CN106340890A - Distributed control method for coordinating charging and discharging efficiency of energy storage systems of power distribution network - Google Patents
Distributed control method for coordinating charging and discharging efficiency of energy storage systems of power distribution network Download PDFInfo
- Publication number
- CN106340890A CN106340890A CN201610856012.3A CN201610856012A CN106340890A CN 106340890 A CN106340890 A CN 106340890A CN 201610856012 A CN201610856012 A CN 201610856012A CN 106340890 A CN106340890 A CN 106340890A
- Authority
- CN
- China
- Prior art keywords
- behalf
- represent
- power
- acting
- energy
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- 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
- H02J3/28—Arrangements for balancing of the load in a network by storage of energy
- H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
-
- 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
- H02J3/26—Arrangements for eliminating or reducing asymmetry in polyphase networks
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/50—Arrangements for eliminating or reducing asymmetry in polyphase networks
Landscapes
- Supply And Distribution Of Alternating Current (AREA)
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Charge And Discharge Circuits For Batteries Or The Like (AREA)
Abstract
The invention discloses a distributed control method for coordinating the charging and discharging efficiency of the energy storage systems of a power distribution network. The method includes the following steps that: step 10) local power shortage is calculated: step 20) the sharing of the power shortage is realized, and the total power shortage of the systems is obtained; step 30) the marginal charging cost of each energy storage system is calculated, a preset pinning consistency value is determined; step 40) each energy storage agency is made to achieve consistency through pinning control; and step 50) the charging power of the energy storage systems in the power distribution network is adjusted. The control method is a completely distributed control method. With the control method adopted, global information sharing can be realized in a distributed manner, the requirement of distributed units, for plug-and-play operation, can be satisfied; marginal charging cost and charging states are considered, and the charging power of the energy storage systems is adjusted finely; and therefore, the charging and discharging efficiency of the energy storage systems in the power distribution network can be coordinated and optimized.
Description
Technical field
The invention belongs to active distribution network runs control field, it particularly relates to one kind is used for coordinating power distribution network energy storage
The distributed control method of system efficiency for charge-discharge.
Background technology
With distributed power source, new controllable burden, the permeability of energy-storage system distributed resource steps up, distribution
Net arises at the historic moment being changed into the active electric network of to and fro flow of power, active distribution network technology from passively unidirectional supply network.
Active distribution network is the actual motion state according to power system, with economy, safety as target, to a large amount of distributions accessing
Formula power supply carries out active management, being capable of Automatic adjusument network, power supply, the power distribution network of load.Active distribution network both can be realized
Active control to controllable resources such as distributed power source, flexible load and energy storage, can utilize flexible network topology structure again
Realize effective management of trend, and on the basis of rational supervision and accessing criterion, make distributed power source that distribution system is provided
Certain supporting role.Active distribution network can increase the reliability of power supplied locally, reduce network loss, considerably increase utilization of energy
Efficiency, is a kind of new distribution system meeting following intelligent grid demand for development.
Due to randomness and uncertain and load the multiformity of distributed type renewable generator unit, active distribution network
Disturbance and accident can often occur.Therefore, the mutation of power supply and load proposes challenge to the stable operation of active distribution network.Mesh
Before, there is the local optimal control of many research concern energy-storage system efficiency for charge-discharges and coordinate to control, to stabilize by distributed electrical
Source and the unbalanced power of load fluctuation initiation, improve reliability and the utilization of new energy resources efficiency of active distribution network.Energy-storage system
Coordination control model include centralized and distributed.Centerized fusion needs a central controller to process substantial amounts of number
According to being susceptible to fault, moreover, it is contemplated that to the uncertainty of intermittent regenerative resource, the fluctuation of generating may lead to anticipate
Outer structure change, this just increases central controlled burden further.Additionally, the distributed control method of master-slave mode, due to
Employ leader or virtual leader carry out acquisition process information, similar fault or attack are likely to occur on leader,
Systematic function and reliability are impacted.Completely distributed control method should comprise advantages below to one kind, resists uncertain dry
Disturb and obtain the ability that complete decentralized data updates, it is possible to achieve efficient information sharing, finally realize faster decision-making
And operation.
Content of the invention
Technical problem: the technical problem to be solved is: provide one kind to be used for coordinating power distribution network energy-storage system filling
The distributed control method of discharging efficiency, this control method is one kind completely distributed control method, realizes global information
Distributed sharing, meets the demand of distributed unit plug-and-play operation, and considers marginal charging cost and charged state, to storage
The charge power of energy system is accurately adjusted, thus coordinating the charge efficiency of each energy-storage system in power distribution network.
Technical scheme: for solving above-mentioned technical problem, one kind that the present invention adopts is used for coordinating power distribution network energy-storage system filling
The distributed control method of discharging efficiency, described power distribution network adopts multi-agent system, and multi-agent system includes two-layer: ground floor generation
Reason system is for realizing distributed global information collection and shared information sharing layer；Second layer agency plant is for reality
Existing distributed energy storage system is based on the coordination key-course pining down；Total n agency in multi-agent system, each energy-storage system corresponds to
One agency, the numbering of energy-storage system and identical with the numbering of the corresponding agency of this energy-storage system；Each agency passes through ground floor generation
Reason system obtains global information, is controlled by the distributed collaboration that second layer agency plant is directly realized by energy-storage system；Work as charging
Value and power reference pe,c,i< when 0, as discharge process；
Described control method comprises the steps:
Step 10) calculate local power shortage: when power distribution network occurs power swing, multi-agent system monitors entirely to join
The power disturbance of electrical network, obtains the power shortage of each agency；
Step 20) realize the shared of power shortage, obtain system total power vacancy；
Step 30) calculate the marginal charging cost of each energy-storage system, determine and default pin down concordance value；
Step 40) make each energy storage agency reach by pinning control to pin down concordance；
Step 50) adjustment power distribution network in energy-storage system charge power.
As preference, described step 20) specifically include:
In ground floor agency plant, distributed global information is carried out based on average homogeneity algorithm and shares, realize general power
Vacancy is shared in multi-agent system；
Carry out acting on behalf of the shared procedure of a power shortage using formula (1), until the power shortage of all agencies reaches averagely
During concordance, complete power shortage shared in multi-agent system:
In formula,Represent the power shortage acting on behalf of i in kth time iterative process,Represent in kth time iterative process
The middle distributed power source output power acting on behalf of i, σloss,iRepresent the Transmission loss of load power,Represent in kth time repeatedly
The distributed power source load power of i is acted on behalf of during generation,Represent that the power acting on behalf of i in+1 iterative process of kth lacks
Volume；Represent the power shortage acting on behalf of j in kth time iterative process；wijRepresent and act on behalf of i and act on behalf of the communicative couplings between j
Coefficient, when act on behalf of i and act on behalf of j have communication line connect when, wij≠ 0, otherwise wij=0；niRepresent the set of energy-storage system numbering；
General power vacancy in power distribution network is obtained according to formula (2):
In formula, pmRepresent general power vacancy；nδ(t)The agency's sum controlling is participated in expression system；Represent average one
Cause property convergence of algorithm value；δpm,iRepresent the power shortage acting on behalf of i.
As preference, described step 30) specifically include:
In second layer agency plant, shown in the optimization aim of energy-storage system charging process and constraints such as formula (3):
In formula, pe,c,iRepresent the reference value of charge power；ηc,iRepresent the charge efficiency of i-th energy-storage system；αiIt is i-th
First coefficient of individual energy-storage system；βiIt is the second coefficient of i-th energy-storage system, pmRepresent general power vacancy；δpm,iRepresent generation
The power shortage of reason i；pg,iRepresent the distributed power source output power acting on behalf of i；pl,iRepresent the load power acting on behalf of i；ploss,iTable
Show the loss power acting on behalf of i；Represent the lower limit acting on behalf of i charge power reference value,Represent and act on behalf of i charging work(
The higher limit of rate reference value；
According to formula (4) calculate each agency marginal charging cost:
In formula, ρc,iRepresent that the marginal charging cost function of i is acted on behalf of in energy storage；pe,c,iRepresent the reference value of charge power；
Determine the default concordance value that pins down according to formula (5):
In formula,Represent the marginal charging cost acting on behalf of i in kth time iterative process；Represent in kth time iteration mistake
The charge power reference value of i is acted on behalf of in journey；γiIt is the power shortage coefficient acting on behalf of i；Represent and act on behalf of i side in an iterative process
The final value of border charging cost；Represent default and pin down concordance value, when the asymptotic receipts of marginal charging cost of all energy-storage systems
Hold back in a common valueWhen, the object function of formula (3) reaches optimum.
As preference, described step 40) specifically include: by based on the distributed and coordinated control pining down, being stored up
The marginal charging cost optimization of system default can pin down homogeneity value so as to converge to；
According to the information interactive process acting on behalf of i, obtain acting on behalf of i based on the distributed collaboration governing equation such as formula (6) pining down
Shown:
In formula,Represent the marginal charging cost acting on behalf of i in+1 iterative process of kth；Represent in kth time iteration
During act on behalf of the marginal charging cost of j；diIt is the pinning control gain acting on behalf of i, di≥0；di=0 expression is not directed to acts on behalf of i
Pinning control；
Using formula (7) and formula (8) to wijIt is updated:
In formula, δ (t) represents the change of communication topology in power distribution network；λ represents concordance constant, and the double-deck concordance of impact is calculated
The convergence property of method, and 0 < λ < 1；ni,δ(t)Represent the quantity acting on behalf of i neighbours agency, nj,δ(t)Represent the number acting on behalf of j neighbours agency
Amount, ni,δ(t)Represent the set acting on behalf of i neighbours agency.
As preference, described step 50) specifically include: according to step 40) limit that optimizes of each agency of obtaining
Charging cost, and the charged state in view of energy-storage system, according to formula (9) adjustment charge power reference value:
In formula, ζiRepresent the charged state acting on behalf of i；Represent the lower limit acting on behalf of i charged state；Represent that acting on behalf of i fills
The upper limit of electricity condition；
Charged state ζ acting on behalf of i is calculated according to formula (10)i:
In formula,Represent the charged state acting on behalf of i in kth time iterative process；Represent in -1 iterative process of kth
The middle charged state acting on behalf of i；Represent the charge power reference value acting on behalf of i in -1 iterative process of kth；Represent
The charge efficiency of i is acted on behalf of in -1 iterative process of kth；δ t represents discrete time intervals；ce,iRepresent the storage volume acting on behalf of i.
As preference, described σloss,iValue is 5% to the 7% of total load power.
Beneficial effect: the control method of the embodiment of the present invention is one kind completely distributed control method, is acted on behalf of based on more
The double-deck consistency algorithm of system, coordinates the efficiency for charge-discharge of power distribution network energy-storage system, it is possible to achieve the efficiently distributed overall situation
Information sharing, and consider marginal discharge and recharge cost and charging and discharging state, carry out efficiency for charge-discharge optimization, there is good self adaptation
Property, the demand of distributed unit plug and play can be met.The coordination power distribution network energy-storage system discharge and recharge effect of the embodiment of the present invention
The distributed control method of rate, monitors the power swing of power distribution network by local agent, in power distribution network emergent power vacancy, from
There is acquisition global information in the multi-agent system of communication constraint, obtain system total power vacancy.In ground floor, using average
Consistency algorithm carry out distributed information share, when result reaches average homogeneity, complete global information multi-agent system it
Between shared.This algorithm can carry out adaptive weighting renewal, can adapt to the change of communication topology, realizes the fast of global information
Speed is efficiently shared.In the second layer, each agency, according to charge and discharge process, solves charge and discharge process using pining down consistency algorithm
Optimized model, when all proxy isochronous converge to default pin down concordance value when, obtain optimum marginal discharge and recharge cost.
Adjust the charge-discharge electric power reference value of energy-storage system according to the optimal result obtaining, thus coordinating the charge and discharge of power distribution network energy-storage system
Electrical efficiency.
Brief description
Fig. 1 is the FB(flow block) of the embodiment of the present invention.
Fig. 2 is the structural representation of power distribution network analogue system in the embodiment of the present invention.
Fig. 3 is the control effect figure of simulating scenes one in the embodiment of the present invention.
Fig. 4 is the control effect figure of simulating scenes two in the embodiment of the present invention.
Fig. 5 is the control effect figure of simulating scenes three in the embodiment of the present invention.
Specific embodiment
In order that the objects, technical solutions and advantages of the present invention become more apparent, below in conjunction with accompanying drawing and case study on implementation
The present invention is in depth described in detail.It should be appreciated that described herein be embodied as case only in order to explain this
Bright, it is not used to limit invention.
In the embodiment of the present invention, power distribution network adopts multi-agent system, and multi-agent system includes two-layer: ground floor agency plant
It is for realizing distributed global information collection and shared information sharing layer；Second layer agency plant is for realizing distribution
Formula energy-storage system is based on the coordination key-course pining down；Total n agency in multi-agent system, each energy-storage system corresponds to a generation
Reason, the numbering of energy-storage system and identical with the numbering of the corresponding agency of this energy-storage system；Each agency passes through ground floor agency plant
Obtain global information, controlled by the distributed collaboration that second layer agency plant is directly realized by energy-storage system；When charge power ginseng
Examine value pe,c,i< when 0, as discharge process.
As shown in figure 1, the embodiment of the present invention a kind of for coordinating the distributed of power distribution network energy-storage system efficiency for charge-discharge
Control method, comprises the steps:
Step 10) calculate local power shortage: when power distribution network occurs power swing, multi-agent system monitors entirely to join
The power disturbance of electrical network, obtains the power shortage of each agency.
Step 20) realize the shared of power shortage, obtain system total power vacancy: in ground floor agency plant, be based on
Average homogeneity algorithm carries out distributed global information and shares, and realizes general power vacancy shared in multi-agent system；
Carry out acting on behalf of the shared procedure of a power shortage using formula (1), until the power shortage of all agencies reaches averagely
During concordance, complete power shortage shared in multi-agent system:
In formula,Represent the power shortage acting on behalf of i in kth time iterative process,Represent in kth time iterative process
The middle distributed power source output power acting on behalf of i, σloss,iRepresent the Transmission loss of load power, preferably, described
σloss,iValue is 5% to the 7% of total load power.Represent the distributed power source load acting on behalf of i in kth time iterative process
Power,Represent the power shortage acting on behalf of i in+1 iterative process of kth；Represent generation in kth time iterative process
The power shortage of reason j；wijRepresent and act on behalf of i and act on behalf of communicative couplings coefficient between j, when acting on behalf of i and act on behalf of j and have communication line even
When connecing, wij≠ 0, otherwise wij=0；niRepresent the set of energy-storage system numbering；
General power vacancy in power distribution network is obtained according to formula (2):
In formula, pmRepresent general power vacancy；nδ(t)The agency's sum controlling is participated in expression system；Represent average one
Cause property convergence of algorithm value；δpm,iRepresent the power shortage acting on behalf of i；
Step 30) calculate the marginal charging cost of each energy-storage system, determine and default pin down concordance value；
In second layer agency plant, shown in the optimization aim of energy-storage system charging process and constraints such as formula (3):
In formula, pe,c,iRepresent the reference value of charge power；ηc,iRepresent the charge efficiency of i-th energy-storage system；αiIt is i-th
First coefficient of individual energy-storage system；βiIt is the second coefficient of i-th energy-storage system, pmRepresent general power vacancy；δpm,iRepresent generation
The power shortage of reason i；pg,iRepresent the distributed power source output power acting on behalf of i；pl,iRepresent the load power acting on behalf of i；ploss,iTable
Show the loss power acting on behalf of i；Represent the lower limit acting on behalf of i charge power reference value,Represent and act on behalf of i charging work(
The higher limit of rate reference value；
According to formula (4) calculate each agency marginal charging cost:
In formula, ρc,iRepresent that the marginal charging cost function of i is acted on behalf of in energy storage；pe,c,iRepresent the reference value of charge power；
Determine the default concordance value that pins down according to formula (5):
In formula,Represent the marginal charging cost acting on behalf of i in kth time iterative process；Represent in kth time iteration mistake
The charge power reference value of i is acted on behalf of in journey；γiIt is the power shortage coefficient acting on behalf of i；Represent and act on behalf of i side in an iterative process
The final value of border charging cost；Represent default and pin down concordance value, when the asymptotic receipts of marginal charging cost of all energy-storage systems
Hold back in a common valueWhen, the object function of formula (3) reaches optimum.
Step 40) make each energy storage agency reach by pinning control to pin down concordance: by based on the distributed association pining down
Regulation and control system, carries out the marginal charging cost optimization of energy-storage system so as to converge to and default pins down homogeneity value；
According to the information interactive process acting on behalf of i, obtain acting on behalf of i based on the distributed collaboration governing equation such as formula (6) pining down
Shown:
In formula,Represent the marginal charging cost acting on behalf of i in+1 iterative process of kth；Represent in kth time iteration
During act on behalf of the marginal charging cost of j；diIt is the pinning control gain acting on behalf of i, di≥0；di=0 expression is not directed to acts on behalf of i
Pinning control；
Using formula (7) and formula (8) to wijIt is updated:
In formula, δ (t) represents the change of communication topology in power distribution network；λ represents concordance constant, and the double-deck concordance of impact is calculated
The convergence property of method, and 0 < λ < 1；ni,δ(t)Represent the quantity acting on behalf of i neighbours agency, nj,δ(t)Represent the number acting on behalf of j neighbours agency
Amount, ni,δ(t)Represent the set acting on behalf of i neighbours agency.
Step 50) adjustment power distribution network in energy-storage system charge power: according to step 40) obtain each agency optimize
Marginal charging cost, and the charged state in view of energy-storage system, according to formula (9) adjustment charge power reference value:
In formula, ζiRepresent the charged state acting on behalf of i；Represent the lower limit acting on behalf of i charged state；Represent that acting on behalf of i charges
The upper limit of state；
Charged state ζ acting on behalf of i is calculated according to formula (10)i:
In formula,Represent the charged state acting on behalf of i in kth time iterative process；Represent in -1 iterative process of kth
The middle charged state acting on behalf of i；Represent the charge power reference value acting on behalf of i in -1 iterative process of kth；Represent
The charge efficiency of i is acted on behalf of in -1 iterative process of kth；δ t represents discrete time intervals；ce,iRepresent the storage volume acting on behalf of i.
The control method of the embodiment of the present invention can coordinate the efficiency for charge-discharge of energy-storage system in power distribution network, it is possible to achieve high
The distributed global information of effect is shared, and considers marginal discharge and recharge cost and charging and discharging state, has good adaptivity, can
To meet the demand of distributed unit plug and play.
An embodiment is set forth below.
As shown in Fig. 2 the communication topology figure of the power distribution network analogue system of the present embodiment employing.This phantom uses 33 sections
Point power distribution system network structure, including 6 distribution type power supplys (abbreviation dgs), 5 energy-storage systems (ess1, ess2, ess3,
Ess4, ess5), each energy-storage system accesses power distribution network by transformator.System has 5 distributed agents (agent), uses respectively
A1, a2, a3, a4, a5 represent, correspond to each energy-storage system respectively.Each agency can only with it in communication topology direct neighbor
Agency communicated, the information updating cycle be 0.1 second.Based on power system computation machine Aided Design/transient state containing direct solenoid
Emulation (English abbreviation: pscad/emtdc) platform building power distribution network phantom, at matrix labotstory (English abbreviation matlab)
Middle simulation multi-agent system, sets up the double-deck consistency algorithm of multi-agent system, will using fortran language compilation's interface routine
Algorithm in matlab and power system computation machine Aided Design (English abbreviation pscad) model cooperation, thus using connection
Close the simulating, verifying that emulation technology realizes the control method of the present invention.
Emulated for system power fluctuation in power distribution network and communication topology change both of these case, verified the present invention
The control effect of method, that is, distributed global information is shared, marginal charging cost optimization and energy-storage system charge power adjust.This
Embodiment three simulating scenes of setting:
Scene one is for load variations and fixed communication topology.When emulation starts, in active distribution network, access four storages
Energy system (ess1, ess2, ess3, ess4), and the communication line disconnection between a1 and a4, active distribution network operates in stable
State.During t=1s, in active distribution network, load breaks down, emergent power vacancy, and distributed and coordinated control starts immediately.First
First, carry out global information in ground floor and share: each agency is local to calculate power shortage, and is exchanged by average homogeneity algorithm
Information, obtains system total power vacancy δ pm=60kw；Then, carry out based on the complete distributed coordination control pining down in the second layer
System: by solving the optimal solution of object function it is determined that default pin down concordance valueAnd made based on pinning control
The marginal charging cost of all agencies all converges to and default pins down concordance value；Finally, after each agency is according to the optimization obtaining
Marginal charging cost, adjustment charge power reference value be respectively 13.96kw, 14.41kw, 22kw, 13.34kw.Simulation result
As shown in Figure 3.Wherein, Fig. 3 (a) represents shared procedure in each agency for the power shortage information.From Fig. 3 (a) it can be seen that each
Agency is finally reached average homogeneity, obtains general power vacancy information.Fig. 3 (b) represents the pinning control process of each agency.From
Fig. 3 (b) is it can be seen that the marginal charging cost of each agency all converges to and default pins down concordance value.Fig. 3 (c) represents each generation
The process of reason adjustment charge power reference value.From Fig. 3 (c) it can be seen that each agency adjusts according to the marginal charging cost after optimizing
Whole respective charge power reference value, thus collaborative increase charge power.
Scene two is for distributed power source power swing and communication line switching.When emulation starts, in active distribution network
Access four energy-storage systems (ess1, ess2, ess3, ess4), and the communication line between a1 and a4 disconnects, active distribution network
Operate in steady statue.During t=1s, distributed power source emergent power fluctuates, and produces power shortage, connects between a1 and a4 simultaneously
New communication line.By the distributed and coordinated control based on double-deck consistency algorithm, system total power vacancy δ pm=50kw,
Default pin down concordance value The charge power reference value of adjustment is respectively 11.89kw, 12.10kw, 16.47kw,
9.54kw.Simulation result is as shown in Figure 4.Fig. 4 (a) represents shared procedure in each agency for the power shortage information.Fig. 4 (b) table
Show the pinning control process of each agency.It can be seen that each agency is obtained in that general power by double-deck consistency algorithm
Vacancy information, makes marginal charging cost converge to and default pins down concordance value；Due to increased communication line, communicative couplings system
Number wijCan be updated, double-deck conforming convergence rate is than the fast convergence rate in scene one；Fig. 4 (c) represents that each agency adjusts
The process of whole charge power reference value, each agency adjusts respective charge power reference according to the marginal charging cost after optimizing
Value, thus collaborative increase charge power.
Scene three is with load variations and to access new energy-storage system for distributed power source.When emulation starts, actively
Newly access an energy-storage system (ess5) in power distribution network, corresponding act on behalf of as a5, communication topology changes.During t=1s, by point
Cloth power fluctuation and load variations and produce power shortage, distributed and coordinated control start start.Firstly, since accessing
New energy-storage system, carries out that identity updates and communicative couplings coefficient update is it is only necessary to the neighbours agency of a5 carries out information updating
?；Then carry out sharing and carrying out based on the distributed coordination pining down in the second layer of system total power vacancy in ground floor
Control, obtain system total power vacancy δ pm=80kw, default pins down concordance valueThe charging work(finally adjusting
Rate reference value is respectively 16.82kw, 16.06kw, 14.18kw, 16.90kw, 16.04kw.Simulation result is as shown in Figure 5.Fig. 5
A () represents shared procedure in each agency for the power shortage information.Fig. 5 (b) represents the pinning control process of each agency.From in figure
As can be seen that each agency is obtained in that general power vacancy information by double-deck consistency algorithm, marginal charging cost is made to converge to
Default pin down concordance value；But due to the access operation carrying out energy-storage system, communication topology change is complicated, double-deck consistent
The convergence rate of property is slower than the convergence rate in scene one.Fig. 4 (c) represents the process of each agency's adjustment charge power reference value,
Each agency adjusts respective charge power reference value according to the marginal charging cost after optimizing, thus collaborative increase charge power,
Illustrate that the method for the present invention adaptively can be carried out when carrying out acting on behalf of access operation.
As can be seen here, scene one can illustrate that the method for the present invention can solve the problem that and asked by the unbalanced power that load variations cause
Topic, scene two can illustrate unbalanced power problem and the order wire that the method for the present invention can solve the problem that power-supply fluctuation causes
Road variation issue, scene three can illustrate the method for the present invention can solve the problem that load variations and power-supply fluctuation causes simultaneously power not
Equilibrium problem and power supply plug and play problem.
From the present embodiment as can be seen that after using the control method of the present invention, active distribution network can coordinate power distribution network storage
The charge efficiency of energy system, it is possible to achieve efficiently distributed global information is shared, and considers marginal charging cost and charging shape
State, is charged efficiency optimization, has good adaptivity, disclosure satisfy that the demand of distributed unit plug and play, explanation
Method proposed by the present invention has control effect well.
Claims (6)
1. a kind of distributed control method for coordinating power distribution network energy-storage system efficiency for charge-discharge is it is characterised in that described join
Electrical network adopts multi-agent system, and multi-agent system includes two-layer: ground floor agency plant is for realizing distributed overall situation letter
Breath collection and shared information sharing layer；Second layer agency plant is for realizing distributed energy storage system based on the coordination pining down
Key-course；Total n agency in multi-agent system, corresponding one of each energy-storage system is acted on behalf of, the numbering of energy-storage system and with this
The numbering of the corresponding agency of energy-storage system is identical；Each agency obtains global information by ground floor agency plant, by the second layer
The distributed collaboration that agency plant is directly realized by energy-storage system controls；When charge power reference value pe,c,i< when 0, as discharged
Journey；
Described control method comprises the steps:
Step 10) calculate local power shortage: when power distribution network occurs power swing, multi-agent system monitors whole power distribution network
Power disturbance, obtain each agency power shortage；
Step 20) realize the shared of power shortage, obtain system total power vacancy；
Step 30) calculate the marginal charging cost of each energy-storage system, determine and default pin down concordance value；
Step 40) make each energy storage agency reach by pinning control to pin down concordance；
Step 50) adjustment power distribution network in energy-storage system charge power.
2. according to described in claim 1 for coordinating the distributed control method of power distribution network energy-storage system efficiency for charge-discharge, its
It is characterised by, described step 20) specifically include:
In ground floor agency plant, distributed global information is carried out based on average homogeneity algorithm and shares, realize general power vacancy
Shared in multi-agent system；
Carry out acting on behalf of the shared procedure of a power shortage using formula (1), until the power shortage of all agencies reaches average homogeneity
Property when, complete power shortage shared in multi-agent system:
In formula,Represent the power shortage acting on behalf of i in kth time iterative process,Represent generation in kth time iterative process
The distributed power source output power of reason i, σloss,iRepresent the Transmission loss of load power,Represent in kth time iteration mistake
The distributed power source load power of i is acted on behalf of in journey,Represent the power shortage acting on behalf of i in+1 iterative process of kth；Represent the power shortage acting on behalf of j in kth time iterative process；wijRepresent and act on behalf of i and act on behalf of the communicative couplings system between j
Number, when act on behalf of i and act on behalf of j have communication line connect when, wij≠ 0, otherwise wij=0；niRepresent the set of energy-storage system numbering；
General power vacancy in power distribution network is obtained according to formula (2):
In formula, pmRepresent general power vacancy；nδ(t)The agency's sum controlling is participated in expression system；Represent average homogeneity
Convergence of algorithm value；δpm,iRepresent the power shortage acting on behalf of i.
3. according to described in claim 1 for coordinating the distributed control method of power distribution network energy-storage system efficiency for charge-discharge, its
It is characterised by, described step 30) specifically include:
In second layer agency plant, shown in the optimization aim of energy-storage system charging process and constraints such as formula (3):
In formula, pe,c,iRepresent the reference value of charge power；ηc,iRepresent the charge efficiency of i-th energy-storage system；αiIt is i-th storage
First coefficient of energy system；βiIt is the second coefficient of i-th energy-storage system, pmRepresent general power vacancy；δpm,iRepresent and act on behalf of i's
Power shortage；pg,iRepresent the distributed power source output power acting on behalf of i；pl,iRepresent the load power acting on behalf of i；ploss,iRepresent generation
The loss power of reason i；Represent the lower limit acting on behalf of i charge power reference value,Represent and act on behalf of i charge power ginseng
Examine the higher limit of value；
According to formula (4) calculate each agency marginal charging cost:
In formula, ρc,iRepresent that the marginal charging cost function of i is acted on behalf of in energy storage；pe,c,iRepresent the reference value of charge power；
Determine the default concordance value that pins down according to formula (5):
In formula,Represent the marginal charging cost acting on behalf of i in kth time iterative process；Represent in kth time iterative process
Act on behalf of the charge power reference value of i；γiIt is the power shortage coefficient acting on behalf of i；I is acted on behalf of in expression, and limit is filled in an iterative process
The final value of electric cost；Represent default pins down concordance value, when all energy-storage systems marginal charging cost asymptotic convergence in
One common valueWhen, the object function of formula (3) reaches optimum.
4. according to described in claim 1 for coordinating the distributed control method of power distribution network energy-storage system efficiency for charge-discharge, its
It is characterised by, described step 40) specifically include: by based on the distributed and coordinated control pining down, carrying out the side of energy-storage system
Border charging cost optimization default pins down homogeneity value so as to converge to；
According to the information interactive process acting on behalf of i, obtain acting on behalf of i based on the distributed collaboration governing equation such as formula (6) pining down Suo Shi:
In formula,Represent the marginal charging cost acting on behalf of i in+1 iterative process of kth；Represent in kth time iterative process
The middle marginal charging cost acting on behalf of j；diIt is the pinning control gain acting on behalf of i, di≥0；di=0 expression is not directed to acts on behalf of leading of i
System controls；
Using formula (7) and formula (8) to wijIt is updated:
In formula, δ (t) represents the change of communication topology in power distribution network；λ represents concordance constant, the double-deck consistency algorithm of impact
Convergence property, and 0 < λ < 1；ni,δ(t)Represent the quantity acting on behalf of i neighbours agency, nj,δ(t)Represent the quantity acting on behalf of j neighbours agency,
ni,δ(t)Represent the set acting on behalf of i neighbours agency.
5. according to described in claim 1 for coordinating the distributed control method of power distribution network energy-storage system efficiency for charge-discharge, its
It is characterised by, described step 50) specifically include: according to step 40) the marginal charging cost that optimizes of each agency of obtaining, and
In view of the charged state of energy-storage system, according to formula (9) adjustment charge power reference value:
In formula, ζiRepresent the charged state acting on behalf of i；Represent the lower limit acting on behalf of i charged state；Represent and act on behalf of i charged state
The upper limit；
Charged state ζ acting on behalf of i is calculated according to formula (10)i:
In formula,Represent the charged state acting on behalf of i in kth time iterative process；Represent generation in -1 iterative process of kth
The charged state of reason i；Represent the charge power reference value acting on behalf of i in -1 iterative process of kth；Represent in kth -1
The charge efficiency of i is acted on behalf of in secondary iterative process；δ t represents discrete time intervals；ce,iRepresent the storage volume acting on behalf of i.
6. according to described in claim 1 for coordinating the distributed control method of power distribution network energy-storage system efficiency for charge-discharge, its
It is characterised by, described σloss,iValue is 5% to the 7% of total load power.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610856012.3A CN106340890B (en) | 2016-09-27 | 2016-09-27 | For coordinating the distributed control method of power distribution network energy-storage system efficiency for charge-discharge |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610856012.3A CN106340890B (en) | 2016-09-27 | 2016-09-27 | For coordinating the distributed control method of power distribution network energy-storage system efficiency for charge-discharge |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106340890A true CN106340890A (en) | 2017-01-18 |
| CN106340890B CN106340890B (en) | 2018-12-28 |
Family
ID=57839377
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610856012.3A Active CN106340890B (en) | 2016-09-27 | 2016-09-27 | For coordinating the distributed control method of power distribution network energy-storage system efficiency for charge-discharge |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106340890B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107069776A (en) * | 2017-04-12 | 2017-08-18 | 东南大学 | A kind of energy storage prediction distributed control method of smooth microgrid dominant eigenvalues |
| CN107623337A (en) * | 2017-09-26 | 2018-01-23 | 武汉大学 | A kind of energy management method for micro-grid |
| CN109066812A (en) * | 2018-10-29 | 2018-12-21 | 东北大学 | A kind of electric system Multiobjective Optimal Operation method based on the double-deck consistency algorithm |
| CN109301892A (en) * | 2018-09-21 | 2019-02-01 | 国网重庆市电力公司电力科学研究院 | A kind of charging method and system of distributed energy storage system |
| CN111373423A (en) * | 2017-07-18 | 2020-07-03 | 西门子公司 | Distributed planning, scheduling and control of multi-agent flow control system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103427432A (en) * | 2013-08-09 | 2013-12-04 | 江苏欧力特能源科技有限公司 | Control method to balance microgrid mismatch power by aid of distributed storage battery energy storing stations |
| CN104218681A (en) * | 2014-09-28 | 2014-12-17 | 东南大学 | Controlling method for reducing load shedding costs of island microgrid |
| CN105391090A (en) * | 2015-11-10 | 2016-03-09 | 南京邮电大学 | Multi-intelligent-agent multi-target consistency optimization method of intelligent power grid |
-
2016
- 2016-09-27 CN CN201610856012.3A patent/CN106340890B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103427432A (en) * | 2013-08-09 | 2013-12-04 | 江苏欧力特能源科技有限公司 | Control method to balance microgrid mismatch power by aid of distributed storage battery energy storing stations |
| CN104218681A (en) * | 2014-09-28 | 2014-12-17 | 东南大学 | Controlling method for reducing load shedding costs of island microgrid |
| CN105391090A (en) * | 2015-11-10 | 2016-03-09 | 南京邮电大学 | Multi-intelligent-agent multi-target consistency optimization method of intelligent power grid |
Non-Patent Citations (2)
| Title |
|---|
| CHENDAN LI 等: "Multiagent based distributed control for state-of-charge balance of distributed energy storage in DC microgrids", 《INDUSTRIAL ELECTRONICS SOCIETY, IECON 2014 - 40TH ANNUAL CONFERENCE OF THE IEEE》 * |
| 刘延博 等: "孤岛运行下含储能系统的微电网多代理博弈模型", 《高压电器》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107069776A (en) * | 2017-04-12 | 2017-08-18 | 东南大学 | A kind of energy storage prediction distributed control method of smooth microgrid dominant eigenvalues |
| CN107069776B (en) * | 2017-04-12 | 2019-12-24 | 东南大学 | Energy storage look-ahead distributed control method for smooth microgrid tie line power |
| CN111373423A (en) * | 2017-07-18 | 2020-07-03 | 西门子公司 | Distributed planning, scheduling and control of multi-agent flow control system |
| CN107623337A (en) * | 2017-09-26 | 2018-01-23 | 武汉大学 | A kind of energy management method for micro-grid |
| CN107623337B (en) * | 2017-09-26 | 2019-09-10 | 武汉大学 | A kind of energy management method for micro-grid |
| CN109301892A (en) * | 2018-09-21 | 2019-02-01 | 国网重庆市电力公司电力科学研究院 | A kind of charging method and system of distributed energy storage system |
| CN109066812A (en) * | 2018-10-29 | 2018-12-21 | 东北大学 | A kind of electric system Multiobjective Optimal Operation method based on the double-deck consistency algorithm |
| CN109066812B (en) * | 2018-10-29 | 2021-01-26 | 东北大学 | Electric power system multi-objective optimization scheduling method based on double-layer consistency algorithm |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106340890B (en) | 2018-12-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106340890B (en) | For coordinating the distributed control method of power distribution network energy-storage system efficiency for charge-discharge | |
| Li et al. | Multiagent-based distributed state of charge balancing control for distributed energy storage units in AC microgrids | |
| Zhao et al. | An MAS based energy management system for a stand-alone microgrid at high altitude | |
| CN106410808B (en) | Universal micro-capacitance sensor group distributed control method comprising invariable power and droop control | |
| CN101777769B (en) | Multi-agent optimized coordination control method of electric network | |
| CN103870649B (en) | Active power distribution network autonomous simulation method based on distributive intelligent computing | |
| CN107221937B (en) | Distribution network failure reconstruct and voltage control method and system based on distributed energy storage | |
| CN105870949B (en) | A kind of micro-capacitance sensor energy-storage units optimal control method based on distributed gradient algorithm | |
| CN105186500B (en) | A kind of power distribution network power dissipation coordination optimizing method based on weighting acceleration Lagrangian again | |
| CN110826880A (en) | Active power distribution network optimal scheduling method for large-scale electric vehicle access | |
| CN103151802A (en) | Coordinated control system and method for DG (Differential Gain) of multi-time scale active power distribution network | |
| CN112769160B (en) | Microgrid cluster self-optimization-seeking control method considering grid-connected and island operation modes | |
| Chen et al. | A unified time scale intelligent control algorithm for microgrid based on extreme dynamic programming | |
| CN110474353A (en) | Layer-stepping energy-storage system and its power grid frequency modulation control method for coordinating of participation | |
| CN104218681B (en) | A kind of control method for reducing isolated island micro-capacitance sensor cutting load cost | |
| CN104659811A (en) | Distributed cooperative control method of micro power grid on basis of holdback | |
| CN103746384A (en) | Electrical load dispatching control method and system thereof | |
| CN108365627A (en) | A kind of wind storage isolated network power supply system control method for coordinating based on flexible coordinating factor | |
| CN104332985A (en) | Hybrid control strategy based direct current distribution network operation control and optimization scheduling method | |
| CN106712113A (en) | Droop control method of voltage source inverter for photovoltaic energy storage independent microgrid | |
| CN110120673A (en) | Distributed transmission & distribution collaboration idle work optimization method and system based on Thevenin's equivalence parameter identification | |
| CN113328425A (en) | Power distribution network consistency economic control method considering event triggering | |
| CN104698859A (en) | Distributed energy generation experiment system | |
| CN110518641A (en) | A kind of exchange micro-capacitance sensor realizes the distributed layer control method for coordinating of power distribution | |
| CN115800276A (en) | Power system emergency scheduling method considering unit climbing |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |