A distributed energy scheduling management method and system of a virtual power plant

Abstract

The application provides a kind of virtual power plant distributed energy scheduling management method and system, the method is by obtaining energy scheduling area, determine the first position of distributed power station in energy scheduling area and the second position of charging pile;According to the second position, adjacent charging pile is combined to form a charging network;Obtain the power of each new energy vehicle in the energy scheduling area, judge whether the power reaches the threshold value;If it is judged that the power reaches the threshold value, the moving track of the corresponding new energy vehicle is obtained, and it is judged whether there is a charging intention;If it is judged that there is a charging intention, the charging sub-network in the charging network is determined according to the current position of the corresponding new energy vehicle and the predicted moving track;According to the first position, the corresponding distributed power station is controlled to transport energy to the charging sub-network, specifically, by intelligently scheduling the energy of distributed power station and each charging facility, the loss of energy in the transmission process is optimized to achieve the purpose of energy saving.

Description

Technical Field

[0001] This invention belongs to the field of energy dispatch management technology, and specifically relates to a distributed energy dispatch management method and system for a virtual power plant. Background Technology

[0002] In today's era, society places increasing emphasis on sustainable energy, environmental awareness is deeply ingrained, and the electricity market is experiencing rapid development. However, these developments have also brought unprecedented and complex challenges to the power system. Traditional centralized power systems, due to their inherent limitations, are gradually becoming inadequate in addressing these challenges.

[0003] On the one hand, centralized large power plants employ long-distance power transmission, a process characterized by severe energy loss. A significant amount of energy is wasted along the transmission lines, directly leading to a substantial increase in operating costs and a marked decrease in energy efficiency. For example, during long-distance high-voltage transmission, electrical energy is continuously converted into heat and dissipated into the environment due to conductor resistance. On the other hand, this traditional power supply model suffers from a severe lack of flexibility. If a link in the power system fails, the recovery time for the entire power network is often lengthy, significantly impacting power supply reliability and potentially causing widespread power outages, resulting in considerable inconvenience and losses for society and its daily lives.

[0004] Of particular note is that, as the proportion of renewable energy in the power supply system continues to rise, traditional power transmission models have revealed their weakness in integrating distributed energy resources. Distributed energy is characterized by its decentralized and intermittent nature, making it difficult for traditional models to effectively coordinate and manage it. This leads to frequent imbalances in power supply and demand, further exacerbating fluctuations and instability in grid load, and posing a serious threat to the safe and stable operation of the power grid.

[0005] As the number of new energy vehicles increases daily, charging infrastructure such as charging piles also needs to be developed. General green energy sources such as solar power are no longer sufficient to meet the charging needs of new energy vehicles. The above-mentioned method, which uses centralized power plants to transmit electricity over long distances, undoubtedly increases energy loss. Furthermore, if a link in the power system fails, it is difficult to restore it in a timely manner. Summary of the Invention

[0006] Based on this, the present invention provides a distributed energy dispatching and management method and system for virtual power plants, which aims to intelligently dispatch the energy of distributed power stations and various charging facilities to optimize energy loss during transmission and achieve the goal of energy conservation.

[0007] The first aspect of the embodiment of the present invention provides a distributed energy scheduling management method for a virtual power plant, which is applied to an application scenario with a distributed power station and a charging pile supporting new energy vehicles, and the energy transmission lines between the distributed power station and each charging pile are connected, and the energy transmission lines between each charging pile are connected. The method includes:

[0008] Obtain an energy scheduling area, and determine the first position of the distributed power station and the second position of the charging pile in the energy scheduling area;

[0009] According to the second position, combine adjacent charging piles to form a charging network;

[0010] Obtain the power of each new energy vehicle in the energy scheduling area, and judge whether the power reaches a threshold value;

[0011] If it is judged that the power reaches the threshold value, obtain the moving trajectory of the corresponding new energy vehicle, and judge whether there is a charging intention;

[0012] If it is judged that there is a charging intention, determine the charging subnet in the charging network according to the current position and the predicted moving trajectory of the corresponding new energy vehicle;

[0013] According to the first position, control the corresponding distributed power station to deliver energy to the charging subnet.

[0014] Further, the step of obtaining the moving trajectory of the corresponding new energy vehicle and judging whether there is a charging intention includes:

[0015] Judge whether the corresponding new energy vehicle has a navigation task;

[0016] If it is judged that the corresponding new energy vehicle has a navigation task, judge whether the destination is a charging area according to the navigation task;

[0017] If it is judged that the destination is a charging area, determine that there is a charging intention;

[0018] If it is judged that the corresponding new energy vehicle does not have a navigation task, obtain the first moving trajectory of the new energy vehicle after the power reaches the threshold value, and determine the target historical moving trajectory according to the first moving trajectory;

[0019] Calculate a charging intention score according to the first moving trajectory and the target historical moving trajectory, and judge whether the charging intention score is greater than a preset score;

[0020] If it is judged that the charging intention score is greater than the preset score, determine that there is a charging intention.

[0021] Further, the step of determining the target historical moving trajectory according to the first moving trajectory includes:

[0022] In the historical records, before the new energy vehicle starts charging, all historical movement trajectories within a preset distance are obtained, and it is determined whether there is a trajectory among all historical movement trajectories that completely overlaps with the first movement trajectory.

[0023] If it is determined that there is a trajectory among all historical movement trajectories that completely overlaps with the first movement trajectory, then the trajectory that completely overlaps with the first movement trajectory is determined as the target historical movement trajectory.

[0024] If it is determined that there is no trajectory among all historical movement trajectories that completely overlaps with the first movement trajectory, then all trajectories that overlap with the first movement trajectory for more than a preset length are determined as the target historical movement trajectory.

[0025] Furthermore, the step of calculating the charging intention score based on the first movement trajectory and the target's historical movement trajectory includes:

[0026] When the target's historical movement trajectory completely overlaps with the first movement trajectory, the end position of the first movement trajectory is determined, and the first distance between the end position and the end position of the target's historical movement trajectory is obtained;

[0027] Based on the first distance and the pre-established first mapping relationship, a first weight coefficient corresponding to the first distance is determined, wherein the first mapping relationship is used to input the first distance, match the first distance with the distance range value, and output the weight coefficient corresponding to the distance range value after a successful match.

[0028] Substitute the first weighting coefficient into the first fitting formula to calculate the charging intention score;

[0029] When there are several target historical movement trajectories, it is determined whether the part of each target historical movement trajectory that overlaps with the first movement trajectory is continuous;

[0030] If it is determined that the part of each target's historical movement trajectory that overlaps with the first movement trajectory is continuous, the end position of the last overlapping trajectory is determined, and the second distance between the end position of the last overlapping trajectory and the end position of the corresponding target's historical movement trajectory is obtained.

[0031] Based on the second distance and the pre-established first mapping relationship, determine the second weight coefficient corresponding to the second distance;

[0032] Substitute the second weighting coefficient into the first fitting formula to calculate the charging intention score;

[0033] If it is determined that the part of the historical movement trajectory of each target that overlaps with the first movement trajectory is not continuous, then the number of continuous overlapping trajectories is obtained, and a base number is set according to the number of continuous overlapping trajectories;

[0034] Obtain the end position of each overlapping part of the trajectory, and obtain the third distance between the end position of each overlapping part of the trajectory and the corresponding end position of the target's historical movement trajectory.

[0035] Based on the third distance and the first mapping relationship, determine the corresponding third weight coefficient;

[0036] Substitute the base number and the corresponding third weight coefficient into the second fitting formula to calculate the charging intention score.

[0037] Furthermore, the step of determining the charging sub-network within the charging network based on the current location and predicted movement trajectory of the corresponding new energy vehicle includes:

[0038] Based on the current location and historical charging location of the corresponding new energy vehicle, a sector-shaped area is determined. The direction of the sector is determined by the driving direction of the new energy vehicle, the angle of the sector is determined by the maximum angle formed by the current location of the new energy vehicle and any two historical charging locations, and the area of ​​the sector is determined by the number of kilometers the new energy vehicle can travel with its remaining battery power.

[0039] The network formed by the charging piles covered in the sector area is defined as the charging subnetwork.

[0040] Furthermore, the step of controlling the corresponding distributed power station to supply energy to the charging subgrid based on the first location includes:

[0041] By combining the various charging subnets, the target charging subnet is obtained;

[0042] Calculate the target energy required for each part of the target charging subnetwork and determine the geometric center of each part of the target charging subnetwork;

[0043] Based on the geometric center, locate the distributed power station closest to the geometric center and control the distributed power station to transmit the target energy to the corresponding part of the target charging subgrid.

[0044] Furthermore, the step of finding the nearest distributed power station to the geometric center based on the geometric center, and controlling the distributed power station to transmit the target energy to the corresponding part of the target charging subgrid includes:

[0045] Determine whether the number of distributed power stations closest to the geometric center is unique;

[0046] If the number of distributed power stations closest to the geometric center is not unique, then the distributed power station that currently delivers the least amount of energy is determined as the target distributed power station.

[0047] A second aspect of this invention provides a distributed energy dispatch and management system for a virtual power plant, used to implement the distributed energy dispatch and management method for a virtual power plant provided in the first aspect, the system comprising:

[0048] The acquisition module is used to acquire the energy dispatch area and determine the first location of the distributed power station and the second location of the charging pile in the energy dispatch area;

[0049] The combination module is used to combine adjacent charging piles according to the second position to form a charging network;

[0050] The first judgment module is used to obtain the power of each new energy vehicle in the energy dispatch area and determine whether the power has reached a threshold.

[0051] The second judgment module is used to obtain the movement trajectory of the corresponding new energy vehicle and determine whether there is a charging intention if the battery level reaches the threshold.

[0052] The determination module is used to determine the charging sub-network in the charging network based on the current location and predicted movement trajectory of the corresponding new energy vehicle if it is determined that there is a charging intention.

[0053] The control module is used to control the corresponding distributed power station to supply energy to the charging subgrid based on the first location.

[0054] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the distributed energy dispatch and management method for a virtual power plant provided in the first aspect.

[0055] A fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the distributed energy dispatch management method for a virtual power plant provided in the first aspect.

[0056] This invention provides a distributed energy dispatch management method and system for a virtual power plant. The method acquires an energy dispatch area and determines the first location of distributed power stations and the second location of charging piles within that area. Based on the second location, adjacent charging piles are combined to form a charging network. The method acquires the battery level of each new energy vehicle in the energy dispatch area and determines whether the battery level has reached a threshold. If the battery level reaches the threshold, the method acquires the movement trajectory of the corresponding new energy vehicle to determine if there is a charging intention. If a charging intention is determined, a charging sub-network is determined within the charging network based on the current location and predicted movement trajectory of the corresponding new energy vehicle. Based on the first location, the method controls the corresponding distributed power station to supply energy to the charging sub-network. Specifically, by intelligently dispatching the energy between the distributed power station and each charging facility, energy loss during transmission is optimized to achieve energy conservation. Attached Figure Description

[0057] Figure 1 This is a flowchart illustrating the implementation of a distributed energy dispatch and management method for a virtual power plant, as provided in Embodiment 1 of the present invention.

[0058] Figure 2 This is a structural block diagram of a distributed energy dispatch and management system for a virtual power plant provided in Embodiment 2 of the present invention;

[0059] Figure 3 This is a structural block diagram of an electronic device provided in Embodiment 3 of the present invention. Detailed Implementation

[0060] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Several embodiments of the invention are illustrated in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

[0061] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0062] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this invention belongs. The terms used in the specification of this invention are for the purpose of describing specific embodiments only and are not intended to limit the invention. The term "and / or" used herein includes any and all combinations of one or more of the associated listed items.

[0063] Embodiment 1

[0064] According to an embodiment of the present invention, a method for distributed energy scheduling management of a virtual power plant is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0065] In Embodiment 1, a method for distributed energy scheduling management of a virtual power plant is provided, which can be used in an electronic device, such as a computer. It should be noted that this method is applied to an application scenario with a distributed power station and charging piles supporting new energy vehicles, and the energy transmission lines between the distributed power station and each charging pile are connected, and the energy transmission lines between each charging pile are connected, and it can be applied when green energy cannot meet the demand. Please refer to Figure 1 , Figure 1 FIG. shows an implementation flowchart of a method for distributed energy scheduling management of a virtual power plant provided in Embodiment 1 of the present invention, which specifically includes steps S01 to S06.

[0066] Step S01, obtain an energy scheduling area, and determine the first position of the distributed power station and the second position of the charging pile in the energy scheduling area.

[0067] Specifically, a two-dimensional electronic bird's-eye view can be obtained, and the energy scheduling area can be delineated by manual delineation. After the energy scheduling area is delineated, since the geographical locations of the distributed power station and the charging pile are known, the first position of the distributed power station and the second position of the charging pile can be automatically obtained. It can be understood that the first position and the second position can be longitude and latitude, or plane rectangular coordinate points obtained through processing and transformation.

[0068] Step S02, combine adjacent charging piles according to the second position to form a charging network.

[0069] Step S03, obtain the battery levels of each new energy vehicle in the energy scheduling area, and determine whether the battery levels reach a threshold. If so, execute Step S04.

[0070] Specifically, by connecting the new energy vehicle to the server, the system can obtain the vehicle's battery level and remaining driving range in real time. When the battery level reaches a threshold, it indicates that the new energy vehicle needs to be charged promptly.

[0071] In step S04, the movement trajectory of the corresponding new energy vehicle is obtained, and it is determined whether there is a charging intention. If so, step S05 is executed.

[0072] It should be noted that the determination of whether the corresponding new energy vehicle has a navigation task is required;

[0073] If it is determined that the corresponding new energy vehicle has a navigation task, then determine whether the destination is a charging area based on the navigation task;

[0074] If the destination is determined to be a charging area, then the intention to charge is confirmed.

[0075] If it is determined that the corresponding new energy vehicle does not have a navigation task, the first movement trajectory of the new energy vehicle after the battery reaches the threshold is obtained, and the target historical movement trajectory is determined based on the first movement trajectory. Specifically, all historical movement trajectories within a preset distance before the new energy vehicle starts charging are obtained from the historical records, and it is determined whether there is a trajectory that completely overlaps with the first movement trajectory among all historical movement trajectories.

[0076] If it is determined that there is a trajectory among all historical movement trajectories that completely overlaps with the first movement trajectory, then the trajectory that completely overlaps with the first movement trajectory is determined as the target historical movement trajectory.

[0077] If it is determined that there is no trajectory that completely overlaps with the first trajectory among all historical movement trajectories, then all trajectories that overlap with the first trajectory for more than a preset length are determined as the target historical movement trajectory.

[0078] Based on the first moving trajectory and the target historical moving trajectory, calculate the charging intention score and determine whether the charging intention score is greater than the preset score. When the target historical moving trajectory completely overlaps with the first moving trajectory, determine the end position of the first moving trajectory and obtain the first distance between the end position and the end position of the target historical moving trajectory.

[0079] Based on the first distance and the pre-established first mapping relationship, the first weight coefficient corresponding to the first distance is determined. The first mapping relationship is used to input the first distance, match the first distance with the distance range value, and output the weight coefficient corresponding to the distance range value after a successful match.

[0080] Substitute the first weighting coefficient into the first fitting formula to calculate the charging intention score. For example, the first fitting formula can be N1 = αF, where α is the weighting coefficient and F is the preset base score.

[0081] When there are several historical movement trajectories of targets, determine whether the parts of each historical movement trajectory of a target that overlap with the first movement trajectory are continuous.

[0082] If it is determined that the part of the historical movement trajectory of each target that overlaps with the first movement trajectory is continuous, the end position of the last overlapping trajectory is determined, and the second distance between the end position of the last overlapping trajectory and the end position of the corresponding historical movement trajectory of the target is obtained.

[0083] Based on the second distance and the pre-established first mapping relationship, determine the second weight coefficient corresponding to the second distance;

[0084] Substitute the second weighting coefficient into the first fitting formula to calculate the charging intention score;

[0085] If it is determined that the part of the historical movement trajectory of each target that overlaps with the first movement trajectory is not continuous, then the number of continuous overlapping trajectories is obtained, and a base number is set based on the number of continuous overlapping trajectories.

[0086] Obtain the end position of each overlapping part of the trajectory, and obtain the third distance between the end position of each overlapping part of the trajectory and the end position of the corresponding target historical movement trajectory.

[0087] Based on the third distance and the first mapping relationship, determine the corresponding third weight coefficient;

[0088] Substituting the base number and the corresponding third weight coefficient into the second fitting formula, the charging intention score is calculated. For example, the second fitting formula can be expressed as N2=j+β1F+β2F+...+β i F, where β i is the third weighting coefficient for the overlapping portion of the i-th trajectory, and j is the base number;

[0089] If the score indicating a charging intention is greater than the preset score, then a charging intention is confirmed.

[0090] Step S05 involves determining the charging sub-network within the charging network based on the current location and predicted movement trajectory of the corresponding new energy vehicle.

[0091] In this embodiment, a sector is determined based on the current location and historical charging location of the corresponding new energy vehicle. The unfolding direction of the sector is determined by the driving direction of the new energy vehicle, the unfolding angle of the sector is determined by the maximum angle formed by the current location of the new energy vehicle and any two historical charging locations, and the unfolding area of ​​the sector is determined by the number of kilometers the new energy vehicle can travel with its remaining battery power.

[0092] The network formed by the charging piles covered in the sector area is defined as the charging subnetwork.

[0093] Step S06: Based on the first location, control the corresponding distributed power station to supply energy to the charging subgrid.

[0094] It should be noted that since the charging status of all new energy vehicles in the energy dispatch area is dispatched in real time, several charging sub-networks will be formed. Specifically, the charging sub-networks will be combined to obtain the target charging sub-network. That is, the target charging sub-network will be obtained by superimposing the charging sub-networks. Since there are different numbers of superpositions, the target charging sub-network can be divided into parts according to the degree of superposition.

[0095] Calculate the target energy required for each part of the target charging subnet and determine the geometric center of each part of the target charging subnet;

[0096] Based on the geometric center, find the distributed power station closest to the geometric center and control the distributed power station to transmit the target energy to the corresponding part of the target charging subgrid. It is determined whether the number of distributed power stations closest to the geometric center is unique.

[0097] If the number of distributed power stations closest to the geometric center is not unique, then the distributed power station that currently delivers the least amount of energy will be identified as the target distributed power station.

[0098] In summary, the distributed energy dispatching and management method for virtual power plants in the above embodiments of the present invention involves: acquiring an energy dispatching area; determining the first location of distributed power stations and the second location of charging piles within the energy dispatching area; combining adjacent charging piles to form a charging network based on the second location; acquiring the battery level of each new energy vehicle in the energy dispatching area and determining whether the battery level has reached a threshold; if the battery level has reached the threshold, acquiring the movement trajectory of the corresponding new energy vehicle to determine whether there is a charging intention; if there is a charging intention, determining the charging sub-network within the charging network based on the current location and predicted movement trajectory of the corresponding new energy vehicle; and controlling the corresponding distributed power station to supply energy to the charging sub-network based on the first location. Specifically, by intelligently dispatching the energy of distributed power stations and charging facilities, energy loss during transmission is optimized to achieve energy conservation.

[0099] Example 2

[0100] Please see Figure 2 , Figure 2This is a structural block diagram of a distributed energy dispatch management system for a virtual power plant according to Embodiment 2 of the present invention. This distributed energy dispatch management system 200 for the virtual power plant is used to implement the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0101] Specifically, the distributed energy dispatch management system 200 of the virtual power plant includes: an acquisition module 21, a combination module 22, a first judgment module 23, a second judgment module 24, a determination module 25, and a control module 26, wherein:

[0102] The acquisition module 21 is used to acquire the energy dispatch area and determine the first location of the distributed power station and the second location of the charging pile in the energy dispatch area;

[0103] The combination module 22 is used to combine adjacent charging piles according to the second position to form a charging network;

[0104] The first judgment module 23 is used to obtain the power of each new energy vehicle in the energy dispatch area and determine whether the power has reached a threshold.

[0105] The second judgment module 24 is used to obtain the movement trajectory of the corresponding new energy vehicle and determine whether there is a charging intention if the power level is determined to reach the threshold.

[0106] The determination module 25 is used to determine the charging sub-network in the charging network based on the current location and predicted movement trajectory of the corresponding new energy vehicle if it is determined that there is a charging intention.

[0107] The control module 26 is used to control the corresponding distributed power station to deliver energy to the charging subgrid according to the first location.

[0108] Furthermore, in some optional embodiments of the present invention, the second determining module 24 includes:

[0109] The first judgment unit is used to determine whether the corresponding new energy vehicle has a navigation task.

[0110] The second judgment unit is used to determine whether the destination is a charging area based on the navigation task if the corresponding new energy vehicle has a navigation task.

[0111] The first determining unit is used to determine that there is a charging intention if the destination is a charging area.

[0112] The second determining unit is used to obtain the first movement trajectory of the new energy vehicle after the battery level reaches a threshold if it is determined that the corresponding new energy vehicle does not have a navigation task, and to determine the target's historical movement trajectory based on the first movement trajectory.

[0113] The third judgment unit is used to calculate the charging intention score based on the first movement trajectory and the target's historical movement trajectory, and to determine whether the charging intention score is greater than a preset score.

[0114] The third determining unit is used to determine that there is a charging intention if the score of the charging intention is greater than a preset score.

[0115] Furthermore, in some optional embodiments of the present invention, the second determining unit includes:

[0116] The first judgment subunit is used to obtain all historical movement trajectories within a preset distance before the new energy vehicle starts charging in the historical records, and to determine whether there is a trajectory among all historical movement trajectories that completely overlaps with the first movement trajectory.

[0117] The first determining subunit is used to determine the trajectory that completely overlaps with the first trajectory as the target historical movement trajectory if it is determined that there is a trajectory among all historical movement trajectories that completely overlaps with the first movement trajectory.

[0118] The second determining subunit is used to determine all trajectories that overlap with the first movement trajectory for more than a preset length as the target historical movement trajectory if it is determined that there is no trajectory that completely overlaps with the first movement trajectory among all historical movement trajectories.

[0119] Furthermore, in some optional embodiments of the present invention, the third determining unit includes:

[0120] The third determining subunit is used to determine the end position of the first movement trajectory when the target historical movement trajectory completely overlaps with the first movement trajectory, and to obtain the first distance between the end position and the end position of the target historical movement trajectory.

[0121] The fourth determining subunit is used to determine the first weight coefficient corresponding to the first distance based on the first distance and the pre-established first mapping relationship, wherein the first mapping relationship is used to input the first distance, match the first distance with the distance range value, and output the weight coefficient corresponding to the distance range value after successful matching;

[0122] The first calculation subunit is used to substitute the first weighting coefficient into the first fitting formula to calculate the charging intention score;

[0123] The second judgment subunit is used to determine whether the part of each target historical movement trajectory that overlaps with the first movement trajectory is continuous when there are several target historical movement trajectories.

[0124] The fifth determining subunit is used to determine the end position of the last overlapping trajectory if it is determined that the part of each target historical movement trajectory that overlaps with the first movement trajectory is continuous, and to obtain the second distance between the end position of the last overlapping trajectory and the end position of the corresponding target historical movement trajectory.

[0125] The sixth determining subunit is used to determine the second weight coefficient corresponding to the second distance based on the second distance and the pre-established first mapping relationship;

[0126] The second calculation subunit is used to substitute the second weighting coefficient into the first fitting formula to calculate the charging intention score;

[0127] The first acquisition subunit is used to acquire the number of consecutively overlapping trajectories if it is determined that the parts of the historical movement trajectories of each target that overlap with the first movement trajectory are not continuous, and to set a base number based on the number of consecutively overlapping trajectories.

[0128] The second acquisition subunit is used to acquire the end position of each trajectory overlap portion and acquire the third distance between the end position of each trajectory overlap portion and the corresponding end position of the target historical movement trajectory.

[0129] The seventh determining subunit is used to determine the corresponding third weight coefficient based on the third distance and the first mapping relationship;

[0130] The third calculation subunit is used to substitute the base number and the corresponding third weight coefficient into the second fitting formula to calculate the charging intention score.

[0131] Furthermore, in some optional embodiments of the present invention, the determining module 25 includes:

[0132] The fourth determining unit is used to determine a sector area based on the current location and historical charging location of the corresponding new energy vehicle. The unfolding direction of the sector area is determined by the driving direction of the new energy vehicle, the unfolding angle of the sector area is determined by the maximum angle formed by the current location of the new energy vehicle and any two historical charging locations, and the unfolding area of ​​the sector area is determined by the number of kilometers the new energy vehicle can travel with its remaining battery power.

[0133] The fifth determining unit is used to determine the network formed by the charging piles covered in the fan-shaped area as the charging sub-network.

[0134] Furthermore, in some optional embodiments of the present invention, the control module 26 includes:

[0135] The combination unit is used to combine the various charging subnetworks to obtain the target charging subnetwork.

[0136] The sixth determining unit is used to calculate the target energy required for each part of the target charging subnetwork and to determine the geometric center of each part of the target charging subnetwork.

[0137] The control unit is used to locate the nearest distributed power station to the geometric center based on the geometric center, and control the distributed power station to deliver the target energy to the corresponding part of the target charging subgrid.

[0138] Furthermore, in some optional embodiments of the present invention, the control unit includes:

[0139] The third judgment subunit is used to determine whether the number of distributed power stations closest to the geometric center is unique;

[0140] The eighth determining subunit is used to determine the distributed power station that currently transmits the least energy as the target distributed power station if the number of distributed power stations closest to the geometric center is not unique.

[0141] Example 3

[0142] In another aspect, the present invention also proposes an electronic device, please refer to [link to relevant documentation]. Figure 3 The image shows an electronic device according to Embodiment 3 of the present invention, including a memory 20, a processor 10, and a computer program 30 stored in the memory and executable on the processor. When the processor 10 executes the computer program 30, it implements the distributed energy dispatch management method of the virtual power plant as described above.

[0143] In some embodiments, the processor 10 may be a central processing unit (CPU), controller, microcontroller, microprocessor or other data processing chip, used to run program code stored in memory 20 or process data, such as executing access restriction programs.

[0144] The memory 20 includes at least one type of readable storage medium, such as flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 20 can be an internal storage unit of an electronic device, such as the hard disk of the electronic device. In other embodiments, the memory 20 can also be an external storage device of the electronic device, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc. Furthermore, the memory 20 can include both internal and external storage units of the electronic device. The memory 20 can be used not only to store application software and various types of data of the electronic device, but also to temporarily store data that has been output or will be output.

[0145] It should be pointed out that, Figure 3 The structure shown does not constitute a limitation on the electronic device. In other embodiments, the electronic device may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0146] This invention also proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the distributed energy dispatch and management method for a virtual power plant as described above.

[0147] Those skilled in the art will understand that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequential list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can mean any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0148] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0149] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0150] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0151] The above embodiments merely illustrate several implementation methods of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this patent should be determined by the appended claims.

Claims

1. A distributed energy dispatch and management method for a virtual power plant, characterized in that, The method is applicable to scenarios where distributed power stations and charging piles are connected, and the energy transmission lines between the distributed power stations and each charging pile are connected, and the energy transmission lines between each charging pile are also connected. Obtain the energy dispatch area, and determine the first location of the distributed power station and the second location of the charging pile in the energy dispatch area; Based on the second location, adjacent charging piles are combined to form a charging network; Obtain the battery level of each new energy vehicle in the energy dispatch area and determine whether the battery level has reached a threshold. If it is determined that the battery level has reached the threshold, the movement trajectory of the corresponding new energy vehicle is obtained to determine whether there is an intention to charge. If it is determined that there is a charging intention, then the charging sub-network in the charging network is determined based on the current location and predicted movement trajectory of the corresponding new energy vehicle. Based on the first location, control the corresponding distributed power station to supply energy to the charging subgrid; The step of obtaining the movement trajectory of the corresponding new energy vehicle and determining whether there is a charging intention includes: Determine whether the corresponding new energy vehicle has a navigation task; If it is determined that the corresponding new energy vehicle has a navigation task, then based on the navigation task, determine whether the destination is a charging area; If the destination is determined to be a charging area, then the intention to charge is confirmed. If it is determined that the corresponding new energy vehicle does not have a navigation task, the first movement trajectory of the new energy vehicle after the battery level reaches the threshold is obtained, and the target's historical movement trajectory is determined based on the first movement trajectory. Based on the first movement trajectory and the target's historical movement trajectory, calculate the charging intention score and determine whether the charging intention score is greater than a preset score; If the score of the charging intention is greater than the preset score, then it is determined that there is a charging intention; The step of determining the charging sub-network in the charging network based on the current location and predicted movement trajectory of the corresponding new energy vehicle includes: Based on the current location and historical charging location of the corresponding new energy vehicle, a sector-shaped area is determined. The direction of the sector is determined by the driving direction of the new energy vehicle, the angle of the sector is determined by the maximum angle formed by the current location of the new energy vehicle and any two historical charging locations, and the area of ​​the sector is determined by the number of kilometers the new energy vehicle can travel with its remaining battery power. The network formed by the charging piles covered in the sector area is defined as the charging subnetwork.

2. The distributed energy dispatch and management method for virtual power plants according to claim 1, characterized in that, The step of determining the target's historical movement trajectory based on the first movement trajectory includes: In the historical records, before the new energy vehicle starts charging, all historical movement trajectories within a preset distance are obtained, and it is determined whether there is a trajectory among all historical movement trajectories that completely overlaps with the first movement trajectory. If it is determined that there is a trajectory among all historical movement trajectories that completely overlaps with the first movement trajectory, then the trajectory that completely overlaps with the first movement trajectory is determined as the target historical movement trajectory. If it is determined that there is no trajectory among all historical movement trajectories that completely overlaps with the first movement trajectory, then all trajectories that overlap with the first movement trajectory for more than a preset length are determined as the target historical movement trajectory.

3. The distributed energy dispatch and management method for virtual power plants according to claim 2, characterized in that, The step of calculating the charging intention score based on the first movement trajectory and the target's historical movement trajectory includes: When the target's historical movement trajectory completely overlaps with the first movement trajectory, the end position of the first movement trajectory is determined, and the first distance between the end position and the end position of the target's historical movement trajectory is obtained; Based on the first distance and the pre-established first mapping relationship, a first weight coefficient corresponding to the first distance is determined, wherein the first mapping relationship is used to input the first distance, match the first distance with the distance range value, and output the weight coefficient corresponding to the distance range value after a successful match. Substitute the first weighting coefficient into the first fitting formula to calculate the charging intention score; When there are several target historical movement trajectories, it is determined whether the part of each target historical movement trajectory that overlaps with the first movement trajectory is continuous; If it is determined that the part of each target's historical movement trajectory that overlaps with the first movement trajectory is continuous, the end position of the last overlapping trajectory is determined, and the second distance between the end position of the last overlapping trajectory and the end position of the corresponding target's historical movement trajectory is obtained. Based on the second distance and the pre-established first mapping relationship, determine the second weight coefficient corresponding to the second distance; Substitute the second weighting coefficient into the first fitting formula to calculate the charging intention score; If it is determined that the part of the historical movement trajectory of each target that overlaps with the first movement trajectory is not continuous, then the number of continuous overlapping trajectories is obtained, and a base number is set according to the number of continuous overlapping trajectories; Obtain the end position of each overlapping part of the trajectory, and obtain the third distance between the end position of each overlapping part of the trajectory and the corresponding end position of the target's historical movement trajectory. Based on the third distance and the first mapping relationship, determine the corresponding third weight coefficient; Substitute the base number and the corresponding third weight coefficient into the second fitting formula to calculate the charging intention score.

4. The distributed energy dispatch and management method for virtual power plants according to claim 3, characterized in that, The step of controlling the corresponding distributed power station to supply energy to the charging subgrid based on the first location includes: By combining the various charging subnets, the target charging subnet is obtained; Calculate the target energy required for each part of the target charging subnetwork and determine the geometric center of each part of the target charging subnetwork; Based on the geometric center, locate the distributed power station closest to the geometric center and control the distributed power station to transmit the target energy to the corresponding part of the target charging subgrid.

5. The distributed energy dispatch and management method for virtual power plants according to claim 4, characterized in that, The step of finding the nearest distributed power station to the geometric center based on the geometric center, and controlling the distributed power station to transmit the target energy to the corresponding part of the target charging subgrid includes: Determine whether the number of distributed power stations closest to the geometric center is unique; If the number of distributed power stations closest to the geometric center is not unique, then the distributed power station that currently delivers the least amount of energy is determined as the target distributed power station.

6. A distributed energy dispatch and management system for a virtual power plant, characterized in that, The system is used to implement the distributed energy dispatch management method for a virtual power plant as described in any one of claims 1-5, the system comprising: The acquisition module is used to acquire the energy dispatch area and determine the first location of the distributed power station and the second location of the charging pile in the energy dispatch area; The combination module is used to combine adjacent charging piles according to the second position to form a charging network; The first judgment module is used to obtain the power of each new energy vehicle in the energy dispatch area and determine whether the power has reached a threshold. The second judgment module is used to obtain the movement trajectory of the corresponding new energy vehicle and determine whether there is a charging intention if the battery level reaches the threshold. The determination module is used to determine the charging sub-network in the charging network based on the current location and predicted movement trajectory of the corresponding new energy vehicle if it is determined that there is a charging intention. The control module is used to control the corresponding distributed power station to supply energy to the charging subgrid based on the first location.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the distributed energy dispatch management method for the virtual power plant as described in any one of claims 1-5.

8. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the distributed energy dispatch management method for a virtual power plant as described in any one of claims 1-5.

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