CN106340899B - A kind of dynamic isolated island division methods to reduce Custom interruption cost target - Google Patents
A kind of dynamic isolated island division methods to reduce Custom interruption cost target Download PDFInfo
- Publication number
- CN106340899B CN106340899B CN201610838309.7A CN201610838309A CN106340899B CN 106340899 B CN106340899 B CN 106340899B CN 201610838309 A CN201610838309 A CN 201610838309A CN 106340899 B CN106340899 B CN 106340899B
- Authority
- CN
- China
- Prior art keywords
- node
- power
- load
- formula
- isolated island
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000005192 partition Methods 0.000 claims abstract description 15
- 230000009194 climbing Effects 0.000 claims abstract description 5
- 238000004146 energy storage Methods 0.000 claims description 57
- 238000005457 optimization Methods 0.000 claims description 5
- 230000005611 electricity Effects 0.000 claims description 4
- NAWXUBYGYWOOIX-SFHVURJKSA-N (2s)-2-[[4-[2-(2,4-diaminoquinazolin-6-yl)ethyl]benzoyl]amino]-4-methylidenepentanedioic acid Chemical compound C1=CC2=NC(N)=NC(N)=C2C=C1CCC1=CC=C(C(=O)N[C@@H](CC(=C)C(O)=O)C(O)=O)C=C1 NAWXUBYGYWOOIX-SFHVURJKSA-N 0.000 claims description 3
- 230000004888 barrier function Effects 0.000 claims description 3
- ONIBWKKTOPOVIA-UHFFFAOYSA-M prolinate Chemical compound [O-]C(=O)C1CCCN1 ONIBWKKTOPOVIA-UHFFFAOYSA-M 0.000 claims description 3
- 150000002500 ions Chemical class 0.000 claims 1
- 230000003068 static effect Effects 0.000 description 5
- 240000002853 Nelumbo nucifera Species 0.000 description 3
- 235000006508 Nelumbo nucifera Nutrition 0.000 description 3
- 235000006510 Nelumbo pentapetala Nutrition 0.000 description 3
- 230000008901 benefit Effects 0.000 description 3
- 241000208340 Araliaceae Species 0.000 description 2
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 2
- 235000003140 Panax quinquefolius Nutrition 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 235000008434 ginseng Nutrition 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 241000196324 Embryophyta Species 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 230000035699 permeability Effects 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
- 238000011084 recovery Methods 0.000 description 1
- 238000000638 solvent extraction Methods 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Classifications
-
- H02J3/383—
-
- 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]
-
- 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
- H02J3/388—Islanding, i.e. disconnection of local power supply from the network
-
- 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
- Y02E10/00—Energy generation through renewable energy sources
- Y02E10/50—Photovoltaic [PV] energy
- Y02E10/56—Power conversion systems, e.g. maximum power point trackers
Abstract
The invention discloses a kind of dynamic isolated island division methods to reduce Custom interruption cost target, step includes: 1) to be fitted all types of user loss of outage function；2) uncertainty models of distributed generation resource and load are established；3) it establishes with the dynamic isolated island Partition Theory optimal models of the minimum target of loss of outage；4) it establishes and simplified model is divided with the dynamic isolated island of the minimum target of loss of outage；5) simplified model is solved with climbing method, obtains dynamic isolated island division result.The method of the present invention can dynamically divide isolated island during system blackout, utilize distributed generation resource in maximum efficiency, reduce user because losing caused by having a power failure.
Description
Technical field
The invention belongs to power distribution network control, operation and optimization fields, are related to a kind of to reduce Custom interruption cost target
Dynamic isolated island division methods.
Background technique
Electric power isolated operation is the special method of operation of one of smart grid.For power distribution network, due to distribution
The permeability of power supply (distributed generator, DG) is more and more stronger, and such as country 6MW photovoltaic plant below is unconditional
Grid-connected policy is tried to execute in some areas.It, will in various regions power distribution network at home with the integral implementation of the policy
It include the DG system largely based on small photovoltaic power generation, it is special that power distribution network is just gradually possessing certain operations similar with power transmission network
Property.It breaks down in the case where leading to distribution system blackout because of transmission system or distribution system, is actively sent out because DG has
The ability of electricity, can restore the confession of a part of important load and being formed using DG as the power distribution network electric power isolated operation of power supply
Electricity.Isolated island division is the important link of isolated operation, and for determining the supply district of DG, reasonable isolated island division can be further
The utilization efficiency of DG is promoted, loss caused by Distribution Network Failure is reduced, promotes power supply reliability.
Summary of the invention
Technical problem: the present invention provides a kind of dynamic isolated island division methods to reduce Custom interruption cost target, the party
Method can farthest reduce the total loss of outage of system, promote the economy of power distribution network operation.
Technical solution: the dynamic isolated island division methods of the invention to reduce Custom interruption cost target, including following step
It is rapid:
1) it is fitted all types of user loss of outage function；
2) uncertainty models of distributed generation resource and load are established；
3) it establishes with the dynamic isolated island Partition Theory optimal models of the minimum target of loss of outage；
4) dynamic isolated island Partition Theory optimal models are simplified, obtains simplified model；
5) simplified model is solved with climbing method, obtains dynamic isolated island division result.
As preference, in the step 1), all types of user loss of outage Function Fitting method is as follows:
The relationship of all types of user loss of outage and power failure duration is referred to using least square method according to statistical data
Number Function Fitting:
fIC,type(t)=10^ (αtype*ln(t)+βtype)/t formula (1)
Wherein, type is load type, type ∈ Ωtype, ΩtypeIt is the set of load type, fIC,typeIt is that type is
The customer interruption cost function of the load of type, t are power failure duration, αtypeIt is the first fitting parameter, βtypeIt is the second fitting ginseng
Number.
As preference, in the step 2), distributed generation resource includes photovoltaic and energy storage, wherein the power output of photovoltaic is random
Property is indicated with normal distribution, as shown in formula (2):
PPV~N (PPV,exp,σPV) formula (2)
Wherein, PPVFor practical photovoltaic power generating value, PPV,expFor the desired value of normal distribution, value is the prediction of photovoltaic power output
Value, σPVFor the standard deviation of normal distribution, N is normal distribution symbol；
The remaining capacity SOC of energy storage, as shown in formula (3):
Wherein, SOC (BE, t2) indicate energy storage in t2The remaining capacity at moment, SOC (BE, t1) indicate energy storage in t1Moment
Remaining capacity.PBEFor the power of energy storage, when energy storage electric discharge, PBEValue is negative；When energy storage charging, PBEValue is positive；η is
The efficiency of energy storage charge and discharge, CapBEFor the capacity of energy storage, t1For initial time, t2For end time；
The uncertainty of load is indicated with normal distribution, as shown in formula (4):
PL~N (PL,exp,σL) formula (4)
Wherein, PLFor actual load performance number, PL,expFor the desired value of normal distribution, value is the prediction power of load,
σLFor the standard deviation of normal distribution.
As preference, in the step 3), establish with the dynamic isolated island Partition Theory of the minimum target of loss of outage most
The optimization aim expression formula of excellent model, such as formula (5):
Wherein, V0For the node set of power supply interrupted district, NiFor the frequency of power cut of node i, Ts i,jHave a power failure for node i jth time
Start time, Te i,jFor the finish time that node i jth time has a power failure, PLiIt (t) is wattful power of the load at node i in t moment
Rate, itype are the user type of load at node i, fIC,itypeIt is the customer interruption cost function of the load at node i, Pi,j,a
It is load at node i in time interval [Ts i,j,Te i,j] in average active power；
The constraint condition of dynamic isolated island Partition Theory optimal models includes:
Power-balance constraint in isolated island:
Energy storage power constraint:
PDis,i>PBEi(t)>-PCh,iFormula (7)
Energy storage Constraint:
SOC(BE,t)>SOCminFormula (8)
Wherein, PRO () indicates the probability that event occurs in bracket, VkFor GkThe set of interior joint, GkIndicate k-th of isolated island,
Gk∈ΩCS(t), ΩcsIt (t) is the set of the isolated island in the system of t moment, PPViIt (t) is photovoltaic the having in t moment at node i
Function power, PBEi(t) active power for the energy storage at node i in t moment, PLiIt (t) is load the having in t moment at node i
Function power, ε are confidence level, PDis,iFor the upper limit of the power that energy storage at node i is discharged, PCh,iThe power to charge for energy storage at node i
The upper limit, SOC (BE, t) indicate remaining capacity of the energy storage in t moment, SOCminFor the remaining capacity lower limit of energy storage.
As preference, the step 4) is specifically included:
By time discretization, isolated island divide in all switches operation every t ' time carry out it is primary, by the t ' time zone
Interior system mode is considered as constant；Wherein, t ' value is 10-20min；Even if maximum during isolated island divides based on energy storage
Power discharge is not up to lower bound of capacity, ignores energy storage Constraint；Based on the frequent power failure for avoiding load, if load is being
It can only be at most powered during system failure primary；
The objective function expression formula of simplified model, such as formula (9) are as follows:
Wherein, TsFor the initial time of the system failure, TeFor the end time of the system failure, Ti sIt is node i in system event
The initial time being powered during barrier, Ti eFor the end time that node i is powered during the system failure,To be born at node i
Lotus is in time interval [Ts,Ti s] in average active power,It is load at node i in time interval [Ti e,Te] in be averaged
Active power；If node i is not powered during the system failure, T is seti s=Ti e=Ts, and
Constraint condition are as follows:
Wherein, t ∈ [Ts,Te]。
As preference, the step 5) is specifically included:
501) initial feasible solution is initialized, the control amount A expression formula of simplified model is optimized, as shown in formula (11):
A={ [T1 s,T1 e],[T2 s,T2 e]...[Ti s,Ti e]...[Tm s,Tm e] formula (11)
Wherein, [T1 s,T1 e] be node 1 control amount, [T2 s,T2 e] be node 2 control amount, [Ti s,Ti e] it is node i
Control amount, [Tm s,Tm e] be node m control amount, m is node total number, and i is the integer less than or equal to m；
Initial feasible solution is provided that for the node containing load, the control amount [T of the nodei s,Ti e] it is set as [Ts,
Ts]；For being free of the node of load, the control amount [T of the nodei s,Ti e] it is set as [Ts,Te]；
502) neighbours of present feasible solution are found: total power-on time than present feasible solution is had more into a time step
Control amount, the neighbours as present feasible solution；
The neighbours refer to: the time versus control A that is powered of one and only one node is increased in control amount B
One time step, and other node control variables are constant, then control amount B is the neighbours of control amount A；
503) neighbours for meeting constraint condition are filtered out in the neighbours of present feasible solution:
It will be converted into deterministic constraint condition containing probabilistic constraint condition first,
According to formula (2), formula (4) and probability theory, formula (12) are obtained:
Wherein, PPVi, expBy the desired value for the normal distribution that the photovoltaic power output at node i meets, value is at node i
Photovoltaic power output predicted value；PLi,expBy the desired value for the normal distribution that the load power at node i meets, value is section
The predicted value of load power at point i；σPVi(t) variance of the normal distribution met by the photovoltaic power output at node i, σLi(t)
By the variance for the normal distribution that the load power at node i meets；
Convolution (12), formula (10) are converted into formula (13):
PRO(Pk(t) > 0) > 1- ε formula (13)
Wherein,
According to the characteristic of normal distribution, if stochastic variable X meets normal distribution, i.e. X~N (x, σ1), for what is given
ε determines x1Value range, as shown in formula (14), to convert certainty about for the uncertain constraint in simplified model
Beam:
PRO(X>x1) > 1- ε formula (14)
504) stopping criterion: if step 503) does not find the neighbours for meeting constraint condition, terminate to search for, and will work as
Preceding feasible solution is as optimal solution；If step 503) finds the neighbours for meeting constraint condition, present feasible solution is updated to pair
Answer the smallest neighbours for meeting constraint condition of target function value, and return step 502)；
505) according to optimal solution, the isolated island for obtaining system in each period divides state
The utility model has the advantages that compared with prior art, the present invention having the advantage that existing distribution isolated island division is normally set up
Static load weight, does not account for influence of the power failure duration to weight, and method provided by the invention is taken using Custom interruption cost
It is more accurate to the estimation of the importance of user for static weight.Existing distribution isolated island division is normally set up static load function
Rate and distributed electrical source power, the system running state of discontinuity surface when can only embody one, method provided by the invention consider negative
The fluctuation of lotus and distributed generation resource in failure recovery time section, while considering the uncertain of load and distributed generation resource prediction
Property, more meet power distribution network actual operating state.Existing distribution isolated island division methods are usually that static isolated island divides, island state
Constant, method provided by the invention allows the dynamic change of island state, makes full use of the characteristic of each type load loss of outage, more
The efficiency for increasing to big degree distributed generation resource, promotes the economy of distribution operation.
Detailed description of the invention
Fig. 1 is the flow diagram of the embodiment of the present invention.
Fig. 2 is the system construction drawing used in present example.
Fig. 3 is all kinds of load fluctuation figures in present example.
Fig. 4 is the isolated island division result schematic diagram of present example.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with attached drawing and case study on implementation
The present invention is in depth described in detail.It should be appreciated that specific implementation case described herein is only used to explain this hair
It is bright, it is not used to limit invention.
As shown in Figure 1, a kind of dynamic isolated island division methods to reduce Custom interruption cost target of the embodiment of the present invention,
Include the following steps:
1) it is fitted all types of user loss of outage function；
2) uncertainty models of distributed generation resource and load are established；
3) it establishes with the dynamic isolated island Partition Theory optimal models of the minimum target of loss of outage；
4) dynamic isolated island Partition Theory optimal models are simplified, obtains simplified model；
5) simplified model is solved with climbing method, obtains dynamic isolated island division result.
In the above-described embodiments, preferably, in the step 1), all types of user loss of outage Function Fitting method is such as
Under:
The relationship of all types of user loss of outage and power failure duration is referred to using least square method according to statistical data
Number Function Fitting:
fIC,type(t)=10^ (αtype*ln(t)+βtype)/t formula (1)
Wherein, type is load type, type ∈ Ωtype, ΩtypeIt is the set of load type, fIC,typeIt is that type is
The customer interruption cost function of the load of type, t are power failure duration, αtypeIt is the first fitting parameter, βtypeIt is the second fitting ginseng
Number.
Preferably, distributed generation resource includes photovoltaic and energy storage in the step 2), wherein the power output randomness of photovoltaic
It is indicated with normal distribution, as shown in formula (2):
PPV~N (PPV,exp,σPV) formula (2)
Wherein, PPVFor practical photovoltaic power generating value, PPV, expFor the desired value of normal distribution, value is the prediction of photovoltaic power output
Value, σPVFor the standard deviation of normal distribution, N is normal distribution symbol；
The remaining capacity SOC of energy storage, as shown in formula (3):
Wherein, SOC (BE, t2) indicate energy storage in t2The remaining capacity at moment, SOC (BE, t1) indicate energy storage in t1Moment
Remaining capacity.PBEFor the power of energy storage, when energy storage electric discharge, PBEValue is negative；When energy storage charging, PBEValue is positive；η is
The efficiency of energy storage charge and discharge, CapBEFor the capacity of energy storage, t1For initial time, t2For end time；
The uncertainty of load is indicated with normal distribution, as shown in formula (4):
PL~N (PL,exp,σL) formula (4)
Wherein, PLFor actual load performance number, PL,expFor the desired value of normal distribution, value is the prediction power of load,
σLFor the standard deviation of normal distribution.
Preferably, being established optimal with the dynamic isolated island Partition Theory of the minimum target of loss of outage in the step 3)
The optimization aim expression formula of model, such as formula (5):
Wherein, V0For the node set of power supply interrupted district, NiFor the frequency of power cut of node i, Ts I, jHave a power failure for node i jth time
Start time, Te I, jFor the finish time that node i jth time has a power failure, PLiIt (t) is wattful power of the load at node i in t moment
Rate, itype are the user type of load at node i, fIC, itypeIt is the customer interruption cost function of the load at node i, Pi,j,a
It is load at node i in time interval [Ts I, j,Te i,j] in average active power；
The constraint condition of dynamic isolated island Partition Theory optimal models includes:
Power-balance constraint in isolated island:
Energy storage power constraint:
PDis,i>PBEi(t)>-PCh,iFormula (7)
Energy storage Constraint:
SOC(BE,t)>SOCminFormula (8)
Wherein, PRO () indicates the probability that event occurs in bracket, VkFor GkThe set of interior joint, GkIndicate k-th of isolated island,
Gk∈ΩCS(t), ΩcsIt (t) is the set of the isolated island in the system of t moment, PPViIt (t) is photovoltaic the having in t moment at node i
Function power, PBEi(t) active power for the energy storage at node i in t moment, PLiIt (t) is load the having in t moment at node i
Function power, ε are confidence level, PDis,iFor the upper limit of the power that energy storage at node i is discharged, PCh,iThe power to charge for energy storage at node i
The upper limit, SOC (BE, t) indicate remaining capacity of the energy storage in t moment, SOCminFor the remaining capacity lower limit of energy storage.
Preferably, the step 4) specifically includes:
By time discretization, isolated island divide in all switches operation every t ' time carry out it is primary, by the t ' time zone
Interior system mode is considered as constant；Wherein, t ' value is 10-20min；Even if maximum during isolated island divides based on energy storage
Power discharge is not up to lower bound of capacity, ignores energy storage Constraint；Based on the frequent power failure for avoiding load, if load is being
It can only be at most powered during system failure primary；
The objective function expression formula of simplified model, as shown in formula (9):
Wherein, TsFor the initial time of the system failure, TeFor the end time of the system failure, Ti sIt is node i in system event
The initial time being powered during barrier, Ti eFor the end time that node i is powered during the system failure,To be born at node i
Lotus is in time interval [Ts,Ti s] in average active power,It is load at node i in time interval [Ti e,Te] in be averaged
Active power；If node i is not powered during the system failure, T is seti s=Ti e=Ts, and
Constraint condition are as follows:
Wherein, t ∈ [Ts,Te]。
Preferably, the step 5) specifically includes:
501) initial feasible solution is initialized, the control amount A expression formula of simplified model is optimized, as shown in formula (11):
A={ [T1 s,T1 e],[T2 s,T2 e]...[Ti s,Ti e]...[Tm s,Tm e] formula (11)
Wherein, [T1 s,T1 e] be node 1 control amount, [T2 s,T2 e] be node 2 control amount, [Ti s,Ti e] it is node i
Control amount, [Tm s,Tm e] be node m control amount, m is node total number, and i is the integer less than or equal to m；
Initial feasible solution is provided that for the node containing load, the control amount [T of the nodei s,Ti e] it is set as [Ts,
Ts]；For being free of the node of load, the control amount [T of the nodei s,Ti e] it is set as [Ts,Te]；
502) neighbours of present feasible solution are found: total power-on time than present feasible solution is had more into a time step
Control amount, the neighbours as present feasible solution.
The neighbours refer to: the time versus control A that is powered of one and only one node is increased in control amount B
One time step, and other node control variables are constant, then control amount B is the neighbours of control amount A.According to this definition, control
It measures loss of outage corresponding to the neighbours of A and is centainly less than control amount A.
503) neighbours for meeting constraint condition are filtered out in the neighbours of present feasible solution:
It will be converted into deterministic constraint condition containing probabilistic constraint condition first,
According to formula (2), formula (4) and probability theory, formula (12) are obtained:
Wherein, PPVi,expBy the desired value for the normal distribution that the photovoltaic power output at node i meets, value is at node i
Photovoltaic power output predicted value；PLi, expBy the desired value for the normal distribution that the load power at node i meets, value is section
The predicted value of load power at point i；σPVi(t) variance of the normal distribution met by the photovoltaic power output at node i, σLi(t)
By the variance for the normal distribution that the load power at node i meets；
Convolution (12), formula (10) are converted into formula (13):
PRO(Pk(t) > 0) > 1- ε formula (13)
Wherein,
According to the characteristic of normal distribution, if stochastic variable X meets normal distribution, i.e. X~N (x, σ1), for what is given
ε determines x1Value range, as shown in formula (14), to convert certainty about for the uncertain constraint in simplified model
Beam:
PRO(X>x1) > 1- ε formula (14)
For example, when ε value is 0.05, x1Value range be (- ∞, x-1.65 σ1).By this conversion, can incite somebody to action
Uncertain constraint in simplified model is converted into certainty constraint.
For any given control amount, the island state of system at any time can be determined, each isolated island is carried out
The inspection of certainty constraint, if any time all meets the inspection, then it is assumed that be feasible solution.
504) stopping criterion: if step 503) does not find the neighbours for meeting constraint condition, terminate to search for, and will work as
Preceding feasible solution is as optimal solution；If step 503) finds the neighbours for meeting constraint condition, present feasible solution is updated to pair
Answer the smallest neighbours for meeting constraint condition of target function value, and return step 502)；
505) according to optimal solution, the isolated island for obtaining system in each period divides state.
The above method is by the analysis to Custom interruption cost data, when fitting each type load loss of outage about having a power failure
Long function, the foundation divided as isolated island.By establishing to distributed generation resource, load and the modeling of energy storage with the damage that has a power failure
The dynamic isolated island Partition Theory optimal models of minimum target are lost, and the model is simplified, simplified model is obtained, finally builds
It has found climbing method and has solved simplified model.The optimization in each node power supply section in distribution may be implemented in this method, realizes isolated island field
The dynamic transition of scape farthest reduces the total loss of outage of system using the difference of each type load loss of outage characteristic, is promoted
The economy of power distribution network operation.
An embodiment is enumerated below.
In the present embodiment, 4 system of RBTS Bus 6Feeder modified is chosen as distribution example, in original test
On the basis of system, photovoltaic and energy-storage system are accessed in node 24,25,26,27 respectively.Fault point is appeared in be connected with node 5
Feeder line at, after Fault Isolation, node 6-29 be power supply interrupted district, as shown in Figure 2.
In customer interruption cost function fitting, statistical data is as shown in table 1:
1 Custom interruption cost of table ($/kW)
Using least square method, exponential function fitting is carried out to the relationship of all types of Custom interruption costs and power failure duration:
fIC, type(t)=10^ (αtype*ln(t)+βtype)/t type∈Ωtype
Wherein, type is load type, fIC, typeIt is the customer interruption cost function for the load that type is type, t is to stop
Electric duration, αtypeAnd βtypeIt is fitting parameter, ΩtypeIt is the set of load type.
Fitting result is as shown in table 2:
2 loss of outage function parameter match value of table
Parameter setting is as follows:
Node 24,25,26,27 is respectively connected to photovoltaic and energy-storage system.Capacity is as shown in table 3.
Table 3
The load type and power of each node are as shown in table 4:
Table 4
The standard deviation of load and PV random distribution is set as the 10% of desired value.All kinds of load fluctuation curves are as shown in Figure 3.
Failure occurs on the feeder line being connected with node 5, first node 0, and the breaker between 1 disconnects automatically, secondly, node 5 and section
The circuit breaker closing that block switch between point 4,6 is disconnected with isolated fault, between final node 0,1 is got togather, and load 1-4 restores to supply
Electricity.Node 6-27 is in power failure, divides region for isolated island.Fault correction time is 5 hours.
Isolated island division result is as shown in table 5:
Table 5
For selection 08:00-08:15,09:00-09:15,10:00-10:15,11:00-11:15 and 12:00-12:15,
It is as shown in Figure 4 that isolated island divides state.
In the case where dividing without isolated island, changing all users in example is fault correction time, i.e., and 5 hours.It adopts
With above-mentioned customer interruption cost function, it is 88,811 ($) that total user loss of outage, which can be calculated,.
Using traditional static isolated island partitioning algorithm, (source is: J, Lin, X.Wang, " Two-stage method for
optimal island partition of distribution system with distributed
Generations, " IET Gener., Transmiss.Distrib., vol.6, no.3, pp.218-225, Mar.2012.) it is right
The example carries out isolated island division, and Custom interruption cost can be dropped to 54,697 ($), the range of decrease 38.41%.It is disclosed by the invention
Custom interruption cost can be dropped to 38899 ($), the range of decrease 56.20% from 88,811 ($) by dynamic isolated island division methods.This can
To find out, the method for the present invention can further decrease Custom interruption cost, promote the utilization efficiency of distributed generation resource, promote distribution
The economy of operation.
Claims (3)
1. a kind of dynamic isolated island division methods to reduce Custom interruption cost target, which is characterized in that this method includes as follows
Step:
1) it is fitted all types of user loss of outage function；
2) uncertainty models of distributed generation resource and load are established；
3) it establishes with the dynamic isolated island Partition Theory optimal models of the minimum target of loss of outage；In the step 3), establish with
The optimization aim expression formula of the dynamic isolated island Partition Theory optimal models of the minimum target of loss of outage, such as formula (5):
Wherein, V0For the node set of power supply interrupted district, NiFor the frequency of power cut of node i, Ts i,jThe beginning having a power failure for node i jth time
Moment, Te i,jFor the finish time that node i jth time has a power failure, PLiIt (t) is active power of the load at node i in t moment,
Itype is the user type of load at node i, fIC,itypeIt is the customer interruption cost function of the load at node i, Pi,j,aFor
Load is in time interval [T at node is i,j,Te i,j] in average active power；
The constraint condition of dynamic isolated island Partition Theory optimal models includes:
Power-balance constraint in isolated island:
Energy storage power constraint:
PDis,i>PBEi(t)>-PCh,iFormula (7)
Energy storage Constraint:
SOC(BE,t)>SOCminFormula (8)
Wherein, PRO () indicates the probability that event occurs in bracket, VkFor GkThe set of interior joint, GkIndicate k-th of isolated island, Gk∈
ΩCS(t), ΩcsIt (t) is the set of the isolated island in the system of t moment, PPViIt (t) is the photovoltaic at node i in the active of t moment
Power, PBEi(t) active power for the energy storage at node i in t moment, PLiIt (t) is the load at node i in the active of t moment
Power, ε are confidence level, PDis,iFor the upper limit of the power that energy storage at node i is discharged, PCh,iOn the power to charge for energy storage at node i
Limit, SOC (BE, t) indicate remaining capacity of the energy storage in t moment, SOCminFor the remaining capacity lower limit of energy storage；
4) dynamic isolated island Partition Theory optimal models are simplified, obtains simplified model；The step 4) specifically includes:
By time discretization, isolated island divide in all switches operation every t ' time carry out it is primary, will be in the t ' time interval
System mode be considered as it is constant；Wherein, t ' value is 10-20min；Even if based on energy storage isolated island divide during maximum power
Electric discharge, is not up to lower bound of capacity, ignores energy storage Constraint；Based on the frequent power failure for avoiding load, if load is in system event
It can only be at most powered during barrier primary；
The objective function expression formula of simplified model, such as formula (9) are as follows:
Wherein, TsFor the initial time of the system failure, TeFor the end time of the system failure,It is node i during the system failure
The initial time being powered, Ti eFor the end time that node i is powered during the system failure,For load at node i when
Between section [Ts,Ti s] in average active power,It is load at node i in time interval [Ti e,Te] in average wattful power
Rate；If node i is not powered during the system failure, T is seti s=Ti e=Ts, and
Constraint condition are as follows:
Wherein, t ∈ [Ts,Te]；
5) simplified model is solved with climbing method, obtains dynamic isolated island division result；The step 5) specifically includes:
501) initial feasible solution is initialized, the control amount A expression formula of simplified model is optimized, as shown in formula (11):
A={ [T1 s,T1 e],[T2 s,T2 e]...[Ti s,Ti e]...[Tm s,Tm e] formula (11)
Wherein, [T1 s,T1 e] be node 1 control amount, [T2 s,T2 e] be node 2 control amount, [Ti s,Ti e] be node i control
Amount, [Tm s,Tm e] be node m control amount, m is node total number, and i is the integer less than or equal to m；
Initial feasible solution is provided that for the node containing load, the control amount [T of the nodei s,Ti e] it is set as [Ts,Ts]；
For being free of the node of load, the control amount [T of the nodei s,Ti e] it is set as [Ts,Te]；
502) neighbours of present feasible solution are found: total power-on time than present feasible solution is had more to the control of a time step
Amount, the neighbours as present feasible solution；
The neighbours refer to: the time versus control A that is powered of one and only one node increases one in control amount B
Time step, and other node control variables are constant, then control amount B is the neighbours of control amount A；
503) neighbours for meeting constraint condition are filtered out in the neighbours of present feasible solution:
It will be converted into deterministic constraint condition containing probabilistic constraint condition first,
According to formula (2), formula (4) and probability theory, formula (12) are obtained:
PPV~N (PPV,exp,σPV) formula (2)
Wherein, PPVFor practical photovoltaic power generating value, PPV,expFor the desired value of normal distribution, value is the predicted value of photovoltaic power output, σPV
For the standard deviation of normal distribution, N is normal distribution symbol；
PL~N (PL,exp,σL) formula (4)
Wherein, PLFor actual load performance number, PL,expFor the desired value of normal distribution, value is the prediction power of load, σLIt is positive
The standard deviation of state distribution；
Wherein, PPVi,expBy the desired value for the normal distribution that the photovoltaic power output at node i meets, value is the photovoltaic at node i
The predicted value of power output；PLi,expBy the desired value for the normal distribution that the load power at node i meets, value is at node i
The predicted value of load power；σPVi(t) variance of the normal distribution met by the photovoltaic power output at node i, σLiIt (t) is node i
The variance for the normal distribution that the load power at place is met；
Convolution (12), formula (10) are converted into formula (13):
PRO(Pk(t) > 0) > 1- ε formula (13)
Wherein,
According to the characteristic of normal distribution, if stochastic variable X meets normal distribution, i.e. X~N (x, σ1), for given ε, determine
x1Value range, as shown in formula (14), to convert certainty constraint for the uncertain constraint in simplified model:
PRO(X>x1) > 1- ε formula (14)
504) stopping criterion: if step 503) does not find the neighbours for meeting constraint condition, terminate to search for, and will currently may be used
Row solution is used as optimal solution；If step 503) finds the neighbours for meeting constraint condition, present feasible solution is updated to corresponding mesh
The smallest neighbours for meeting constraint condition of offer of tender numerical value, and return step 502)；
505) according to optimal solution, the isolated island for obtaining system in each period divides state.
2. the dynamic isolated island division methods according to claim 1 to reduce Custom interruption cost target, which is characterized in that
In the step 1), all types of user loss of outage Function Fitting method is as follows:
According to statistical data, using least square method, index letter is carried out to the relationship of all types of user loss of outage and power failure duration
Number fitting:
fIC,type(t)=10^ (αtype*ln(t)+βtype)/t formula (1)
Wherein, type is load type, type ∈ Ωtype, ΩtypeIt is the set of load type, fIC,typeBe type be type
The customer interruption cost function of load, t are power failure duration, αtypeIt is the first fitting parameter, βtypeIt is the second fitting parameter.
3. the dynamic isolated island division methods according to claim 1 to reduce Custom interruption cost target, which is characterized in that
In the step 2), distributed generation resource includes photovoltaic and energy storage, wherein the power output randomness of photovoltaic indicates with normal distribution, such as
Shown in formula (2):
PPV~N (PPV,exp,σPV) formula (2)
Wherein, PPVFor practical photovoltaic power generating value, PPV,expFor the desired value of normal distribution, value is the predicted value of photovoltaic power output, σPV
For the standard deviation of normal distribution, N is normal distribution symbol；
The remaining capacity SOC of energy storage, as shown in formula (3):
Wherein, SOC (BE, t2) indicate energy storage in t2The remaining capacity at moment, SOC (BE, t1) indicate energy storage in t1The residue at moment
Electricity；PBEFor the power of energy storage, when energy storage electric discharge, PBEValue is negative；When energy storage charging, PBEValue is positive；η is energy storage
The efficiency of charge and discharge, CapBEFor the capacity of energy storage, t1For initial time, t2For end time；
The uncertainty of load is indicated with normal distribution, as shown in formula (4):
PL~N (PL,exp,σL) formula (4)
Wherein, PLFor actual load performance number, PL,expFor the desired value of normal distribution, value is the prediction power of load, σLIt is positive
The standard deviation of state distribution.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610838309.7A CN106340899B (en) | 2016-09-21 | 2016-09-21 | A kind of dynamic isolated island division methods to reduce Custom interruption cost target |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610838309.7A CN106340899B (en) | 2016-09-21 | 2016-09-21 | A kind of dynamic isolated island division methods to reduce Custom interruption cost target |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106340899A CN106340899A (en) | 2017-01-18 |
| CN106340899B true CN106340899B (en) | 2018-12-28 |
Family
ID=57840199
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610838309.7A Active CN106340899B (en) | 2016-09-21 | 2016-09-21 | A kind of dynamic isolated island division methods to reduce Custom interruption cost target |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106340899B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107069801B (en) * | 2017-03-13 | 2019-09-24 | 中国电力科学研究院有限公司 | A kind of power distribution network isolated island division methods based on minimum Custom interruption cost |
| CN112510750B (en) * | 2020-10-19 | 2023-06-02 | 许继集团有限公司 | Island division method and device for power distribution network after fault under high-permeability distributed power supply |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103812131A (en) * | 2013-10-29 | 2014-05-21 | 国网辽宁省电力有限公司沈阳供电公司 | Multi-agent-based urban power grid isolated island black-start system and method |
| CN104881723A (en) * | 2015-06-12 | 2015-09-02 | 国网内蒙古东部电力有限公司通辽供电公司 | Source-included power distribution network fault power failure scheme optimization method considering influence of equivalent load points |
-
2016
- 2016-09-21 CN CN201610838309.7A patent/CN106340899B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103812131A (en) * | 2013-10-29 | 2014-05-21 | 国网辽宁省电力有限公司沈阳供电公司 | Multi-agent-based urban power grid isolated island black-start system and method |
| CN104881723A (en) * | 2015-06-12 | 2015-09-02 | 国网内蒙古东部电力有限公司通辽供电公司 | Source-included power distribution network fault power failure scheme optimization method considering influence of equivalent load points |
Non-Patent Citations (3)
| Title |
|---|
| Island Partition of the Distribution System With Distributed Generation Based on Improved Dynamic Programming;Cheng Long ZHANG 等;《2014 China International Conference on Electricity Distribution (CICED 2014)》;20140926;1734-1738 * |
| 含分布式电源的配电网动态孤岛划分博弈模型;王晶 等;《电力系统保护与控制》;20160716;第44卷(第14期);14-24 * |
| 计及分布式电源出力和负荷不确定性的配电网孤岛划分;李飞 等;《电力系统自动化》;20150725;第39卷(第14期);105-113,132 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106340899A (en) | 2017-01-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Liu et al. | Decentralized multi-agent system-based cooperative frequency control for autonomous microgrids with communication constraints | |
| CN106026092B (en) | It is a kind of for the power distribution network isolated island division methods containing distributed generation resource | |
| JP2022500998A (en) | Systems, methods, and computer program products that make up the microgrid | |
| Peng et al. | Grid-friendly power control for smart photovoltaic systems | |
| Diaz et al. | Fuzzy-logic-based gain-scheduling control for state-of-charge balance of distributed energy storage systems for DC microgrids | |
| CN105552860B (en) | A kind of power distribution network islet operation division methods based on energy storage and distributed generation resource | |
| CN107944757A (en) | Electric power interacted system regenerative resource digestion capability analysis and assessment method | |
| CN110783963B (en) | Power system optimal scheduling method and device, computer equipment and storage medium | |
| CN112381375B (en) | Rapid generation method for power grid economic operation domain based on tide distribution matrix | |
| CN103971299A (en) | Power distribution network islanding method based on harmonic algorithm | |
| AU2016368519B2 (en) | Method for providing an energy reserve for an energy supply system | |
| CN109919398A (en) | The zonal reserve Optimal Configuration Method of electric system containing wind-powered electricity generation based on figure partitioning algorithm | |
| Bruno et al. | Predictive dispatch across time of hybrid isolated power systems | |
| Azeroual et al. | Intelligent energy management system of a smart microgrid using multiagent systems | |
| CN106340899B (en) | A kind of dynamic isolated island division methods to reduce Custom interruption cost target | |
| Zhang et al. | Service restoration based on dynamic programming | |
| CN109901389A (en) | A kind of new energy consumption method based on deep learning | |
| Zhi-jian et al. | Reliability assessment of distribution network considering the randomness of distributed generation | |
| CN108985561A (en) | A kind of active power distribution network isolated island division methods based on chance constraint | |
| KR20120012992A (en) | Method of controlling a network computing cluster providing it-services | |
| Prathyush et al. | Fuzzy logic based energy management system design for AC microgrid | |
| CN106505637B (en) | A kind of optimization method of the conservative degree of electric system active power dispatch | |
| Fikari et al. | Modeling and simulation of an autonomous hybrid power system | |
| Zhou et al. | Power failure risk assessment and management based on stochastic line failures in distribution network including distributed generation | |
| Elgamal et al. | An adaptive multiagent control system for autonomous economic operation and resilience assurance in a hybrid-energy islanded microgrid |
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 |