CN112287500A - Grid planning method for power distribution network in grid based on optimal cutting - Google Patents

Grid planning method for power distribution network in grid based on optimal cutting Download PDF

Info

Publication number
CN112287500A
CN112287500A CN202011176175.XA CN202011176175A CN112287500A CN 112287500 A CN112287500 A CN 112287500A CN 202011176175 A CN202011176175 A CN 202011176175A CN 112287500 A CN112287500 A CN 112287500A
Authority
CN
China
Prior art keywords
line
grid
edge
distribution network
feeder
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202011176175.XA
Other languages
Chinese (zh)
Other versions
CN112287500B (en
Inventor
宁超
杨俊�
张峰
朱咏明
刘莎
李卫华
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
State Grid Xinjiang Electric Power Co Ltd Changji Power Supply Co
Original Assignee
State Grid Xinjiang Electric Power Co Ltd Changji Power Supply Co
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by State Grid Xinjiang Electric Power Co Ltd Changji Power Supply Co filed Critical State Grid Xinjiang Electric Power Co Ltd Changji Power Supply Co
Priority to CN202011176175.XA priority Critical patent/CN112287500B/en
Publication of CN112287500A publication Critical patent/CN112287500A/en
Application granted granted Critical
Publication of CN112287500B publication Critical patent/CN112287500B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/18—Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/04—Power grid distribution networks
    • 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 discloses a cutting-optimal-based grid planning method for a power distribution network in a grid, which relates to the technical field of power distribution network planning, in particular to a graph formed by each grid of a power distribution network, wherein the graph is formed by starting from an edge connected with a 10KV power supply point, a minimum cut in a cut set is selected each time, such as a spanning tree, until all nodes enter the spanning tree, the minimum cut refers to that the accessed edge meets the sum of equivalent annual investment cost of the edge and line loss increment of the spanning tree, and a connecting branch with the minimum equivalent annual cost is selected as a connecting line, so that an optimal or approximately optimal grid planning scheme is quickly obtained, the planning cost of the power distribution network is effectively reduced, the economic benefit of a power distribution network company is improved, compared with the traditional grid planning method, the practicability and the convenience are greatly improved, and the method is suitable for large-scale popularization and application in the industry.

Description

Grid planning method for power distribution network in grid based on optimal cutting
Technical Field
The invention relates to the technical field of power distribution network planning, in particular to a method for planning a power distribution network frame in a grid based on optimal cutting.
Background
Under the condition that a planning area is divided into a plurality of grids, the optimal planning of the power distribution grid frame in each grid refers to seeking a group of optimal decision variables (the path and the model of a feeder) on the premise of meeting the power supply, radial constraint, node voltage, feeder section current and constraint of a user, so that the sum of investment and operation cost is minimum.
The solving method for the power distribution network frame planning in the grid mainly comprises a mathematical optimization method and an artificial intelligence search algorithm. The radial constraint condition processing of the mathematical optimization algorithm is complex, and the developed algorithm is difficult to be practically applied; the artificial intelligence search algorithm not only can generate a large number of infeasible solutions, but also is easy to fall into a local optimal solution.
Disclosure of Invention
In order to solve the technical problems, the invention provides the grid planning method for the power distribution network in the grid based on the optimal cutting, the algorithm is simple, the optimal or approximately optimal grid planning scheme is quickly obtained, and the practical application is easy.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a mesh frame planning method for a distribution network in a grid based on optimal cutting is realized by the following steps:
step S1: the planned area in the grid forms a graph G, 10kV buses are combined into one vertex of the graph G and numbered as the 1 st vertex, the intersection points of loads and possible line corridors are other vertices of the graph G, the numbering is from 2 to N, the line corridors between the vertices are edges of the graph G, and the numbering is from 1 to L;
step S2: inputting data, inputting line model, active and reactive power of load, length of side, investment cost of unit length side, planning period, electricity price and discount rate;
step S3: calculating the annual value W of the investment cost of each side, wherein the annual value W of the investment cost of L is 1,2lThe calculation formula is as follows:
Figure BDA0002746282650000011
in the formula LlIs the length of the l-th side, K is the investment cost per unit length, the unit is Yuan/km, r is the discount rate, and T is the planning time limit;
step S4: forming a 1 st edge of each feeder line, and if one vertex of an edge L of the graph G is numbered as 1, putting the edge L into an optimal spanning tree set E (G), wherein the set E (G) corresponds to one feeder line, and the number of the edges in the set E (G) is the number of the feeder lines;
step S5: assigning, and enabling the vertex calculator n to be 2;
step S6: calculating a cut of an edge selected from the set G-e (G) and having only one vertex in the set e (G), and an edge selected from the set G-e (G) and having only one vertex in the set e (G), wherein if there are M edges, the M is 1, 2.
Gm＝ΔPloss,m×tmax×C+Wm (2)
In the formula,. DELTA.Ploss,mIs the line loss increase, t, after increasing the mth side and its loadmaxIs the annual maximum load equivalent time, in hours, C is the electricity price, unit/kWh;
step S7: the shortest cut is selected from the M edges 1, 2., G of the M edges by comparing M1, 2., G of the M edges in step S5mTo obtain a minimum cut
Figure BDA0002746282650000021
And cutting the minimum corresponding edge mminPut into the set E (G);
step S8: assigning, wherein n is n + 1;
step S9: judging that if N is less than N,turning to step S6; otherwise, calculating the line loss delta P of the radial network by using the forward-push-back power flowlossAnd further calculating the radial network equal-year-value cost according to the following formula:
Figure BDA0002746282650000022
turning to step S10;
step S10: the lengths of the branches are sequenced, all the branches are sequenced from small to large, the number B of the branches is 1, and the number of the branches is B;
step S11: searching the feeder lines connected with the branches, and for each branch, starting from two vertexes of the branch respectively, and searching the connected feeder lines on the obtained spanning tree by adopting depth-first;
step S12: judging that the connecting branch b is not a connecting line between the feeders if the connecting branch b is connected with the same feeder, and turning to the step S15;
step S13: judging that if two different feeder lines connected with the connecting branch b do not have tie lines, the connecting branch is a tie line, and the feeder line is marked to have the tie line, and turning to the step S15;
step S14: judging that if one of the two different feeder lines connected with the branch b has a tie line, turning to the step S15;
step S15: judging, if the number B of the branch is equal to B +1, if B is less than or equal to B, turning to step S11; otherwise, go to step S16;
step S16: giving the junctor and the cost thereof, and calculating the equivalent annual cost of all the junctors according to the following formula:
Figure BDA0002746282650000031
in the formula NbIs the number of contact lines.
The invention discloses a cutting-optimal-based grid planning method for a power distribution network in a grid, and particularly relates to a graph formed by each grid of the power distribution network, which starts from an edge connected with a 10KV power supply point, selects a cutting-concentrated minimum cut such as a spanning tree each time until all nodes enter the spanning tree, wherein the minimum cut means that the accessed edge meets the sum of equivalent annual investment cost of the edge and line loss increment of the spanning tree, and selects a connecting branch with the minimum equivalent annual cost as a connecting line, so that an optimal or approximately optimal grid internal grid planning scheme is quickly obtained, the power distribution network planning cost is effectively reduced, the economic benefit of a power distribution network company is improved, the practicability and the convenience are greatly improved compared with the traditional grid planning method, and the method is suitable for large-scale popularization and application in the industry.
Drawings
FIG. 1 is a diagram illustrating the formation of a planned area within a grid in an embodiment of the present invention;
FIG. 2 shows a radial network structure from S4 to S9 in an embodiment.
Detailed Description
The invention is described in detail below with reference to the following figures and specific embodiments:
the optimal grid cutting-based method for planning the power distribution network frame in the grid is realized by the following steps:
step S1: the planned area in the grid forms a graph G, 10kV buses are combined into one vertex of the graph G and numbered as the 1 st vertex, the intersection points of loads and possible line corridors are other vertices of the graph G, the numbering is from 2 to N, the line corridors between the vertices are edges of the graph G, and the numbering is from 1 to L;
step S2: inputting data, inputting line model, active and reactive power of load, length of side, investment cost of unit length side, planning period, electricity price and discount rate;
step S3: calculating the annual value W of the investment cost of each side, wherein the annual value W of the investment cost of L is 1,2lThe calculation formula is as follows:
Figure BDA0002746282650000041
in the formula LlIs the length of the first side, K is the investment cost per unit lengthThe unit is Yuan/km, r is the discount rate, and T is the planning time limit;
step S4: forming a 1 st edge of each feeder line, and if one vertex of an edge L of the graph G is numbered as 1, putting the edge L into an optimal spanning tree set E (G), wherein the set E (G) corresponds to one feeder line, and the number of the edges in the set E (G) is the number of the feeder lines;
step S5: assigning, and enabling the vertex calculator n to be 2;
step S6: calculating a cut of an edge selected from the set G-e (G) and having only one vertex in the set e (G), and an edge selected from the set G-e (G) and having only one vertex in the set e (G), wherein if there are M edges, the M is 1, 2.
Gm＝ΔPloss,m×tmax×C+Wm (2)
In the formula,. DELTA.Ploss,mIs the line loss increase, t, after increasing the mth side and its loadmaxIs the annual maximum load equivalent time, in hours, C is the electricity price, unit/kWh;
step S7: the shortest cut is selected from the M edges 1, 2., G of the M edges by comparing M1, 2., G of the M edges in step S5mTo obtain a minimum cut
Figure BDA0002746282650000042
And cutting the minimum corresponding edge mminPut into the set E (G);
step S8: assigning, wherein n is n + 1;
step S9: judging, if N is less than N, turning to step S6; otherwise, calculating the line loss delta P of the radial network by using the forward-push-back power flowlossAnd further calculating the radial network equal-year-value cost according to the following formula:
Figure BDA0002746282650000043
turning to step S10;
step S10: the lengths of the branches are sequenced, all the branches are sequenced from small to large, the number B of the branches is 1, and the number of the branches is B;
step S11: searching the feeder lines connected with the branches, and for each branch, starting from two vertexes of the branch respectively, and searching the connected feeder lines on the obtained spanning tree by adopting depth-first;
step S12: judging that the connecting branch b is not a connecting line between the feeders if the connecting branch b is connected with the same feeder, and turning to the step S15;
step S13: judging that if two different feeder lines connected with the connecting branch b do not have tie lines, the connecting branch is a tie line, and the feeder line is marked to have the tie line, and turning to the step S15;
step S14: judging that if one of the two different feeder lines connected with the branch b has a tie line, turning to the step S15;
step S15: judging, if the number B of the branch is equal to B +1, if B is less than or equal to B, turning to step S11; otherwise, go to step S16;
step S16: giving the junctor and the cost thereof, and calculating the equivalent annual cost of all the junctors according to the following formula:
Figure BDA0002746282650000051
in the formula NbIs the number of contact lines.
As shown in fig. 1, the present invention provides a specific embodiment, and the final rack planning scheme is obtained through the following specific steps.
Step S1: a graph G is formed in a planned area in a grid, a graph 1 is generated by 10kV buses, loads and possible line corridors in a certain grid of a certain planned area, and the 10kV buses are equivalent to 1 vertex due to power supply points.
Step S2: the unified line model is JKLGYJ-240mm2The impedance per unit length is 0.125+ j0.34 ohm, the cost per unit length is 20 ten thousand yuan/km, the maximum current is 553 amperes, the planning period is 20 years, the electricity price is 0.5 yuan/kilowatt hour, the discount rate is 2 percent, the annual maximum load equivalent time is 3230 hours, and the data of the side (feeder segment) is shown in the following table:
Figure BDA0002746282650000052
Figure BDA0002746282650000061
the node loads are shown in the following table:
numbering Active power (MW) Reactive power (Mvar) Numbering Active power (MW) Reactive power (Mvar)
1 0 0 18 0.08 0.014
2 0.631 0.097 19 0.461 0.089
3 0.077 0.014 20 0.052 0.01
4 0.502 0.09 21 1.387 0.211
5 0.293 0.053 22 0.998 0.173
6 0.321 0.059 23 1.609 0.287
7 0.687 0.108 24 0.05 0.008
8 0.315 0.055 25 0.628 0.107
9 0.772 0.128 26 1.487 0.261
10 0.076 0.012 27 0.63 0.112
11 1.712 0.269 28 1.295 0.212
12 1.224 0.215 29 0.514 0.086
13 0.046 0.007 30 0.076 0.014
14 0.473 0.09 31 0.458 0.076
15 0.122 0.02 32 0.16 0.026
16 0.074 0.013 33 0.46 0.08
17 0.398 0.069 34 0.151 0.026
Step S3: the annual investment cost value of each edge is as follows:
Figure BDA0002746282650000062
Figure BDA0002746282650000071
step S4: the 1 st edge of each feeder is as follows:
feeder line name Numbering Starting node End node
Feeder line A 1 1 2
Feeder B 3 1 21
Feeder C 2 1 9
Feeder line D 4 1 28
Step S5 to step S9: the edges added for each iteration and the optimum are cut as follows
Number of iterations Edge Cutting (Wanyuan) Number of iterations Edge Cutting (Wanyuan)
1 6 1.34616 16 40 6.70185
2 27 1.49032 17 16 6.73055
3 5 1.80583 18 19 8.22683
4 33 1.94689 19 24 9.86102
5 34 2.40397 20 25 10.9429
6 7 2.5698 21 26 11.4536
7 13 3.15313 22 32 12.6955
8 11 2.8637 23 44 14.013
9 12 2.52327 24 31 15.1955
10 10 3.80199 25 30 15.1284
11 41 3.60896 26 14 17.4386
12 20 3.73576 27 43 19.6299
13 9 4.15924 28 38 21.2661
14 21 5.12425 29 28 23.5862
15 35 6.51045
The radial network structure obtained from steps S4 to S9 is shown in fig. 2, and the calculated equivalent annual cost of the radial network is 49.4689 ten thousand yuan.
Step S10: the numbers and lengths of the branches are shown in the table
Figure BDA0002746282650000072
Figure BDA0002746282650000081
Steps S11 to S15: after iteration, as shown by the dashed line in fig. 2, the selected tie lines are branch 29 and branch 17;
step S16: the equivalent annual cost of the connecting line is calculated as follows: 1.8665 ten thousand yuan.
It is to be understood that the above description is not intended to limit the present invention, and the present invention is not limited to the above examples, and those skilled in the art may make modifications, alterations, additions or substitutions within the spirit and scope of the present invention.

Claims (1)

1. A mesh frame planning method for a distribution network in a grid based on optimal cutting is characterized by comprising the following steps:
step S1: the planned area in the grid forms a graph G, 10kV buses are combined into one vertex of the graph G and numbered as the 1 st vertex, the intersection points of loads and possible line corridors are other vertices of the graph G, the numbering is from 2 to N, the line corridors between the vertices are edges of the graph G, and the numbering is from 1 to L;
step S2: inputting data, inputting line model, active and reactive power of load, length of side, investment cost of unit length side, planning period, electricity price and discount rate;
step S3: calculating the annual value W of the investment cost of each side, wherein the annual value W of the investment cost of L is 1,2lThe calculation formula is as follows:
Figure FDA0002746282640000011
in the formula LlIs the length of the l-th side, K is the investment cost per unit length, the unit is Yuan/km, r is the discount rate, and T is the planning time limit;
step S4: forming a 1 st edge of each feeder line, and if one vertex of an edge L of the graph G is numbered as 1, putting the edge L into an optimal spanning tree set E (G), wherein the set E (G) corresponds to one feeder line, and the number of the edges in the set E (G) is the number of the feeder lines;
step S5: assigning, and enabling the vertex calculator n to be 2;
step S6: calculating a cut of an edge selected from the set G-e (G) and having only one vertex in the set e (G), and an edge selected from the set G-e (G) and having only one vertex in the set e (G), wherein if there are M edges, the M is 1, 2.
Gm＝ΔPloss,m×tmax×C+Wm (2)
In the formula,. DELTA.Ploss,mIs the line loss increase, t, after increasing the mth side and its loadmaxIs the annual maximum load equivalent time, in hours, C is the electricity price, unit/kWh;
step S7: the shortest cut is selected from the M edges 1, 2., G of the M edges by comparing M1, 2., G of the M edges in step S5mTo obtain the minimumCutting
Figure FDA0002746282640000012
And cutting the minimum corresponding edge mminPut into the set E (G);
step S8: assigning, wherein n is n + 1;
step S9: judging, if N is less than N, turning to step S6; otherwise, calculating the line loss delta P of the radial network by using the forward-push-back power flowlossAnd further calculating the radial network equal-year-value cost according to the following formula:
Figure FDA0002746282640000021
turning to step S10;
step S10: the lengths of the branches are sequenced, all the branches are sequenced from small to large, the number B of the branches is 1, and the number of the branches is B;
step S11: searching the feeder lines connected with the branches, and for each branch, starting from two vertexes of the branch respectively, and searching the connected feeder lines on the obtained spanning tree by adopting depth-first;
step S12: judging that the connecting branch b is not a connecting line between the feeders if the connecting branch b is connected with the same feeder, and turning to the step S15;
step S13: judging that if two different feeder lines connected with the connecting branch b do not have tie lines, the connecting branch is a tie line, and the feeder line is marked to have the tie line, and turning to the step S15;
step S14: judging that if one of the two different feeder lines connected with the branch b has a tie line, turning to the step S15;
step S15: judging, if the number B of the branch is equal to B +1, if B is less than or equal to B, turning to step S11; otherwise, go to step S16;
step S16: giving the junctor and the cost thereof, and calculating the equivalent annual cost of all the junctors according to the following formula:
Figure FDA0002746282640000022
in the formula NbIs the number of contact lines.
CN202011176175.XA 2020-10-28 2020-10-28 Grid planning method for power distribution network in grid based on optimal cutting Active CN112287500B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202011176175.XA CN112287500B (en) 2020-10-28 2020-10-28 Grid planning method for power distribution network in grid based on optimal cutting

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202011176175.XA CN112287500B (en) 2020-10-28 2020-10-28 Grid planning method for power distribution network in grid based on optimal cutting

Publications (2)

Publication Number Publication Date
CN112287500A true CN112287500A (en) 2021-01-29
CN112287500B CN112287500B (en) 2023-04-07

Family

ID=74373804

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202011176175.XA Active CN112287500B (en) 2020-10-28 2020-10-28 Grid planning method for power distribution network in grid based on optimal cutting

Country Status (1)

Country Link
CN (1) CN112287500B (en)

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2004052073A2 (en) * 2002-12-12 2004-06-24 Bhagat Nitin S Optimal feeder design in distribution system planning
CN110619454A (en) * 2019-08-09 2019-12-27 东北大学 Power distribution network planning method based on improved genetic algorithm and PRIM algorithm
US20200257971A1 (en) * 2019-01-11 2020-08-13 Chongqing University Full-linear model for optimal power flow of integrated power and natural-gas system based on deep learning methods

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2004052073A2 (en) * 2002-12-12 2004-06-24 Bhagat Nitin S Optimal feeder design in distribution system planning
US20200257971A1 (en) * 2019-01-11 2020-08-13 Chongqing University Full-linear model for optimal power flow of integrated power and natural-gas system based on deep learning methods
CN110619454A (en) * 2019-08-09 2019-12-27 东北大学 Power distribution network planning method based on improved genetic algorithm and PRIM algorithm

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
SANDFORD BESSLER 等: "Distributed flexibility management targeting energy cost and total power limitations in electricity distribution grids" *
蔡志远 等: "多微电源混合系统在微电网中最优定位和规划研究" *

Also Published As

Publication number Publication date
CN112287500B (en) 2023-04-07

Similar Documents

Publication Publication Date Title
CN110619454B (en) Power distribution network planning method based on improved genetic algorithm and PRIM algorithm
Najafi et al. A framework for optimal planning in large distribution networks
Yan et al. Planning of Electric Vehicle charging station based on hierarchic genetic algorithm
CN107591807B (en) Optimization method for power transmission network planning under new energy access
Moreira et al. Large-scale network layout optimization for radial distribution networks by parallel computing
CN106803130B (en) Planning method for distributed power supply to be connected into power distribution network
CN109598377B (en) AC/DC hybrid power distribution network robust planning method based on fault constraint
CN112255567B (en) Short-circuit current rapid determination method for power distribution network containing photovoltaic power supply
CN111668843A (en) Low-voltage distribution network three-phase load flow calculation method based on phase sequence mixing method
CN106159944A (en) Multi-stage transmission expansion planning method based on bilevel programming model under low-carbon (LC) environment
Thanh Nguyen et al. Optimal network reconfiguration to reduce power loss using an initial searching point for continuous genetic algorithm
CN109768543B (en) Elastic bottom-preserving net rack search modeling method based on mixed integer linear programming
CN109004639B (en) Power distribution network partition power supply recovery strategy optimization method based on completely distributed algorithm
CN104836240A (en) Power grid inherent structural characteristic-based power distribution network optimal reactive compensation method
CN112287500B (en) Grid planning method for power distribution network in grid based on optimal cutting
CN106951619B (en) Offshore wind farm topology design method considering reliability constraint
CN112234598B (en) Electromagnetic transient simulation initialization method
Mujezinović et al. Use of integer genetic algorithm for optimal allocation and sizing of the shunt capacitor banks in the radial distribution networks
Žarković et al. Reliability improvement of distribution system through distribution system planning: MILP vs. GA
CN108418211B (en) Power supply path optimization method based on Dijlstra algorithm and genetic algorithm
CN116388376A (en) Distribution network monitoring point configuration method, system and storage medium
Mahdavi et al. Evaluation of GA performance in TNEP considering voltage level, network losses and number of bundle lines
CN112287501A (en) Gridding power distribution network frame planning method based on improved Minty algorithm
Cai et al. Urban medium voltage distribution network planning based on ASAGA and TSP path optimization method
CN114491924A (en) Offshore booster station site selection method considering fan-wind power plant collaborative optimization

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant