CN109217383B - Intelligent wind power plant parameter self-adaptive rapid frequency modulation control method and system - Google Patents
Intelligent wind power plant parameter self-adaptive rapid frequency modulation control method and system Download PDFInfo
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- CN109217383B CN109217383B CN201811154456.8A CN201811154456A CN109217383B CN 109217383 B CN109217383 B CN 109217383B CN 201811154456 A CN201811154456 A CN 201811154456A CN 109217383 B CN109217383 B CN 109217383B
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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
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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
- H02J3/50—Controlling the sharing of the out-of-phase component
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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
- 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]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/70—Wind energy
- Y02E10/76—Power conversion electric or electronic aspects
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Abstract
The invention relates to the field of intelligent control systems of wind turbine generators of wind power plants, in particular to an intelligent wind power plant parameter self-adaptive fast frequency modulation control method and a system thereof, wherein the method comprises the following steps: the method comprises the steps of collecting a grid-connected frequency value at the current moment, judging whether the frequency value jumps out of a frequency dead zone range, calculating a full-field active power set value, calculating an error according to the current-moment set value and a real-time value, adjusting a proportional parameter according to the error, adjusting an integral term according to the error, calculating a differential term, superposing a differential term result obtained by calculation, a proportional parameter and the integral term to obtain full-field power adjustment at the current moment, and distributing full-field power adjustment quantity to each wind turbine generator according to control logic.
Description
Technical Field
The invention relates to the field of intelligent control systems of wind turbine generators of wind power plants, in particular to an intelligent wind power plant parameter self-adaptive rapid frequency modulation control method and system.
Background
The intelligent control system field of the wind power plant: with the rapid development of digitization and intellectualization of the wind power industry, more and more scientific research institutions begin to research the field-level intelligent control system of the wind power generation field for improving the generated energy of the whole field. However, the research results are few due to the reasons that the field starts late, the resources input by superposition scientific research institutions are limited, and the like. When an actual wind power plant operates, multiple systems and multiple platforms are required to be coordinated and matched, but data among the systems are not fully utilized, data of a core control module of each system are relatively independent, the data cannot be shared in time, the control effect can meet the examination requirements, but the degree of intellectualization and refinement is not achieved, so that the loss of generated energy which can be avoided by the wind power plant cannot be timely and effectively recovered.
When the frequency of a power grid fluctuates, the wind power plant actively adjusts the active power output of the wind power plant to participate in frequency adjustment, and the frequency adjustment is called wind power primary frequency modulation. At present, frequency modulation control of a wind turbine generator is researched more, and a common method comprises rotating speed control, pitch angle control and a method for matching the two control strategies. In the prior art, a sectional control method is adopted, the wind turbine generator participating in frequency modulation is divided into a plurality of sections of dynamic adjustment, and the improvement of the primary frequency modulation performance of a single unit is realized.
Wind power plants are generally composed of dozens of wind power generation sets, wind power participates in power grid frequency modulation, the adjustment performance of the whole plant cannot be considered, and the effect of realizing frequency modulation of only a single wind power generation set is obviously insufficient. The energy management platform takes the new energy power plant as a virtual synchronous generator to realize the primary frequency modulation function of the whole wind power plant through the communication management machine and the farm group controller. Most of the prior documents only research the control of a single unit when participating in frequency modulation, and the consideration to the whole field is less. The patent CN107749644 of my department provides a method for participating in primary frequency modulation of a wind power plant, an energy management platform collects frequency signals of a grid-connected point, and double-layer PID control is adopted to realize frequency modulation. However, the wind power generation system is a complex system with the characteristics of nonlinearity, hysteresis, time-varying property, inertia and the like, and an accurate mathematical model of the wind power generation system is difficult to establish by using a data method, so that the traditional PID control cannot adapt to variable power generation working conditions, generally has low response speed and is easy to generate overshoot, and is difficult to meet the performance requirements of increasingly severe accuracy, response speed and the like of a power grid.
Based on the above situation, the invention provides an intelligent wind power plant parameter self-adaptive fast frequency modulation control method and system to solve the problems.
Disclosure of Invention
The invention aims to provide an intelligent wind power plant parameter self-adaptive fast frequency modulation control method and system, and solves the problems that an existing control system is low in response speed, easy to generate overshoot, and difficult to meet the increasingly severe accuracy and response speed performance requirements of a power grid.
The invention provides an intelligent wind power plant parameter self-adaptive rapid frequency modulation control method, which comprises the following steps of:
s1, collecting a grid connection frequency value at the current moment;
s2, judging whether the frequency value is out of the frequency dead zone range, if so, carrying out S3, otherwise, returning to S1;
s3, calculating a full-field active power given value;
s4, calculating an error according to the given value and the real-time value of the current moment;
s5, adjusting the proportional parameters according to the errors;
s6, adjusting an integral term according to the error;
s7, calculating a differential term, and obtaining the full-field power adjustment quantity at the current moment after superposing the calculated differential term result, the proportional parameter and the integral term;
s8, distributing the full-field power regulating quantity to each wind turbine generator according to the control logic;
s9, detecting errors, if an error dead zone is reached, ending the frequency modulation, and returning to S1; if the error has not reached the dead zone, the routine returns to S5.
Further, when calculating the given value of the full-field active power, a calculation model established based on the following formula is used:
wherein f isdIs a primary frequency modulation dead zone;
fNis the rated frequency of the system;
PNis the nominal rate;
delta% is the primary frequency modulation difference rate of the new energy;
P0the initial value of active power.
Further, when the proportion parameter is adjusted, the following method is included:
adjusting to meet | E (k) | > E2 initially, and selecting the maximum parameter kp3 convergence error by the proportionality coefficient; when the error converges to E1< E (k) < E2, the proportionality coefficient will automatically adjust to kp 2; when the error converges to E (k) < E1, the scaling factor is automatically adjusted to the minimum parameter kp1, and the system converges smoothly by changing to a small parameter.
Further, when the proportion parameter is adjusted, the following method is included:
when | e (k) is more than 2% of the full-field rated power, the proportional link control parameter Kp is increased, and the system can quickly track the target quantity by using larger output; when | e (k) | is less than 0.5% of the rated power of the whole field, the proportional link control parameter Kp is reduced;
when e (k) is more than 0, the differential control is introduced or the differential control parameter Kd is increased to twist the error adjustment direction;
when the absolute value of the error becomes very small, an integral link is introduced or an integral control parameter Ki is increased.
Further, when the integral term is adjusted according to the error, the following method is included:
when the error is large, the integral adjustment item is closed, and when the error is lower than a certain value, the integral adjustment is started.
The invention also provides a smart wind power plant parameter self-adaptive rapid frequency modulation control system using the smart wind power plant parameter self-adaptive rapid frequency modulation control method, which comprises an energy management platform EMS, a power grid center, a booster station monitoring device, a frequency monitoring device and a reactive power compensation device, wherein the energy management platform EMS is respectively and electrically connected with the power grid center, the booster station monitoring device, the frequency monitoring device and the reactive power compensation device.
Compared with the prior art, the invention has the following advantages:
the invention adopts a PID parameter self-adjusting method, increases the adjustment quantity when the system error is large, and tracks quickly; when the error is small, the adjustment amount is reduced, and the operation is rapid and stable; when the error is lower than a certain value, integral control is introduced to eliminate residual error. The control parameters are dynamically adjusted according to the errors, and compared with the previous wind power plant primary frequency modulation method, the adjusting speed is higher and more stable.
Drawings
The invention is further illustrated by the following figures and examples.
FIG. 1 is a schematic diagram of the algorithmic logic of the present invention;
FIG. 2 is a schematic diagram of the system architecture of the present invention;
fig. 3 is a graph comparing the response effect of the method of the present invention and the prior art method when the power is suddenly changed.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The invention aims to provide an intelligent wind power plant parameter self-adaptive fast frequency modulation control method and system, which can ensure that a wind turbine generator can be smoothly connected and disconnected in a squirrel-cage mode or a double-fed mode and can be smoothly switched between the squirrel-cage motor mode and the double-fed motor mode.
As shown in fig. 1, the invention provides an intelligent wind farm parameter adaptive fast frequency modulation control method, which comprises the following steps:
s1, collecting a grid connection frequency value at the current moment;
s2, judging whether the frequency value is out of the frequency dead zone range, if so, carrying out S3, otherwise, returning to S1;
s3, calculating a full-field active power given value;
s4, calculating an error according to the given value and the real-time value of the current moment;
s5, adjusting the proportional parameters according to the errors;
s6, adjusting an integral term according to the error;
s7, calculating a differential term, and obtaining the full-field power adjustment quantity at the current moment after superposing the calculated differential term result, the proportional parameter and the integral term;
s8, distributing the full-field power regulating quantity to each wind turbine generator according to the control logic;
s9, detecting errors, if an error dead zone is reached, ending the frequency modulation, and returning to S1; if the error has not reached the dead zone, the routine returns to S5.
Further, when calculating the given value of the full-field active power, a calculation model established based on the following formula is used:
wherein f isdIs a primary frequency modulation dead zone;
fNis the rated frequency of the system;
PNis the nominal rate;
delta% is the primary frequency modulation difference rate of the new energy;
P0the initial value of active power.
Further, when the proportion parameter is adjusted, the following method is included:
the adjustment initially meets | E (k) | > E2, and at the moment, the maximum parameter kp3 is selected by the proportionality coefficient, so that the error is converged quickly; when the error converges to E1< E (k) < E2, the proportionality coefficient is automatically adjusted to kp2, and the adjusting rate is reduced to prevent large overshoot; when the error converges to E (k) < E1, the scaling factor is automatically adjusted to the minimum parameter kp1, which has reached the vicinity of the target value, and then changed to a small parameter to make the system converge smoothly.
Further, when the proportion parameter is adjusted, the following method is included:
when | e (k) | is greater than 2% of the full-field rated power, if the error is very large, the proportional link control parameter Kp is increased, and the system can quickly track the target quantity through larger output, so that the effects of quick response and quick error adjustment are achieved; when | e (k) | is less than 0.5% of the rated power of the whole field, the proportional link control parameter Kp is reduced to reduce the overshoot, so that the system quickly reaches a steady state;
when e (k) Δ e (k) > 0, the error changes in the direction of increasing absolute value, and differential control is introduced or the differential control parameter Kd is increased to twist the error adjustment direction;
when the absolute value of the error becomes very small, an integral link is introduced or an integral control parameter Ki is increased so as to reduce the steady-state error.
Further, when the integral term is adjusted according to the error, the following method is included:
when the error is large, the integral adjustment item is closed, and when the error is lower than a certain value, the integral adjustment is started.
The invention also provides a smart wind power plant parameter self-adaptive rapid frequency modulation control system using the smart wind power plant parameter self-adaptive rapid frequency modulation control method, which comprises an energy management platform EMS, a power grid center, a booster station monitoring device, a frequency monitoring device and a reactive power compensation device, wherein the energy management platform EMS is respectively and electrically connected with the power grid center, the booster station monitoring device, the frequency monitoring device and the reactive power compensation device.
The transient response of the system under the fixed large parameter, the fixed small parameter and the parameter self-adjusting method is tested, as shown in fig. 3. Blue indicates a given power, red is the response under the parameter self-tuning method, green indicates a fixed large parameter, and purple indicates a fixed small parameter. Comparing the red line with the green line, the response speed of the red line and the green line is close, but the red line reaches a steady state quickly, and the small-amplitude oscillation time of the green line is longer. Comparing the red line with the purple line, it is clear that the speed of the purple line is much slower. The rising time t is 0.9, the time for the parameter self-adjusting method is 4s, the time for the fixed large parameter method is 4.6s, and the time for the fixed small parameter method is 12 s.
The invention adopts a PID parameter self-adjusting method, increases the adjustment quantity when the system error is large, and tracks quickly; when the error is small, the adjustment amount is reduced, and the operation is rapid and stable; when the error is lower than a certain value, integral control is introduced to eliminate residual error. The control parameters are dynamically adjusted according to the errors, and compared with the previous wind power plant primary frequency modulation method, the adjusting speed is higher and more stable.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (3)
1. An intelligent wind power plant parameter self-adaptive rapid frequency modulation control method is characterized by comprising the following steps:
s1, collecting a grid connection frequency value at the current moment;
s2, judging whether the frequency value is out of the frequency dead zone range, if so, carrying out S3, otherwise, returning to S1;
s3, calculating a full-field active power given value;
s4, calculating an error according to the given value and the real-time value of the current moment;
s5, adjusting the proportional parameters according to the errors;
s6, adjusting an integral term according to the error;
s7, calculating a differential term, and obtaining the full-field power adjustment quantity at the current moment after superposing the calculated differential term result, the proportional parameter and the integral term;
s8, distributing the full-field power regulating quantity to each wind turbine generator according to the control logic;
s9, detecting errors, if an error dead zone is reached, ending the frequency modulation, and returning to S1; returning to S5 if the error has not reached the deadband;
when the proportion parameter is adjusted, the method comprises the following steps:
adjusting to meet | E (k) | > E2 initially, and selecting the maximum parameter kp3 convergence error by the proportionality coefficient; when the error converges to E1< E (k) < E2, the proportionality coefficient will automatically adjust to kp 2; when the error converges to E (k) < E1, the proportionality coefficient is automatically adjusted to the minimum parameter kp1, and the small parameter is changed to enable the system to converge smoothly;
when the proportion parameter is adjusted, the method comprises the following steps:
when | e (k) | is more than 2% of the rated power of the whole field, the proportional link control parameter Kp is increased, and the system can quickly track the target quantity by using larger output; when | e (k) | is less than 0.5% of the rated power of the whole field, the proportional link control parameter Kp is reduced;
when e (k) delta e (k) is more than 0, the differential control is introduced or the differential control parameter Kd is adjusted to be larger;
when the absolute value of the error becomes very small, introducing an integral link or increasing an integral control parameter Ki;
when the integral term is adjusted according to the error, the following method is included:
when the error is large, the integral adjustment item is closed, and when the error is lower than a certain value, the integral adjustment is started.
2. The intelligent wind farm parameter adaptive fast frequency modulation control method according to claim 1, wherein in calculating a full-farm active power given value, a calculation model based on the following formula is used:
wherein fd is a primary frequency modulation dead zone;
fN is the rated frequency of the system;
PN is rated rate;
delta% is the primary frequency modulation difference rate of the new energy;
p0 is the initial value of active power.
3. An intelligent wind farm parameter adaptive fast frequency modulation control system using the intelligent wind farm parameter adaptive fast frequency modulation control method according to any one of claims 1 and 2, characterized by comprising an energy management platform EMS, a power grid center, a booster station monitoring device, a frequency monitoring device and a reactive power compensation device, wherein the energy management platform EMS is electrically connected to the power grid center, the booster station monitoring device, the frequency monitoring device and the reactive power compensation device respectively.
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| CN111668883A (en) * | 2020-06-24 | 2020-09-15 | 国电联合动力技术有限公司 | Wind power plant reactive voltage control method and system |
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| CN108306312A (en) * | 2018-03-01 | 2018-07-20 | 科诺伟业风能设备（北京）有限公司 | A kind of wind power plant primary frequency modulation control method |
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| ES2338396B1 (en) * | 2007-12-27 | 2011-04-08 | GAMESA INNOVATION & TECHONOLOGY S.L. | WIND ENERGY INSTALLATION AND PROCEDURE FOR OPERATION. |
| US7805207B2 (en) * | 2008-03-28 | 2010-09-28 | Mitsubishi Electric Research Laboratories, Inc. | Method and apparatus for adaptive parallel proportional-integral-derivative controller |
| CN101662157A (en) * | 2009-09-27 | 2010-03-03 | 北京东标电子有限公司 | Method of obtaining PID parameter in wind power generation inversion grid connection |
| CN103592844B (en) * | 2012-08-15 | 2016-12-21 | 湖南涉外经济学院 | Increment type PI parameter time varying intelligent optimal control |
| CN104832368B (en) * | 2015-04-08 | 2017-07-07 | 华北电力大学 | Concentarted wind energy Wind turbines variable pitch control method based on PD characteristic |
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| CN106773652B (en) * | 2017-01-25 | 2021-01-19 | 北京鸿智电通科技有限公司 | PID system and automatic parameter adjusting method thereof |
| CN107171368B (en) * | 2017-07-19 | 2020-12-08 | 国家电网公司 | Wind power generation primary frequency modulation function implementation method based on wind power plant power control |
| CN107370179B (en) * | 2017-07-27 | 2019-04-30 | 潍柴西港新能源动力有限公司 | The method that generating set and mesh belt carry is controlled with the mode that segmentation PID is adjusted |
| CN108412688A (en) * | 2018-04-11 | 2018-08-17 | 上海电机学院 | A kind of pitch control method that wind speed feedforward is combined with fuzzy |
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| CN108306312A (en) * | 2018-03-01 | 2018-07-20 | 科诺伟业风能设备（北京）有限公司 | A kind of wind power plant primary frequency modulation control method |
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