CN104200263B - Power distribution network route planning method based on tabu differential evolution and GIS (Geographic Information System) - Google Patents
Power distribution network route planning method based on tabu differential evolution and GIS (Geographic Information System) Download PDFInfo
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Abstract
The invention discloses a power distribution network route planning method based on tabu differential evolution and a GIS (Geographic Information System). Equal allotment capital recovery calculation is performed under the consideration of the time value of capital, a model is established specific to the aims of minimal annul investment and minimal running maintenance cost, a tabu differential evolution algorithm is put forward on the basis of the model, an obtained optimal solution is decoded, and a planned route is drawn on an electric power GIS platform according to the route number obtained by decoding. According to the method, a non-optimal solution is allowed to be accepted by using tobu search, the problem the differential evolution algorithm tends to falling into local optimum easily is solved by improving the capability of jump-out local optimum, and the planning process of a power distribution network line has the advantages of interactivity, more intuitive planning result and higher flexibility in adjustment of a planning scheme by using the electric power GIS system.
Description
Technical field
The present invention relates to a kind of geographic information data process, system for distribution network of power winding thread circuit planning, more particularly to,
It is a kind of based on taboo differential evolution and GIS distribution network layout of roads method.
Background technology
Distribution network layout of roads is referred on the basis of electrical network As-Is analysis and future load forecast of distribution, in transformer station
After the work of addressing constant volume is completed, seek an optimum cabling scenario that can meet future customer capacity and the quality of power supply.
In recent years, using Meta-heurist algorithm (such as genetic algorithm, simulated annealing, TABU search, ant group algorithm
Deng) solve the problems, such as to achieve the achievement of some protrusions in the global optimizing of distribution network layout of roads.As Wang Jinfeng et al. is proposed
A kind of improved adaptive GA-IAGA, in Optimized model consider track investment the time value, and using the spanning tree of alternative network as
Initial solution, it is to avoid the drawbacks of solving speed is slower when randomly generating initial feasible solution, the thought design for using for reference branch exchange is miscellaneous
Hand over operator and mutation operator, it is to avoid radioactivity checking process;Gao Weixin et al. is proposed load point as food, calculated using ant colony
Method carries out layout of roads.Additionally, continuous with GIS (Geographic Information System, GIS-Geographic Information System)
Development and progress, also bring new approaches to distribution network layout of roads.Such as soup is red defend et al. propose it is a kind of based on GIS's
Distribution system planning, using the spatial analysis capacity of GIS, can effective avoiding obstacles.But current most of distribution networks
The heuritic approach that layout of roads is adopted is easily trapped into locally optimal solution seldom in combination with GIS, and arithmetic result is not straight enough
See and be also easy to produce invalid branch road, when large-scale distribution network layout of roads is solved, the problems such as efficiency of algorithm is not ideal enough.Cause
This, is how effectively by global optimizing algorithm in combination with optimizing algorithm, how effectively by optimizing algorithm in combination with GIS,
It is major issue that distribution network layout of roads faces.
The content of the invention
In order to overcome existing be easily trapped into local optimum, algorithm for existing distribution network layout of roads method to be also easy to produce
The deficiency of invalid branch road, the present invention propose it is a kind of be prevented effectively from be absorbed in local optimum, reliability it is good based on taboo difference enter
Change the distribution network layout of roads method with GIS.
The technical solution adopted for the present invention to solve the technical problems is:
It is a kind of based on taboo differential evolution and GIS distribution network layout of roads method, comprise the following steps:
A1, according to substation locating and sizing and the result of future load forecast of distribution, create load on electric power GIS platform
Point, transformer station and branch road to be selected, built branch road element information, and set up the topology rule in corresponding point-point, point-line, line-face
Then;
A2, the element information to creating carry out pretreatment:All load points and transformer substation sequence are numbered, all to be selected
Road and built branch road serial number, and start of record peripheral node numbering;Relief area is generated for geographic barrier, enters row buffer
Analysis, finds out the line corridor for being not suitable for the construction of line;
A3, consideration time value on assets, pay separately capital recovery and calculate by single-candidate, with year investment and operation and maintenance cost most
It is little for target, object function such as formula (1):
In formula:S1、S2, S be respectively newly-built sets of lines, built sets of lines and total line collection;ω be year equivalence recovery coefficient, λ
For the percentage ratio that maintenance, depreciation account for investment cost;liIt is the length of circuit i, f (Di) it is that line footpath is DiCircuit unit length
Cost, XiFor the decision variable on i-th line road, the circuit is selected as feeder line branch road, then XiTake 1, otherwise take 0;g(Di) it is line
Footpath is DiCircuit resistivity;PiIt is circuit i by power, UNFor rated voltage;τmaxMaximum loss time in year, d is single
Position electricity price;
In differential evolution algorithm, dimension D is branch road quantity N to be selectedline, population quantity NP=10*D, mutation operator F be with
The string of binary characters that machine is produced, crossover operator CR takes 0.1, and end condition is the optimum for obtaining after tabu search algorithm
It is individual identical with the optimum individual fitness before tabu search algorithm is switched into;Switching condition into tabu search algorithm is
Iteration exceedes some generations and optimum individual continuous some generations do not change;The condition for exiting tabu search algorithm exceedes for step-length
In some steps and optimum individual continuous some generations, do not change;
A4, reading element information, generating algorithm initial population, and initial population is evaluated;
A5, judge whether to reach end condition, if so, then evolving terminates, using optimized individual as solution output, go to step
A13;If it is not, then continue algorithm, into step A6;
A6, enter row variation and crossover operation, carry out constraints verification, replacement is unsatisfactory for the individuality for constraining, and obtains interim
Population, evaluates interim population;
A7, selection operation is carried out, obtain new population, if so, evaluation algorithm switching condition then enters step A8, be switched into
Enter Tabu (TABU search) algorithm;If it is not, then going to step A5;
A8, using optimized individual as initial solution incoming Tabu (TABU search) algorithm, put taboo list for sky;
Whether A9, evaluation algorithm switching condition meet, and if so, then go to step A5, exit Tabu (TABU search) algorithm;If
It is no, then into step A10;
A10, the field function generation all spectra solution for utilizing current solution, therefrom take some solutions as candidate solution;
A11, judge candidate solution whether aspiration criterion meets, if so, then replaced with the optimum state y for meeting aspiration criterion
X becomes new current solution, and is replaced earliest into the taboo object of taboo list with the corresponding taboo objects of y, while being replaced most with y
Good solution, then goes to step A9;If it is not, then entering step A12;
A12, the taboo attribute for judging the corresponding each object of candidate solution, select candidate solution to concentrate non-taboo object corresponding most
Good state is new current solution, while replaced earliest into the taboo object elements of taboo list with corresponding taboo object,
Then A9 is gone to step;
A13, the optimal solution that algorithm is obtained is decoded, the circuit number obtained according to decoding is on electric power GIS platform
Draw out planning circuit.
Wherein, DE (Differential Evolution, differential evolution) algorithm adopts binary coding, i.e. character string every
One upper " 1 " represents that the branch road of corresponding numbering is selected, and " 0 " represents that the branch road of corresponding numbering is not chosen.
Further, in step A4, read load point positional information and payload, the positional information of transformer station,
Branch road to be selected, built branch road.The random length that generates is NlineString of binary characters, and guarantee the quantity of " 1 " in character string
For Nnode(number of nodes), the function for applying mechanically (1) formula calculates each individual target function value.
Further, in step A6, mutation operation is to each target individual Xi,G, i=1,2 ..., NP, according to formula
(2) variation is produced individual.Wherein, randomly selected sequence number r1, r2, r3It is different, and r1, r2, r3With target individual sequence number i
It is different.Arithmetic operator is logical operator, i.e. X in formulaR2, GAnd Xr3,GFirst logic is carried out or, acquired results and mutation operator F
Carry out logic XOR, finally again with XR1, GLogic and operation is carried out, variation is obtained individual.
Then carry out crossover operation according to formula (3), (4), (5), wherein randb (j) be between [0,1] it is random generate the
J estimated value, rnbr (i) is a randomly selected sequence.
Ui,G+1=(U1i,G+1,U2i,G+1,…,UDi,G+1) (3)
(i=1,2 ..., NP, j=1,2 ..., D) (5)
Connectedness, radioactivity, node voltage constraint, capacity-constrained verification are carried out to individuality, if constraint is unsatisfactory for again
The individuality for randomly generating meet the constraint is substituted.
Further, in step A7, the individual mesh with relevant position in current population will be tested according to greedy criterion
Mark individuality is compared, and takes fitness less individual as of future generation individual.Judge the switching condition into Tabu algorithms, if
Satisfaction then carries out optimizing using current optimized individual as the incoming Tabu algorithms of initial individuals, to avoid being absorbed in locally optimal solution.
In step A10, the encoded radio on any two position in initial solution sequence is exchanged at random, produce NlineIndividual time
Choosing solution.
Beneficial effects of the present invention are mainly manifested in:The present invention solves single calculation when distribution network layout of roads is carried out
Method is easily absorbed in the problem of local optimum, and the analysis of network with reference to GIS, buffer finish blasting optimized algorithm process, makes arithmetic result more
Intuitively.
Description of the drawings
Fig. 1 is the flow chart of the distribution network layout of roads method based on taboo differential evolution and GIS.
Fig. 2 is power transformation station location and load point distribution.
Fig. 3 is initial distribution network.
Fig. 4 is carried out the optimization distribution line obtained after algorithm.
Specific embodiment
Below in conjunction with the accompanying drawings the invention will be further described.
It is a kind of based on the distribution network layout of roads method for avoiding differential evolution and GIS with reference to Fig. 1~Fig. 4, such as Fig. 1 institutes
Show, comprise the following steps:
A1, according to substation locating and sizing and future load forecast of distribution result, create relevant factor in electric power GIS platform
Information;
A2, the element information to creating carry out pretreatment;
A3, determine object function, the corresponding control parameter of algorithm and the specific strategy for being adopted are set;
A4, reading element information, generating algorithm initial population, and initial population is evaluated;
A5, judge whether to reach end condition, if so, then evolving terminates, using optimized individual as solution output, go to step
A13;If it is not, then continue algorithm, into step A6;
A6, enter row variation and crossover operation, carry out constraints verification, replacement is unsatisfactory for the individuality for constraining, and obtains interim
Population, evaluates interim population;
A7, selection operation is carried out, obtain new population, if so, evaluation algorithm switching condition then enters step A8, be switched into
Enter Tabu algorithms;If it is not, then going to step A5;
A8, using optimized individual as the incoming Tabu algorithms of initial solution, put taboo list for sky;
Whether A9, evaluation algorithm switching condition meet, and if so, then go to step A5, exit Tabu algorithms;If it is not, then entering
Step A10;
A10, the field function generation all spectra solution for utilizing current solution, therefrom take some solutions as candidate solution;
A11, judge candidate solution whether aspiration criterion meets, if so, then replaced with the optimum state y for meeting aspiration criterion
X becomes new current solution, and is replaced earliest into the taboo object of taboo list with the corresponding taboo objects of y, while being replaced most with y
Good solution, then goes to step A9;If it is not, then entering step A12;
A12, the taboo attribute for judging the corresponding each object of candidate solution, select candidate solution to concentrate non-taboo object corresponding most
Good state is new current solution, while replaced earliest into the taboo object elements of taboo list with corresponding taboo object,
Then A9 is gone to step;
A13, the optimal solution that algorithm is obtained is decoded, the circuit number obtained according to decoding is on electric power GIS platform
Draw out planning circuit.
Wherein, DE algorithms adopt binary coding, i.e. character string on each " 1 " represent that the branch road of corresponding numbering is selected
In, " 0 " represents that the branch road of corresponding numbering is not chosen.
Described method, wherein in step A1, according to substation locating and sizing and the result of future load forecast of distribution,
Create load point, transformer station and branch road to be selected, built branch road element information on electric power GIS platform, and set up corresponding point-
Point, point-line, the topology rule in line-face.
Described method, wherein in step A2, all nodes (including load point and transformer station) serial number owns
Branch road (including branch road to be selected and built branch road) serial number, and start of record peripheral node numbering;Generate for geographic barrier
Relief area, carries out buffer zone analysis, finds out the line corridor for being not suitable for the construction of line, reduces algorithm dimension space, reduces blindly
Search.
Described method, wherein in step A3, Optimized model considers time value on assets, pays separately capital and returns by single-candidate
Receive and calculate, with year investment and the minimum target of operation and maintenance cost, object function such as formula (6).
In formula:S1、S2, S be respectively newly-built sets of lines, built sets of lines and total line collection;ω be year equivalence recovery coefficient, λ
For the percentage ratio that maintenance, depreciation account for investment cost;liIt is the length of circuit i, f (Di) it is that line footpath is DiCircuit unit length
Cost, XiDecision variable for i-th line road (selects the circuit as feeder line branch road, then Xi1 is taken, otherwise is taken 0);g(Di) it is line
Footpath is DiCircuit resistivity;PiIt is circuit i by power, UNFor rated voltage;τmaxMaximum loss time in year, d is single
Position electricity price.In DE (Differential Evolution, differential evolution) algorithm, dimension D is branch road quantity N to be selectedline, population
Quantity NP=10*D, mutation operator F is the string of binary characters for randomly generating, and crossover operator CR takes 0.1, end condition be through
The optimum individual for obtaining after Tabu (TABU search) algorithm is identical with the optimum individual fitness before Tabu algorithms is switched into.
DE algorithms are that iteration exceedes some generations and optimum individual continuous some generations do not change into the switching condition of Tabu;Exit
The condition of Tabu algorithms is that step-length exceedes some steps and optimum individual continuous some generations do not change;
Described method, wherein in step A4, reading positional information and payload, the position of transformer station of load point
Information, branch road to be selected, built branch road.The random length that generates is NlineString of binary characters, and guarantee " 1 " in character string
Quantity is Nnode(number of nodes), the function for applying mechanically (1) formula calculates each individual target function value.
Described method, wherein in step A6, mutation operation is to each target individual Xi,G, i=1,2 ..., NP, according to
It is individual that formula (7) produces variation.Wherein, randomly selected sequence number r1, r2, r3It is different, and r1, r2, r3With target individual sequence number i
Also it is different.Arithmetic operator is logical operator, i.e. X in formulaR2, GAnd XR3, GFirst logic is carried out or, acquired results and mutation operator F
Carry out logic XOR, finally again with XR1, GLogic and operation is carried out, variation is obtained individual.
Then crossover operation is carried out according to formula (8), (9), (10), wherein randb (j) is random between [0,1] generation
J-th estimated value, rnbr (i) is a randomly selected sequence.
Ui,G+1=(U1i,G+1,U2i,G+1,…,UDi,G+1) (8)
(i=1,2 ..., NP, j=1,2 ..., D) (10)
Connectedness, radioactivity, node voltage constraint, capacity-constrained verification are carried out to individuality, if constraint is unsatisfactory for again
The individuality for randomly generating meet the constraint is substituted.
Described method, wherein in step A7, will test individual with relevant position in current population according to greedy criterion
Target individual be compared, take fitness less individual as of future generation individual.Judge the switching bar into Tabu algorithms
Part, carries out optimizing, to avoid being absorbed in local optimum if meeting using current optimized individual as the incoming Tabu algorithms of initial individuals
Solution.
Described method, wherein in step A10, the coding on any two position in initial solution sequence is exchanged at random
Value, produces NlineIndividual candidate solution.
Example:The present embodiment is one and has 37 nodes, 2 existing branch roads and 57 10kv distribution that can extend branch road
The real system of net, electric power GIS platform manages GIS information systeies using electric lines of force, and the system puts on Shandong Yantai and other places
On probation, operation reflection is good.
Node data as shown in table 1, capacity 0 for transformer station.DE algorithms are set to into the switching condition of Tabu algorithms
More than 100 generations and continuous 20 generation optimal solution does not change;The condition setting for exiting Tabu algorithms is more than 40 steps and continuous 20
Step optimal solution does not change.Circuit maximum capacity is limited and is set to 5000kw.
Node key element such as Fig. 2 is created on electric lines of force management GIS information system platforms, capacity 0 for transformer station in the middle part of figure
(hollow dots), remaining is load point (solid dot), creates circuit key element such as Fig. 3, and to extend circuit, dotted line is to build to solid line
Circuit.Carry out after computing using algorithm, obtain the distribution line cabling scenario such as Fig. 4, circuit mounting node details are shown in Table 2.
Table 1
Table 2
Can be seen that every loop line road from above-mentioned wiring result has the supply district of clear and non-overlapping copies, per loop line road
The load capacity of mounting also meets the restriction of circuit maximum capacity, it is seen that its result is rational, and meets engineering reality.This reality
Apply example and show that method of the present invention is more effectively to calculate a feasible wiring side under certain calculation scale
Case, and intuitively reflect result on electric power GIS platform, so as to improve planning personnel's work efficiency.
Claims (5)
1. a kind of based on the distribution network layout of roads method for avoiding differential evolution and GIS, it is characterised in that:The distribution network
Layout of roads method is comprised the following steps:
A1, according to substation locating and sizing and the result of future load forecast of distribution, on electric power GIS platform create load point,
Transformer station and branch road to be selected, built branch road element information, and set up corresponding point-point, point-line, the topology rule in line-face;
A2, the element information to creating carry out pretreatment:All load points and transformer substation sequence are numbered, all branch roads to be selected and
Built branch road serial number, and start of record peripheral node numbering;Relief area is generated for geographic barrier, enters row buffer point
Analysis, finds out the line corridor for being not suitable for the construction of line;
A3, consideration time value on assets, pay separately capital recovery and calculate by single-candidate, minimum with year investment and operation and maintenance cost
Target, object function such as formula (1):
In formula:S1、S2, S be respectively newly-built sets of lines, built sets of lines and total line collection;ω is year equivalence recovery coefficient, and λ is dimension
Repair, depreciation accounts for the percentage ratio of investment cost;liIt is the length of circuit i, f (Di) it is that line footpath is DiCircuit unit length cost,
XiFor the decision variable on i-th line road, the circuit is selected as feeder line branch road, then XiTake 1, otherwise take 0;g(Di) it is that line footpath is Di
Circuit resistivity;PiIt is circuit i by power, UNFor rated voltage;τmaxMaximum loss time in year, d is unit electricity price;
In differential evolution algorithm, dimension D is branch road quantity N to be selectedline, population quantity NP=10*D, mutation operator F is random product
Raw string of binary characters, crossover operator CR takes 0.1, and end condition is the optimum individual for obtaining after tabu search algorithm
It is identical with the optimum individual fitness before tabu search algorithm is switched into;Switching condition into tabu search algorithm is iteration
More than some generations and optimum individual continuous some generations do not change;The condition for exiting tabu search algorithm is step-length more than some
Walk and optimum individual continuous some generations do not change;
A4, reading element information, generating algorithm initial population, and initial population is evaluated;
A5, judge whether to reach end condition, if so, then evolving terminates, using optimized individual as solution output, go to step A13;If
It is no, then continue algorithm, into step A6;
A6, enter row variation and crossover operation, carry out constraints verification, replacement is unsatisfactory for the individuality for constraining, obtains interim population,
Interim population is evaluated;
A7, selection operation is carried out, obtain new population, if so, evaluation algorithm switching condition then enters step A8, switch into taboo
Avoid searching algorithm;If it is not, then going to step A5;
A8, using optimized individual as the incoming tabu search algorithm of initial solution, put taboo list for sky;
Whether A9, evaluation algorithm switching condition meet, and if so, then go to step A5, exit tabu search algorithm;If it is not, then entering
Step A10;
A10, the field function generation all spectra solution for utilizing current solution, therefrom take some solutions as candidate solution;
A11, judge candidate solution whether aspiration criterion meets, if so, then with the optimum state y for meeting aspiration criterion replace x into
For new current solution, and replaced earliest into the taboo object of taboo list with the corresponding taboo objects of y, while replacing optimal with y
Solution, then goes to step A9;If it is not, then entering step A12;
A12, the taboo attribute for judging the corresponding each object of candidate solution, select candidate solution to concentrate the corresponding optimal shape of non-taboo object
State is new current solution, while the taboo object elements for entering taboo list earliest are replaced with corresponding taboo object, then
Go to step A9;
A13, the optimal solution to obtaining are decoded, and rule are drawn out on electric power GIS platform according to the circuit number that decoding is obtained
Line road.
2. as claimed in claim 1 a kind of based on the distribution network layout of roads method for avoiding differential evolution and GIS, its feature
It is:In step A4, positional information and payload, the positional information of transformer station, the branch road to be selected, of load point is read
Branch road is built, the random length that generates is NlineString of binary characters, and guarantee that the quantity of " 1 " in character string is number of nodes
Nnode, the function for applying mechanically (1) formula calculates each individual target function value.
3. as claimed in claim 1 or 2 a kind of based on the distribution network layout of roads method for avoiding differential evolution and GIS, its
It is characterised by:In step A6, mutation operation is to each target individual Xi,G, i=1,2 ..., NP produce change according to formula (2)
Different individuality, wherein, randomly selected sequence number r1, r2, r3It is different, and r1, r2, r3It is also different from target individual sequence number i, in formula
Arithmetic operator is logical operator, i.e. XR2, GAnd XR3, GFirst carry out logic or, acquired results to carry out logic with mutation operator F different
Or computing, finally again with XR1, GLogic and operation is carried out, variation is obtained individual;
Then crossover operation is carried out according to formula (3), (4), (5), wherein randb (j) is random j-th for generating between [0,1]
Estimated value, rnbr (i) is a randomly selected sequence;
Ui,G+1=(U1i,G+1,U2i,G+1,…,UDi,G+1) (3)
(i=1,2 ..., NP, j=1,2 ..., D) (5)
Connectedness, radioactivity, node voltage constraint, capacity-constrained verification are carried out to individuality, it is again random if constraint is unsatisfactory for
The individuality for producing meet the constraint is substituted.
4. as claimed in claim 1 or 2 a kind of based on the distribution network layout of roads method for avoiding differential evolution and GIS, its
It is characterised by:In step A7, enter the individual target individual with relevant position in current population is tested according to greedy criterion
Row compares, and takes the less individuality of fitness as of future generation individual, judges the switching condition for entering Tabu algorithms, will if meeting
Current optimized individual carries out optimizing as the incoming Tabu algorithms of initial individuals, to avoid being absorbed in locally optimal solution.
5. as claimed in claim 1 or 2 a kind of based on the distribution network layout of roads method for avoiding differential evolution and GIS, its
It is characterised by:In step A10, the encoded radio on any two position in initial solution sequence is exchanged at random, produce NlineIt is individual
Candidate solution.
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