An adaptive power supply vehicle parallel connection method

Abstract

The invention discloses an adaptive power supply vehicle parallel connection and grid connection method, comprising: defining each power supply vehicle as a power supply vehicle network node, paralleling a plurality of power supply vehicles to form a power supply vehicle network node group, and grid-connecting a plurality of power supply vehicle network node groups to form a power supply vehicle power carrier self-organizing network; predicting the predicted load of the current power supply area through a prediction model, and estimating the number of required power supply vehicles according to the predicted load; judging whether the number of power supply vehicles in the current power supply vehicle network node group is greater than the required number of power supply vehicles, and if so, performing load balancing power supply, otherwise calculating the required number of power supply vehicles gap; and remotely dispatching the power supply vehicles to grid-connect and transmit electricity through the power supply vehicle power carrier self-organizing network according to the required number of power supply vehicles gap.

Description

Technical Field

[0001] The present invention relates to the technical field of power supply vehicle parallel connection and grid connection, and in particular to an adaptive power supply vehicle parallel connection and grid connection method. Background Art

[0002] A power supply vehicle is a mobile power generation device, which is often used to supply electricity in major disasters and emergencies. Traditional single power supply vehicle systems often cannot meet large-scale, high-load power demands. Therefore, flexible power supply can be achieved by connecting multiple power supply vehicles in parallel and in grid connection. The parallel connection and grid connection of multiple power supply vehicles refers to connecting multiple mobile power sources or generator systems together to jointly provide power output, or connecting them to the public grid to achieve greater power supply and stability. These two methods can work together to meet higher or more complex power demands.

[0003] In a major disaster environment, multiple power supply vehicles may be affected by multiple factors such as the environment, communication interruption and equipment failure. Parallel operation requires synchronization of multiple parameters such as frequency, phase and voltage. Conventional wireless communication may have high latency in a disaster environment. In addition, power supply vehicles may not be able to be parked in a centralized manner due to the disaster environment and may be scattered in different areas. Especially when multiple power supply vehicles are far apart, not only can the parallel signal transmission not be performed through conventional wireless communication methods, but parallel operation cannot be performed directly through cable series connection.

[0004] Furthermore, when the power supply demand in the disaster area increases, the current parallel operation of several power supply vehicles often cannot meet the demand. More power supply vehicles are needed to provide joint power output. The only way is to transfer power supply vehicles across regions to the power supply site, which requires a lot of manpower and material resources. In addition, the parallel power output of multiple power supply vehicles also requires solving the power consumption distribution and load balancing problems within the network of multiple power supply vehicles. Traditional energy consumption control strategies are difficult to effectively cope with the complex dynamic changes under the conditions of multiple vehicles being connected in parallel.

[0005] The purpose of the present invention is to design an adaptive power supply vehicle parallel connection method in view of the above-mentioned problems in the prior art. Summary of the invention

[0006] In view of this, an object of the present invention is to provide an adaptive power supply vehicle parallel connection method, which can solve the above-mentioned problems.

[0007] The present invention provides an adaptive power supply vehicle parallel connection method, comprising:

[0008] Each power supply vehicle is defined as a power supply vehicle network node, several power supply vehicles are connected in parallel to form a power supply vehicle network node group, and several power supply vehicle network node groups are connected in parallel to form a power supply vehicle power carrier self-organizing network;

[0009] Predict the load in the current power supply area through the prediction model, and estimate the number of power supply vehicles required based on the predicted load;

[0010] Determine whether the number of power supply vehicles in the current power supply vehicle network node group is greater than the required number of power supply vehicles. If so, load balancing power supply is performed; otherwise, the required number of power supply vehicles is calculated;

[0011] According to the shortfall in the number of power supply vehicles required, the power supply vehicles are remotely dispatched through the power supply vehicle's power carrier self-organizing network to connect to the grid and transmit electricity.

[0012] Further, each power supply vehicle is defined as a power supply vehicle network node, several power supply vehicles are connected in parallel to form a power supply vehicle network node group, and several power supply vehicle network node groups are connected in parallel to form a power supply vehicle power carrier self-organizing network, including:

[0013] Assign a unique identifier to each power vehicle network node, obtain the memory capacity, current load, and geographic location of the power vehicle controller, and each power vehicle network node broadcasts its own memory capacity, current load, and geographic location;

[0014] Calculate the priority parameter according to the memory capacity, current load, and geographic location, compare the priority parameter sizes, elect the power supply vehicle network node with the largest priority as the main power supply vehicle network node, mark the corresponding identifier as the main power supply vehicle network node, and form a power supply vehicle network node group;

[0015] Select any power supply vehicle network node in the power supply vehicle network node group and connect it to the grid to form a power carrier self-organizing network of the power supply vehicle.

[0016] Further, the calculation of priority parameters according to memory capacity, current load, and geographic location includes:

[0017] The standardized memory capacity is calculated by the minimum and maximum memory capacities of all power vehicle network nodes. The calculation formula is as follows:

[0018] ,

[0019] in, To standardize memory capacity, is the memory capacity of the current power supply vehicle network node, is the minimum memory capacity of all power car nodes, It is the maximum value of memory capacity in all power car nodes;

[0020] The standardized load is calculated by the minimum and maximum values ​​of the loads of all power supply vehicle network nodes. The calculation formula is as follows:

[0021] ,

[0022] in, For standardized load, is the current load, is the minimum value of the load in all power supply vehicle network nodes, is the maximum value of the load in all power supply vehicle network nodes;

[0023] Define the central location, and calculate the standardized geographic location by the minimum and maximum distances from all power supply vehicle network nodes to the central location. The calculation formula is as follows:

[0024] ,

[0025] in, To standardize geographic location, For the current geographic location, is the minimum distance from all power car network nodes to the center, is the maximum distance from all power car network nodes to the center;

[0026] The priority parameter is calculated based on the standardized memory capacity, standardized load capacity, and standardized geographic location. The calculation formula is as follows:

[0027] ,

[0028] in, is the priority parameter, is the memory capacity weight, Load weight, is the geographical location weight, To standardize memory capacity, For standardized load, Standardized geographic location.

[0029] Further, after forming the power vehicle network node group, the following steps are performed:

[0030] Each power supply vehicle network node monitors the status of the current main power supply vehicle network node by sending heartbeat messages regularly;

[0031] If any main power supply vehicle network node does not receive the heartbeat information fed back by the main power supply vehicle network node within the specified time, a re-election will be started.

[0032] Further, predicting the predicted load of the current power supply area by using the prediction model includes:

[0033] Collect historical load data and its corresponding temperature, weather, holiday information, and regional historical electricity consumption data to build load training samples;

[0034] The prediction model is constructed through the neural network model, and the temperature, weather, holiday information, and regional historical electricity consumption data are used as the input of the prediction model, and the historical load data is used as the output of the prediction model to train the prediction model;

[0035] The current temperature, weather, holiday information, and regional historical electricity consumption data are input into the prediction model to obtain the predicted load capacity of the current power supply area.

[0036] Further, estimating the number of power supply vehicles required according to the predicted load includes:

[0037] The idle load of each power supply vehicle is calculated based on the rated power and current load of each power supply vehicle in the current power supply vehicle network node group. The calculation formula is as follows:

[0038] ,

[0039] in, For idle load, For rated power, For idle load, is the coefficient of rated power;

[0040] Calculate the average idle load of the power supply vehicles in the current power supply vehicle network node group, and estimate the number of power supply vehicles required based on the predicted load of the current power supply area.

[0041] Further, the load balancing power supply includes:

[0042] In the power supply vehicle network node group, a number of initial power supply vehicle network node parallel combinations are randomly generated to form a population, and each parallel combination is an individual;

[0043] Design a fitness function based on the optimal target of rated power, current load, and geographical location, and calculate the fitness of each parallel combination through the fitness function;

[0044] Select the node parallel combination whose fitness is greater than the fitness threshold to perform a cross combination of a single node or multiple nodes to obtain a new node parallel combination;

[0045] Calculate the fitness of the new node parallel combination, select the node parallel combination with a fitness greater than the fitness threshold for cross iteration, and stop when the fitness converges to the target value;

[0046] Select the node parallel combination with the highest fitness, and send a parallel signal to the corresponding power supply vehicle network node through the power supply vehicle network node group.

[0047] Furthermore, the fitness function is:

[0048] ,

[0049] Among them, the S node parallel combination, are weight coefficients respectively.

[0050] Further, the method of remotely dispatching the power supply vehicle to connect to the grid and transmit electricity through the power carrier self-organizing network of the power supply vehicle according to the shortage of the required number of power supply vehicles includes:

[0051] Obtain the nearby power supply vehicle network node group through the power carrier self-organizing network of the power supply vehicle, and calculate the relative distance between the current power supply area and each nearby power supply vehicle network node group according to the geographical location of each nearby power supply vehicle network node group;

[0052] Calculate the relative distance and rated power comprehensive score of each nearby power supply vehicle network node group, sort the nearby power supply vehicle network node groups according to the relative distance and rated power comprehensive score, and obtain a scheduling list;

[0053] According to the required number of power supply vehicles, the corresponding power supply vehicle network node group in the scheduling list is selected in order to send a scheduling signal through the power supply vehicle's power carrier self-organizing network.

[0054] Furthermore, the calculation formula for the comprehensive score of relative distance and rated power is as follows:

[0055] ,

[0056] Among them, Q is the comprehensive score of relative distance and rated power, A is the relative distance, is the rated power of the power supply vehicle network node, is the weight coefficient.

[0057] Beneficial effects of the present invention:

[0058] First, the power supply vehicle can be connected to the public power grid through parallel connection, and the wired transmission channel can be obtained. The public power grid line can be used to communicate with the grid-connected power supply vehicle at a distance to form a power carrier self-organizing network of the power supply vehicle. Power lines are more stable than ground facilities and often have a widely distributed network, so using them for carrier communication can improve the communication reliability of the system.

[0059] The second is to predict the load of the current power supply area through big data models, better allocate and manage power supply vehicle resources, ensure that the power supply vehicle group can meet the demand without causing waste, and anticipate the situation of insufficient power supply vehicles in advance, and then dispatch power supply vehicles from other areas.

[0060] Third, based on the estimated number of power supply vehicles required, determine whether the number of power supply vehicles in the current power supply vehicle network node group is sufficient. If sufficient, calculate the load balancing power supply and adaptively implement the parallel operation or parallel operation and grid connection strategy. By using the genetic algorithm to iteratively select high-fitness node combinations for crossover, the optimal node parallel operation combination for resource utilization, load balancing, and power transmission can be found. Balanced power output can reduce voltage and frequency fluctuations, improve power quality, and optimize power transmission efficiency.

[0061] Fourth, by forming a power carrier self-organizing network of power supply vehicles through the public power grid, the power of power supply vehicles distributed in different geographical locations can be flexibly transmitted to the target area, which avoids physical aggregation and saves time and resources. The calculation of relative distance and rated power helps optimize the selection of power supply vehicles and improve the efficiency and response speed of resource allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0063] Figure 1 It is a flow chart of the method of embodiment 1.

[0064] Figure 2 It is a schematic diagram of the power carrier ad hoc network of the power supply vehicle of the first embodiment. DETAILED DESCRIPTION

[0065] To facilitate understanding by those skilled in the art, the structure of the present invention is now further described in detail with reference to the embodiments and the accompanying drawings. It should be understood that the steps mentioned in the present embodiment, unless otherwise specified in their order, can be adjusted in order according to actual needs, and can even be executed simultaneously or partially simultaneously.

[0066] Embodiment 1

[0067] like Figure 1 As shown, an embodiment of the present invention provides an adaptive power supply vehicle parallel connection method, including:

[0068] S1 defines each power supply vehicle as a power supply vehicle network node, several power supply vehicles are connected in parallel to form a power supply vehicle network node group, and several power supply vehicle network node groups are connected in parallel to form a power supply vehicle power carrier self-organizing network;

[0069] In this step, if Figure 2As shown, several power supply vehicles distributed in the same area can be connected in parallel to form a power supply vehicle network node group. The power supply vehicle parallel connection is to connect multiple power supply vehicles in series through cables to supply power to the outside. Therefore, these power supply vehicles can communicate with each other through power carriers through cables, and transmit parallel signals to each other to ensure synchronous operation between the power supply vehicles to achieve parallel connection. The parallel connection method of the power supply vehicle is a prior art and will not be described in detail in the present invention. In a major disaster environment, the power supply vehicles may not be able to be parked in a centralized manner due to the disaster environment and may be scattered in different areas. In particular, when multiple power supply vehicles are far apart, not only can the parallel signal transmission not be performed through conventional wireless communication methods, but also the parallel connection cannot be performed directly through cable series connection. Since the public power grid is distributed in various areas, although the public power grid cannot supply power, the public power grid has basic lines. Therefore, the power supply vehicle and the public power grid are connected to the grid to obtain a wired transmission channel. The lines of the public power grid can be used to communicate with the grid-connected power supply vehicle at a long distance to form a power carrier self-organizing network of the power supply vehicle. Power line communication (PLC) is a mature technology that uses existing power transmission lines for data transmission. It achieves remote data transmission by modulating high-frequency signals in power lines, which is very suitable for the transmission of synchronous control and status information. In the event of a major disaster, ground wireless communication facilities may be destroyed or unable to supply power. Power lines are more stable than ground facilities and often have a widely distributed network, so using them for carrier communication can improve the communication reliability of the system.

[0070] S101 assigns a unique identifier to each power vehicle network node, obtains the memory capacity, current load, and geographic location of the power vehicle controller, and each power vehicle network node broadcasts its own memory capacity, current load, and geographic location;

[0071] S102 calculates the priority parameter according to the memory capacity, current load, and geographical location, compares the priority parameter, selects the power supply vehicle network node with the largest priority as the main power supply vehicle network node, marks the corresponding identifier as the main power supply vehicle network node, and forms a power supply vehicle network node group;

[0072] In this step, since each power supply vehicle is actually connected in series and requires a main power supply vehicle network node to coordinate and manage other nodes in the network to ensure the effective allocation and use of resources, the main node centrally processes and forwards information, reducing the need for direct communication between nodes, thereby reducing the complexity and overhead of network communications. When rapid decision-making and response are required, the main node can make decisions quickly and direct other nodes to execute, thereby improving the response speed of the network.

[0073] Furthermore, the calculation steps of the priority parameter are as follows:

[0074] S1021 calculates the standardized memory capacity through the minimum and maximum memory capacities of all power vehicle network nodes. The calculation formula is as follows:

[0075] ,

[0076] in, To standardize memory capacity, is the memory capacity of the current power supply vehicle network node, is the minimum memory capacity of all power car nodes, It is the maximum value of memory capacity in all power car nodes;

[0077] S1022 calculates the standardized load through the minimum and maximum values ​​of the loads of all power supply vehicle network nodes. The calculation formula is as follows:

[0078] ,

[0079] in, For standardized load, is the current load, is the minimum value of the load in all power supply vehicle network nodes, is the maximum value of the load in all power supply vehicle network nodes;

[0080] S1023 defines the central location and calculates the standardized geographical location through the minimum and maximum distances from all power supply vehicle network nodes to the central location. The calculation formula is as follows:

[0081] ,

[0082] in, To standardize geographic location, For the current geographic location, is the minimum distance from all power car network nodes to the center, is the maximum distance from all power car network nodes to the center;

[0083] S1024 calculates the priority parameter based on the standardized memory capacity, standardized load capacity, and standardized geographic location. The calculation formula is as follows:

[0084] ,

[0085] in, is the priority parameter, is the memory capacity weight, Load weight, is the geographical location weight, To standardize memory capacity, For standardized load, Standardized geographic location.

[0086] In this step, memory capacity, load, and geographic location are selected as the core basis for calculating the priority parameters of the master node because they are crucial in determining the suitability and effectiveness of the node. Memory capacity is an important indicator of node processing power and storage capacity. Nodes with larger memory can better handle complex tasks, store more information, and bear more network management burdens. The front load reflects the real-time operating status of the node. Selecting nodes with lighter loads as master nodes can avoid further burdening nodes with excessive workloads, speed up response speed and improve reliability. Geographic location affects communication delay and data transmission speed in the network topology. Selecting nodes close to the center of the network as master nodes can reduce the length of the communication path, reduce delays, and improve overall communication efficiency. Using weights (α, β, γ) to combine these three standardized parameters for priority calculation allows the election mechanism to be flexibly adjusted according to actual needs.

[0087] S103 selects any power supply vehicle network node in the power supply vehicle network node group and connects to the grid to form a power carrier self-organizing network of the power supply vehicle.

[0088] S104 Each power supply vehicle network node monitors the status of the current main power supply vehicle network node by regularly sending heartbeat messages;

[0089] S105: If any main power supply vehicle network node fails to receive the heartbeat information fed back by the main power supply vehicle network node within the specified time, a re-election is started.

[0090] In this step, the heartbeat information is a simple and effective way for nodes to confirm each other's normal operation. By regularly sending and receiving heartbeat information, it is possible to quickly detect whether the main power supply vehicle network node is in normal working condition. Since the main power supply vehicle network node is the core of the power supply vehicle network node group, it is necessary to monitor and identify it. If an abnormality is found, a power supply vehicle network node without fault is re-selected as the main power supply vehicle network node to reduce the impact of the fault on the network.

[0091] S2 predicts the predicted load of the current power supply area through the prediction model, and estimates the number of power supply vehicles required based on the predicted load;

[0092] S201 collects historical load data and its corresponding temperature, weather, holiday information, and regional historical electricity consumption data to construct load training samples;

[0093] S202 constructs a prediction model through a neural network model, takes temperature, weather, holiday information, and regional historical electricity consumption data as inputs of the prediction model, and takes historical load data as outputs of the prediction model, and trains the prediction model;

[0094] S203 inputs the current temperature, weather, holiday information, and regional historical electricity consumption data into the prediction model to obtain the predicted load capacity of the current power supply area.

[0095] In this step, the load in the current power supply area is predicted through the big data model, so as to better allocate and manage the power supply vehicle resources, ensure that the power supply vehicle group can meet the demand without waste, and anticipate the situation that the power supply vehicle is insufficient in advance, so as to dispatch the power supply vehicle from other areas. Temperature: Temperature has a significant impact on power demand, especially in terms of air conditioning and heating demand. High temperatures usually lead to increased air conditioning use, while low temperatures increase heating demand. Weather conditions (such as sunny days, rainy days, storms, etc.) directly affect power use. For example, cloudy days have insufficient sunlight, and the demand for indoor and street lighting increases, resulting in increased electricity consumption. Holidays are usually accompanied by different electricity consumption patterns. For example, industrial electricity consumption may decrease during holidays, while household electricity consumption increases. Combining historical electricity consumption data in the area can help the prediction model understand and predict load changes more accurately.

[0096] S204 calculates the idle load of each power supply vehicle according to the rated power and current load of each power supply vehicle in the current power supply vehicle network node group. The calculation formula is as follows:

[0097] ,

[0098] in, For idle load, For rated power, For idle load, is the coefficient of rated power;

[0099] S205 calculates the average idle load of the power supply vehicles in the current power supply vehicle network node group, and estimates the number of power supply vehicles required in combination with the predicted load of the current power supply area.

[0100] In this step, The factor of rated power can be set to 0.8. Setting the rated power factor to 0.8 is usually a safety measure to ensure that the power supply vehicle does not continue to operate at maximum power during actual operation. This can reduce the risk of overheating or overloading of the equipment, thereby extending the life of the equipment and improving operational reliability. Since most of the loads of the power supply vehicles used in the same batch are at the same level, the use of the idle load average combined with the predicted load can quickly estimate the number of power supply vehicles required.

[0101] S3 determines whether the number of power supply vehicles in the current power supply vehicle network node group is greater than the required number of power supply vehicles. If so, load balancing power supply is performed; otherwise, the required number of power supply vehicles is calculated;

[0102] In this step, it is determined whether the number of power supply vehicles in the current power supply vehicle network node group is sufficient based on the estimated number of power supply vehicles required. If it is sufficient, the load balancing power supply calculation is performed, and the parallel operation or parallel operation and grid connection strategy is adaptively performed. In some power supply situations, it is not necessary for all power supply vehicles to be paralleled for power supply, and only a few of them are needed for parallel operation. However, the existing parallel operation mode of power supply vehicles is generally to start all power supply vehicles at the same time or to start a few power supply vehicles for parallel operation. Such a parallel operation combination mode will cause the load of each power supply vehicle to be unbalanced, and then cause some power supply vehicle equipment to bear too high a load, which may cause the equipment to fail or be damaged easily. Therefore, a load balancing strategy is needed to make the power supply vehicle parallel operation combination reach the optimal efficiency.

[0103] Specifically, the steps for load balancing power supply are as follows:

[0104] S301 randomly generates a number of initial power supply vehicle network node parallel combinations in the power supply vehicle network node group to form a population, each parallel combination being an individual;

[0105] S302 designs a fitness function according to the optimal target of rated power, current load, and geographical location, and calculates the fitness of each parallel combination through the fitness function;

[0106] Furthermore, the fitness function is:

[0107] ,

[0108] Among them, the S node parallel combination,

[0109] In this step, by maximizing the ratio of actual power used to total rated power, it is possible to ensure that the power supply vehicle operates within its optimal performance range, thereby improving resource utilization. Improving this ratio means that the power generation equipment is closer to efficient operation. Unbalanced loads may cause individual nodes to be overloaded and other nodes to be idle, which will increase the risk of system failure. Therefore, reducing the degree of load imbalance helps to maintain the stability of the overall system. Balanced load distribution can average the wear and heat load of equipment and extend the life of equipment. Geographical location has an important impact on the transmission route and energy loss of power supply. Choosing a combination with a lower geographical location cost can reduce power transmission losses. Nodes closer to the power supply point can respond to changes in load demand more quickly and provide more stable services. The actual power used by the power supply vehicle generator can be obtained in real time during operation or directly measured by power metering equipment. The total rated power is usually the design and specification parameters of the power supply vehicle generator, provided by the equipment manufacturer.

[0110] Furthermore, the degree of load imbalance can be calculated by the actual power usage. The calculation steps are as follows:

[0111] Calculate the average actual power used by all nodes, which is regarded as the desired balanced load level. The calculation formula is as follows:

[0112] ,

[0113] in, is the actual power used by the ith node, and N is the total number of nodes;

[0114] The standard deviation is calculated by averaging the actual power usage to evaluate the degree of load imbalance. The calculation formula is as follows:

[0115] .

[0116] In this step, the load distribution of each node can be analyzed to calculate, for example, using the standard deviation to measure the uniformity of the load of each node. A smaller standard deviation means that the load is evenly distributed among the nodes, while a larger standard deviation means that there is a significant imbalance. Smaller and larger standard deviations can be judged by setting a standard deviation threshold.

[0117] The location cost can be estimated by the path loss. P loss= × R Calculate, where I is the current, R is the line resistance (depending on line length and material), and the line length can be estimated by the geographical coordinates of each node and the coordinate position of the power supply area.

[0118] S303 selects a node parallel combination whose fitness is greater than a fitness threshold to perform a cross combination of a single node or multiple nodes to obtain a new node parallel combination;

[0119] S304 calculates the fitness of the new node parallel combination, selects the node parallel combination whose fitness is greater than the fitness threshold, and performs cross iteration until the fitness converges to the target value;

[0120] S305 selects the node parallel combination with the highest fitness, and sends a parallel signal to the corresponding power supply vehicle network node through the power supply vehicle network node group.

[0121] In this step, by using the genetic algorithm to iteratively select node combinations with high fitness for crossover, the optimal node parallel combination for resource utilization, load balancing, and power transmission can be found. Balanced power output can reduce voltage and frequency fluctuations, improve power quality, and optimize power transmission efficiency.

[0122] S4 remotely dispatches power supply vehicles to the grid and transmits electricity through the power supply vehicle's power carrier self-organizing network according to the shortfall in the number of power supply vehicles required.

[0123] S401 obtains the nearby power supply vehicle network node group through the power supply vehicle's power carrier self-organizing network, and calculates the relative distance between the current power supply area and each nearby power supply vehicle network node group according to the geographical location of each nearby power supply vehicle network node group;

[0124] S402 calculates the relative distance and rated power comprehensive score of each nearby power supply vehicle network node group, sorts the nearby power supply vehicle network node groups according to the relative distance and rated power comprehensive score, and obtains a scheduling list;

[0125] Furthermore, the calculation formula for the comprehensive score of relative distance and rated power is as follows:

[0126] ,

[0127] Among them, Q is the comprehensive score of relative distance and rated power, A is the relative distance, is the rated power of the power supply vehicle network node, is the weight coefficient.

[0128] S403 selects the corresponding power supply vehicle network node group in the scheduling list in order according to the required number of power supply vehicles and sends a scheduling signal through the power supply vehicle's power carrier self-organizing network.

[0129] In this step, the current parallel connection of several power supply vehicles often cannot meet the demand, and more power supply vehicles are needed to provide joint power output. The only way is to allocate power supply vehicles across regions to reach the power supply site, which requires a lot of manpower and material resources. Through the power carrier self-organizing network, power supply vehicles are remotely dispatched to connect to the grid to transmit electricity. There is no need for power supply vehicles to drive to the same area for parallel connection. Through the public power grid remote connection, the power of power supply vehicles distributed in different geographical locations can be flexibly transmitted to the target area, which avoids physical aggregation and saves time and resources. The calculation of relative distance and rated power helps optimize the selection of power supply vehicles, and improves the efficiency and response speed of resource allocation by maximizing the effectiveness of these parameters.

[0130] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0131] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0132] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0133] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0134] It should be noted that in the claims, any reference signs placed between brackets shall not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claim. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention may be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names.

[0135] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0136] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

[0137] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0138] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. 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 should not be understood as necessarily referring 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. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are contradictory.

Claims

1. An adaptive power supply vehicle parallel connection method, characterized in that: include: Each power supply vehicle is defined as a power supply vehicle network node. Several power supply vehicles are connected in parallel to form a power supply vehicle network node group. Several power supply vehicle network node groups are connected in parallel to form a power supply vehicle power carrier self-organizing network. Specifically: Assign a unique identifier to each power vehicle network node, obtain the memory capacity, current load, and geographic location of the power vehicle controller, and each power vehicle network node broadcasts its own memory capacity, current load, and geographic location; Calculate the priority parameters based on memory capacity, current load, and geographic location, compare the priority parameters, elect the power supply vehicle network node with the largest priority as the main power supply vehicle network node, mark the corresponding identifier as the main power supply vehicle network node, and form a power supply vehicle network node group. Specifically: The standardized memory capacity is calculated by the minimum and maximum memory capacities of all power vehicle network nodes. The calculation formula is as follows: , in, To standardize memory capacity, is the memory capacity of the current power supply vehicle network node, is the minimum memory capacity of all power car nodes, It is the maximum value of memory capacity in all power car nodes; The standardized load is calculated by the minimum and maximum values ​​of the loads of all power supply vehicle network nodes. The calculation formula is as follows: , in, For standardized load, is the current load, is the minimum value of the load in all power supply vehicle network nodes, is the maximum value of the load in all power supply vehicle network nodes; Define the central location, and calculate the standardized geographic location by the minimum and maximum distances from all power supply vehicle network nodes to the central location. The calculation formula is as follows: , in, To standardize geographic location, For the current geographic location, is the minimum distance from all power car network nodes to the center, is the maximum distance from all power car network nodes to the center; The priority parameter is calculated based on the standardized memory capacity, standardized load capacity, and standardized geographic location. The calculation formula is as follows: ， in, is the priority parameter, is the memory capacity weight, Load weight, is the geographical location weight, To standardize memory capacity, For standardized load, To standardize geographic location; Select any power supply vehicle network node in the power supply vehicle network node group and connect it to the grid to form a power carrier self-organizing network of the power supply vehicle; After forming the power supply vehicle network node group, execute: Each power supply vehicle network node monitors the status of the current main power supply vehicle network node by sending heartbeat messages regularly; If any of the main power supply vehicle network nodes does not receive the heartbeat information fed back by the main power supply vehicle network node within the specified time, a new election will be started; Predict the load in the current power supply area through the prediction model, and estimate the number of power supply vehicles required based on the predicted load; Determine whether the number of power supply vehicles in the current power supply vehicle network node group is greater than the required number of power supply vehicles. If so, load balancing power supply is performed. Otherwise, the required number of power supply vehicles is calculated. Specifically: In the power supply vehicle network node group, a number of initial power supply vehicle network node parallel combinations are randomly generated to form a population, and each parallel combination is an individual; Design a fitness function based on the optimal target of rated power, current load, and geographical location, and calculate the fitness of each parallel combination through the fitness function; Select the node parallel combination whose fitness is greater than the fitness threshold to perform a cross combination of a single node or multiple nodes to obtain a new node parallel combination; Calculate the fitness of the new node parallel combination, select the node parallel combination with a fitness greater than the fitness threshold for cross iteration, and stop when the fitness converges to the target value; Select the node parallel combination with the highest fitness, and send a parallel signal to the corresponding power supply vehicle network node through the power supply vehicle network node group; According to the shortage of power supply vehicles, the power supply vehicles are remotely dispatched to connect to the grid and transmit electricity through the power supply vehicle's power carrier self-organizing network. Specifically: Obtain the nearby power supply vehicle network node group through the power carrier self-organizing network of the power supply vehicle, and calculate the relative distance between the current power supply area and each nearby power supply vehicle network node group according to the geographical location of each nearby power supply vehicle network node group; Calculate the relative distance and rated power comprehensive score of each nearby power supply vehicle network node group, sort the nearby power supply vehicle network node groups according to the relative distance and rated power comprehensive score, and obtain a scheduling list; According to the required number of power supply vehicles, the corresponding power supply vehicle network node group in the scheduling list is selected in order and the scheduling signal is sent through the power supply vehicle's power carrier self-organizing network.

2. The adaptive power supply vehicle parallel connection method according to claim 1, characterized in that: The predicting load of the current power supply area by using the prediction model includes: Collect historical load data and its corresponding temperature, weather, holiday information, and regional historical electricity consumption data to build load training samples; The prediction model is constructed through the neural network model, and the temperature, weather, holiday information, and regional historical electricity consumption data are used as the input of the prediction model, and the historical load data is used as the output of the prediction model to train the prediction model; The current temperature, weather, holiday information, and regional historical electricity consumption data are input into the prediction model to obtain the predicted load capacity of the current power supply area.

3. The adaptive power supply vehicle parallel connection method according to claim 2, characterized in that: The estimation of the number of power supply vehicles required according to the predicted load includes: The idle load of each power supply vehicle is calculated based on the rated power and current load of each power supply vehicle in the current power supply vehicle network node group. The calculation formula is as follows: , in, For idle load, For rated power, is the current load, is the coefficient of rated power; Calculate the average idle load of the power supply vehicles in the current power supply vehicle network node group, and estimate the number of power supply vehicles required based on the predicted load of the current power supply area.

4. The adaptive power supply vehicle parallel connection method according to claim 1, characterized in that: The fitness function is: ， in, S Node parallel combination, are weight coefficients respectively.

5. The adaptive power supply vehicle parallel connection method according to claim 1, characterized in that: The calculation formula for the comprehensive score of relative distance and rated power is as follows: ， Among them, Q is the comprehensive score of relative distance and rated power, A is the relative distance, is the rated power of the power supply vehicle network node, is the weight coefficient.

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