Distributed energy scheduling management method and system for virtual power plant

Abstract

The invention provides a distributed energy scheduling management method and system for a virtual power plant, and the method comprises the steps: determining a first position of a distributed power station and a second position of a charging pile in an energy scheduling region through obtaining the energy scheduling region; according to the second position, the adjacent charging piles are combined to form a charging network; obtaining the electric quantity of each new energy automobile in the energy dispatching area, and judging whether the electric quantity reaches a threshold value or not; if it is judged that the electric quantity reaches the threshold value, the corresponding moving track of the new energy automobile is obtained, and whether a charging intention exists or not is judged; if it is judged that the charging intention exists, a charging sub-network in the charging network is determined according to the current position of the corresponding new energy automobile and the predicted moving track; and according to the first position, the corresponding distributed power station is controlled to transmit energy to the charging sub-network, specifically, the energy of the distributed power station and each charging facility is intelligently dispatched to optimize the loss of the energy in the transmission process, and the purpose of saving the energy is achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of energy dispatching management, and in particular relates to a distributed energy dispatching management method and system for a virtual power plant. Background Art

[0002] In today's era, society pays more and more attention to sustainable energy, environmental protection awareness is deeply rooted in people's hearts, and the power market is showing a rapid development trend. However, these developments have also made the power system face unprecedented complex challenges. The traditional centralized power system is gradually unable to cope with such challenges due to its inherent limitations.

[0003] On the one hand, large centralized power plants use a long-distance power transmission model, which results in extremely serious energy loss in the process. A large amount of energy is lost in the transmission lines, which directly leads to a sharp increase in operating costs and a significant reduction in energy efficiency. For example, during long-distance high-voltage power transmission, due to the existence of wire resistance, electrical energy will continue to be converted into heat energy and dissipated in the environment. On the other hand, this traditional power supply model is seriously inflexible. Once a link in the power system fails, the recovery time of the entire power supply network is often long, which has a great negative impact on power supply reliability and may cause large-scale power outages, bringing many inconveniences and losses to social production and life.

[0004] In particular, as the proportion of renewable energy in the power supply system continues to rise, the traditional power transmission model has exposed its weak ability to integrate distributed energy resources. Distributed energy has the characteristics of dispersion and intermittency, and it is difficult for the traditional model to effectively coordinate and manage it, resulting in frequent imbalances in power supply and demand, further exacerbating the fluctuations and instability of the power 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 day by day, charging piles and other related charging facilities also need to be equipped. General green energy such as solar energy is no longer sufficient to meet the charging needs of new energy vehicles. The above-mentioned method, that is, supplying power through a centralized power plant using a long-distance power transmission mode, undoubtedly increases energy loss. At the same time, once a link in the power system fails, it is difficult to recover in time. Summary of the invention

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

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

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

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

[0010] Obtaining the power of each new energy vehicle in the energy dispatching area, and determining whether the power reaches a threshold;

[0011] If it is determined that the power level reaches the threshold, the movement trajectory of the corresponding new energy vehicle is obtained to determine whether there is a charging intention;

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

[0013] According to the first position, the corresponding distributed power station is controlled to transmit energy to the charging subgrid.

[0014] Furthermore, the step of obtaining the movement trajectory of the corresponding new energy vehicle and determining whether there is a charging intention includes:

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

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

[0017] If the destination is determined to be a charging area, it is determined that there is a charging intention;

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

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

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

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

[0022] Obtain all historical movement trajectories within a preset number of kilometers before the new energy vehicle starts charging in the historical records, and determine whether there is a trajectory in all the historical movement trajectories that completely overlaps with the first movement trajectory;

[0023] If it is determined that there is a trajectory that completely overlaps with the first movement trajectory among all the historical movement trajectories, 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 that completely overlaps with the first movement trajectory among all the historical movement trajectories, 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 according to the first moving trajectory and the target historical moving trajectory includes:

[0026] When the target historical movement trajectory completely overlaps with the first movement trajectory, determining the end position of the first movement trajectory, and obtaining a first distance between the end position and the end position of the target historical movement trajectory;

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

[0028] Substituting the first weight coefficient into a first fitting formula to calculate the charging intention score;

[0029] When there are a plurality of target historical movement trajectories, determining whether the overlapped portions of the target historical movement trajectories and the first movement trajectory are continuous;

[0030] If it is determined that the overlapped parts of the historical movement trajectories of the target and the first movement trajectory are continuous, determining the end position of the last overlapping trajectory, and obtaining a second distance between the end position of the last overlapping trajectory and the corresponding end position of the historical movement trajectory of the target;

[0031] Determining a second weight coefficient corresponding to the second distance according to the second distance and a pre-established first mapping relationship;

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

[0033] If it is determined that the overlapped portion of each of the target historical movement trajectories and the first movement trajectory is discontinuous, the number of continuous overlapped trajectories is obtained, and a base number is set according to the number of continuous overlapped trajectories;

[0034] Obtaining the end position of the overlapping portion of each track, and obtaining a third distance between the end position of the overlapping portion of each track and the corresponding end position of the target historical movement track;

[0035] Determining a corresponding third weight coefficient according to the third distance and the first mapping relationship;

[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 a charging subnet in the charging network according to the current position and predicted movement trajectory of the corresponding new energy vehicle includes:

[0038] According to the current position and historical charging position of the corresponding new energy vehicle, a sector area is determined, wherein the expansion direction of the sector area is determined by the driving direction of the new energy vehicle, the expansion angle of the sector area is determined by the maximum angle formed by the current position of the new energy vehicle and any two historical charging positions, and the expansion area of ​​the sector area is determined by the number of kilometers traveled by the remaining power of the new energy vehicle;

[0039] The network formed by the charging piles covered in the sector-shaped area is determined as the charging subnet.

[0040] Furthermore, the step of controlling the corresponding distributed power station to transmit energy to the charging subnet according to the first position includes:

[0041] Combine the charging subnets to obtain a target charging subnet;

[0042] Calculating the target energy required by each part of the target charging subnet and determining the geometric center of each part of the target charging subnet;

[0043] According to the geometric center, the distributed power stations closest to the geometric center are found respectively, and the distributed power stations are controlled to transport the target energy to the corresponding part of the target charging subnet.

[0044] Furthermore, the step of searching for the distributed power station closest to the geometric center and controlling the distributed power station to deliver the target energy to the corresponding part of the target charging subnet includes:

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

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

[0047] A second aspect of an embodiment of the present invention provides a distributed energy dispatching and management system for a virtual power plant, which is used to implement the distributed energy dispatching and management method for a virtual power plant provided in the first aspect. The system includes:

[0048] An acquisition module, used to acquire an energy scheduling area, and determine a first position of a distributed power station and a second position of a charging pile in the energy scheduling area;

[0049] A combining module, used for combining adjacent charging piles according to the second position to form a charging network;

[0050] A first judgment module is used to obtain the power of each new energy vehicle in the energy scheduling area and judge whether the power reaches a threshold;

[0051] The second judgment module is used to obtain the movement trajectory of the corresponding new energy vehicle and judge whether there is a charging intention if it is judged that the power reaches the threshold;

[0052] A determination module, for determining a charging subnet in the charging network according to the current position and predicted movement trajectory of the corresponding new energy vehicle if it is determined that there is a charging intention;

[0053] A control module is used to control the corresponding distributed power station to transmit energy to the charging subnet according to the first position.

[0054] A third aspect of an embodiment 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 dispatching and management method for a virtual power plant provided in the first aspect.

[0055] The fourth aspect of an embodiment 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 when the processor executes the program, the distributed energy dispatching and management method for a virtual power plant provided in the first aspect is implemented.

[0056] A distributed energy dispatching management method and system for a virtual power plant is provided in an embodiment of the present invention. The method determines a first position of a distributed power station and a second position of a charging pile in the energy dispatching area by acquiring an energy dispatching area; according to the second position, adjacent charging piles are combined to form a charging network; the power of each new energy vehicle in the energy dispatching area is acquired to determine whether the power has reached a threshold; if it is determined that the power has reached the threshold, the moving trajectory of the corresponding new energy vehicle is acquired to determine whether there is a charging intention; if it is determined that there is a charging intention, the charging subnet in the charging network is determined according to the current position and predicted moving trajectory of the corresponding new energy vehicle; according to the first position, the corresponding distributed power station is controlled to transmit energy to the charging subnet. Specifically, the energy of the distributed power station and each charging facility is intelligently dispatched to optimize the energy loss during the transmission process, thereby achieving the purpose of energy saving. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 A flowchart of a distributed energy scheduling management method for a virtual power plant provided in the first embodiment of the present invention;

[0058] Figure 2 A structural block diagram of a distributed energy dispatching 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 DESCRIPTION

[0060] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.

[0061] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

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

[0063] Embodiment 1

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

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

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

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

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

[0069] Step S03, obtaining the power of each new energy vehicle in the energy scheduling area, and determining whether the power reaches a threshold, if so, executing step S04.

[0070] Specifically, by connecting the new energy vehicle to the server, the power level and mileage of the new energy vehicle can be obtained in real time. When the power level reaches a threshold, it means that the new energy vehicle needs to be charged in time.

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

[0072] It should be noted that it is necessary to determine whether the corresponding new energy vehicle has a navigation task;

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

[0074] If the destination is determined to be a charging area, it is determined that there is a charging intention;

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

[0076] If it is determined that there is a trajectory that completely overlaps with the first movement trajectory among all the historical movement trajectories, 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 movement trajectory among all the historical movement trajectories, all trajectories that overlap with the first movement trajectory for more than a preset length are determined as target historical movement trajectories;

[0078] Calculate the charging intention score according to the first moving trajectory and the target historical moving trajectory, and determine whether the charging intention score is greater than a preset score, wherein when the target historical moving trajectory completely overlaps with the first moving trajectory, determine the end position of the first moving trajectory, and obtain a first distance between the end position and the end position of the target historical moving trajectory;

[0079] Determine a first weight coefficient corresponding to the first distance according to the first distance and a 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 the match is successful;

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

[0081] When there are several target historical movement trajectories, determining whether the parts of the target historical movement trajectories that overlap with the first movement trajectory are continuous;

[0082] If it is determined that the overlapped parts of the historical movement trajectories of each target are continuous with the first movement trajectory, the end position of the last overlapped trajectory is determined, and a second distance between the end position of the last overlapped trajectory and the end position of the corresponding historical movement trajectory of the target is obtained;

[0083] Determine a second weight coefficient corresponding to the second distance according to the second distance and the pre-established first mapping relationship;

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

[0085] If it is determined that the part of each target's historical moving trajectory that overlaps with the first moving trajectory is discontinuous, the number of continuous overlapping trajectories is obtained, and a base number is set according to the number of continuous overlapping trajectories;

[0086] Obtaining the end position of the overlapping portion of each trajectory, and obtaining a third distance between the end position of the overlapping portion of each trajectory and the end position of the corresponding target historical movement trajectory;

[0087] Determine a corresponding third weight coefficient according to the third distance and the first mapping relationship;

[0088] Substitute the base number and the corresponding third weight coefficient into the second fitting formula to calculate the charging intention score. For example, the second fitting formula can be expressed as N2=j+β1F+β2F+...+β i F, where β i is the third weight coefficient of the overlapped part of the i-th trajectory, and j is the cardinality;

[0089] If it is determined that the charging intention score is greater than the preset score, it is determined that there is a charging intention.

[0090] In step S05, a charging subnet in the charging network is determined according to the current position and predicted movement trajectory of the corresponding new energy vehicle.

[0091] In this embodiment, a sector area is determined according to the current position and historical charging position of the corresponding new energy vehicle, wherein the expansion direction of the sector area is determined by the driving direction of the new energy vehicle, the expansion angle of the sector area is determined by the maximum angle formed by the current position of the new energy vehicle and any two historical charging positions, and the expansion area of ​​the sector area is determined by the number of kilometers traveled by the remaining power of the new energy vehicle;

[0092] The network formed by the charging piles covered in the sector-shaped area is determined as a charging subnet.

[0093] Step S06: According to the first position, control the corresponding distributed power station to transmit energy to the charging subnet.

[0094] It should be noted that, since the charging status of all new energy vehicles in the energy dispatching area is dispatched in real time, several charging subnets will be formed. Specifically, the charging subnets are combined to obtain the target charging subnet, that is, the target charging subnet is obtained by superimposing the charging subnets. Since there are different times of superposition, the target charging subnet can be divided into various 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] According to the geometric center, the distributed power stations closest to the geometric center are found respectively, and the distributed power stations are controlled to deliver the target energy to the corresponding part of the target charging subnet, wherein it is determined whether the number of distributed power stations closest to the geometric center is unique;

[0097] If it is determined that the number of distributed power stations closest to the geometric center is not unique, the distributed power station that currently transmits the least energy is determined as the target distributed power station.

[0098] In summary, the distributed energy dispatching and management method of the virtual power plant in the above-mentioned embodiment of the present invention determines the first position of the distributed power station and the second position of the charging pile in the energy dispatching area by acquiring the energy dispatching area; according to the second position, the adjacent charging piles are combined to form a charging network; the power of each new energy vehicle in the energy dispatching area is obtained to determine whether the power reaches the threshold; if it is determined that the power reaches the threshold, the moving trajectory of the corresponding new energy vehicle is obtained to determine whether there is a charging intention; if it is determined that there is a charging intention, the charging subnet in the charging network is determined according to the current position of the corresponding new energy vehicle and the predicted moving trajectory; according to the first position, the corresponding distributed power station is controlled to transmit energy to the charging subnet. Specifically, the energy of the distributed power station and each charging facility is intelligently dispatched to optimize the energy loss during the transmission process, so as to achieve the purpose of energy saving.

[0099] Embodiment 2

[0100] See also Figure 2 , Figure 2It is a structural block diagram of a distributed energy dispatching and management system for a virtual power plant provided in the second embodiment of the present invention. The distributed energy dispatching and management system 200 for the virtual power plant is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation in hardware, or a combination of software and hardware, is also possible and conceivable.

[0101] Specifically, the distributed energy dispatching and 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] An acquisition module 21 is used to acquire an energy scheduling area and determine a first position of a distributed power station and a second position of a charging pile in the energy scheduling area;

[0103] A combining module 22, configured 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 scheduling area and judge whether the power reaches a threshold;

[0105] The second judgment module 24 is used to obtain the movement track of the corresponding new energy vehicle and judge whether there is a charging intention if it is judged that the power reaches the threshold;

[0106] A determination module 25, for determining a charging subnet in the charging network according to the current position 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 transmit energy to the charging subnet according to the first position.

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

[0109] A first judgment unit is used to judge whether the corresponding new energy vehicle has a navigation task;

[0110] A second judgment unit is used to judge whether the destination is a charging area according to the navigation task if it is judged that the corresponding new energy vehicle has a navigation task;

[0111] a first determining unit, configured to determine that there is a charging intention if the destination is determined to be a charging area;

[0112] A second determination unit is configured to obtain a first moving trajectory of the new energy vehicle after the power of the new energy vehicle reaches a threshold value if it is determined that the corresponding new energy vehicle does not have a navigation task, and determine a target historical moving trajectory according to the first moving trajectory;

[0113] a third judgment unit, configured to 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;

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

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

[0116] A first judgment subunit is used to obtain all historical movement trajectories within a preset number of kilometers before the new energy vehicle starts charging in the historical records, and to judge whether there is a trajectory in all the historical movement trajectories that completely overlaps with the first movement trajectory;

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

[0118] The second determining subunit is configured 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 the historical movement trajectories.

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

[0120] a third determining subunit, configured to determine an end position of the first moving trajectory when the target historical moving trajectory completely overlaps with the first moving trajectory, and to obtain a first distance between the end position and an end position of the target historical moving trajectory;

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

[0122] A first calculation subunit, configured to substitute the first weight coefficient into a first fitting formula to calculate the charging intention score;

[0123] A second judgment subunit is used to judge whether the overlapped parts of the target historical movement trajectories and the first movement trajectory are continuous when there are a plurality of target historical movement trajectories;

[0124] a fifth determining subunit, configured to determine the end position of the last overlapping trajectory if it is determined that the overlapped portion of each of the target historical movement trajectories with the first movement trajectory is continuous, and obtain a second distance between the end position of the last overlapping trajectory and the corresponding end position of the target historical movement trajectory;

[0125] a sixth determining subunit, configured to determine a second weight coefficient corresponding to the second distance according to the second distance and a pre-established first mapping relationship;

[0126] a second calculation subunit, configured to substitute the second weight coefficient into the first fitting formula to calculate the charging intention score;

[0127] A first acquisition subunit is used for acquiring the number of continuous overlapping trajectories if it is determined that the overlapped portion of each of the target historical movement trajectories and the first movement trajectory is discontinuous, and setting a base number according to the number of continuous overlapping trajectories;

[0128] A second acquisition subunit is used to acquire the end position of the overlapping part of each track, and acquire a third distance between the end position of the overlapping part of each track and the corresponding end position of the target historical movement track;

[0129] a seventh determining subunit, configured to determine a corresponding third weight coefficient according to 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] Further, in some optional embodiments of the present invention, the determining module 25 includes:

[0132] A fourth determination unit is used to determine a fan-shaped area according to the current position and the historical charging position of the corresponding new energy vehicle, wherein the expansion direction of the fan-shaped area is determined by the driving direction of the new energy vehicle, the expansion angle of the fan-shaped area is determined by the maximum angle formed by the current position of the new energy vehicle and any two historical charging positions, and the expansion area of ​​the fan-shaped area is determined by the number of kilometers traveled by the remaining power of the new energy vehicle;

[0133] The fifth determining unit is configured to determine a network formed by charging piles covered in the sector-shaped area as the charging subnet.

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

[0135] A combining unit, used for combining the charging subnets to obtain a target charging subnet;

[0136] a sixth determining unit, configured to calculate the target energy required by each part of the target charging subnet and determine the geometric center of each part of the target charging subnet;

[0137] The control unit is used to find the distributed power station closest to the geometric center according to the geometric center, and control the distributed power station to transport the target energy to the corresponding part of the target charging subnet.

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

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

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

[0141] Embodiment 3

[0142] Another aspect of the present invention provides an electronic device, see Figure 3 , shown is an electronic device in embodiment three 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, and when the processor 10 executes the computer program 30, it implements the distributed energy dispatching management method of the virtual power plant as described above.

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

[0144] Among them, the memory 20 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), magnetic memory, disk, optical disk, etc. The memory 20 may be an internal storage unit of an electronic device in some embodiments, such as a hard disk of the electronic device. The memory 20 may also be an external storage device of an electronic device in other embodiments, such as a plug-in hard disk equipped on the electronic device, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. Further, the memory 20 may also include both an internal storage unit and an external storage device of the electronic device. The memory 20 may 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 is to 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 those shown in the figure, or combine certain components, or arrange the components differently.

[0146] An embodiment of the present invention further proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the distributed energy dispatching and management method of a virtual power plant as described above.

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

[0148] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0149] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0150] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0151] The above embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present invention. It should be pointed out that, for a person of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention patent shall be subject to the attached claims.

Claims

1. A distributed energy dispatching and management method for a virtual power plant, characterized in that: Applied to an application scenario with a distributed power station and charging piles supporting new energy vehicles, and the energy transmission lines of the distributed power station and each charging pile are connected, and the energy transmission lines between the charging piles are connected, the method includes: Acquire an energy dispatching area, and determine a first position of a distributed power station and a second position of a charging pile in the energy dispatching area; According to the second position, adjacent charging piles are combined to form a charging network; Obtaining the power of each new energy vehicle in the energy dispatching area, and determining whether the power reaches a threshold; If it is determined that the power level reaches the threshold, the movement trajectory of the corresponding new energy vehicle is obtained to determine whether there is a charging intention; If it is determined that there is a charging intention, determining a charging subnet in the charging network according to the current position and predicted movement trajectory of the corresponding new energy vehicle; According to the first position, the corresponding distributed power station is controlled to transmit energy to the charging subgrid.

2. The distributed energy dispatching management method of a virtual power plant according to claim 1 is characterized in that: 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 judging whether the destination is a charging area according to the navigation task; If the destination is determined to be a charging area, it is determined that there is a charging intention; If it is determined that the corresponding new energy vehicle does not have a navigation task, a first moving trajectory of the new energy vehicle after the power level reaches a threshold is obtained, and a target historical moving trajectory is determined according to the first moving trajectory; Calculating a charging intention score according to the first moving trajectory and the target historical moving trajectory, and determining whether the charging intention score is greater than a preset score; If it is determined that the charging intention score is greater than a preset score, it is determined that there is a charging intention.

3. The distributed energy dispatching management method of a virtual power plant according to claim 2 is characterized in that: The step of determining the target historical movement trajectory according to the first movement trajectory comprises: Obtain all historical movement trajectories within a preset number of kilometers before the new energy vehicle starts charging in the historical records, and determine whether there is a trajectory in all the historical movement trajectories that completely overlaps with the first movement trajectory; If it is determined that there is a trajectory that completely overlaps with the first movement trajectory among all the historical movement trajectories, 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 that completely overlaps with the first movement trajectory among all the historical movement trajectories, all trajectories that overlap with the first movement trajectory for more than a preset length are determined as the target historical movement trajectory.

4. The distributed energy dispatching management method of a virtual power plant according to claim 3 is characterized in that: The step of calculating the charging intention score according to the first moving trajectory and the target historical moving trajectory includes: When the target historical movement trajectory completely overlaps with the first movement trajectory, determining the end position of the first movement trajectory, and obtaining a first distance between the end position and the end position of the target historical movement trajectory; Determine a first weight coefficient corresponding to the first distance according to the first distance and a pre-established first mapping relationship, wherein the first mapping relationship is used to input the first distance, match the first distance with a distance range value, and output the weight coefficient corresponding to the distance range value after the match is successful; Substituting the first weight coefficient into a first fitting formula to calculate the charging intention score; When there are a plurality of target historical movement trajectories, determining whether the overlapped portions of the target historical movement trajectories and the first movement trajectory are continuous; If it is determined that the overlapped parts of the historical movement trajectories of the target and the first movement trajectory are continuous, determining the end position of the last overlapping trajectory, and obtaining a second distance between the end position of the last overlapping trajectory and the corresponding end position of the historical movement trajectory of the target; Determining a second weight coefficient corresponding to the second distance according to the second distance and a pre-established first mapping relationship; Substituting the second weight coefficient into the first fitting formula to calculate the charging intention score; If it is determined that the overlapped portion of each of the target historical movement trajectories and the first movement trajectory is discontinuous, the number of continuous overlapped trajectories is obtained, and a base number is set according to the number of continuous overlapped trajectories; Obtaining the end position of the overlapping portion of each track, and obtaining a third distance between the end position of the overlapping portion of each track and the corresponding end position of the target historical movement track; Determining a corresponding third weight coefficient according to the third distance and the first mapping relationship; Substitute the base number and the corresponding third weight coefficient into the second fitting formula to calculate the charging intention score.

5. The distributed energy dispatching management method of a virtual power plant according to claim 4 is characterized in that: The step of determining a charging subnet in the charging network according to the current position and predicted movement trajectory of the corresponding new energy vehicle includes: According to the current position and historical charging position of the corresponding new energy vehicle, a sector area is determined, wherein the expansion direction of the sector area is determined by the driving direction of the new energy vehicle, the expansion angle of the sector area is determined by the maximum angle formed by the current position of the new energy vehicle and any two historical charging positions, and the expansion area of ​​the sector area is determined by the number of kilometers traveled by the remaining power of the new energy vehicle; The network formed by the charging piles covered in the sector-shaped area is determined as the charging subnet.

6. The distributed energy dispatching management method of a virtual power plant according to claim 5 is characterized in that: The step of controlling the corresponding distributed power station to transmit energy to the charging subnet according to the first position includes: Combine the charging subnets to obtain a target charging subnet; Calculating the target energy required by each part of the target charging subnet and determining the geometric center of each part of the target charging subnet; According to the geometric center, the distributed power stations closest to the geometric center are found respectively, and the distributed power stations are controlled to transport the target energy to the corresponding part of the target charging subnet.

7. The distributed energy dispatching management method of a virtual power plant according to claim 6, characterized in that: The step of searching for the distributed power station closest to the geometric center according to the geometric center and controlling the distributed power station to deliver the target energy to the corresponding part of the target charging subnet includes: Determining whether the number of distributed power stations closest to the geometric center is unique; If it is determined that the number of distributed power stations closest to the geometric center is not unique, the distributed power station that currently transmits the least energy is determined as the target distributed power station.

8. A distributed energy dispatching and management system for a virtual power plant, characterized in that: A distributed energy dispatching management method for implementing a virtual power plant according to any one of claims 1 to 7, the system comprising: An acquisition module, used to acquire an energy scheduling area, and determine a first position of a distributed power station and a second position of a charging pile in the energy scheduling area; A combining module, used for combining adjacent charging piles according to the second position to form a charging network; A first judgment module is used to obtain the power of each new energy vehicle in the energy scheduling area and judge whether the power reaches a threshold; The second judgment module is used to obtain the movement trajectory of the corresponding new energy vehicle and judge whether there is a charging intention if it is judged that the power reaches the threshold; A determination module, for determining a charging subnet in the charging network according to the current position and predicted movement trajectory of the corresponding new energy vehicle if it is determined that there is a charging intention; A control module is used to control the corresponding distributed power station to transmit energy to the charging subnet according to the first position.

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

10. 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. When the processor executes the program, it implements the distributed energy dispatching and management method of a virtual power plant as described in any one of claims 1 to 7.

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