CN110148936A - The coordinated planning method of flexible multimode switch and distributed generation resource in active power distribution network - Google Patents
The coordinated planning method of flexible multimode switch and distributed generation resource in active power distribution network Download PDFInfo
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- CN110148936A CN110148936A CN201910435816.XA CN201910435816A CN110148936A CN 110148936 A CN110148936 A CN 110148936A CN 201910435816 A CN201910435816 A CN 201910435816A CN 110148936 A CN110148936 A CN 110148936A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/04—Circuit arrangements for ac mains or ac distribution networks for connecting networks of the same frequency but supplied from different sources
- H02J3/06—Controlling transfer of power between connected networks; Controlling sharing of load between connected networks
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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- 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
- H02J2310/00—The network for supplying or distributing electric power characterised by its spatial reach or by the load
- H02J2310/50—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads
- H02J2310/56—The network for supplying or distributing electric power characterised by its spatial reach or by the load for selectively controlling the operation of the loads characterised by the condition upon which the selective controlling is based
- H02J2310/62—The condition being non-electrical, e.g. temperature
- H02J2310/64—The condition being economic, e.g. tariff based load management
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Abstract
The invention discloses a kind of coordinated planning method of multimode switch and distributed generation resource flexible in active power distribution network, step includes: 1 foundation flexibility multimode switch equivalent model；2 establish the power distribution network optimal load flow computation model switched based on flexible multimode；3 establish in active power distribution network flexible multimode switch and distributed generation resource combine addressing constant volume model；4 use improved Genetic Particle Swarm hybrid optimization algorithm, solve to flexible multimode switch with the addressing constant volume model of combining of distributed generation resource access power distribution network.Position and the capacity of the flexible multimode switch of planning and distributed generation resource access power distribution network that the present invention can be scientific and reasonable, and the grid-connected bring adverse effect of distributed generation resource is reduced with the tide optimization ability of flexible multimode switch, it reduces active power distribution network via net loss, improve voltage level, improve the operation potentiality of active power distribution network.
Description
Technical field
The present invention relates to distribution network planning technical field, flexible multimode switchs and divides in especially a kind of active power distribution network
The coordinated planning method of cloth power supply.
Background technique
The grid-connected trend distribution changed in system of renewable distributed generation resource at high proportion, to the planning and operation of power distribution network
Tremendous influence is brought, influence degree is related with distributed generation resource installation site and capacity configuration.With distributed generation resource
Permeability is gradually increased, and traditional distributed generation resource planning has shown obvious deficiency, and flexible multimode switch is
Solve the problems, such as that this brings opportunity.The function of flexible multimode switch is realized based on all-controlling power electronics device, phase
Switching state only than ordinary tap, flexible multimode switch also add the continuous controllable state of power, can accuracy controlling institute
The even active power and reactive power at feeder line end, can efficiently solve distributed generation resource " bi-directional current " and rush to power distribution network
It hits.But a kind of concrete measure switchs flexible multimode not yet and the capacity of distributed generation resource and position carry out coordination rule
It draws.
Domestic and foreign scholars are broadly divided into two classes to the research of electric power system optimization algorithm: mathematic programming methods and heuristic searching
Rope algorithm.The latter mainly has particle swarm algorithm and genetic algorithm.Particle swarm algorithm is by simulating biotic population characteristic, by data
Random initializtion forms primary particle group, is updated using fundamental formular to the speed of population and position, to obtain most
Whole optimal solution.Particle swarm algorithm thought is simple, fast convergence rate, but is easily trapped into local optimum and precocity occur.Heredity
Algorithm is that the process by simulating biological heredity and evolution keeps its heavy by being selected chromosome, being intersected and mutation operation
Combination nova, to obtain final optimal solution.Population in Genetic Algorithms multiplicity is suitable for global search, but individual is not remembered, and loses
It is blindly directionless to pass operation, required convergence time is long.Therefore for active power distribution network flexibility multimode switch and distribution
Power supply coordinated planning problem needs sufficiently to realize have complementary advantages to two kinds of algorithms, on the basis of existing heuristic search algorithm
It improves.
Summary of the invention
The present invention is to overcome above-mentioned the shortcomings of the prior art, provides flexible more shapes in a kind of active power distribution network
The coordinated planning method of state switch and distributed generation resource, to planning flexibility multimode switch and distributed electrical that can be scientific and reasonable
Position and the capacity of power distribution network are accessed in source, and grid-connected with the tide optimization ability reduction distributed generation resource of flexible multimode switch
Bring adverse effect reduces grid loss, improves distribution network voltage level, to improve the operation potentiality of power distribution network.
In order to achieve the above object, the technical scheme adopted by the invention is as follows:
In a kind of active power distribution network of the present invention the characteristics of coordinated planning method of flexible multimode switch and distributed generation resource
It is, includes the following steps:
Step 1: establishing flexible multimode switchs equivalent model；
At M power supply and M branch and active power distribution network is connected to for the flexible multimode switch with M port is equivalent
In, and impedance is introduced in every branch, to the capacity for the capacity branch that flexible multimode switchs be indicated, by flexible more shapes
The loss of state switch is with branch loss come approximate substitution；
Step 2: establishing the active power distribution network optimal load flow computation model switched based on flexible multimode；
Equivalent model is switched based on flexible multimode, most with multi-period active power distribution network variation minimum and via net loss
Small is objective function, and all kinds of constraint conditions are arranged, to establish the active power distribution network optimal load flow switched containing flexible multimode
Computation model；
Step 3: that establishes in active power distribution network flexible multimode switch and distributed generation resource combines addressing constant volume model；
Power grid operator Income Maximum and the minimum objective function of power distribution company overall cost in a distributed manner, and be arranged all kinds of
Constraint condition, so that establishes in active power distribution network flexible multimode switch and distributed generation resource combines addressing constant volume model；
Step 4: using improved Genetic Particle Swarm hybrid optimization algorithm, to flexible multimode switch and distributed generation resource
Joint addressing constant volume model solved, connection of the obtained population optimal solution as flexible multimode switch and distributed generation resource
Close addressing constant volume scheme.
The characteristics of active power distribution network flexibility multimode switch of the present invention is with distributed generation resource coordinated planning method
It is, the step 1 is to carry out according to the following procedure:
Step 1.1 establishes flexible multimode switch equivalent model using formula (1):
In formula (1), RmIt is the equivalent equivalent resistance in flexible m-th of port of multimode switch；Imax,mIt is that flexible multimode is opened
Close the equivalent maximum branch current in m-th of port；Af,mFor m-th of port loss coefficient of flexible multimode switch；
Step 1.2, the active balance constraint for establishing flexible multimode switch operation control respectively using formula (2)-formula (5),
Reactive balance constraint and capacity-constrained:
-μSFMSS,m≤Qf,m≤μSFMSS,m (4)
Sf,m≤SFMSS,m (5)
In formula (2)-formula (5), M is the port number of flexible multimode switch；Pf,mFor m-th of end of flexible multimode switch
Port transmission active power；Ploss,mFor the active loss of m-th of port of flexible multimode switch；ImIt is flexible multimode switch
The equivalent branch current in the port m；RmIt is the equivalent equivalent resistance in the port m of flexible multimode switch；μ is power factor
The absolute value of angle sine；Qf,mFor the reactive power of m-th of port output of flexible multimode switch；SFMSS,mFor flexible multimode
M-th of port current transformer access capacity of switch；Sf,mIt is for the apparent energy of m-th of port of flexible multimode switch, i.e., flexible
The transimission power of m-th of port of multimode switch, m=1,2 ..., M.
The step 2 is to carry out according to the following procedure:
Step 2.1 determines objective function F using linear weight sum method shown in formula (6)L:
FL=min (α1Q+α2T) (6)
In formula (6), α1For variation weight, α in active power distribution network2For via net loss weight in active power distribution network, and 0
≤α1≤ 1,0≤α2≤ 1, α1+α2=1；Q is variation function, and is characterized by formula (7), and T is via net loss function, and by
Formula (8) is characterized:
In formula (7), NnFor active power distribution network node total number；UiIt (t) is the voltage magnitude of t period node i；Umax,iFor node
I voltage magnitude upper limit value；Umin,iFor node i voltage magnitude lower limit value；" | | " indicate "or"；
Step 2.2 establishes distribution system trend constraint using formula (9):
In formula (9), Pi(t)、QiIt (t) is respectively the active power and reactive power injected in t period node i；φiFor with
The set of node i connected node；Ui(t)、UjIt (t) is respectively the voltage magnitude of t period node i, j；θijIt (t) is t period node
I, the phase difference of voltage of j；Gij、BijTransconductance and mutual susceptance respectively in node admittance matrix, and have:
In formula (10), PDG,i(t)、QDG,i(t) be respectively in t period node i distributed generation resource inject active power and nothing
Function power；Pf,i(t)、Qf,i(t) be respectively flexible multimode switch injection in t period node i active power and reactive power；
PLD,i(t)、QLD,i(t) be respectively load in t period node i active power and reactive power；
Step 2.3 establishes power distribution system secure operation constraint using formula (11) and formula (12):
Umin,i≤Ui(t)≤Umax,i (11)
Iij(t)2≤(Imax,ij)2 (12)
In formula (12): Iij(t) current amplitude of node j, I are flowed to for t period node imax,ijFlow to node j's for node i
The current amplitude upper limit.
The step 3 is to carry out according to the following procedure:
Step 3.1 establishes objective function F using formula (13)M:
FM=EP+EO (13)
In formula (13), EPFor distributed generation resource operator annual earnings, and obtained by formula (14), EOIt is comprehensive for power distribution company year
Cost, and obtained by formula (15):
In formula (14), max, which is represented, to be maximized；T is the total period that optimization calculates；NDGFor the distributed generation resource installed
Quantity；CsFor government subsidy electricity price；CeFor wind-powered electricity generation rate for incorporation into the power network；CopFor operation and maintenance cost；For kth class distributed generation resource
In the generated energy of t period；σ is distributed generation resource year value operator；Cdg,kFor the unit capacity capital cost of kth class distributed generation resource
With；PDG,kFor the installed capacity of kth class distributed generation resource；
EO=min (EG+ELOSS+EFMSS) (15)
In formula (15), min, which is represented, to be minimized；EGFor conventional electric power generation cost；ELOSSIt include line power for power transmission and distribution cost
The active loss cost of cost depletions and flexible multimode switch, is obtained, E by formula (16)FMSSIt switchs and installs for flexible multimode
And operation and maintenance cost, and obtained by formula (17):
In formula (16), ClossFor network loss electricity price；NbFor number of branches in active power distribution network；IL(t) electricity for being t period branch L
Flow valuve；RlFor the resistance of branch L；Ploss,mIt (t) is the active loss of m-th of port of t period flexibility multimode switch；
In formula (17), ε is mounting cost year value operator；γ is year operation and maintenance cost coefficient；NFMSSFor flexible more shapes
State switchs number to be installed；SFMSS,kFor the capacity of k-th of installation flexible multimode switch；CFMSS,kIt is flexible for k-th of installation
The unit capacity cost of investment of multimode switch；
Step 3.2, the distributed generation resource power output for establishing flexible multimode switch operation respectively using formula (18)-formula (20)
Constraint:
0≤PDG,i≤PDG,i,max (18)
PDG,i=λiPrated,i (19)
In formula (18)-formula (20), PDG,iFor the power output of distributed generation resource at node i；PDG,i,maxTo allow to pacify at node i
The distributed generation resource maximum size of dress；Prated,iFor the unit rated capacity of distributed generation resource at node i；λiTo be installed at node i
The number of distributed generation resource；PLDFor burden with power total in active power distribution network；η be active power distribution network allow distributed generation resource most
Big permeability.
The improved Genetic Particle Swarm hybrid optimization algorithm of step 4 is to carry out as follows:
Step 4.1, initialization maximum number of iterations Nmax, population quantity Z, chromosomal gene length D join in genetic algorithm
Number self study rate R1, social learning lead R2With from aberration rate R3；
Step 4.2 carries out hybrid coding to flexible multimode contact capacity, position and distributed generation resource capacity, position, and
The initial random population for generating Z chromosome；
Any pth chromosome is enabled to be denoted as zp, p belongs to [1, Z]；
Q is enabled to indicate pth chromosome zpUpper any one gene serial number, q belong to [1, D]；
Mbest_p is enabled to indicate pth chromosome zpHistory optimal solution, corresponding fitness function value be fbest_p；
Initialize fbest_p=0；
Enabling current iteration number is e；
Enabling Mbest_e is the population optimal solution in e generation, and e belongs to [1, Nmax], corresponding fitness function value is
Fbset_e initializes Fbset_e=0；
Enabling population optimal solution is Mbest, and corresponding fitness function value is Fbset, initializes Fbset=0；
Initialize e=1, p=1；
Step 4.3 judges whether to meet p > Z, if satisfied, thening follow the steps 4.4；Otherwise, step 4.5- step is executed
4.8；
Step 4.4, Population Regeneration optimal solution Mbest:
If meeting Fbest_e > Fbset, Fbset_e is assigned to Fbset, Mbest_e is assigned to Mbest；If no
Meet, then keeps Fbset and Mbest constant；To obtain after updating later population optimal solution Mbest, executed after enabling p=1
Step 4.9；
Step 4.5, to pth chromosome zpCarry out the power distribution network optimal load flow that equivalent model is switched based on flexible multimode
It calculates, obtains pth chromosome zpFitness function value fp；
Step 4.6, according to pth chromosome zpFitness function value fpUpdate the history optimal solution of pth chromosome
Mbest_p:
If meeting fp> fbest_p, then by fpIt is assigned to fbest_p, by zpIt is assigned to mbest_p；If not satisfied, then keeping
Fbest_p and mbest_p are constant；To obtain updating later history optimal solution mbest_p；
Step 4.7, according to pth chromosome zpFitness function value fpUpdate the optimal solution Mbest_e of contemporary population e:
If meeting fp> Fbset_e, then by fpIt is assigned to Fbest_e, by zpIt is assigned to Mbest_e；If not satisfied, then keeping
Fbest_e and Mbest_e are constant；To obtain updating later optimal solution Mbest_e；
Step 4.8 after enabling p+1 be assigned to p, executes step 4.3；
Step 4.9 judges whether to meet p > Z, if satisfied, going to step 4.11；Otherwise, q=1 is enabled, step 4.10 is executed；
Step 4.10 judges whether to meet q > D, if satisfied, p+1 is then assigned to p, executes step 4.9；Otherwise, to pth
Chromosome zpIt carries out self study, social learning and from after mutation operation, after q+1 is assigned to q, executes step 4.10；
The self study, social learning and the behaviour that makes a variation certainly include:
A) q-th of random number r is generatedq1If meeting rq1<R1, then pth chromosome zpQ genes itself history
The q genes of optimal solution mbset_p are replaced；Otherwise, it does not replace；
B) q-th of random number r is generatedq2If meeting rq2<R2, pth chromosome zpQ gene population optimal solutions
The q genes of Mbest are replaced；Otherwise, it does not replace；
C) q-th of random number r is generatedq3If meeting rq3<R3, q genes progress random mutations of chromosome；Otherwise, it does not dash forward
Become；
Step 4.11 judges whether to meet e > Nmax, if satisfied, executing step 4.12；Otherwise, it enables and e+1 is assigned to e simultaneously
Go to step 4.3；
Step 4.12, output population optimum dyeing body Mbest are population optimal solution.
Compared with the prior art, the beneficial effects of the present invention are embodied in:
1 present invention is for the grid-connected bring adverse effect of high proportion distributed generation resource, the planning of analysis conventional distributed generation resource
Deficiency, introduce flexible multimode switch, and establish the equivalent model of flexible multimode switch, it is soft in considering active power distribution network
Property multimode switch with distributed generation resource coordinated planning while, optimize distribution power flow in real time；Active power distribution network is planned
It is combined with running optimizatin, while ensure that the operation of power distribution network economic security, improves the operation potentiality of power distribution network；
The equivalent model of flexible multimode that 2 present invention establish switch, by flexible multimode contact capacity it is non-linear about
Beam is mutually unified with the nonlinear restriction in active power distribution network Load flow calculation, resolves tool Unified Solution using existing trend, makes
The model parameter for obtaining flexible multimode switch is consistent with the network parameter of power distribution network, is distributed to adjust the trend of power distribution network, thus
The power quality for improving power distribution network is provided convenience；
The limitation of 3 analysis conventional control measures of the present invention, from active power distribution network integral layout, according to power distribution network
Practical operation situation, position and capacity of the coordinated planning flexibility multimode switch with distributed generation resource access active power distribution network, mentions
High distribution network planning design level；
4 present invention open on the basis of flexible multimode switch and distributed generation resource coordinated planning from steady-state operation regulation
Exhibition research, all carries out when planning each time with active the matching of multi-period systematic offset voltage minimum and the minimum target of via net loss
Electric network swim optimization, strictly ensures the economy and safety of power distribution network operation；
5 present invention are switched using improved Genetic Particle Swarm hybrid optimization algorithm to flexible multimode and distributed generation resource association
It adjusts plan model to be solved, has used for reference particle swarm algorithm, make chromosome that there is " memory function ", and in operatings of genetic algorithm
" learning rate " and " aberration rate " the two concepts are introduced in the process, can rapidly and accurately solve flexible multimode switch and are divided
The optimal case of cloth plant-grid connection active power distribution network.
Detailed description of the invention
Fig. 1 is the flexible multimode switch access power distribution network schematic diagram of the present invention；
Fig. 2 is the flexible multimode two kinds of damage curve figures of switch of the present invention；
Fig. 3 is the improved Genetic Particle Swarm hybrid optimization algorithm flow diagram of the present invention.
Specific embodiment
In the present embodiment, as shown in Figure 1, flexible active power distribution network of the multimode switch access containing distributed generation resource；It is a kind of
The coordinated planning method of flexible multimode switch and distributed generation resource is to carry out as follows in active power distribution network:
Step 1: establishing flexible multimode switchs equivalent model:
At M power supply and M branch and active power distribution network is connected to for the flexible multimode switch with M port is equivalent
In, and impedance is introduced in every branch, to the capacity for the capacity branch that flexible multimode switchs be indicated, by flexible more shapes
The loss of state switch is with branch loss come approximate substitution；Since flexible multimode switch only has active loss, therefore do not consider branch
Reactance, branch resistance are determined by formula (1).
In the flexible multimode switch equivalent model established, M power supply embodies the electric energy tune of flexible multimode switch
Degree effect, the nonlinear restriction and loss of the equivalent flexible multimode contact capacity of M branch, introduces impedance and carrys out approximate description flexibility
The loss of multimode switch, one group of equality constraint embody the conservation of energy in flexible multimode switch energy scheduling.
Flexible multimode, which is established, using formula (1) switchs equivalent model:
In formula (1), RmIt is the equivalent equivalent resistance in flexible m-th of port of multimode switch；Imax,mIt is that flexible multimode is opened
Close the equivalent maximum branch current in m-th of port；Af,mFor m-th of port loss coefficient of flexible multimode switch；
Establish active balance constraint, the reactive balance of flexible multimode switch operation control respectively using formula (2)-formula (5)
Constraint and capacity-constrained:
-μSFMSS,m≤Qf,m≤μSFMSS,m (4)
Sf,m≤SFMSS,m (5)
In formula (2)-formula (5), M is the port number of flexible multimode switch；Pf,mFor m-th of end of flexible multimode switch
Port transmission active power；Ploss,mFor the active loss of m-th of port of flexible multimode switch；ImIt is flexible multimode switch
The equivalent branch current in the port m；RmIt is the equivalent equivalent resistance in the port m of flexible multimode switch；μ is power factor
The absolute value of angle sine；Qf,mFor the reactive power of m-th of port output of flexible multimode switch；SFMSS,mFor flexible multimode
M-th of port current transformer access capacity of switch；Sf,mIt is for the apparent energy of m-th of port of flexible multimode switch, i.e., flexible
The transimission power of m-th of port of multimode switch, m=1,2 ..., M；
It is to be derived to the formula for the flexible multimode switch equivalent model established below:
Assuming that flexible multimode switching loss is directly proportional to self transmission power, such as formula (6):
In formula, Af,mFor m-th of port loss coefficient of flexible multimode switch；
The end M flexibility multimode is switched and is added in network as the new branch of M item, it is public according to the capacity of branch and loss
Formula, the capacity and branch loss for obtaining flexible multimode switch can be indicated by formula (7), formula (8) respectively:
Sf,m=UmIm (7)
In formula (7), UmIt is the equivalent branch voltage in the port flexible multimode switch m；
Assuming that the voltage of a branch road is constant, and amplitude Um≈ 1pu can be obtained by formula (6), formula (7):
Ploss,m=Af,m·Im (9)
Fig. 2 is formula (8), the damage curve figure of the corresponding flexible multimode two kinds of forms of switch of formula (9), and the following are test
It is equal for demonstrate,proving loss of two kinds of flexible multimode switching loss models on probability meaning.
Assuming that transimission power S of the flexible multimode switch in t momentf,mIn 0~Smax,mIt is evenly distributed in range, Smax,m
Indicate the maximum transmission power of m-th of port of flexible multimode switch, i.e. Sf,mIn 0~Imax,mObedience is uniformly distributed.ByIt can obtainFor fixed value.
Formula (8), formula (9) simultaneously integrate I, calculate its probability and are lost and enable the two probability loss equal:
Formula (10) are solved and are obtained:
That is equivalent resistance RmIt takesWhen, formula (6), formula (9) they are equivalent on probability meaning.
Step 2: establishing the active power distribution network optimal load flow computation model switched based on flexible multimode；
Equivalent model is switched based on flexible multimode, most with multi-period active power distribution network variation minimum and via net loss
Small is objective function, and all kinds of constraint conditions are arranged, to establish the active power distribution network optimal load flow switched containing flexible multimode
Computation model；
Step 2.1, the objective function F determined using linear weight sum method shown in formula (12)L:
FL=min (α1Q+α2T) (12)
In formula (12), α1For variation weight, α in active power distribution network2For via net loss weight in active power distribution network, and 0
≤α1≤ 1,0≤α2≤ 1, α1+α2=1；Q is variation function, and is characterized by formula (13), and T is via net loss function, and
It is characterized by formula (14):
In formula (13), NnFor active power distribution network node total number；UiIt (t) is the voltage magnitude of t period node i；Umax,iFor section
Point i voltage magnitude upper limit value；Umin,iFor node i voltage magnitude lower limit value；" | | " indicate "or"；
Formula (13) is indicated when node voltage is beyond optimization section [Umin,i,Umax,i] when, it is switched by flexible multimode to nothing
The control of function reduces variation optimization section degree, so as to improve voltage's distribiuting situation.
Step 2.2 establishes distribution system trend constraint using formula (15):
In formula (15), Pi(t)、QiIt (t) is respectively the active power and reactive power injected in t period node i；φiFor with
The set of node i connected node；Ui(t)、UjIt (t) is respectively the voltage magnitude of t period node i, j；θijIt (t) is t period node
I, the phase difference of voltage of j；Gij、BijTransconductance and mutual susceptance respectively in node admittance matrix, and have:
In formula (16), PDG,i(t)、QDG,i(t) be respectively in t period node i distributed generation resource inject active power and nothing
Function power；Pf,i(t)、Qf,i(t) be respectively flexible multimode switch injection in t period node i active power and reactive power；
PLD,i(t)、QLD,i(t) be respectively load in t period node i active power and reactive power；
Step 2.3 establishes power distribution system secure operation constraint using formula (17) and formula (18):
Umin,i≤Ui(t)≤Umax,i (17)
Iij(t)2≤(Imax,ij)2 (18)
In formula (18): Iij(t) current amplitude of node j, I are flowed to for t period node imax,ijFlow to node j's for node i
The current amplitude upper limit；
Step 3: that establishes in active power distribution network flexible multimode switch and distributed generation resource combines addressing constant volume model；
From economy point, power grid operator Income Maximum and the minimum mesh of power distribution company overall cost in a distributed manner
Scalar functions, and all kinds of constraint conditions are set, to establish the connection of flexible multimode switch and distributed generation resource in active power distribution network
Close addressing constant volume model；Wherein, distributed generation resource mainly considers blower unit and photovoltaic plant.
Step 3.1 establishes objective function F using formula (19)M:
FM=EP+EO (19)
In formula (19), EPFor distributed generation resource operator annual earnings, and obtained by formula (20), EOIt is comprehensive for power distribution company year
Cost, and obtained by formula (21):
In formula (20), max, which is represented, to be maximized；T is the total period that optimization calculates；NDGFor the distributed generation resource installed
Quantity；CsFor government subsidy electricity price；CeFor wind-powered electricity generation rate for incorporation into the power network；CopFor operation and maintenance cost；For kth class distributed generation resource
In the generated energy of t period；σ is distributed generation resource year value operator；Cdg,kFor the unit capacity capital cost of kth class distributed generation resource
With；PDG,kFor the installed capacity of kth class distributed generation resource；
EO=min (EG+ELOSS+EFMSS) (21)
In formula (21), min, which is represented, to be minimized；EGFor conventional electric power generation cost；ELOSSIt include line power for power transmission and distribution cost
The active loss cost of cost depletions and flexible multimode switch, is obtained, E by formula (22)FMSSIt switchs and installs for flexible multimode
And operation and maintenance cost, and obtained by formula (23):
In formula (22), ClossFor network loss electricity price；NbFor number of branches in active power distribution network；IL(t) electricity for being t period branch L
Flow valuve；RlFor the resistance of branch L；Ploss,mIt (t) is the active loss of m-th of port of t period flexibility multimode switch；
In formula (23), ε is mounting cost year value operator；γ is year operation and maintenance cost coefficient；NFMSSFor flexible more shapes
State switchs number to be installed；SFMSS,kFor the capacity of k-th of installation flexible multimode switch；CFMSS,kIt is flexible for k-th of installation
The unit capacity cost of investment of multimode switch；
Step 3.2, the distributed generation resource power output for establishing flexible multimode switch operation respectively using formula (24)-formula (26)
Constraint:
0≤PDG,i≤PDG,i,max (24)
PDG,i=λiPrated,i (25)
In formula (24)-formula (26), PDG,iFor the power output of distributed generation resource at node i；PDG,i,maxTo allow to pacify at node i
The distributed generation resource maximum size of dress；Prated,iFor the unit rated capacity of distributed generation resource at node i；λiTo be installed at node i
The number of distributed generation resource；PLDFor burden with power total in active power distribution network；η be active power distribution network allow distributed generation resource most
Big permeability；
Step 4: using improved Genetic Particle Swarm hybrid optimization algorithm, to flexible multimode switch and distributed generation resource
Joint addressing constant volume model solved, connection of the obtained population optimal solution as flexible multimode switch and distributed generation resource
Close addressing constant volume scheme；The flow diagram of improved Genetic Particle Swarm hybrid optimization algorithm as shown in figure 3, specific steps such as
Under:
Step 4.1, initialization maximum number of iterations Nmax, population quantity Z, chromosomal gene length D join in genetic algorithm
Number self study rate R1, social learning lead R2With from aberration rate R3；
Step 4.2 carries out hybrid coding to flexible multimode contact capacity, position and distributed generation resource capacity, position, obtains
To code set Cb, in CbIn it is initial random generate Z chromosome coded sequence, obtain blending heredity particle swarm algorithm just
For population；
Any pth chromosome is enabled to be denoted as zp, p belongs to [1, Z]；
Q is enabled to indicate pth chromosome zpUpper any one gene serial number, q belong to [1, D]；
Mbest_p is enabled to indicate pth chromosome zpHistory optimal solution, corresponding fitness function value be fbest_p；
Initialize fbest_p=0；
Enabling current iteration number is e；
Enabling Mbest_e is the population optimal solution in e generation, and e belongs to [1, Nmax], corresponding fitness function value is
Fbset_e initializes Fbset_e=0；
Enabling population optimal solution is Mbest, and corresponding fitness function value is Fbset, initializes Fbset=0；
Initialize e=1, p=1；
Step 4.3 judges whether to meet p > Z, if satisfied, thening follow the steps 4.4；Otherwise, step 4.5- step is executed
4.8；
Step 4.4, Population Regeneration optimal solution Mbest:
If meeting Fbest_e > Fbset, Fbset_e is assigned to Fbset, Mbest_e is assigned to Mbest；If no
Meet, then keeps Fbset and Mbest constant；To obtain after updating later population optimal solution Mbest, executed after enabling p=1
Step 4.9；
Step 4.5, to pth chromosome zpCarry out the power distribution network optimal load flow that equivalent model is switched based on flexible multimode
It calculates, obtains pth chromosome zpFitness function value fp；
Step 4.6, according to pth chromosome zpFitness function value fpUpdate the history optimal solution of pth chromosome
Mbest_p:
If meeting fp> fbest_p, then by fpIt is assigned to fbest_p, by zpIt is assigned to mbest_p；If not satisfied, then keeping
Fbest_p and mbest_p are constant；To obtain updating later history optimal solution mbest_p；
Step 4.7, according to pth chromosome zpFitness function value fpUpdate the optimal solution Mbest_e of contemporary population e:
If meeting fp> Fbset_e, then by fpIt is assigned to Fbest_e, by zpIt is assigned to Mbest_e；If not satisfied, then keeping
Fbest_e and Mbest_e are constant；To obtain updating later optimal solution Mbest_e；
Step 4.8 after enabling p+1 be assigned to p, executes step 4.3；
Step 4.9 judges whether to meet p > Z, if satisfied, going to step 4.11；Otherwise, q=1 is enabled, step 4.10 is executed；
Step 4.10 judges whether to meet q > D, if satisfied, p+1 is then assigned to p, executes step 4.9；Otherwise, to pth
Chromosome zpIt carries out self study, social learning and from after mutation operation, after q+1 is assigned to q by order, executes step 4.10；
The self study, social learning and the behaviour that makes a variation certainly include:
D) q-th of random number r is generatedq1If meeting rq1<R1, then pth chromosome zpQ genes itself history
The q genes of optimal solution mbset_p are replaced；Otherwise, it does not replace；
E) q-th of random number r is generatedq2If meeting rq2<R2, pth chromosome zpQ gene population optimal solutions
The q genes of Mbest are replaced；Otherwise, it does not replace；
F) q-th of random number r is generatedq3If meeting rq3<R3, q genes progress random mutations of chromosome；Otherwise, it does not dash forward
Become；
Step 4.11 judges whether to meet e > Nmax, if satisfied, executing step 4.12；Otherwise, it enables and e+1 is assigned to e simultaneously
Go to step 4.3；
Step 4.12, output population optimum dyeing body Mbest are population optimal solution, that is, flexible multimode switch with
Distributed generation resource joint addressing constant volume scheme.
The key content of above-mentioned improved Genetic Particle Swarm hybrid optimization algorithm has at 3 points, introduces individually below:
1, coding and decoding mode
For optimization problem:
minf(X) (27)
In formula (27), X is the solution of any given optimization problem, and f (X) is the corresponding fitness function value of X；
X={ xb, b=1,2...n (28)
In formula (28), xbFor the b digit in X, xb∈Cb, CbFor xbCandidate solution set, are as follows:
In formula (29),For CbIn v digit；
Each x in XbIt is carried out being encoded into g with the integer between 1-wb:
gb=F (xb),1≤gb≤ w and
In formula (30), F () is coding function, gbFor xbValue after coding meets It is set of integers
It closes；
X is encoded, exactly X each is encoded, it may be assumed that
G=F (X)={ F (xb)={ gb, b=1,2...n (31)
In formula (31), G is an any given coding, each of these gbAccording to candidate collection CbIt is decoded into
xb:
In formula (32), F-1() is decoding functions.
G is decoded, exactly each in G is decoded, it may be assumed that
X=F-1(G)={ F-1(gb)={ xb, b=1,2...n (33)
2, the reference of particle swarm algorithm
The power distribution network optimal load flow for switched based on flexible multimode equivalent model to every chromosome is calculated, according to institute
The objective function to be optimized calculates fitness function value, to obtain the optimal chromosome mbest_p of history and the optimal dyeing of population
Body Mbest, and " memory function " of particle in particle swarm algorithm is used for reference, record the optimal mbest_p of history and the population of chromosome
Optimal Mbest modifies next-generation chromosome；
3, the introducing of genetic operator
" self study rate R is introduced in the crossover process of genetic algorithm1" and " social learning leads R2", during variation
It introduces " from aberration rate R3", concrete operations are as follows: the renewal process of every chromosome includes three parts, is self-teaching first
Process, chromosome is with certain probability R1Learn outstanding gene to itself history optimal solution, i.e., is carried out with itself history optimal solution
Gene replacement；Followed by social learning's process, chromosome is with certain probability R2Learn outstanding gene to social elite, i.e., with kind
Group's optimal solution carries out gene replacement；It is finally local search procedure, chromosome is with certain probability R3The gene chosen is carried out
Mutation.
Claims (5)
1. a kind of coordinated planning method of flexible multimode switch and distributed generation resource in active power distribution network, which is characterized in that packet
Include following steps:
Step 1: establishing flexible multimode switchs equivalent model；
It at M power supply and M branch and is connected to the flexible multimode switch with M port is equivalent in active power distribution network,
And impedance is introduced in every branch, to the capacity for the capacity branch that flexible multimode switchs be indicated, by flexible multimode
The loss of switch is with branch loss come approximate substitution；
Step 2: establishing the active power distribution network optimal load flow computation model switched based on flexible multimode；
Equivalent model is switched based on flexible multimode, it is minimum with multi-period active power distribution network variation minimum and via net loss
Objective function, and all kinds of constraint conditions are set, it is calculated to establish the active power distribution network optimal load flow switched containing flexible multimode
Model；
Step 3: that establishes in active power distribution network flexible multimode switch and distributed generation resource combines addressing constant volume model；
Power grid operator Income Maximum and the minimum objective function of power distribution company overall cost in a distributed manner, and all kinds of constraints are set
Condition, so that establishes in active power distribution network flexible multimode switch and distributed generation resource combines addressing constant volume model；
Step 4: using improved Genetic Particle Swarm hybrid optimization algorithm, to the connection of flexible multimode switch and distributed generation resource
It closes addressing constant volume model to be solved, obtained population optimal solution is switched as flexible multimode combines choosing with distributed generation resource
Location constant volume scheme.
2. active power distribution network flexibility multimode switch according to claim 1 and distributed generation resource coordinated planning method,
Be characterized in that: the step 1 is to carry out according to the following procedure:
Step 1.1 establishes flexible multimode switch equivalent model using formula (1):
In formula (1), RmIt is the equivalent equivalent resistance in flexible m-th of port of multimode switch；Imax,mIt is flexible multimode switch m
The equivalent maximum branch current in a port；Af,mFor m-th of port loss coefficient of flexible multimode switch；
Step 1.2, the active balance for being established flexible multimode switch operation control respectively using formula (2)-formula (5) are constrained, are idle
Constraints of Equilibrium and capacity-constrained:
-μSFMSS,m≤Qf,m≤μSFMSS,m (4)
Sf,m≤SFMSS,m (5)
In formula (2)-formula (5), M is the port number of flexible multimode switch；Pf,mM-th of port for flexible multimode switch passes
Defeated active power；Ploss,mFor the active loss of m-th of port of flexible multimode switch；ImIt is the m of flexible multimode switch
The equivalent branch current in port；RmIt is the equivalent equivalent resistance in the port m of flexible multimode switch；μ be power-factor angle just
The absolute value of string；Qf,mFor the reactive power of m-th of port output of flexible multimode switch；SFMSS,mFor flexible multimode switch
M-th of port current transformer access capacity；Sf,mFor the apparent energy of m-th of port of flexible multimode switch, i.e., flexible more shapes
The transimission power of m-th of port of state switch, m=1,2 ..., M.
3. active power distribution network flexibility multimode switch according to claim 1 and distributed generation resource coordinated planning method,
Be characterized in that: the step 2 is to carry out according to the following procedure:
Step 2.1 determines objective function F using linear weight sum method shown in formula (6)L:
FL=min (α1Q+α2T) (6)
In formula (6), α1For variation weight, α in active power distribution network2For via net loss weight in active power distribution network, and 0≤α1
≤ 1,0≤α2≤ 1, α1+α2=1；Q is variation function, and is characterized by formula (7), and T is via net loss function, and by formula
(8) it is characterized:
In formula (7), NnFor active power distribution network node total number；UiIt (t) is the voltage magnitude of t period node i；Umax,iFor node i voltage
Amplitude upper limit value；Umin,iFor node i voltage magnitude lower limit value；" | | " indicate "or"；
Step 2.2 establishes distribution system trend constraint using formula (9):
In formula (9), Pi(t)、QiIt (t) is respectively the active power and reactive power injected in t period node i；φiFor with node i
The set of connected node；Ui(t)、UjIt (t) is respectively the voltage magnitude of t period node i, j；θijIt (t) is t period node i, j
Phase difference of voltage；Gij、BijTransconductance and mutual susceptance respectively in node admittance matrix, and have:
In formula (10), PDG,i(t)、QDG,iIt (t) is respectively the active power of distributed generation resource injection and idle function in t period node i
Rate；Pf,i(t)、Qf,i(t) be respectively flexible multimode switch injection in t period node i active power and reactive power；PLD,i
(t)、QLD,i(t) be respectively load in t period node i active power and reactive power；
Step 2.3 establishes power distribution system secure operation constraint using formula (11) and formula (12):
Umin,i≤Ui(t)≤Umax,i (11)
Iij(t)2≤(Imax,ij)2 (12)
In formula (12): Iij(t) current amplitude of node j, I are flowed to for t period node imax,ijThe electric current of node j is flowed to for node i
The amplitude upper limit.
4. active power distribution network flexibility multimode switch according to claim 1 and distributed generation resource coordinated planning method,
Be characterized in that: the step 3 is to carry out according to the following procedure:
Step 3.1 establishes objective function F using formula (13)M:
FM=EP+EO (13)
In formula (13), EPFor distributed generation resource operator annual earnings, and obtained by formula (14), EOFor power distribution company year overall cost,
And it is obtained by formula (15):
In formula (14), max, which is represented, to be maximized；T is the total period that optimization calculates；NDGNumber for the distributed generation resource installed
Amount；CsFor government subsidy electricity price；CeFor wind-powered electricity generation rate for incorporation into the power network；CopFor operation and maintenance cost；It is kth class distributed generation resource in t
The generated energy of period；σ is distributed generation resource year value operator；Cdg,kFor the unit capacity investment cost of kth class distributed generation resource；
PDG,kFor the installed capacity of kth class distributed generation resource；
EO=min (EG+ELOSS+EFMSS) (15)
In formula (15), min, which is represented, to be minimized；EGFor conventional electric power generation cost；ELOSSFor power transmission and distribution cost, it is lost comprising line power
The active loss cost of cost and flexible multimode switch, is obtained, E by formula (16)FMSSInstallation and fortune are switched for flexible multimode
Row maintenance cost, and obtained by formula (17):
In formula (16), ClossFor network loss electricity price；NbFor number of branches in active power distribution network；IL(t) electric current for being t period branch L
Value；RlFor the resistance of branch L；Ploss,mIt (t) is the active loss of m-th of port of t period flexibility multimode switch；
In formula (17), ε is mounting cost year value operator；γ is year operation and maintenance cost coefficient；NFMSSFor flexible multimode switch
Number to be installed；SFMSS,kFor the capacity of k-th of installation flexible multimode switch；CFMSS,kFor k-th of installation flexible multimode
The unit capacity cost of investment of switch；
Step 3.2, the distributed generation resource units limits for establishing flexible multimode switch operation respectively using formula (18)-formula (20):
0≤PDG,i≤PDG,i,max (18)
PDG,i=λiPrated,i (19)
In formula (18)-formula (20), PDG,iFor the power output of distributed generation resource at node i；PDG,i,maxFor allow to install at node i
Distributed generation resource maximum size；Prated,iFor the unit rated capacity of distributed generation resource at node i；λiTo install distribution at node i
The number of formula power supply；PLDFor burden with power total in active power distribution network；η is that the distributed generation resource maximum that active power distribution network allows is seeped
Saturating rate.
5. active power distribution network flexibility multimode switch according to claim 1 and distributed generation resource coordinated planning method,
Be characterized in that: the improved Genetic Particle Swarm hybrid optimization algorithm of step 4 is to carry out as follows:
Step 4.1, initialization maximum number of iterations Nmax, population quantity Z, chromosomal gene length D, in genetic algorithm parameter from
Learning rate R1, social learning lead R2With from aberration rate R3；
Step 4.2 carries out hybrid coding to flexible multimode contact capacity, position and distributed generation resource capacity, position, and initial
The population of Z chromosome is generated at random；
Any pth chromosome is enabled to be denoted as zp, p belongs to [1, Z]；
Q is enabled to indicate pth chromosome zpUpper any one gene serial number, q belong to [1, D]；
Mbest_p is enabled to indicate pth chromosome zpHistory optimal solution, corresponding fitness function value be fbest_p；Initially
Change fbest_p=0；
Enabling current iteration number is e；
Enabling Mbest_e is the population optimal solution in e generation, and e belongs to [1, Nmax], corresponding fitness function value is Fbset_e,
Initialize Fbset_e=0；
Enabling population optimal solution is Mbest, and corresponding fitness function value is Fbset, initializes Fbset=0；
Initialize e=1, p=1；
Step 4.3 judges whether to meet p > Z, if satisfied, thening follow the steps 4.4；Otherwise, step 4.5- step 4.8 is executed；
Step 4.4, Population Regeneration optimal solution Mbest:
If meeting Fbest_e > Fbset, Fbset_e is assigned to Fbset, Mbest_e is assigned to Mbest；If not satisfied,
Then keep Fbset and Mbest constant；To obtain after updating later population optimal solution Mbest, step is executed after enabling p=1
4.9；
Step 4.5, to pth chromosome zpThe power distribution network optimal load flow for switched based on flexible multimode equivalent model is calculated,
Obtain pth chromosome zpFitness function value fp；
Step 4.6, according to pth chromosome zpFitness function value fpUpdate the history optimal solution mbest_ of pth chromosome
P:
If meeting fp> fbest_p, then by fpIt is assigned to fbest_p, by zpIt is assigned to mbest_p；If not satisfied, then keeping
Fbest_p and mbest_p are constant；To obtain updating later history optimal solution mbest_p；
Step 4.7, according to pth chromosome zpFitness function value fpUpdate the optimal solution Mbest_e of contemporary population e:
If meeting fp> Fbset_e, then by fpIt is assigned to Fbest_e, by zpIt is assigned to Mbest_e；If not satisfied, then keeping
Fbest_e and Mbest_e are constant；To obtain updating later optimal solution Mbest_e；
Step 4.8 after enabling p+1 be assigned to p, executes step 4.3；
Step 4.9 judges whether to meet p > Z, if satisfied, going to step 4.11；Otherwise, q=1 is enabled, step 4.10 is executed；
Step 4.10 judges whether to meet q > D, if satisfied, p+1 is then assigned to p, executes step 4.9；Otherwise, pth item is contaminated
Colour solid zpIt carries out self study, social learning and from after mutation operation, after q+1 is assigned to q, executes step 4.10；
The self study, social learning and the behaviour that makes a variation certainly include:
A) q-th of random number r is generatedq1If meeting rq1<R1, then pth chromosome zpQ genes it is optimal with itself history
The q genes of solution mbset_p are replaced；Otherwise, it does not replace；
B) q-th of random number r is generatedq2If meeting rq2<R2, pth chromosome zpQ genes population optimal solution Mbest
Q genes be replaced；Otherwise, it does not replace；
C) q-th of random number r is generatedq3If meeting rq3<R3, q genes progress random mutations of chromosome；Otherwise, it is not mutated；
Step 4.11 judges whether to meet e > Nmax, if satisfied, executing step 4.12；Otherwise, it enables and e+1 is assigned to e and is gone to
Step 4.3；
Step 4.12, output population optimum dyeing body Mbest are population optimal solution.
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