CN106487005B - A kind of Electric power network planning method considering T-D tariff - Google Patents
A kind of Electric power network planning method considering T-D tariff Download PDFInfo
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Abstract
The invention discloses a kind of Electric power network planning methods for considering T-D tariff.The planning systems such as existing Electric Power Network Planning principle, investment decision method, Electric power network planning method are difficult to adapt to the new demand that electroduct restricts the complicated Uncertain environments such as beam, new-energy grid-connected.The present invention constructs the Electric Power Network Planning model for considering T-D tariff and the constraint condition for establishing the Electric Power Network Planning model；Constraint condition is verified using the probabilistic loadflow method based on Cumulants method, converts deterministic optimization problem for uncertain probability optimization problem；The Electric Power Network Planning model is solved using improved II algorithm of NSGA-, acquires optimal power distribution network Expansion Planning scheme.Electric Power Network Planning model realization that the present invention uses appraises and decides power grid cost and power transmission and distribution income in planning process, reduces power grid enterprises' idle cost, further improves and complies with the economic benefit that electricity marketization builds lower power network planning scheme.
Description
Technical field
The present invention relates to technical field of power systems, especially a kind of Electric power network planning method for considering T-D tariff.
Background technique
With the continuous development of world economy, energy crisis and environmental pollution receive the extensive concern of all circles.In recent years,
Due to distributed power generation have cleaning, environmental protection and flexibly etc. advantages, obtained quick development.Renewable energy type is distributed
Power supply (DG) most significant feature is that climate influences, and generated output has randomness, and the access of distributed generation resource is power train
System planning brings new problem.Need to fully consider that distributed generation resource generated output is uncertain in distribution network planning, it is comprehensive
The relationship for considering both economy and security risk, is included in Electric Power Network Planning model for power grid uncertain factor.
In addition, with the propulsion of China's T-D tariff reform, the profit model of the traditional price difference between purchase and sale of grid company
Right-about will occur.Power grid enterprises, which are appraised and decided, with " permit cost+reasonable benefit " principle permits total income and component voltage grade
T-D tariff mode, strengthens the cost constraint to power grid enterprises, and power grid enterprises will take by reduction at its power transmission and distribution is improved originally
The earning rate of business, to strengthen the requirement to Electric Power Network Planning economy, need to consider T-D tariff to Electric Power Network Planning model and
The influence of planing method.
The planning systems such as existing Electric Power Network Planning principle, investment decision method, Electric power network planning method are difficult to adapt to electroduct
Restrict the new demand of the complicated Uncertain environments such as beam, new-energy grid-connected.Need to redefine Electric Power Network Planning model, research adapts to
The Electric power network planning method of T-D tariff reform.
Influence of the T-D tariff reform to Electric Power Network Planning is mainly reflected in:
1) it needs to combine overall life cycle cost management mode, power grid cost is effectively appraised and decided；
2) new T-D tariff mode requires to consider defeated Price Regulation constraint in Electric Power Network Planning model；
3) Electric Power Network Planning no longer excessively pursues high performance technology index, and economic power system requires to improve；
4) to the performance assessment criteria aspect of power grid, the examination that will be subject to through government's index of correlation.
Summary of the invention
In order to overcome the shortcomings of the prior art described above, the present invention provides a kind of Electric Power Network Planning side for considering T-D tariff
Method, by the inclusion of power supply equalization social cost objective function, power transmission and distribution earnings target function and network loss constraint condition
Chance-Constrained Programming Model, to solve the problems, such as the power network expansion planning under T-D tariff reform background.
The technical solution adopted by the present invention to solve the technical problems is: a kind of Electric Power Network Planning side considering T-D tariff
Method comprising following steps: building considers the Electric Power Network Planning model of T-D tariff and establishes the constraint item of the Electric Power Network Planning model
Part；Constraint condition is verified using the probabilistic loadflow method based on Cumulants method, converts uncertain probability optimization problem to
Deterministic optimization problem；The Electric Power Network Planning model is solved using improved II algorithm of NSGA-, acquires optimal distribution
Net Expansion Planning scheme.
Further, the Electric Power Network Planning model includes power grid enlarging overall life cycle cost, power transmission and distribution operation income
And the objective function of load bus voltage deviation.
Further, P is taken in target power transmission and distribution operationTDMaximum, calculation formula are as follows:
In formula, ΨVLFor the set of each voltage class of T-D tariff,The distributed generation resource for being VL-k for voltage class
Set,The Bulk Supply Substation set for being VL-k for voltage class；pTCFor power transmission and distribution transformer capacity electricity price, pMDFor power transmission and distribution
Greatest requirements capacity price of electricity,The power transmission and distribution electric degree electricity price for being VL-k for voltage class,It is VL-k's for voltage class
The active power of substation j,For the active power for the distributed generation resource i that voltage class is VL-k, PsubFor having for substation
Function power, PDGFor the active power of distributed generation resource, pDG_adElectricity price, p are added for renewable energy electricity priceOGFor rate for incorporation into the power network, r
Ratio, P are referred to for the comprehensive line loss per unit of grid companyiFor the burden with power of load node i, PlossFor system active power loss, Ψload
For load node set.
Further, target grid enlarging overall life cycle cost is minimum, and calculation formula is as follows:
Power grid extends overall life cycle cost CLCCIt include: electric grid investment cost CI, operating cost CO, maintenance cost CM, therefore
Hinder cost CF, scrap cost CD；
The calculation method of above-mentioned each cost is as follows:
In formula, r is benchmark discount rate, and T is the full electric network service life time limit；ΨATo increase line set, Ψ newlyITo create substation
Node set, ΨEFor enlarging substation set；Lline_iFor the length of route i to be selected, clineFor new route unit price,
csub,iFor the investment cost for creating substation i, csub_e,iFor original substation's dilatation expense；xline,iFor control whether to choose to
The 0-1 variable on route selection road；xsub,iTo control whether to create the 0-1 variable of substation to be selected, xsub_e,iFor control whether enlarging to
Select the 0-1 variable of substation；PlossFor system active power loss, cpriceFor electricity price, TlossFor system year maximum loss hourage, δi
For the year failure rate of route i, cmiFor the unit fault maintenance cost of route i, ΨlineFor all line sets of power grid, f is failure
The ratio of indirect cost and direct cost when generation, cFoutageFor direct failure punishment cost, E (R) is cutting load expectation,
TLOLDPower-on time, c are lacked for system yeardFor the retired processing unit cost of equipment, rrFor salvage value rate, LijFor node i to node j it
Between line length.
Further, the constraint condition of the Electric Power Network Planning model include system load flow equality constraint under polar coordinates,
Node voltage random constraints condition, branch transimission power random constraints condition, network loss constraint condition and distribution network structure structure are about
Beam condition.
Further, the calculation formula of the network loss constraint condition is as follows:
In formula, r is that the comprehensive line loss per unit of grid company refers to ratio, PlossFor system active loss, PiFor the active of node i
Load, ΨloadLoad bus set.
Further, include: using the process that improved II algorithm of NSGA- solves the Electric Power Network Planning model
The initial population for meeting grid structure constraint is generated with root node fusion method；Load flow calculation based on Cumulants method calculates mesh
Scalar functions, verification constraint condition；Non-dominated ranking and crowding distance calculate；Selection intersects, the genetic manipulation of variation；Topology
Constraint checking, rejecting are unsatisfactory for individual；Probabilistic loadflow calculates, and obtains ideal adaptation angle value；Population merges；Interim population is non-dominant
Level and crowding distance-taxis；Break-in operation generates new contemporary initial population；When reaching maximum evolutionary generation, generate
The optimal collection of Pareto screens optimal case.
Further, the specific step Electric Power Network Planning model solved using improved II algorithm of NSGA-
It is rapid as follows:
1) individual UVR exposure: Electric Power Network Planning model is treated route selection road and is selected, and decision vector x is compiled using by-line binary system
Code, is indicated whether to build corresponding route to be selected with 0-1 variable；
2) it initializes initial population G: utilizing root node fusion method, be randomly generated and meet network connectivty and radiativity requirement
Individual, generate population quantity be Np initial population G, to initial population carry out non-dominated ranking and crowding distance calculate；
3) genetic manipulation: being based on crowding distance-taxis, selects parent individuality using binary system tournament method, passes through two o'clock
Intersect, exchange serial number variation mode carries out intersection and mutation operator；In conjunction with distribution network source and load bus quantity and circuitry number
The relationship of amount guarantees that parent two individual exchange bases because the number of branches individual selected in section is identical, exclude in crossover operation
A large amount of infeasible solutions；In mutation operation, the gene position that genic value is respectively 0 and 1 is randomly choosed in chromosome and is interchangeable
Serial number variation, avoids invalid mutation operation；Progeny population Q is generated by genetic manipulation；
4) calculating target function: utilizing the tidal current computing method based on Cumulants method, solves the mesh of population Different Individual
Scalar functions, and constraint condition is handled using penalty function method；
5) population merges: merge initial population G and progeny population Q, and rejects the individual for being unsatisfactory for network topology constraint, it is raw
The interim population Q ' of Cheng Xin；
6) non-dominated ranking and crowding calculate: carrying out quick non-dominated ranking to interim population Q ' and crowding calculates；
7) it generates new contemporary initial population: interim population Q ' being arranged according to non-dominated ranking level and crowding distance
Sequence, Np individual, forms new contemporary initial population G before selection；
8) g=g+1, as evolutionary generation g < gmaxWhen, it returns to operation and 3) enters next circulate operation；
9) after iteration, non-domination solution is ranked up using approximate ideal solution, exports optimal power distribution network extension rule
The scheme of drawing.
Compared with prior art, the invention has the advantages that: the present invention considers me during Electric Power Network Planning
State's T-D tariff reforms the influence to Electric power network planning method, carries out new transformation and optimization to Electric Power Network Planning model and method and adjusts
It is whole.In plan model, carries out power supply equalization social cost and calculate, meter and power grid enterprises' power transmission and distribution profit maximization mesh
Mark and the constraint of government's performance assessment criteria network loss, using Chance-Constrained Programming Model, foundation considers the Electric Power Network Planning model of T-D tariff,
And utilize Load flow calculation and II algorithm of improved NSGA- solution multiple target Chance-Constrained Programming Model based on Cumulants method.
Electric Power Network Planning model realization that the present invention uses is in planning process to the core of power grid cost and power transmission and distribution income
It is fixed, power grid enterprises' idle cost is reduced, further improves and complies with the economic effect that electricity marketization builds lower power network planning scheme
Benefit.
Detailed description of the invention
Fig. 1 is the principle of the present invention figure.
Fig. 2 is the flow chart of improved II algorithm of NSGA- of the present invention.
Fig. 3 is IEEE54 node power distribution net original network topology figure.
Fig. 4 is that Fig. 3 implements the power network expansion planning optimal case topological diagram after the method for the present invention.
Specific embodiment
1) consider the Multi-Objective Electric Power Network Planning model of T-D tariff
Traditional power grid planning more focus on electric network reliability requirement, under new power transmission and distribution mechanism, the investment of power grid and
Income receives the supervision of government, improves to the requirements such as electric grid investment benefit and return efficiency, Electric Power Network Planning work has economy
Higher requirement.As the development and new electricity of power grid change the propulsion of work, a large amount of distributed generation resources access power distribution networks, in conjunction with point
The characteristics of cloth power supply power output randomness, guarantees centainly may be used in satisfaction using probabilistic Chance-Constrained Programming Model is considered
Under the premise of property level, the economy of Electric Power Network Planning is improved.
The Electric Power Network Planning model of the considerations of building is made of objective function and constraint condition T-D tariff.
1.1) objective function
(1) power grid extends overall life cycle cost
The requirement of " economy " is not only short-term investment or cost minimization in Electric Power Network Planning, but is conceived to long term time
Interior all cost minimizations are made an investment in section including project construction, operation etc., need to introduce new cost after T-D tariff reform
Calculation method measures " economy " of investment.Reinforce asset life cycle management, improves the requirement of project study depth, mention
The comprehensive benefit of high Electric Power Network Planning construction.
Power grid construction overall life cycle cost CLCCIt include: electric grid investment cost CI, operating cost CO, maintenance cost CM, therefore
Hinder cost CF, scrap cost CD.It is minimum that target grid extends overall life cycle cost.
Calculation method is as follows；
In formula, r is benchmark discount rate, and T is the full electric network service life time limit；ΨATo increase line set, Ψ newlyITo create substation
Node set, ΨEFor enlarging substation set；Lline_iFor the length of route i to be selected, clineFor new route unit price,
csub_iFor the investment cost for creating substation i, csub_eFor original substation's dilatation expense；xline,iIt is to be selected to control whether to choose
The 0-1 variable of route；xsub,iTo control whether to create the 0-1 variable of substation to be selected, xsub_e,iIt is to be selected to control whether to extend
The 0-1 variable of substation；PlossFor system active power loss, cpriceFor electricity price, TlossFor system year maximum loss hourage, δiFor
The year failure rate of route i, cmiFor the unit fault maintenance cost of route i, ΨlineFor all line sets of power grid, f is failure hair
The ratio of indirect cost and direct cost when raw, cFoutageFor direct failure punishment cost, E (R) is cutting load expectation, TLOLD
Power-on time, c are lacked for system yeardFor the retired processing unit cost of equipment, rrFor salvage value rate, LijIt is node i between node j
Line length.
(2) power transmission and distribution operation is taken in
Different power distribution network planning schemes can also generate T-D tariff operation income.Calculate entire distribution network component voltage etc.
P is taken in the power transmission and distribution operation of gradeTD, including electricity price, four parts of capacity price of electricity, additional electricity price and operation of power networks line loss profit.
P is taken in target power transmission and distribution operationTDIt is maximum.
Different power distribution network planning schemes can also generate T-D tariff operation income.Calculate entire distribution network component voltage etc.
P is taken in the power transmission and distribution operation of gradeTD, including electricity price, four parts of capacity price of electricity, additional electricity price and operation of power networks line loss profit.
P is taken in target power transmission and distribution operationTDIt is maximum.
In formula, ΨVLFor the set of each voltage class of T-D tariff,The distributed generation resource for being VL-k for voltage class
Set,The Bulk Supply Substation set for being VL-k for voltage class；pTCFor power transmission and distribution transformer capacity electricity price, pMDFor power transmission and distribution
Greatest requirements capacity price of electricity,The power transmission and distribution electric degree electricity price for being VL-k for voltage class,It is VL-k's for voltage class
The active power of substation j,For the active power for the distributed generation resource i that voltage class is VL-k, PsubFor having for substation
Function power, PDGFor the active power of distributed generation resource, pDG_adElectricity price, p are added for renewable energy electricity priceOGFor rate for incorporation into the power network, r
Ratio, P are referred to for the comprehensive line loss per unit of grid companyiFor the burden with power of load node i, PlossFor system active power loss, Ψload
For load node set.
(3) load bus voltage deviation is minimum
In formula: Δ U is load node i voltage deviation；Ui is node i virtual voltage；For desired voltage values；
For maximum permissible voltage deviation；γi=Pi/PlodeFor weight factor, PiFor node i original loads, PlodeIt is always born for distribution system
Lotus.
1.2) constraint condition
(1) system load flow equality constraint under polar coordinates:
In formula: PgiAnd QgiThe respectively active and idle injecting power vector of bus；PLiAnd QLiRespectively bus is active and nothing
Workload vector；P(V,θ)iWith Q (V, θ)iRespectively each bus nodes load is active and reactive power.
(2) node voltage random constraints:
In formula: PrFor probability event, ViFor each load bus voltage value,WithRespectively each node voltage lower limit
And upper limit value, βVFor the confidence level of voltage constraint, Φ is system node set.
(3) branch transimission power random constraints:
In formula, SjRoute j apparent energy capacity,Allow maximum capacity, β for feeder lineLFor the confidence of Branch Power Flow constraint
Level, Ω are grid branch set.
(4) network loss constrains:
After T-D tariff reform, the comprehensive line loss per unit of each provincial electric power company is calculated in each self-reference ratio, actual motion middle line
Loss rate is undertaken above or below the ratio bring risk or income by power grid enterprises.Network loss should be less than with reference to line loss in principle
Rate, network loss constraint are as follows:
In formula, r is that the comprehensive line loss per unit of grid company refers to ratio, PlossFor system active loss.PiFor the active of node i
Load, ΨloadFor load node set.
(5) distribution network structure structural constraint
Grid structure is the important component of power distribution network, in order to guarantee that the feasibility of program results, programme are necessary
Strictly meet distribution network structure connectivity and radial constraint.
2) consider the Electric Power Network Planning model solution method of T-D tariff
2.1) based on the tidal current computing method of Cumulants method
The present invention carries out school to the random constraints condition of Electric Power Network Planning model using the probabilistic loadflow based on Cumulants method
It tests.In the power distribution network probabilistic loadflow calculating process containing distributed generation resource, by population at individual decision vector determine network structure and
Its parameter, in conjunction with each node load prediction result and distributed generation resource uncertainty models, using cumulant and newton-pressgang
The probabilistic loadflow calculation method that inferior Load flow calculation combines examines Electric Power Network Planning model constraints condition of opportunity.It is specific to calculate step
It is as follows.
The Load flow calculation under normal operating condition is carried out, the node voltage vector X under benchmark operating status is obtained0, branch
Transimission power vector Z0, Jacobian matrix J0.The present invention only considers the uncertain stochastic variable Δ generated of distributed generation resource power output
WDG, calculate each rank cumulant Δ W of distributed generation resource installation node power(f)。
Power flow equation is linearized in benchmark operating point:
Wherein:W is node injecting power.
Each rank cumulant of each node voltage states variable Δ X and Branch Power Flow Δ Z are acquired by formula, are utilized
The probability density function of the acquisition of Edgeworth series expansion Δ X and Δ Z.Calculate node voltage and Branch Power Flow are in confidence interval
Interior distribution probability verifies constraints condition of opportunity, converts certainty multiple-objection optimization for uncertain probabilistic programming problem and ask
Topic.
2.2) the improved non-dominated sorted genetic algorithm (NSGA- II) with elitism strategy
Non-dominated sorted genetic algorithm (NSGA- II) with elitism strategy is widely used in solving multiple target, non-linear mixed
Close integer optimization problem.II algorithm of NSGA- be based on traditional genetic algorithm (GA), by introduce crowding operator and quickly it is non-dominant
Sequence, algorithm have elitism strategy and lower computation complexity, have preferable whole optimizing ability.
It is constrained in conjunction with real power distribution network network topology structure, to the initialization of population, intersection, mutation operation of II algorithm of NSGA-
It is correspondingly improved, the infeasible solution by excluding largely to be unsatisfactory for network topology cuts down search space, accelerates Evolution of Population
Speed.The key step that II algorithm of NSGA- of application enhancements solves distribution network planning model is as follows:
(1) individual UVR exposure.Plan model is treated route selection road and is selected, and decision vector x uses by-line binary coding, uses
0-1 variable indicates whether to build corresponding route to be selected.
(2) initial population G is initialized.Using root node fusion method, it is randomly generated and meets network connectivty and radiativity is wanted
The individual asked generates the initial population G that population quantity is Np.Non-dominated ranking and crowding distance meter are carried out to initial population
It calculates.
(3) genetic manipulation.Based on crowding distance-taxis, parent individuality is selected using binary system tournament method.Pass through two
Point intersects, exchange serial number variation mode carries out intersection and mutation operator.In conjunction with distribution network source and load bus quantity and branch
The relationship of quantity guarantees that parent two individual exchange bases, can because the number of branches individual selected in section is identical in crossover operation
Exclude a large amount of infeasible solutions.In mutation operation, the gene position that genic value is respectively 0 and 1 is randomly choosed in chromosome and is carried out
Serial number variation is exchanged, can avoid invalid mutation operation.Progeny population Q is generated by genetic manipulation.
(4) calculating target function.Using the tidal current computing method based on Cumulants method, the mesh of population Different Individual is solved
Scalar functions, and constraint condition is handled using penalty function method.
(5) population merges.Merge present age population G and progeny population Q, and reject the individual for being unsatisfactory for network topology constraint,
Generate new interim population Q '.
(6) non-dominated ranking and crowding calculate.Quick non-dominated ranking is carried out to interim population Q ' and crowding calculates.
(7) new contemporary initial population is generated.Interim population Q ' is arranged according to non-dominated ranking level and crowding distance
Sequence, Np individual, forms new contemporary initial population G before selection.
(8) g=g+1 returns to operation (3) and enters next circulate operation as evolutionary generation g < gmax.
It is multi-objective optimization question that all non-dominant levels, which are the individual of first layer, after iteration, in obtained population
Pareto forward position, non-domination solution is ranked up using approximate ideal solution, export optimum programming scheme.
The improved non-dominated sorted genetic algorithm algorithm basic flow chart with elitism strategy is as shown in Fig. 2.
3) example and analysis
Using 54 node example of IEEE, original network topology figure is as shown in Fig. 3.Wherein S1, S2 are built power transformation
It stands, S3, S4 are newly-built substation, and solid line is to be completed route, and dotted line is to consider new route, and node 10,33,49 connects for wind-powered electricity generation
Access point, capacity is as shown in topological diagram.Node 17 to 50 is newly-increased load bus, and load prediction situation is shown in Table 1.The present invention uses
The considerations of proposition T-D tariff Electric power network planning method, under distributed generation resource certain situation example implement multiple target power distribution network
Expansion Planning.
1 54 Node power distribution system load prediction situation of table
If line resistance r=0.1208 Ω/km, reactance x=0.1442 Ω/km, capacity of trunk 10MVA, node voltage
It is limited to 0.95p.u.-1.05p.u., 220,000 yuan/km of new route cost, power grid service life is 15 years, and discount rate is
10%, power grid value-added tax is 17%, and salvage value of fixed assets rate is 5%.Using improved II algorithm of NSGA-, population scale Pop=
200, the number of iterations G=500, crossover probability P1=0.9.
Based on the distribution network planning model for considering T-D tariff, when setting constraints condition of opportunity confidence level as 0.9, in conjunction with
II algorithm of Load flow calculation and improved NSGA- based on cumulant obtains Pareto forward position individual 42.Using approaching ideal
Solution is to non-dominated sorting, ' virtual optimal solution ' objective function are as follows: [6924,24059,0.008], ' virtually most inferior solution ' target
Functional vector are as follows: [7184,21725,0.044] filter out optimum programming scheme, and it is 7031 that power grid, which extends overall life cycle cost,
Wan Yuan, 237,240,000 yuan of income of the operation of power grid year, load bus voltage deviation is 0.8%.The electricity being obtained by the present invention
Net Expansion Planning optimal case network topological diagram is as shown in Fig. 4.Method of the invention is before meeting certain reliability level
It puts, improves the economy of Electric Power Network Planning.
Claims (6)
1. a kind of Electric power network planning method for considering T-D tariff comprising following steps: building considers the power grid rule of T-D tariff
It draws model and establishes the constraint condition of the Electric Power Network Planning model；Constraint is verified using the probabilistic loadflow method based on Cumulants method
Uncertain probability optimization problem is converted deterministic optimization problem by condition；Using improved II algorithm of NSGA- to described
Electric Power Network Planning model is solved, and optimal power distribution network Expansion Planning scheme is acquired；
The Electric Power Network Planning model includes power grid enlarging overall life cycle cost, power transmission and distribution operation income and load bus voltage
The objective function of offset；
P is taken in target power transmission and distribution operationTDMaximum, calculation formula are as follows:
In formula, ΨVLFor the set of each voltage class of T-D tariff,The distributed generation resource set for being VL-k for voltage class,The Bulk Supply Substation set for being VL-k for voltage class；pTCFor power transmission and distribution transformer capacity electricity price, pMDIt is needed for power transmission and distribution maximum
Capacity price of electricity is sought,The power transmission and distribution electric degree electricity price for being VL-k for voltage class,The substation for being VL-k for voltage class
The active power of j,For the active power for the distributed generation resource i that voltage class is VL-k, PsubFor the wattful power of substation
Rate, PDGFor the active power of distributed generation resource, pDG_adElectricity price, p are added for renewable energy electricity priceOGFor rate for incorporation into the power network, r is electricity
The comprehensive line loss per unit of net company refers to ratio, PiFor the burden with power of load node i, PlossFor system active power loss, ΨloadIt is negative
Lotus node set.
2. Electric power network planning method according to claim 1, which is characterized in that target grid extends overall life cycle cost most
Small, calculation formula is as follows:
Power grid extends overall life cycle cost CLCCIt include: electric grid investment cost CI, operating cost CO, maintenance cost CM, failure at
This CF, scrap cost CD；
The calculation method of above-mentioned each cost is as follows:
In formula, r is benchmark discount rate, and T is the full electric network service life time limit；ΨATo increase line set, Ψ newlyITo create power transformation tiny node
Set, ΨEFor enlarging substation set；Lline_iFor the length of route i to be selected, clineFor new route unit price, csub,iFor
The investment cost of newly-built substation i, csub_e,iFor original substation's dilatation expense；xline,iTo control whether to choose route to be selected
0-1 variable；xsub,iTo control whether to create the 0-1 variable of substation to be selected, xsub_e,iTo control whether to extend power transformation to be selected
The 0-1 variable stood；PlossFor system active power loss, cpriceFor electricity price, TlossFor system year maximum loss hourage, δiFor route i
Year failure rate, cmiFor the unit fault maintenance cost of route i, ΨlineFor all line sets of power grid, when f is that failure occurs
Indirect cost and direct cost ratio, cFoutageFor direct failure punishment cost, E (R) is cutting load expectation, TLOLDTo be
It unites and lacks power-on time, c in yeardFor the retired processing unit cost of equipment, rrFor salvage value rate, LijFor node i to the route between node j
Length.
3. Electric power network planning method according to claim 1, which is characterized in that the constraint condition packet of the Electric Power Network Planning model
Include system load flow equality constraint under polar coordinates, node voltage random constraints condition, branch transimission power random constraints condition,
Network loss constraint condition and distribution network structure structure constraint.
4. Electric power network planning method according to claim 3, which is characterized in that the calculation formula of the network loss constraint condition is such as
Under:
In formula, r is that the comprehensive line loss per unit of grid company refers to ratio, PlossFor system active loss, PiFor the burden with power of node i,
ΨloadFor load node set.
5. Electric power network planning method according to claim 1, which is characterized in that using improved II algorithm of NSGA- to described
The process that is solved of Electric Power Network Planning model include: that initial kind that meets grid structure constraint is generated with root node fusion method
Group；Load flow calculation based on Cumulants method, calculating target function, verification constraint condition；Non-dominated ranking and crowding distance
It calculates；Selection intersects, the genetic manipulation of variation；Topological constraints verification, rejecting are unsatisfactory for individual；Probabilistic loadflow calculates, and obtains a
Body fitness value；Population merges；The interim non-dominant level of population and crowding distance-taxis；Break-in operation generates the new present age
Initial population；When reaching maximum evolutionary generation, the optimal collection of Pareto is generated, screens optimal case.
6. Electric power network planning method according to claim 5, which is characterized in that using improved II algorithm of NSGA- to described
Electric Power Network Planning model solved that specific step is as follows:
1) individual UVR exposure: Electric Power Network Planning model is treated route selection road and is selected, and decision vector x uses by-line binary coding, uses
0-1 variable indicates whether to build corresponding route to be selected；
2) it initializes initial population G: utilizing root node fusion method, for meeting network connectivty and radiativity requirement is randomly generated
Body generates the initial population G that population quantity is Np, carries out non-dominated ranking to initial population and crowding distance calculates；
3) genetic manipulation: being based on crowding distance-taxis, selects parent individuality using binary system tournament method, is handed over by two o'clock
Fork, exchange serial number variation mode carry out intersection and mutation operator；In conjunction with distribution network source and load bus quantity and number of branches
Relationship guarantee that the individual exchange bases of parent two because the number of branches individual selected in section is identical, exclude big in crossover operation
Measure infeasible solution；In mutation operation, the gene position that genic value is respectively 0 and 1 is randomly choosed in chromosome and is interchangeable sequence
Number variation, avoid invalid mutation operation；Progeny population Q is generated by genetic manipulation；
4) calculating target function: utilizing the tidal current computing method based on Cumulants method, solves the target letter of population Different Individual
Number, and constraint condition is handled using penalty function method；
5) population merges: merging initial population G and progeny population Q, and rejects the individual for being unsatisfactory for network topology constraint, generates new
Interim population Q '；
6) non-dominated ranking and crowding calculate: carrying out quick non-dominated ranking to interim population Q ' and crowding calculates；
7) it generates new contemporary initial population: sorting according to non-dominated ranking level and crowding distance to interim population Q ', select
Np individual, forms new contemporary initial population G before selecting；
8) evolutionary generation g=g+1, as evolutionary generation g < gmaxWhen, gmaxFor the maximum value of g, returns to operation and 3) followed into next
Ring operation；
9) after iteration, non-domination solution is ranked up using approximate ideal solution, exports optimal power distribution network Expansion Planning side
Case.
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