A new energy access aided decision method

Abstract

The application provides a new energy access auxiliary decision-making method, constructs a terrain model corresponding to an actual power distribution network area; acquires actual line information of the power distribution network and new energy position information, constructs a power distribution network model and a new energy model on the terrain model; constructs an access planning constraint condition, and plans multiple access points of the access power distribution network model corresponding to each new energy model; acquires actual operation information of the power distribution network, and constructs an access capacity constraint condition, acquires an optimal access point and a backup access point from the acquired multiple access points; the acquired optimal access point and the backup access point are sent to a user end, and are verified and selected and determined by a professional. The application constructs a terrain model through actual terrain of an actual power distribution network area, sets an access planning constraint condition and an access capacity constraint condition, cooperatively considers access capacity determination, access point selection and network frame development planning, guarantees safe and reliable operation of the system, and fully utilizes resources.

Description

Technical Field

[0001] This invention relates to the field of power distribution networks, and in particular to a method for assisting decision-making in the access of new energy sources. Background Technology

[0002] New energy refers to renewable energy sources developed and utilized systematically based on new technologies, such as solar and wind energy. New energy power generation is the process of generating electricity using existing technologies through these new energy sources. However, new energy power generation is characterized by intermittency, randomness, and volatility. With the increase in installed capacity of wind and photovoltaic power generation, it poses safety hazards to the power grid, and the stability of system operation and the decline in power quality will become increasingly serious.

[0003] Due to the distribution of resources, many areas with good wind and solar resources are often located at the far end of the power system, with relatively weak power grid structure and low load levels. Determining the optimal capacity for new energy access systems and rationally selecting grid connection points to ensure both safe and reliable system operation and full utilization of resources has constrained the development of new energy. Summary of the Invention

[0004] To address the problems existing in the background technology, this invention proposes a new energy access auxiliary decision-making method.

[0005] A method for assisting decision-making in the access of new energy sources, comprising the following steps: S100. Obtain the terrain information of the actual power distribution network area and construct the corresponding terrain model; S200: Obtain actual line information and new energy location information of the power distribution network, and construct the power distribution network model and new energy model on the terrain model; S300. Construct access planning constraints, and based on the access planning constraints, plan multiple access points for each new energy model on the terrain model. S400: Obtain actual operation information of the distribution network and construct access capacity constraints. Based on the access capacity constraints, obtain the optimal access point and alternative access points from the multiple access points obtained. S500 sends the obtained optimal access point and alternative access points to the user terminal, where they are verified and selected by professionals.

[0006] Based on the above, in step S100, the actual power distribution network area is the target area associated with the actual power distribution network location, and the terrain information includes at least the ground morphology information, latitude and longitude information, altitude information and vegetation information of the actual power distribution network area.

[0007] Based on the above, in step S200, the actual line information of the distribution network includes at least the line type information, tower type information, tower latitude, longitude and altitude information, and actual operation and maintenance information of the tower and line; the new energy location information includes at least the latitude, longitude and altitude information of the location of the new energy.

[0008] Based on the above, in step S300, the access planning constraints include at least terrain constraints, investment budget constraints, operating cost constraints, grid expansion constraints, and construction constraints.

[0009] Based on the above, in step S400, the access capacity constraints include at least the new energy installed capacity limit, power flow constraint, conventional unit output constraint, node voltage constraint, and line power flow limit constraint.

[0010] Based on the above, in step S300, the access point includes at least access location information on the power distribution network, access path planning information, estimated engineering quantity information, and estimated construction cost information.

[0011] Based on the above, in step S100, the full terrain information of the power distribution network area is obtained by taking pictures with a drone, and a terrain model is constructed accordingly based on the full terrain information.

[0012] Based on the above, in step S400, a weight is configured for each of the access capacity constraints. After obtaining multiple access points through the access capacity constraints, a weighted value for each obtained access point to adapt to the access capacity constraints is calculated. Then, the optimal access point and several alternative access points are selected based on the weighted value.

[0013] This invention has outstanding substantive features and significant progress compared to the prior art. Specifically, this invention constructs a terrain model based on the actual terrain of the actual power distribution network area, and sets access planning constraints and access capacity constraints to determine the reasonable selection of grid connection points and optimal capacity for the new energy access system. It considers the determination of access capacity, selection of access points, and grid development planning in a coordinated manner, and coordinates and unifies the planning of large-scale new energy access and system grid expansion from an overall perspective. It adopts a multi-objective mixed integer nonlinear programming method to ensure the safe and reliable operation of the system while making full use of resources. Attached Figure Description

[0014] Figure 1 This is a flowchart illustrating the process of this invention. Detailed Implementation

[0015] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] like Figure 1 As shown, a new energy access auxiliary decision-making method includes the following steps: S100, acquiring terrain information of the actual distribution network area and constructing a corresponding terrain model; S200, acquiring actual line information of the distribution network and new energy location information, and constructing a distribution network model and a new energy model on the terrain model; S300, constructing access planning constraints, and planning multiple access points for each new energy model on the terrain model according to the access planning constraints; S400, acquiring actual operation information of the distribution network, constructing access capacity constraints, and acquiring the optimal access point and alternative access points from the acquired multiple access points according to the access capacity constraints; S500, sending the acquired optimal access point and alternative access points to the user terminal, where they are verified and selected by professionals.

[0017] Specifically, since new energy resource areas are distributed throughout the target area, in this embodiment, the actual distribution network area refers to the target area associated with the location of the actual distribution network, that is, the target area that the distribution network area can be associated with or that can connect to new energy sources. The target resource area for new energy access is located within this distribution network area. In reality, aerial photography by drones is used to obtain full-terrain information of the distribution network area, and a terrain model is constructed based on the full-terrain information. In this embodiment, the terrain information includes at least the ground morphology information, latitude and longitude information, altitude information, and vegetation information of the actual distribution network area. Ground morphology information includes landforms such as plains, gullies, rivers, and hills. Based on this terrain information, it is convenient to consider the route and difficulty of overhead line construction when planning new energy access.

[0018] The actual line information of the distribution network includes at least the line type information, tower type information, tower latitude, longitude and altitude information, and actual operation and maintenance information of the towers and lines. Based on the actual line information of the distribution network, a corresponding line model of the distribution network is constructed on the terrain model. The location information of the new energy source includes at least the latitude, longitude and altitude information of the location of the new energy source. Similarly, based on the location information of the new energy source, that is, the location information of the target area of ​​the new energy resource, a model of the new energy source is constructed on the terrain model. In reality, the target area of ​​the new energy resource includes new energy points that are considered for construction and access, or even those that have already been built. Therefore, the power generation and other parameters of the new energy source have been calculated or have actual historical data. Therefore, the new energy source model is also configured with the power generation and other parameter information of the new energy source. At this point, the target area of ​​the new energy source and the actual line information of the distribution network have been completely constructed on the terrain model. After the constraints are constructed, the possible access points of each new energy point on the distribution network line are automatically calculated to provide assistance for the access decision of the new energy source.

[0019] In this embodiment, the constraints include access planning constraints and access capacity constraints. Access planning constraints consider the limiting factors of access points, while access capacity constraints consider the limiting factors of access capacity. In this embodiment, access planning constraints include at least terrain constraints, investment budget constraints, operating cost constraints, grid expansion constraints, and construction constraints. Terrain constraints consider the limitations of terrain during construction, such as gullies, hills, and rivers; investment budget constraints consider the cost limits of construction materials and labor; operating cost constraints consider the costs of regular operation and maintenance after completion; grid expansion constraints consider the coordination limitations of system grid expansion; and construction constraints consider the limitations of specific construction routes and difficulty levels. Access capacity constraints include at least new energy installed capacity limits, power flow constraints, conventional unit output constraints, node voltage constraints, and line power flow limit constraints. These access capacity constraints are all common grid-connected power parameter constraints and will not be elaborated further.

[0020] By applying access planning constraints, potential access points for each renewable energy source to the distribution network are first identified. These access points include at least the access location information on the distribution network, access path planning information, estimated engineering quantities, and estimated construction costs. After obtaining multiple access points for each renewable energy source, access points that meet the actual operating parameters of the distribution network, such as its capacity, are further filtered based on access capacity constraints. If no suitable access point can be found, the constraint parameters are adjusted, and the filtering continues until a suitable access point is found. If no suitable access point can be found, the renewable energy resource area is considered unsuitable for renewable energy source construction. In practice, multiple access points may still be identified after the second filtering, requiring further analysis.

[0021] In this embodiment, a weight is assigned to each access capacity constraint. For multiple access points obtained through the access capacity constraints, a weighted value for each access point to adapt to the access capacity constraints is calculated. Then, the weighted sum of the adaptation weighted values ​​of each access point to all access capacity constraints is calculated. Based on the weighted sum, the access points are sorted from highest to lowest, with the highest weighted sum being the optimal access point. The next few, such as two or three, are selected as alternative access points for staff to verify and choose, thereby assisting in the decision-making process for new energy access.

[0022] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for assisting decision-making in the access of new energy sources, characterized in that, Including the following steps: S100. Obtain the terrain information of the actual power distribution network area and construct the corresponding terrain model; S200: Obtain actual line information and new energy location information of the power distribution network, and construct the power distribution network model and new energy model on the terrain model; S300. Construct access planning constraints, and based on the access planning constraints, plan multiple access points for each new energy model on the terrain model. S400: Obtain actual operation information of the distribution network and construct access capacity constraints. Based on the access capacity constraints, obtain the optimal access point and alternative access points from the multiple access points obtained. S500 sends the obtained optimal access point and alternative access points to the user terminal, where they are verified and selected by professionals.

2. The new energy access auxiliary decision-making method according to claim 1, characterized in that: In step S100, the actual power distribution network area is the target area associated with the actual power distribution network location, and the terrain information includes at least the ground morphology information, latitude and longitude information, altitude information and vegetation information of the actual power distribution network area.

3. The new energy access auxiliary decision-making method according to claim 1, characterized in that: In step S200, the actual line information of the distribution network includes at least the line type information, tower type information, tower latitude, longitude and altitude information, and actual operation and maintenance information of the tower and line; the new energy location information includes at least the latitude, longitude and altitude information of the location of the new energy.

4. The new energy access auxiliary decision-making method according to claim 1, characterized in that: In step S300, the access planning constraints include at least terrain constraints, investment budget constraints, operating cost constraints, grid expansion constraints, and construction constraints.

5. The new energy access auxiliary decision-making method according to claim 1, characterized in that: In step S400, the access capacity constraints include at least the new energy installed capacity limit, power flow constraint, conventional unit output constraint, node voltage constraint, and line power flow limit constraint.

6. The new energy access auxiliary decision-making method according to claim 1, characterized in that: In step S300, the access point includes at least access location information on the distribution network, access path planning information, estimated engineering quantity information, and estimated construction cost information.

7. The new energy access auxiliary decision-making method according to claim 1, characterized in that: In step S100, the full terrain information of the power distribution network area is obtained by taking pictures with a drone, and a terrain model is constructed based on the full terrain information.

8. The new energy access auxiliary decision-making method according to claim 1, characterized in that: In step S400, a weight is configured for each access capacity constraint. After obtaining multiple access points through the access capacity constraints, a weighted value for each obtained access point to adapt to the access capacity constraints is calculated. Then, the optimal access point and several alternative access points are selected based on the weighted value.

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