CN107959287A - A kind of construction method of two voltage class power grids growth evolutionary model - Google Patents
A kind of construction method of two voltage class power grids growth evolutionary model Download PDFInfo
- Publication number
- CN107959287A CN107959287A CN201711117291.2A CN201711117291A CN107959287A CN 107959287 A CN107959287 A CN 107959287A CN 201711117291 A CN201711117291 A CN 201711117291A CN 107959287 A CN107959287 A CN 107959287A
- Authority
- CN
- China
- Prior art keywords
- power grid
- voltage
- evolution model
- substation
- power
- 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
Links
Classifications
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
A kind of construction method of two voltage class power grids growth evolutionary model, step are as follows：Annual load increase and the injection of higher level's electricity grid substation power are simulated, enlarging higher level's electricity grid substation is judged whether by higher level's power grid capacity-load ratio that be averaged；Determine whether the same day needs newly-built subordinate electricity grid substation, if need to create, it is determined that newly-built power transformation station location, load, capacity, and by space-time evolutionary model access power grid；Decision-making system whether short of electricity, if so, then creating higher level's electricity grid substation or grid generation factory of subordinate by determine the probability；N 1 is carried out to circuit to verify, and upgrading is carried out to the weak circuit for being unsatisfactory for verification；It steps be repeated alternatively until that iteration number of days exceedes and require iteration number of days.The design is for there is the power grid of two voltage class, the newly-built of substation in evolutionary process, power plant and circuit, enlarging and upgrading are grown in view of power grid, develop from time and two, space aspect to power grid, there is certain directive significance to Electric Power Network Planning and construction.
Description
Technical Field
The invention relates to the technical field of power grid growth evolution, in particular to a construction method of a power grid growth evolution model with two voltage levels.
Background
With the continuous enlargement of the scale of the power grid in China, the interconnection of the cross-regional power grids brings great economic and social benefits, and simultaneously, the network structure and the operation mode are more complicated, so that the difficulty of ensuring the safe and stable operation of the power system is also increased.
When the power demand is increased to a certain extent, which causes the standby capacity of the system to be too low, a power plant needs to be newly built according to the energy distribution condition, and the voltage grade and the mode of the power plant accessing to the power grid are determined, and if the local load density is too high, the address and the capacity of the newly built power plant need to be determined, and the voltage grade and the mode of the power plant accessing to the power grid are determined. Therefore, increasing load requirements gradually threaten the safety and reliability of power supply of the power grid, and therefore the growth and the evolution of the power grid are promoted. Therefore, an evolution model of the power system conforming to the actual power grid condition needs to be established to assist in guiding the planning and construction of the power grid.
Disclosure of Invention
The invention aims to solve the problem of evolving a power grid from two time and space layers when a substation, a power plant and a line are newly built, expanded and upgraded in the process of evolving the power grid, and provides a method for constructing a power grid growth evolution model with two voltage levels.
In order to achieve the above purpose, the technical solution of the invention is as follows: a method for constructing a growth evolution model of a power grid with two voltage levels comprises the following steps:
s1, simulating annual load increase and power injection of a superior power grid substation, and judging whether the superior power grid substation is expanded or not according to the average capacity-load ratio of the superior power grid;
s2, determining whether a lower-level power grid transformer substation needs to be newly built at the same day, if the lower-level power grid transformer substation needs to be newly built, determining the position, the load and the capacity of the newly built lower-level power grid transformer substation, and accessing the power grid according to the space-time evolution model;
s3, judging whether the system is in power shortage, if so, determining to newly build a superior power grid transformer substation or a subordinate power grid power plant according to probability;
s4, performing N-1 verification on the line, and upgrading and transforming the weak line which does not meet the verification;
s5, repeating the steps S1-S4 until the number of iteration days exceeds the number of iteration days required;
and S6, evaluating the evolution result through the characteristic path length, the clustering coefficient, the average degree and the power flow variance of the lower-level power grid line.
In step S1, the average capacity-to-load ratio of the higher-level power grid is:
in the above formula, the first and second carbon atoms are,and P dHM，k Capacity and load of the kth upper-level power grid node i substation respectively, ifExpanding a superior power grid substation; and xi is the sum of the loads of all subordinate power grid substations within the growth point load range d.
In the steps S2 and S3, the position of the newly-built transformer substation is determined through network growing points, the network growing points are defined as points which are not occupied in the network and have integral coordinates, and the load concentration degree xi of each growing point is the sum of loads of all subordinate power grid transformer substations within the load range d of the growing point.
In step S3, whether the system is in power shortage is determined according to the power-electricity balance of the system, and the determination criteria are:
P yu ＝P L +max{P genm ，γP L }
in the above formula, alpha is the lower limit value of the capacity-to-load ratio specified by two voltage class guiding rules, beta is the unit available capacity ratio, gamma is the sum of the load reserve ratio and the accident reserve ratio, S H Total capacity of higher-level power grid substation, P L Is the total load of the system, P genm For the maximum single machine capacity, P, of the power plant of the subordinate grid g Is the total power generation of the power plant.
In the steps S2 and S3, the newly-built transformer substation and the power plant are both accessed into the power grid according to a space-time evolution model of the power grid, the space-time evolution model of the power grid expresses the newly-added line impedance by the product of the reactance x with unit length and the physical distance between two nodes related to the reactance x, namely:
X ij ＝x×d ij
in the above formula, X ij Is the reactance of the line between nodes i and j, d ij Is the length of the line between nodes i and j.
In step S6, the characteristic path length is defined as an average value of distances between all node pairs:
in the above formula, n is the number of network nodes, d ij Is the length of the line between nodes i and j.
In step S6, the clustering coefficient is defined as:
in the above formula, n is the number of network nodes, a i Number of triangles connected to node i, b i Is the number of triples connected to node i.
In step S6, the average degree is defined as:
in the above formula, the first and second carbon atoms are,<k> is the average value of all node degrees in the network, node degree k i N is the number of network nodes, and n is the number of edges having the node as an end point.
In step S6, the power flow variance of the lower-level power grid line is defined as:
in the above formula, F i And the mu is the average value of the tidal current of the lower-level power grid line, and the N is the number of the lower-level power grid lines.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a growth evolution model of two voltage-level power grids based on a power grid space-time evolution model, wherein the growth evolution model considers comprehensive factors such as load increase, new construction, upgrading and reconstruction of a transformer substation and a power plant, verification of a line N-1 and the like; the model judges whether the power grid is in short of power or not by a power grid company power and electric quantity balance empirical formula according to the actual condition of the power grid, adopts a mode of adding one transformer and considering the maximum capacity of the transformer substation when the transformer substation of the upper-level power grid is upgraded and transformed, adopts a mode of adding one circuit when the circuit is upgraded and transformed, and is more in line with the actual condition of the power grid than the method of multiplying growth factors adopted in other models; in addition, the load range d provided by the invention can be used for calculating the concentration degree in the range when the lower-level power grid transformer substation is newly added for site selection, and the loads of other transformer substations in the range are reduced in proportion after the lower-level power grid transformer substation is newly added, so that the actual condition that the loads in a certain area are shared after site selection and construction of the power grid transformer substation in the actual power grid can be reflected better.
Drawings
FIG. 1 is a flow chart of a method for constructing a two-voltage-level power grid growth evolution model.
Fig. 2 is a schematic diagram of the northwest Hubei province grid topology in an embodiment of the invention.
Fig. 3 is the result of the evolution of the state of the vitex grid over 5 years of growth in an embodiment of the present invention.
Fig. 4 is the result of the evolution of the state of the vitex power grid over 10 years of growth in an embodiment of the present invention.
Fig. 5 is the result of the evolution of the state of the vitex power grid over 15 years of growth in an embodiment of the present invention.
In fig. 3 to 5, a black dot 1 indicates a 500KV substation-jianling 1 station, a black dot 2 indicates a 500KV substation-xinglong station, a black dot 3 indicates a 220KV power plant-sha city power plant, a black dot 4 indicates a 220KV power plant-jianling power plant, a black dot 5 indicates a 500KV substation-xiantao station, a black dot 6 indicates a 500KV substation-jianling 2 station, black dots on the left side of the jianling 1 station and above the xinglong station indicate power supply points, and the remaining black dots all indicate 220KV substations.
Detailed Description
The present invention will be described in further detail with reference to the following description and embodiments in conjunction with the accompanying drawings.
Referring to fig. 1, a method for constructing a two-voltage-level power grid growth evolution model includes the following steps:
s1, simulating annual load increase and power injection of a superior power grid substation, and judging whether the superior power grid substation is expanded or not according to the average capacity-load ratio of the superior power grid;
s2, determining whether a lower-level power grid transformer substation needs to be newly built at the same day, if so, determining the position, load and capacity of the newly built lower-level power grid transformer substation, and accessing the transformer substation into a power grid according to a time-space evolution model;
s3, judging whether the system is in power shortage, if so, determining to newly build a superior power grid transformer substation or a subordinate power grid power plant according to probability;
s4, performing N-1 verification on the line, and upgrading and transforming the weak line which does not meet the verification;
s5, repeating the steps S1-S4 until the number of iteration days exceeds the number of required iteration days;
and S6, evaluating the evolution result through the characteristic path length, the clustering coefficient, the average degree and the power flow variance of the lower-level power grid line.
In step S1, the average capacity-to-load ratio of the upper-level power grid is:
in the above formula, the first and second carbon atoms are,and P dHM，k Capacity and load of the kth upper-level power grid node i substation respectively, ifExpanding a superior power grid substation; and xi is the sum of the loads of all subordinate power grid substations within the growth point load range d.
In the steps S2 and S3, the position of the newly-built substation is determined through network growing points, the network growing points are defined as points which are not occupied in the network and have integral coordinates, and the load concentration degree xi of each growing point is the sum of loads of all lower-level power grid substations within the load range d of the growing point.
In step S3, whether the system is in power shortage is determined according to the power-electricity balance of the system, and the determination criteria are:
P yu ＝P L +max{P genm ，γP L }
in the above formula, alpha is the lower limit value of the capacity-to-load ratio specified by two voltage class guiding rules, beta is the unit available capacity ratio, gamma is the sum of the load reserve ratio and the accident reserve ratio, and S H For the total capacity of the upper level grid substation, P L Is the total load of the system, P genm Maximum single machine capacity, P, of power plant of lower-level power grid g Is the total power generation of the power plant.
In the steps S2 and S3, the newly-built transformer substation and the power plant are both accessed into the power grid according to the space-time evolution model of the power grid, and the space-time evolution model of the power grid expresses the impedance of the newly-added line by the product of the reactance x with unit length and the physical distance between two nodes related to the reactance x, namely:
X ij ＝x×d ij
in the above formula, X ij Is the reactance of the line between nodes i and j, d ij Is the length of the line between nodes i and j.
In step S6, the characteristic path length is defined as an average value of distances between all node pairs:
in the above formula, n is the number of network nodes, d ij Is the length of the line between nodes i and j.
In step S6, the clustering coefficient is defined as:
in the above formula, n is the number of network nodes, a i Number of triangles connected to node i, b i The number of triples connected to node i.
In step S6, the average degree is defined as:
in the above-mentioned formula, the compound has the following structure,<k> is the average value of all node degrees in the network, node degree k i N is the number of network nodes, and n is the number of edges having the node as an end point.
In step S6, the power flow variance of the lower-level power grid line is defined as:
in the above formula, F i And the current value of the node i, mu is the average current value of the lower-level power grid lines, and N is the number of the lower-level power grid lines.
The embodiment is as follows:
in this embodiment, a power grid growth evolution model simulation analysis is performed on a 500KV-220KV power grid in the north of the state of northward of hubei vitex, and the topological structure of the power transmission network in the region is shown in fig. 2 and is drawn by reducing the actual geographical position information of the local power network according to a certain proportion. In fig. 2, only the topology of the power grid is shown, and information such as the number of lines, the number of transformers, the number of generators, some transformer branches, and 500KV power injection is not shown. The load of the original 2 500KV transformer stations (Jiangling transformer stations and Xinglong transformer stations), 2 220KV power plants (Sha city power plants and Jiangling power plants) and 16 220KV transformer stations in the area is 2897.7MW. The power grid has 7 double-circuit lines and 21 single-circuit lines. In order to simulate the trend process of the west-east power transmission, 1 power supply point is respectively arranged on the left side of Jiangling 1 and above Xinglong. The capacity and the grid shedding load of the 220KV transformer substation in the northern region of Jingzhou are shown in table 1, and as can be seen from table 1, the load of the power grid in Jingzhou is concentrated in the northern region, and the annual load increase rate of the region is about 8% -6%. Assuming that the load increase factor λ of the first 5 years is 1.00018, the load increase factor λ from the 5 th to the 10 th years is 1.00015, and the load increase factor λ after the 10 th year is 1.00012.
Referring to fig. 1, the method for constructing the two-voltage-level power grid growth evolution model comprises the following steps:
s1, simulating annual load increase and power injection of a superior power grid substation, and judging whether the superior power grid substation is expanded or not according to the average capacity-load ratio of the superior power grid;
the power that subordinate's electric wire netting obtained from higher level electric wire netting simulates the increase of higher level electric wire netting transformer substation injection power according to the load increase factor, promptly:
P Hi，k+1 ＝λP Hi，k
in the above formula, P Hi，k The injection power of the upper-level power grid transformer substation i on the kth day is represented, and lambda is a load increase factor;
the average capacity-load ratio of the superior power grid is as follows:
in the above-mentioned formula, the compound has the following structure,and P dHM，k Capacity and load of the kth upper-level power grid node i substation respectively, ifExpanding a superior power grid substation; xi is the sum of all subordinate power grid substation loads within the growth point load range d;
s2, determining whether a lower-level power grid transformer substation needs to be newly built at the same day, if so, determining the position, load and capacity of the newly built lower-level power grid transformer substation, and accessing the transformer substation into a power grid according to a time-space evolution model;
with N sub The probability of/365 determines whether a new lower-level power grid transformer substation is needed to be built at the current day, if yes, the position of the new transformer substation is determined according to the load concentration degree, the new transformer substation is accessed into a power grid according to the space-time evolution model, and the load of the lower-level power grid transformer substation within the distance d is reduced in proportion;
the position of the newly-built transformer substation is determined through network growing points, the network growing points are defined as points which are not occupied in the network and have integral coordinates, the points are used as possible sites of the newly-built transformer substation, and the load concentration degree xi of each growing point is the sum of loads of all subordinate power grid transformer substations within the load range d of the growing point;
s3, judging whether the system is in power shortage or not, if so, determining to newly build a superior power grid transformer substation or a subordinate power grid power plant according to probability;
judging whether the system is in power shortage according to the balance of the electric power and the electric quantity of the system, wherein the judgment criterion is as follows:
P yu ＝P L +max{P genm ，γP L }
in the above formula, alpha is the lower limit value of the capacity-to-load ratio specified by two voltage class guiding rules, beta is the unit available capacity ratio, gamma is the sum of the load reserve ratio and the accident reserve ratio, S H For the total capacity of the upper level grid substation, P L Is the total load of the system, P genm For the maximum single machine capacity, P, of the power plant of the subordinate grid g The total power generation capacity of the power plant;
newly-built transformer substation and power plant all insert the electric wire netting according to the spatio-temporal evolution model of electric wire netting, because newly-increased circuit impedance receives the influence of multiple factor, consequently does not lose the generality, and the spatio-temporal evolution model of electric wire netting will newly-increased circuit impedance with the product of unit length reactance x and the physical distance between two nodes that it is relevant, promptly:
X ij ＝x×d ij
in the above formula, X ij Reactance of the line between nodes i and j, d ij Is the length of the line between nodes i and j;
s4, performing N-1 verification on the line, and upgrading and transforming weak lines which do not meet the verification;
the load factor of the line is defined as:
ρ＝|F l /F lmax |
in the above formula, F l For line currents, F lmax For the capacity of the line, the line with rho larger than 1 is an overload line;
the model carries out N-1 verification on the power grid lines and requires that each line meets the N-1 principle;
s5, repeating the steps S1-S4 until the number of iteration days exceeds the number of iteration days required;
specifically, the results of 5 years, 10 years and 15 years of evolution are respectively shown in fig. 3, fig. 4 and fig. 5, and as can be seen from fig. 3 to fig. 5, after 5 years (2022 years), 1 500KV transformer station, namely a peach station, 4 220KV transformer stations and 10 lines are newly added in the area; after 10 years (2027), 1 500KV transformer substation-Jiangling 2 station, 15 220KV transformer substations and 20 lines are newly added in the area; after 15 years (2032 years), 11 new 220KV substations and 25 lines are added in the area;
as can be seen in connection with fig. 5: most newly-built transformer substations are concentrated in northern part of Jingzhou with concentrated loads, the site selection of the transformer substation of the model is reasonable, and after the model evolves for 5 years for many times, a 500KV transformer substation-Xiantao station is newly added to a power grid in the area, which is identical with 2020-year power grid geographical wiring of Jingzhou power grid planning, and the correctness of the model is shown;
s6, evaluating an evolution result through the characteristic path length, the clustering coefficient, the average degree and the power flow variance of a lower-level power grid line;
the characteristic path length is defined as the average of the distances between all pairs of nodes:
in the above formula, n is the number of network nodes, d ij Is the length of the line between nodes i and j;
the clustering coefficient is a parameter for describing the clustering degree of the network, and the clustering coefficient C of the whole network is defined as:
in the above formula, n is the number of network nodes, a i Number of triangles connected to node i, b i The number of triples connected to the node i;
the average is defined as:
in the above-mentioned formula, the compound has the following structure,<k> is the average value of all node degrees in the network, node degree k i The number of edges taking the node as an end point, and n is the number of network nodes;
the power flow variance of the lower-level power grid line is defined as:
in the above formula, F i And the mu is the average value of the tidal current of the lower-level power grid line, and the N is the number of the lower-level power grid lines.
The specific evolution results are evaluated as shown in the following table:
TABLE 1
As can be seen from table 1, the complex network characteristic parameters of the power grid finally obtained by using the model for evolution are as follows: the characteristic path length L, the clustering coefficient C, the mean degree < k >, and the lower-level power grid line power flow variance D (F) are all close to the initial network, and the clustering performance of nodes in the power grid can be reflected.
Claims (9)
1. A method for constructing a two-voltage-level power grid growth evolution model is characterized by comprising the following steps of:
s1, simulating annual load increase and power injection of a superior power grid substation, and judging whether the superior power grid substation is expanded or not according to the average capacity-load ratio of the superior power grid;
s2, determining whether a lower-level power grid transformer substation needs to be newly built at the same day, if the lower-level power grid transformer substation needs to be newly built, determining the position, the load and the capacity of the newly built lower-level power grid transformer substation, and accessing the power grid according to the space-time evolution model;
s3, judging whether the system is in power shortage, if so, determining to newly build a superior power grid transformer substation or a subordinate power grid power plant according to probability;
s4, performing N-1 verification on the line, and upgrading and transforming the weak line which does not meet the verification;
s5, repeating the steps S1-S4 until the number of iteration days exceeds the number of required iteration days;
and S6, evaluating the evolution result through the characteristic path length, the clustering coefficient, the average degree and the power flow variance of the lower-level power grid line.
2. The method for constructing the two-voltage-class power grid growth evolution model according to claim 1, wherein the two-voltage-class power grid growth evolution model comprises the following steps: in step S1, the average capacity-to-load ratio of the upper-level power grid is:
in the above formula, the first and second carbon atoms are,and P dHM，k Capacity and load of the kth upper-level power grid node i substation respectively, ifExpanding a superior power grid substation; xi is all subordinate power grid transformation within growth point load range dThe sum of the station loads.
3. The method for constructing the two-voltage-level power grid growth evolution model according to claim 1, wherein the two-voltage-level power grid growth evolution model comprises the following steps: in the steps S2 and S3, the position of the newly-built substation is determined through network growing points, the network growing points are defined as points which are not occupied in the network and have integral coordinates, and the load concentration degree xi of each growing point is the sum of loads of all lower-level power grid substations within the load range d of the growing point.
4. The method for constructing the two-voltage-level power grid growth evolution model according to claim 1, wherein the two-voltage-level power grid growth evolution model comprises the following steps: in step S3, whether the system is in power shortage is determined according to the power-electricity balance of the system, and the determination criteria are:
P yu ＝P L +maX{P genm ，γP L }
in the above formula, alpha is the lower limit value of the capacity-to-load ratio specified by two voltage class guiding rules, beta is the unit available capacity ratio, gamma is the sum of the load reserve ratio and the accident reserve ratio, S H For the total capacity of the upper level grid substation, P L Is the total load of the system, P genm Maximum single machine capacity, P, of power plant of lower-level power grid g Is the total power generation of the power plant.
5. The method for constructing the two-voltage-class power grid growth evolution model according to claim 1, wherein the two-voltage-class power grid growth evolution model comprises the following steps: in the steps S2 and S3, the newly-built transformer substation and the power plant are both accessed into the power grid according to a space-time evolution model of the power grid, the space-time evolution model of the power grid expresses the newly-added line impedance by the product of the reactance x with unit length and the physical distance between two nodes related to the reactance x, namely:
X ij ＝x×d ij
in the above formula, X ij Is the node i and jReactance of the line between, d ij Is the length of the line between nodes i and j.
6. The method for constructing the two-voltage-class power grid growth evolution model according to claim 1, wherein the two-voltage-class power grid growth evolution model comprises the following steps: in step S6, the characteristic path length is defined as an average value of distances between all node pairs:
in the above formula, n is the number of network nodes, d ij Is the length of the line between nodes i and j.
7. The method for constructing the two-voltage-class power grid growth evolution model according to claim 1, wherein the two-voltage-class power grid growth evolution model comprises the following steps: in step S6, the clustering coefficient is defined as:
in the above formula, n is the number of network nodes, a i For the number of triangles connected to node i, b i Is the number of triples connected to node i.
8. The method for constructing the two-voltage-class power grid growth evolution model according to claim 1, wherein the two-voltage-class power grid growth evolution model comprises the following steps: in step S6, the average degree is defined as:
in the above formula, the first and second carbon atoms are,<k> is the average value of all node degrees in the network, the node degree k i N is the number of network nodes, and n is the number of edges having the node as an end point.
9. The method for constructing the two-voltage-class power grid growth evolution model according to claim 1, wherein the two-voltage-class power grid growth evolution model comprises the following steps: in step S6, the power flow variance of the lower-level power grid line is defined as:
in the above formula, F i And the mu is the average value of the tidal current of the lower-level power grid line, and the N is the number of the lower-level power grid lines.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711117291.2A CN107959287B (en) | 2017-11-13 | 2017-11-13 | Method for constructing two-voltage-level power grid growth evolution model |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711117291.2A CN107959287B (en) | 2017-11-13 | 2017-11-13 | Method for constructing two-voltage-level power grid growth evolution model |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107959287A true CN107959287A (en) | 2018-04-24 |
| CN107959287B CN107959287B (en) | 2020-05-08 |
Family
ID=61964447
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711117291.2A Active CN107959287B (en) | 2017-11-13 | 2017-11-13 | Method for constructing two-voltage-level power grid growth evolution model |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107959287B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110232642A (en) * | 2019-06-28 | 2019-09-13 | 国网河北省电力有限公司经济技术研究院 | A kind of topology planning and optimization method towards power failure risk-aversion |
| CN112131689A (en) * | 2020-08-05 | 2020-12-25 | 长沙理工大学 | Method for constructing partial information network growth evolution model based on topological graph of power system |
| CN113888350A (en) * | 2021-09-26 | 2022-01-04 | 国网湖北省电力有限公司经济技术研究院 | Power grid planning project ordering method considering power supply reliability in transition period |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104793107A (en) * | 2015-04-29 | 2015-07-22 | 东北大学 | Power grid cascading failure determination method based on improved OPA model |
| CN107294103A (en) * | 2017-07-24 | 2017-10-24 | 广东工业大学 | A kind of section tidal current control method and device |
-
2017
- 2017-11-13 CN CN201711117291.2A patent/CN107959287B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104793107A (en) * | 2015-04-29 | 2015-07-22 | 东北大学 | Power grid cascading failure determination method based on improved OPA model |
| CN107294103A (en) * | 2017-07-24 | 2017-10-24 | 广东工业大学 | A kind of section tidal current control method and device |
Non-Patent Citations (1)
| Title |
|---|
| 杨蕾: "复杂电力网络建模与自组织临界性分析", 《CNKI中国优秀硕士学位论文全文库》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110232642A (en) * | 2019-06-28 | 2019-09-13 | 国网河北省电力有限公司经济技术研究院 | A kind of topology planning and optimization method towards power failure risk-aversion |
| CN110232642B (en) * | 2019-06-28 | 2021-07-09 | 国网河北省电力有限公司经济技术研究院 | Topology planning and optimizing method and device for power failure risk prevention |
| CN112131689A (en) * | 2020-08-05 | 2020-12-25 | 长沙理工大学 | Method for constructing partial information network growth evolution model based on topological graph of power system |
| CN113888350A (en) * | 2021-09-26 | 2022-01-04 | 国网湖北省电力有限公司经济技术研究院 | Power grid planning project ordering method considering power supply reliability in transition period |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107959287B (en) | 2020-05-08 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110619454B (en) | Power distribution network planning method based on improved genetic algorithm and PRIM algorithm | |
| Muljadi et al. | Equivalencing the collector system of a large wind power plant | |
| CN107591841B (en) | Power grid Evolution Simulation method under being accessed on a large scale suitable for new energy | |
| CN108462210B (en) | Photovoltaic open capacity calculation method based on data mining | |
| CN107959287B (en) | Method for constructing two-voltage-level power grid growth evolution model | |
| CN109598377B (en) | AC/DC hybrid power distribution network robust planning method based on fault constraint | |
| CN107230999B (en) | Regional distributed photovoltaic maximum capacity access evaluation method | |
| CN108400595A (en) | A kind of voltage dip Stochastic prediction method considering new energy output correlation | |
| CN104866919A (en) | Multi-target planning method for power grid of wind farms based on improved NSGA-II | |
| CN113569411B (en) | Disaster weather-oriented power grid operation risk situation awareness method | |
| CN110299762A (en) | Active distribution network Robust filter method based on PMU near-realtime data | |
| CN114676569B (en) | Power grid simulation analysis example, and generation method, generation system, equipment and medium thereof | |
| CN112561273A (en) | Active power distribution network renewable DG planning method based on improved PSO | |
| CN109301870A (en) | A kind of more feed-in power system capacity optimization methods of power electronics | |
| CN112103950B (en) | Power grid partitioning method based on improved GN splitting algorithm | |
| CN113991856A (en) | Multi-adaptability mu PMU optimal point distribution method for micro energy network | |
| CN111756075B (en) | Method for designing and testing power distribution system examples containing distributed power supply | |
| Yu et al. | Optimization of an offshore oilfield multi-platform interconnected power system structure | |
| CN113690930B (en) | NSGA-III algorithm-based medium and long term locating and sizing method for distributed photovoltaic power supply | |
| Wirtz et al. | Modelling of synthetic high voltage networks based on open data and integration into a modular synthetic distribution grid generator | |
| Moeini et al. | Disco planner flexible DG allocation in MV distribution networks using multi-objective optimization procedures | |
| CN104793107B (en) | A kind of power grid cascading fault determination method based on improvement OPA models | |
| CN114741858A (en) | Multi-level power grid planning method based on growth evolution model | |
| CN112018757A (en) | General example generation method for morphological evolution of power distribution network | |
| Wang et al. | Optimal Planning of Distributed Generation and Loads in Active Distribution Network: A Review |
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 |