CN108448586A - A kind of assessment of micro-capacitance sensor power supply quality and its simulation Load balanced control system and method - Google Patents
A kind of assessment of micro-capacitance sensor power supply quality and its simulation Load balanced control system and method Download PDFInfo
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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
- H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
- H02J3/14—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load by switching loads on to, or off from, network, e.g. progressively balanced loading
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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
- Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02B70/00—Technologies for an efficient end-user side electric power management and consumption
- Y02B70/30—Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
- Y02B70/3225—Demand response systems, e.g. load shedding, peak shaving
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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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
- Y04S20/20—End-user application control systems
- Y04S20/222—Demand response systems, e.g. load shedding, peak shaving
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Abstract
The invention discloses a kind of assessment of micro-capacitance sensor power supply quality and its simulation Load balanced control system and methods.Using micro-capacitance sensor power supply quality intelligent evaluation device, solution micro-capacitance sensor power supply quality evaluation index is more, the cumbersome backwardness of appraisal procedure, assesses the problem of validity difference.Using power equalizer, a kind of autonomous equalization algorithm of power is proposed, set value of the power is balancedly distributed into simulation load cell, it is poor to solve the problems, such as that micro-capacitance sensor power supply quality assesses follow-up regulation effect.Robust droop control device is added in the decoupling control of simulation load, the influence of balance micro-capacitance alternating current bus voltage, frequency fluctuation to simulation load parallel system operation improves the robustness that system power follows setting value to run.In the charge/discharge control of energy storage device; it is comprehensive to stabilize microgrid power fluctuation and protection two constraintss of energy storage device, the invariable power charge and discharge of energy storage device are maintained to the maximum extent, while protecting energy storage device; extend service life of equipment, reduces system operation cost.
Description
Technical background
The invention belongs to technical field of power systems, more particularly to a kind of micro-capacitance sensor power supply quality intelligent evaluation system and
Simulate Load balanced control system and method.
Background technology
Aggravate as the non-regeneration energies such as coal, oil, natural gas consume, from sustainable development and environmental protection,
The clean types distributed power generation such as solar energy, wind energy is quickly grown, and distributed power generation is intermittent, randomness and band solving for micro-capacitance sensor
Significant role is played on the power quality problems such as mains frequency fluctuation, the variation come.Micro-capacitance sensor utility power quality control with
And be to study the key technology of micro-capacitance sensor to the power support and control of bulk power grid, existing bulk power grid electricity quality evaluation method exists
Application in micro-capacitance sensor is not extensive, and there are evaluation indexes more, the cumbersome backwardness of appraisal procedure, the follow-up regulation effect difference of assessment etc.
Disadvantage, the present invention propose a kind of micro-capacitance sensor power supply quality intelligent evaluation method based on power supply quality national standard, can be well
Solve the problems, such as that micro-capacitance sensor power supply quality is assessed, at the same propose a kind of simulation Load balanced control device and power oneself
Main equalization algorithm, which has well solved micro-capacitance sensor power supply quality, to be assessed follow-up regulation effect and pays no attention to and think over a problem, and is powered matter to micro-capacitance sensor
The close friend of the raising of amount, micro-capacitance sensor and bulk power grid is interactive and the development of " internet+" wisdom energy has active influence.
Invention content
The present invention is in view of the deficienciess of the prior art, propose that a kind of micro-capacitance sensor power supply quality is assessed and its simulation load is equal
The control system that weighs and method improve micro-capacitance sensor power supply quality assessment efficiency and validity, after improving power supply quality assessment to reach
Continuous regulation effect effectively stabilizes microgrid power fluctuation, improves the power quality issues such as voltage, frequency shift (FS), improves micro-capacitance sensor
The purpose of power supply reliability.
A kind of assessment of micro-capacitance sensor power supply quality and its simulation Load balanced control system, the system include micro-capacitance sensor voltage,
Electric current, frequency acquisition module, micro-capacitance sensor power supply quality intelligent evaluation device and simulation Load balanced control device, wherein：
Micro-capacitance sensor voltage, electric current, frequency acquisition module：For acquiring real-time micro-capacitance sensor voltage, electric current, frequency values and transmitting
Into micro-capacitance sensor power supply quality intelligent evaluation device；
Micro-capacitance sensor power supply quality intelligent evaluation device：Real-time micro-capacitance sensor voltage, electric current, frequency are calculated for analyzing, assessment is micro-
Whether grid supply quality meets the requirements, and judges to simulate whether Load balanced control device needs to devote oneself to work；
Simulation Load balanced control device includes power equalizer, simulation load system；
Power equalizer：Value is received and sent out to active power and reactive power for calculating simulation loading module, is
Value is received and sent out to each energy storage device equilibrium assignment active power and reactive power for simulating load；
Simulate load system：For absorbing or sending out active power or reactive power, microgrid power fluctuation is stabilized, is improved
Micro-capacitance sensor power supply quality constitutes analog load parallel running system by the parallel connection of multiple simulation load cells；The simulation is negative
Lotus unit includes two-way AC-DC current transformers, bidirectional DC-DC converter, two-way AC-DC current transformers power controller, bi-directional DC-DC
Converter controller and energy storage device.The bidirectional DC-DC converter control unit automatically switches according to the SOC of energy storage device
Constant current/three kinds of invariable power/constant voltage charge/discharge pattern reaches protection energy storage device, improves energy storage device service life, drop
The target of low system cost.
The method of a kind of above-mentioned micro-capacitance sensor power supply quality assessment and its simulation Load balanced control system, including walk as follows
Suddenly：
Step 1：Using micro-capacitance sensor power supply quality intelligent evaluation device, calculates analysis and pass through micro-capacitance sensor voltage, electric current, frequency
The real-time micro-capacitance sensor voltage of acquisition module acquisition, electric current, frequency data, and assess micro- electricity in real time according to national power quality standard
Whether net power supply quality meets standard, comes into operation if being unsatisfactory for standard analog Load balanced control device needs；
Step 2：When judging to need to put into Load balanced control device, power equalizer will be according to micro-capacitance sensor power supply quality
Voltage in intelligent evaluation device and frequency obtain the setting value of system charge-discharge electric power using the autonomous equalization algorithm of power, and tie
Mold the maximum allowable of the SOC calculating simulations load cell and system for intending that load cell energy storage device is each simulated in load system
Charge-discharge electric power, while calculating the charge-discharge electric power setting value that each simulation load cell should distribute according to the SOC of energy storage device.
Further, above-mentioned steps one specifically include following steps：
Step 1：It is obtained after being handled by sampling module comprising voltage deviation, voltage fluctuation and flicker, harmonic content, three-phase electricity
The sample characteristics collection of pressure degree of unbalancedness, temporary overvoltage, transient overvoltage, 9 current harmonic content, frequency departure features；
Step 2：Each feature of micro-capacitance sensor power supply quality feature set is normalized；
Step 3：Sample data is labeled according to power supply quality national standard；
Step 4：According to ratio random division training sample and test sample, and according to step 3 to sample data into rower
Note；
Step 5：The each training sample chosen to step 4 is trained using bottom-to-top method, to training process
Input layer, training layer, tuning layer, output layer four levels are divided into, successively training optimizes；
Step 6：Training sample final output value is assessed using test sample, the accuracy rate of assessment system training,
If sample is unsatisfactory for power supply quality requirement, simulates Load balanced control device needs and come into operation.
Further, the step 5 in above-mentioned steps one specifically includes following steps：
Step 5-1：Corresponding initial value is assigned to each layer parameter when training starts, each layer parameter includes that training layer biases γh, output
Layer biasing θj, the connection weight v of i-th of unit of input layer and training h-th of unit of layerih, train h-th of unit of layer and output layer
The connection weight w of j-th of unithj, tuning layer η1、η2、η3、η4It is positive constant amount that 4 Study rate parameters, which are 4 perseverances,；Training
The input value calculation basis formula of layer and output layer
It calculates, in formula, the input layer input value of each sample is xi(i=1,2 ... d), and d is input layer unit number, instruction
It is e to practice layer input valueh(h=1,2 ..., q), q are training layer unit number, and output layer input value is yj(j=1,2 ..., l), l
For output layer unit number；
Step 5-2：Input by the output of training layer as next trained layer, repeats step 5-1, reaches setting training layer
After number, the above parameter is inputted into tuning layer from top to down and carries out arameter optimization；
Step 5-3：Arameter optimization processing is carried out to evaluation process.
Calculate the mean square error E of each sample；
Step 5-3-1：Output layer biases θ in tuning layerjTuning formula be
In formula,It is expected for the output valve of each sample of output layer.
Step 5-3-2：The connection weight w of training j-th of unit of h-th of unit of layer and output layerhjTuning formula be
Step 5-3-3：Training layer biases γ in tuning layerhTuning formula be
Therefore
Step 5-3-4：The connection weight v of i-th of unit of input layer and training h-th of unit of layer in tuning layerihTuning
Formula is
Therefore
Further, the autonomous equalization algorithm of power of the power equalizer in above-mentioned steps two includes the following steps：
Step 1)：According to the assessment result of micro-capacitance sensor power supply quality intelligent evaluation device, make if simulation load need not be put into
With cycle executes this step；If simulation load needs come into operation, step 2) is executed；
Step 2)：According to SOC and energy storage device parameter calculating simulation load cell and the maximum allowable charge-discharge electric power of system；
Step 3)：According to voltage, frequency values and each generating equipment parameter of micro-capacitance sensor power supply quality intelligent evaluation device, meter
Calculation system charge/discharge set value of the power；
Step 4)：It takes smaller in the maximum allowable charge-discharge electric power of system in set value of the power and the step 2) in step 3
Value is as new system power setting value；
Step 5)：According to battery SOC and power weight distribution formula, the power setting of each simulation load cell is obtained
Value, is passed in two-way AC-DC current transformers power controller.
Further, above-mentioned steps 2) in maximum allowable charge/discharge rating formula be
In formula, N indicates that simulation load cell, that is, energy storage device number, each load cell of simulating are indicated with letter i, each
The state-of-charge of energy storage device is SOCi(i=1,2 ... ... N), Pi mcIndicate maximum allowable charging active power, Qi mcIt indicates most
It is big to allow charge reactive power, Pi mdIndicate maximum allowable electric discharge active power, Qi mdIndicate maximum allowable electric discharge reactive power, often
A energy storage maximum charge/discharge power determines, switching value u according to energy storage device self-characteristic when being dispatched from the factory by equipmentiTake 1 expression mould
Quasi- load cell comes into operation, ui0 expression simulation load cell is taken not come into operation, uiValue depend on energy storage device
SOC, i.e. energy storage device the SOC u when equipment allows in working rangei1 is taken, energy storage device SOC allows in equipment outside working range
When uiTake 0.
Further, above-mentioned steps 3) calculating of system charge/discharge set value of the power, it is obtained by the electric generating set rotor equation of motion
Simulate the relationship of load system set value of the power and rotary speed of generator group
Being write as state equation form is
Wherein, ωNFor rated angular velocity, δ is generator rotor angle, PT、PE、PDThe respectively mechanical output of generating set, output power
And loss power, TJFor equivalent inertia time constant, calculation formula isTJiFor the inertial time of every generating set
Between constant, continue to derive simulation load system set value of the power and frequency relationship
Wherein, ω and f is respectively center of inertia angular speed and center of inertia frequency, by
Calculating is got.
Further, above-mentioned steps 5) it is calculated by battery SOC and power weight distribution formula and each simulates load cell
Set value of the power, power weight distribution formula are
In formula, each charge power for simulating load cell is Pi c(Qi c), discharge power Pi d(Qi d), by result of calculation
It send into two-way AC-DC current transformers power controller.
Further, above-mentioned steps 5) in two-way AC-DC current transformers power control unit according to obtained by power equalizer
Set value of the power controls two-way AC-DC current transformers, completes microgrid power decoupling control, and reaching improves micro-capacitance sensor power supply quality
Target；Robust droop control device balance micro-capacitance sensor frequency and voltage deviation is added in power decoupled control simultaneously, improves system
Robustness, specially：Frequency departure and voltage deviation are added after the proportional action of the sagging coefficient of robust and clipping module
To in the deviation of active power and reactive power, the robustness of system is improved, the efficiency analysis of robust droop control device passes through
Relative difference on frequency embodies, and obtaining power relative error according to sagging relationship is
In formula, P and P* are respectively practical micro-capacitance alternating current bus active power value and active power setting value, and Q and Q* divide
It Wei not practical micro-capacitance alternating current bus reactive power value and reactive power setting value, U and U0The micro-capacitance sensor exchange respectively surveyed
Busbar voltage and busbar voltage standard value, f and f0The standard of respectively actually measured micro-capacitance alternating current bus frequency and frequency
It is worth (50Hz), m, n are sagging coefficient；Micro-capacitance alternating current bus frequency and voltage relative errorWithBecome over a period to come
Change less, then sagging Coefficient m and n are bigger, and the relative error of micro-capacitance alternating current bus side active power is bigger.It is added under robust
Hang down controller after power relative error be
Pass through the sagging COEFFICIENT K of robustp、KqThe influence of sagging Coefficient m, n to power relative error is balanced, power control is improved
Precision.
Beneficial effects of the present invention：
A kind of micro-capacitance sensor power supply quality assessment of the present invention and its simulation Load balanced control system and method, coordinate micro-capacitance sensor
Multiple indexs of power supply quality assessment, propose power supply quality intelligent evaluation method, solve the cumbersome backwardness of appraisal procedure, assessment effect
Fruit difference problem realizes the intelligent and validity of micro-capacitance sensor power supply quality assessment；It is independently equal by the power to energy storage device
Weighing apparatus control, realize to the maximum extent protection energy storage device, extend the energy storage device service life, reduce system operation cost with stabilize it is micro-
Coordination between grid power fluctuation, raising micro-capacitance sensor power supply quality；Analog load parallel running, it is more to meet micro-grid load
Sample demand improves the reliability of simulation load operation；Robust droop control is added in two-way AC-DC current transformers power control
Device balances micro-capacitance sensor frequency and voltage deviation, improves the robustness of system.
Description of the drawings
Fig. 1 is the block diagram of system of the embodiment of the present invention；
Fig. 2 is the micro-capacitance sensor power supply quality intelligent evaluation device flow chart of the embodiment of the present invention；
Fig. 3 is the intelligent evaluation device structure chart of the embodiment of the present invention；
Fig. 4 is the power equalization control device work flow diagram of the embodiment of the present invention；
Fig. 5 is the simulation load cell composition frame chart of the embodiment of the present invention；
Fig. 6 is the simulation load cell topology diagram of the embodiment of the present invention；
Fig. 7 is the two-way AC-DC current transformers control block diagram of the embodiment of the present invention；
Fig. 8 is the bidirectional DC-DC converter control block diagram of the embodiment of the present invention；
Fig. 9 is energy storage device charge power, voltage, current-mode the switching figure of the embodiment of the present invention；
Figure 10 is energy storage device discharge power, voltage, current-mode the switching figure of the embodiment of the present invention
Figure 11 is the micro-capacitance sensor voltage oscillogram of the embodiment of the present invention；
Figure 12 is the micro-capacitance sensor current waveform figure of the embodiment of the present invention；
Figure 13 is the micro-capacitance sensor frequency oscillogram of the embodiment of the present invention；
Figure 14 is the simulation load exchange side active power oscillogram of the embodiment of the present invention；
Figure 15 is the simulation load exchange side reactive power oscillogram of the embodiment of the present invention.
Specific implementation mode
An embodiment of the present invention is described further below in conjunction with the accompanying drawings.
Fig. 1 is the block diagram of system of the embodiment of the present invention, including micro-capacitance sensor voltage, electric current, frequency acquisition module, micro- electricity
Net power supply quality intelligent evaluation device, power equalizer and simulation load parallel system, wherein micro-capacitance sensor voltage, electric current, frequency are adopted
Collection module can complete the acquisition to exchanging micro-capacitance sensor busbar voltage, bus current and busbar frequency in real time, and acquisition is believed
Breath is sent in micro-capacitance sensor power supply quality intelligent evaluation device, and micro-capacitance sensor power supply quality intelligent evaluation device simulates assessment result negative
Whether lotus, which needs to come into operation, is sent in power equalizer, if currently micro-capacitance sensor power supply quality is not in critical field, work(
Real-time micro-capacitance alternating current bus voltage, bus current and busbar frequency and micro-capacitance sensor power supply of the rate balanced device according to acquisition module
Quality intelligent evaluator assessment result is received realtime power in conjunction with current energy storage device SOC by the autonomous equalization algorithm of power
Or value equilibrium assignment is sent out to each simulation load, in each energy storage device, simulation load parallel system is then according to power equalization
The apportioning cost of device completes micro-capacitance alternating current bus side by the control of two-way AC-DC current transformers and bidirectional DC-DC converter
Power is run according to setting value, and microgrid power fluctuation is stabilized in completion, and then improves micro-capacitance sensor power supply quality.
Fig. 2 and Fig. 3 is the micro-capacitance sensor power supply quality intelligent evaluation device flow chart and structure chart of the embodiment of the present invention, micro-capacitance sensor
The specific implementation of power supply quality intelligent evaluation device includes the following steps：
Step 1：Data after being calculated by sampling module obtain four voltage, electric current, frequency, power factor aspect data,
Voltage includes voltage deviation, voltage fluctuation and flicker, harmonic content, non-equilibrium among three phase voltages, temporary overvoltage, transient state mistake again
Six features such as voltage, electric current include one feature of current harmonic content, and frequency includes one feature of frequency departure, power factor
Including one feature of power factor size, i.e. each variable of sample set include 9 features, sample set is expressed as matrix
N is sample size.
Step 2：Place is normalized to each feature of micro-capacitance sensor power supply quality feature set using 0 mean value standardization formula
Reason, normalization formula are
In formula, mean (x) is that each sample characteristics concentrate the average value of each feature, and σ is the standard deviation of this feature, at normalization
Reason is capable of training speed and the accuracy of lift scheme.
Step 3：Sample data is labeled according to national standard, labeled data collection is used
It indicates, i.e., concentrates the sample for meeting power supply quality requirement to be labeled as (1,0) sample characteristicsT, it is unsatisfactory for power supply matter
The sample of amount standard is labeled as (0,1)T。
Specific power supply quality national standard respectively refers to《Power quality admissible deviation of supply volt- age》(GB/T12325-
2003),《Utility network harmonic wave》(GB/T 14549-1993),《Three-phase voltage allows degree of unbalancedness》(GB/T 15543-
2008),《Power system frequency tolerance》(GB/T 15949-1995),《Voltage fluctuation and flicker》(GB/T 12326-
2008),《Temporary overvoltage and transient overvoltage》(GB/T 18481-2001).
Step 4：According to ratio random division training sample and test sample, and according to step 3 to sample data into rower
Note.
Step 5：The each training sample chosen to step 4 is trained using bottom-to-top method, to training process
Input layer, training layer, tuning layer, output layer four levels are divided into, the input layer input value of each sample is xi(i=1,
2 ... 9), and training layer input value is eh(h=1,2 ..., q), q are training layer unit number, and 5 layers are chosen in the embodiment of the present invention
Training layer, every layer of trained layer number are followed successively by 45,36,18,9,2, and output layer input value is yj(j=1,2) is biased to training layer
γh, output layer bias θj, i-th of unit of input layer and training layer h-th of unit connection weight vih, training layer h-th of unit
With the connection weight w of j-th of unit of output layerhj4 parameters assign random value, tuning layer parameter η1、η2、η3、η44 learning rate ginsengs
Number assigns initial value 0.1.
Step 5-1：The input value calculation basis formula of training layer and output layer
It calculates.
Step 5-2：Input by the output of training layer as next trained layer, repeats step 5-1, reaches setting training layer
After number, the above parameter is inputted into tuning layer from top to down and carries out arameter optimization.
Step 5-3：Foundation in the processing of tuning layer data
Calculate the mean square error of each sample, in formula,It is expected for the output valve of each sample of output layer.
Step 5-3-1：Output layer biases θ in tuning layerjTuning formula be
In formulaCalculation formula be
Step 5-3-2：The connection weight w of training j-th of unit of h-th of unit of layer and output layerhjTuning formula be
In formulaCalculation formula be
Step 5-3-3：Training layer biases γ in tuning layerhTuning formula be
The solution formula of partial derivative is in formula
Therefore
Step 5-3-4：The connection weight v of i-th of unit of input layer and training h-th of unit of layer in tuning layerihTuning
Formula is
In formulaSolution formula be
Therefore
Step 6：Training sample final output value is assessed using test sample, if training result is unsatisfactory for accuracy
It is required that return to step 5, continues to carry out tuning to parameter, if training result meets accuracy requirement, whether foundation power supply quality
It is that standard set judges that simulation Load balanced control device needs come into operation.
Fig. 4 is the autonomous equalization algorithm work flow diagram of power equalization control device power of the embodiment of the present invention, and the present invention is implemented
In example, energy storage device has N number of, that is, simulating load cell has N number of, and each load cell of simulating is indicated with letter i, power equalizer
The middle autonomous equalization algorithm of power includes the following steps：
Step 1：Receive micro-capacitance sensor power supply quality intelligent evaluation device needs to simulate the instruction that load comes into operation；
Step 2：Power equalizer reads micro-capacitance alternating current bus voltage, electricity from micro-capacitance sensor power supply quality intelligent evaluation device
Stream, frequency, and current state-of-charge SOC (State of Charge) and maximum discharge charge electric work are read from each energy storage device
Rate, maximum charge power Pi mc(Qi mc) indicate, maximum discharge power Pi md(Qi md) expression, the wherein maximum of energy storage device
Charge/discharge power determines, the state-of-charge of each energy storage device is labeled as according to energy storage device self-characteristic when being dispatched from the factory by equipment
SOCi(i=1,2 ... ... N)；
Step 3：Whether each simulation load cell is come into operation with switching value uiIt indicates, ui1 expression is taken to simulate load list
Member comes into operation, ui0 expression simulation load cell is taken not come into operation, uiValue depend on energy storage device SOC, i.e. energy storage
Equipment SOC u when equipment allows in working rangei1 is taken, energy storage device SOC u when equipment allows outside working rangei0 is taken, energy storage
The permission working range of equipment is determined also according to energy storage device self-characteristic when being dispatched from the factory by equipment；
Step 4：By maximum allowable charge/discharge rating formula
Calculate separately the simulation maximum allowable charge/discharge power of load parallel system, the wherein maximum allowable charge power of system
For Pmc(Qmc), the maximum allowable discharge power of system is Pmd(Qmd)；
Step 5：Load charge/discharge set value of the power is simulated to calculate.It can must be simulated by the electric generating set rotor equation of motion negative
The relationship of G system set value of the power and rotary speed of generator group
Being write as state equation form is
Wherein, ωNFor rated angular velocity, δ is generator rotor angle, PT、PE、PDThe respectively mechanical output of generating set, output power
And loss power, TJFor equivalent inertia time constant, calculation formula isTJiFor the inertial time of every generating set
Between constant, continue to derive the relationship of load system set value of the power and frequency of can must simulating
Wherein, ω and f is respectively center of inertia angular speed and center of inertia frequency, can be by
Calculating is got.
Simulating load need to be from the work(in the reactive power foundation active power setting value and step 1 of net side absorption/compensation
Rate factor is got by Q*=P* × tan θ calculating, and wherein θ is power-factor angle.
Step 6：By the simulation load parallel system set value of the power for calculating gained in step 5 and calculating gained in step 4
The maximum allowable charge/discharge power of simulation load parallel system compare, take in the two smaller value as new simulation load simultaneously
Contact system set value of the power；
Step 7：According to the SOC of the respective energy storage device of simulation load cell, by calculation formula
Calculate the charge/discharge power that each simulation load cell should distribute, wherein the charging work(of each simulation load cell
Rate is Pi c(Qi c), discharge power Pi d(Qi d),
Step 8：The performance number that each simulation load cell is assigned to is sent to two-way AC-DC current transformers and bi-directional DC-DC
The control unit of converter.
Fig. 5 is the simulation load cell composition frame chart of the embodiment of the present invention, and simulation load cell is by two-way AC-DC unsteady flows
Device, bidirectional DC-DC converter and energy storage device composition, Fig. 6 are the simulation load cell topology diagram of the embodiment of the present invention,
In the topological structures of two-way AC-DC current transformers include that micro-capacitance alternating current bus side filter inductance, six switching devices constitute three
Controlled bridge arm A, B, C and DC side filter capacitor；The topological structure of bidirectional DC-DC converter includes two IGBT and inductance
Constitute the two-way Buck/Boost circuits of the two-way lifting/voltage reducing of energy.
Fig. 7 is the two-way AC-DC current transformers control block diagram of the embodiment of the present invention, is obtaining each simulation load cell
After charge/discharge set value of the power P* (Q*), simulation load and micro-capacitance sensor are handed over to realize using the full decoupled control method of power
Active power, the Reactive Power Control at bus interface are flowed, the sagging of active power and frequency and reactive power and voltage is utilized
Relationship
It is finally reached the target for adjusting micro-capacitance sensor voltage and frequency in critical field, wherein U and U0Respectively survey
Micro-capacitance alternating current bus voltage and busbar voltage standard value (380V), f and f0Respectively actually measured micro-capacitance alternating current bus
The standard value (50Hz) of frequency and frequency, P and P* are respectively that practical micro-capacitance alternating current bus active power value and active power are set
Definite value, Q and Q* are respectively practical micro-capacitance alternating current bus reactive power value and reactive power setting value, and m, n are sagging coefficient, just
The sagging coefficient that begins is set as 0.11.
According to the thought and Kirchhoff's law of rectification and inversion, controls, can obtain in conjunction with the power decoupled of PWM rectifier
Rotation dq coordinate systems under current equation be
Wherein, LsFor micro-capacitance alternating current bus side filter inductance, 0.5mH, e are taken as in the embodiment of the present inventiond、eqFor transformation
Micro-capacitance alternating current bus voltage under to dq coordinate systems, id、iqTo transform to the micro-capacitance alternating current bus electric current under dq coordinate systems, R
For micro-capacitance alternating current bus side line resistance, ω is micro-capacitance alternating current bus angular frequency, ud、uqFor the switch electricity under dq coordinate systems
Press vector.
D axis in selection dq rotating coordinate systems is overlapped with voltage vector, ignores switching loss and exchange side resistance loss, is tied
Close electric current and instantaneous power equation under rotating coordinate system
Power is set as closed loop to adjust, is obtained
On the basis of decoupling control, according to active power and frequency and the sagging relationship of reactive power and voltage, increase pair
The robust droop control device of frequency and voltage deviation, i.e., by the proportional action of frequency departure and voltage deviation through the sagging coefficient of robust
Be added to after clipping module in the deviation of active power and reactive power, then carry out power and obtain decoupling control, improve system
Robustness.The efficiency analysis of robust droop control device includes the following steps：
Step 1：According to formula
Micro-capacitance alternating current bus side power regulation relative error is calculated, e is usedP、eQIt indicates, P and P* is respectively practical micro- in formula
Power grid ac bus active power value and active power setting value, Q and Q* are respectively practical micro-capacitance alternating current bus reactive power
Value and reactive power setting value；
Step 2：According to sagging relationship
Arrange to obtain power deviation and frequency, the mathematical relationship of voltage deviation
And power relative error formula is substituted into, obtain power relative error
Step 2-1：Micro-capacitance alternating current bus relative difference on frequencyVariation is little over a period to come, then sagging Coefficient m
Bigger, the relative error of micro-capacitance alternating current bus side active power is bigger；
Step 2-2：Micro-capacitance alternating current bus voltage relative errorVariation is little over a period to come, then sagging coefficient n
Bigger, the relative error of micro-capacitance alternating current bus side reactive power is bigger；
Step 3：Micro-capacitance alternating current bus frequency and voltage deviation are after robust droop control, power regulation relative error
Become
K in formulap、KqFor the sagging coefficient in robust droop control device in Fig. 7, initial value is set as 0.1, by under robust
Vertical COEFFICIENT Kp、KqThe influence of sagging Coefficient m, n to power relative error is balanced, to improve power control accuracy.
Fig. 8 is the bidirectional DC-DC converter control block diagram of the embodiment of the present invention, bidirectional DC-DC converter control section
Specific implementation includes the following steps：
Step 1：Compare the size of micro-capacitance alternating current bus side power and set value of the power；
Step 2：When micro-capacitance alternating current bus side power is more than set value of the power, selection simulates load charge mode to inhale
Receive micro-capacitance sensor surplus power, energy storage device electric current, voltage and SOC detected by sensor, stabilize microgrid power fluctuation and
It protects under two constraintss of energy storage device,
Step 2-1：When energy storage device SOC is less than 10%, to prevent initial stage charging current is excessive from causing to energy storage device
Damage, using constant current charge pattern come to energy storage device carry out charging process；
Step 2-2：When energy storage device SOC reaches 20%, switching charge mode is invariable power charge mode, this charging mould
Under formula, the power and micro-capacitance sensor surplus power that energy storage device absorbs are properly balanced, and energy storage device most effective can play flat at this time
Press down the effect of microgrid power fluctuation；
Step 2-3：After charging voltage reaches energy storage device nominal voltage, it is switched to constant voltage charge mode, prevents from filling
The excessively high damage energy storage device of piezoelectric voltage；
Step 2-4：When the SOC of energy storage device is higher than 90%, to protect energy storage device, the mistake for causing energy storage device is avoided
Degree charges, at this time switch function ui0 is taken, i.e., energy storage device under this state no longer comes into operation.
Step 3：When micro-capacitance alternating current bus side power is less than set value of the power, selection simulates load discharge mode to mend
The power for repaying micro-capacitance sensor missing detects energy storage device electric current, voltage and SOC by sensor, is stabilizing microgrid power fluctuation
Under protection two constraintss of energy storage device,
Step 3-1：When energy storage device discharge voltage is higher than minimum discharge voltage, discharge mode is selected to discharge for invariable power
Pattern, under this discharge mode, the power that power and micro-capacitance sensor that energy storage device is released lack is properly balanced, at this time energy storage device energy
The effect of microgrid power fluctuation is stabilized in most effective performance；
Step 3-2：When energy storage device SOC is less than 30%, with the reduction of energy storage device itself internal resistance, to prevent from discharging
Electric current is excessive, and the constant current discharge pattern of selection simulation load carries out discharge treatment；
Step 3-3：After discharge voltage reaches energy storage device minimum discharge voltage, to protect energy storage device, avoid causing
The over-discharge of energy storage device, at this time switch function ui0 is taken, i.e., energy storage device under this state no longer comes into operation.
Described in conjunction with the control block diagram and step of Fig. 8, Fig. 9 be the energy storage device charge power of the embodiment of the present invention, voltage,
Current-mode switching figure, Figure 10 are the energy storage device discharge power of the embodiment of the present invention, voltage, current-mode switching figure, can be with
Energy storage device is clearly seen in when switching charge/discharge pattern.
In the embodiment of the present invention, Figure 11 is micro-capacitance sensor voltage oscillogram, and Figure 12 is micro-capacitance sensor current waveform figure, and Figure 13 is micro-
Mains frequency oscillogram meets power supply quality requirement in micro-capacitance alternating current bus voltage, electric current and frequency.
Figure 14 and Figure 15 is the simulation load exchange side active power and reactive power oscillogram of the embodiment of the present invention, active
Power setting initial value is 10kW, 15kW is switched to when system operation is to 0.4s, and micro-capacitance sensor voltage occurs in 0.7s and temporarily drops
And frequency fluctuation, the set value of the power of the load system of adjustment simulation in time make it maintain 10kW；Reactive power sets initial value
For 0kVar, 10kVar is switched to when system operation is to 0.4s, micro-capacitance sensor voltage temporarily drop and frequency fluctuation occurs in 0.7s, and
When adjustment simulation load system set value of the power, so that it is maintained 0.9kVar, from micro-capacitance alternating current bus side active power with
Reach control simulation load exchange side power foundation micro-capacitance alternating current bus power swing requirement on the tracing control of reactive power,
Microgrid power fluctuation is stabilized, the target for improving micro-capacitance sensor power supply quality is finally reached.
Claims (10)
1. a kind of micro-capacitance sensor power supply quality assessment and its simulation Load balanced control system, which is characterized in that the system includes micro-
Network voltage, electric current, frequency acquisition module, micro-capacitance sensor power supply quality intelligent evaluation device and simulation Load balanced control device, wherein：
Micro-capacitance sensor voltage, electric current, frequency acquisition module：For acquiring real-time micro-capacitance sensor voltage, electric current, frequency values and being sent to micro-
In grid supply quality intelligent evaluation device；
Micro-capacitance sensor power supply quality intelligent evaluation device：Real-time micro-capacitance sensor voltage, electric current, frequency are calculated for analyzing, assesses micro-capacitance sensor
Whether power supply quality meets the requirements, and judges to simulate whether Load balanced control device needs to devote oneself to work；
Simulation Load balanced control device includes power equalizer, simulation load system；
Power equalizer：Value is received and sent out to active power and reactive power for calculating simulation loading module, for simulation
Value is received and sent out to each energy storage device equilibrium assignment active power of load and reactive power；
Simulate load system：For absorbing or sending out active power or reactive power, microgrid power fluctuation is stabilized, micro- electricity is improved
Net power supply quality constitutes analog load parallel running system by the parallel connection of multiple simulation load cells；The simulation load list
Member includes two-way AC-DC current transformers, bidirectional DC-DC converter, two-way AC-DC current transformers power controller, bidirectional DC-DC converter
Device controller and energy storage device.
2. a kind of method micro-capacitance sensor power supply quality assessment and its simulate Load balanced control system, special described in claim 1
Sign is, includes the following steps：
Step 1：Using micro-capacitance sensor power supply quality intelligent evaluation device, calculates analysis and pass through micro-capacitance sensor voltage, electric current, frequency collection
The real-time micro-capacitance sensor voltage of module acquisition, electric current, frequency data, and assess real-time micro-capacitance sensor according to national power quality standard and supply
Whether electricity quality meets standard, comes into operation if being unsatisfactory for standard analog Load balanced control device needs；
Step 2：When judging to need to put into Load balanced control device, power equalizer will be according to micro-capacitance sensor power supply quality intelligence
Voltage in evaluator and frequency obtain the setting value of system charge-discharge electric power using the autonomous equalization algorithm of power, and combine mould
The maximum allowable charge and discharge of the SOC calculating simulations load cell and system of load cell energy storage device is each simulated in quasi- load system
Electrical power, while calculating the charge-discharge electric power setting value that each simulation load cell should distribute according to the SOC of energy storage device.
3. a kind of method of micro-capacitance sensor power supply quality assessment and its simulation Load balanced control system according to claim 2,
It is characterized in that, step 1 specifically includes following steps：
Step 1：It is obtained after being handled by sampling module comprising voltage deviation, voltage fluctuation and flicker, harmonic content, three-phase voltage not
The sample characteristics collection of the degree of balance, temporary overvoltage, transient overvoltage, 9 current harmonic content, frequency departure features；
Step 2：Each feature of micro-capacitance sensor power supply quality feature set is normalized；
Step 3：Sample data is labeled according to power supply quality national standard；
Step 4：According to ratio random division training sample and test sample, and sample data is labeled according to step 3；
Step 5：The each training sample chosen to step 4 is trained using bottom-to-top method, is divided to training process
For input layer, training layer, tuning layer, output layer four levels, successively training optimizes；
Step 6：Training sample final output value is assessed using test sample, the accuracy rate of assessment system training, if sample
Originally it is unsatisfactory for power supply quality requirement, then simulates Load balanced control device needs and comes into operation.
4. a kind of method of micro-capacitance sensor power supply quality assessment and its simulation Load balanced control system according to claim 3,
It is characterized in that, the step 5 in step 1 specifically includes following steps：
Step 5-1：When training starts corresponding initial value is assigned to each layer parameter；The input value calculation basis formula of training layer and output layer
It calculates；
Step 5-2：Input by the output of training layer as next trained layer, repeats step 5-1, reaches the setting training number of plies
Afterwards, the above parameter is inputted into tuning layer from top to down and carries out arameter optimization；
Step 5-3：Arameter optimization processing is carried out to evaluation process.
5. special according to the method that a kind of micro-capacitance sensor power supply quality of claim 4 is assessed and its simulates Load balanced control system
Sign is that step 5-3 specifically includes following steps：
Calculate the mean square error E of each sample；
Step 5-3-1：Output layer biases θ in tuning layerjTuning formula be
Step 5-3-2：The connection weight w of training j-th of unit of h-th of unit of layer and output layerhjTuning formula be
Step 5-3-3：Training layer biases γ in tuning layerhTuning formula be
Therefore
Step 5-3-4：The connection weight v of i-th of unit of input layer and training h-th of unit of layer in tuning layerihTuning formula
For
Therefore
6. a kind of method of micro-capacitance sensor power supply quality assessment and its simulation Load balanced control system according to claim 2,
It is characterized in that, the autonomous equalization algorithm of the power of the power equalizer in step 2 includes the following steps：
Step 1)：It is followed according to the assessment result of micro-capacitance sensor power supply quality intelligent evaluation device if simulation load need not come into operation
Ring executes this step；If simulation load needs come into operation, step 2) is executed；
Step 2)：According to SOC and energy storage device parameter calculating simulation load cell and the maximum allowable charge-discharge electric power of system；
Step 3)：According to voltage, frequency values and each generating equipment parameter of micro-capacitance sensor power supply quality intelligent evaluation device, system is calculated
System charge/discharge set value of the power；
Step 4)：The set value of the power in step 3 is taken to make with value smaller in the maximum allowable charge-discharge electric power of system in step 2)
For new system power setting value；
Step 5)：According to battery SOC and power weight distribution formula, the set value of the power of each simulation load cell is obtained, it will
It send into two-way AC-DC current transformers power controller.
7. a kind of method of micro-capacitance sensor power supply quality assessment and its simulation Load balanced control system according to claim 6,
It is characterized in that, maximum allowable charge/discharge rating formula is in step 2)
In formula, N indicates that simulation load cell, that is, energy storage device number, each load cell of simulating are indicated with letter i, each energy storage
The state-of-charge of equipment is SOCi(i=1,2 ... ... N), Pi mcIndicate maximum allowable charging active power, Qi mcIt indicates maximum to permit
Perhaps charge reactive power, Pi mdIndicate maximum allowable electric discharge active power, Qi mdIndicate maximum allowable electric discharge reactive power, it is each to store up
The maximum charge/discharge power of energy determines, switching value u according to energy storage device self-characteristic when being dispatched from the factory by equipmentiTake 1 expression simulation negative
Lotus unit comes into operation, ui0 expression simulation load cell is taken not come into operation, uiValue depend on energy storage device SOC, i.e.,
Energy storage device SOC u when equipment allows in working rangei1 is taken, energy storage device SOC u when equipment allows outside working rangeiTake 0.
8. a kind of method of micro-capacitance sensor power supply quality assessment and its simulation Load balanced control system according to claim 6,
It is characterized in that, step 3) system charge/discharge set value of the power calculates, load system must be simulated by the electric generating set rotor equation of motion
The relationship of system charge-discharge electric power and rotary speed of generator group
Being write as state equation form is
Wherein, ωNFor rated angular velocity, δ is generator rotor angle, PT、PE、PDThe respectively mechanical output of generating set, output power and damage
Wasted work rate, TJFor equivalent inertia time constant, calculation formula isTJiInertia time for every generating set is normal
Number continues the relationship for deriving to simulate load system charge-discharge electric power and frequency
Wherein, ω and f is respectively center of inertia angular speed and center of inertia frequency, by
Calculating is got.
9. a kind of method of micro-capacitance sensor power supply quality assessment and its simulation Load balanced control system according to claim 6,
It is characterized in that, step 5) is calculated the set value of the power of each simulation load cell by battery SOC and power weight distribution formula,
Power weight distribution formula is
In formula, each charge power for simulating load cell is Pi c(Qi c), discharge power Pi d(Qi d), by result of calculation send to
In two-way AC-DC current transformers power controller.
10. a kind of method of micro-capacitance sensor power supply quality assessment and its simulation Load balanced control system according to claim 6,
It is characterized in that, two-way AC-DC current transformers power control unit is according to the set value of the power obtained by power equalizer in step 5)
Two-way AC-DC current transformers are controlled, microgrid power decoupling control is completed, reach the target for improving micro-capacitance sensor power supply quality；Simultaneously
Robust droop control device balance micro-capacitance sensor frequency and voltage deviation are added in power decoupled control, improves the robustness of system,
Specially：Frequency departure and voltage deviation are added to active power after the proportional action of the sagging coefficient of robust and clipping module
In the deviation of reactive power, the robustness of system is improved, the efficiency analysis of robust droop control device is opposite accidentally by frequency
Difference embodies, and obtaining power relative error according to sagging relationship is
Be added robust droop control device after power relative error be
Pass through the sagging COEFFICIENT K of robustp、KqThe influence of sagging Coefficient m, n to power relative error is balanced, power control accuracy is improved.
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