CN109960876B - Power distribution network planning space data model simplification method - Google Patents
Power distribution network planning space data model simplification method Download PDFInfo
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Abstract
The invention provides a method for simplifying a power distribution network planning space data model, which comprises the following steps: s1, integrating power distribution network frame data based on a Neo4j graph database to construct a power distribution network frame data undirected graph; s2, establishing a simplified rule base and a power grid equipment connection specification based on expert knowledge, and establishing an equipment element equivalent simplified model by combining a power distribution network frame data undirected graph to realize equivalent simplification of a power distribution network frame; and S3, carrying out graph simplification on the power distribution network frame based on a Stroke Douglas-Peucke graph simplification algorithm. The method can greatly reduce redundant equipment in network frame planning, improve the visualization quality of the power grid network frame, facilitate displaying the current situation data of the power distribution network, reflect the defects of the current situation network frame, visually display the comprehensive situation of the planned network frame, reflect the rationality of a power distribution network planning scheme, provide auxiliary analysis for power distribution network planning workers, and improve the working efficiency of power distribution network planning and design.
Description
Technical Field
The invention relates to the field of GIS and the field of electric power, in particular to a method for simplifying a power distribution network planning space data model.
Background
In recent years, in the face of increasingly intensified resource environmental pressure, low carbon in the power industry is promoted to be an inevitable choice for realizing the aims of energy conservation, emission reduction and ecological civilization. There are two major ways to reduce the energy consumption of an electrical power system: and the access of renewable energy sources saves energy and reduces loss of a power grid. The distribution network is an important way of power grid transmission and is an important link for connecting a power system or a power supply with user facilities. According to statistics, the electric energy loss generated by a 10kV power distribution network accounts for about half of the total loss of the whole power distribution network, and 80% of power failure accidents of users are caused by power distribution network faults.
Therefore, only by carrying out scientific and reasonable power distribution network planning and selecting proper power distribution network structure and layout, the capability of receiving and optimally configuring various energy sources by the power grid can be improved, the power supply quality is effectively improved, the safety and reliability of power transmission are ensured, the utilization efficiency and the benefit of huge power grid assets are further improved, and higher-quality service is provided for users.
Planning data is the basis of power distribution network planning. At present, the planning of the power distribution network needs to examine and collect mass data so as to ensure that reasonable and effective planning of the power distribution network can be made. However, as the power distribution network becomes increasingly large, the structure becomes increasingly complex and the data is updated frequently, the statistical collection of planning data, the analysis, modeling and calculation of the power distribution network under the current situation become more difficult.
At present, an integrated power grid planning and designing platform is mainly used as a power distribution planning and applying platform. The required distribution network current situation data of this platform relies on artifical arrangement to generate at present, and work load is very big, is unfavorable for the project and popularizes and applies. After the scale is reduced, the net rack line equipment is frequently and integrally displayed in a disordered way, even the main lines and structures of the power distribution network cannot be distinguished, and the decision judgment of planning and designing personnel is seriously influenced. The existing power grid system stores and manages complete power grid data, but data required by power distribution network planning is only a subset of the data, and if huge and detailed power grid data are transmitted, stored, inquired, edited and displayed, huge challenges are brought to an integrated power grid planning and designing platform, and the existing power grid system is very unfavorable for accurately and efficiently extracting the current situation data of the power distribution network.
Therefore, the invention provides a method for simplifying a power distribution network planning space data model.
Disclosure of Invention
The invention aims to overcome the defects and shortcomings of the conventional power distribution network planning system, and provides a method for simplifying a spatial data model of power distribution network planning.
The purpose of the invention is realized by the following technical scheme:
the invention provides a method for simplifying a power distribution network planning space data model, which comprises the following steps in sequence:
s1, integrating power distribution network frame data based on a Neo4j graph database to construct a power distribution network frame data undirected graph;
s2, establishing a simplified rule base based on expert knowledge, and establishing an equipment element equivalence simplified model by combining a power distribution network frame data undirected graph to realize equivalence simplification of a power distribution network frame;
and S3, simplifying the network frame graph of the power distribution network based on a Stroke Douglas-Peucke graph simplification algorithm.
Further, in step S1 of the present invention, the distribution network frame data is integrated based on the Neo4j graph database:
the existing power distribution network data are stored in a power distribution network asset system, dozens of power distribution facilities are involved, complex operation relations and affiliation relations exist among various power distribution facilities, the relations are modeled by a traditional relational database, a large number of relational tables need to be maintained, the detailed power distribution network data are obtained from the existing power distribution network system, a power distribution network frame data undirected graph is constructed according to an actual power grid structure based on a Neo4j graph database, and power distribution network information including attribute information and topology information is stored. The distribution network frame data undirected graph is defined as follows:
G(V,P,R)＝{{V},{P},{R}}
wherein V represents a set of devices V = { V) in the distribution network 1 ,v 2 ,...,v n H, including transformers, busbars, switches, etc., pi represents a set P of attributes of a device i i ＝{p i1 ,p i2 ,...,p ij And the like, wherein R represents a relation set R = { R = between devices 1 ,r 2 ,...,r k Mainly having an affiliated relationship and an operational relationship;
further, in step S2 of the present invention, the establishing a simplified rule base for power distribution network planning based on expert knowledge specifically includes:
the simplified power distribution network simplifies redundant equipment and simultaneously reserves key equipment elements and attributes thereof to meet the requirement of electrical calculation, so that a universal in-station and out-station equipment model is constructed by combining a power distribution network frame data undirected graph according to rules in the actual power distribution network planning process and the existing network frame structure, and an equivalent simplification rule is drawn up.
Further, in step S2 of the present invention, the establishing of the equivalent simplified model of the device element specifically includes:
although the existing power distribution network system stores and manages complete power grid data, data required by actual power distribution network planning is only a subset of the data, so that existing complex equipment is abstracted into a uniform in-station and out-station model according to the simplified rule base determined in the step S1 and the power grid equipment connection specification, and therefore the complex problem existing in the actual data is effectively avoided, and the specific steps are as follows:
s21, building an in-station simplified model according to the simplified rule and the in-station equipment connection relation;
s22, constructing an off-site simplified model according to the simplified rule and the connection relation of the off-site equipment;
and S23, replacing the complex equipment of the original net rack with the uniform in-station model equivalent and the uniform out-station model equivalent to participate in electrical calculation.
Further, in step S3, the graph simplification is performed on the power distribution network frame based on the Douglas-Peucke graph simplification algorithm of Stroke, which is specifically as follows:
s31, carrying out Stroke division on the power distribution network;
s32, simplifying the network frame graph of the power distribution network based on a Stroke Douglas-Peucke graph simplification algorithm;
s33, calculating an optimal simplifying threshold lambda of a Stroke-based Douglas-Peucke graph simplifying algorithm 0 So as to optimize the parameters of the graph simplification method in S32 and realize the optimal graph simplification.
Further, in step S31 of the present invention, a power distribution network is subjected to Stroke division, and the method includes:
first, the distribution network Stroke is defined as follows:
wherein X represents a set of line segments (including conductor segments and cable segments) in the power distribution network, X i Represents the ith line segment therein, st represents the Stroke set, st i Indicating the ith Stroke.
The Stroke partitioning is equivalent to splitting the set X into m sets St 1 ，St 2 ，...，St m And the following three conditions are satisfied:
in the formula, st represents a Stroke set, st i Denotes the ith Stroke, and m denotes the number of divided strokes.
Secondly, according to the above Stroke definition, stroke division is performed on each specific line:
firstly, taking each line as a Stroke according to the line name in the power distribution network; if the T node exists in the Stroke, continuously dividing the T node into a plurality of Stroke, and obtaining a Stroke set St = { St = { (St) 1 ,St 2 ,...St m }；
Further, in step S32 of the present invention, graph simplification is performed on the power distribution network based on the Douglas-Peucke graph simplification algorithm of Stroke, which is specifically as follows:
s321, determining a value range (lambda) of a meaningful simplified threshold value of the Douglas-Peucke graph simplified algorithm according to specific power distribution network frame data and empirical values a ，λ b ) Arbitrarily take λ a ＜λ＜λ b ；
S322, defining important nodes H = { H ] in the original line according to the simplified rule base in the step 2 1 ,H 2 ,...,H n }；
S323, each Stroke St in the set St i Is provided with St i Starting point of (c) is P (x) 1 ,y 1 ) And end point Q (x) 2 ,y 2 )，St i Is M = { M 1 ,M 2 ,...M n In which M is i ＝(x i ,y i ) Calculating M i Distance d to line PQ i :
In the above formula, A, B and C are three coefficients in the general equation of the line PQ, d i Is M i Distance to line segment PQ;
s324, taking D = max { D 1 ,d 2 ,...,d n D is M k If D < lambda, S325 is executed, otherwise, if D > lambda, stroke St is executed i Division into two sub-strokes, i.e. division into starting point P, M k As end point and with M k Taking Q as two sub Stroke of the end point as a starting point, and executing S323;
s325, to Stroke St i Set of other nodes M = { M = { M } 1 ,M 2 ,...M n }，M i ＝(x i ,y i ) If M is i E is H, then M is i Added to the set Z, Z = { Z = { (Z) 1 ,Z 2 ,...,Z n S326 is executed, otherwise, all points in the set M are driven from Stroke St i Deleting;
s326, calculating Z i Distance d to PQ Zi Get it
D Z The corresponding node is Z k Introducing a displacement tolerance eta if D Z If eta, executing S327, otherwise, executing P, Z k And Q is the end point, divide Stroke again, carry out S325;
s327, set Z = { Z 1 ,Z 2 ,...,Z n Point Z in i Projected in a vertical projection onto a straight line PQ and from Stroke St i Deleting points not belonging to the set Z, and calculating Z i Coordinate (X) after projection i ,Y i )：
Stroke St i The remaining point set after simplification is { P, Q, Z 1 ,Z 2 ,...,Z n }；
S328, removing the current Stroke from the St set, circularly executing S323, and processing each Stroke in the St set until the St set is empty;
further, in step S33 of the present invention, an optimal simplification threshold λ of the Douglas-Peucke graph simplification algorithm is determined 0 The method comprises the following steps:
s331, determining the value range (lambda) of the meaningful simplified threshold value of the Douglas-Peucke graph simplified algorithm according to concrete power distribution network frame data and experience a ，λ b )；
S332 at λ a As initial threshold, h = (λ) a -λ b ) 300 is an increasing step length, and a Stroke-based Douglas-Peucke graph simplification algorithm is circularly operated;
s333, counting each lambda i And the total number of the remaining nodes of the Stroke curve simplified by the Stroke-based Douglas-Peucke graph simplification algorithm
S334, fitting function N based on least square method λi ＝f(λ i )；
S335, calculating curve f (lambda) i ) Of (2) is
Taking the threshold lambda for maximizing the K value i For optimum simplification of the threshold, i.e. λ 0 ＝λ i 。
S336, simplifying the optimal threshold value lambda 0 And substituting the lambda in the S324, and executing a simplification algorithm to obtain an optimal simplified graph.
Total number N of nodes left in Stroke curve simplified by Douglas-Peucke graph simplification algorithm based on Stroke λi With reduced threshold λ i Decreases and finally approaches a stable value, where λ i Representing a simplifying force, N λi Can be used to measure the effectiveness of the simplification, the problem of taking the optimum threshold can be ascribed to the value at λ i -N λi Taking an optimal balance point, simultaneously considering the simplification strength and the simplification effect, and taking a curve f (lambda) i ) Threshold lambda corresponding to maximum curvature K 0 The point at which the curve is most curved is defined by the value of λ i ＜λ 0 Further simplification can be continued, if λ i > λ, with λ i The quality of the simplified pattern is seriously degraded by the increase of (2).
Compared with the prior art, the invention has the following advantages and beneficial effects:
(1) The method is based on the characteristics of various devices and complex relationships of the power distribution network, combines a power grid equivalence simplification method and a map synthesis method, divides the power distribution network simplification into equivalence simplification and graph simplification, wherein equivalence simplification is realized by constructing a unified device connection model so as to simplify the device types and connection relationships, and graph simplification simplifies the spatial connection relationships and optimizes the visualization effect by applying a Stroke-based Douglas-Peucke graph simplification algorithm.
(2) The invention realizes concise display of the spatial data of the power distribution network and simultaneously meets the electrical calculation requirement of the network frame for planning the power distribution network. The simplified equipment amount is greatly reduced relative to the original data, the current situation data of the power distribution network is favorably inquired and displayed graphically, digitally and interactively, the defects of the current situation net rack and the rationality of a power distribution network planning scheme are reflected visually, auxiliary analysis is provided for power distribution network planning workers, and the working efficiency of power distribution network planning design is improved.
Drawings
FIG. 1 is a schematic flow chart diagram illustrating a simplified method for planning spatial data models of a power distribution network according to an embodiment of the present invention;
FIG. 2 is a flowchart of a Stroke-based Douglas-Peucke graph simplification algorithm for the method of FIG. 1;
FIG. 3 is a schematic diagram of an in-station equivalence model of the method depicted in FIG. 1;
fig. 4 is a simplified schematic diagram of a power distribution network according to the method of fig. 1.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, the method for simplifying the spatial data model of power distribution network planning according to the embodiment of the present invention includes the following steps:
s1, integrating power distribution network frame data based on a Neo4j graph database to construct a power distribution network frame data undirected graph;
s2, establishing a simplified rule base based on expert knowledge, and establishing an equipment element equivalent simplified model by combining a power distribution network frame data undirected graph to realize equivalent simplification of a power distribution network frame;
and S3, carrying out graph simplification on the power distribution network frame based on a Stroke Douglas-Peucke graph simplification algorithm.
The basic idea of the method of the invention is as follows: the existing power grid system stores complete equipment and data in the whole power system, but for power distribution network planning, a lot of equipment and data are unnecessary, the data required by the power distribution network planning are only a subset of the data, the data are designed only on the level of power stations and lines, and no attention is paid to specific equipment types in the power stations and irrelevant equipment mounted on the lines. If the detailed power grid data are required to be transmitted, stored, inquired, edited and displayed, great challenges are brought to an integrated power grid planning design platform, so that the space data model simplification method for power distribution network planning provided by the invention integrates a power grid equivalent simplification method and a map comprehensive method, starts from two aspects of equivalent simplification and graph simplification, firstly draws a simplification rule according to the actual power distribution network planning requirement in the aspect of equivalent simplification, and then abstracts complex equipment into a model inside and outside a unified station by combining with the power grid equipment connection specification, thereby effectively avoiding the complex problems existing in the actual data, and replacing the original complex equipment with the model to participate in subsequent electrical calculation; in the aspect of graph simplification, the invention provides a Stroke-based Douglas-Peucke graph simplification algorithm, which improves the line visualization effect and simultaneously furthest retains the original geometric characteristics of the line visualization algorithm.
The key creation point of the invention is to innovatively combine the GIS field with the power field, simplify two requirements based on the graph simplification and the electrical calculation of the power distribution network, improve and combine the methods in the two fields, simplify complex power distribution network data, greatly reduce the simplified equipment quantity relative to the original data, be beneficial to displaying the current situation data of the power distribution network, reflect the defects of the current situation network frame, visually display the comprehensive condition of the planned network frame, reflect the rationality of a planning scheme of the power distribution network, provide auxiliary analysis for power distribution network planning workers, improve the working efficiency of power distribution network planning design and have higher practicability.
In another embodiment of the invention:
the invention provides a method for simplifying a space data model for planning a power distribution network, which comprises the following specific steps:
step 1, integrating power distribution network frame data based on a Neo4j graph database to construct a power distribution network frame data undirected graph.
The basis of this embodiment is high-voltage distribution network data in the province city of hubei province, and the power grid data comes from the existing power grid system, and in order to facilitate subsequent simplified operation, this embodiment selects a Neo4j graph database as a database for storing the power grid data, and integrates the data, and ensures that the data used for subsequent operation has correct topological connection relation, device dependency relation, and integrity of the power grid device and its basic ledger data, which is specifically as follows:
G(V,P,R)＝{{V},{P},{R}}
wherein V represents a set of devices V = { V) in the distribution network 1 ,v 2 ,...,v n }，P i Attribute set P representing device i i ＝{p i1 ,p i2 ,...,p ij And basic ledger data and other attribute data are mainly included, wherein R represents a relationship set R = { R = between devices 1 ,r 2 ,...,r k A topology connection relationship and an equipment dependency relationship are included;
step 2, establishing a simplified rule base and a power grid equipment connection standard based on expert knowledge, and establishing an equipment element equivalent simplified model by combining a power distribution network frame data undirected graph to realize equivalent simplification of a power distribution network frame: and establishing a simplified rule base according to the actual power distribution network planning requirement, and then abstracting complex equipment into a model for unifying the inside and outside of the station by combining the power grid equipment connection specification and the power distribution network frame data undirected graph.
In the existing power grid system, detailed data in the whole power distribution network is stored, but only a small subset is needed in the planning process of the power distribution network, and the design is only carried out on the level of power stations and lines in the planning process, and no attention is paid to specific equipment types in the power stations and irrelevant equipment mounted on the lines. Therefore, it is necessary to establish a simplified rule base according to the actual power distribution network planning requirements, and then abstract the complex equipment into a model of unifying the inside and outside of the station by combining with the power grid equipment connection specification. The in-station equivalent model simplification is shown in fig. 3, in order to avoid the complex and variable connection problem existing in actual data or the data quality problem caused by data errors, complex in-station equipment is abstracted into a uniform in-station model, the most main equipment in a transformer substation is provided with general equipment such as a transformer, a bus and a switch and other special equipment which are inevitably present in the transformer substation, so that the same in-station equipment simplification model is established based on the power equipment connection specification, the model comprises the maximum set of simplified equipment and the connection relation among the equipment, and then the actual equipment is mapped into the model. The off-site equivalence simplification method is similar to the on-site equivalence method, and a universal connection model is also constructed, wherein the universal connection model comprises key equipment and equipment related to electric calculation. The method has the greatest advantage that the problem of complex equipment connection caused by data problems can be avoided.
And 3, carrying out graph simplification on the power distribution network frame based on a Stroke Douglas-Peucke graph simplification algorithm (shown in figure 2). The step 3 is specifically as follows:
step S31: stroke partitioning of a power distribution network
According to the definition of Stroke of the power distribution network:
wherein X represents a collection of line segments (including conductor segments and cable segments) in a power distribution network, X i Representing the ith line segment, representing a Stroke set by S, S i Represents the ith Stroke, and meets the following conditions:
in the formula, st represents a Stroke set, st i Denotes the ith Stroke, and m denotes the number of divided strokes.
According to the above Stroke definition, stroke division is performed on each specific line:
firstly, taking each line as a Stroke according to the line name in the power distribution network; if a T node is present in the Stroke, then, the node T is continuously divided into multiple strings, and a string set St = { St = is obtained 1 ,St 2 ,...St m }；
Step S32: graph simplification algorithm for power distribution network frame based on Stroke Douglas-Peucke graph simplification algorithm
S321, determining the value range (lambda) of meaningful simplified threshold of Douglas-Peucke graphic simplified algorithm according to empirical values a ，λ b ) Arbitrarily take λ a ＜λ＜λ b ；
S322, defining important nodes H = { H ] in the original line according to the simplified rule base in the step 2 1 ,H 2 ,...,H n }；
S323, each Stroke St in the set St i Is provided with St i Starting point of (b) is P (x) 1 ,y 1 ) And endpoint Q (x) 2 ,y 2 )，St i Other node in (2) set of (c) M = { M = { M = 1 ,M 2 ,...M n In which M is i ＝(x i ,y i ) Calculating M i Distance d to line PQ i :
In the above formula, A, B and C are three coefficients in the general equation of the line PQ, d i Is M i Distance to line segment PQ;
s324, taking D = max { D 1 ,d 2 ,...,d n D is M k If D < lambda, S325 is executed, otherwise if D > lambda, stroke St is executed i Division into two sub-Stroke, i.e. division into starting points P, M k As end point and with M k Taking Q as two sub Stroke of the end point as a starting point, and executing S323;
s325, to Stroke St i Set of other nodes M = { M = { M } 1 ,M 2 ,...M n }，M i ＝(x i ,y i ) If M is present i E is in H, then M is added i Added to the set Z, Z = { Z = { (Z) 1 ,Z 2 ,...,Z n S326 is executed, otherwise, all points in the set M are driven from Stroke St i Deleting;
s326, calculating Z i Distance to PQ
Fetch and hold>
D Z The corresponding node is Z k Introducing a displacement tolerance eta, if D Z If eta, executing S327, otherwise, executing P, Z k And Q is the end point, divide Stroke again, carry out S325;
s327, set Z = { Z = 1 ,Z 2 ,...,Z n Point Z in i Projected in a perpendicular projection onto a straight line PQ and from Stroke St i Deleting points not belonging to the set Z, and calculating Z i Coordinate (X) after projection i ,Y i )：
Stroke St i The remaining point set after simplification is { P, Q, Z 1 ,Z 2 ,...,Z n }；
S328, removing the current Stroke from the St set, executing the current Stroke circularly S323, and processing each Stroke in the St set until the St set is empty;
step S33: determining an optimal simplification threshold lambda of a Douglas-Peucke graph simplification algorithm 0
S331, determining the value range (0.0001, 0.07) of a meaningful simplification threshold of the Douglas-Peucke graph simplification algorithm according to the empirical value;
s332 at λ a For an initial threshold value, h =0.0002 is an increasing step size, and a Stroke-based Douglas-Peucke graph simplification algorithm is circularly operated;
s333, statistics of lambda i And the total number of the residual nodes of the Stroke curve after being simplified by the Stroke-based Douglas-Peucke graph simplification algorithm
S334, fitting function N by least square method in form of exponential function λ ＝f(λ)：
f(λ)＝278.8*e -309.9λ +88.26*e -4.127λ
S335, calculating a curve f (lambda) i ) Of (2) curvature
Taking the threshold lambda for maximizing the K value i =0.0205 as optimal reduced threshold, i.e. λ 0 ＝0.0250。
S336, simplifying the optimal threshold value lambda 0 And substituting the step S32, and executing an optimization program to obtain the optimal graph simplification effect.
The simplified schematic diagram of the power distribution network graph is shown in fig. 4, in the equivalent simplification of the step S2, the equipment number of the power distribution network frame is simplified, but the graph structure of the network frame is not changed, while the graph simplification of the step S3 is mainly performed on the wires and cables which have influence on the network frame graph, the simplified wires and cables only remain the wires with larger deflection angles, the wires and cables with smaller deflection angles are projected, and the geometric shape of the original network frame is retained to the maximum extent while the graph structure of the power distribution network is simplified.
Aiming at the problems that the current power distribution network data volume is huge, planning data is mainly generated by means of manual arrangement, the workload is large and errors are prone to occurring, a map synthesis method and power grid equivalence simplification are innovatively combined, a simplification method of a power distribution network planning space data model is provided, redundant equipment in network frame planning can be greatly reduced, the visualization quality of a power grid network frame is improved, the simplified equipment volume is greatly reduced relative to original data, the simplified equipment volume can be directly applied to an integrated planning design platform, the method is beneficial to graphical, digital and interactive query and display of power distribution network current situation data, the defects of the current situation network frame are reflected, the optimization degree of the planned network frame is visually displayed, the rationality of a planning scheme is reflected, auxiliary analysis is provided for power distribution network planning workers, and the working efficiency of power distribution network planning design is improved.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are also within the scope of the present invention.
Claims (8)
1. A method for simplifying a power distribution network planning space data model is characterized by comprising the following steps:
s1, integrating power distribution network frame data based on a Neo4j graph database to construct a power distribution network frame data undirected graph;
s2, establishing a simplified rule base and a power grid equipment connection specification based on expert knowledge, and establishing an equipment element equivalent simplified model by combining a power distribution network frame data undirected graph to realize equivalent simplification of a power distribution network frame;
and S3, carrying out graph simplification on the power distribution network frame based on a Stroke Douglas-Peucke graph simplification algorithm.
2. The power distribution network planning spatial data model simplification method of claim 1, characterized in that: in the step S1, power distribution network frame data are integrated based on a Neo4j graph database, and the method specifically comprises the following steps:
acquiring detailed power distribution network data from an existing power grid asset system, constructing a power distribution network frame data undirected graph according to an actual power grid structure based on a Neo4j graph database, and storing power distribution network information including attribute information and topological information;
the distribution network frame data undirected graph is defined as follows:
G(V,P,R)＝{{V},{P},{R}}
wherein V represents a set of devices V = { V) in the distribution network 1 ,v 2 ,...,v n }, including transformer, bus, switch, P i Attribute set P representing device i i ＝{p i1 ,p i2 ,...,p ij And the voltage level, the type number and the length are included, R represents a relation set R = { R = between devices 1 ,r 2 ,...,r k And (4) mainly having an affiliated relationship and an operational relationship.
3. The method for simplifying the planning spatial data model of the power distribution network according to claim 1, wherein: in step S2, a simplified rule base is established based on expert knowledge, specifically: and constructing a universal in-station and out-station equipment model according to rules in the actual power distribution network planning process and the existing grid structure, so as to draw a simplification rule, and the simplified power distribution network simplifies redundant equipment and simultaneously reserves key equipment elements and attributes thereof so as to meet the requirement of electrical calculation.
4. The power distribution network planning spatial data model simplification method of claim 1, characterized in that: in step S2, the establishment of the equivalent simplified model of the device element is specifically as follows:
s21, building an in-station simplified model according to the simplified rule and the in-station equipment connection relation;
s22, constructing an off-site simplified model according to the simplified rule and the connection relation of the off-site equipment;
and S23, replacing the complex equipment of the original net rack with the unified in-station model equivalent and the unified out-station model equivalent to participate in the electrical calculation.
5. The method for simplifying the planning spatial data model of the power distribution network according to claim 1, wherein: in step S3, the graph of the power distribution network frame is simplified based on the Douglas-Peucke graph simplification algorithm of the Stroke, which is specifically as follows:
s31, carrying out Stroke division on the power distribution network;
s32, simplifying the network frame graph of the power distribution network based on a Stroke Douglas-Peucke graph simplification algorithm;
s33, calculating an optimal simplifying threshold lambda of a Stroke-based Douglas-Peucke graph simplifying algorithm 0 To optimize the parameters of the graph simplification method in S32, and to realize the optimal graph simplification.
6. The power distribution network planning spatial data model simplification method of claim 5, characterized in that:
in step S31, the power distribution network is subjected to Stroke division, and first, a power distribution network line Stroke is defined:
wherein X represents a set of line segments in the power distribution network, the line segments including conductor segments and cable segments, X i Represents the ith line segment therein, st represents the Stroke set, st i Indicates the position of the ith string,
the Stroke partitioning is equivalent to splitting the set X into m sets St 1 ,St 2 ,...,St m And the following three conditions are satisfied:
in the formula, m is the number of the divided strokes;
according to the above Stroke definition, stroke division is performed on each specific line: firstly, taking each line as a Stroke according to the line name in the power distribution network; if the T node exists in the Stroke, continuously dividing the T node into a plurality of Stroke, and finally obtaining a Stroke set St = { St = { (St) 1 ,St 2 ,...St m }。
7. The power distribution network planning spatial data model simplification method of claim 5, characterized in that:
in step S32, a Douglas-Peucke graph simplification algorithm based on strokes performs power distribution network frame graph simplification, and the specific steps are as follows:
s321, determining the value range (lambda) of the meaningful simplified threshold of the Douglas-Peucke graph simplified algorithm according to concrete power distribution network frame data and experience a ，λ b ) Arbitrarily take λ a ＜λ＜λ b ；
S322, defining important nodes H = { H ] in the original line according to the simplified rule base in the step S2 1 ,H 2 ,...,H n }；
S323, each Stroke St in set St i St is provided with i Starting point of (c) is P (x) 1 ,y 1 ) And endpoint Q (x) 2 ,y 2 )，St i Is M = { M 1 ,M 2 ,...M n In which M is i ＝(x i ,y i ) Calculate M i Distance d to line segment PQ i :
In the above formula, A, B and C are three coefficients in the general equation of the line PQ, d i Is M i Distance to line segment PQ;
s324, taking D = max { D 1 ,d 2 ,...,d n D is M k If D < lambda, S325 is executed, otherwise if D > lambda, stroke St is executed i Division into two sub-strokes, i.e. division into starting point P, M k As end point and with M k Taking Q as two sub Stroke of the end point as a starting point, and executing S323;
s325, to Stroke St i Set of other nodes M = { M = { M } 1 ,M 2 ,...M n }，M i ＝(x i ,y i ) If M is i E is H, then M is i Added to the set Z, Z = { Z = { (Z) 1 ,Z 2 ,...,Z n S326, otherwise, all points in the set M are sorted St i Deleting;
s326, calculating Z i Distance to PQ
Fetch and hold>
D Z The corresponding node is Z k Introducing a displacement tolerance eta, if D Z If eta, executing S327, otherwise, executing P, Z k And Q is the end point, divide Stroke again, carry out S325;
s327, set Z = { Z 1 ,Z 2 ,...,Z n Point Z in i Projected in a vertical projection onto a straight line PQ and from Stroke St i Deleting points not belonging to the set Z, and calculating Z i Coordinate (X) after projection i ,Y i )：
Stroke St i The remaining point set after simplification is { P, Q, Z 1 ,Z 2 ,...,Z n }；
S328, removing the current string from the St set, and looping to execute S323, processing each string in the St set until the St set is empty.
8. The method for simplifying the planning spatial data model of the power distribution network according to claim 5, wherein:
in step S33, an optimal simplified threshold lambda of the Douglas-Peucke graph simplifying algorithm is calculated 0 The method comprises the following specific steps:
s331, determining the value range (lambda) of the meaningful simplified threshold value of the Douglas-Peucke graph simplified algorithm according to concrete power distribution network frame data and experience a ，λ b )；
S332, using lambda a As initial threshold, h = (λ) a -λ b ) 300 is an increasing step length, and a Stroke-based Douglas-Peucke graph simplification algorithm is circularly operated;
s333, statistics of lambda i And the total number of the residual nodes of the Stroke curve after being simplified by the Stroke-based Douglas-Peucke graph simplification algorithm
S334, fitting function based on least square method
S335, calculating the curvature of the curve f (lambda i)
Taking the threshold lambda for maximizing the K value i For optimum simplification of the threshold, i.e. λ 0 ＝λ i ；
S336, simplifying the optimal threshold value lambda 0 And substituting the step S32, and executing an optimization program to obtain the optimal graph simplification effect.
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