CN106356849A - Power distribution network reconstruction multi-objective optimization method containing section switch configuration - Google Patents

Abstract

The invention discloses a power distribution network reconstruction multi-objective optimization method containing section switch configuration. The method comprises the following steps: constructing a global optimal multi-objective power distribution network reconstruction model for system reliability, electric energy loss as well as section switch installation and operating cost; using an ant colony algorithm to solve the reconstruction model; obtaining an optimal solution of the multi-objective power distribution network reconstruction model; and optimizing the quantity and positions of power distribution network switches according to the optimal solution so as to realize the global optimal multi-objective power distribution network reconstruction. The method has the beneficial effects that the system reliability can be greatly improved through optimal configuration of section switches according to the method provided by the invention, and the overall system cost can be greatly reduced.

Description

A kind of power distribution network reconfiguration Multipurpose Optimal Method containing block switch configuration

Technical field

The invention belongs to Automatization in Power Distribution Network technical field, more particularly, to a kind of joining containing block switch configuration Reconfiguration of electric networks Multipurpose Optimal Method.

Background technology

With the rapidly growth to electricity needs for the society, for Utilities Electric Co., transmission reliability and power transmission efficiency become Obtain more and more important.Power outage is generally primarily focused in distribution rank.Improve customer electricity satisfaction, electric power in order to overall Company needs to improve power supply reliability, and this also becomes Utilities Electric Co. and is planning one of focus with operation stage.Another Aspect, electric energy loss also occurs mostly in distribution, and therefore, the planning of power distribution network must pay close attention to subtracting of loss with running simultaneously Few, to improve systematic economy benefit.For effectively reducing the recovery time after the system failure, the installation of block switch is just in power distribution network Middle popularization.The selection of quantity, position and block switch type that block switch is installed has to distribution network reliability and economy Prominent impact.Power distribution network reconfiguration changes network topology structure by changing the open and-shut mode of interconnection switch and block switch, It is to reduce system recovery time, the important measures of raising power supply reliability.Therefore it is directed to above-mentioned factor foundation and can take into account two sides The reconstruction method of power distribution network of face demand is significantly.

It has been proposed that Fault traversal algorithm, Failure Mode Effective Analysis method, interval in terms of evaluating reliability of distribution network The methods such as algorithm, but the feature how to plan with reference to distribution switch in evaluating reliability of distribution network not yet has research.Intelligence is calculated Method has more application in terms of power distribution network reconfiguration, on the premise of meeting certain optimization aim, can realize the optimization of power distribution network Reconstruct.Wherein, have research using simulated annealing solve staging device location problem, object function by system reliability, set Standby input and maintenance cost three part composition；Triple population optimal algorithms (tpso), improvement ant group algorithm (acs), mixing are whole Number linear programming method is also used for solving block switch location problem in power distribution network；Based on " modern heuristic " random search optimizing The artificial fish-swarm algorithm (afsa) of technology has application in the switch location problem considering client's power failure cost.

Reduce electric energy loss, be also a key factor of impact power distribution network reconfiguration.In view of system reliability and loss Between influence each other, have research using binary particle swarm algorithm (bpso) solve containing Reliability Index and transmission of electricity damage The power distribution network reconfiguration problem of consumption compound target function.Algorithm aspect, micro-oxidation test (μ ga) is solving medium voltage distribution network reconstruct There is application in multi-objective optimization question；Ant group algorithm (aco) have positive feedback, Distributed Calculation, initial value is relied on little and can The features such as with global search optimal solution, also there is application in power distribution network optimum reconstruction, and have research according to power distribution network open loop The feature run, ant group algorithm is improved it is ensured that after search each time power distribution network tree, improve computing Speed.

But, in the research of above-mentioned power distribution network reconfiguration, there is following deficiency:

One be object function consideration comprehensive not enough, block switch to system reliability, Transmission Loss and costliness Install and not yet inquire into the overall balance of operating cost；

Two is in power distribution network reconfiguration, only using the open and close having switched state as decision content, not yet considers block switch The impact to system reliability for the position.

Content of the invention

The purpose of the present invention is exactly to solve the above problems it is proposed that a kind of power distribution network reconfiguration containing block switch configuration Multipurpose Optimal Method, the method constructing system reliability, electric energy loss and block switch are installed with operating cost totally Excellent multi-objective Reconfiguration of Distribution Network model, and quantity and the position of power distribution network switch are optimized it is achieved that many mesh using ant group algorithm The power distribution network reconfiguration of mark total optimization.

For achieving the above object, the concrete scheme of the present invention is as follows:

A kind of power distribution network reconfiguration Multipurpose Optimal Method containing block switch configuration, comprises the following steps:

(1) input system topological relation, load data and dependability parameter；

(2) multiple target with operating cost global optimum installed by constructing system reliability, electric energy loss and block switch Power distribution network reconfiguration model；

(3) initialize ant group algorithm parameter in search space, initialize iterationses n=1；

(4) according to the pheromone level on path, ant colony is allowed to select path to reach " at food "；Obtain the position of system switching Put list, and then change system topological relation；

(5) all paths passed by according to ant colony, draw the optimal solution of object function in current iteration, and according to local and Overall criterion fresh information prime number value；The optimal solution of object function empty position of the switch list in storage current iteration；

(6) installed and operating cost according to systems reliability analysis, electric energy loss amount and block switch, to current iteration The optimal solution that the optimal solution of the object function obtaining is obtained with front an iteration is compared, and updates optimal solution；

(7) loop iteration, until iterationses reach maximum iteration time set in advance or target is not further excellent Change；Obtain the optimal solution of multi-objective Reconfiguration of Distribution Network model；

(8) quantity and the position of power distribution network switch are optimized it is achieved that the power distribution network of multiple target total optimization according to optimal solution Reconstruct.

Further, in described step (2), the multi-objective Reconfiguration of Distribution Network model of structure particularly as follows:

Minj=ω₁·(ecost+sc)+ω₂·el；

Constraints is:

δv_n≤δv_max；

i_b≤i_max；

$\underset{i=1}{\overset{n_i}{\σ}}{p}_i\≤{\mathrm{\δp}}_{max};$

$\underset{b=1}{\overset{n_b}{\π}}{k}_{n_b}=1;$

Wherein, ω₁For the weight of Reliability Index, ω₂For the weight of transmission losses, ecost refers to for system reliability Scalar functions, sc is switch cost function, and el is system transmission losses function；δv_nFor the voltage drop-out value of node, δ v_maxFor section The maximum voltage drop-out value that point allows, i_bThe absolute value of electric current, i is flow through in circuit_maxFor maximum transmitted electric current, p in circuit_iIt is negative The active power of user, n under lotus point_iPower lower user's intersection for feeder line, δ p_maxFor transformer capacity,For ensureing power distribution network It is the state of open loop operation.

Further, described Reliability Index function particularly as follows:

$ecost=\underset{t=1}{\overset{t}{\σ}}(\underset{b=1}{\overset{n_b}{\σ}}{\mathrm{\λ}}_b\·l_b\·(\underset{k=1}{\overset{{\mathrm{ct}}_b}{\σ}}\underset{j=1}{\overset{{\mathrm{nr}}_b}{\σ}}p\left(k.j\right)\·c_k\left(d,b\right)+\underset{k=1}{\overset{{\mathrm{ct}}_b}{\σ}}\underset{j=1}{\overset{{\mathrm{ns}}_b}{\σ}}p\left(k.j\right)\·c_k\left(d,b\right)\left)\right)\·{(1+ir)}^{t-1}\·{(1+dr)}^{-1(t-1)};$

Wherein, t is the time cycle, n_bFor circuit sum, λ_bFor circuit failure rate, l_bFor line length, ct_bIt is to work as When breaking down on circuit, the type sum of affected load, nr_bIt is when breaking down on circuit, persistently have a power failure is negative Lotus point sum, p (k, j) is the average load of different user types under different load point, c_k(d, b) is to occur on circuit b to continue d During the power failure of individual hour, the function that different load type suffers a loss because of power failure, ns_bDuring for line failure, temporarily stop The load point number of electricity, ir is load annual average rate of increase, and dr is load annual rate of descent.

Further, described switch cost function particularly as follows:

$sc=cis+\underset{t=1}{\overset{t}{\σ}}mc\·n_s\·{(1+dr)}^{-1(t-1)};$

Wherein, cis is the expense installing a new block switch, n_sFor the number of the new block switch installed, mc is every Individual block switch is safeguarded and every annual operating cost, and dr is load annual rate of descent.

Further, described system transmission losses function particularly as follows:

$el=\underset{t=1}{\overset{t}{\σ}}\left(\underset{b=1}{\overset{n_b}{\σ}}8760\·i_{bt}^2\·r_b\·e_p\·{\left(1+dr\right)}^{-1(t-1)}\right);$

Wherein, i_btFor flowing through the absolute value of line current, r_bFor the resistance of circuit, e_pFor electric energy average price, dr is negative Lotus annual rate of descent.

Further, in described step (5) local criterion particularly as follows: in the range of whole search space distribution information Element, with the increase of iterationses, its numerical value will be gradually reduced, to ensure that path gradually weakens to the captivation of ant colony；

The computing formula of described local criterion is as follows:

${\mathrm{\τ}}_{i,j}^{x,y}\left(n\right)=(1-\mathrm{\ρ})\·{\mathrm{\τ}}_{i,j}^{x,y}(n-1)+{\mathrm{\τ}}_c;$

Wherein, ρ is pheromones evaporation rate；For the pheromones numerical value of i, j on path in (n-1)th iteration, τ_cFor positive constant.

Further, in described step (5), overall criterion refers to the Pheromone update that optimal path is carried out, particularly as follows: On path bulk information element being distributed to optimal solution in iteration each time；

The computing formula of described overall situation criterion is as follows:

${\mathrm{\τ}}^{x,y}\left(n\right)={\mathrm{\τ}}^{x,y}(n-1)+\mathrm{\ρ}\·\frac{j_{best}\left(n\right)}{j_{best}};$

Wherein,For the pheromones numerical value of i, j on path in (n-1)th iteration, ρ is pheromones evaporation rate, j_bestN () is the optimal solution solving after current iteration, j_bestIt is by the optimal result in front n iteration.

Further, in described step (6), method that system reliability is analyzed particularly as follows:

1) define the binary vector of block switch installation site and interconnection switch opening and closing state；List whole events that have a power failure Barrier；

2) for power-off fault each time, power failure position is determined by the chopper of searching of line upstream and downstream；

3) by power supply interrupted district is isolated to the chopper in line upstream downstream and the action of block switch；

4) classified according to user's requirement different to power supply reliability, by user type be divided into resident, commercial and Small amount straight power purchase user；

5) impact causing according to having a power failure is analyzed to the overall reliability of system.

Further, described step 1) in,

For the position of block switch can be installed, block switch is not installed in 0 this position of expression, 1 this position of expression Put and be mounted with block switch；

For the interconnection switch installed, with binary vector be 1, the 0 opening and closing shape representing interconnection switch respectively State.

Beneficial effects of the present invention:

The present invention passes through constructing system reliability, electric energy loss and block switch and installs and operating cost global optimum Multi-objective Reconfiguration of Distribution Network model, and using ant group algorithm optimize power distribution network switch quantity with position it is achieved that multiple target is whole The optimum power distribution network reconfiguration of body.

When carrying out systems reliability analysis, take into full account the impact to system reliability of the position of the switch of segmentation so that Analysis result is more accurately and reliably.

Practice result proves, method proposed by the present invention can greatly improve system by distributing block switch rationally Reliability, and system whole cost can be significantly reduced.

Brief description

Fig. 1 is assessment system reliability (fmea) flow chart in the present invention；

Fig. 2 is ant group algorithm of the present invention (aco) flow chart；

Fig. 3 distribution network system structure chart used by present invention test；

Fig. 4 is distribution network system structure chart after system reconfiguration.

Specific embodiment:

The present invention is described in detail below in conjunction with the accompanying drawings:

A kind of the invention discloses power distribution network reconfiguration Multipurpose Optimal Method containing block switch configuration, as shown in Fig. 2 bag Include following steps:

(1) input system topological relation, load data and dependability parameter；

(2) multiple target with operating cost global optimum installed by constructing system reliability, electric energy loss and block switch Power distribution network reconfiguration model；

The construction method of target power distribution network reconfiguration model is as follows:

First, each several part of objective function:

1) reliability index:

$ecost=\underset{t=1}{\overset{t}{\σ}}(\underset{b=1}{\overset{n_b}{\σ}}{\mathrm{\λ}}_b\·l_b\·(\underset{k=1}{\overset{{\mathrm{ct}}_b}{\σ}}\underset{j=1}{\overset{{\mathrm{nr}}_b}{\σ}}p\left(k.j\right)\·c_k\left(d,b\right)+\underset{k=1}{\overset{{\mathrm{ct}}_b}{\σ}}\underset{j=1}{\overset{{\mathrm{ns}}_b}{\σ}}p\left(k.j\right)\·c_k\left(d,b\right)\left)\right)\·{(1+ir)}^{t-1}\·{(1+dr)}^{-1(t-1)}$

In formula: t is the time cycle (year), n_bFor circuit sum, λ_bFor circuit failure rate (fault rate/kilometer-year), l_bFor line length, ct_bIt is when breaking down on circuit, the type sum of affected load, nr_bIt is when generation on circuit During fault, the load point persistently having a power failure is total, and p (k, j) is the average load of different user types under different load point, c_k(d, When b) being the power failure that lasting d hour is occurred on circuit b, the function that different load type suffers a loss because of power failure, ns_bFor line When breaking down in road, the load point number of brief power outage, ir is load annual average rate of increase, and dr is load annual rate of descent.

In above-mentioned reliability index, nr_bns_bRelevant with the number and location of block switch in system；(1+ir)^t-1With (1+dr)^-1(t-1)React the change of load level.

2) system transmission losses function:

$el=\underset{t=1}{\overset{t}{\σ}}\left(\underset{b=1}{\overset{n_b}{\σ}}8760\·i_{bt}^2\·r_b\·e_p\·{\left(1+dr\right)}^{-1(t-1)}\right);$

In formula: i_btFor flowing through the absolute value of line current, r_bFor the resistance of circuit, e_pFor electric energy average price.

3) switch expense, comprise switch purchase and mounting cost and follow-up maintenance operation expense:

$sc=cis+\underset{t=1}{\overset{t}{\σ}}mc\·n_s\·{(1+dr)}^{-1(t-1)};$

In formula: cis is the expense (unit $) installing a new block switch, n_sThe number of the block switch for newly installing, Mc safeguards and every annual operating cost (unit) for each block switch.

Then, the mathematical model of this method is:

Minj=ω₁·(ecost+sc)+ω₂·el (1)

Constraints: δ v_n≤δv_max(2)

i_b≤i_max(3)

$\underset{i=1}{\overset{n_i}{\σ}}{p}_i\≤{\mathrm{\δp}}_{max}---\left(4\right)$

$\underset{b=1}{\overset{n_b}{\π}}{k}_{n_b}=1---\left(5\right)$

In formula, ω₁For the weight of Reliability Index, it is a constant more than 0；ω₂For the weight of transmission losses, It is a constant more than 0, δ v_nFor the voltage drop-out value of node, δ v_maxThe maximum voltage drop-out value allowing for node, i_bFor The absolute value of electric current, i is flow through in circuit_maxFor maximum transmitted electric current, p in circuit_iFor the active power of user under load point, n_iFor Feeder line is powered lower user's intersection, δ p_maxFor transformer capacity,For ensureing that power distribution network is the state of open loop operation.

Above-mentioned optimization problem is the Solve problems of nonlinear combining functions, and available ant group algorithm (aco) solves.

(3) using ant group algorithm (aco), multi-objective Reconfiguration of Distribution Network model is solved.

First, in each iteration, system reliability adopts failure modes and effects analysis (fmea) Algorithm Analysis, that is, Determine power-off fault possible each time and analyze its impact to user.Particularly, block switch peace defined in analysis Holding position and the binary vector of interconnection switch opening and closing state, for can installing the position of block switch, 0 expression should On position, block switch is not installed, 1 this position of expression is mounted with block switch；For the interconnection switch installed, With binary vector be 1, the 0 opening and closing state representing interconnection switch respectively.

The block diagram of fema algorithm is as shown in figure 1, specifically comprise the following steps that

1) whole power-off faults are listed；

2) for power-off fault each time, power failure position is determined by the chopper of searching of line upstream and downstream；

3) by power supply interrupted district is isolated to the chopper in line upstream downstream and the action of block switch；

4) classified according to user's requirement different to power supply reliability, user type can be divided into resident, commercialization And small amount straight power purchase user；

5) pass through the reliability of the power supply reliability of the dissimilar user of impact analysis causing and system entirety that has a power failure.

The block diagram of the ant group algorithm (aco) of model solution is as shown in Fig. 2 step is as follows:

1) initialize: the initial position of ant colony is all provided in " in family ", and on path, pheromone numerical value is a series of positive Constant；

2) ant colony scheduling: all of Formica fusca is from " " in family, according to status transition criterion, select the next stage is No by a certain path reach " at food ", wherein, status transition criterion is the function of pheromone on path.For example, in the x stage In the case of state i, Formica fusca selects the probability of next stage y state j as follows:

$p_{i,j}^{x,y}\left(n\right)=\frac{{\mathrm{\τ}}_{i,j}^{x,y}\left(n\right)}{\underset{h\&element;{\mathrm{\δ}}_{x,t}}{\σ}{\mathrm{\τ}}_{i,j}^{x,y}\left(n\right)}---\left(6\right)$

In formula,For pheromones level on path in nth iteration, δ_x,iFor the selectable total number of paths of ant colony.

3) assess object function: after all Formica fuscas all reach " at food ", the position of switch has determined out, and Object function (1) can also be calculated.In current iteration, if being unsatisfactory for the constraints of (2) (5) it is necessary to give up this Reconfiguration scheme；If constraints is all satisfied, just record the value of the object function after current iteration: j_best(n).And will Optimal result j in result of calculation after this iteration and above all of iterative calculation_bestCompare, if nth iteration Result of calculation is better than j_best, then update optimal result, make j_best=j_best(n)；If j_best(n)>j_best, then still keep original Optimum reconfiguration scheme；

4) fresh information prime number value: the purpose of this step is to find optimal solution by higher pheromone level.Update letter Breath prime number value will follow two criterions:

1. local criterion: the pheromone of distribution in the range of whole search space, with the increase of iterationses, its numerical value It is gradually reduced, to ensure that path gradually weakens to the captivation of ant colony.The computing formula of local criterion is as follows:

${\mathrm{\τ}}_{i,j}^{x,y}\left(n\right)=(1-\mathrm{\ρ})\·{\mathrm{\τ}}_{i,j}^{x,y}(n-1)+{\mathrm{\τ}}_c---\left(7\right)$

In formula, ρ is pheromone evaporation rate, is one between the number between 1 and 0；For (n-1)th iteration Pheromone numerical value on middle path；τ_cFor positive constant.

2. overall criterion: global information element replacement criteria is, in iteration each time, bulk information element has been distributed to optimum On the path of solution.Formula is as follows:

${\mathrm{\τ}}^{x,y}\left(n\right)={\mathrm{\τ}}^{x,y}(n-1)+\mathrm{\ρ}\·\frac{j_{best}\left(n\right)}{j_{best}}---\left(8\right)$

Behind application local and global information element replacement criteria, maximum-minimum ant group algorithm is just integrated into following In equation:

In formula, τ_maxFor the pheromone greatest measure allowing on path；

τ_minFor the pheromone minimum value allowing on path.

Boundary to pheromones setting value minima is it is ensured that the pheromone numerical value on each paths is all greater than 0, algorithm so can be avoided only to find optimal solution in local.

5) move in circles calculating, until reaching maximum iteration time set in advance.

Obtain the optimal solution of multi-objective Reconfiguration of Distribution Network model；Optimize quantity and the position of power distribution network switch according to optimal solution Put it is achieved that the power distribution network reconfiguration of multiple target total optimization.

As a example distribution network system used by test shown in below by Fig. 3, effect of the present invention is verified.Table 1 is to correspond to User data.

The corresponding user data of table 1 distribution network system

Using the inventive method, distribution network system is reconstructed, the distribution network system structure after reconstruct is as shown in Figure 4.

The Comparative result obtaining before and after system reconfiguration is as shown in table 2.

Comparative result before and after the reconstruct of table 2 distribution network system

Table 2 shows, the scheme of system optimization reconstruct needs to increase block switch 18, and this can improve system reliability, makes Index ecost drops to $ 226610 by $ 3363900, and system loss drops to $ 867400 by $ 1000800, and system integrally spends $ 1193100 is dropped to by $ 4364700, have dropped 72.66%.As can be seen here, method proposed by the present invention can be by optimizing Configuration block switch, greatly improves system reliability, and can be significantly reduced system whole cost.

Although the above-mentioned accompanying drawing that combines is described to the specific embodiment of the present invention, not model is protected to the present invention The restriction enclosed, one of ordinary skill in the art should be understood that on the basis of technical scheme, and those skilled in the art are not Need to pay the various modifications that creative work can make or deformation still within protection scope of the present invention.

Claims (9)

1. a kind of power distribution network reconfiguration Multipurpose Optimal Method containing block switch configuration, is characterized in that, comprise the following steps:

(1) input system topological relation, load data and dependability parameter；

(2) the multiple target distribution with operating cost global optimum installed by constructing system reliability, electric energy loss and block switch Net reconstruction model；

(3) initialize ant group algorithm parameter in search space, initialize iterationses n=1；

(4) according to the pheromone level on path, ant colony is allowed to select path to reach " at food "；Obtain the location column of system switching Table, and then change system topological relation；

(5) all paths passed by according to ant colony, draw the optimal solution of object function in current iteration, and according to local and the overall situation Criterion fresh information prime number value；The optimal solution of object function empty position of the switch list in storage current iteration；

(6) installed and operating cost according to systems reliability analysis, electric energy loss amount and block switch, current iteration is obtained The optimal solution that obtains with front an iteration of the optimal solution of object function be compared, update optimal solution；

(7) loop iteration, until iterationses reach maximum iteration time set in advance or target does not further optimize；? Optimal solution to multi-objective Reconfiguration of Distribution Network model；

(8) quantity and the position of power distribution network switch are optimized it is achieved that the power distribution network reconfiguration of multiple target total optimization according to optimal solution.

2. a kind of power distribution network reconfiguration Multipurpose Optimal Method containing block switch configuration as claimed in claim 1, is characterized in that, In described step (2), the multi-objective Reconfiguration of Distribution Network model of structure particularly as follows:

Minj=ω₁·(ecost+sc)+ω₂·el；

Constraints is:

δv_n≤δv_max；

i_b≤i_max；

$\underset{i=1}{\overset{n_i}{\σ}}{p}_i\≤{\mathrm{\δp}}_{max};$

$\underset{b=1}{\overset{n_b}{\π}}{k}_{n_b}=1;$

Wherein, ω₁For the weight of Reliability Index, ω₂For the weight of transmission losses, ecost is Reliability Index letter Number, sc is switch cost function, and el is system transmission losses function；δv_nFor the voltage drop-out value of node, δ v_maxPermit for node The maximum voltage drop-out value permitted, i_bThe absolute value of electric current, i is flow through in circuit_maxFor maximum transmitted electric current, p in circuit_iFor load point The active power of lower user, n_iPower lower user's intersection for feeder line, δ p_maxFor transformer capacity,For ensureing that power distribution network is out The state of inscription of loop.

3. a kind of power distribution network reconfiguration Multipurpose Optimal Method containing block switch configuration as claimed in claim 2, is characterized in that, Described Reliability Index function particularly as follows:

$ecost=\underset{t=1}{\overset{t}{\σ}}\left(\underset{b=1}{\overset{n_b}{\σ}}{\mathrm{\λ}}_b\·l_b\·\left(\underset{k=1}{\overset{{\mathrm{ct}}_b}{\σ}}\underset{j=1}{\overset{{\mathrm{nr}}_b}{\σ}}p\left(k.j\right)\·c_k\left(d,b\right)+\underset{k=1}{\overset{{\mathrm{ct}}_b}{\σ}}\underset{j=1}{\overset{{\mathrm{ns}}_b}{\σ}}p\left(k.j\right)\·c_k\left(d,b\right)\right)\right)\·{\left(1+ir\right)}^{t-1}\·{\left(1+dr\right)}^{-1\left(t-1\right)};$

Wherein, t is the time cycle, n_bFor circuit sum, λ_bFor circuit failure rate, l_bFor line length, ct_bIt is when on circuit When breaking down, the type sum of affected load, nr_bIt is when breaking down on circuit, the load point persistently having a power failure is total Number, p (k, j) is the average load of different user types under different load point, c_k(d, b) is to occur on circuit b to continue d hour Power failure when, the function that different load type suffers a loss because of power failure, ns_bDuring for line failure, brief power outage negative Lotus point number, ir is load annual average rate of increase, and dr is load annual rate of descent.

4. a kind of power distribution network reconfiguration Multipurpose Optimal Method containing block switch configuration as claimed in claim 2, is characterized in that, Described switch cost function particularly as follows:

$sc=cis+\underset{t=1}{\overset{t}{\σ}}mc\·n_s\·{\left(1+dr\right)}^{-1\left(t-1\right)};$

Wherein, cis is the expense installing a new block switch, n_sFor the number of the new block switch installed, mc is each segmentation Switch is safeguarded and every annual operating cost, and dr is load annual rate of descent.

5. a kind of power distribution network reconfiguration Multipurpose Optimal Method containing block switch configuration as claimed in claim 2, is characterized in that, Described system transmission losses function particularly as follows:

$el=\underset{t=1}{\overset{t}{\σ}}(\underset{b=1}{\overset{n_b}{\σ}}8760\·i_{bt}^2\·r_b\·e_p\·{\left(1+dr\right)}^{-1\left(t-1\right)});$

Wherein, i_btFor flowing through the absolute value of line current, r_bFor the resistance of circuit, e_pFor electric energy average price, dr put down for load year All rates of descent.

6. a kind of power distribution network reconfiguration Multipurpose Optimal Method containing block switch configuration as claimed in claim 1, is characterized in that, Local criterion in described step (5) particularly as follows: in the range of whole search space distribution pheromones, with the increasing of iterationses Plus, its numerical value will be gradually reduced, to ensure that path gradually weakens to the captivation of ant colony；

The computing formula of described local criterion is as follows:

${\mathrm{\τ}}_{i,j}^{x,y}\left(n\right)=(1-\mathrm{\ρ})\·{\mathrm{\τ}}_{i,j}^{x,y}\left(n-1\right)+{\mathrm{\τ}}_c;$

Wherein, ρ is pheromones evaporation rate；For the pheromones numerical value on path in (n-1)th iteration, τ_cFor positive Constant.

7. a kind of power distribution network reconfiguration Multipurpose Optimal Method containing block switch configuration as claimed in claim 1, is characterized in that, Overall criterion in described step (5) particularly as follows: in iteration each time, bulk information element is distributed to optimal solution path on；

The computing formula of described overall situation criterion is as follows:

${\mathrm{\τ}}^{x,y}\left(n\right)={\mathrm{\τ}}^{x,y}(n-1)+\mathrm{\ρ}\·\frac{j_{best}\left(n\right)}{j_{best}};$

Wherein,For the pheromones numerical value of i, j on path in (n-1)th iteration, ρ is pheromones evaporation rate, j_best N () is the optimal solution solving after current iteration, j_bestIt is by the optimal result in front n iteration.

8. a kind of power distribution network reconfiguration Multipurpose Optimal Method containing block switch configuration as claimed in claim 1, is characterized in that, In described step (6), method that system reliability is analyzed particularly as follows:

1) define the binary vector of block switch installation site and interconnection switch opening and closing state；List whole power-off faults；

2) for power-off fault each time, power failure position is determined by the chopper of searching of line upstream and downstream；

3) by power supply interrupted district is isolated to the chopper in line upstream downstream and the action of block switch；

4) classified according to user's requirement different to power supply reliability, user type is divided into resident, commercial and small amount Straight power purchase user；

5) impact causing according to having a power failure is analyzed to the overall reliability of system.

9. a kind of power distribution network reconfiguration Multipurpose Optimal Method containing block switch configuration as claimed in claim 8, is characterized in that, Described step 1) in,

For the position of block switch can be installed, block switch is not installed in 0 this position of expression, 1 represents on this position It is mounted with block switch；

For the interconnection switch installed, with binary vector be 1, the 0 opening and closing state representing interconnection switch respectively.