CN109494746A - Based on the isolated island alternating current-direct current mixed connection micro-capacitance sensor tidal current computing method for improving adaptive sagging control - Google Patents
Based on the isolated island alternating current-direct current mixed connection micro-capacitance sensor tidal current computing method for improving adaptive sagging control 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
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/381—Dispersed generators
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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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Abstract
The invention discloses based on the isolated island alternating current-direct current mixed connection micro-capacitance sensor tidal current computing method for improving adaptive sagging control, key step are as follows: 1) establish alternating current-direct current mixed connection micro-capacitance sensor Controlling model.2) isolated island alternating current-direct current mixed connection micro-capacitance sensor tide model is established.3) the LMTR derivation algorithm based on trusted zones is established.4) isolated island micro-capacitance sensor alternating current-direct current combined hybrid system Load flow calculation is carried out with alternative iteration method, convergence criterion isIf convergence, is transferred to step 5.Continue iteration if not restraining, until convergence.5) calculation of tidal current is exported, and it is active to change load, using improved adaptive sagging control strategy, updates sagging control coefrficient, re-start Load flow calculation.The present invention can maintain the stabilization of frequency and voltage, when emergent power disturbs in system, also guarantee simultaneously all distributed generation resources according to power supply capacity than contributing, single power supply power output is crossed the border situation when being not in overload, is conducive to maintenance system safety and stability and is reliably efficiently run.
Description
Technical field
The present invention relates to new-energy grid-connected fields, specifically based on the isolated island alternating current-direct current mixed connection for improving adaptive sagging control
Micro-capacitance sensor tidal current computing method.
Background technique
Under the overall background of current energy shortage and environmental degradation, micro-capacitance sensor increasingly obtain the approval of domestic and foreign scholars with
Development.Micro-capacitance sensor is that one kind is collected by distributed generation resource, energy storage device, energy conversion device, load, monitoring and protection system etc.
Made of small-sized electric system, can be realized self-contr ol, protection and the autonomous system of management.Micro-capacitance sensor not only can solve greatly
The flexible access and efficient operation of scale distribution formula power supply, the customer power supply into remote districts, island and desert, and also it is also
The following intelligent distribution network realizes the important channel of self-healing, user side interaction and demand response.
Power supply and load do not need to transmit at a distance, transmission line of electricity impedance operator is matched with tradition at a distance of relatively closely in micro-capacitance sensor
Power grid is similar, at the same the access of distributed generation resource, the diversity of distributed generation resource control mode, micro-grid operation mode it is flexible
Diversity, so that the trend distribution of micro-capacitance sensor is different from traditional power distribution network with diversity with calculating.In addition, among micro-capacitance sensor
The random fault and system loading of the randomness of formula of having a rest distributed generation resource power output, route and distributed generation resource fluctuate not true
Qualitative factor, it will the power quality of system is caused to seriously affect, and is also unfavorable for system safety and stability reliability service.
Load flow calculation is the most basic calculating of one of Power System Analysis, is power system mesomeric state operating analysis and control
The basis of system.Micro-capacitance sensor conventional Load Flow calculate be micro-capacitance sensor technical research a key areas, be micro-capacitance sensor safety analysis,
Electromechanical transient stability analysis, electromagnetic transient analysis basis, electromagnetic transient analysis needs first with electromechanical transient stability analysis
Original state is given, and the given of original state just needs to carry out conventional Load Flow calculating；It is also micro-capacitance sensor isolated island fortune simultaneously
The important evidence of row reliability.Therefore, the model and algorithm of micro-capacitance sensor conventional Load Flow are studied, it is quick, accurate, practical to obtain
Certainty power flow solutions are the bases of micro-capacitance sensor steady-state analysis, there is important research significance and application value.
In isolated island alternating current-direct current mixed connection micro-grid system, each distributed generation resource generallys use the sagging control of equity, system
Inside there are multiple balance nodes, by multiple balance nodes shared imbalance powers, and in micro-grid system route resistance
Reactance cannot be far smaller than, these factors all may cause the unusual of Jacobian matrix.It needs using advanced optimization algorithm solution
Certainly this problem, in isolated island micro-grid system, after being detached from exchange major network support, frequency easily offrating is disturbed when system
When dynamic, need to maintain the stabilization of frequency and voltage using more advanced control mode.While in order to make calculation of tidal current more
Accurately, the frequency/voltage characteristic for needing meter and load, alternating current-direct current combined hybrid system is solved using alternative iteration method.In addition, all
It is not communicated between distributed generation resource, in order to make all distributed generation resources, than contributing, guarantee identical power according to power supply capacity
Nargin, single power supply power output is crossed the border situation when overload will not occur, and needs to propose effective sagging coefficient selection method.
Summary of the invention
Present invention aim to address problems of the prior art.
To realize the present invention purpose and the technical solution adopted is that such, based on the isolated island for improving adaptive sagging control
Alternating current-direct current mixed connection micro-capacitance sensor tidal current computing method, mainly comprises the steps that
1) alternating current-direct current mixed connection micro-capacitance sensor is built.
2) alternating current-direct current mixed connection micro-capacitance sensor Controlling model is established, mainly includes the sagging Controlling model of exchange distributed generation resource, straight
The sagging Controlling model of flow point cloth power supply, load model and the improvement for connecting current transformer Controlling model, meter and frequency/voltage characteristic
Adaptive sagging Controlling model.
It is as follows to exchange the sagging Controlling model of distributed generation resource:
In formula, ωi、Uaci、PGiAnd QGiThe respectively i-th exchange actual frequency of distributed generation resource, set end voltage amplitude,
Active power of output and output reactive power.ω0And Uac0Respectively idling frequency and unloaded set end voltage amplitude.KPiAnd KQiPoint
It Wei not active sagging coefficient and idle sagging coefficient.
Active sagging COEFFICIENT KPiMeet formula 2, it may be assumed that
KP1PN1=KP2PN2=KP3PN3==KPnPNn=ωmax-ωmin。 (2)
In formula, n is exchange distributed generation resource sum.PNiThe active power of distribution power is exchanged for i-th.
Idle sagging COEFFICIENT KQiMeet formula 3, it may be assumed that
KQ1QN1=KQ2QN2=KQ3QN3==KQnQNn=Uac.imax-Uac.imin。 (3)
In formula, QNiThe reactive power of distribution power is exchanged for i-th.Uac.imaxThe maximum of distribution power is exchanged for i-th
Voltage.Uac.iminThe minimum voltage of distribution power is exchanged for i-th.
The sagging Controlling model of direct current distributed generation resource is as follows:
Udi=Ud0-KdciPGdci。 (4)
In formula, Udi、Ud0And PGdciRespectively actual DC voltage magnitude, unloaded DC voltage amplitude and output wattful power
Rate.KdciFor the sagging coefficient of direct current distributed generation resource.
The sagging COEFFICIENT K of direct current distributed generation resourcedciMeet formula 5, it may be assumed that
Kdc1PdN1=Kdc2PdN2==KdcnPdNn=Udc.max-Udc.min。 (5)
In formula, PdNnFor direct current distributed generation resource active power of output.Udc.maxFor direct current distributed generation resource maximum voltage.
Udc.minFor direct current distributed generation resource minimum voltage.
It is as follows to connect current transformer Controlling model:
Utilize the frequencies omega and DC voltage U of 6 pairs of connection current transformers of formulaILCdcIt is normalized, makes to connect unsteady flow
The frequencies omega of devicepuWith DC voltage UILC.puIn identical unit range.
In formula, ωmaxAnd ωminThe respectively maximum frequency and minimum frequency of intercommunion subsystem permission.UILCdc,maxWith
UILCdc,minThe respectively maximum voltage and minimum voltage of direct current subsystem permission.UILCdcFor direct current subsystem voltage.
After normalized, ωpu=[- 1,1], and UILC.pu=[- 1,1].
The power control equations for connecting current transformer are as follows:
In formula, UILCac0And UILCacRespectively unloaded alternating voltage amplitude and practical alternating voltage amplitude.KPILCAnd KQILCPoint
The active and idle control coefrficient of current transformer Wei not connected.PILCdcTo connect current transformer direct current subsystem active power.QILCacFor
Connect current transformer intercommunion subsystem reactive power.PILCacTo connect current transformer intercommunion subsystem active power.
Meter and the load model of frequency/voltage characteristic are as follows:
In formula, when the frequency and voltage of system are respectively fL0iAnd UL0iWhen, PL0iAnd QL0iRespectively corresponding reality is active
Power and reactive power.When frequency and voltage are respectively equal to f and UiWhen, PLiAnd QLiThe respectively corresponding practical active power of load
And reactive power.KPfiAnd KQfiThe respectively static frequency characteristic coefficient of load.KPViAnd KQViRespectively load active power refers to
Several and reactive power index.
The key step for establishing improved adaptive sagging Controlling model is as follows:
I initial sagging coefficient) is obtained according to formula 2 and formula 3, and calculates initial trend.
II) improved adaptive sagging Controlling model is respectively as shown in formula 9 and formula 10:
In formula, ωNAnd UacNRespectively exchange the rated frequency and voltage rating of distributed generation resource.WithRespectively
The practical active power output and idle power output at distributed generation resource t-1 moment before changing load.U'aciIt is exchanged for improved i-th
The set end voltage amplitude of distributed generation resource.ω'iThe actual frequency of distributed generation resource is exchanged for improved i-th.
The reality at distributed generation resource t-1 moment before changing load is activeMeet following formula:
In formula, PminFor the active power output minimum value at distributed generation resource t-1 moment before changing load.PmaxFor distributed electrical
The active power output maximum value at source t-1 moment before changing load.
In formula, QminFor the idle power output minimum value at distributed generation resource t-1 moment before changing load.QmaxFor distributed electrical
The idle power output maximum value at source t-1 moment before changing load.
3) isolated island alternating current-direct current mixed connection micro-capacitance sensor tide model is established.
The key step for establishing isolated island alternating current-direct current mixed connection micro-capacitance sensor tide model is as follows:
3.1) isolated island alternating current-direct current mixed connection micro-capacitance sensor is built.Wherein, exchange node division be 4 classes: PQ node, PV node, under
Hang down node and ILC-AC node.DC node is divided into 3 classes: permanent P node, sagging node and ILC-DC node.
3.2) tide model of intercommunion subsystem is established.
The power balance equation of any i-th of node is as follows in intercommunion subsystem:
In formula, xacFor the state variable of intercommunion subsystem.PGiAnd QGiThe active power output of respectively i-th node generator
With idle power output.PLiAnd QLiThe active power and reactive power of respectively i-th node load.PILCaciAnd QILCaciRespectively
The injection for connecting inverter ILC is active and idle.SPQ、SPV、SDr-ac、SILC-acRespectively PQ node, PV node, sagging node,
The set of ILC-AC node.PiAnd QiRespectively node injection active power and reactive power.
Node injects active-power PiReactive power Q is injected with nodeiIt is as follows respectively:
In formula, N is node total number.UiFor i-th of node voltage.UjFor j-th of node voltage.δijFor voltage UiAnd voltage
UjPhase angle difference.GijFor the conductance between node i and node j.BijFor the susceptance between node i and node j.
FPmis.ac.i(xac) and FQmis.ac.i(xac) it is respectively the active and idle imbalance power of i-th of node.Four kinds of sections
The state variable x of vertex typeac=[xPQi,xPVi,xDr-aci,xILC-aci]TIt is as follows respectively:
δiFor the voltage phase angle of i-th of node.
3.3) tide model of direct current subsystem is established
The power balance equation of any i-th ' a node is as follows in direct current subsystem:
Fdci'(xdc)=PGdci'-PLdci'-Pdci'-PILCdc=0. (16)
In formula, xdcFor direct current subsystem state variable.PGdci'、PLdci'And PILCdcRespectively direct current distributed generation resource is active
Power output, load active power and connection current transformer inject active power.PdciFor direct current subsystem node injecting power.
Direct current subsystem node injecting power Pdci'It is as follows:
In formula, N' is direct current subsystem node number.Udcj'For the voltage of direct current subsystem jth ' a node.Udci'It is straight
Flow the voltage of a node of subsystem i-th '.Yi'j'For the admittance between a node of direct current subsystem i-th ' and jth ' a node.
The state variable x of direct current subsystemdc=[xP-dci',xDr-dci',xILC-dci']TSpecifically it is expressed as follows:
In formula, SP-dcFor direct current subsystem HengPJie Dianji.SDr-dcFor the sagging node collection of direct current subsystem.SILC-dcFor direct current
Subsystem ILC-DC node collection.
4) the LMTR derivation algorithm based on trusted zones is established.
5) trend is carried out to isolated island alternating current-direct current mixed connection micro-capacitance sensor tide model with alternative iteration method and LMTR derivation algorithm
It calculates, convergence criterion is cost function ψ (xk) vector differentiation resultε1For trend
The convergence precision of calculating.If convergence, is transferred to step 6.Continue iteration if not restraining, until convergence.
The key step for establishing the LMTR derivation algorithm based on trusted zones is as follows:
5.1) Jacobian matrix J is eliminated using the trust region method based on one stepkSingularity, it may be assumed that
In formula, Fk=F (xk)。Jk=J (xk)。dLMKFor current point of operation xkIteration direction.xk+1For next iteration point
Value.I is unit vector.FkIndicate active and idle uneven equation, F when convergencekTend to 0.
According to formula 19, work as μkWhen tending to 0, dLMKTend to Gauss-Newton step, works as μkWhen tending to be infinite, dLMKTend to most
Speed decline step.
5.2) according to the LMTR method based on Load flow calculation to current point of operation xkIteration direction dLMKIt is updated, it may be assumed that
In formula, θ is constant, and 0≤θ≤1.Parameter betakIt is updated using trust region method.
5.3) cost function ψ (x is definedk)=0.5 | | F (xk)||2, then practical slippage and estimation slippage ratio rk
Are as follows:
Then after k iteration, operating point xk+1It is as follows:
In formula, η1For iteration success discriminant coefficient, η1> 0.Wherein, xk+1=xk+dLMkIndicate iteration success, xk+1=xkTable
Show that iteration fails.rkFor operating point xkIteration discriminant parameter.
Parameter betakIt updates as follows:
In formula, η2For iteration success discriminant coefficient, 0 < η1< η2< 1.γ1And γ2For βkCorrection factor, γ1> 1 and 0
< γ2< 1.βminFor βkMinimum value.If rk> η2, then it represents that iteration is very successful, at this time βk+1=max (γ2βk,βmin).If η1
< γk< η2, then it represents that iteration is successful, at this time βk+1=βk.If γk< η1, then it represents that iteration fails, at this time βk+1=γ1。γk
For βkIteration discriminant parameter.
6) calculation of tidal current is exported, and it is active to change load, using improved adaptive sagging control strategy, under update
Hang down control coefrficient, re-starts Load flow calculation, until the power output of distributed generation resource is out-of-limit.
The solution have the advantages that unquestionable.The basic idea of the invention is that: pass through adaptively changing distribution
The sagging control coefrficient of power supply realizes the stabilization of isolated island alternating current-direct current mixed connection micro-capacitance sensor frequency and voltage, while use is finer
Load model and advanced derivation algorithm obtain more accurate and quick power flow solutions.The present invention solves isolated island and hands over directly
Jacobian matrix is likely to occur stabilization that is unusual, and can maintaining frequency and voltage in stream mixed connection micro-capacitance sensor, occurs when in system
When power disturbance, while also guaranteeing that all distributed generation resources are contributed according to power supply capacity ratio, it is individually electric when being not in overload
Source power output is crossed the border situation, is conducive to maintenance system safety and stability and is reliably efficiently run.
Detailed description of the invention
Fig. 1 is based on the isolated island alternating current-direct current mixed connection micro-capacitance sensor Load flow calculation flow chart for improving adaptive sagging control；
Fig. 2 is mixed for the isolated island alternating current-direct current formed after IEEE-33 Node power distribution system and the modification of Benchmark low pressure micro-capacitance sensor
Join micro-grid system meshed network；
Fig. 3 is DC bus-bar voltage distribution map；
System frequency curve graph when Fig. 4 is load variations；
The power output schematic diagram of Fig. 5 all exchange DG when being load variations；
No. 11 busbar voltage distribution maps of direct current when Fig. 6 is load variations.
Specific embodiment
Below with reference to embodiment, the invention will be further described, but should not be construed the above-mentioned subject area of the present invention only
It is limited to following embodiments.Without departing from the idea case in the present invention described above, according to ordinary skill knowledge and used
With means, various replacements and change are made, should all include within the scope of the present invention.
Embodiment 1:
As shown in Figure 1 to Figure 2, based on the isolated island alternating current-direct current mixed connection micro-capacitance sensor Load flow calculation side for improving adaptive sagging control
Method mainly comprises the steps that
1) alternating current-direct current mixed connection micro-capacitance sensor is built.Slightly to IEEE-33 Node power distribution system and Benchmark low pressure micro-capacitance sensor
Modification, becomes an isolated island alternating current-direct current mixed connection micro-grid system, the system is as shown in Figure 1.
2) alternating current-direct current mixed connection micro-capacitance sensor Controlling model is established, mainly includes the sagging Controlling model of exchange distributed generation resource, straight
The sagging Controlling model of flow point cloth power supply, load model and the improvement for connecting current transformer Controlling model, meter and frequency/voltage characteristic
Adaptive sagging Controlling model.
When exchanging subnet using reciprocity control strategy, it is special that exchange distributed generation resource generallys use the sagging control of P-f/Q-U
Property, it is as follows to exchange the sagging Controlling model of distributed generation resource:
In formula, ωi、Uaci、PGiAnd QGiThe respectively i-th exchange actual frequency of distributed generation resource, set end voltage amplitude,
Active power of output and output reactive power.ω0And Uac0Respectively idling frequency and unloaded set end voltage amplitude.KPiAnd KQiPoint
It Wei not active sagging coefficient and idle sagging coefficient.
Active sagging COEFFICIENT KPiMeet formula 2, it may be assumed that
KP1PN1=KP2PN2=KP3PN3==KPiPNi==KPnPNn=ωmax-ωmin。 (2)
In formula, n is exchange distributed generation resource sum.PNiThe active power of distribution power is exchanged for i-th.
Idle sagging COEFFICIENT KQiMeet formula 3, i.e.,
KQ1QN1=KQ2QN2=KQ3QN3==KQiQNi==KQnQNn=Uac.imax-Uac.imin (3)
In formula, QNiThe reactive power of distribution power is exchanged for i-th.Uac.imaxThe maximum of distribution power is exchanged for i-th
Voltage.Uac.iminThe minimum voltage of distribution power is exchanged for i-th.
The power output situation of analysis exchange distributed generation resource, brings (2) formula into (1) formula by taking two power supplys in AC network as an example
It can obtain:
Because two power supplys are connected to the same AC network, possess identical frequencies omega1=ω2=ω, convolution (4),
(5) formula (6) can be obtained:
From formula (6) it can be seen that all distributed generation resources are contributed according to power supply capacity ratio, it is ensured that all distributed generation resources tools
There is identical power margin, single power supply will not occur because of overload and cross the border.
The sagging Controlling model of direct current distributed generation resource is as follows:
Udi=Ud0-KdciPGdci。 (7)
In formula, Udi、Ud0And PGdciRespectively actual DC voltage magnitude, unloaded DC voltage amplitude and output wattful power
Rate.KdciFor the sagging coefficient of direct current distributed generation resource.
The sagging COEFFICIENT K of direct current distributed generation resourcedciMeet formula 8, it may be assumed that
Kdc1PdN1=Kdc2PdN2==KdcnPdNn=Udc.max-Udc.min。 (8)
In formula, PdNnFor DC power supply active power of output.Udc.maxFor direct current distributed generation resource maximum voltage.Udc.minFor
Direct current distributed generation resource minimum voltage.
It is as follows to connect current transformer (ILC) Controlling model:
Alternating current and direct current active power droop characteristic is different, and characteristic ordinate respectively represents frequency and direct current
Pressure, unit are inconsistent.Therefore, it is necessary to frequencies omega and DC voltage UILCdcThe normalized of carry out formula (9).Make to connect unsteady flow
The frequencies omega of devicepuWith DC voltage UILC.puIn identical unit range.
In formula, ωmaxAnd ωminThe respectively maximum frequency and minimum frequency of intercommunion subsystem permission.UILCdc,maxWith
UILCdc,minThe respectively maximum voltage and minimum voltage of direct current subsystem permission.UILCdcFor direct current subsystem voltage.
After normalized, ωpu=[- 1,1], and UILC.pu=[- 1,1].
The power control equations for connecting current transformer are as follows:
In formula, UILCac0And UILCacRespectively unloaded alternating voltage amplitude and practical alternating voltage amplitude.KPILCAnd KQILCPoint
The active and idle control coefrficient of current transformer Wei not connected.PILCdcTo connect current transformer direct current subsystem active power.QILCacFor
Connect current transformer intercommunion subsystem reactive power.PILCacTo connect current transformer intercommunion subsystem active power.
In isolated island alternating current-direct current micro-capacitance sensor, frequency is not always equivalent to rated frequency.Therefore, it needs to consider in trend modeling
The frequency/voltage characteristic of load.Accurate load model can be expressed as follows:
In formula, when the frequency and voltage of system are respectively fL0iAnd UL0iWhen, PL0iAnd QL0iRespectively corresponding reality is active
Power and reactive power.When frequency and voltage are respectively equal to f and UiWhen, PLiAnd QLiThe respectively corresponding practical active power of load
And reactive power.KPfiAnd KQfiThe respectively static frequency characteristic coefficient of load.KPViAnd KQViRespectively load active power refers to
Several and reactive power index.
1. Static Load parameter selection rule table of table
The key step for establishing improved adaptive sagging Controlling model is as follows:
I initial sagging coefficient) is obtained according to formula 2 and formula 3, and calculates initial trend.
II) improved adaptive sagging Controlling model is respectively as shown in formula 12 and formula 13:
In formula, ωNAnd UacNRespectively exchange the rated frequency and voltage rating of distributed generation resource.WithRespectively
The practical active power output and idle power output at distributed generation resource t-1 moment before changing load.U'aciIt is exchanged for improved i-th
The set end voltage amplitude of distributed generation resource.ω'iThe actual frequency of distributed generation resource is exchanged for improved i-th.
The reality at distributed generation resource t-1 moment before changing load is activeMeet following formula:
In formula, PminFor the active power output minimum value at distributed generation resource t-1 moment before changing load.PmaxFor distributed electrical
The active power output maximum value at source t-1 moment before changing load.
In formula, QminFor the idle power output minimum value at distributed generation resource t-1 moment before changing load.QmaxFor distributed electrical
The idle power output maximum value at source t-1 moment before changing load.
3) isolated island alternating current-direct current mixed connection micro-capacitance sensor tide model is established.
The key step for establishing isolated island alternating current-direct current mixed connection micro-capacitance sensor tide model is as follows:
3.1) isolated island alternating current-direct current mixed connection micro-capacitance sensor is built.Wherein, exchange node division be 4 classes: PQ node, PV node, under
Hang down node and ILC-AC node.DC node is divided into 3 classes: permanent P node, sagging node and ILC-DC node.PV node is
Know active-power P, voltage magnitude V, usually generator node；PQ node is known active-power P, reactive power Q, usually
Load bus.
3.2) tide model of intercommunion subsystem is established.
The power balance equation of any i-th of node is as follows in intercommunion subsystem:
In formula, xacFor the state variable of intercommunion subsystem.PGiAnd QGiThe active power output of respectively i-th node generator
With idle power output.PLiAnd QLiThe active power and reactive power of respectively i-th node load.PILCaciAnd QILCaciRespectively
The injection for connecting inverter ILC is active and idle.SPQ、SPV、SDr-ac、SILC-acRespectively PQ node, PV node, sagging node,
The set of ILC-AC node.PiAnd QiRespectively node injection active power and reactive power.
Node injects active-power PiReactive power Q is injected with nodeiIt is as follows respectively:
In formula, N is node total number；UiFor i-th of node voltage；UjFor j-th of node voltage；δijFor voltage UiAnd voltage
UjPhase angle difference；GijFor the conductance between node i and node j；BijFor the susceptance between node i and node j；
FPmis.ac.i(xac) and FQmis.ac.i(xac) it is respectively the active and idle imbalance power of i-th of node.Four kinds of sections
The state variable x of vertex typeac=[xPQi,xPVi,xDr-aci,xILC-aci]TIt is as follows respectively:
δiFor the voltage phase angle of i-th of node.
Wherein, xPQiIt indicates when node i is PQ node, corresponding state variable.xPViIndicate that when node i be PV node
When, corresponding state variable.xDr-aciIt indicates when node i is sagging node, corresponding state variable.xILC-aciIt indicates when section
When point i is ILC-AC node, corresponding state variable.
3.3) tide model of direct current subsystem is established
The power balance equation of any i-th ' a node is as follows in direct current subsystem:
Fdci'(xdc)=PGdci'-PLdci'-Pdci'-PILCdc=0. (19)
In formula, xdcFor direct current subsystem state variable.PGdci'、PLdci'And PILCdcRespectively direct current distributed generation resource is active
Power output, load active power and connection current transformer inject active power.PdciFor direct current subsystem node injecting power.
Direct current subsystem node injecting power Pdci'It is as follows:
The state variable x of direct current subsystemdc=[xP-dci',xDr-dci',xILC-dci']TSpecifically it is expressed as follows:
In formula, SP-dcFor direct current subsystem HengPJie Dianji.SDr-dcFor the sagging node collection of direct current subsystem.SILC-dcFor direct current
Subsystem ILC-DC node collection.
xP-dci'Indicate when node i ' for perseverance P node when, corresponding state variable.xDr-dci'Indicate when node i ' to be sagging
When node, corresponding state variable.xILC-dci'Indicate when node i ' for ILC-DC node when, corresponding state variable.
4) the Levenberg Marquardt method combined with trust based on trusted zones is established
Region technique derivation algorithm namely LMTR derivation algorithm.Under the sagging control strategy of equity, isolated island alternating current-direct current mixed connection
Balance nodes are not present in micro-grid system.In addition, line resistance cannot be far smaller than reactance in micro-capacitance sensor.These features all will
It is unusual to may cause Jacobian matrix.Therefore, the trust region method based on one step is made to solve this problem.
5) trend is carried out to isolated island alternating current-direct current mixed connection micro-capacitance sensor tide model with alternative iteration method and LMTR derivation algorithm
It calculates, convergence criterion is cost function ψ (xk) vector differentiation resultThe present embodiment
InFor cost function ψ (xk) gradient.ε1For the convergence precision of Load flow calculation.If convergence, is transferred to step 6.If no
Convergence then continues iteration, until convergence.
The key step for establishing the LMTR derivation algorithm based on trusted zones is as follows:
5.1) Jacobian matrix J is eliminated using the trust region method based on one stepkSingularity, it may be assumed that
In formula, Fk=F (xk)。Jk=J (xk)。dLMKFor current point of operation xkIteration direction.xk+1For next iteration point
Value.I is unit vector.
According to formula 19, work as μkWhen tending to 0, dLMKTend to Gauss-Newton (Gauss-Newton) step, works as μkTend to be infinite
When, dLMKTend to steepest decline step.
5.2) according to the LMTR method based on Load flow calculation to current point of operation xkIteration direction dLMKIt is updated, it may be assumed that
In formula, θ is constant, and 0≤θ≤1.Parameter betakIt is updated using trust region method.FkIndicate active and idle injustice
Weigh equation, F when convergencekTend to 0.
5.3) cost function ψ (x is definedk)=0.5 | | F (xk)||2, then practical slippage and estimation slippage ratio rk
Are as follows:
Then after k iteration, operating point xk+1It is as follows:
In formula, η1For iteration success discriminant coefficient, η1> 0.Wherein, xk+1=xk+dLMkIndicate iteration success, xk+1=xkTable
Show that iteration fails.rkFor operating point xkIteration discriminant parameter.
Parameter betakIt updates as follows:
In formula, η2For iteration success discriminant coefficient, 0 < η1< η2< 1.γ1And γ2For βkCorrection factor, γ1> 1 and 0
< γ2< 1.βminFor βkMinimum value.If rk> η2, then it represents that iteration is very successful, at this time βk+1=max (γ2βk,βmin).If η1
< γk< η2, then it represents that iteration is successful, at this time βk+1=βk.If γk< η1, then it represents that iteration fails, at this time βk+1=γ1。γk
For βkIteration discriminant parameter.
6) after solving direct current subsystem trend using LMTR algorithm, judgementIt is whether true, if so,
Then obtain the power flow solutions x of direct current subsystemdckAnd PILCdc, subscript dc expression direct current subsystem.And by PILCdc=PILCacIt brings into
The power flow equation of intercommunion subsystem solves intercommunion subsystem trend using LMTR algorithm.If not, then renewal frequency ω, and
Re-start Load flow calculation.
After solving intercommunion subsystem trend, judgementIt is whether true, if so, then obtain direct current subsystem
The power flow solutions of system, subscript ac indicates direct current subsystem, and is transferred to step 7.If not, then renewal frequency ω, and again into
Row Load flow calculation.
7) information such as output system frequency, alternating current-direct current busbar voltage, branch power, current transformer exchange power, and change negative
Lotus is active, using improved adaptive sagging control strategy, updates sagging control coefrficient, re-starts Load flow calculation, until institute
There is load parameter to carry out Load flow calculation.
The present invention realizes the micro- electricity of isolated island alternating current-direct current mixed connection by the sagging control coefrficient of adaptively changing distributed generation resource
The stabilization of net frequency and voltage, at the same obtained using finer load model and advanced derivation algorithm it is more accurate and
Quick power flow solutions.Fig. 6 is that the alternating of the isolated island alternating current-direct current mixed connection micro-capacitance sensor Load flow calculation based on adaptive sagging control changes
The process in generation.
Embodiment 2:
A kind of reality of the verifying based on the isolated island alternating current-direct current mixed connection micro-capacitance sensor tidal current computing method for improving adaptive sagging control
It tests, mainly comprises the steps that
1) experiment parameter of isolated island alternating current-direct current mixed connection micro-capacitance sensor is set, it may be assumed that η1=0.25, η2=0.75, γ1=4, γ2=
0.25, θ=0.5, β0=0.005, βmin=10-8.All sagging control DG devices contain reactive-load compensation equipment, floating voltage width
Value is 1.06pu, the floating voltage frequency of the sagging control DG device of exchange P-f/Q-U is 1.004pu.Sagging DG device parameter master
It is as shown in table 2.
Intercommunion subsystem parameter setting: system reference power is 1MVA, reference frequency 50Hz, and steady frequency range is
[0.996,1.004] pu, the voltage phase angle of node 39 are fixed phase angle.Direct current subsystem reference power is 100kVA.ILC
Device parameter setting: UILCdc.max、UILCdc.minRespectively 1.06pu and 0.94pu, ωmax、ωminRespectively 1.004pu and
0.996pu, KPILC=8, KQILC=5.E is setM=0.05pu, the frequency of intercommunion subsystem, unknown exchange node voltage amplitude and
The initial value at phase angle is taken as 1pu, 1pu, 0rad respectively, and the initial value of direct current subsystem unknown node voltage is taken as 1pu.
The sagging DG device parameter of table 2
2) isolated island alternating current-direct current mixed connection micro-capacitance sensor ground state trend is calculated, the results are shown in Table 3 and table 4.
3 isolated island alternating current-direct current mixed connection micro-capacitance sensor calculation of tidal current of table
| Node number | Ui/pu | δi/(°) | Node number | Ui/pu | δi/(°) |
| 1 | 0.9846 | 0.0700 | 21 | 1.0021 | 0.4559 |
| 2 | 0.9845 | 0.0827 | 22 | 1.0100 | 0.7033 |
| 3 | 0.9811 | 0.1383 | 23 | 0.9793 | 0.1072 |
| 4 | 0.9803 | 0.1933 | 24 | 0.9762 | 0.0333 |
| 5 | 0.9798 | 0.2483 | 25 | 0.9762 | 0.0030 |
| 6 | 0.9784 | 0.3727 | 26 | 0.9786 | 0.4153 |
| 7 | 0.9785 | 0.3253 | 27 | 0.9788 | 0.4754 |
| 8 | 0.9788 | 0.2826 | 28 | 0.9795 | 0.7624 |
| 9 | 0.9778 | 0.2304 | 29 | 0.9804 | 0.9880 |
| 10 | 0.9772 | 0.1867 | 30 | 0.9819 | 1.0963 |
| 11 | 0.9772 | 0.1815 | 31 | 0.9886 | 1.2675 |
| 12 | 0.9772 | 0.1697 | 32 | 0.9912 | 1.3491 |
| 13 | 0.9785 | 0.1280 | 33 | 0.9953 | 1.5107 |
| 14 | 0.9796 | 0.1267 | 34 | 0.9865 | 0.3746 |
| 15 | 0.9812 | 0.1211 | 35 | 0.9962 | 0.4172 |
| 16 | 0.9833 | 0.1132 | 36 | 1.0155 | 0.8207 |
| 17 | 0.9889 | 0.2084 | 37 | 0.9841 | 0.0896 |
| 18 | 0.9937 | 0.3859 | 38 | 1.0169 | 1.9991 |
| 19 | 0.9857 | 0.1092 | 39 | 0.9857 | 0 |
| 20 | 0.9981 | 0.3461 |
The other information of 4 Load flow calculation of table
Can be seen that alternative iteration method is very effective from ground state power flow solutions, all parameters all in the normal range,
Simultaneously from experimental result it is also seen that LMTR derivation algorithm has the rapidity of very high convergence and calculating.In addition this algorithm
The steady frequency that electric system can also be calculated is 0.9991Hz.
2) effect for improving adaptive sagging control compares
As shown in Figures 3 to 6, it is stable when wave occurs for load to can be very good keep frequency for improved adaptive sagging control
When dynamic, there is very strong robustness.Simultaneously in load fluctuation, all DG still can be by respective capacity than contributing, thus
Avoid that separate unit DG in isolated island micro-capacitance sensor is out-of-limit to cause failure, while by the coordination of all DGs and alternating current-direct current side power, to straight
The stabilization of galvanic electricity pressure also has certain help, and it is steady safely to can be seen that the control method proposed is conducive to maintenance system from experiment
Fixed reliable efficient operation.
Claims (4)
1. based on the isolated island alternating current-direct current mixed connection micro-capacitance sensor tidal current computing method for improving adaptive sagging control, which is characterized in that main
Want the following steps are included:
1) the alternating current-direct current mixed connection micro-capacitance sensor is built；
2) alternating current-direct current mixed connection micro-capacitance sensor Controlling model is established.Main includes the sagging Controlling model of exchange distributed generation resource, direct current point
The sagging Controlling model of cloth power supply, connection current transformer Controlling model, meter and frequency/voltage characteristic load model and it is improved from
Adapt to sagging Controlling model；
3) isolated island alternating current-direct current mixed connection micro-capacitance sensor tide model is established；
4) the LMTR derivation algorithm based on trusted zones is established；
5) Load flow calculation is carried out to isolated island alternating current-direct current mixed connection micro-capacitance sensor tide model with alternative iteration method and LMTR derivation algorithm,
Restraining criterion is cost function ψ (xk) vector differentiation resultε1For Load flow calculation
Convergence precision；If convergence, is transferred to step 6；Continue iteration if not restraining, until convergence.
6) calculation of tidal current is exported, and it is active to change load, using improved adaptive sagging control strategy, updates sagging control
Coefficient processed, re-starts Load flow calculation, until the power output of distributed generation resource is out-of-limit.
2. according to claim 1 based on the isolated island alternating current-direct current mixed connection micro-capacitance sensor Load flow calculation for improving adaptive sagging control
Method, it is characterised in that:
It is as follows to exchange the sagging Controlling model of distributed generation resource:
In formula, ωi、Uaci、PGiAnd QGiThe actual frequency of respectively i-th exchange distributed generation resource, set end voltage amplitude, output
Active power and output reactive power；ω0And Uac0Respectively idling frequency and unloaded set end voltage amplitude；KPiAnd KQiRespectively
Active sagging coefficient and idle sagging coefficient；
Active sagging COEFFICIENT KPiMeet formula 2, it may be assumed that
KP1PN1=KP2PN2=KP3PN3=...=KPnPNn=ωmax-ωmin； (2)
In formula, n is exchange distributed generation resource sum；PNiThe active power of distribution power is exchanged for i-th.
Idle sagging COEFFICIENT KQiMeet formula 3, it may be assumed that
KQ1QN1=KQ2QN2=KQ3QN3=...=KQnQNn=Uac.imax-Uac.imin； (3)
In formula, QNiThe reactive power of distribution power is exchanged for i-th；Uac.imaxThe maximum voltage of distribution power is exchanged for i-th；
Uac.iminThe minimum voltage of distribution power is exchanged for i-th；
The sagging Controlling model of direct current distributed generation resource is as follows:
Udi=Ud0-KdciPGdci； (4)
In formula, Udi、Ud0And PGdciRespectively actual DC voltage magnitude, unloaded DC voltage amplitude and active power of output；Kdci
For the sagging coefficient of direct current distributed generation resource；
The sagging COEFFICIENT K of direct current distributed generation resourcedciMeet formula 5, it may be assumed that
Kdc1PdN1=Kdc2PdN2=...=KdcnPdNn=Udc.max-Udc.min； (5)
In formula, PdNnFor direct current distributed generation resource active power of output；Udc.maxFor direct current distributed generation resource maximum voltage；Udc.min
For direct current distributed generation resource minimum voltage；
It is as follows to connect current transformer Controlling model:
Utilize the frequencies omega and DC voltage U of 6 pairs of connection current transformers of formulaILCdcIt is normalized, makes to connect current transformer
Frequencies omegapuWith DC voltage UILC.puIn identical unit range；
In formula, ωmaxAnd ωminThe respectively maximum frequency and minimum frequency of intercommunion subsystem permission；UILCdc,maxAnd UILCdc,min
The respectively maximum voltage and minimum voltage of direct current subsystem permission；UILCdcFor direct current subsystem voltage；
After normalized, ωpu=[- 1,1], and UILC.pu=[- 1,1]；
The power control equations for connecting current transformer are as follows:
In formula, UILCac0And UILCacRespectively unloaded alternating voltage amplitude and practical alternating voltage amplitude；KPILCAnd KQILCRespectively
Connect the active and idle control coefrficient of current transformer；PILCdcTo connect current transformer direct current subsystem active power；QILCacFor connection
Current transformer intercommunion subsystem reactive power；PILCacTo connect current transformer intercommunion subsystem active power；
Meter and the load model of frequency/voltage characteristic are as follows:
In formula, when the frequency and voltage of system are respectively fL0iAnd UL0iWhen, PL0iAnd QL0iRespectively corresponding practical active power
And reactive power；When frequency and voltage are respectively equal to f and UiWhen, PLiAnd QLiThe respectively corresponding practical active power of load and nothing
Function power；KPfiAnd KQfiThe respectively static frequency characteristic coefficient of load；KPViAnd KQViRespectively load active power index and
Reactive power index；
The key step for establishing improved adaptive sagging Controlling model is as follows:
I initial sagging coefficient) is obtained according to formula 2 and formula 3, and calculates initial trend；
II) improved adaptive sagging Controlling model is respectively as shown in formula 9 and formula 10:
In formula, ωNAnd UacNRespectively exchange the rated frequency and voltage rating of distributed generation resource；WithIt is respectively distributed
The practical active power output and idle power output at power supply t-1 moment before changing load；U'aciIt is distributed for improved i-th of exchange
The set end voltage amplitude of power supply；ω'iThe actual frequency of distributed generation resource is exchanged for improved i-th；
The reality at distributed generation resource t-1 moment before changing load is activeMeet following formula:
In formula, PminFor the active power output minimum value at distributed generation resource t-1 moment before changing load；PmaxExist for distributed generation resource
The active power output maximum value at t-1 moment before changing load；
In formula, QminFor the idle power output minimum value at distributed generation resource t-1 moment before changing load；QmaxExist for distributed generation resource
The idle power output maximum value at t-1 moment before changing load.
3. according to claim 1 or 2 based on the isolated island alternating current-direct current mixed connection micro-capacitance sensor trend for improving adaptive sagging control
Calculation method, which is characterized in that the key step for establishing isolated island alternating current-direct current mixed connection micro-capacitance sensor tide model is as follows:
1) isolated island alternating current-direct current mixed connection micro-capacitance sensor is built；Wherein, exchange node division is 4 classes: PQ node, PV node, sagging node
With ILC-AC node；DC node is divided into 3 classes: permanent P node, sagging node and ILC-DC node；
2) tide model of intercommunion subsystem is established；
The power balance equation of any i-th of node is as follows in intercommunion subsystem:
In formula, xacFor the state variable of intercommunion subsystem；PGiAnd QGiThe active power output and nothing of respectively i-th node generator
Function power output；PLiAnd QLiThe active power and reactive power of respectively i-th node load；PILCaciAnd QILCaciRespectively connect
The injection of inverter ILC is active and idle；SPQ、SPV、SDr-ac、SILC-acRespectively PQ node, PV node, sagging node, ILC-
The set of AC node；PiAnd QiRespectively node injection active power and reactive power；
Node injects active-power PiReactive power Q is injected with nodeiIt is as follows respectively:
In formula, N is node total number；UiFor i-th of node voltage；UjFor j-th of node voltage；δijFor voltage UiWith voltage Uj's
Phase angle difference；GijFor the conductance between node i and node j；BijFor the susceptance between node i and node j；
FPmis.ac.i(xac) and FQmis.ac.i(xac) it is respectively the active and idle imbalance power of i-th of node；
The state variable x of four kinds of node typesac=[xPQi,xPVi,xDr-aci,xILC-aci]TIt is as follows respectively:
δiFor the voltage phase angle of i-th of node；
2) tide model of direct current subsystem is established
The power balance equation of any i-th ' a node is as follows in direct current subsystem:
Fdci'(xdc)=PGdci'-PLdci'-Pdci'-PILCdc=0； (16)
In formula, xdcFor direct current subsystem state variable；PGdci'、PLdci'And PILCdcRespectively direct current distributed generation resource active power output,
Load active power and connection current transformer inject active power；Pdci'For direct current subsystem node injecting power；
Direct current subsystem node injecting power Pdci'It is as follows:
In formula, N' is direct current subsystem node number；Udcj'For the voltage of direct current subsystem jth ' a node；Udci'For direct current
The voltage of a node of system i-th '；Yi'j'For the admittance between a node of direct current subsystem i-th ' and jth ' a node；
The state variable x of direct current subsystemdc=[xP-dci',xDr-dci',xILC-dci']TSpecifically it is expressed as follows:
In formula, SP-dcFor direct current subsystem HengPJie Dianji；SDr-dcFor the sagging node collection of direct current subsystem；SILC-dcFor direct current subsystem
System ILC-DC node collection.
4. according to claim 1 or 2 based on the isolated island alternating current-direct current mixed connection micro-capacitance sensor trend for improving adaptive sagging control
Calculation method, which is characterized in that the key step for establishing the LMTR derivation algorithm based on trusted zones is as follows:
1) Jacobian matrix J is eliminated using the trust region method based on one stepkSingularity, it may be assumed that
In formula, Fk=F (xk)；Jk=J (xk)；FkThe uneven equation for indicating active power and reactive power, F when convergencekTend to
0。dLMKFor current point of operation xkIteration direction；xk+1For the value of next iteration point；I is unit vector；
According to formula 19, work as μkWhen tending to 0, dLMKTend to Gauss-Newton step, works as μkWhen tending to be infinite, dLMKTend under steepest
Drop step；
2) according to the LMTR method based on Load flow calculation to current point of operation xkIteration direction dLMKIt is updated, it may be assumed that
In formula, θ is constant, and 0≤θ≤1；Parameter betakIt is updated using trust region method；
3) cost function ψ (x is definedk)=0.5 | | F (xk)||2, then practical slippage and estimation slippage ratio rkAre as follows:
Then after k iteration, operating point xk+1It is as follows:
In formula, η1For iteration success discriminant coefficient, η1> 0；Wherein, xk+1=xk+dLMkIndicate iteration success, xk+1=xkExpression changes
Generation failure；rkFor operating point xkIteration discriminant parameter；
Parameter betakIt updates as follows:
In formula, η2For iteration success discriminant coefficient, 0 < η1< η2< 1；γ1And γ2For βkCorrection factor, γ1> 1 and 0 < γ2
< 1；βminFor βkMinimum value；If rk> η2, then it represents that iteration is very successful, at this time βk+1=max (γ2βk,βmin)；If η1< γk
< η2, then it represents that iteration is successful, at this time βk+1=βk；If γk< η1, then it represents that iteration fails, at this time βk+1=γ1。γkFor βk's
Iteration discriminant parameter.
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