CN103036234B - Power distribution network anti-error optimization method - Google Patents
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- Y—GENERAL 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
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
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- Y—GENERAL 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Abstract
The invention provides a power distribution network anti-error optimization method. The power distribution network anti-error optimization method is characterized by comprising the following steps: 1, dividing a power distribution network topological system into a plurality of independent units according to a current running state, wherein each unit is provided with only one off switch and the number of the units is equal to the number of switches with off states; 2, performing real number encoding on the on-off state of each unit by a switch exchange algorithm, and connecting all the units into a chromosome; and 3, through a set objective function and set constraints, calculating the network by a chaos genetic algorithm so as to obtain an optimal solution. The invention has the advantages as follows: the power distribution network anti-error optimization method has certain theoretical study value and certain practical value; on the premise of meeting security constraints, the running way of a distributing line is changed by a switch operating method and the like, so that branch circuit overload and voltage out-of-limit are eliminated, feeder load is balanced and network loss is minimum; and the power distribution network anti-error optimization method has an obvious advantage in network loss improvement and convergence rate and is more suitable for on-site real-time application.
Description
Technical field
The present invention proposes the anti-error optimization method of a kind of power distribution network.The method combines branch exchange algorithm and Chaos Genetic Algorithm, is meeting under the prerequisite of voltage and Line Flow constraint, and in anti-error optimization, the state of block switch and interconnection switch is determined by genetic algorithm.Then the network loss of computing network and desired on-off times in different networks, the scheme finally with minimum network loss, minimal switches number of times is optimal case.
Background technology
The research of the anti-error optimization method of power distribution network was risen in the eighties of last century later stage eighties, because it receives many scholars' concern in the important function that reduces network loss and improve the aspects such as system safety.Early stage For Distribution Networks Reconfiguration is mainly the reconstruction of research distribution planning stage.Along with the progressively intensification to power distribution network reconfiguration understanding, scholars find to add network reconfiguration not only economical and technical feasible in electrical power distribution automatization system, and can greatly optimize the operation of distribution system.
Power distribution network when normal operation radially, by network structure, determine that tree is not unique, make power distribution network determine that by network structure tree-shaped operational mode is not unique, switch folding condition can form multiple combination, and arbitrary combination all forms a kind of operational mode.Although interconnection switch disconnects when normal operation, to maintain the tree-shaped running status of Radiation of system, its existence makes the webbed structure of system.The essence of distribution reconstruct is exactly to meet under certain constraints, by changing on off state in network, optimize the network configuration of power distribution network, thereby improve the trend distribution of distribution system, ideal situation is to reach optimal load flow to distribute, and makes distribution system loss minimization or other indexs optimum.
Different operational mode correspondences different trends and is distributed, and causes different via net loss, so just exists the problem of economical operation, in forming the combination of tree-shaped operational mode, have a kind of combination, by the mode of this combination, move, a certain index of network is optimum.Different operational mode correspondences different trend distributions, via net loss and network operation reliability, thereby produced the problem that network configuration is optimized, for the multiple radial operational mode of distribution, exist a kind of operational mode can make a certain index of network optimum.
In actual power distribution network, number of switches is huge, so the anti-error optimization of distribution network is extensive a, MIXED INTEGER, multiple target, nonlinear combinatorial optimization problem.One of method of processing multi-objective optimization question is exactly dimensionality reduction optimization method, selects a main target function, and other target is processed as constraint.
Existing algorithm is target function mainly with loss minimization greatly, is meeting under various service conditionss, and the anti-error optimization of power distribution network that the loss minimization of take is target function is still a non-linear hybrid optimization problem.Due to the nonlinear characteristic of the anti-error optimization of power distribution network, the iteration being optimized each time all needs to carry out the calculating of primary distribution trend, and continuous distribution power system load flow calculation needs a large amount of computing times.In order to improve computational speed, assurance draws the Distributing network structure of global optimum or suboptimum, main reconstruction and optimization algorithm has as follows at present: branch exchange method (Branch Exchange Method, BEM), optimal flow pattern (Optimal Flow Pattern, OFP), expert system approach (Expert System, ES), artificial neural network method (Artificial Neural Networks, ANN), simulated annealing (Simulated Annealing, SA), genetic algorithm (Genetic Algorithm, GA), tabu search algorithm (Tabu Search, TS) etc.
Radially, radial structure is not unique for power distribution network topological structure, makes power distribution network determine that by network structure tree-shaped operational mode is not unique, and switch folding condition can form multiple combination, and arbitrary combination all forms a kind of operational mode.In actual distribution system, the permutation and combination number of switching manipulation is very huge, so the anti-error optimization problem of power distribution network is a huge non-linear integer combinations optimization problem in theory.Due to the switch combination enormous amount as optimized variable, exhaustive search will face " multiple shot array " problem.And solution space is too huge, makes when direct Mathematical amount of calculation very large, thereby will take a large amount of machines time, and cannot guarantee the reliability of convergence.
Summary of the invention
What the present invention proposed is the anti-error optimization method of a kind of power distribution network, and its object purport combines branch exchange method and Chaos Genetic Algorithm, is meeting under the prerequisite of voltage and Line Flow constraint, and in optimization, the state of block switch and interconnection switch is determined by genetic algorithm; Then the network loss of computing network and desired on-off times in different networks, the scheme finally with minimum network loss, minimal switches number of times is optimal case.
Technical solution of the present invention: the anti-error optimization method of power distribution network, comprises the steps:
One, power distribution network topological system is divided into several independently unit according to current running status, guarantees that each unit has and only have a switch to disconnect, the quantity of unit equals the number of switches of the state of opening the light for disconnecting like this;
Two, the on off state with each unit carries out real coding by switch exchange algorithm, more all unit are connected into a chromosome;
Three, by target setting function and constraints, by Chaos Genetic Algorithm, network is calculated, thereby try to achieve optimal solution.
Advantage of the present invention: the present invention has certain theoretical research and practical value, meeting under the prerequisite of security constraint, by methods such as switching manipulations, changing the operational mode of distribution line, eliminating branch road overload and voltage out-of-limit, balanced feeder line load, makes loss minimization.Occupying clear superiority aspect network loss improvement and convergence rate, be more suitable for applying in real time at the scene.
Accompanying drawing explanation
Fig. 1 is ieee standard 3 feeder line 16 node distribution system schematic diagrames.
Fig. 2 is gene interlace operation schematic diagram.
Fig. 3 is solution instance graph.
Fig. 4 is whole progress figure.
Fig. 5 is flow chart of the present invention.
Embodiment
The anti-error optimization method of power distribution network, comprises the steps:
One, power distribution network topological system is divided into several independently unit according to current running status, guarantees that each unit has and only have a switch to disconnect, the quantity of unit equals the number of switches of the state of opening the light for disconnecting like this;
Two, the on off state with each unit carries out real coding by switch exchange algorithm, more all unit are connected into a chromosome;
Three, by target setting function and constraints, by Chaos Genetic Algorithm, network is calculated, thereby try to achieve optimal solution.
During enforcement
The Mathematical Modeling of 1 anti-error optimization
The target function of 1.1 anti-error optimizations
The target function that the present invention adopts is to reduce matching net wire loss with minimum on-off times, makes the loss minimization of network.Its network loss target function can be expressed as:
（1）
In formula, the way that b is power distribution network; K is the running status of branch road i, and 0 represents that this branch road disconnects, and 1 represents this branch road operation; R is the resistance of branch road i; I is for passing through the electric current of branch road i.
Network loss is calculated and is tried to achieve by trend.While normally moving due to distribution, be open loop, therefore the present invention pushes back for method and calculates trend before adopting.The state contrast of on-off times by front-rear switch draw, last general objective function representation is:
（2）
In formula, the income of F for optimizing, m is front network loss, f is the network loss after optimizing, k1Wei unit's electricity price, k2 is each switch motion cost, n is wanted switch motion number of times by optimization.
1.2 constraintss of optimizing
The anti-error optimization of power distribution network also requires formula (1) should meet following constraints:
(1) power capacity constraint:
,
;
In formula,
,
be respectively power calculation value and maximum power value thereof that each branch road i flows through,
,
what be respectively transformer confesses power and maximum capacity thereof;
(2) node voltage constraint:
;
In formula,
,
be respectively the permission minimum value of i node voltage and the maximum of permission;
(3) network configuration constraint: if the network open loop after optimization, can not there is looped network;
(4) power supply constraint: all loads all will have Power supply belt, can not occur isolated island situation;
(5) trend constraint: the anti-error optimization of distribution will meet power flow equation.
The anti-error optimized algorithm of 2 distribution
2.1 power distribution network network structures are divided ring
In the anti-error optimization of distribution, so-called loop refers to the circuit that forms closed loop in grid structure, has two kinds of forms: 1,, from a power supply point of power distribution network, each point, only through 1 time, arrives the ring of another power supply point; 2, from certain point of power distribution network, each node, only through 1 time, is got back to again the ring of this point.The running status that the present invention be take before the anti-error optimization of power distribution network is divided ring as basis, guarantee that every loop has and only have a switch disconnecting under current running status.
2.2 improved genetic algorithms
First genetic algorithm will form chromosome, then copies, the work such as crossover and mutation, and finally selecting the new individuality that fitness is the highest is preferred plan.
2.2.1 chromosome forms and optimizes
The anti-error optimization of distribution is reconstructed while optimizing by traditional genetic algorithm, splits to close to be numbered, and the on off state in network is opened with 0() or 1(close) represent, each on off state accounts for chromosomal one, chromosomal length equals the sum of switch.
If because the network after the anti-error optimization of power distribution network network will meet network open loop after optimization, all loads all will have Power supply belt.Therefore some in network must closed switching branches can be removed from loop according to these 2, the switching branches being connected with power supply point is removed from loop.Removed the branch road that some must be closed, chromosomal length reduces.
The interconnection switch number disconnecting before the network optimization will equate with the interconnection switch number that disconnects after the network optimization.The present invention is by the search of network topology, and the network operation state based on before optimizing, through optimizing, is divided into some loops by network, and the interconnection switch number of loop number and disconnection is the same.By each loop, be that body arranges all loops with the order of fixing one by one, then respectively the on off state of every ring encoded respectively.Because each loop is that to have and only have a switch be in off-state, other switches must, in closure state, carry out real coding according to this feature.In loop, the position of each switch is fixed, and in loop, i switch disconnects and this loop be encoded to i (i is natural number), and the span of i is that 1～N(N is the total number of switch in loop).All loops all carry out real coding according to the method described above, then according to the order between existing loop, whole network loop are integrated, and obtain the chromosome of a real coding.
Ieee standard 3 feeder line 16 node distribution systems take below as example explanation real coding.
As shown in Figure 1, according to the principle of optimizing, the on off state of branch road 1, branch road 7, branch road 10, branch road 15 can be removed from chromosome.By remaining branch road, divide ring operation, obtain a kind of minute ring scheme below:
Loop 1: branch road 3-4-6-8; Loop 2: branch road 9-13-14; Loop 3: branch road 2-5-11-12-16
In Fig. 1 loop 1, the switch of branch road 4 disconnects, and is 1011, and can be expressed as 2 by real coding mode with traditional binary coding representation, and the transformation range of state encoding is 1～4.In like manner the state of loop 2 is expressed as 2 with real coding, and the transformation range of state encoding is 1～3; The state of loop 3 is expressed as 3 with real coding, and the transformation range of state encoding is 1～5; According to the order of loop 1 loop 2 loops 3, arrange, in Fig. 1, network operation state can represent with real coding 223.
Upper example can be found out, adopt a minute ring real number coding method can make chromosomal length reduce on a large scale, chromosomal all codings are all feasible codings, there will not be the coding that does not meet the normal operation of distribution, therefore without not revising meeting the chromosome of distribution operation.This coded system has significant improvement the efficiency of the anti-error optimized Genetic Algorithm of distribution.
2.2.2 chromosomal genetic manipulation
The clone method that the present invention adopts is squirrel wheel method.Copied, after formation population, will carry out interlace operation.What the present invention adopted is the real coding of minute loop, and interlace operation occurs between loop and loop.Below or take ieee standard 3 feeder line 16 node distribution systems interlace operations of the present invention as example illustrates.
Suppose that through real coding copy operation after pairing, occurs the right chromosome of an assembly: A:234 B:322 between two; Crossover location is chosen in second, forms two new chromosome A1:222 B1:334.Concrete operations as shown in Figure 2.
Just may there is mistake in the chromosome after gene morphs, do not meet the operation condition of network of distribution.Occur will revise chromosome after chromosome mistake.Chromosomal variation of the present invention occurs that mistake is that number of switches is out-of-limit, will be by wrong loop transcoding, coding transform in the transformation range of state encoding after out-of-limit.Above routine chromosome A1 is example.The second of A1 morphs, the new chromosome A1:252 of formation after variation.And deputy excursion is 1～3, therefore will revise second, second is transformed to 1～3 random number, revised chromosome A1:232.The network operation state obtaining meets the network configuration of distribution.
2.2.3 Chaos Genetic Algorithm
The random irregular movement seemingly that chaos refers to occur in deterministic system.Defect based on traditional genetic algorithm, the present invention proposes a kind of Chaos Genetic Algorithm, using chaotic optimization algorithm in the middle of additional factor joins genetic algorithm, the individuality that fitness in population is poor replaces to chaos emigration, increase randomness and the ergodic of gene individuality in population, promote effective evolution of population, prevent that algorithm is absorbed in local optimum.Great many of experiments shows that, when colony's total scale is 50～100, immigrant's ratio should select 0.2～0.4, and immigrant's ratio that the present invention chooses is 0.2.
2.2.4 locally optimal solution solution
What the present invention adopted is branch exchange algorithm, because branch exchange method exists limitation, although i.e. branch exchange algorithm fast convergence rate is easily absorbed in locally optimal solution.Now provide a kind of solution that prevents from being absorbed in locally optimal solution.Divide when ring carrying out power distribution network network structure, because the branch road of network configuration much causes the result minute encircled not unique.And while being optimized with the above-mentioned algorithm of the present invention, just on minute good loop basis, obtain an optimal solution, to other different networks, divide ring structure helpless.This solution is considered the diversity that network divides ring, specifically by Fig. 3, is illustrated.In Fig. 3,1 ' is power supply point, and branch road 1-2 is for must dividing ring not consider by closing section.By the present invention, divide ring method can obtain following a kind of scheme: A loop 1: branch road 2 '-8 '-9 '-3 '-2 '; B loop 2: branch road 2 '-5 '-6 '-3 '; C loop 3: branch road 9 '-10 '-4 '-3 '; D loop 4: branch road 6 '-7 '-4 '.
From such scheme, can find out, the node that occurrence number is maximum is 3 ' node, occur altogether 3 times, and 3 ' node connects 4 branch roads, the network topology of Fig. 4 can guarantee that all switch situations of cut-offfing can represent by these three kinds of schemes by three kinds of different minute ring schemes.Can infer thus each network the switch situation of cut-offfing can with N-1(N be in network, connect that the maximum node of branch road connects way) plant different minute ring schemes and represent.This N-1 kind scheme is calculated by algorithm of the present invention, just then compare and can draw optimal solution, thereby limitation problem is resolved.Whole progress as shown in Figure 4.
Referring to Fig. 5, the anti-error optimization method flow chart of power distribution network, comprises following processing step:
The first step: the topological structure of determining power distribution network;
Second step: judge whether network is correct network; Network judgement comprises: whether whether be active network, be Radial network;
The 3rd step: Adoption Network divides and around-Francely divides ring based on current network state;
The 4th step: the ring that last link has been divided carries out real coding; Guarantee that each loop only has a switch in open mode, so each real number corresponding state that particular switch is opened only;
The 5th step: the real coding of all ring sections is compiled to a chromosome according to sequencing;
The 6th step: real coding process is complete;
The 7th step: call genetic algorithm; The scheme that is resolved, obtains scheme, provides its network loss size, the parameters such as on-off times;
The 8th step: anti-error optimization finishes.
Claims (3)
1. the anti-error optimization method of power distribution network, is characterized in that the method comprises the steps:
One, power distribution network topological system is divided into several independently unit according to current running status, guarantees that each unit has and only have a switch to disconnect, the quantity of unit equals the number of switches of on off state for disconnecting like this;
Two, the on off state with each unit carries out real coding by switch exchange algorithm, more all unit are connected into a chromosome;
Three, by target setting function and constraints, by Chaos Genetic Algorithm, network is calculated, thereby try to achieve optimal solution;
Described carries out real coding with ieee standard 3 feeder line 16 node distribution system explanation real codings, and the on off state of the first branch road (1), the 7th branch road (7), the tenth branch road (10), the 15 branch road (15) is removed from chromosome; By remaining branch road, divide ring operation, obtain a kind of minute ring scheme below: the first loop (1) by third and fourth, six, eight branch roads (3-4-6-8) form; The second loop (2) by the 9th, 13,14 branch roads (9-13-14) form; The 3rd loop (3) consists of second, five, 11,12,16 branch roads (2-5-11-12-16), wherein the switch of the 4th branch road (4) in the first loop (1) disconnects, by real coding mode, be expressed as 2, the transformation range of state encoding is 1～4; In like manner the state of the second loop (2) is expressed as 2 with real coding, and the transformation range of state encoding is 1～3; The state of the 3rd loop (3) is expressed as 3 with real coding, and the transformation range of state encoding is 1～5; According to the order of the first loop (1), the second loop (2), the 3rd loop (3), arrange, network operation state represents with real coding 223.
2. the anti-error optimization method of power distribution network according to claim 1, is characterized in that described target setting function and constraints are respectively
1) target function is to reduce matching net wire loss with minimum on-off times, makes the loss minimization of network; Its network loss target function can be expressed as:
（1）
In formula, the way that b is power distribution network; K is the running status of branch road i, and 0 represents that this branch road disconnects, and 1 represents this branch road operation; R is the resistance of branch road i; I is for passing through the electric current of branch road i;
Network loss is calculated and is tried to achieve by trend; While normally moving due to distribution, be open loop, therefore the present invention pushes back for method and calculates trend before adopting; The state contrast of on-off times by front-rear switch draw, last general objective function representation is:
（2）
In formula, the income of F for optimizing, m is the network loss before optimizing, f is the network loss after optimizing, k1Wei unit's electricity price, k2 is each switch motion cost, n is wanted switch motion number of times by optimization;
2) constraints of optimizing
The anti-error optimization of power distribution network also requires formula (1) should meet following constraints:
(1) power capacity constraint:
,
;
In formula,
,
be respectively power calculation value and maximum power value thereof that each branch road i flows through,
,
what be respectively transformer confesses power and maximum capacity thereof;
(2) node voltage constraint:
;
In formula,
,
be respectively the permission minimum value of i node voltage and the maximum of permission;
(3) network configuration constraint: if the network open loop after optimization, can not there is looped network;
(4) power supply constraint: all loads all will have Power supply belt, can not occur isolated island situation;
(5) trend constraint: distribution optimization will meet power flow equation.
3. the anti-error optimization method of power distribution network according to claim 1, is characterized in that first described Chaos Genetic Algorithm will form chromosome, then copies, crossover and mutation, and finally selecting new individuality is preferred plan; Described chromosome forms and optimizes, when the anti-error optimization of distribution is reconstructed optimization by traditional genetic algorithm, splits pass and be numbered, the on off state in network is represented out with 0 or represent to close with 1, each on off state accounts for chromosomal one, and chromosomal length equals the sum of switch; If because the network after the anti-error optimization of power distribution network network will meet network open loop after reconstruct, all loads all will have Power supply belt; Therefore some in network must closed switching branches be removed from loop, the switching branches being connected with power supply point are removed from loop; The interconnection switch number disconnecting before the network optimization will equate with the interconnection switch number that disconnects after the network optimization, by the search of network topology, network operation state based on before optimizing, through optimizing, network is divided into some loops, the interconnection switch number of loop number and disconnection is the same, by each loop, is that body arranges all loops with the order of fixing one by one, then respectively the on off state of every ring is encoded respectively; Because each loop is that to have and only have a switch be in off-state, other switches must, in closure state, carry out real coding according to this feature; In loop, the position of each switch is fixed, and in loop, i switch disconnects and this loop be encoded to i, and i is natural number, and the span of i is 1～N, and N is the total number of switch in loop; All loops all carry out real coding according to the method described above, then according to the order between existing loop, whole network loop are integrated, and obtain the chromosome of a real coding;
Described clone method is squirrel wheel method, has copied, and after formation population, will carry out interlace operation; What the present invention adopted is the real coding of minute loop, and interlace operation occurs between loop and loop; Through real coding, copy operation, after pairing, there is the right chromosome of an assembly: A:234 B:322 between two; Crossover location is chosen in second, forms two new chromosome A1:222 B1:334;
Described variation, chromosomal variation occurs that mistake is that number of switches is out-of-limit, will be by wrong loop transcoding, coding transform in the transformation range of state encoding after out-of-limit, when the second of A1 morphs, the new chromosome A1:252 of formation after variation; And deputy excursion is 1～3, therefore will revise second, second is transformed to 1～3 random number, revised chromosome A1:232, the network operation state obtaining meets the network configuration of distribution.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2019030246A1 (en) * | 2017-08-11 | 2019-02-14 | Commissariat A L'energie Atomique Et Aux Energies Alternatives | Computer-implemented method for reconstructing the topology of a network of cables, using a genetic algorithm |
| FR3070075A1 (en) * | 2017-08-11 | 2019-02-15 | Commissariat A L'energie Atomique Et Aux Energies Alternatives | COMPUTER-IMPLEMENTED METHOD OF RECONSTRUCTING THE TOPOLOGY OF A CABLES NETWORK USING GENETIC ALGORITHM |
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