rotating speed omega of the ith group of equivalent fans in the MPPT working mode tdeli Is the rotating speed omega of the ith group of equivalent fans in the load shedding mode tmaxi Is the maximum rotation speed allowed by the ith equivalent fan, J i The rotational inertia of the ith equivalent fan, P 1 、P 2 、…、P n Respectively represents the active power emitted by each group of equivalent fans,representing active scheduling instructions of wind power plant, Q 1 、Q 2 、…、Q n Respectively representing reactive power emitted by equivalent fans of each group, < >>Representing reactive scheduling instructions for the wind farm.
For the three sets of equivalent fans embodiments shown in fig. 2 and 3, then n=3.
Therefore, the minimum value of the opposite numbers of the objective function can be solved through an interior point method, and the optimized result is the rotating speed and reactive power of the three groups of equivalent fans in the load shedding mode.
The strategy is a static optimization process under the condition that the wind speed is stable, namely, the active power loss and the distribution condition of the wind power plant after rotor kinetic energy optimization under a single wind speed are only considered. In the actual running process, the wind speed is continuously changed, and meanwhile, the converter and the PI controller of the wind power plant have corresponding dynamic response time and other influences. Thus, in the next step, the active power allocation strategy for the dynamic wind speed case will be considered.
In step S5, active power configuration based on rotor kinetic energy optimization at dynamic wind speed is performed based on the trend distribution of the wind farm at the static wind speed determined in step S2, the dynamic mathematical model of the wind farm established in step S3, and the active power instruction optimization model of the wind farm established in step S4.
The active power configuration based on rotor kinetic energy optimization at dynamic wind speed in step S5 comprises: the rotor kinetic energy is optimized for optimizing the active power configuration of the wind farm per predetermined optimization time period based on the real-time wind speed of each set of equivalent fans measured per predetermined optimization time period.
The active power emitted by each group of equivalent fans in the preset optimization time can be determined based on the dynamic mathematical model of the wind power plant and the power flow distribution of the wind power plant according to the real-time wind speed of each group of equivalent fans measured in the preset optimization time. Wherein, the determining the active power sent by each group of equivalent fans within the preset optimization time length comprises the following steps: the active power of the equivalent fan serving as the relaxation node is dynamically confirmed in each preset step length within the preset optimization time, so that the accuracy of determining the active power loss of the wind power plant within the preset optimization time can be improved, and the accuracy of determining the active power of the equivalent fan serving as the relaxation node can be further improved.
The third group of equivalent fans serving as the relaxation nodes have the functions of balancing the active power loss of the wind power plant to ensure the active power P of the grid-connected point 4 Reach toActive dispatch instruction P 4 ref Is expressed as P 4 ref -P 4 As input quantity, the PI (Proportional Integral ) controller of the wind power plant can be used for adjusting the active power reference value sent by the third group of equivalent fans serving as relaxation nodes, and the PI controller parameters K P 、K I P 4 The deviation is determined, and the mathematical model of the PI controller is as follows:
wherein K is P 、K I The proportional and integral coefficients of the PI controller, respectively.
The rotor kinetic energy may then be optimized based on the active power emitted by each set of equivalent fans for a predetermined optimization period, thereby to optimize the active power configuration of the wind farm.
In some embodiments, optimizing rotor kinetic energy based on active power emitted by each set of equivalent fans for a predetermined optimization time period for optimizing active power configurations of a wind farm may include: determining the rotating speed of each group of equivalent fans in a load shedding mode based on an active power instruction optimization model of the wind power plant with the maximum rotor kinetic energy, wherein the active power is sent out by each group of equivalent fans in a preset optimization time; determining the maximum kinetic energy which can be stored by the rotor of each group of equivalent fans based on the determined rotating speed of each group of equivalent fans in the load shedding mode; and storing the maximum kinetic energy which can be stored by the rotors of each group of equivalent fans by controlling the rotation speed of the rotors for releasing the kinetic energy when the frequency of the power grid is reduced so as to support the active power output of the wind power plant.
Referring to fig. 5 and equation (18) above, the maximum kinetic energy that can be stored by the rotor of each set of equivalent blowers may be determined based on the determined rotational speed of each set of equivalent blowers in the load shedding mode and the rotational speed of each set of equivalent blowers operating in the maximum power point tracking mode.
In the method for optimizing and configuring the active power of the wind farm, which is disclosed by the embodiment of the invention, the power equal proportion distribution strategy and the power equal proportion distribution strategy are adoptedThe optimal power distribution strategy of rotor kinetic energy optimized once every preset optimization time length needs to use a PI controller to control P 3 ref Adjusting the proportional coefficient K of the PI controller P Integral coefficient K I When different values are taken, the effects of the PI controller are different.
The wind speeds received by the three groups of equivalent fans are 13m/s, 12.5m/s and 12m/s respectively, and the AGC/AVC gives an instruction of P 4 ref ＝9MW,Q 4 ref Simulation was performed for the case of =0mw, observe K P 、K I Influence of parameters on the effect of PI controllers.
First, the integral coefficient K is fixed I For 50, change the proportionality coefficient K P Record the active power P of the point of connection 4 Is a change curve of (a). FIG. 6 shows the scaling factor K of the PI controller according to one embodiment of the invention P An impact curve on the active power P4 of the point of connection. As can be seen from FIG. 6, at K P Given four cases of 0.3, 0.5, 0.7 and 1.5, the PI controller is stable and the active power P of the grid-connected point 4 Eventually, a given reference of 9MW can be reached, but this differs in the speed of response and the amount of overshoot. K (K) P When=0.3, the active power P of the point of connection 4 The maximum deviation was.014 MW, the overshoot was 1.56% and the oscillations were not stable until around 0.35 s. K (K) P When=0.5, the active power P of the point of connection 4 The maximum deviation was 0.1MW, the overshoot was 1.11%, and the oscillation settling time was about 0.2s. K (K) P When=0.7, the maximum deviation of the active power P4 of the grid-connected point is 0.09MW, the overshoot is 1%, and the active power P4 is stabilized at a given value after only one oscillation for about 0.15 s. Continue to increase K P When reaching 1.5, the maximum deviation of the first pendulum is 0.20MW, the overshoot is 2.22%, and although reaching a stable value at 0.2s, the first pendulum undergoes a plurality of oscillations, the oscillation times being greater than K P More in the case of=0.3, it can be seen that this time with K P The effect of the PI controller is rather reduced as the PI controller continues to increase. When K is P At=2, the PI controller is no longer stable, and eventually the oscillation diverges. Thus, K can be deduced to be within a certain range P The greater the coefficient of (2), the more active the point of presencePower P 4 The smaller the maximum deviation, overshoot, the shorter the time required to reach a given value, the better the control effect.
Next, take K P In the case of =0.5, change K I Recording the active power P of the point of connection 4 Is a change curve of (a). FIG. 7 shows the integral coefficient K of the PI controller according to one embodiment of the invention I An impact curve on the active power P4 of the point of connection. As can be seen from FIG. 7, at K I Active power P of grid-connected point under three conditions of 50, 100 and 150 respectively 4 The time to reach the stable value of 9MW is almost the same, about 0.2s, but different in maximum deviation and overshoot, K I At=150, the maximum deviation is 0.19MW and the overshoot is 2.11%; k (K) I When=100, the maximum deviation is 0.16MW and the overshoot is 1.78%; k (K) I At=50, the maximum deviation is 0.1MW and the overshoot is 1.11%. It can be seen that K I Active power P to a point of parallel connection 4 Has little influence on the stabilization time of the point of connection 4 Has a certain influence on the maximum deviation and overshoot of K I The smaller the maximum deviation and overshoot are, the smaller.
Therefore, the proportional coefficient K of the PI controller can be reasonably set P And integral coefficient K I To achieve the active power P to the grid connection point 4 Is used for stable control.
The embodiment of the invention also provides an optimal configuration system 200 for the active power of the wind farm. FIG. 8 discloses a schematic block diagram of a wind farm active power optimization configuration system 200 according to one embodiment of the invention. As shown in fig. 8, the wind farm active power optimization configuration system 200 may include one or more processors 201 configured to implement the wind farm active power optimization configuration method described in any of the above embodiments. In some embodiments, the wind farm active power optimization configuration system 200 may include a computer readable storage medium 202, where the computer readable storage medium 202 may store programs that may be invoked by the processor 201, and may include a non-volatile storage medium. In some embodiments, the optimal configuration system 200 for wind farm active power may include a memory 203 and an interface 204. In some embodiments, the system for optimally configuring the active power of the wind farm according to the embodiment of the invention can further comprise other hardware according to practical applications.
The wind farm active power optimizing configuration system 200 according to the embodiment of the present invention has similar beneficial technical effects as the wind farm active power optimizing configuration method described above, and therefore, the description thereof will not be repeated here.
The embodiment of the invention also provides a computer readable storage medium. The computer readable storage medium stores a program, which when executed by a processor, implements the method for optimizing and configuring active power of a wind farm according to any of the above embodiments.
Embodiments of the invention may take the form of a computer program product embodied on one or more storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having program code embodied therein. Computer-readable storage media include both non-transitory and non-transitory, removable and non-removable media, and information storage may be implemented by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer readable storage media include, but are not limited to: new types of memory, such as phase change memory/resistive random access memory/magnetic memory/ferroelectric memory (PRAM/RRAM/MRAM/FeRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, may be used to store information that may be accessed by the computing device.
According to the wind farm active power optimizing configuration method, the wind farm active power optimizing configuration system and the wind farm active power optimizing configuration computer system, the wind farm active power optimizing configuration computer system can be used for realizing effective response to a power grid active power dispatching instruction as an effective method for supporting the power grid frequency in a large-scale high-permeability grid-connected process of the wind farm due to the characteristics of fluctuation, randomness, uncertainty and the like of wind resources. Meanwhile, active loss is inevitably generated in the power transmission lines in the wind power stations and among the stations, and the influence on the effectiveness, instantaneity and the like of active power control of the wind power stations is further aggravated. Therefore, the wind power plant active power optimizing configuration strategy considering the station line loss under the dynamic wind speed is provided, the active power instruction optimizing model of the wind power plant based on the maximization of the rotor kinetic energy and the dynamic mathematical model of the wind power plant under the dynamic wind speed are established by comprehensively considering the active power loss of the power transmission lines in the stations and between the stations and the wake effects of the wind power plant, the optimal configuration of each group of equivalent fan active power in the wind power plant is realized, the effective response of the wind power plant to the power grid active power output requirement is ensured, the maximization of the stored rotor kinetic energy in the wind power plant is realized, the frequency supporting capability of a high-proportion wind power plant access system is fully exerted, and the wind power plant active power optimizing configuration strategy is well suitable for engineering application of wind power plant active frequency modulation optimizing technology.
The method and the system for optimizing the active power of the wind farm and the computer readable storage medium provided by the embodiment of the invention are described in detail. Specific examples are applied to describe the method for optimizing and configuring the active power of the wind farm, the system thereof and the computer readable storage medium according to the embodiments of the present invention, and the description of the above embodiments is only for helping to understand the core idea of the present invention, and is not intended to limit the present invention. It should be noted that it will be apparent to those skilled in the art that various changes and modifications can be made herein without departing from the spirit and principles of the invention, which should also fall within the scope of the appended claims.
Claims (17)
1. An optimal configuration method for active power of a wind farm is characterized by comprising the following steps of: it comprises the following steps:
establishing an equivalent network of a wind power plant, wherein the equivalent network of the wind power plant comprises a plurality of groups of equivalent fans which are respectively connected to an alternating current bus through power transmission lines;
selecting at least one group of equivalent fans from the multiple groups of equivalent fans as relaxation nodes, and determining the power flow distribution of the wind power plant at the static wind speed based on the active scheduling instruction of the wind power plant and the established equivalent network of the wind power plant, wherein the determining the power flow distribution of the wind power plant at the static wind speed based on the active scheduling instruction of the wind power plant and the established equivalent network of the wind power plant comprises: distributing the active scheduling instructions of the wind power plant to the plurality of groups of equivalent fans according to an equal proportion distribution rule; determining the tide distribution of the wind power plant under static wind speed based on an equivalent network of the wind power plant and a preset active power distribution rule;
establishing a dynamic mathematical model of the wind power plant at a dynamic wind speed;
establishing an active power instruction optimization model of the wind power plant based on rotor kinetic energy maximization, wherein the establishing the active power instruction optimization model of the wind power plant based on rotor kinetic energy maximization comprises the following steps: solving an optimization problem of an active power instruction of the wind power plant with maximized rotor kinetic energy of each group of equivalent fans by adopting an interior point method to determine the rotating speed of each group of equivalent fans in a load shedding mode; and
and carrying out active power configuration based on rotor kinetic energy optimization at dynamic wind speed based on the trend distribution of the wind power plant at static wind speed, the established active power instruction optimization model of the wind power plant and the dynamic mathematical model of the wind power plant.
2. The method of claim 1, wherein: the multiple groups of equivalent fans comprise multiple fan groups or multiple sub-wind fields which are assembled in a single wind field.
3. The method of claim 1, wherein: the establishing the equivalent network of the wind power plant comprises the following steps:
an equivalent network of the wind farm is established with a radial network.
4. The method of claim 1, wherein: the establishing of the dynamic mathematical model of the wind farm at the dynamic wind speed comprises the following steps:
and establishing a dynamic mathematical model of the wind power plant under dynamic wind speed based on the change of the mechanical power captured by the fan along with the wind speed, the motion equation of the rotor of the fan and the change of the electromagnetic power of the fan along with the rotating speed.
5. The method of claim 4, wherein: the dynamic mathematical model of the wind farm comprises a formula of mechanical power of each group of equivalent fans, a rotor motion equation of each group of equivalent fans and an equation of electromagnetic power reference values of each group of equivalent fans.
6. The method of claim 1, wherein: the distributing the active scheduling instructions of the wind power plant to the plurality of groups of equivalent fans according to the equal proportion distribution rule comprises the following steps:
and determining the active power emitted by the plurality of groups of equivalent fans according to the same fan utilization rate, wherein the fan utilization rate is equal to the ratio of the active scheduling instruction of the wind power plant to the sum of the maximum output powers emitted by the plurality of groups of equivalent fans.
7. The method of claim 1, wherein: the determining the power flow distribution of the wind farm at the static wind speed comprises:
and determining the tide distribution of the wind power plant at the static wind speed by adopting a forward push back substitution method.
8. The method of claim 6, wherein: the determining the power flow distribution of the wind farm at the static wind speed comprises:
and determining the active power emitted by the equivalent fans serving as the relaxation nodes to balance the active power loss of the wind farm so as to meet the requirements of the active scheduling instructions.
9. The method as recited in claim 8, wherein: the optimization problem of the active power command of the wind power plant with the maximized rotor kinetic energy of each group of equivalent fans is as follows:
ω topti <ω tdeli <ω tmaxi
wherein f (x) is the kinetic energy of the rotor, n represents the number of groups of equivalent fans, omega topti Is the rotating speed omega of the equivalent fan in the ith group in the MPPT working mode tdeli Is the rotating speed omega of the equivalent fan in the ith group in the load shedding mode tmaxi Is the maximum rotation speed allowed by the equivalent fan in the ith group, J i For the moment of inertia, P, of the equivalent fan of the ith group 1 、P 2 、P 3 、…、P n Respectively representing the active power emitted by each group of equivalent fans,representing an active scheduling instruction of the wind power plant, Q 1 、Q 2 、Q 3 、…、Q n Respectively representing reactive power emitted by the equivalent fans of each group, < >>Representing reactive scheduling instructions for the wind farm.
10. The method as recited in claim 8, wherein: the active power configuration based on rotor kinetic energy optimization at dynamic wind speed comprises the following steps:
rotor kinetic energy is optimized for optimizing an active power configuration of the wind farm per predetermined optimization time period based on real-time wind speeds of each set of the equivalent fans measured per predetermined optimization time period.
11. The method of claim 10, wherein: optimizing rotor kinetic energy for optimizing an active power configuration of the wind farm per a predetermined optimization time based on real-time wind speeds of each set of the equivalent fans measured per the predetermined optimization time comprises:
determining the active power emitted by each group of equivalent fans in the preset optimization time based on a dynamic mathematical model of the wind power plant and the power flow distribution of the wind power plant according to the real-time wind speed of each group of equivalent fans measured in each preset optimization time; and
Rotor kinetic energy is optimized for optimizing active power configuration of the wind farm based on active power emitted by each set of the equivalent fans within the predetermined optimization time period.
12. The method of claim 11, wherein: the determining the active power emitted by each group of equivalent fans within the preset optimization time period comprises the following steps:
and dynamically confirming the active power of the equivalent fan serving as the relaxation node every preset step length within the preset optimization time.
13. The method as recited in claim 12, wherein: further comprises:
and regulating the active power emitted by the equivalent fan serving as the relaxation node through a PI controller of the wind farm.
14. The method of claim 11, wherein: the optimizing rotor kinetic energy based on the active power emitted by each group of equivalent fans within the predetermined optimization time period for optimizing the active power configuration of the wind farm comprises:
determining the rotating speed of each group of equivalent fans in a load shedding mode based on the active power emitted by each group of equivalent fans in the preset optimization time and an established active power instruction optimization model of the wind power plant with the maximized rotor kinetic energy;
determining the maximum kinetic energy which can be stored by the rotor of each group of equivalent fans based on the determined rotating speed of each group of equivalent fans in the load shedding mode; and
The maximum kinetic energy which can be stored by the rotors of each group of equivalent fans is stored by controlling the rotation speed of the rotors for releasing the kinetic energy when the frequency of the power grid is reduced so as to support the active power output of the wind power plant.
15. The method as recited in claim 14, wherein: the determining the maximum kinetic energy which can be stored by the rotor of each group of equivalent fans based on the determined rotating speed of each group of equivalent fans in the load shedding mode comprises the following steps:
and determining the maximum kinetic energy which can be stored by the rotor of each group of equivalent fans based on the determined optimal rotation speed of each group of equivalent fans in the load shedding mode and the rotation speed of each group of equivalent fans in the maximum power point tracking mode.
16. An optimal configuration system for active power of a wind farm is characterized in that: comprising one or more processors for implementing a method of optimizing configuration of active power of a wind farm as claimed in any of claims 1-15.
17. A computer-readable storage medium, characterized in that it has stored thereon a program which, when executed by a processor, implements a method for optimizing the configuration of active power of a wind farm according to any of claims 1-15.
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