CN111509770B - Intelligent wind power plant active power control method based on multi-working-condition expert strategy - Google Patents

Intelligent wind power plant active power control method based on multi-working-condition expert strategy Download PDF

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CN111509770B
CN111509770B CN202010318197.9A CN202010318197A CN111509770B CN 111509770 B CN111509770 B CN 111509770B CN 202010318197 A CN202010318197 A CN 202010318197A CN 111509770 B CN111509770 B CN 111509770B
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active control
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power
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CN111509770A (en
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史晓鸣
朱博文
徐劲松
应有
李浩源
朱长江
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Zhejiang Windey Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/48—Controlling the sharing of the in-phase component
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381—Dispersed generators
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
    • H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
    • H02J2300/20—The dispersed energy generation being of renewable origin
    • H02J2300/28—The renewable source being wind energy
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/70—Wind energy
    • Y02E10/76—Power conversion electric or electronic aspects

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  • Power Engineering (AREA)
  • Feedback Control In General (AREA)
  • Control Of Eletrric Generators (AREA)

Abstract

The invention discloses an intelligent wind power plant active power control method based on a multi-working condition expert strategy, which overcomes the problems that the prior art cannot fully exert the variable pitch power changing capability of a unit and cannot quickly adjust due to the contradiction between the adjusting speed of a wind power plant and the system stability, carries out error processing through a controller, carries out different processing on different working conditions through active control quantity increment calculation, calculates active control quantity, distributes the active control quantity to a fan to execute active power control action, improves the control effect of the controller, enables the wind power plant to quickly raise and lower power when the error is large, ensures accurate adjustment when the error is small, greatly improves the robustness of the controller by designing the output of the controller when the error is large according to the wind power generation rule, ensures that the active power cannot oscillate when the active power of the wind power plant is quickly adjusted, and can fully exert the adjusting capability of a single fan, meanwhile, when the system characteristics are changed, the system can be kept stable even when the PID parameters are not strictly regulated.

Description

Intelligent wind power plant active power control method based on multi-working-condition expert strategy
Technical Field
The invention relates to the technical field of automatic control of wind power generation, in particular to an intelligent wind power plant active power control method based on a multi-working-condition expert strategy, which can quickly adjust the active power of a wind power plant and prevent the active power from oscillating.
Background
The active power control of the wind power plant aims at meeting the requirements of frequency modulation of a power grid and wind power consumption, and the basic scheme is that an active power instruction is issued to the wind power plant through a power grid dispatching system, and after receiving the active power instruction, an energy management system of the wind power plant issues an active control target value to each managed wind power unit through a certain control strategy so as to control the output power of the wind power units, so that the active power of the wind power plant is increased or reduced. The current control strategy used for wind farm energy management platforms is mainly ordinary logic control or PID control. Meanwhile, researches on active power control of the wind power plant are concentrated on improving the power generation efficiency and reducing the loss of the wind turbine generator, and researches on improvement and promotion of the control method are fresh in the aspects of improving the control speed and optimizing the stability of the system under different working conditions and parameters.
With the gradual increase of the occupation ratio of wind power generation in the electric power structure of China, the wind power generation is gradually popularized by participating in the frequency modulation of a power grid, and higher requirements are provided for the power control performance, particularly the control speed, of a wind power plant. In the process of technical development, the targets of power tracking control of the wind power plant are basically realized by common open-loop control, climbing type closed-loop control, conventional PI control and the like. However, these conventional control approaches have two problems:
1. due to the contradictory relation between the adjusting speed and the system stability, the system climbing speed or the controller gain cannot be too large, so that the variable pitch power capability of the unit cannot be fully exerted, and the requirement of quick adjustment cannot be supported;
2. aiming at the conditions that the generating capacity of the wind turbine generator is limited by wind energy and the generator in the plant can dynamically participate in or quit the regulation due to maintenance and the like, the conventional control system has insufficient robustness, the parameters are difficult to regulate, and active oscillation is caused in serious cases.
For example, a chinese patent document discloses a "method for controlling gust of a variable speed variable pitch wind turbine", which is published under the publication number CN107131100A, and comprises the following steps: A) detecting whether the rotating speed omega of the wind turbine generator is greater than the rated rotating speed omega rate of the wind turbine generator; B) calculating whether the acceleration delta omega/delta t of the wind turbine generator is larger than a set acceleration threshold value or not; C) if the wind turbine generator simultaneously meets the two conditions A and B, the variable pitch angle is directly given as 90 degrees, open-loop control is carried out, and the variable pitch speed is increased to a set threshold value; D) during variable pitch open-loop control, the torque control output is kept as an original torque value; E) after the feathering setting time T, if the wind turbine generator does not meet the conditions A and B, the pitch control is switched to the conventional closed-loop control, and if the wind turbine generator still meets the conditions A and B, the pitch control system continues feathering. According to the control method of the wind turbine generator set in the scheme, switching is performed in simple open-loop control and closed-loop control, the contradiction between the regulation speed and the system stability cannot be read quickly in the switching process, the situation of dynamic participation or quitting regulation is easy to occur, the conventional control system is insufficient in robustness, parameters are difficult to regulate, and active oscillation is caused in serious cases.
Disclosure of Invention
The invention provides an intelligent wind power plant active power control method based on a multi-working condition expert strategy, aiming at overcoming the problems that the contradiction between the wind power plant regulation speed and the system stability in the prior art can not be completely utilized to exert the variable pitch power capability of a unit and can not be quickly regulated.
The second purpose of the invention is to overcome the problem that the parameters are difficult to adjust and generate active oscillation due to the limited generating capacity of the unit, greatly improve the robustness of the controller and ensure that the active power cannot oscillate while the active power of the wind power plant is rapidly adjusted.
In order to achieve the purpose, the invention adopts the following technical scheme:
an intelligent wind power plant active power control method based on a multi-working-condition expert strategy comprises the following steps:
s1: the controller carries out preliminary processing on input data to judge the state of the fan to obtain a given value sp and a feedback value pv;
s2: the controller processes the error and refreshes the current error according to the given value sp and the feedback value pv;
s3: dividing the error into four working conditions and calculating the increment of the active control quantity;
s4: the controller calculates the active control quantity according to the active control quantity increment of the four working conditions;
s5: and the active control quantity is subjected to amplitude limiting processing by the controller and then distributed to the fan to execute active power control action calculation and output.
The wind power plant is divided into four working condition design control strategies by combining PID control, so that the control effect of the controller is improved, the wind power plant can rapidly raise and lower power when the error is large, and the adjustment accuracy can be ensured when the error is small. Meanwhile, the output of the controller is designed according to the wind field power generation rule when the error is large, so that the robustness of the controller can be greatly improved, and the active power of the wind power plant can be rapidly adjusted while the active power cannot oscillate.
Preferably, the S1 includes the following steps:
s11: the PLC acquires the data of the wind turbine generator set to judge the state of the fan;
s12: the controller defines the fans which are normally connected to the grid and allowed to participate in active power regulation as controllable states, and the other fans are uncontrollable states; s13: a given value sp and a feedback value pv are calculated.
Preferably, the step of calculating the given value sp and the feedback value pv in S13 is:
s131: accumulating the active power of the uncontrollable fan into P';
s132: accumulating the active power of the controllable fan to be P;
s133: setting the active target instruction of the wind power plant as P0；
S134: obtaining sp ═ P0-P; the pv is determined as P-P'.
Preferably, the S2 includes the following steps:
s21: the backward translation yields the error of the first two cycles, e2＝e1And e1E, wherein e, e1And e2Respectively representing the error of the current period, the error of the previous period and the error of the previous two periods;
s22: the refresh current period error is e-sp-pv.
Preferably, the S3 includes the following steps:
s31: when | e | < A, the first working condition is carried out, and the Δ U is made equal to Kp(e-e1)+Ki·e+Kd(e-2e1+e2)；
If | e | ≧ A, enter S32;
wherein: kp，Ki，KdThe parameter is a differential PID parameter, and A is an adjusting parameter of an improved PID controller;
s32: judging whether to satisfy e (e-e)1) If the working condition is more than or equal to 0, entering a working condition II;
let the active control variation be: Δ U ═ Kp2(e-e1)+Ki2·e+Kd2(e-2e1+e2)，
Otherwise, go to S33;
wherein: kp2，Ki2，Kd2Is a differential PID parameter;
s33: and entering a working condition III, wherein the active control variable quantity is as follows: Δ U is 0
S34: entering working condition four, judging whether | e | > ═ B is satisfied
If yes, executing S35, otherwise stopping;
s35: judging whether e is more than 0 or not,
if so, rapidly increasing the power; otherwise, performing fast power down.
Preferably, the fast power-up in S35 is: let Δ U be max { sp-C1Δ U }, where C1To improve the tuning parameters of the PID controller; and the delta U is an active control variable quantity and is used as a variable together with the active control quantity in the previous period to calculate the active control quantity.
Preferably, the fast power reduction in S35 is: let Δ U be max { sp + C2Δ U }, where C2To improve the tuning parameters of the PID controller; and the delta U is an active control variable quantity and is used as a variable together with the active control quantity in the previous period to calculate the active control quantity.
Preferably, the S4 includes the following steps:
s41: active control quantity U of last period0；
S42: according to the active control quantity U of the last period0And calculating the active control quantity U.
Preferably, the active control quantity U of the last cycle in S410The calculation method is as follows:
Figure GDA0003210733280000041
wherein i is the number of controllable fans, PiThe active power target parameter of the controllable fan i is obtained.
Preferably, the active control quantity is calculated by:
U＝U0+ΔU，
wherein U is an active control quantity, U0And delta U is the active control variable of the previous period.
The active control quantity can be distributed to the fan to execute active power control action after amplitude limiting processing. That is, Uout ═ min { U, Umax }, Uout ═ max { Uout, Umin }, where Umax, uman are adjustment parameters, are sequentially calculated.
Therefore, the invention has the following beneficial effects:
1. according to the invention, the wind power plant is divided into four working condition design control strategies, so that the control effect of the controller is improved, the wind power plant can rapidly raise and lower the power when the error is large, and the adjustment accuracy can be ensured when the error is small.
2. According to the method, the output of the controller when the error is large is designed according to the wind field power generation rule, the robustness of the controller can be greatly improved, the active power of the wind power plant can be rapidly adjusted, meanwhile, the active power cannot oscillate, the wind power plant is divided into four working condition design control strategies, the fan is divided into a controllable state and an uncontrollable state, the active power of the uncontrollable fan and the active power of the controllable fan are accumulated, the PID controller is used for carrying out error processing and active control quantity increment calculation to carry out different processing on the four working conditions to calculate the active control quantity, and the active control quantity can be distributed to the fan to execute active power control action through amplitude limiting processing of the PID controller.
3. The invention can give full play to the adjusting capability of a single fan, and can keep the system stable even when the PID parameter is not strictly adjusted when the system characteristic changes.
Drawings
FIG. 1 is a flowchart of example 1 of the present invention.
Fig. 2 is a calculation flowchart in one cycle of embodiment 2 of the present invention.
FIG. 3 is a schematic structural diagram of a control system of the controller for wind power plant active power control.
Detailed Description
The invention is further described with reference to the following detailed description and accompanying drawings.
Example 1:
the invention provides an intelligent wind power plant active power control method based on a multi-working condition expert strategy, which is shown in figure 1 and comprises the following steps:
s1: the controller carries out preliminary processing on input data to judge the state of the fan to obtain a given value sp and a feedback value pv;
s2: the controller processes the error and refreshes the current error according to the given value sp and the feedback value pv;
s3: dividing the error into four working conditions and calculating the increment of the active control quantity;
s4: the controller calculates the active control quantity according to the active control quantity increment of the four working conditions;
s5: and the active control quantity is subjected to amplitude limiting processing by the controller and then distributed to the fan to execute active power control action calculation and output.
Example 2:
as shown in fig. 2 and 3, the invention provides an intelligent wind farm active power control method based on a multi-condition expert strategy, which specifically comprises the following steps:
s1: the controller carries out preliminary processing on input data to judge the state of the fan to obtain a given value sp and a feedback value pv;
wherein, step S1 specifically includes the following steps:
s11: the PLC acquires the data of the wind turbine generator set to judge the state of the fan;
s12: the controller defines the fans which are normally connected to the grid and allowed to participate in active power regulation as controllable states, and the other fans are uncontrollable states; s13: a given value sp and a feedback value pv are calculated.
The calculation of the given value sp and the feedback value pv in S13 specifically includes the following steps:
s131: accumulating the active power of the uncontrollable fan into P';
s132: accumulating the active power of the controllable fan to be P;
s133: setting the active target instruction of the wind power plant as P0；
S134: obtaining sp ═ P0-P; the pv is determined as P-P'.
S2: the controller processes the error and refreshes the current error according to the given value sp and the feedback value pv;
wherein, step S2 specifically includes the following steps:
s21: the backward translation yields the error of the first two cycles, e2＝e1And e1E, wherein e, e1And e2Respectively representing the error of the current period, the error of the previous period and the error of the previous two periods;
s22: the refresh current period error is e-sp-pv.
S3: dividing the error into four working conditions and calculating the increment of the active control quantity;
wherein, step S3 specifically includes the following steps:
s31: when | e | < A, the first working condition is carried out, and the Δ U is made equal to Kp(e-e1)+Ki·e+Kd(e-2e1+e2)；
If | e | ≧ A, enter S32;
wherein: kp，Ki，KdThe parameter is a differential PID parameter, and A is an adjusting parameter of an improved PID controller;
s32: judging whether to satisfy e (e-e)1) If the working condition is more than or equal to 0, entering a working condition II;
let the active control variation be: Δ U ═ Kp2(e-e1)+Ki2·e+Kd2(e-2e1+e2)，
Otherwise, go to S33;
wherein: kp2，Ki2，Kd2Is a differential PID parameter;
s33: and entering a working condition III, wherein the active control variable quantity is as follows: Δ U is 0
S34: entering working condition four, judging whether | e | > ═ B is satisfied
If yes, executing S35, otherwise stopping;
s35: judging whether e is more than 0 or not,
if so, rapidly increasing the power; otherwise, performing fast power down.
Specifically, the step of performing fast power rise comprises the following steps: let Δ U be max { sp-C1Δ U }, where C1To improve the tuning parameters of the PID controller; and the delta U is an active control variable quantity and is used as a variable together with the active control quantity in the previous period to calculate the active control quantity.
Specifically, the step of rapidly reducing power is as follows: let Δ U be max { sp + C2Δ U }, where C2To improve the tuning parameters of the PID controller; and the delta U is an active control variable quantity and is used as a variable together with the active control quantity in the previous period to calculate the active control quantity.
S4: the controller calculates the active control quantity according to the active control quantity increment of the four working conditions;
wherein, step S4 specifically includes the following steps:
s41: active control quantity U of last period0；
S42: according to the active control quantity U of the last period0And calculating the active control quantity U.
Wherein, the active control quantity U of the last period0The calculation method is as follows:
Figure GDA0003210733280000061
wherein i is the number of controllable fans, PiThe active power target parameter of the controllable fan i is obtained.
The active control quantity calculation method comprises the following steps:
U＝U0+ Δ U, where U is the active control quantity,U0and delta U is the active control variable of the previous period.
S5: and the active control quantity is subjected to amplitude limiting processing by the controller and then distributed to the fan to execute active power control action calculation and output.
The active control quantity can be distributed to the fan to execute active power control action through amplitude limiting processing, namely, the active power control action is sequentially calculated to be Uout { U, Umax }, Uout ═ max { Uout, uman }, wherein Umax and uman are adjusting parameters.
The invention divides the wind power field into four working condition design control strategies, divides the fans into a controllable state and an uncontrollable state, calculates the active control quantity by accumulating the active power of the uncontrollable fans and the controllable fans, uses a PID controller to carry out error processing and active control quantity increment calculation to carry out different processing on the four working conditions, and distributes the active control quantity to the fans to carry out active power control action by the amplitude limiting processing of the PID controller, thereby improving the control effect of the controller, ensuring that the wind field can rapidly raise and lower the power when the error is larger, ensuring the adjustment accuracy when the error is smaller, greatly improving the robustness of the controller by designing the output of the controller when the error is larger according to the wind field power generation rule, ensuring that the active power cannot oscillate when the active power of the wind field is rapidly adjusted, and fully playing the adjustment capability of a single fan, meanwhile, when the system characteristics are changed, the system can be kept stable even when the PID parameters are not strictly regulated.
The above embodiments are described in detail for the purpose of further illustrating the present invention and should not be construed as limiting the scope of the present invention, and the skilled engineer can make insubstantial modifications and variations of the present invention based on the above disclosure.

Claims (7)

1. An intelligent wind power plant active power control method based on a multi-working-condition expert strategy is characterized by comprising the following steps:
s1: the controller carries out preliminary processing on input data to judge the state of the fan to obtain a given value sp and a feedback value pv;
the S1 includes the steps of:
s11: the PLC acquires the data of the wind turbine generator set to judge the state of the fan;
s12: the controller defines the fans which are normally connected to the grid and allowed to participate in active power regulation as controllable states, and the other fans are uncontrollable states;
s13: calculating a given value sp and a feedback value pv;
the calculation steps of the given value sp and the feedback value pv in the S13 are as follows:
s131: accumulating the active power of the uncontrollable fan into P';
s132: accumulating the active power of the controllable fan to be P;
s133: setting the active target instruction of the wind power plant as P0；
S134: obtaining sp ═ P0-P; obtaining pv ═ P-P';
s2: the controller processes the error and refreshes the current error according to the given value sp and the feedback value pv;
the S2 includes the steps of:
s21: the backward translation yields the error of the first two cycles, e2＝e1And e1E, wherein e, e1And e2Respectively representing the error of the current period, the error of the previous period and the error of the previous two periods;
s22: refreshing the current period error to be e-sp-pv;
s3: dividing the error into four working conditions and calculating the increment of the active control quantity;
s4: the controller calculates the active control quantity according to the active control quantity increment of the four working conditions;
s5: and the active control quantity is subjected to amplitude limiting processing by the controller and then distributed to the fan to execute active power control action calculation and output.
2. The intelligent wind farm active power control method based on the multi-condition expert strategy as claimed in claim 1, wherein the S3 comprises the following steps:
s31: when | e | < A, the first working condition is carried out, and the Δ U is made equal to Kp(e-e1)+Ki·e+Kd(e-2e1+e2) (ii) a If | e | ≧ A, enter S32;
wherein: kp，Ki，KdThe parameter is a differential PID parameter, and A is an adjusting parameter of an improved PID controller;
s32: judging whether to satisfy e (e-e)1) If the working condition is more than or equal to 0, entering a working condition II;
let the active control variation be: Δ U ═ Kp2(e-e1)+Ki2·e+Kd2(e-2e1+e2)，
Otherwise, go to S33;
wherein: kp2，Ki2，Kd2Is a differential PID parameter;
s33: and entering a working condition III, wherein the active control variable quantity is as follows: Δ U is 0
S34: entering working condition four, judging whether | e | > ═ B is satisfied
If yes, executing S35, otherwise stopping;
s35: judging whether e is more than 0 or not,
if so, rapidly increasing the power; otherwise, performing fast power down.
3. The intelligent wind farm active power control method based on the multi-condition expert strategy as claimed in claim 2, wherein the fast power-up in S35 is: let Δ U be max { sp-C1Δ U }, where C1To improve the tuning parameters of the PID controller; and the delta U is an active control variable quantity and is used as a variable together with the active control quantity in the previous period to calculate the active control quantity.
4. The intelligent wind farm active power control method based on the multi-condition expert strategy as claimed in claim 2, wherein the fast power reduction in S35 is: let Δ U be max { sp + C2Δ U }, where C2To improve the tuning parameters of the PID controller; and the delta U is an active control variable quantity and is used as a variable together with the active control quantity in the previous period to calculate the active control quantity.
5. The intelligent wind farm active power control method based on the multi-condition expert strategy as claimed in claim 1, wherein the S4 comprises the following steps:
s41: active control quantity U of last period0；
S42: according to the active control quantity U of the last period0And calculating the active control quantity U.
6. The intelligent wind farm active power control method based on the multi-condition expert strategy as claimed in claim 5, characterized in that the active control quantity U of the last period in S410The calculation method is as follows:
Figure FDA0003369650950000021
wherein i is the number of controllable fans, PiThe active power target parameter of the controllable fan i is obtained.
7. An intelligent wind farm active power control method based on a multi-condition expert strategy according to claim 3, 4 or 5, characterized in that the active control quantity is calculated in the following manner:
U＝U0+ΔU，
wherein U is an active control quantity, U0And delta U is the active control variable of the previous period.
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