CN108599240B - The Wind turbines converter controller parameter tuning method of meter and small signal stability - Google Patents
The Wind turbines converter controller parameter tuning method of meter and small signal stability Download PDFInfo
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- CN108599240B CN108599240B CN201810396981.4A CN201810396981A CN108599240B CN 108599240 B CN108599240 B CN 108599240B CN 201810396981 A CN201810396981 A CN 201810396981A CN 108599240 B CN108599240 B CN 108599240B
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Classifications
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- H02J3/386—
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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 present invention relates to Wind turbines converter controller parameter tuning methods, specially the Wind turbines convertor controls parameter tuning method of meter and small signal stability, the specific steps are that: it determines each controller parameter feasible region, generates small interference stability state matrix；Set maximum number of iterations asD；A group controller parameter is generated in feasible zone at random；Attitude conirol under rated wind speed；It is finely tuned lower than controller parameter under rated wind speed；Examine small signal stability under full blast speed；Export the maximum controller parameter optimum results of small interference stability nargin.Using this method, Small signal stability analysis characteristic is based in parameter tuning, it is constraint and target with small interference stability nargin and characteristic root real part threshold value, the controller parameter for needing to adjust with correlation factor selection, influence of each controller parameter next to full blast condition to system small interference stability is analyzed, and then determines the controller parameter value for being suitable for full blast condition.
Description
Technical field
The present invention relates to convertor controls Parameters design, the specially Wind turbines of meter and small signal stability transformation
Device attitude conirol method.
Background technique
With the fast development of wind generating technology, installed capacity of wind-driven power is growing, and randomness and fluctuation are to electricity
It is adversely affected caused by Force system stability increasingly prominent.Contain PI link in blower converter controller, system band can be given
Carry out new state variable, so that the correlation between controller of fan parameter and power grid small interference stability is closer.
Currently, determining each parameter mainly from controller performance requirement itself when the transducer parameters design of blower
Feasible region.Pertinent literature proposes pwm converter controller design method, and the calculating for giving converter controller parameter is public
Formula, controller parameter are mainly related to system damping ratio, middle bandwidth.According to existing converter controller parameter designing scheme,
Only consider control circuit internal control requirement, it is impossible to meet blower under full blast condition it is grid-connected after power grid small interference stability is wanted
It asks.
Such as under the premise of ensuring the small interference stability of power grid, targetedly the convertor controls parameter of blower is carried out whole
Surely urgent problem to be solved is had become.
Summary of the invention
The present invention is to solve existing blower convertor controls parameter designing scheme not considering that system small signal stability is wanted
The problem of asking, propose it is a kind of meter and small signal stability Wind turbines convertor controls parameter tuning method.Using the party
Method is based on Small signal stability analysis characteristic in parameter tuning, is constraint with small interference stability nargin and characteristic root real part threshold value
And target, it is small to system to each controller parameter under full blast condition dry with the controller parameter that correlation factor selection needs to adjust
It disturbs stable influence to be analyzed, and then determines the controller parameter value for being suitable for full blast condition.The program is applicable to all classes
The Wind turbines and the attitude conirol under control strategy of type.
The present invention adopts the following technical scheme that realization:
The Wind turbines converter controller parameter tuning method of meter and small signal stability, comprising the following steps:
S1: the full blast condition Small signal stability analysis model containing Wind turbines is established, determines state matrix A；According to converter
Performance requirement determines the feasible zone of each controller parameter of blower according to PWM controller parameter tuning method；
S2: iteration maximum times are set as D；
S3: a group controller parameter is generated at random in each controller parameter feasible zone；
S4: attitude conirol under rated wind speed: under rated wind speed, the characteristic root of state matrix A is calculated, and each
Correlation factor between a characteristic root and controller parameter, calculated characteristic root is abundant by the small interference stability of each characteristic root
Spend Yk=[- Re (λk)]-|Im(λk) | ascending sort, Re (λk) it is characterized root λkReal part, | Im (λk) | it is λkImaginary part it is absolute
Value；For according to the ith feature root λ after nargin ascending sorti, by its correlation factor between controller parameter according to exhausted
To value descending, correlation factor absolute value is then sequentially adjusted in greater than 0 corresponding controller parameter, controller parameter is enabled to increase △,
The characteristic root of solving state matrix A and for characteristic root λiIf characteristic root λiReal part increases, then step-length d=-△ is arranged, otherwise
Step-length d=△ is set；Controller parameter is adjusted according to step-length d in each controller parameter feasible region, if system margins valueIncrease, N is the order of system, then continues to adjust the parameter according to step-length d, is otherwise adjusted according to step-length d next
Controller parameter, controller parameter are directed to ith feature root λiAgain for next after nargin ascending sort after the completion of adjustment
Characteristic root λi+1It is adjusted, if controller parameter makes all characteristic root real parts small after adjusting for all characteristic roots
In 0, then to S5, otherwise to S3；
S5: it is finely tuned lower than controller parameter under rated wind speed: since rated wind speed, reducing wind according to the step-length of S m/s
Speed adjusts the controller parameter after S4 adjusting lower than under rated wind speed each, until wind speed is less than incision wind speed:
Each lower than under specified wind speed, the characteristic root of state matrix A is calculated, if it exists unstable characteristic root λj(the real part of characteristic root
Greater than 0), under the wind speed, characteristic root presses small interference stability margin value ascending sort, and solves each unstable characteristic root and control
Correlation factor between device parameter processed, for unstable characteristic root λj, it is sequentially adjusted in controller parameter according to correlation factor descending,
Controller parameter is enabled to increase △, the characteristic root of solving state matrix A and for the unstable characteristic root λjIf characteristic root λjReal part
Increase, then step-length d=- △ is set, otherwise step-length d=△ is set；It is adjusted in each controller parameter feasible region according to step-length d
Controller parameter, if system margins valueIncrease, then continues to adjust the parameter according to step-length d, otherwise according to step-length d
Next controller parameter is adjusted, controller parameter is directed to j-th of unstable characteristic root λjAdjustment after the completion of again be directed to nargin
Next unstable characteristic root λ after ascending sortj+1It is adjusted so that system margins increase, and the real part of all characteristic roots is equal
Less than zero；
S6: examine small signal stability under full blast speed: according to the step-length of S m/s, verification whether full blast condition (including specified wind
The wind speed of speed, incision wind speed and the increments by S m/s between the two) under all characteristic roots to be all satisfied characteristic root real part steady
Determine threshold formula Re (λi) < C i=1,2 ..., N, wherein C exports each controller parameter value if meeting the requirements for negative,
Otherwise, this group of control parameter value is stored, until S7, the number of iterations adds one；
S7: judging whether the number of iterations reaches maximum value, if being less than D, until Step3；Otherwise, according to system margins valueThe small interference stability nargin under rated wind speed of D group controller parameter value is calculated, selects small interference stability nargin maximum
Controller parameter be adjusting result.
Meter and the Wind turbines convertor controls parameter tuning method of small signal stability proposed by the present invention are to increase
System small interference stability nargin Y is optimization aim, is constraint with characteristic root real part stable threshold C, with controller parameter and characteristic root
Between correlation factor be ranking criteria.Control parameter is adjusted in rated wind speed makes power grid small interference stability nargin maximum
Change, in other wind speed, controller parameter Adjusted Option is determined by related-factors analysis and stability margin, so that controller is joined
Number can guarantee power grid small interference stability under each wind speed, quickly obtain the stable feasible controller parameter value of full blast condition.
Specific embodiment
The Wind turbines converter controller parameter tuning method of meter and small signal stability, comprising the following steps:
S1: the full blast condition Small signal stability analysis model containing Wind turbines is established, determines state matrix A；According to converter
Performance requirement determines the feasible zone of each controller parameter of blower according to PWM controller parameter tuning method；
S2: iteration maximum times are set as D；
S3: a group controller parameter is generated at random in each controller parameter feasible zone；
S4: attitude conirol under rated wind speed: under rated wind speed, the characteristic root of state matrix A is calculated, and each
Correlation factor between a characteristic root and controller parameter, calculated characteristic root is abundant by the small interference stability of each characteristic root
Spend Yk=[- Re (λk)]-|Im(λk) | ascending sort, Re (λk) it is characterized root λkReal part, | Im (λk) | it is λkImaginary part it is absolute
Value；For according to the ith feature root λ after nargin ascending sorti, by its correlation factor between controller parameter according to exhausted
To value descending, correlation factor absolute value is then sequentially adjusted in greater than 0 corresponding controller parameter, controller parameter is enabled to increase △,
The characteristic root of solving state matrix A and for characteristic root λiIf characteristic root λiReal part increases, then step-length d=-△ is arranged, otherwise
Step-length d=△ is set；Controller parameter is adjusted according to step-length d in each controller parameter feasible region, if system margins valueIncrease, N is the order of system, then continues to adjust the parameter according to step-length d, is otherwise adjusted according to step-length d next
Controller parameter, controller parameter are directed to ith feature root λiAgain for next after nargin ascending sort after the completion of adjustment
Characteristic root λi+1It is adjusted, if controller parameter makes all characteristic root real parts small after adjusting for all characteristic roots
In 0, then to S5, otherwise to S3；
S5: it is finely tuned lower than controller parameter under rated wind speed: since rated wind speed, reducing wind according to the step-length of Sm/s
Speed adjusts the controller parameter after S4 adjusting lower than under rated wind speed each, until wind speed is less than incision wind speed:
Each lower than under specified wind speed, the characteristic root of state matrix A is calculated, if it exists unstable characteristic root λj(the real part of characteristic root
Greater than 0), under the wind speed, characteristic root presses small interference stability margin value ascending sort, and solves each unstable characteristic root and control
Correlation factor between device parameter processed, for unstable characteristic root λj, it is sequentially adjusted in controller parameter according to correlation factor descending,
Controller parameter is enabled to increase △, the characteristic root of solving state matrix A and for the unstable characteristic root λjIf characteristic root λjReal part
Increase, then step-length d=- △ is set, otherwise step-length d=△ is set；It is adjusted in each controller parameter feasible region according to step-length d
Controller parameter, if system margins valueIncrease, then continues to adjust the parameter according to step-length d, otherwise according to step-length d
Next controller parameter is adjusted, controller parameter is directed to j-th of unstable characteristic root λjAdjustment after the completion of again be directed to nargin
Next unstable characteristic root λ after ascending sortj+1It is adjusted so that system margins increase, and the real part of all characteristic roots is equal
Less than zero；
S6: examine small signal stability under full blast speed: according to the step-length of S m/s, verification whether all features under full blast condition
Root is all satisfied characteristic root real part stable threshold formula Re (λi) < C i=1,2 ..., N, wherein C is negative, if meeting the requirements,
Each controller parameter value is then exported, otherwise, stores this group of control parameter value, until S7, the number of iterations adds one；
S7: judging whether the number of iterations reaches maximum value, if being less than D, until Step3；Otherwise, according to system margins valueThe small interference stability nargin under rated wind speed of D group controller parameter value is calculated, small interference stability nargin is selected
Maximum controller parameter is adjusting result.
Claims (1)
1. the Wind turbines converter controller parameter tuning method of meter and small signal stability, it is characterised in that including following step
It is rapid:
S1: the full blast condition Small signal stability analysis model containing Wind turbines is established, determines state matrix A；According to transducer performance
It is required that determining the feasible zone of each controller parameter of blower according to PWM controller parameter tuning method；
S2: iteration maximum times are set as D；
S3: a group controller parameter is generated at random in each controller parameter feasible zone；
S4: attitude conirol under rated wind speed: under rated wind speed, the characteristic root of calculating state matrix A and each feature
Calculated characteristic root is pressed the small interference stability nargin Y of each characteristic root by the correlation factor between root and controller parameterk=
[-Re(λk)]-|Im(λk) | ascending sort, Re (λk) it is characterized root λkReal part, | Im (λk) | it is λkImaginary part absolute value；For
According to the ith feature root λ after nargin ascending sorti, its correlation factor between controller parameter is dropped according to absolute value
Then sequence is sequentially adjusted in correlation factor absolute value greater than 0 corresponding controller parameter, enables controller parameter increase △, solve shape
The characteristic root of state matrix A and for characteristic root λiIf characteristic root λiReal part increases, then step-length d=-△ is arranged, otherwise setting step
Long d=△；Controller parameter is adjusted according to step-length d in each controller parameter feasible region, if system margins valueIncrease, N is the order of system, then continues to adjust the parameter according to step-length d, is otherwise adjusted according to step-length d next
A controller parameter, controller parameter are directed to ith feature root λi+1Again for next after nargin ascending sort after the completion of adjustment
A characteristic root λiIt is adjusted, if controller parameter makes all characteristic root real parts small after adjusting for all characteristic roots
In 0, then to S5, otherwise to S3；
S5: it is finely tuned lower than controller parameter under rated wind speed: since rated wind speed, reducing wind speed according to the step-length of S m/s,
It is each that the controller parameter after S4 adjusting is adjusted lower than under rated wind speed, until wind speed is less than incision wind speed: each
Lower than under specified wind speed, the characteristic root of state matrix A is calculated, if it exists unstable characteristic root λj, the real part of characteristic root is greater than
0, under the wind speed, characteristic root presses small interference stability margin value ascending sort, and solves each unstable characteristic root and controller
Correlation factor between parameter, for unstable characteristic root λj, it is sequentially adjusted in controller parameter according to correlation factor descending, enables control
Device parameter processed increases △, the characteristic root of solving state matrix A and for the unstable characteristic root λjIf characteristic root λjReal part increases,
Step-length d=- △ is then set, otherwise step-length d=△ is set；It adjusts and controls according to step-length d in each controller parameter feasible region
Device parameter, if system margins valueIncrease, then continues to adjust the parameter according to step-length d, otherwise be adjusted according to step-length d
Next controller parameter, controller parameter are directed to j-th of unstable characteristic root λjAdjustment after the completion of again be directed to nargin ascending order
Next unstable characteristic root λ after sequencej+1It is adjusted so that system margins increase, and the real part of all characteristic roots is respectively less than
Zero；
S6: examine small signal stability under full blast speed: according to the step-length of S m/s, whether all characteristic roots are equal under full blast condition for verification
Meet characteristic root real part stable threshold formula Re (λi) < C i=1,2 ..., N, wherein C is that negative exports if meeting the requirements
Otherwise each controller parameter value stores this group of control parameter value, until S7, the number of iterations adds 1；
S7: judging whether the number of iterations reaches maximum value, if being less than D, until Step3；Otherwise, according to system margins valueThe small interference stability nargin under rated wind speed of D group controller parameter value is calculated, small interference stability nargin is selected
Maximum controller parameter is adjusting result.
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| CN113162096A (en) * | 2021-03-10 | 2021-07-23 | 江苏大学 | Parameter optimization design method for wind power grid-connected flexible and direct system controller |
| CN117311138B (en) * | 2023-11-30 | 2024-02-23 | 华中科技大学 | Method and system for calculating stability margin domain of control parameter of water turbine adjusting system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102621883A (en) * | 2012-04-01 | 2012-08-01 | 广东电网公司电力科学研究院 | PID (proportion integration differentiation) parameter turning method and PID parameter turning system |
| CN103197559A (en) * | 2013-03-29 | 2013-07-10 | 华北电力大学 | Method of improving system small interfering stability after accessing of double-fed unit |
| CN103473393A (en) * | 2013-08-20 | 2013-12-25 | 国家电网公司 | Method for modeling power transmission margin control model considering random probability |
| CN103713517A (en) * | 2013-12-20 | 2014-04-09 | 南京航空航天大学 | Flight control system self-adaption parameter adjustment method |
| CN107168101A (en) * | 2017-06-07 | 2017-09-15 | 国网福建省电力有限公司 | Consider frequency modulation and the set speed adjustment system control parameters setting method of scleronomic constraint |
| WO2017223222A1 (en) * | 2016-06-21 | 2017-12-28 | General Electric Company | System and method for controlling a power generating unit |
| CN107579531A (en) * | 2017-10-13 | 2018-01-12 | 东南大学 | A kind of " domain " design method of meter and the probabilistic double-fed fan motor additional damping controller of wind speed |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10089641B2 (en) * | 2013-08-28 | 2018-10-02 | San Diego Gas & Electric Company | Interconnect socket adapter for adapting one or more power sources and power sinks |
-
2018
- 2018-04-28 CN CN201810396981.4A patent/CN108599240B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102621883A (en) * | 2012-04-01 | 2012-08-01 | 广东电网公司电力科学研究院 | PID (proportion integration differentiation) parameter turning method and PID parameter turning system |
| CN103197559A (en) * | 2013-03-29 | 2013-07-10 | 华北电力大学 | Method of improving system small interfering stability after accessing of double-fed unit |
| CN103473393A (en) * | 2013-08-20 | 2013-12-25 | 国家电网公司 | Method for modeling power transmission margin control model considering random probability |
| CN103713517A (en) * | 2013-12-20 | 2014-04-09 | 南京航空航天大学 | Flight control system self-adaption parameter adjustment method |
| WO2017223222A1 (en) * | 2016-06-21 | 2017-12-28 | General Electric Company | System and method for controlling a power generating unit |
| CN107168101A (en) * | 2017-06-07 | 2017-09-15 | 国网福建省电力有限公司 | Consider frequency modulation and the set speed adjustment system control parameters setting method of scleronomic constraint |
| CN107579531A (en) * | 2017-10-13 | 2018-01-12 | 东南大学 | A kind of " domain " design method of meter and the probabilistic double-fed fan motor additional damping controller of wind speed |
Non-Patent Citations (1)
| Title |
|---|
| 双馈风电机全风况条件下小干扰稳定性分析;陈波 等;《太阳能学报》;20120430;第33卷(第4期);第525-531页 * |
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