CN105069704B - A kind of quick traversal reconstruction method of power distribution network improving distributed generation resource permeability - Google Patents

A kind of quick traversal reconstruction method of power distribution network improving distributed generation resource permeability Download PDF

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CN105069704B
CN105069704B CN201510500662.XA CN201510500662A CN105069704B CN 105069704 B CN105069704 B CN 105069704B CN 201510500662 A CN201510500662 A CN 201510500662A CN 105069704 B CN105069704 B CN 105069704B
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power
distribution network
power distribution
distributed generation
generation resource
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CN105069704A (en
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刘科研
何开元
贾东梨
胡丽娟
叶学顺
刁赢龙
唐建岗
朱俊澎
宋杉
顾伟
聂颖惠
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State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd
State Grid Beijing Electric Power Co
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State Grid Corp of China SGCC
China Electric Power Research Institute Co Ltd
State Grid Beijing Electric Power Co
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    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02ATECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A30/00Adapting or protecting infrastructure or their operation
    • Y02A30/60Planning or developing urban green infrastructure
    • YGENERAL 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
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00Energy generation through renewable energy sources
    • Y02E10/50Photovoltaic [PV] energy
    • Y02E10/56Power conversion systems, e.g. maximum power point trackers

Abstract

The present invention provides a kind of quick traversal Distribution system method for improving distributed generation resource permeability, which comprises (1) establishes the uncertain power output model of wind-powered electricity generation, photovoltaic;(2) it based on wind-powered electricity generation, photovoltaic uncertainty power output model, establishes to improve power distribution network reconfiguration model of the distributed generation resource permeability as target;It (3) will be deterministic models containing probabilistic Distribution system model conversation;(4) the feasible solution set of reconstruction is searched for;(5) feasible solution set is quickly traversed, and finds globally optimal solution, obtains the Distributing network structure of consumption maximum capacity distributed generation resource.The present invention, which promotes distributed generation resource by network reconfiguration, can access the quick traversal method of capacity, and this method can reduce distributed generation resource in active power distribution network operational process and cut machine, increase the economy of power distribution network operation.

Description

A kind of quick traversal reconstruction method of power distribution network improving distributed generation resource permeability
Technical field
The present invention relates to a kind of reconstruction method of power distribution network, and in particular to a kind of quick time for improving distributed generation resource permeability Go through reconstruction method of power distribution network.
Background technique
Distribution Networks Reconfiguration is also known as distribution network configuration, or the reconstruct of distribution network feeder line configuration, distribution network feeder line.Distribution Network reconfiguration is exactly the assembled state by changing block switch, interconnection switch, to change topological structure and the user of network Supply path.Traditional power distribution network reconfiguration purpose mainly has reduction network loss, elimination overload, balanced load, raising quality of voltage etc..
Three branches of stochastic programming are model of expected value, chance constrained programming and Dependent-chance Programming.Wherein chance is about Beam planning is proposed by Cha Nasi (A.Charnes) He Kubai (W.W.Cooper), is reached under certain probability meaning Optimal theory.It is a kind of stochastic programming method, for containing stochastic variable in constraint condition, and must observe with The problem of making a policy before the realization of machine variable.
Chance constrained programming may be unsatisfactory for constraint condition when adverse conditions occurs in view of done decision, and use A kind of principle: done decision is allowed to be unsatisfactory for constraint condition to a certain extent, but the decision makes the general of constraint condition establishment Rate is not less than some sufficiently small confidence level.To some special circumstances, Chance Constrained Programs can be converted into equivalence Really qualitative mathematics planning problem, but for more complex Chance Constrained Programs, then to utilize the calculation based on stochastic simulation Method solves general Chance Constrained Programs and multi-object programming with randomized restriction problem.
Summary of the invention
In order to overcome the above-mentioned deficiencies of the prior art, the present invention provides a kind of quick time for improving distributed generation resource permeability Reconstruction method of power distribution network is gone through, the present invention, which promotes distributed generation resource by network reconfiguration, can access the quick traversal method of capacity, should Method can reduce distributed generation resource in active power distribution network operational process and cut machine, increase the economy of power distribution network operation.
In order to achieve the above-mentioned object of the invention, the present invention adopts the following technical scheme that:
A kind of quick traversal reconstruction method of power distribution network improving distributed generation resource permeability, the method includes walking as follows It is rapid:
(1) the uncertain power output model of wind-powered electricity generation, photovoltaic is established;
(2) it based on wind-powered electricity generation, photovoltaic uncertainty power output model, establishes to improve distributed generation resource permeability matching as target Reconfiguration of electric networks model;
It (3) will be deterministic models containing probabilistic power distribution network reconfiguration model conversation;
(4) the feasible solution set of reconstruction is searched for;
(5) feasible solution set is quickly traversed, and finds globally optimal solution, obtains matching for consumption maximum capacity distributed generation resource Electric network composition.
Preferably, in the step (1), the wind-powered electricity generation uncertainty power output model is expressed as follows:
In formula, Pw(v) and Qw(v) be respectively wind speed be v when wind-powered electricity generation active and idle power output, PRIt is rated active power, N is blower number, and ρ is atmospheric density, CpIt is energy conversion efficiency, R is fan blade radius, vRIt is rated wind speed, vciAnd vco It is incision wind speed and cut-out wind speed, θ respectivelywIt is the power factor of wind-powered electricity generation;
Wherein, uncertain be distributed with Weibull of wind speed v describes:
F (v) is the probability density function of wind speed v, μ1For the desired value of wind speed, k is distribution parameter;
The photovoltaic uncertainty power output model is expressed as follows:
G (P) is the probability density function of photovoltaic active power output P, μ2For the desired value of P, σ is standard deviation.
Preferably, in the step (2), the premise of the power distribution network reconfiguration is the position of distributed generation resource access and each A distributed generation resource active power ratio has determined;Power distribution network reconfiguration objective function is described as follows:
In formula, CobjFor the distributed generation resource active power of power distribution network maximum access, Ω α is all structures of power distribution network, CapαIt is to meet the distributed generation resource maximum access power under operation constraint condition as distribution network selecting structure α;Pi cBe with The active power of the connected distributed generation resource of node i, ΩgIt is the set of the node serial number of all connection distributed generation resources;
The constraint condition of power distribution network reconfiguration includes:
Network structure constraint, i.e. network structure keep radial pattern;
Power-balance constraint is described as follows:
Wherein, Pi grid、Pi g、Pi lPower distribution network respectively at node i injects active power, and distributed generation resource injection is active Power and load active power,Qi lPower distribution network respectively at node i injects reactive power, distributed generation resource note Enter reactive power and reactive load power;Vi, VjIt is i, the voltage of j node, Y respectivelyijIt is the value of node admittance matrix i row j column, θijIt is YijAngle under polar form, δj, δiIt is i, the phase angle of j node voltage respectively;
Node voltage constraint, is described as follows:
Vimin≤Vi≤Vimax
Wherein, Vi, Vimin, VimaxVoltage magnitude respectively at node i, voltage magnitude lower limit and the voltage magnitude upper limit;
Restriction of current, i.e. line current are no more than rated value.
Preferably, in the step (3), the uncertain power output model of meter and wind-powered electricity generation and photovoltaic is uncertainty optimization mould Type converts deterministic optimization model for uncertain power distribution network Optimized model, method is such as using chance constrained programming method Under:
Step 3-1, original uncertainty optimization Model Abstraction is indicated are as follows:
max f(x,ξ)
s.t.gi(x, ξ)≤0, i=1,2 ..., q
Wherein x is control variable, i.e., the state of block switch and contact wiretap in power distribution network, ξ is Uncertainty, i.e. wind Electricity and photovoltaic;F (x, ξ) is objective function, i.e., access distributed generation resource active power, gi (x, ξ) indicate inequality constraints condition, The number of q expression inequality constraints condition;
Step 3-2, use chance constrained programming method by the model conversation for following form:
min f'
s.t.Pr{f(x,ξ)≤f'}≥β
Pr{gi(x, ξ)≤0 } >=α, i=1,2 ..., q
Wherein, f' is the objective function after conversion, and Pr { } indicates the probability occurred { } interior time, α and β be objective function and The confidence interval of constraint examines whether the condition in Chance-Constrained Programming Model meets using Monte Carlo Analogue Method.
Preferably, in the step (4), the coding mode of minimum ring is taken to screen all power distribution network reconfiguration feasible solutions,
Step 4-1, all contact wiretaps are closed, minimum ring identical with contact wiretap number, each minimum are obtained One dimension of the corresponding coding of ring;
Step 4-2, the switch in each ring is numbered, the corresponding coding of feasible solution is to open in the numerical value of the dimension Disconnected switch number;
Step 4-3, when traversing all codings, the connectivity of corresponding network structure only need to be examined, if meeting connectivity demand, Then guarantee that the structure is radial pattern structure, it will be in coding income feasible solution set;Network structure meets condition of connectedness and is equivalent to Following equation:
Wherein, N is node number, and A is the corresponding adjacency matrix of network structure, and A ' is the transposition of A, (A')iFor matrix A ' I power, E (N) is N-dimensional unit matrix, the minimum value in min () representing matrix.
Preferably, in the step (5), the method for the quick traversal feasible solution is as follows:
Step 6-1, it initializes, recording current optimum structure number is 1, and maximum access power is 0, is currently traversed to Structure number is 1;
Step 6-2, into the 1st period in one day;
Step 6-3, according to Chance-Constrained Programming Model, test whether constraint condition under current power meets, if not satisfied, Execute step 6-4;If satisfied, executing step 6-5;
Step 6-4, currently being traversed structure number adds 1 for detection, detects whether to be more than feasible solution sum, if exceeding, operation Terminate, returns to current optimum structure and maximum access power;If without departing from return step 6-2;
Step 6-5, present period adds 1, checks whether beyond a period sum, if exceeding, current maximum access power Increase a step-length, optimum structure number is updated to current structure number;If without departing from return step 6-3.
Compared with prior art, the beneficial effects of the present invention are:
Method of the invention is reduced the running machine of cutting of power distribution network and is held by the accessible power of promotion distributed generation resource Amount, promotes the utilization efficiency of renewable energy, promotes the economy that power distribution network is run from source.The present invention considers can be again The randomness of the raw energy, establishes the reconstruction model more to tally with the actual situation, takes quick ergodic algorithm, it is ensured that obtains complete Office's optimal solution.
Detailed description of the invention
Fig. 1 is a kind of quick traversal reconstruction method of power distribution network process for improving distributed generation resource permeability provided by the invention Figure
Fig. 2 is the 33 node structure figure of IEEE of all interconnection switch closures provided by the invention
Fig. 3 is the method flow diagram of quick traversal feasible solution provided by the invention
Fig. 4 is 33 node structure figure of the IEEE after traversing provided by the invention
Specific embodiment
The present invention is described in further detail below in conjunction with the accompanying drawings.
In the implementation case, 33 node of IEEE modified is chosen as power distribution network example, as shown in Fig. 2, original On the basis of 33 node of IEEE, the wind-powered electricity generation of fixed capacity ratio is accessed in node 10,20,28 respectively, respectively in node 13,18 Access the photovoltaic of fixed capacity ratio.
As shown in Figure 1, a kind of quick traversal reconstruction method of power distribution network for improving distributed generation resource permeability, the method packet Include following steps:
(1) the uncertain power output model of wind-powered electricity generation, photovoltaic is established;
(2) it based on wind-powered electricity generation, photovoltaic uncertainty power output model, establishes to improve distributed generation resource permeability matching as target Reconfiguration of electric networks model;
It (3) will be deterministic models containing probabilistic power distribution network reconfiguration model conversation;
(4) the feasible solution set of reconstruction is searched for;
(5) feasible solution set is quickly traversed, and finds globally optimal solution, obtains matching for consumption maximum capacity distributed generation resource Electric network composition.
Wind power output is expressed as follows:
In formula, Pw(v) and Qw(v) be respectively wind speed be v when wind-powered electricity generation active and idle power output, PRIt is rated active power, N is blower number, and ρ is atmospheric density, CpIt is energy conversion efficiency, R is fan blade radius, vRIt is rated wind speed, vciAnd vco It is incision wind speed and cut-out wind speed, θ respectivelywIt is the power factor of wind-powered electricity generation;
Wherein, uncertain be distributed with Weibull of wind speed v describes:
F (v) is probability density function, μ1For the desired value of wind speed, k is distribution parameter.
Photovoltaic active power output indicates as follows with normal distribution:
G (P) is the probability density function of photovoltaic active power output P, μ2For the desired value of P, σ is standard deviation.
The premise of power distribution network reconfiguration is the position and each distributed generation resource active power ratio that distributed generation resource accesses It has determined.Power distribution network reconfiguration objective function is described as follows:
In formula, CobjFor the distributed generation resource active power of power distribution network maximum access, Ω α is all structures of power distribution network, CapαIt is to meet the distributed generation resource maximum access power under operation constraint condition as distribution network selecting structure α;Pi cBe with The active power of the connected distributed generation resource of node i, ΩgIt is the set of the node serial number of all connection distributed generation resources;
Since 5 node access capacity ratios are fixed, 1:Cap can be denoted as13:Cap18:Cap20:Cap28So reconstruct mesh Scalar functions can be rewritten are as follows:
Wherein, S10It is the active power for connecing the distributed generation resource on No. 10 nodes.
The constraint condition of power distribution network reconfiguration includes:
(1) network structure constrains, i.e., network structure keeps radial pattern;
(2) power-balance constraint is described as follows:
Wherein, Pi grid、Pi g、Pi lPower distribution network respectively at node i injects active power, and distributed generation resource injection is active Power and load active power,Qi lPower distribution network respectively at node i injects reactive power, distributed generation resource note Enter reactive power and reactive load power;Vi, VjIt is i, the voltage of j node, Y respectivelyijIt is the value of node admittance matrix i row j column, θijIt is YijAngle under polar form, δj, δiIt is i, the phase angle of j node voltage respectively;
(3) node voltage constrains, and is described as follows:
Vimin≤Vi≤Vimax
Wherein, Vi、Vimin、VimaxFor the voltage magnitude at node i, voltage magnitude lower limit and the voltage magnitude upper limit;
(4) restriction of current, i.e. line current are no more than rated value.
Since probabilistic power distribution network reconfiguration of meter and wind-powered electricity generation and photovoltaic is uncertainty optimization model, machine is used Planing method can be constrained, converts deterministic optimization model for uncertain power distribution network Optimized model, the method is as follows:
Original uncertainty optimization model can abstract representation are as follows:
max f(x,ξ)
s.t.gi(x, ξ)≤0, i=1,2 ..., q
Wherein x is control variable, i.e., the state of block switch and contact wiretap in power distribution network.ξ is Uncertainty, i.e. wind Electricity and photovoltaic;F (x, ξ) is objective function, i.e. access distributed generation resource active power, gi(x, ξ) indicates inequality constraints condition, The number of q expression inequality constraints condition.
The model conversation is following form by chance constrained programming:
min f'
s.t.Pr{f(x,ξ)≤f'}≥β
Pr{gi(x, ξ)≤0 } >=α, i=1,2 ..., q
Wherein, f' be conversion after objective function, Pr { } indicate { } in the time occur probability α and β be objective function and The confidence interval of constraint is herein, and random quantity is not present in objective function, therefore only Prescribed Properties need to rewrite.Using Monte Carlo Analogue Method examines whether the condition in Chance-Constrained Programming Model meets.
The coding mode of minimum ring is taken to screen all power distribution network reconfiguration feasible solutions.It is closed all contact wiretaps first, Obtain minimum ring identical with contact wiretap number, a dimension of the corresponding coding of each minimum ring.To opening in each ring Put row number into, the corresponding coding of feasible solution is the switch number cut-off in the numerical value of the dimension.The coding mode can protect It demonstrate,proves all feasible solutions and has corresponded to unique coding.When all interconnection switches of 33 node of IEEE are closed, there are 5 minimum rings, such as Shown in attached drawing 2.Each feasible solution corresponds to 5 dimensional vectors, and the numerical value on i-th dimension vector, which represents i-th of minimum and changes, cut-offs volume Number be the numerical value switch.
When traversing all possible coding, the connectivity of corresponding network structure only need to be examined, if meeting connectivity demand, Guarantee that the structure is radial pattern structure, it will be in coding income feasible solution set.Network structure meet condition of connectedness be equivalent to as Lower equation:
Wherein, N is node number, and A is the corresponding adjacency matrix of network structure, and A' is the transposition of A, (A')iFor matrix A ' I power, E (N) is N-dimensional unit matrix, the minimum value in min () representing matrix.
Quick traversal method of the invention is as shown in Fig. 3, and ergodic process is as follows:
(1) it initializes, recording current optimum structure number is I=1, and maximum access power is S10=0, currently it is traversed to Structure number be n=1;
(2) enter the 1st period in one day;
(3) according to chance constrained programming (CCP) model, test whether constraint condition under current power meets, if not satisfied, It executes (4);If satisfied, executing (5);
(4) currently being traversed structure number adds 1 for detection, detects whether to be more than feasible solution sum 50751, if exceeding, operation Terminate, returns to current optimum structure and maximum access power;If without departing from returning (2);
(5) next moment is examined, present period adds 1, checks whether beyond a period sum, if exceeding, currently most Big access power increases a step-length, i.e. S10=S10+ ks, 5kW is set as in the embodiment, and optimum structure number is updated to work as Preceding network structure number, i.e. n=I;If without departing from returning (3).
The process only saves optimum structure number and corresponding maximum access power in ergodic process, farthest subtracts Lack unnecessary calculating process, improves computational efficiency.
After traversal, the structure for obtaining to dissolve maximum power formula power supply is as shown in Fig. 4, route 10-11, 5 switches on 17-18,26-27,9-15,8-21 are cut-off.Reconstruct the ability pair of both front and back structure consumption distributed generation resource Than as shown in the table:
The different structure operation conditions comparison of the reconstruct of table 1 front and back
From table, it can be seen that before the distributed generation resource maximum capacity that the distribution network interface after reconstruct can access relatively reconstructs About 102% is improved, while scope range of the fluctuation of voltage becomes smaller, consumption distributed electrical source capability enhancing.
Finally it should be noted that: the above embodiments are merely illustrative of the technical scheme of the present invention and are not intended to be limiting thereof, to the greatest extent Invention is explained in detail referring to above-described embodiment for pipe, it should be understood by those ordinary skilled in the art that: still It can be with modifications or equivalent substitutions are made to specific embodiments of the invention, and without departing from any of spirit and scope of the invention Modification or equivalent replacement, are intended to be within the scope of the claims of the invention.

Claims (4)

1. a kind of quick traversal reconstruction method of power distribution network for improving distributed generation resource permeability, which is characterized in that the method packet Include following steps:
(1) the uncertain power output model of wind-powered electricity generation, photovoltaic is established;
(2) it based on wind-powered electricity generation, photovoltaic uncertainty power output model, establishes to improve distributed generation resource permeability as the power distribution network of target Reconstruction model;
It (3) will be deterministic models containing probabilistic power distribution network reconfiguration model conversation;
(4) the feasible solution set of reconstruction is searched for;
(5) feasible solution set is quickly traversed, and finds globally optimal solution, obtains the power distribution network of consumption maximum capacity distributed generation resource Structure;
In the step (2), the premise of the power distribution network reconfiguration is the position and each distributed electrical that distributed generation resource accesses Source active power ratio has determined;Power distribution network reconfiguration objective function is described as follows:
In formula, CobjFor the distributed generation resource active power of power distribution network maximum access, ΩαFor all structures of power distribution network, CapαIt is As distribution network selecting structure α, meet the distributed generation resource maximum access power under operation constraint condition;Pi cIt is and node i The active power of connected distributed generation resource, ΩgIt is the set of the node serial number of all connection distributed generation resources;
The constraint condition of power distribution network reconfiguration includes:
Network structure constraint, i.e. network structure keep radial pattern;
Power-balance constraint is described as follows:
Wherein, Pi grid、Pi g、Pi lPower distribution network respectively at node i injects active power, and distributed generation resource injects active power With load active power,Qi lPower distribution network respectively at node i injects reactive power, and distributed generation resource injects nothing Function power and reactive load power;Vi, VjIt is i, the voltage of j node, Y respectivelyijIt is the value of node admittance matrix i row j column, θijIt is YijAngle under polar form, δj, δiIt is i, the phase angle of j node voltage respectively;
Node voltage constraint, is described as follows:
Vimin≤Vi≤Vimax
Wherein, Vi, Vimin, VimaxVoltage magnitude respectively at node i, voltage magnitude lower limit and the voltage magnitude upper limit;
Restriction of current, i.e. line current are no more than rated value;
In the step (4), the coding mode of minimum ring is taken to screen all power distribution network reconfiguration feasible solutions,
Step 4-1, all contact wiretaps are closed, minimum ring identical with contact wiretap number, each minimum ring pair are obtained The dimension that should be encoded;
Step 4-2, the switch in each ring is numbered, the corresponding coding of feasible solution is to cut-off in the numerical value of the dimension Switch number;
Step 4-3, when traversing all codings, the connectivity of corresponding network structure only need to be examined, if meeting connectivity demand, is protected Demonstrate,proving the structure is radial pattern structure, will be in coding income feasible solution set;Network structure meet condition of connectedness be equivalent to it is as follows Equation:
Wherein, N is node number, and A is the corresponding adjacency matrix of network structure, and A ' is the transposition of A, (A')iFor matrix A ' i times Side, E (N) is N-dimensional unit matrix, the minimum value in min () representing matrix.
2. reconstructing method according to claim 1, which is characterized in that in the step (1), the wind-powered electricity generation uncertainty power output Model is expressed as follows:
In formula, Pw(v) and Qw(v) be respectively wind speed be v when wind-powered electricity generation active and idle power output, PRIt is rated active power, N is Blower number, ρ are atmospheric density, CpIt is energy conversion efficiency, R is fan blade radius, vRIt is rated wind speed, vciAnd vcoRespectively It is incision wind speed and cut-out wind speed, θwIt is the power factor of wind-powered electricity generation;
Wherein, uncertain be distributed with Weibull of wind speed v describes:
F (v) is the probability density function of wind speed v, μ1For the desired value of wind speed, k is distribution parameter;
The photovoltaic uncertainty power output model is expressed as follows:
G (P) is the probability density function of photovoltaic active power output P, μ2For the desired value of P, σ is standard deviation.
3. reconstructing method according to claim 1, which is characterized in that in the step (3), based on wind-powered electricity generation and photovoltaic not really Qualitative power output model is uncertainty optimization model, using chance constrained programming method, by uncertain power distribution network Optimized model It is converted into deterministic optimization model, the method is as follows:
Step 3-1, original uncertainty optimization Model Abstraction is indicated are as follows:
max f(x,ξ)
s.t.gi(x, ξ)≤0, i=1,2 ..., q
Wherein x be control variable, i.e., in power distribution network block switch and contact wiretap state, ξ is Uncertainty, i.e., wind-powered electricity generation and Photovoltaic;F (x, ξ) is objective function, i.e. access distributed generation resource active power, gi(x, ξ) indicates inequality constraints condition, q table Show the number of inequality constraints condition;
Step 3-2, use chance constrained programming method by the model conversation for following form:
min f'
s.t.Pr{f(x,ξ)≤f'}≥β
Pr{gi(x, ξ)≤0 } >=α, i=1,2 ..., q
Wherein, f' is the objective function after conversion, and Pr { } indicates the probability occurred { } interior time, and α and β are objective function and constraint Confidence interval, using Monte Carlo Analogue Method examine Chance-Constrained Programming Model in condition whether meet.
4. reconstructing method according to claim 1, which is characterized in that in the step (5), the quick traversal feasible solution Method is as follows:
Step 6-1, it initializes, recording current optimum structure number is 1, and maximum access power is 0, the structure being currently traversed to Number is 1;
Step 6-2, into the 1st period in one day;
Step 6-3, according to Chance-Constrained Programming Model, test whether constraint condition under current power meets, if not satisfied, executing Step 6-4;If satisfied, executing step 6-5;
Step 6-4, currently being traversed structure number adds 1 for detection, detects whether to be more than feasible solution sum, if exceeding, end of run, Return to current optimum structure and maximum access power;If without departing from return step 6-2;
Step 6-5, present period adds 1, checks whether beyond a period sum, if exceeding, current maximum access power increases One step-length, optimum structure number are updated to current structure number;If without departing from return step 6-3.
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