CN109962485A - A kind of composite energy storing device addressing constant volume method towards source net lotus close friend interaction - Google Patents
A kind of composite energy storing device addressing constant volume method towards source net lotus close friend interaction Download PDFInfo
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Abstract
The invention discloses a kind of composite energy storing device addressing constant volume methods towards source net lotus close friend interaction, include: site selecting method: distribution network system being abstracted turn to tree-shaped catalogue model first, then the Nonlinear System of Equations of any dimension is solved by least square method, obtain the node voltage vector of all nodes in model, finally addressing purpose index according to actual needs, to evaluate the superiority and inferiority of energy storage device on-position, and with other on-position scheme across comparisons, obtain the optimal addressing of energy storage device under the model；Constant volume method: optimizing constant volume model by building composite energy storage first, determines the objective function of optimization and the constraint condition of model；Then pass through the capacity ratio of both PSO Algorithm battery/super capacitors.The present invention realizes the accurate modeling to composite energy storing device Optimizing Site Selection constant volume Optimized model, and ideal objective optimization has been calculated as a result, energy storage device is made to reach preferable access effect.
Description
Technical field
The present invention relates to the composite energy storing device addressing constant volume skills in intelligent power grid technology field, especially active distribution network
Art.
Background technique
As a kind of Managed Solution of Permeability Distribution formula power supply, active distribution network has obtained universal concern.As one
The important energy snubber link of kind, energy storage device have great significance in the operation of micro-capacitance sensor.It is filled compared to single energy storage
It sets, composite energy storing device has huge in terms of effectively extending working life, reply distributed generation resource fluctuates frequent
Advantage.In view of the introducing of high-cost super capacitor, addressing constant volume of the composite energy storing device in micro-capacitance sensor, which becomes, to be needed to solve
Certainly the problem of.Capacity configuration and addressing it is reasonable whether, be directly related to effect quality that composite energy storing device can rise and
The height of cost.Due to the two usually conflict objective each other, how finding equalization point and carrying out choice is the most important thing.Only it is based on
Accurate composite energy storing device addressing constant volume model foundation and mathematical algorithm is correctly solved, can preferably complete to optimize
Index makes energy storage device reach preferable access effect.
Summary of the invention
The technical problem to be solved by the invention is to provide a kind of effects preferably, with suitable feasibility based on most
Composite energy storing device addressing constant volume method in small square law and the micro-capacitance sensor of particle swarm algorithm.
In order to solve the above technical problems, the present invention adopts the following technical scheme: a kind of answering towards source net lotus close friend interaction
Close energy storage device addressing constant volume method, comprising:
Site selecting method: turning to tree-shaped catalogue model for distribution network system is abstract first, then according to branch impedance with
And model topology constructs node admittance matrix, then is balanced using the inflow and outflow of a certain node power as the foundation to establish an equation, and
All nodes are expanded to, formation is essentially the nodal voltage equation group of Nonlinear System of Equations, solves and appoints by least square method
Anticipate dimension Nonlinear System of Equations, obtain the node voltage vector of all nodes in model, in model the calculating of trend by by
The mode of grade iteration obtains the inflow and outflow power of each node and the line loss of each branch road, finally according to reality
The addressing purpose index of demand, to evaluate the superiority and inferiority of energy storage device on-position, and with other on-position scheme across comparisons,
Obtain the optimal addressing of energy storage device under the model；
Constant volume method: constant volume model is optimized by building composite energy storage first, determines the objective function and model of optimization
Constraint condition；Then pass through the capacity ratio of both PSO Algorithm battery/super capacitors.
Optionally, site selecting method includes the following steps:
Practical distribution network is abstracted as tree-shaped nodal analysis method by step (1), obtains branch impedance and the position of all branches
In the payload of each node, and unify dimension, obtains place in distributed generation resource that is to be applied, the determining scale typical odd-numbered day
Manage delta data, it is assumed here that abstract result is the electricity distribution network model of a n node；
Step (2) constructs the node admittance of n*n dimension by the obtained model parameter of step (1) and its topological structure
Matrix Yij, expression and calculating for nodal voltage equation；
Step (3) determines energy storage device on-position and distributed generation resource power output size that this is calculated；
Step (4), building n-1 tie up nodal voltage equation group, are flowed into according to each node and flow out power-balance come structure
Equation group is built, due to without the concern for balance nodes, so equation only has n-1, for the convenience of operation later, equation group
Using the representation of rectangular co-ordinate:
Step (5) solves the Nonlinear System of Equations using least square method, obtain the node voltage of each node to
Amount；
Step (6) calculates network trend, Load flow calculation used by this method be from the final stage anti-mode pushed away step by step, certain
The mode of one single recursion byIt realizes, from end up recursion institute step by step
There is a line loss Δ S of branch, and the apparent energy S of outflow node j, it, can be with by the balance of node power until at branch beginning
Calculate energy storage device it is a certain when absorption/delivered power power for inscribing, it is hereby achieved that each energy storage device access digit is commented on
Data required for valence mode；
Step (7), replacement to next distributed generation resource power output sampled point, repeats step (3) to step (6) until all
Steady-state load flow parameter has all obtained under distributed generation resource power output sampled point；
Step (8) designs and calculates access scheme Quantitative evaluation standard, using four kinds of evaluation parameters: capacity of energy storing device
It is required that the requirement of voltage fluctuation minimum, loss minimization requirement, node voltage limitation require, adopted according to all of acquisition in step (7)
The system load flow parameter at sampling point moment substitutes into the parametric results (f for obtaining all evaluation methods1, f2, f3, f4)；
Step (9) replaces energy storage device on-position, repeat step (1) to step (9) until it is all it is potential most preferably
The result of all evaluation parameters has all obtained in the case of location
(f1 2, f2 1, f3 1, f4 1......f1 n, f2 n, f3 n, f4 n)；
Step (10), the various access way parameters of across comparison, selects optimal access result.
Optionally, according to the requirement of Load flow calculation, it is specified that the access node of the power output device in generating set, power distribution network is
PV node, it is characterized in that the active power input determined and determining node voltage virtual value；Provide general load point for PQ section
Point, it is characterized in that active power and the reactive power input determined；Energy storage device is regarded as balance section due to its effect here
Point, it is characterized in that the uncertain active node voltage vector with reactive power input/output and determination, is used as entire distribution
The reference of net node voltage is, it is specified that for a certain node, and power inflow is positive, and outflow is negative.
Optionally, step (10) selects optimal access by design weighting function quantitative manner or artificial perceptual knowledge
As a result.
Optionally, constant volume method includes the following steps:
Step (11) obtains processing variation data in distributed generation resource that is to be applied, the determining scale typical odd-numbered day；
Step (12) constructs the objective function and constraint item of composite energy storing device constant volume Optimized model according to actual needs
Part, wherein two objective functions of setting: 1. cost minimization targets and 2. system powers vacancy/surplus are minimum, the constraint of consideration
Condition has: capacity of energy storing device constraint, energy storage device export/absorb power constraint, system operating power Constraints of Equilibrium, load and lack
Electric rate/energy spilling constraint；
Distributed generation resource power output is subtracted payload and obtains composite energy storage power compensation ideal value P by step (13)hess=
Ppv-Pload, its spectral characteristic is obtained by Fast Fourier Transform, and P is determined according to its spectral characteristichessNeed by from
Dissipate the cutoff frequency of low-pass filter；
Step (14) designs Butterworth low-pass filter, respectively based on the cutoff frequency that step (13) obtains
A parameter designing is as follows: cut-off frequecy of passband Wp；Stopband cutoff frequency Ws；Decaying maximum value Rp in passband；Declining in stopband
Subtract minimum value Rs；Sample frequency fs；
Step (15), by PhessBy discrete low-pass filter, P is obtainedhessLow frequency component, be battery ideal compensation
Step (16) determines that the battery/super capacitor operating parameter used, the parameter considered here have: rated power,
Maximum/minimum state-of-charge, unit price, self discharge efficiency；
The subproblem of only objective function 1 and only objective function 2 is separately optimized with particle swarm algorithm in step (17),
Wherein the objective function in each subproblem is as the adaptive response function in each subproblem；
Step (18) respectively substitutes into subproblem 1 and 2 optimum results of subproblem in objective function 2 and objective function 1, fortune
With fitness profit ranking method, the weighting coefficient of different target function is adjusted by quantitative method, multiple objective function is excellent
Change problem is integrated into single-goal function optimization problem
Step (19) calculates the single-goal function optimization through integrating that step (15) obtain with particle swarm algorithm again and asks
Topic, obtains cost and system power vacancy/surplus of last capacity configuration result and the allocation plan.
Optionally, each constraint condition implementation of step (17) is as follows: battery is repaired with super capacitor power, state-of-charge
Just, it corrects according to the constraint condition to introduce；System power Constraints of Equilibrium passes through introducing system vacancy power/system surplus power
Variable balances power equation, is both greater than and at most only has one and is greater than zero；Calculate current capacities under system vacancy power/
System surplus power obtains load short of electricity rate/energy spilling constraint, if calculated result exceeds feasible zone range, by adding
The mode of a upper penalty function forces particle to return to feasible zone.
The present invention by adopting the above technical scheme, according to the data that the existing distributed generation resource odd-numbered day contributes, fully considers
All kinds of constraint conditions in micro-capacitance sensor operational process, schematically illustrate representative optimization object function, realize to composite energy storage
The accurate modeling of installation optimization addressing constant volume Optimized model.On the basis of this model, used respectively with least square method with
Particle swarm algorithm is the derivation algorithm of core, and during all kinds of constraint conditions are integrated into derivation algorithm, reason has been calculated
The objective optimization thought is as a result, make energy storage device reach preferable access effect.
The specific technical solution of the present invention and its advantages will in the following detailed description in conjunction with attached drawing into
Row detailed description.
Detailed description of the invention
Present invention will be further described below with reference to the accompanying drawings and specific embodiments:
Fig. 1 is Load flow calculation recurrence model；
Fig. 2 is IEEE-14 node power distribution pessimistic concurrency control topology；
Fig. 3 is that battery/super capacitor output power and state-of-charge correct flow chart；
Fig. 4 is composite energy storing device ideal compensation value Phess；
Fig. 5 is Phess frequency response chart；
Fig. 6 is the waveform after Phess low-pass filter；
Fig. 7 is output/absorption power of battery and super capacitor；
Fig. 8 is power shortage/surplus；
Fig. 9 is battery/super capacitor SoC state-of-charge；
Figure 10 is Butterworth low-pass filter effect.
Specific embodiment
For addressing constant volume problem common in active distribution network, the invention proposes a kind of effects preferably, has phase
When composite energy storing device addressing constant volume method in a kind of micro-capacitance sensor based on least square method and particle swarm algorithm of feasibility.It should
Addressing is divided into two sub-problems with constant volume and accounted for by method.
Wherein, step (1) to step (10) are site selecting method.
Practical distribution network is abstracted as tree-shaped nodal analysis method by step (1), obtains branch impedance and the position of all branches
In the payload of each node, and unify dimension.Obtain place in distributed generation resource that is to be applied, the determining scale typical odd-numbered day
Delta data is managed, the sampling interval should not be too large also unsuitable too small.Here example uses ieee-14 node power distribution pessimistic concurrency control in Fig. 2.
Each branch data and node load enter following table:
Step (2) constructs the node admittance of n*n dimension by the obtained model parameter of step (1) and its topological structure
Matrix Yij, expression and calculating for nodal voltage equation.
Step (3) determines energy storage device on-position and distributed generation resource power output size that this is calculated.According to trend
The requirement of calculating, usually regulation generating set, power output device in power distribution network access node be PV node, be 1 in this example
Number node；Provide that general load point is PQ node；Energy storage device accesses for the first time since its effect is regarded as balance nodes here
Position is determined using random function, is selected as No. 3 nodes in this example.For a certain node, power inflow is positive regulation, flows out and is
It is negative.The photovoltaic devices odd-numbered day that this example uses in addressing and constant volume calculate goes out force data and all comes from green electric power supply net photovoltaic
Monitor supervision platform (lvsedianli.com) has used Jiuquan technical college 0.4MWp roof solar photovoltaic on May 11st, 2018
Device is contributed, and is divided into 5 minutes, i.e. 288 sampled points between former data time, only used the light at integral point moment in addressing calculating
Volt device goes out force data, and photovoltaic data are as follows:
| 0:00 | 1:00 | 2:00 | 3:00 | 4:00 | 5:00 | 6:00 | 7:00 |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7.8 |
| 8:00 | 9:00 | 10:00 | 11:00 | 12:00 | 13:00 | 14:00 | 15:00 |
| 23.3 | 37.7 | 49.8 | 51.8 | 53.2 | 52.2 | 54.1 | 51.7 |
| 16:00 | 17:00 | 18:00 | 19:00 | 20:00 | 21:00 | 22:00 | 23:00 |
| 41.4 | 45.7 | 33.3 | 19.4 | 6.3 | 0 | 0 | 0 |
Step (4), building n-1 tie up nodal voltage equation group.It is flowed into according to each node and flows out power-balance come structure
Equation group is built, due to without the concern for balance nodes, so equation only has n-1.For the convenience of operation later, equation group
Using the representation of rectangular co-ordinate:
Wherein:
UiFor the node voltage of i-th of node；
Pi、QiThe power component of respectively No. i-th node load, reactive component.Due to being power injection equation, so rule
Fixed is just injecting power, is born to consume power；
Gij、BijThe respectively real part of the i-th row of node admittance matrix jth column element, imaginary part.Node admittance matrix is by micro- electricity
Net topology and its branch terminal impedance determine；
ei、fiReal part, imaginary part for No. i-th node voltage.
Step (5) solves the Nonlinear System of Equations using least square method, obtain a certain access scheme, it is a certain when inscribe
The node voltage vector U=[e of each node1, f1, e2, f2..., e14, f14]。
Step (6) calculates network trend.Load flow calculation used by this method be from the final stage anti-mode pushed away step by step, certain
The mode of one single recursion byIt realizes, wherein assuming that trend flows into node j, P and Q points from node i
The active power and reactive power of node j Wei not be flowed into, R and X respectively indicate resistance and reactance of the node i to node j branch road,
UjIndicate the node voltage at node j.From the end up line loss Δ S of all branches of recursion, and the view of outflow node j step by step
In power Sj, Sj=Si+ Δ S, wherein SiIndicate the apparent energy of outflow node i.To branch beginning (energy storage device access node)
Place, by the balance of node power can calculate energy storage device it is a certain when absorption/delivered power power for inscribing.It is possible thereby to
Obtain data required for the evaluation method of each energy storage device on-position, i.e. capacity of energy storing device, voltage fluctuation and line loss.
Step (7), replacement to next distributed generation resource power output sampled point, repeats step (3) to step (6) until all
Steady-state load flow parameter has all been arranged under distributed generation resource power output sampled point.
Step (8) designs and calculates access scheme Quantitative evaluation standard.Assessment parameter with practical significance can be made
For one of judgment criteria, while appropriate choice can also be done to it according to actual operational objective and expectation.This programme uses four
Kind evaluation parameter:
1) capacity of energy storing device requirement:
E(k)≥|Eup-Elo|
Wherein, E(k)Indicate that electricity after kth kind energy storage device access way places an order in a few days energy storage device peak regulation is full of
Surplus, EupIndicate energy storage device maximum charge/discharge capacity, EloIndicate energy storage device minimum charge/discharge capacity, PsiIt indicates at i-th
The charge-discharge electric power of energy storage device in period, Δ t indicate time interval.
2) voltage fluctuation minimum requirement:
Wherein, Δ U(k)Indicate that the voltage of energy storage device always fluctuates under kth kind energy storage device access way, M is node
Number, number at the time of T indicates total, UijIndicate the voltage value at j-th of moment of i-th of node,Indicate i-th of node in time T
Average voltage
3) loss minimization requirement:
Wherein,Indicate the line loss summation in the system under kth kind energy storage device access way,It indicates i-th
Line loss of the node in t moment, Δ t expression time interval.
4) node voltage limitation requires:
UI, min≤Ui≤UI, mmx(i=1,2..., M)
Wherein, UI, minIndicate the lower voltage limit of i-th of node, UI, maxIndicate the upper voltage limit of i-th of node, M is node
Number；
According to the system load flow parameter of all sampling point moments obtained in step (7), substitutes into and obtain all evaluation methods
Parametric results, here obtain energy storage device access No. 3 nodes when evaluation parameter:
f1=667984 (kWh)；f2=3545.34；f3=67597.32208 (kWh)
Step (9) replaces energy storage device on-position, repeat step (1) to step (9) until it is all it is potential most preferably
The result of all evaluation parameters has all been as follows: in the case of location
Step (10), the various access way parameters of across comparison can pass through design weighting function quantitative manner or people
Optimal access result is selected for perceptual knowledge.Here the optimal addressing result of No. 1 node can be selected by artificially judgement.
Step (11) to step (17) are site selecting method.
Step (11) obtains processing variation data in distributed generation resource that is to be applied, the determining scale typical odd-numbered day.In order to
It can correctly reflect the fluctuation of distributed generation resource, the sampling interval cannot be excessive.5 minutes sampling intervals are used in this method.
Step (12) constructs the objective function and constraint item of composite energy storing device constant volume Optimized model according to actual needs
Part.Two objective functions are set herein:
1. cost minimization target
min Ctotal=CbatEbat+CucEuc
2. system power vacancy/surplus is minimum
Wherein, EbatAnd EucRespectively indicate the capacity of battery and super capacitor, CbatAnd CucIt respectively indicates battery and surpasses
The unit price of grade capacitor, CtotalIndicate totle drilling cost, PLack, iIndicate ith sample dot system power shortage, PWoste, iIt indicates i-th
Sampled point system power surplus, PtotalIndicate the total vacancy/surplus value of system power.The two, which respectively represents, requires energy storage device to hold
Measure it is low as far as possible with it is high as far as possible, conflict with each other.The constraint condition that this programme considers has:
1. capacity of energy storing device constrains
SOCBat, min≤SOCBat, t≤SOCBat, max
SOCUc, min≤SOCUc, t≤SOCUc, max
Wherein, SOCBat, tIndicate the state of charge of the battery at the end of t period, SOCUc, tExpression terminates in the t period
When super capacitor state of charge, SOCBat, minAnd SOCBat, maxRespectively indicate the minimum value and maximum of storage battery charge state
Value, SOCUc, minAnd SOCUc, maxRespectively indicate the minimum value and maximum value of super capacitor state-of-charge.
When energy-storage system is charged state, for battery,
Wherein, ωbatIndicate the automatic discharging loss late of battery；PBat, tIt indicates within the t period, the charge-discharge electric power of battery is
Electric discharge is indicated when positive value, and charging is indicated when negative value；Δ t indicates the sampling period；ηBat, cIndicate battery charge efficiency；EbatIt indicates
The capacity of battery, unit kwh.For super capacitor,Its
In, ωucIndicate the automatic discharging loss late of super capacitor；PUc, tIt indicates within the t period, the charge-discharge electric power of super capacitor,
Indicate electric discharge when for positive value, when negative value indicates charging；ηUc, cIndicate super capacitor charge efficiency；EucIndicate the appearance of super capacitor
Amount, unit kwh；
When energy-storage system is discharge condition, for batteryIts
In, ηBat, dIndicate battery discharging efficiency；For super capacitorWherein,
ηUc, dIndicate super capacitor discharging efficiency
2. energy storage device exports/absorb power constraint
1) there is no in the case where capacity of energy storing device limitation:
PBat, t, max≤PBat, max；PUc, t, max≤PUc, max
Wherein, PBat, t, maxIt indicates in the maximum allowable output of t moment battery/absorption power, PUc, t, maxIt is super in t moment
The maximum allowable output of capacitor/absorption power, PbatmaxIndicate the maximum output of battery/absorption power, PucmaxIndicate super capacitor
Maximum output/absorption power.
2) there is no in the case where capacity of energy storing device limitation:
When charging:
When electric discharge:
3. system operating power Constraints of Equilibrium
PPv, t+PLack, t=PBat, t+PUc, t+PLoad, t+PWaste, t
Wherein, PWaste, tIndicate electricity generation system surplus power, P within the t periodLack, tIndicate the system that generates electricity within the t period
System vacancy power, PBat, tIt indicates within the t period, the charge-discharge electric power of battery, PUc, tIndicate the super electricity within the t period
The charge-discharge electric power of appearance, PPv, tFor the photovoltaic generation power within the t period, PLoad, tFor the load power within the t period.
4. load short of electricity rate/energy spilling constraint
Wherein, LPSP indicates system short of electricity rate, and SPSP indicates energy spilling rate.
Distributed generation resource power output is subtracted payload and obtains composite energy storage power compensation ideal value P by step (13)hess=
Ppv-Pload.Its spectral characteristic is obtained by Fast Fourier Transform, and P is determined according to its spectral characteristichessNeed by from
The cutoff frequency for dissipating low-pass filter, frequency is as cutoff frequency f where taking first maximum peak of frequency responsesample。
Step (14), the cutoff frequency f obtained with step (13)sampleBased on, design Butterworth low-pass filtering
Device, parameters design are as follows:
Cut-off frequecy of passband Wp=fpass/(fs/2)；
Stopband cutoff frequency Ws=fstop/(fs/2)；
Decaying maximum value Rp=2 in passband；
Decaying minimum value Rs=40 in stopband；
Sample frequency fs=1/ Δ t (Hz)
Wherein, fpassIt is derived from first minimum of frequency response, is 0.0001, f in this examplestopIt is derived from formulaIt is taken as representative value for 0.00026, Rp and Rs in this example, Δ t is sampling time interval, in seconds,
It is 300 in this example.
Step (15), by PhessBy discrete low-pass filter, P is obtainedhessLow frequency component, be battery ideal compensation
Step (16) determines that the battery/super capacitor operating parameter used, the parameter considered here have: rated power
(being regarded as maximum output/absorption power)；Maximum/minimum state-of-charge；Unit price；Self discharge efficiency.This example is taken typically
Battery/super capacitor operating parameter, parameter are as follows:
The subproblem of only objective function 1 and only objective function 2 is separately optimized with particle swarm algorithm in step (17).
Wherein the objective function in each subproblem is as the adaptive response function in each subproblem.Each constraint condition implementation is as follows:
1. battery and super capacitor power, state-of-charge are corrected, amendment is according to the constraint condition to introduce in this method；
2. system power Constraints of Equilibrium balances power etc. by introducing system vacancy power/system surplus power and variable
Both formula is greater than and at most only has one greater than zero；
3. calculating system vacancy power/system surplus power under current capacities, load short of electricity rate/energy spilling is obtained about
Beam forces particle to return to feasible zone if calculated result exceeds feasible zone range by way of plus a penalty function.
Step (18) respectively substitutes into subproblem 1 and 2 optimum results of subproblem in objective function 2 and objective function 1, fortune
With fitness profit ranking method, the weighting coefficient of different target function is adjusted by quantitative method, multiple objective function is excellent
Change problem is integrated into single-goal function optimization problem:
Step (19) calculates the single-goal function optimization through integrating that step (5) obtain with particle swarm algorithm again and asks
Topic, obtains cost and system power vacancy/surplus of last capacity configuration result and the allocation plan, as a result are as follows:
fmin=379.5409
Ebat=399.73 (kWh)；Euc=3.70 (kWh)
Cost Ctotal=282619.1 yuan.
To sum up, the present invention is given detailed algorithm and is retouched based on processing of existing somewhere photovoltaic devices odd-numbered day data
State, finally obtain addressing optimal under this method, constant volume scheme, it was demonstrated that the program solve the problems, such as on addressing constant volume can
Row and validity.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, is familiar with
The those skilled in the art should be understood that the present invention includes but is not limited to content described in specific embodiment above.It is any
Modification without departing from function and structure principle of the invention is intended to be included in the range of claims.
Claims (6)
1. a kind of composite energy storing device addressing constant volume method towards source net lotus close friend interaction, characterized by comprising: addressing side
Distribution network system: being abstracted turn to tree-shaped catalogue model first by method, is then constructed according to branch impedance and model topology
Node admittance matrix, then balanced using the inflow and outflow of a certain node power as the foundation to establish an equation, and expand to all nodes,
Formation is essentially the nodal voltage equation group of Nonlinear System of Equations, and the non-linear side of any dimension is solved by least square method
Journey group obtains the node voltage vector of all nodes in model, and the calculating of trend is obtained by way of iteration step by step in model
The inflow and outflow power of each node and the line loss of each branch road are obtained, finally addressing purpose according to actual needs refers to
Mark, to evaluate the superiority and inferiority of energy storage device on-position, and with other on-position scheme across comparisons, obtain the storage under the model
It can the optimal addressing of device；
Constant volume method: optimizing constant volume model by building composite energy storage first, determines the objective function of optimization and the pact of model
Beam condition；Then pass through the capacity ratio of both PSO Algorithm battery/super capacitors.
2. a kind of composite energy storing device addressing constant volume method towards source net lotus close friend interaction according to claim 1,
It is characterized in that site selecting method includes the following steps:
Practical distribution network is abstracted as tree-shaped nodal analysis method by step (1), is obtained the branch impedance of all branches and is located at each
The payload of a node, and unified dimension obtain processing in distributed generation resource that is to be applied, the determining scale typical odd-numbered day and become
Change data, it is assumed here that abstract result is the electricity distribution network model of a n node；
Step (2) constructs the node admittance matrix of n*n dimension by the obtained model parameter of step (1) and its topological structure
Yij, expression and calculating for nodal voltage equation；
Step (3) determines energy storage device on-position and distributed generation resource power output size that this is calculated；
Step (4), building n-1 tie up nodal voltage equation group, are flowed into according to each node and flow out power-balance come the side of building
Journey group, since without the concern for balance nodes, so equation only has n-1, for the convenience of operation later, equation group is used
The representation of rectangular co-ordinate:
Step (5) solves the Nonlinear System of Equations using least square method, obtains the node voltage vector of each node；
Step (6), calculates network trend, and used Load flow calculation is from the final stage anti-mode pushed away step by step, a certain single recursion
Mode byIt realizes, from the end up line of all branches of recursion step by step
DamageAnd the apparent energy S of outflow node j, until calculating energy storage device by the equilbristat of node power at branch beginning
Absorption/delivered power the power inscribed for the moment, thus obtains data required for the evaluation method of each energy storage device on-position；
Step (7), replacement repeat step (3) to step (6) until being distributed to next distributed generation resource power output sampled point
Steady-state load flow parameter has all obtained under formula power supply power output sampled point；
Step (8) designs and calculates access scheme Quantitative evaluation standard, using four kinds of evaluation parameters: capacity of energy storing device requirement,
The requirement of voltage fluctuation minimum, loss minimization requirement, node voltage limitation requires, according to all sampled points obtained in step (7)
The system load flow parameter at moment substitutes into the parametric results (f for obtaining all evaluation methods1, f2, f3, f4)；
Step (9) replaces energy storage device on-position, repeats step (1) to step (9) until all potential optimal addressing feelings
The result of all evaluation parameters has all obtained (f under condition1 1, f2 1, f3 1, f4 1......f1 n, f2 n, f3 n, f4 n)；
Step (10), the various access way parameters of across comparison, selects optimal access result.
3. a kind of composite energy storing device addressing constant volume method towards source net lotus close friend interaction according to claim 2,
It is characterized in that: according to the requirement of Load flow calculation, it is specified that the access node of the power output device in generating set, power distribution network is PV section
Point, it is characterized in that the active power input determined and determining node voltage virtual value；Provide that general load point is PQ node,
Feature is determining active power and reactive power input；Energy storage device since its effect is regarded as balance nodes here,
Feature is the uncertain active node voltage vector with reactive power input/output and determination, is used as entire power distribution network section
The reference of point voltage is, it is specified that for a certain node, and power inflow is positive, and outflow is negative.
4. a kind of composite energy storing device addressing constant volume method towards source net lotus close friend interaction according to claim 2,
Be characterized in that: step (10) selects optimal access result by design weighting function quantitative manner or artificial perceptual knowledge.
5. a kind of composite energy storing device addressing constant volume method towards source net lotus close friend interaction according to claim 1,
It is characterized in that constant volume method includes the following steps:
Step (11) obtains processing variation data in distributed generation resource that is to be applied, the determining scale typical odd-numbered day；
Step (12) constructs the objective function and constraint condition of composite energy storing device constant volume Optimized model according to actual needs,
Two objective functions of middle setting: 1. cost minimization targets and 2. system powers vacancy/surplus are minimum, the constraint condition of consideration
Have: capacity of energy storing device constraint, energy storage device export/absorb power constraint, system operating power Constraints of Equilibrium, load short of electricity
Rate/energy spilling constraint；
Distributed generation resource power output is subtracted payload and obtains composite energy storage power compensation ideal value P by step (13)hess=Ppv-
Pload, its spectral characteristic is obtained by Fast Fourier Transform, and P is determined according to its spectral characteristichessNeed by it is discrete low
The cutoff frequency of bandpass filter；
Step (14) designs Butterworth low-pass filter, Ge Gecan based on the cutoff frequency that step (13) obtains
Number design is as follows: cut-off frequecy of passband Wp；Stopband cutoff frequency Ws；Decaying maximum value Rp in passband；Decaying in stopband is most
Small value Rs；Sample frequency fs；
Step (15), by PhessBy discrete low-pass filter, P is obtainedhessLow frequency component, be battery ideal compensation
Step (16) determines the battery/super capacitor operating parameter used, and the parameter considered here has: rated power, most
Greatly/minimum state-of-charge, unit price, self discharge efficiency；
The subproblem of only objective function 1 and only objective function 2 is separately optimized with particle swarm algorithm in step (17), wherein
Objective function in each subproblem is as the adaptive response function in each subproblem；
Step (18) respectively substitutes into subproblem 1 and 2 optimum results of subproblem in objective function 2 and objective function 1, with suitable
Response profit ranking method is adjusted the weighting coefficient of different target function by quantitative method, multi objective function optimization is asked
Topic is integrated into single-goal function optimization problem
Step (19) calculates the single-goal function optimization problem through integrating that step (15) obtain with particle swarm algorithm again,
Obtain cost and system power vacancy/surplus of last capacity configuration result and the allocation plan.
6. a kind of composite energy storing device addressing constant volume method towards source net lotus close friend interaction according to claim 5,
Be characterized in that: each constraint condition implementation of step (17) is as follows: battery and super capacitor power, state-of-charge are corrected, and are repaired
The positive constraint condition according to introduce；System power Constraints of Equilibrium passes through introducing system vacancy power/system surplus power and variable
Balancing power equation, being both greater than and at most only having one greater than zero；Calculate system vacancy power/system under current capacities
Surplus power obtains load short of electricity rate/energy spilling constraint, if calculated result exceeds feasible zone range, by adding one
The mode of a penalty function forces particle to return to feasible zone.
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