CN106961122A - A kind of micro-capacitance sensor dynamic equivalent modeling method of feature based model - Google Patents
A kind of micro-capacitance sensor dynamic equivalent modeling method of feature based model Download PDFInfo
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- CN106961122A CN106961122A CN201710316528.3A CN201710316528A CN106961122A CN 106961122 A CN106961122 A CN 106961122A CN 201710316528 A CN201710316528 A CN 201710316528A CN 106961122 A CN106961122 A CN 106961122A
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- 238000000034 method Methods 0.000 title claims abstract description 30
- 230000003542 behavioural effect Effects 0.000 claims abstract description 6
- 238000010276 construction Methods 0.000 claims abstract description 4
- 238000013016 damping Methods 0.000 claims description 12
- 239000011159 matrix material Substances 0.000 claims description 6
- 230000005611 electricity Effects 0.000 claims description 5
- 238000005070 sampling Methods 0.000 claims description 3
- 230000009897 systematic effect Effects 0.000 claims description 3
- 238000005259 measurement Methods 0.000 claims description 2
- 238000004088 simulation Methods 0.000 abstract description 5
- 238000004458 analytical method Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 238000004146 energy storage Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005094 computer simulation Methods 0.000 description 1
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Classifications
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- H02J3/382—
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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]
Abstract
The invention discloses a kind of micro-capacitance sensor dynamic equivalent modeling method of feature based model, it is characterised in that：Collection can disclose the metric data of micro-capacitance sensor behavioral characteristics first, it is then based on metric data construction feature model, it is finally based on the exponent number that metric data determines characteristic model, the parameter of specific exponent number characteristic model is determined based on metric data, it is determined that exponent number and the characteristic model of parameter are the dynamic equivalent model of micro-capacitance sensor.The present invention is by micro-capacitance sensor depending on being integral controllable, start with from the access point metric data of micro-capacitance sensor, micro-grid system dynamic characteristic is described using characteristic model, when analyzing influence and micro-capacitance sensor planning of the micro-capacitance sensor access to power system, specific micro-capacitance sensor structure need not be analyzed, but micro-capacitance sensor is characterized in the form of characteristic model, micro-capacitance sensor dynamic characteristic is simulated using its equivalent model, the simulation velocity of system is thus improved.
Description
Technical field
The present invention relates to a kind of micro-capacitance sensor dynamic equivalent modeling method of feature based model, belong to power system modeling with
Control field.
Background technology
Micro-capacitance sensor is to improve distribution type renewable energy utilization ratio, the effective means of block supply reliability.Micro-capacitance sensor
Concentrated-distributed electricity generation system, load and energy-storage system realize that regenerative resource is distributed in one by power electronic equipment
The power supply nearby of electricity generation system, and realize by energy-storage system the safe and stable operation of system.With generating, the hair of power supply technique
Exhibition, more and more new energy distributed generation systems will generate electricity by way of merging two or more grid systems, or by way of cluster, or disperseed by micro-capacitance sensor
Mode, many X factors are brought with this to conventional electric power system.Its randomness, fluctuation are made to the safe and stable operation of power network
Into certain influence.
Micro-capacitance sensor may operate in island state and can also operate in and net state, with micro-capacitance sensor scale, capacity and
The continuous improvement of voltage class, micro-capacitance sensor is more obvious for the influence of distribution.Therefore, micro-capacitance sensor planning, build should include
Carried out under bulk power grid Unified frame, participate in the planning application and simulation calculation of bulk power grid, therefore a suitable micro-capacitance sensor models
It is most important.
Included inside micro-capacitance sensor in a large amount of power electronic equipments, actual moving process, pass through the conjunction to power electronic equipment
Manage control realization micro-capacitance sensor safe and stable operation.The dynamic process of power electronic equipment is extremely complex, with micro-capacitance sensor capacity and
Quantity increases, and the interaction of its inner member is more complicated, utilizes micro-capacitance sensor element internal detailed model to participate in power distribution network
Emulation seems improper.
The content of the invention
In order to solve the above-mentioned technical problem, the invention provides a kind of modeling of the micro-capacitance sensor dynamic equivalent of feature based model
Method.
In order to achieve the above object, the technical solution adopted in the present invention is：
A kind of micro-capacitance sensor dynamic equivalent modeling method of feature based model, first collection can disclose micro-capacitance sensor behavioral characteristics
Metric data, be then based on metric data construction feature model, be finally based on the exponent number that metric data determines characteristic model, base
The parameter of specific exponent number characteristic model is determined in metric data, it is determined that exponent number and the characteristic model of parameter are the dynamic of micro-capacitance sensor
State equivalent model.
Identification fitting is carried out to the characteristic model of different rank using metric data using damping least square method of recursion, with
Fitting precision and calculating speed sum determine model order as the judgment criteria for judging iteration.
Characteristic model is second order characteristic model, specifically,
Y (t+1)=F1(t)y(t)+F2(t)y(t-1)+G1(t)u(t)+G2(t)u(t-1)
Wherein, y (t+1) is the output of subsequent time, and y (t) is the output at current time, and y (t-1) is defeated for last moment
Go out, u (t) is the input at current time, u (t-1) is the input of last moment, F1(t), F2(t), G1(t), G2(t) for it is current when
The systematic parameter matrix at quarter.
Parameter identification is carried out to specific exponent number characteristic model using metric data using damping recursion most young waiter in a wineshop or an inn's preconceived plan method；
The object function of the damping least square method of recursion is,
Wherein,For object function, Y (t) is metric data output quantity, and H (t) is micro-capacitance sensor matrix,To be current
The parameter value at moment,For the parameter value of last moment, λ is forgetting factor, and μ is damping factor, when k=[t-N, t] is
Between sequence, t is the sampling time, and N is integer.
Metric data is voltage data, current data and the power data of micro-grid connection access point when disturbing.
During parameter identification, voltage data and power data are subjected to parameter identification as input and output respectively, point
Parameter identification is not carried out using current data and power data as input and output, increases the robustness and stably of identification system with this
Property.
The dynamic equivalent model of micro-capacitance sensor is fitted using new metric data, determine model accuracy and rationally
Property.
The beneficial effect that the present invention is reached：The present invention by micro-capacitance sensor depending on being integral controllable, from connecing for micro-capacitance sensor
Access point metric data is started with, and micro-grid system dynamic characteristic is described using characteristic model, in analysis micro-capacitance sensor access to electric power
When the influence of system and micro-capacitance sensor planning, it is not necessary to analyze specific micro-capacitance sensor structure, but carry out table in the form of characteristic model
Micro-capacitance sensor is levied, micro-capacitance sensor dynamic characteristic is simulated using its equivalent model, the simulation velocity of system is thus improved.
Embodiment
The following examples are only intended to illustrate the technical solution of the present invention more clearly, and can not limit the present invention with this
Protection domain.
Micro-capacitance sensor is by power electronics control access bulk power grid, and from the angle of bulk power grid, it can be considered a controllable element,
" power supply " that can behave as " load " of energy absorption or release energy, is shown generally as one controllable " virtual component ".When
When micro-capacitance sensor participates in electric system simulation, it is not necessary to the dynamic characteristic of excessive concern micro-capacitance sensor therein, from connecing for micro-capacitance sensor
Access point voltage, electric current, power and frequency data are started with, and analyze its dynamic characteristic, extract its behavioral characteristics.
Based on above-mentioned principle, a kind of micro-capacitance sensor dynamic equivalent modeling method of feature based model of the application, specifically such as
Under：
Step 1：Collection can disclose the metric data of micro-capacitance sensor behavioral characteristics.
The selection of metric data needs to meet some requirements, due to being in stable state under micro-capacitance sensor normal operation, this
When data can not disclose the behavioral characteristics of micro-capacitance sensor inner member, therefore, metric data must be noisy data, i.e. bulk power grid
Failure, micro-capacitance sensor internal fault or grid integration caused by running status change measure dynamic data, including micro-grid connection
Voltage data, current data, power data and the frequency data of access point, because frequency data are determined by bulk power grid, therefore
Frequency remains unchanged in most cases, therefore the metric data gathered here can be the voltage number of micro-grid connection access point
According to, current data and power data.
Step 2, based on metric data construction feature model.
Step 3, the exponent number of characteristic model is determined based on metric data.
Identification fitting is carried out to the characteristic model of different rank using metric data using damping least square method of recursion, with
The increase of characteristic model exponent number, fitting precision is consequently increased, but amount of calculation and calculating speed will be reduced, to be fitted essence
Degree and calculating speed sum determine model order as the judgment criteria for judging iteration.
Characteristic model is second order characteristic model, specifically,
Y (t+1)=F1(t)y(t)+F2(t)y(t-1)+G1(t)u(t)+G2(t)u(t-1)
Wherein, y (t+1) is the output of subsequent time, and y (t) is the output at current time, and y (t-1) is defeated for last moment
Go out, u (t) is the input at current time, u (t-1) is the input of last moment, F1(t), F2(t), G1(t), G2(t) for it is current when
The systematic parameter matrix at quarter.Characteristic model parameter has slow time-varying, embodies the change of micro-capacitance sensor running, such as：Micro- electricity
Net is necessarily influenceed by the natural cause condition such as wind speed, illumination in the process of running, is joined using the slow time-varying of characteristic model
Number can reflect that natural cause change causes the change of micro-grid system operation characteristic.
Step 4, the parameter of specific exponent number characteristic model is determined based on metric data, it is determined that the character modules of exponent number and parameter
Type is the dynamic equivalent model of micro-capacitance sensor.
Parameter identification is carried out to specific exponent number characteristic model using metric data using damping recursion most young waiter in a wineshop or an inn's preconceived plan method.This
In the object function of damping least square method of recursion be：
Wherein,For object function, Y (k) is system measurements output quantity, and H (k) is micro-capacitance sensor matrix,To be current
The parameter value at moment,For the parameter value of last moment, λ is forgetting factor, and μ is damping factor, when k=[t-N, t] is
Between sequence, t is the sampling time, and N is integer, and value here is 2.
Parameter in identification processUpdate according to the following formula：
T0' (t-1)=T (t-1)
Wherein, riFor r1Follow-up vector, r1=[1,0 ..., 0]T, μ '=(1- λ) μ/λ, k is time series,
During parameter identification, because voltage, electric current and power data are related data, respectively by voltage data and work(
Rate data carry out parameter identification as input and output, and current data and power data are carried out into parameter as input and output respectively distinguishes
Know, increase the robustness and stability of identification system with this.
Step 4, the dynamic equivalent model of micro-capacitance sensor is fitted using new metric data, determines the accuracy of model
And reasonability.
The above method depending on being integral controllable, starts with micro-capacitance sensor from the access point metric data of micro-capacitance sensor, utilizes
Characteristic model describes micro-grid system dynamic characteristic, in influence of the analysis micro-capacitance sensor access to power system and micro-capacitance sensor rule
When drawing, it is not necessary to analyze specific micro-capacitance sensor structure, but micro-capacitance sensor is characterized in the form of characteristic model, utilize its equivalent model
To simulate micro-capacitance sensor dynamic characteristic, the simulation velocity of system is thus improved.The equivalent model highly versatile of the above method, it is adaptable to
The micro-grid system of different type, different structure.
The above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, on the premise of the technology of the present invention principle is not departed from, some improvement and deformation can also be made, these improve and deformed
Also it should be regarded as protection scope of the present invention.
Claims (7)
1. a kind of micro-capacitance sensor dynamic equivalent modeling method of feature based model, it is characterised in that：Collection can disclose micro- electricity first
The metric data of net behavioral characteristics, is then based on metric data construction feature model, is finally based on metric data and determines character modules
The exponent number of type, the parameter of specific exponent number characteristic model is determined based on metric data, it is determined that exponent number and the characteristic model of parameter are
For the dynamic equivalent model of micro-capacitance sensor.
2. a kind of micro-capacitance sensor dynamic equivalent modeling method of feature based model according to claim 1, it is characterised in that：
Identification fitting is carried out to the characteristic model of different rank using metric data using damping least square method of recursion, with fitting precision
With calculating speed sum as the judgment criteria for judging iteration, model order is determined.
3. a kind of micro-capacitance sensor dynamic equivalent modeling method of feature based model according to claim 2, it is characterised in that：
Characteristic model is second order characteristic model, specifically,
Y (t+1)=F1(t)y(t)+F2(t)y(t-1)+G1(t)u(t)+G2(t)u(t-1)
Wherein, y (t+1) is the output of subsequent time, and y (t) is the output at current time, and y (t-1) is the output of last moment, u
(t) it is the input at current time, u (t-1) is the input of last moment, F1(t), F2(t), G1(t), G2(t) it is current time
Systematic parameter matrix.
4. a kind of micro-capacitance sensor dynamic equivalent modeling method of feature based model according to claim 1, it is characterised in that：
Parameter identification is carried out to specific exponent number characteristic model using metric data using damping recursion most young waiter in a wineshop or an inn's preconceived plan method；
The object function of the damping least square method of recursion is,
Wherein,For object function, Y (k) is system measurements output quantity, and H (k) is micro-capacitance sensor matrix,For current time
Parameter value,For the parameter value of last moment, λ is forgetting factor, and μ is damping factor, and k=[t-N, t] is time sequence
Row, t is the sampling time, and N is integer.
5. a kind of micro-capacitance sensor dynamic equivalent modeling side of feature based model according to claim 1,2 or 4 any one
Method, it is characterised in that：Metric data is voltage data, current data and the power number of micro-grid connection access point when disturbing
According to.
6. a kind of micro-capacitance sensor dynamic equivalent modeling method of feature based model according to claim 5, it is characterised in that：
During parameter identification, voltage data and power data are subjected to parameter identification as input and output respectively, respectively by electric current
Data and power data carry out parameter identification as input and output, increase the robustness and stability of identification system with this.
7. a kind of micro-capacitance sensor equivalent modeling method of feature based pattern according to claim 1, it is characterised in that：Utilize
New metric data is fitted to the dynamic equivalent model of micro-capacitance sensor, determines the accuracy and reasonability of model.
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| US11856424B2 (en) | 2019-05-22 | 2023-12-26 | Huawei Technologies Co., Ltd. | Method for creating network simulation platform, network simulation method, and corresponding apparatuses |
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| CN101814160A (en) * | 2010-03-08 | 2010-08-25 | 清华大学 | RBF neural network modeling method based on feature clustering |
| CN102033491A (en) * | 2010-09-29 | 2011-04-27 | 北京控制工程研究所 | Method for controlling flexible satellite based on feature model |
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Application publication date: 20170718 |