Intelligent analysis and control method for water-adaptive ecological power grid

Abstract

The invention relates to the technical field of power grids, in particular to an intelligent analysis and control method for a water-adaptive ecological power grid, and the method comprises the steps: respectively calculating a scale density coefficient and a productivity analysis value with a natural data set through an analysis model to obtain a first correlation value and a second correlation value, and reflecting the influence degree of the scale density coefficient on the natural data set according to the first correlation value; the influence degree of the productivity analysis value on the natural data set is reflected through the second correlation value, the influence degree of the scale density coefficient and the productivity analysis value on the ecology is further reflected, the theoretical coefficient sum is calculated through the management and control calculation model, the theoretical data set is analyzed, and the ecological nodes are managed and controlled according to the analysis result. The intelligent analysis effect of the ecological power grid is improved, and the management and control process is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of power grids, and in particular to a method for intelligent analysis and control of water-adaptive ecological power grids. Background Art

[0002] The water-adaptive ecological power grid is a new type of power grid that integrates the power system and water resources. It realizes efficient and environmentally friendly power production and transmission through the management of the entire power system and water resources. Among them, the power system includes hydropower generation equipment, power storage equipment, and power transmission equipment. The construction of the power system also has a considerable impact on water resources, such as the project density of power-related equipment in the ecological region, and the balance between regional distribution and actual production capacity, which have different degrees of impact on water resources. The higher the density or the imbalance between regional distribution and actual production capacity, the greater the impact on the environmental health of the water area, such as changes in water flow and water biological density.

[0003] In order to ensure the ecological health of water resources, it is necessary to intelligently analyze the impact of the project density of the power system and the balance relationship of the ecological area on water resources, and manage the ecological power grid based on the analysis results. Summary of the invention

[0004] The purpose of the present invention is to solve the problems in the background technology and to propose a method for intelligent analysis and control of a water-adaptive ecological power grid.

[0005] The present invention adopts the following technical scheme: obtaining the project engineering of the ecological power grid, processing the project engineering, dividing the ecological power grid into a number of ecological nodes, monitoring and counting the ecological nodes to obtain a natural data set, calculating the characteristic value of the natural data set and using the characteristic value as the passive coefficient of the ecological node;

[0006] Calculate the scale density coefficient and capacity analysis value of the ecological node, and use the scale density coefficient and capacity analysis value as the first active coefficient and the second active coefficient of the ecological node respectively;

[0007] respectively judging whether the first active coefficient and the second active coefficient are associated with the passive coefficient, obtaining a judgment result, establishing an analysis model according to the judgment result, and calculating a first correlation value and a second correlation value;

[0008] Based on the larger and smaller of the first correlation value and the second correlation value, the corresponding active coefficients are marked as key active coefficients and secondary active coefficients respectively, and a control calculation model is established;

[0009] According to the control calculation model, the status of the ecological nodes is analyzed to obtain the analysis results, and the ecological nodes are controlled according to the analysis results.

[0010] In the above-mentioned method for intelligent analysis and control of water-adaptive ecological power grid, the processing method of the project engineering is:

[0011] Obtain a processed image of the ecological power grid, use image recognition technology to obtain a number of project points, obtain the project numbers and project sequences of the project points, divide the project points with the same project number into similar project points, and connect the similar project points according to the project sequence to obtain the engineering paths of the similar project points.

[0012] In the above-mentioned method for intelligent analysis and control of water-adaptive ecological power grid, the method for dividing ecological nodes is:

[0013] Get the image midpoint of the processed image, take the image midpoint as the origin, establish a two-dimensional coordinate system with the horizontal and vertical coordinates as the horizontal distance from the origin and the vertical distance from the origin respectively, get several project points of the same type of project points located on the same engineering path, establish a project point set based on several project points, determine the minimum circle coverage area based on the project point set, get the radius R and center of the minimum circle coverage area, draw a target area with a radius L based on the center of the circle, L>R, and mark the target area as an ecological node.

[0014] In the above-mentioned method for intelligent analysis and control of water-adaptive ecological power grid, the characteristic value is calculated as follows:

[0015] By the eigenvalue formula Obtain the characteristic value TZ of the natural data set; where SZi represents the ecological sub-value, i represents the number of the ecological sub-value in the natural data set, N1 represents the total number of ecological sub-values; BZi represents the standard value corresponding to the ecological sub-value SZi.

[0016] In the above-mentioned intelligent analysis and control method of water-adaptive ecological power grid, the calculation method of scale density coefficient is:

[0017] The scale density coefficient is calculated by the formula The scale density coefficient GM is calculated; XSj represents the project duration; j represents the number of the project factor in the ecological node, N2 represents the total number of project factors; S represents the regional area in the ecological node.

[0018] In the above-mentioned method for intelligent analysis and control of water-adaptive ecological power grid, the calculation method of the capacity analysis value is:

[0019] Calculation formula based on capacity analysis value The capacity analysis value CF is calculated; SC is the actual capacity of the ecological node, in kWh, obtained through historical data statistics; CM is the area of ​​the capacity region; πL 2 -CM is the area of ​​natural areas, L is the radius of ecological nodes, in square kilometers; k is the proportionality coefficient.

[0020] In the above-mentioned method for intelligent analysis and control of water-adaptive ecological power grid, the method for establishing the analysis model is:

[0021] Sort a number of first active coefficients in descending order to obtain a first decreasing sequence, sort a number of second active coefficients in descending order to obtain a second decreasing sequence, mark the first decreasing sequence or the second decreasing sequence as the target sequence {MXh}, MX is an element of the target sequence, h is the ecological node number corresponding to the active coefficient, h∈[1, N3], N3 is the total number of ecological nodes, and obtain the number sequence of the ecological nodes corresponding to the target sequence {MXh};

[0022] According to the sorting order of the numbering sequence, the passive coefficients of the corresponding ecological nodes are sorted to obtain the detection sequence {BXh}, where BX is the passive coefficient;

[0023] Determine whether any two adjacent passive coefficients of the detection sequence {BXh} satisfy the decreasing relationship BXh×(1+ZKh)-BX(h+1)>0, and obtain a determination result; wherein ZKh is the minimum variable threshold between two adjacent passive coefficients.

[0024] In the above-mentioned method for intelligent analysis and control of a water-adaptive ecological power grid, the judgment results are traversed, and if there are no two adjacent passive coefficients that do not satisfy the decreasing relationship, it is judged that the active coefficient and the passive coefficient corresponding to the target sequence {MXh} are related;

[0025] If there are two adjacent passive coefficients that do not satisfy the decreasing relationship, it is determined that the active coefficient and the passive coefficient corresponding to the target sequence {MXh} are not associated;

[0026] Calculate the value by the formula The target association value of the target sequence is calculated.

[0027] In the above-mentioned method for intelligent analysis and control of water-adaptive ecological power grid, the method for establishing the control calculation model is:

[0028] The theoretical coefficient and LXh are calculated by the theoretical coefficient and calculation formula LXh=x1×GJh+x2×CYh; GJh is the key active coefficient, CYh is the secondary active coefficient, x1 and x2 are the key active coefficient and secondary active coefficient influence coefficient respectively, x1>x2;

[0029] The theoretical coefficient and LXh should satisfy the limited relationship:

[0030] LXh∈BXh×[1-(GJh+ZY), 1+(GJh+ZY)];

[0031] ZY is the natural impact threshold.

[0032] In the above-mentioned method for intelligent analysis and control of water-adaptive ecological power grid, the analysis method of ecological node status is:

[0033] If the theoretical coefficient and LXh satisfy the limited relationship, the state of the ecological node is judged to be normal and a continuous monitoring signal is generated; if the theoretical coefficient and LXh do not satisfy the limited relationship, the state of the ecological node is judged to be abnormal and a control signal is generated;

[0034] Maintain the operation of ecological nodes based on continuous detection signals, and notify the technical department to adjust the ecological nodes based on control signals.

[0035] Compared with the existing technology, the advantages of the present invention are: the first correlation value and the second correlation value are obtained by respectively calculating the scale density coefficient and the production capacity analysis value with the natural data set through the analysis model, the influence of the scale density coefficient on the natural data set is reflected according to the first correlation value, and the influence of the production capacity analysis value on the natural data set is reflected by the second correlation value, and the influence of the scale density coefficient and the production capacity analysis value on the ecology is further reflected, the theoretical coefficients and are calculated by the management and control calculation model, and the theoretical data set is analyzed, and the ecological nodes are controlled according to the analysis results, thereby improving the intelligent analysis effect of the ecological power grid and optimizing the management and control process. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0037] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0038] Reference Figure 1 , a method for intelligent analysis and control of water-adaptive ecological power grid, obtains the project engineering of the ecological power grid, processes the project engineering, and obtains several engineering paths in the project engineering;

[0039] The project engineering approach is:

[0040] Obtain a processed image of the ecological power grid, obtain a number of project points using image recognition technology, obtain project numbers and project sequences of the project points, classify the project points with the same project number into similar project points, and connect the similar project points according to the project sequence to obtain engineering paths of the similar project points; image recognition technology is an existing technology and will not be described in detail here; the project points may be ecological power grid technical equipment such as reservoirs, hydroelectric power generation equipment, power transmission equipment and power storage equipment;

[0041] Divide the ecological power grid into several ecological nodes according to different engineering paths;

[0042] The method of dividing ecological nodes is:

[0043] The image midpoint of the processed image is obtained, and the image midpoint is taken as the origin. The horizontal and vertical coordinates are respectively the horizontal distance from the origin and the vertical distance from the origin to establish a two-dimensional coordinate system, and several project points of the same type of project points located on the same engineering path are obtained. A project point set is established based on the several project points, and the minimum circle coverage area is determined based on the project point set. The radius R and the center of the minimum circle coverage area are obtained, and a target area with a radius of L is drawn based on the center of the circle. L>R, and the target area is marked as an ecological node; wherein, the minimum circle coverage area is determined in this embodiment using a minimum circle coverage algorithm, which is a prior art and will not be described in detail here;

[0044] The ecological nodes are monitored and counted to obtain several ecological sub-values ​​and several project factors, and the ecological sub-values ​​are combined to obtain the natural data set; the project factors are the project points in the ecological nodes; the ecological sub-values ​​can be the upstream flow, downstream flow, water biological density, etc. of the ecological water area, and the standard values ​​corresponding to the ecological sub-values ​​are measured and recorded before the construction of the sub-project;

[0045] Calculate the eigenvalues ​​of the natural data set and use the eigenvalues ​​as the passive coefficients of the ecological nodes;

[0046] The eigenvalue is calculated as:

[0047] By the eigenvalue formula Get the characteristic value TZ of the natural data set; where SZ represents the ecological sub-value, i represents the number of the ecological sub-value in the natural data set, i is a positive integer, i∈[1, N1], N1 represents the total number of ecological sub-values; BZi represents the standard value corresponding to the ecological sub-value SZi, which is obtained by testing big data with relevant equipment; the characteristic value TZ can be understood as the total change of all ecological sub-values, and the larger the characteristic subset, the larger the variable of the natural sub-value;

[0048] Obtain the project duration of several project factors in the ecological node, calculate the scale density coefficient of the ecological node according to the project duration of several project factors, and use the scale density coefficient as the first active coefficient of the ecological node; the calculation method of the scale density coefficient is:

[0049] The scale density coefficient is calculated by the formula The scale density coefficient GM is calculated; XS represents the project duration in days; j represents the number of the project factor in the ecological node, j is a positive integer, j∈[1, N2], N2 represents the total number of project factors; S represents the area of ​​the ecological node in square kilometers; the scale density coefficient can be understood as the average scale of the ecological node. The larger the scale density coefficient, the larger the average scale.

[0050] The ecological node is divided into production area and natural area, the production capacity analysis value is calculated according to the area of ​​the production capacity area, and the production capacity analysis value is used as the second active coefficient of the ecological node;

[0051] The calculation method of capacity analysis value is:

[0052] Calculation formula based on capacity analysis value The capacity analysis value CF is calculated; SC is the actual capacity of the ecological node, in kWh, obtained through historical data statistics; CM is the area of ​​the capacity area. In this embodiment, the convex hull algorithm is used to calculate the capacity area and the area of ​​the capacity area CM for several project point sets in the ecological node, in square kilometers; πL 2 -CM is the natural area, in square kilometers; k is the proportionality coefficient; the capacity analysis value CF can be understood as the equilibrium relationship between regional distribution and actual capacity. The larger the capacity analysis value CF is, the more unbalanced the equilibrium relationship between regional distribution and actual capacity is.

[0053] Determine whether the first active coefficient is associated with the passive coefficient, and whether the second active coefficient is associated with the passive coefficient, obtain a determination result, establish an analysis model according to the determination result, and calculate a first correlation value and a second correlation value;

[0054] The method to establish the analysis model is:

[0055] Sort a number of first active coefficients in descending order to obtain a first descending sequence, sort a number of second active coefficients in descending order to obtain a second descending sequence, mark the first descending sequence or the second descending sequence as a target sequence {MXh}, MX is an element of the target sequence, h is the ecological node number corresponding to the active coefficient, h∈[1, N3], N3 is the total number of ecological nodes, and obtain the numbering sequence of the ecological nodes corresponding to the target sequence {MXh}; it should be noted that the first descending sequence is preferentially used as the target sequence to perform judgment and calculate the current association value, and the current association value is used as the first association value between the first active coefficient and the passive coefficient; then the second descending sequence is used as the target sequence to perform judgment and calculate the current association value, and the current association value is used as the second association value between the second active coefficient and the passive coefficient;

[0056] According to the sorting order of the numbering sequence, the passive coefficients of the corresponding ecological nodes are sorted to obtain the detection sequence {BXh}, where BX is the passive coefficient;

[0057] Determine whether any two adjacent passive coefficients of the detection sequence {BXh} satisfy the decreasing relationship BXh×(1+ZKh)-BX(h+1)>0, and obtain the judgment result; wherein ZKh is the minimum variable threshold between two adjacent passive coefficients, ZKh∈[0,0.1]; the value of the minimum variable threshold ZKh can start from 0, when 0 does not satisfy the decreasing relationship, the value of the minimum variable threshold ZK can be adjusted to 0.01, if it still does not satisfy, it can be adjusted to 0.02, 0.03, ... 0.1;

[0058] Traverse the judgment results, if all two adjacent passive coefficients do not satisfy the decreasing relationship, then it is judged that the active coefficient and the passive coefficient corresponding to the target sequence {MXh} are related;

[0059] If there are two adjacent passive coefficients that do not satisfy the decreasing relationship, it is judged that the active coefficient and the passive coefficient corresponding to the target sequence {MXh} are not associated; when the minimum variable threshold ZK is adjusted to 0.1 and still does not satisfy the decreasing relationship, it is judged that the two adjacent passive coefficients have no decreasing relationship, that is, the active coefficient and the passive coefficient corresponding to the target sequence are not associated;

[0060] Calculate the value by the formula Calculate and obtain the target correlation value of the target sequence; wherein, the larger the target correlation value is, the higher the correlation degree between the associated target sequence and the detection sequence is;

[0061] The first correlation value and the second correlation value are compared, and based on the larger and smaller of the first correlation value and the second correlation value, the corresponding active coefficients are marked as key active coefficients and secondary active coefficients, and a control calculation model is established; the key active coefficient can be understood as having a higher degree of influence on the passive coefficient, and the secondary active coefficient can be understood as having a lower degree of influence on the passive coefficient;

[0062] The method for establishing a control calculation model is:

[0063] The theoretical coefficients and LXh of the key active coefficient and the secondary active coefficient are calculated by the theoretical coefficient calculation formula LXh=x1×GJh+x2×CYh; GJh is the key active coefficient, CYh is the secondary active coefficient, x1 and x2 are the key active coefficient and the secondary active coefficient influence coefficient respectively, x1>x2;

[0064] The theoretical coefficient and LXh should satisfy the limited relationship:

[0065] LXh∈BXh×[1-(GJh+ZY), 1+(GJh+ZY)];

[0066] ZY is the natural impact threshold. It should be noted that the natural impact threshold ZY is determined according to the natural climate of the ecological node. It is used to balance the impact of natural factors. For example, when the passive coefficient of the ecological node increases due to the natural climate, the natural impact threshold ZY can take a negative value.

[0067] Perform data analysis on the status of ecological nodes according to the control calculation model, obtain analysis results, and control ecological nodes according to the analysis results;

[0068] The analysis method of ecological node status is:

[0069] If the theoretical coefficient and LXh satisfy the limited relationship, the state of the ecological node is judged to be normal and a continuous monitoring signal is generated; if the theoretical coefficient and LXh do not satisfy the limited relationship, the state of the ecological node is judged to be abnormal and a control signal is generated;

[0070] Maintain the operation of ecological nodes based on continuous detection signals, and notify the technical department to adjust ecological nodes based on control signals;

[0071] The first correlation value and the second correlation value are obtained by respectively calculating the scale density coefficient and the capacity analysis value with the natural data set through the analysis model. The first correlation value reflects the influence of the scale density coefficient on the natural data set, and the second correlation value reflects the influence of the capacity analysis value on the natural data set. The influence of the scale density coefficient and the capacity analysis value on the ecology is further reflected. The theoretical coefficients and are calculated through the management and control calculation model. By analyzing the theoretical data set, the ecological nodes are controlled according to the analysis results, which improves the intelligent analysis effect of the ecological power grid and optimizes the management and control process.

[0072] The above are only preferred specific implementation modes of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical solutions and inventive concepts of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A method for intelligent analysis and control of water-adaptive ecological power grid, characterized by: Obtain the project engineering of the ecological power grid, process the project engineering, divide the ecological power grid into several ecological nodes, monitor and count the ecological nodes to obtain a natural data set, calculate the characteristic value of the natural data set and use the characteristic value as the passive coefficient of the ecological node; Calculate the scale density coefficient and capacity analysis value of the ecological node, and use the scale density coefficient and capacity analysis value as the first active coefficient and the second active coefficient of the ecological node respectively; respectively judging whether the first active coefficient and the second active coefficient are associated with the passive coefficient, obtaining a judgment result, establishing an analysis model according to the judgment result, and calculating a first correlation value and a second correlation value; Based on the larger and smaller of the first correlation value and the second correlation value, the corresponding active coefficients are marked as key active coefficients and secondary active coefficients respectively, and a control calculation model is established; According to the control calculation model, the status of the ecological nodes is analyzed to obtain the analysis results, and the ecological nodes are controlled according to the analysis results.

2. According to claim 1, a method for intelligent analysis and control of water-adaptive ecological power grid is characterized by: The project engineering approach is: Obtain a processed image of the ecological power grid, use image recognition technology to obtain a number of project points, obtain the project numbers and project sequences of the project points, divide the project points with the same project number into similar project points, and connect the similar project points according to the project sequence to obtain the engineering paths of the similar project points.

3. The method for intelligent analysis and control of a water-adaptive ecological power grid according to claim 2 is characterized by: The method of dividing ecological nodes is: Get the image midpoint of the processed image, take the image midpoint as the origin, establish a two-dimensional coordinate system with the horizontal and vertical coordinates as the horizontal distance from the origin and the vertical distance from the origin respectively, get several project points of the same type of project points located on the same engineering path, establish a project point set based on several project points, determine the minimum circle coverage area based on the project point set, get the radius R and center of the minimum circle coverage area, draw a target area with a radius L based on the center of the circle, L>R, and mark the target area as an ecological node.

4. The method for intelligent analysis and control of a water-adaptive ecological power grid according to claim 3 is characterized by: The eigenvalue is calculated as: By the eigenvalue formula Obtain the characteristic value TZ of the natural data set; where SZi represents the ecological sub-value, i represents the number of the ecological sub-value in the natural data set, N1 represents the total number of ecological sub-values; BZi represents the standard value corresponding to the ecological sub-value SZi.

5. The method for intelligent analysis and control of water-adaptive ecological power grid according to claim 4 is characterized by: The calculation method of scale density coefficient is: The scale density coefficient is calculated by the formula The scale density coefficient GM is calculated; XSj represents the project duration; j represents the number of the project factor in the ecological node, N2 represents the total number of project factors; S represents the regional area in the ecological node.

6. The method for intelligent analysis and control of water-adaptive ecological power grid according to claim 5 is characterized by: The calculation method of capacity analysis value is: Calculation formula based on capacity analysis value The capacity analysis value CF is calculated; SC is the actual capacity of the ecological node, in kWh, obtained through historical data statistics; CM is the area of ​​the capacity region; πL 2 -CM is the area of ​​natural areas, L is the radius of ecological nodes, in square kilometers; k is the proportionality coefficient.

7. The method for intelligent analysis and control of water-adaptive ecological power grid according to claim 6 is characterized by: The method to establish the analysis model is: Sort a number of first active coefficients in descending order to obtain a first decreasing sequence, sort a number of second active coefficients in descending order to obtain a second decreasing sequence, mark the first decreasing sequence or the second decreasing sequence as the target sequence {MXh}, MX is an element of the target sequence, h is the ecological node number corresponding to the active coefficient, h∈[1, N3], N3 is the total number of ecological nodes, and obtain the number sequence of the ecological nodes corresponding to the target sequence {MXh}; According to the sorting order of the numbering sequence, the passive coefficients of the corresponding ecological nodes are sorted to obtain the detection sequence {BXh}, where BX is the passive coefficient; Determine whether any two adjacent passive coefficients of the detection sequence {BXh} satisfy the decreasing relationship BXh×(1+ZKh)-BX(h+1)>0, and obtain a determination result; wherein ZKh is the minimum variable threshold between two adjacent passive coefficients.

8. The method for intelligent analysis and control of water-adaptive ecological power grid according to claim 7 is characterized by: Traverse the judgment results, if there are no two adjacent passive coefficients that do not satisfy the decreasing relationship, then it is determined that the active coefficient and the passive coefficient corresponding to the target sequence {MXh} are related; If there are two adjacent passive coefficients that do not satisfy the decreasing relationship, it is determined that the active coefficient and the passive coefficient corresponding to the target sequence {MXh} are not associated; Calculate the value by the formula The target association value of the target sequence is calculated.

9. The method for intelligent analysis and control of water-adaptive ecological power grid according to claim 8, characterized in that: The method for establishing a control calculation model is: The theoretical coefficient and LXh are calculated by the theoretical coefficient and calculation formula LXh=x1×GJh+x2×CYh; GJh is the key active coefficient, CYh is the secondary active coefficient, x1 and x2 are the key active coefficient and secondary active coefficient influence coefficient respectively, x1>x2; The theoretical coefficient and LXh should satisfy the limited relationship: LXh∈BXh×[1-(GJh+ZY), 1+(GJh+ZY)]; ZY is the natural impact threshold.

10. The method for intelligent analysis and control of water-adaptive ecological power grid according to claim 9, characterized in that: The analysis method of ecological node status is: If the theoretical coefficient and LXh satisfy the limited relationship, the state of the ecological node is judged to be normal and a continuous monitoring signal is generated; if the theoretical coefficient and LXh do not satisfy the limited relationship, the state of the ecological node is judged to be abnormal and a control signal is generated; Maintain the operation of ecological nodes based on continuous detection signals, and notify the technical department to adjust the ecological nodes based on control signals.

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