Electric energy dispatching method and system based on railway mobile energy storage

Abstract

The present application discloses an electric energy dispatching method based on railway mobile energy storage, which relates to the field of rail transit power grid. The method comprises: obtaining energy change parameters of each node in the power grid, the energy change parameters including at least one of energy injection and energy output; determining the energy interaction parameters between the two adjacent nodes based on the respective energy change parameters of the two adjacent nodes to obtain the regional energy balance of the two adjacent nodes, wherein the larger the energy interaction parameter, the higher the regional energy balance; determining the regional frequency deviation of each node based on the energy injection and energy output of each node; and obtaining the starting and ending points of electric energy transportation in the power grid based on the regional energy balance and regional frequency deviation. This method can effectively improve the adaptability and stability of the power grid to the volatility of renewable energy generation and enhance the reliability of power supply.

Description

Technical Field

[0001] The present application relates to the field of rail transit power grids, and in particular to an electric energy dispatching method and system based on railway mobile energy storage. Background Art

[0002] With the rapid development of the global economy and continued population growth, electricity demand continues to rise. Traditional energy sources face the dual challenges of resource shortages and environmental pollution. Renewable energy (such as solar and wind power) has become a key focus of energy transformation due to its cleanliness and reproducibility. However, renewable energy generation is intermittent and uncertain, and its output power is significantly affected by natural conditions. For example, solar power generation depends on sunlight intensity, while wind power generation is affected by wind speed. This volatility leads to unstable grid frequency and voltage, increasing the complexity and difficulty of grid scheduling.

[0003] Grid dispatch primarily relies on relatively stable power sources such as fossil fuel generation and large-scale hydropower, balancing supply and demand by adjusting the output power of generators. However, this approach is slow to respond to rapid fluctuations in renewable energy generation and struggles to achieve precise power regulation. Furthermore, while the widespread use of distributed generation and energy storage systems has improved energy efficiency and power supply reliability to a certain extent, it has also complicated the grid's topology and power flow, increasing the difficulty of dispatch.

[0004] Stable grid operation requires a real-time balance between the generation and load sides. Random load fluctuations and the uncertainty of renewable energy generation pose significant challenges to grid frequency control and power quality assurance. Existing grid dispatching systems often rely on short-term load forecasting and generation plan adjustments to address these complex issues. However, these forecasts have limited accuracy and are difficult to adapt to rapidly changing grid conditions. Summary of the Invention

[0005] In order to address the deficiencies of the prior art, the purpose of this application is to provide an electric energy dispatching method and system based on railway mobile energy storage, which can effectively improve the adaptability and stability of the power grid to the volatility of renewable energy power generation and enhance the reliability of power supply.

[0006] To achieve the above objectives, this application adopts the following technical solutions:

[0007] In a first aspect, the present application provides a method for dispatching electric energy based on railway mobile energy storage, the method comprising:

[0008] Obtain energy change parameters of each node in the power grid, where the energy change parameters include at least one of energy injection and energy output; determine an energy interaction parameter between the two adjacent nodes based on the respective energy change parameters of the two adjacent nodes to obtain a regional energy balance of the two adjacent nodes, wherein a larger energy interaction parameter indicates a higher regional energy balance; determine a regional frequency deviation of each node based on the energy injection and energy output of each node; obtain the starting and ending points of electric energy transportation in the power grid based on the regional energy balance and the regional frequency deviation, wherein the starting and ending points include a starting node and an ending node of the electric energy transportation; and control a train to transport electric energy from the starting node to the ending node.

[0009] In one embodiment, based on the regional energy balance and the regional frequency deviation, the starting and ending points of electric energy transmission in the power grid are obtained, including:

[0010] Obtain the regional energy balance and regional frequency deviation of the first node; if the regional frequency deviation of the first node is greater than 0 and the regional energy balance of the first node is lower than the set balance threshold, determine the first node as the starting node; obtain the regional energy balance and regional frequency deviation of the second node; if the regional frequency deviation of the second node is less than 0 and the regional energy balance of the second node is higher than the balance threshold, determine the second node as the ending node.

[0011] In one embodiment, the energy exchange parameter includes an amount of electric energy transferred between a starting node and an ending node; before controlling the train to transfer the electric energy from the starting node to the ending node, the method further includes:

[0012] Determine the transmission distance between the starting node and the ending node and the train's electrical energy capacity; substitute the electrical energy transmission amount and transmission distance into the preset objective function to minimize the value of the objective function; obtain the decision variable that minimizes the objective function value, and determine whether the train transports the energy from the starting node to the ending node based on the decision variable. The objective function satisfies the following relationship:

[0013] ;

[0014] In the formula, min means the objective function takes the minimum value, represents the cost coefficient related to the transmission distance, Indicates the transmission distance, represents the decision variable, represents the cost of electric energy transmission per unit distance from the starting node to the ending node, Indicates the electrical energy capacity, Represents the cost coefficient related to electrical energy capacity.

[0015] In one embodiment, the objective function satisfies the following constraints:

[0016] The node does not have its own transportation demand; the power transmission amount of the starting node is less than or equal to the energy injection amount of the node; the power transmission amount of the ending node is equal to the energy demand of the node; transportation is only allowed from the starting node to the ending node; the power capacity of the train is associated with the transmission distance, and the power transmission amount does not exceed the power capacity.

[0017] In one embodiment, obtaining energy change parameters of each node in the power grid includes:

[0018] If the uncertainty of the energy output per unit time of the power generation system connected to the node satisfies the normal distribution, the uncertainty parameters of the power output of the power generation system under different operating conditions are determined based on a preset first probability function; the output power of the power generation system under different operating conditions and the starting time of the power output in each operating condition are obtained; and the energy injection amount of the power generation system per unit time is obtained based on the power output uncertainty parameters, the output power under different operating conditions and the starting time of the power output in each operating condition.

[0019] In one embodiment, obtaining energy change parameters of each node in the power grid includes:

[0020] If the uncertainty of the energy demand of the load connected to the node per unit time satisfies the normal distribution, the power demand uncertainty parameter of the load is determined based on the preset second probability function; based on the power demand uncertainty parameter and the preset power demand function, the total load demand of the load per unit time is obtained; based on the total load demand, the energy output of the node is determined.

[0021] In one embodiment, obtaining energy change parameters of each node in the power grid includes:

[0022] If the state of charge deviation of the energy storage device connected to the node satisfies a normal distribution per unit time, the state of charge uncertainty parameter of the energy storage device is determined based on a preset third probability function; the charge and discharge variables and charge and discharge power of the energy storage device per unit time are obtained; and the state of charge of the energy storage device per unit time is determined based on the charge and discharge variables, charge and discharge power, and the state of charge uncertainty parameter. The state of charge satisfies the following relationship:

[0023] ;

[0024] Where, Indicates the state of charge, represents the energy dissipation coefficient, represents the state of charge uncertainty parameter, represents the charge and discharge variables, represents the energy conversion efficiency, Indicates the charge and discharge power.

[0025] In one embodiment, determining the energy interaction parameter between the two adjacent nodes based on the energy change parameters of the two adjacent nodes to obtain the regional energy balance of the two adjacent nodes includes:

[0026] Obtaining a first energy change parameter of the first node and a second energy change parameter of the second node;

[0027] Based on the first energy change parameter, the second energy change parameter, and the energy interaction parameter between the first node and the second node, the regional energy balance between the first node and the second node is obtained, wherein the energy interaction parameter represents the energy value injected or consumed by the first node, or the energy value injected or consumed by the second node. The regional energy balance satisfies the following relationship:

[0028] ;

[0029] Where, represents the regional energy balance, represents the first energy change parameter, represents the second energy change parameter, represents the energy interaction parameter.

[0030] In one embodiment, determining the regional frequency deviation of each node based on the energy injection amount and energy output amount of each node includes:

[0031] Based on the regional control deviation method, it is determined whether the energy injection and energy output within the node meet the set balance standard, where the regional frequency deviation satisfies the following relationship:

[0032] ;

[0033] Where, Indicates the regional frequency deviation, represents the sum of the actual power of all nodes in the power grid, Represents the sum of the electric energy transactions between the node and other nodes outside the node, represents the frequency response coefficient of the node, represents the actual frequency of the node, represents the rated frequency of the node, Indicates the nominal value of the node's frequency deviation.

[0034] In a second aspect, the present application also provides an electric energy dispatching system based on railway mobile energy storage, the system comprising:

[0035] a data acquisition unit, configured to acquire energy change parameters of each node in the power grid, the energy change parameters including at least one of energy injection amount and energy output amount;

[0036] A calculation unit is configured to determine an energy interaction parameter between two adjacent nodes based on respective energy change parameters of the two adjacent nodes, so as to obtain a regional energy balance degree between the two adjacent nodes, wherein a larger energy interaction parameter indicates a higher regional energy balance degree; determine a regional frequency deviation degree of each node based on energy injection and energy output of each node; and obtain a starting and ending point of electric energy transport in the power grid based on the regional energy balance degree and the regional frequency deviation degree, wherein the starting and ending points include a starting node and an ending node of the electric energy transport;

[0037] The execution unit is used to control the train to transport the electric energy from the starting node to the ending node.

[0038] The aforementioned railway mobile energy storage-based power dispatch method obtains energy variation parameters (including energy injection and output) at each node in the power grid. Using these parameters, it determines the energy interaction parameters between adjacent nodes, thereby calculating the regional energy balance. A larger energy interaction parameter indicates more frequent energy flow between adjacent nodes and a higher regional energy balance. By monitoring and analyzing energy injection and output data in real time, this method accurately assesses the grid's energy balance and optimizes energy distribution. Furthermore, by analyzing the energy injection and output of each node, it determines the regional frequency deviation, which reflects the grid's frequency stability and power balance. This technical feature effectively assesses grid frequency stability by monitoring the grid frequency in real time and combining energy injection and output data, thereby improving grid operational stability. Based on the regional energy balance and frequency deviation, areas of power surplus and shortage can be precisely located, the starting and ending points of power transportation can be determined, and trains can be controlled to transport power from the starting node to the ending node. By optimizing the way of electricity allocation, the utilization efficiency of railway mobile energy storage systems can be improved, the reliability and flexibility of the power grid can be enhanced, the cost of electricity transmission can be reduced, and ultimately the optimal allocation of energy can be achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 Flowchart of a method for dispatching electric energy based on railway mobile energy storage in one embodiment;

[0040] Figure 2 A vehicle-network collaborative operation framework in one embodiment;

[0041] Figure 3 A flowchart of obtaining the starting and ending points of electric energy transportation in a power grid based on regional energy balance and regional frequency deviation in one embodiment;

[0042] Figure 4 A flowchart of determining whether a train transports energy from a starting node to an ending node based on a decision variable in one embodiment;

[0043] Figure 5 This is a flow chart for obtaining energy change parameters of each node in the power grid in the first embodiment;

[0044] Figure 6 This is a flow chart for obtaining energy change parameters of each node in the power grid in the second embodiment;

[0045] Figure 7 This is a flow chart of obtaining energy change parameters of each node in the power grid in the third embodiment;

[0046] Figure 8 A flowchart of obtaining the regional energy balance degree of two adjacent nodes in one embodiment;

[0047] Figure 9 Schematic diagram of an electric energy dispatching system based on railway mobile energy storage in one embodiment. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solutions and advantages of this application more clear, the present application is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application. Unless otherwise defined, the technical terms or scientific terms involved in this application should have the general meaning understood by people with ordinary skills in the technical field to which this application belongs.

[0049] In this document, relational terms such as first and second, etc., are used solely to distinguish one entity or operation from another entity or operation and do not necessarily require or imply any actual relationship or order between these entities or operations. Furthermore, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed or that are inherent to such process, method, article, or apparatus.

[0050] In one embodiment, Figure 1 As shown, a method for dispatching electric energy based on railway mobile energy storage is provided, the method comprising:

[0051] Step 101: Acquire energy variation parameters of each node in the power grid, where the energy variation parameters include at least one of energy injection amount and energy output amount;

[0052] Energy change parameters include at least one of energy injection and energy output. Energy injection refers to the total amount of energy input from external power sources (such as power stations and distributed energy resources) to a grid node within a specific time period, reflecting the node's power supply capacity and the external energy supply to the grid. Energy output represents the total amount of energy transmitted or provided from a grid node to users and loads, reflecting the node's load demand and the grid's power supply status.

[0053] Step 102: Determine an energy interaction parameter between the two adjacent nodes based on the energy change parameters of the two adjacent nodes to obtain a regional energy balance degree between the two adjacent nodes. The larger the energy interaction parameter, the higher the regional energy balance degree.

[0054] It's important to note that each node in the power grid is effectively managed through regional divisions. Each region contains multiple nodes and must include at least one traction substation. Traction substations are the critical link in energy transmission between the railway and the power grid, responsible for converting the grid's high-voltage alternating current into a form suitable for use by trains and supporting bidirectional transmission of electrical energy. Regenerative energy generated during train braking can be fed back into the grid through the traction substation, enabling energy recycling.

[0055] Traction substations ensure a balanced supply and demand of electricity within each area. They provide electricity to trains and transfer excess power to the grid, optimizing energy distribution. Furthermore, they regulate the amount of energy transmitted, distributing it appropriately based on train demand and grid conditions, ensuring stable operation of both the railway and the grid.

[0056] In the coordinated operation of the power grid and railway system, regional divisions are centered around traction substations to ensure the rational allocation of power within the region. Nodes within the region (such as starting and ending nodes) are connected to the power grid through traction substations, enabling efficient transmission and optimized allocation of power.

[0057] The regional energy balance can reflect the energy supply and demand balance between two adjacent nodes and can be evaluated by comparing the energy injection and energy output of the two nodes.

[0058] Exemplarily, when calculating the regional energy balance, the energy change parameters of each of the two adjacent nodes are determined, which can be the energy injection or output. Further, the energy difference between the two adjacent nodes and the product of the sum of their energy interactions with other nodes are calculated. These values are added together to obtain a comprehensive index, which is used as the numerator. Further, the denominator is calculated, including the adjustment factor of the energy difference between the nodes and the smaller value of the sum of the energy interactions of each node with other nodes. Finally, the numerator is divided by the denominator to obtain the regional energy balance. The greater the regional energy balance, the more balanced the energy distribution between the two adjacent nodes.

[0059] Step 103: Determine the regional frequency deviation of each node based on the energy injection amount and energy output amount of each node;

[0060] Regional frequency deviation reflects the deviation between the actual grid frequency and the rated frequency. To determine the regional frequency deviation of each node, it is necessary to monitor and record the energy input and output of each node.

[0061] By analyzing the energy injection and output at each node, we can understand the grid's supply and demand balance in real time. For example, when energy injection exceeds output, the grid frequency may increase; conversely, when energy injection is less than output, the grid frequency may decrease.

[0062] For example, when calculating regional frequency deviation, the difference between the total actual power and the total planned power must be considered: that is, the sum of the actual power of all nodes in the grid minus the sum of the planned power. Furthermore, the difference in energy transactions must be considered: that is, the difference between the total energy transactions between a node and other external nodes and the total planned transactions. Furthermore, the impact of frequency response must be considered: the deviation between the actual frequency and the rated frequency multiplied by the frequency response coefficient. Ultimately, these factors are combined to calculate the regional frequency deviation. This metric is used to measure grid frequency stability and power balance.

[0063] It should be noted that in different scenarios, specific adjustment factors may be incorporated into the calculation of regional frequency deviation based on actual conditions. For example, in areas with a high concentration of distributed energy resources, the impact of distributed energy volatility on frequency may be considered; in scenarios where energy storage systems participate in frequency regulation, the response speed and capacity of the energy storage system may be factored in. The adjustment factor can be calibrated and adjusted based on historical data, real-time monitoring data, and grid models to more accurately reflect the actual operating status of the grid and improve the accuracy of dispatch decisions.

[0064] Step 104: Based on the regional energy balance and the regional frequency deviation, the starting and ending points of the electric energy transmission in the power grid are obtained, wherein the starting and ending points include the starting node and the ending node of the electric energy transmission;

[0065] In power grid dispatching and management, a comprehensive analysis of regional energy balance and regional frequency deviation allows for precise determination of the starting and ending points of power transmission—that is, the clearest possible starting and ending nodes. Regional energy balance reflects the intensity and balance of energy interactions between adjacent nodes. A larger energy interaction parameter indicates more frequent and balanced energy flow between the two nodes, and the higher the regional energy balance. Regional frequency deviation reflects the stability of the grid's frequency and power balance, and together with regional energy balance, it influences the grid's operational status. When one region's regional energy balance indicates an energy surplus and its regional frequency deviation indicates a high frequency, while another region exhibits an energy shortage and a low frequency, the starting node of power transmission should be in the energy-surplus region, and the ending node should be in the energy-deficient region. Based on these two indicators, the grid dispatching center can scientifically and rationally plan power transmission routes, optimize energy allocation, and ensure stable grid operation.

[0066] Step 105: Control the train to transport the electric energy from the starting node to the ending node.

[0067] like Figure 2 As shown in the figure, after the central controller determines the starting and ending nodes, it issues transport instructions to the train. Upon receiving the instructions, the train uses its onboard energy storage device to obtain power from the traction substation at the starting node. During operation, the train recovers and stores energy through regenerative braking and other energy storage devices. The train can also directly draw power from the traction substation at the starting node for charging. The train transports the stored energy to the ending node according to the predetermined route and schedule. At the ending node, the train releases the energy into the power grid through the traction substation to meet the power needs of the area. Throughout this process, the train's operation is monitored and adjusted in real time by the central dispatching system to ensure efficient, safe, and timely energy transportation.

[0068] It should be noted that if Figure 2 As shown in the figure, the system architecture of the vehicle-grid collaborative operation framework is presented. Among them, photovoltaic power generation equipment and wind power generation equipment convert solar energy and wind energy into electrical energy through solar panels and wind turbines respectively, so that they can meet the grid connection requirements. The power grid, as the backbone network for power transmission, transmits electricity from power stations to various load centers, represented by high-voltage transmission line icons. Distributed energy storage equipment is used to charge when the grid load is low and discharge when the load is high, balancing the supply and demand of the grid. The main power transmission lines in the AC bus grid connect different power generation sources and energy storage devices. The central control layer can monitor the power data of the power generation source and energy storage equipment in real time, determine the starting and ending nodes of the power transportation after analysis and calculation, and generate dispatching instructions to coordinate train operations. Among them, such as Figure 2As shown, the energy transmission between different power generation sources and energy storage devices and the central control layer is represented by solid lines, and the information transmission between different power generation sources (such as photovoltaic power generation equipment and wind power generation equipment), power grids, distributed energy storage devices and the central control layer is represented by dotted lines. The traction substation includes a traction transformer, an energy feedback device, a ground energy storage device and a converter. The traction transformer can convert the high voltage of the power grid into a voltage suitable for use by railway trains. The energy feedback device can feed back electrical energy to the power grid when the train brakes. The ground energy storage device can store electrical energy when there is excess electrical energy transmitted by the train to the traction substation, and release electrical energy when there is a shortage of electrical energy in the power grid. The converter can adjust the quality and frequency of electrical energy to ensure a stable supply of electrical energy. The upline and downline are the two directions of the railway track. The upline refers to the track on which the train travels from the starting station to the terminal station, and the downline refers to the track on which the train returns from the terminal station to the starting station. In Figure 2 In the diagram, the upline and downline show the direction of the train's movement. The on-board energy storage device can store and release electrical energy while the train is running, supporting two-way transmission of electrical energy.

[0069] like Figure 2 As shown, taking one traction substation and a train as an example, the central control layer can supply power to the train's onboard energy storage device, obtain the train's operating status, and adjust the energy supply to the train based on the train's operating status. The central control layer can also supply power to the traction substation's energy feedback device, obtain the substation's operating status and energy storage status, and adjust the energy supply to the traction substation based on these two statuses. The onboard energy storage device can feed excess electricity back to the energy feedback device.

[0070] In this embodiment, the method obtains energy variation parameters (including energy injection and output) for each node in the power grid and uses these parameters to determine energy interaction parameters between adjacent nodes, thereby calculating the regional energy balance. A larger energy interaction parameter indicates more frequent energy flow between adjacent nodes and a higher regional energy balance. This technical feature enables accurate assessment of the power grid's energy balance through real-time monitoring and analysis of energy injection and output data, thereby optimizing the grid's energy distribution. Furthermore, by analyzing the energy injection and output of each node, the regional frequency deviation is determined, which reflects the grid's frequency stability and power balance. This technical feature enables effective assessment of grid frequency stability through real-time monitoring of the grid frequency and integration of energy injection and output data, thereby improving the grid's operational stability. Based on the regional energy balance and frequency deviation, areas of power surplus and shortage can be precisely located, the starting and ending points of power transportation can be determined, and trains can be controlled to transport power from the starting node to the ending node. This technical feature can improve the utilization efficiency of railway mobile energy storage systems by optimizing the allocation of electricity, enhance the reliability and resilience of the power grid, reduce the cost of electricity transmission, and ultimately achieve optimal energy allocation.

[0071] In one embodiment, Figure 3 As shown, based on the regional energy balance and regional frequency deviation, the starting and ending points of power transmission in the power grid are obtained, including the following steps:

[0072] Step 301: Obtain the regional energy balance and regional frequency deviation of the first node;

[0073] To obtain the regional energy balance and regional frequency deviation of the first node, it is necessary to collect data on the energy injection and energy output of the first node. The regional energy balance can be determined by comparing the difference in energy injection and output between two adjacent nodes. Using the method described in step 102 above, the regional energy balance of the first node can be calculated. Similarly, the regional frequency deviation of the first node can be calculated using the method described in step 103 above.

[0074] Step 302: If the regional frequency deviation of the first node is greater than 0, and the regional energy balance of the first node is lower than a set balance threshold, the first node is determined to be the starting node;

[0075] When the regional frequency deviation of the first node is greater than 0, it indicates that the actual frequency of the first node is higher than the rated frequency, indicating that power generation exceeds local demand and the grid frequency is rising. At the same time, if the regional energy balance falls below the set balance threshold, it indicates that the energy flow between the first node and adjacent nodes is unbalanced, resulting in excess energy. In this case, the first node can be designated as the starting node, indicating that it is the starting point for power transmission. Excess power can be transmitted to other nodes in need, helping to restore the grid frequency to the rated value and enhancing grid stability and reliability.

[0076] Step 303: Obtain the regional energy balance and regional frequency deviation of the second node;

[0077] Similarly, to obtain the regional energy balance and regional frequency deviation of the second node, it is necessary to collect data on the energy injection and energy output of the second node. The regional energy balance can be determined by comparing the difference in energy injection and output between two adjacent nodes. Using the method described in step 102 above, the regional energy balance of the second node can be calculated. Similarly, the regional frequency deviation of the second node can be calculated using the method described in step 103 above.

[0078] Step 304: If the regional frequency deviation of the second node is less than 0, and the regional energy balance of the second node is higher than the balance threshold, the second node is determined to be an end node.

[0079] When the regional frequency deviation of the second node is less than 0, it indicates that the actual frequency of the second node is lower than the rated frequency, which means that the power generation of the second node is insufficient to meet the local electricity demand, resulting in a decrease in the grid frequency. At the same time, if the regional energy balance of the second node is higher than the set balance threshold, it means that the energy flow between the second node and other adjacent nodes is relatively balanced, but there is still an energy shortage. In this case, the second node is determined to be the end node, indicating that the second node can serve as the destination of power transportation and receive excess power from other nodes to balance the supply and demand of the grid and stabilize the frequency.

[0080] In this embodiment, when the regional frequency deviation of the first node is greater than 0 and the regional energy balance is lower than the set balance threshold, it is determined to be the starting node; when the regional frequency deviation of the second node is less than 0 and the regional energy balance is higher than the set balance threshold, it is determined to be the ending node. This method can accurately locate areas of power surplus and shortage, achieve efficient power allocation, reduce energy waste, and enhance the stability and reliability of the power grid.

[0081] In one embodiment, Figure 4As shown, the energy interaction parameter includes the amount of electric energy transmitted between the starting node and the ending node; before controlling the train to transport the electric energy from the starting node to the ending node, the method further includes the following steps:

[0082] Step 401: Determine the transmission distance between the starting node and the ending node and the power capacity of the train;

[0083] Determining the transmission distance between the starting and ending nodes and the train's electrical energy capacity is a key step in achieving efficient electrical energy transportation. The transmission distance, which can be determined using a geographic information system (GIS) or a railway track database, can affect train operating time and energy consumption.

[0084] It should be noted that the train's electrical energy capacity is determined by the specifications of its energy storage equipment, which determines the maximum amount of energy it can transport in a single trip. The train can also recover braking energy during transport, increasing the effective amount of electrical energy transported.

[0085] Step 402: Substitute the power transmission amount and transmission distance into a preset objective function to minimize the value of the objective function;

[0086] Substituting the power transmission amount and transmission distance into the preset objective function to minimize the value of the objective function means that in power transportation scheduling, an objective function including variables such as power transmission amount and transmission distance is established, and the appropriate transportation path and transportation amount are selected through the optimization algorithm to minimize the objective function.

[0087] For example, the objective function can be expressed as transportation cost, where the transportation cost is proportional to the amount of energy transmitted and the distance transmitted, with proportional coefficients being the transportation cost per unit of energy and the transportation cost per unit of distance, respectively. By substituting the actual amount of energy transmitted and the distance, the minimum cost path required to transport the energy can be determined.

[0088] Step 403: Obtain the decision variable that minimizes the objective function. Determine whether the train transports the energy of the starting node to the ending node based on the decision variable. The objective function satisfies the following relationship:

[0089] ;

[0090] In the formula, min means the objective function takes the minimum value, represents the cost coefficient related to the transmission distance, Indicates the transmission distance, represents the decision variable, represents the cost of electricity transmission per unit distance from the starting node to the ending node, Indicates the electrical energy capacity, Represents the cost coefficient related to electrical energy capacity.

[0091] For example, assume there are three nodes (A, B, C) and two trains (K1, K2). The transmission distances between the nodes are D AB =100 km, D AC =150 km, D BC = 50 km. The cost of power transmission per unit distance is c AB =0.1 yuan / km·kWh, c AC = 0.15 yuan / km·kWh, c BC = 0.08 yuan / km·kWh. The electric energy capacity of trains K1 and K2 is 500kWh and 300kWh respectively. The cost coefficient is set as w 1=0.5 and w 2=0.8.

[0092] Substitute the above data into the objective function and calculate it through the optimization algorithm. Assuming that the optimal solution is Z ABK1 =1 (train K1 from A to B), Z ABK2 =1 (train K2 goes from B to C), and the other decision variables are 0. The objective function value is:

[0093] min=0.5×(100×1+50×1)+0.8×(0.1×500×1+0.08×300×1)=25+22.4=47.4 yuan.

[0094] The objective function can be expressed as achieving the optimization of electric energy transportation at the minimum cost while meeting the grid demand.

[0095] In one embodiment, the objective function satisfies the following constraints: the node does not have its own transportation demand; the amount of power transmitted from the starting node is less than or equal to the energy injection amount of the node; the amount of power transmitted from the ending node is equal to the energy demand of the node; only transportation from the starting node to the ending node is allowed; the power capacity of the train is associated with the transmission distance, and the power transmission amount does not exceed the power capacity.

[0096] Specifically, a node does not have its own transportation demand, that is, the starting node and the ending node of the power transportation must be different nodes, and the node is not allowed to transport power to itself. The node does not have its own transportation demand can be expressed by the following formula: ijk =0, if i=j. x ijk The decision variable is represented as the electric energy capacity that train k transports from substation i to substation j.

[0097] The amount of energy transmitted by the starting node cannot exceed its energy injection amount, ensuring that the energy output by the starting node does not exceed the energy it obtains from the external power supply, thus avoiding insufficient energy at the starting node. s ∈ S The total quantity shipped out of is equal to its supply: .

[0098] The amount of energy transmitted to the end node must be equal to its energy demand to ensure that the energy transported to the end node is sufficient to meet the load demand of the node and maintain the supply and demand balance of the power grid. r ∈ R The total import quantity of is equal to the demand quantity: .

[0099] Only transportation from the starting node (power surplus area) to the end node (power shortage area) is allowed, and reverse transportation is not allowed to ensure the logic of energy flow. S To the end node R Transportation: .

[0100] The train's power capacity is constrained by the transmission distance. The amount of power transmitted cannot exceed the train's power capacity. The impact of the transmission distance on power loss and transportation efficiency must also be considered to ensure the economy and feasibility of power transportation. The capacity is constrained by the path. The transport volume cannot exceed the train's capacity and is related to the path: .

[0101] In this embodiment, these constraints jointly ensure the rationality of electric energy transportation and the stable operation of the power grid. By meeting these conditions, the railway mobile energy storage system can be effectively utilized to optimize the energy distribution of the power grid and enhance the reliability and resilience of the power grid.

[0102] In one embodiment, the economics of using train-based mobile energy storage as a distributed power source for grid dispatch must be compared with other energy transfer methods before each implementation. Because train-based mobile energy storage relies on existing railway lines for transportation, no additional line construction investment is required. The main variable costs include transportation and operation and maintenance costs, as well as the fixed costs of installing energy storage devices such as large-capacity batteries.

[0103] The comprehensive cost of the specific full-day life cycle is expressed as: .

[0104] in, The daily comprehensive cost of the train mobile energy storage system; and The construction cost and operation and maintenance cost of the energy storage system during the configuration period; Operation and maintenance costs of fluctuating power generation; The train mobile energy storage system can save the daily electricity purchase cost in the “peak discharge and valley storage” mode. Responsible for profiting from energy transmission for train mobile energy storage systems.

[0105] In one embodiment, Figure 5 As shown, obtaining the energy change parameters of each node in the power grid includes the following steps:

[0106] Step 501: If the uncertainty of the energy output per unit time of the power generation system connected to the node satisfies a normal distribution, determine the uncertainty parameters of the power output of the power generation system under different operating conditions based on a preset first probability function;

[0107] Step 502: Obtain the output power of the power generation system under different operating conditions, and the starting time of power output under each operating condition;

[0108] Step 503: Obtain the energy injection amount of the power generation system per unit time according to the power output uncertainty parameter, the output power under different working conditions, and the starting time of power output under each working condition.

[0109] Specifically, different operating conditions of power generation systems can be divided into wind power generation systems and photovoltaic power generation systems.

[0110] For example, taking a wind power generation system as an example, the energy output of the wind power generation system is expressed as:

[0111] ;

[0112] Where, is the energy output of the wind power generation system per unit time step; Output power to the wind power generation system; The conversion efficiency between wind energy and electrical energy; is the air density; is the swept area of the rotor blades; is the wind speed. The wind power output considering the uncertainty parameters can be expressed as:

[0113] ;

[0114] Where, It represents the energy injection per unit time of the wind power generation system considering uncertainty; The wind power output power when the wind speed in the wind farm is higher than the cut-in wind speed and lower than the rated wind speed; The wind power output power when the wind speed in the wind farm is higher than the rated wind speed and lower than the cut-out wind speed; and are the uncertainty parameters of wind power output under the above two conditions respectively; , , , They are the starting time when the wind speed in the wind farm is lower than the cut-in wind speed, the starting time when the wind speed is higher than the rated wind speed, the starting time when the wind speed is higher than the cut-in wind speed, and the starting time when the wind speed is higher than the cut-out wind speed.

[0115] Assuming that the uncertainty parameters of energy output per unit time of each wind farm in the integrated energy power system obey the normal distribution, the uncertainty parameters of wind power generation can be obtained: and The first probability function of:

[0116] ;

[0117] Where, and are the maximum uncertain parameter values of wind power generation under different wind speed conditions.

[0118] Taking the photovoltaic power generation system as an example, the power output characteristics of the photovoltaic power generation system are affected by multiple factors such as photoelectric conversion efficiency, irradiance distribution, and component thermodynamic parameters. Its energy output is expressed as:

[0119] ;

[0120] Where, is the energy output of the photovoltaic power generation system per unit time; Output power for photovoltaic power generation system; The conversion efficiency between solar energy and electrical energy; is the area of photovoltaic cells in the photovoltaic power station; is the solar radiation intensity; is the ambient temperature of the photovoltaic power station. The photovoltaic energy output considering uncertainty is expressed as:

[0121] ;

[0122] Where, It represents the energy injection amount per unit time of the photovoltaic power generation system considering the uncertainty parameters; The photovoltaic output power in the photovoltaic power station when the solar radiation intensity is higher than the minimum requirement and lower than the rated intensity; The photovoltaic output power in the photovoltaic power station when the solar radiation intensity is higher than the rated intensity; and Uncertainty of photovoltaic output power under the above two conditions respectively; , , , They are the starting time when the light irradiation intensity in the photovoltaic power station is lower than the minimum required intensity, the starting time when the irradiation intensity is higher than the rated intensity, the starting time when the irradiation intensity is higher than the minimum required intensity, and the ending time when the irradiation intensity is higher than the rated intensity.

[0123] Assuming that the uncertainty parameters of the energy output per unit time of each photovoltaic power station in the integrated energy power system obey the normal distribution, the uncertainty parameters of the photovoltaic power generation system can be obtained as and The first probability function of:

[0124] ;

[0125] Where, and are the maximum uncertain parameter values of photovoltaic power generation under different irradiation conditions.

[0126] In one embodiment, Figure 6 As shown, obtaining the energy change parameters of each node in the power grid includes the following steps:

[0127] Step 601: If the uncertainty of the energy demand per unit time of the load connected to the node satisfies the normal distribution, determine the power demand uncertainty parameter of the load based on a preset second probability function;

[0128] Step 602: Obtaining the total load demand per unit time based on the power demand uncertainty parameter and a preset power demand function;

[0129] Step 603: Determine the energy output of the node according to the total load demand.

[0130] In power system operation, random load fluctuations and the intermittent nature of renewable energy generation present similar regulatory challenges, both of which significantly impact the dispatch strategy of the integrated energy system. When actual power consumption deviates from the short-term or ultra-short-term load forecast curve, the power system needs to quickly activate the reserve capacity adjustment mechanism to dynamically optimize the output distribution of power generation units to ensure that the power supply and demand matching and frequency control indicators in different time dimensions meet the operating standards. The energy demand per unit time can be expressed as:

[0131] ;

[0132] Among them, the unit time meets , and It is expressed as the starting time and ending time of the i-th load in the corresponding power demand function, Expressed as the energy demand of the i-th load, Expressed as the power demand function of the i-th load per unit time, and They are respectively expressed as the minimum power and maximum power of the i-th load. The energy demand considering the uncertainty parameters of the load is expressed as:

[0133] ;

[0134] Where, Expressed as the total load demand taking into account the uncertainty of the parameters, Expressed as the total load power demand function considering uncertainty, Expressed as the total power demand uncertainty parameter. Similarly, assuming that the demand uncertainty of each load in the integrated energy power system per unit time follows a normal distribution, the load uncertainty parameter can be obtained The probability distribution function of :

[0135] ;

[0136] Where, It is expressed as the maximum uncertain parameter value of the total load in the integrated energy and power system.

[0137] In one embodiment, Figure 7 As shown, obtaining the energy change parameters of each node in the power grid includes the following steps:

[0138] Step 701: If the state of charge deviation of the energy storage device connected to the node within a unit time satisfies a normal distribution, determine a state of charge uncertainty parameter of the energy storage device based on a preset third probability function;

[0139] Step 702: Obtain the charge and discharge variables and charge and discharge power of the energy storage device per unit time;

[0140] Step 703: Determine the state of charge of the energy storage device per unit time based on the charge and discharge variables, charge and discharge power, and state of charge uncertainty parameter. The state of charge satisfies the following relationship:

[0141] ;

[0142] Where, Indicates the state of charge, represents the energy dissipation coefficient, represents the state of charge uncertainty parameter, represents the charge and discharge variables, represents the energy conversion efficiency, Indicates the charge and discharge power.

[0143] Specifically, considering the uncertainty parameters of the energy storage device during the charging and discharging process, the state of charge of the energy storage device per unit time can be obtained:

[0144] ;

[0145] Where, It is expressed as the state of charge of the energy storage device in the power system per unit time. Expressed as the energy dissipation coefficient, is expressed as the uncertainty of the state of charge, It represents the charge and discharge state variable of the energy storage device per unit time. When it is positive, it represents charging, and when it is negative, it represents discharging. represents the energy conversion efficiency, Represents the charge and discharge power. Assuming that the state of charge deviation of the energy storage device in unit time obeys the normal distribution, the uncertainty parameter of the energy storage state of charge can be obtained The third probability function of:

[0146] ;

[0147] Where, It is expressed as the maximum uncertain parameter value of the total load in the integrated energy and power system.

[0148] In one embodiment, the train is mainly affected by the combined effects of traction, braking and resistance during operation. The torque output by the traction motor is transmitted to the driving wheel through the gear reducer. Then, through the friction between the wheel and rail, the rail generates a tangential reaction force on the wheel, driving the train. The specific formula can be obtained from the following formula:

[0149] ;

[0150] in, Expressed as the traction motor output torque, It is expressed as the mechanical reduction ratio between the traction motor output shaft and the driving wheel. It is expressed as the mechanical transmission efficiency between the traction motor output shaft and the driving wheel. is the rolling circle diameter of the driving wheel. In actual calculations, the traction characteristic curve is often used to reflect the change of train traction with speed.

[0151] Braking force It is mainly divided into mechanical braking and electric braking. It is the longitudinal force exerted by the wheel tread on the rail surface, which can be expressed as:

[0152] ;

[0153] in, Expressed as the pressure per brake shoe, Expressed as the brake shoe friction coefficient, Expressed as the radius of the wheel rolling circle, Expressed as the moment of inertia of the wheelset, Expressed as the angular deceleration of the wheelset. In practical applications, the braking force can be calculated based on the known braking deceleration:

[0154] ;

[0155] in, Expressed as the train mass, It is expressed as the rotational mass coefficient converted from the wheelset rotation inertia, Expressed as the known braking deceleration, The braking force calculation often also takes into account the braking characteristic curve, which reflects how the train braking force changes with speed.

[0156] resistance Including basic resistance and additional resistance The basic resistance is composed of the friction resistance between the journal and the bearing, the rolling friction resistance between the wheel and the rail, the sliding friction resistance of the wheel on the rail, the impact and vibration resistance caused by track unevenness and wheel tread scratches, and air resistance. It is usually calculated using an empirical formula derived from a large number of experiments. The unit basic resistance is generally used. The calculation formula is:

[0157] ;

[0158] in Indicates the train speed. 、 、 are the Davis equation coefficients, which are determined experimentally and vary with vehicle type.

[0159] Unit additional resistance It is the resistance that the train encounters when running under specific conditions, including slope additional resistance, curve additional resistance and tunnel additional resistance. It is believed that the resistance encountered by the train during running is mainly determined by the running speed. and running distance Decide.

[0160] ;

[0161] in, It represents the additional resistance of the slope determined by the slope. It represents the additional resistance of the curve determined by the curve radius, It represents the additional resistance of the tunnel determined by the tunnel length. The total resistance of train operation is expressed as:

[0162] ; where g is the gravitational constant.

[0163] In one embodiment, the train will experience a change in operating mode when running between stations. Generally, the operation strategy of traction-cruise-coast-brake is more energy-efficient. When the train runs on a flat road without considering the slope factor, it is assumed that the net force acting on the train is , which changes over time.

[0164] Traction conditions: ;

[0165] Cruising condition: ;

[0166] Coasting condition: ;

[0167] Braking conditions: .

[0168] The electric power consumed or regenerated by the high-speed train is obtained from the electromechanical energy conversion relationship 、 The expression between and mechanical power is shown below. is the regenerative braking energy utilization coefficient, It is the conversion coefficient of mechanical energy into electrical energy in other working conditions except BR.

[0169] ;

[0170] Therefore, the energy demand of trains participating in demand response per unit time can be expressed as:

[0171] ;

[0172] In the formula, the unit time satisfies , and They represent the start and end times of the corresponding power demand function when train i does not participate in grid demand response, and They are respectively represented as the starting time and ending time of train i participating in the grid demand response in the corresponding power demand function, and satisfy Expressed as the energy demand of the i-th train, It is expressed as the power demand function when the i-th train cannot respond to demand and consumes electricity in unit time, It is expressed as the power demand function when the i-th train can respond to demand and perform regenerative braking energy feedback in unit time, and They represent the minimum and maximum power when train i cannot respond to grid dispatch, and They represent the minimum and maximum power that train i can respond to grid dispatch. Its energy demand can be expressed as:

[0173] ;

[0174] Where, Expressed as the total load demand of the train group considering uncertainty, Expressed as the total load power demand function of the train group, Expressed as the total load power response function of the train group, It is expressed as the total power demand uncertainty of the train group. Similarly, assuming that the demand uncertainty of the train group load in the integrated energy and power system in unit time follows a normal distribution, the load uncertainty parameter can be obtained The probability function of :

[0175] ;

[0176] Where, It is expressed as the maximum uncertainty value of the train group load in the integrated energy and power system.

[0177] In one embodiment, Figure 8 The method of determining the energy interaction parameter between the two adjacent nodes based on the respective energy change parameters of the two adjacent nodes to obtain the regional energy balance of the two adjacent nodes includes the following steps:

[0178] Step 801: Acquire a first energy change parameter of a first node and a second energy change parameter of a second node;

[0179] Energy change parameters include at least one of energy injection and energy output, reflecting the energy flow of a node per unit time. For the first node, energy injection may come from power generation equipment such as solar panels, wind turbines, or traditional power plants; energy output may be the electricity delivered by the node to the grid. For the second node, energy change parameters may involve both the electricity received from the grid and the electricity transmitted to users or other nodes. By monitoring and recording energy change parameters, the energy flow status of the grid can be monitored in real time, providing data support for grid scheduling and optimization.

[0180] For example, if the power generation equipment of the first node generates 1000 kWh of electricity in a certain period of time and transmits 800 kWh to the grid, then its energy injection amount is 1000 kWh and its energy output amount is 800 kWh.

[0181] Step 802: Based on the first energy change parameter, the second energy change parameter, and the energy interaction parameter between the first node and the second node, obtain the regional energy balance between the first node and the second node, wherein the energy interaction parameter represents the energy value injected or consumed by the first node, or the energy value injected or consumed by the second node, and the regional energy balance satisfies the following relationship:

[0182] ;

[0183] Where, represents the regional energy balance, represents the first energy change parameter, represents the second energy change parameter, represents the energy interaction parameter.

[0184] Assume that the state variable set of each partitioned network node is: ST = {Y1, Y2, …, YN}. The energy interaction parameter Yi represents the value of energy injection or consumption in each node, and N represents the total number of nodes. represents the regional energy balance, represents the first energy change parameter, represents the second energy change parameter, Represents the energy interaction parameter and defines the regional energy balance as:

[0185] ;

[0186] When the energy interaction between two adjacent first nodes m and second nodes n and node i is greater, the regional energy balance between the first node m and the second node n is greater. The higher the value, and the . At the same time, it is believed that , the energy interaction between the first node m and the second node n is weak, and the risk transfer is slow. , the energy interaction between the first node m and the second node n is stronger, the risk transfer is faster, and the priority is higher. Further, the balance matrix between each adjacent node can be obtained as:

[0187] .

[0188] In one embodiment, determining the regional frequency deviation of each node based on the energy injection amount and energy output amount of each node includes:

[0189] Based on the regional control deviation method, it is determined whether the energy injection and energy output within the node meet the set balance standard, where the regional frequency deviation satisfies the following relationship:

[0190] ;

[0191] Where, Indicates the regional frequency deviation, represents the sum of the actual power of all nodes in the power grid, Represents the sum of the electric energy transactions between the node and other nodes outside the node, represents the frequency response coefficient of the node, represents the actual frequency of the node, represents the rated frequency of the node, Indicates the nominal value of the node's frequency deviation.

[0192] Specifically, each power grid region has its own dedicated Automatic Generation Control (AGC) system. The grid's dispatch center sends real-time signals to the AGC units in each region. By integrating mobile energy storage on trains as a distributed power source into grid dispatch, the AGC system maintains frequency stability within a specified range and distributes power across regions, ensuring that inter-regional exchange rates remain within the specified range.

[0193] The degree of frequency deviation is related to the regulation coefficient of each system, the degree of load disturbance, and the load regulation effect. When a system disturbance occurs in a region, it affects the entire interconnected system. The Area Control Error (ACE) is generally used to judge whether the power generation and load in the control area are balanced. It refers to the deviation between the actual value and the standard value caused by the current power system due to factors such as load, power generation, and frequency. The regional frequency deviation is expressed as follows:

[0194] ;

[0195] in, Indicates the regional frequency deviation, represents the sum of the actual power of all nodes in the power grid, Represents the sum of the electric energy transactions between the node and other nodes outside the node, represents the frequency response coefficient of the node, represents the actual frequency of the node, represents the rated frequency of the node, Indicates the nominal value of the node's frequency deviation.

[0196] Based on the same concept, Figure 9 As shown, the present application also provides an electric energy dispatching system based on railway mobile energy storage, which includes:

[0197] The data acquisition unit 901 is configured to acquire energy variation parameters of each node in the power grid, where the energy variation parameters include at least one of energy injection amount and energy output amount;

[0198] Calculation unit 902 is configured to determine an energy interaction parameter between two adjacent nodes based on respective energy change parameters of the two adjacent nodes, thereby obtaining a regional energy balance between the two adjacent nodes, wherein a larger energy interaction parameter indicates a higher regional energy balance; determine a regional frequency deviation for each node based on energy injection and energy output of each node; and obtain a starting and ending point for electric energy transport in the power grid based on the regional energy balance and the regional frequency deviation, wherein the starting and ending points include the starting and ending nodes of the electric energy transport;

[0199] The execution unit 903 is used to control the train to transport the electric energy from the starting node to the ending node.

[0200] In one embodiment, the calculation unit 902 obtains the regional energy balance and regional frequency deviation of the first node; if the regional frequency deviation of the first node is greater than 0, and the regional energy balance of the first node is lower than the set balance threshold, the first node is determined to be the starting node; the regional energy balance and regional frequency deviation of the second node are obtained; if the regional frequency deviation of the second node is less than 0, and the regional energy balance of the second node is higher than the balance threshold, the second node is determined to be the ending node.

[0201] In one embodiment, the energy interaction parameter of the calculation unit 902 includes the amount of electric energy transmitted between the starting node and the ending node; before controlling the train to transport the electric energy from the starting node to the ending node, the method further includes: determining the transmission distance between the starting node and the ending node and the electric energy capacity of the train; substituting the electric energy transmission amount and the transmission distance into a preset objective function to minimize the value of the objective function; obtaining a decision variable that minimizes the value of the objective function, and determining whether the train transports the energy from the starting node to the ending node based on the decision variable, wherein the objective function satisfies the following relationship:

[0202] ;

[0203] In the formula, min means the objective function takes the minimum value, represents the cost coefficient related to the transmission distance, Indicates the transmission distance, represents the decision variable, represents the cost of electric energy transmission per unit distance from the starting node to the ending node, Indicates the electrical energy capacity, Represents the cost coefficient related to electrical energy capacity.

[0204] In one embodiment, the objective function of the computing unit 902 satisfies the following constraints: the node does not have its own transportation demand; the amount of electric energy transmitted from the starting node is less than or equal to the energy injection amount of the node; the amount of electric energy transmitted from the ending node is equal to the energy demand of the node; only transportation from the starting node to the ending node is allowed; the electric energy capacity of the train is associated with the transmission distance, and the electric energy transmission amount does not exceed the electric energy capacity.

[0205] In one embodiment, the data acquisition unit 901 acquires energy change parameters of each node in the power grid, specifically for: if the uncertainty of the energy output of the power generation system connected to the node per unit time satisfies the normal distribution, determining the uncertainty parameters of the power output of the power generation system under different operating conditions based on a preset first probability function; acquiring the output power of the power generation system under different operating conditions, and the starting time of the power output in each operating condition; and obtaining the energy injection amount of the power generation system per unit time based on the power output uncertainty parameters, the output power under different operating conditions, and the starting time of the power output in each operating condition.

[0206] In one embodiment, the data acquisition unit 901 obtains the energy change parameters of each node in the power grid, specifically for: if the uncertainty of the energy demand of the load connected to the node per unit time satisfies the normal distribution, determining the power demand uncertainty parameter of the load based on a preset second probability function; based on the power demand uncertainty parameter and the preset power demand function, obtaining the total load demand of the load per unit time; and determining the energy output of the node based on the total load demand.

[0207] In one embodiment, the data acquisition unit 901 acquires energy variation parameters of each node in the power grid, specifically for: if the state of charge deviation of the energy storage device connected to the node satisfies a normal distribution per unit time, determining the state of charge uncertainty parameter of the energy storage device based on a preset third probability function; acquiring the charge and discharge variables and charge and discharge power of the energy storage device per unit time; and determining the state of charge of the energy storage device per unit time based on the charge and discharge variables, charge and discharge power, and state of charge uncertainty parameter, where the state of charge satisfies the following relationship:

[0208] ;

[0209] Where, Indicates the state of charge, represents the energy dissipation coefficient, represents the state of charge uncertainty parameter, represents the charge and discharge variables, represents the energy conversion efficiency, Indicates the charge and discharge power.

[0210] In one embodiment, the calculation unit 902 determines the energy interaction parameter between the two adjacent nodes based on the energy change parameters of the two adjacent nodes to obtain the regional energy balance of the two adjacent nodes. Specifically, the calculation unit 902 is used to: obtain a first energy change parameter of the first node and a second energy change parameter of the second node; based on the first energy change parameter, the second energy change parameter, and the energy interaction parameter between the first node and the second node, obtain the regional energy balance between the first node and the second node, wherein the energy interaction parameter is characterized by the energy value injected or consumed by the first node, or the energy value injected or consumed by the second node, and the regional energy balance satisfies the following relationship:

[0211] ;

[0212] Where, represents the regional energy balance, represents the first energy change parameter, represents the second energy change parameter, represents the energy interaction parameter.

[0213] In one embodiment, the calculation unit 902 determines the regional frequency deviation of each node based on the energy injection amount and energy output amount of each node, specifically for determining whether the energy injection amount and energy output amount within the node meet the set balance standard based on the regional control deviation method, wherein the regional frequency deviation satisfies the following relationship:

[0214] ;

[0215] Where, Indicates the regional frequency deviation, represents the sum of the actual power of all nodes in the power grid, Represents the sum of the electric energy transactions between the node and other nodes outside the node, represents the frequency response coefficient of the node, represents the actual frequency of the node, represents the rated frequency of the node, Indicates the nominal value of the node's frequency deviation.

[0216] It should be understood that those skilled in the art can make improvements or changes based on the above description, and all such improvements and changes should fall within the scope of protection of the claims appended to this application.

Claims

1. A method for dispatching electric energy based on railway mobile energy storage, characterized in that: The method comprises: Acquiring energy change parameters of each node in the power grid, wherein the energy change parameters include at least one of energy injection amount and energy output amount; determining an energy interaction parameter between the two adjacent nodes according to the respective energy change parameters of the two adjacent nodes, so as to obtain a regional energy balance degree between the two adjacent nodes, wherein a larger energy interaction parameter indicates a higher regional energy balance degree; Determining the regional frequency deviation of each of the nodes according to the energy injection amount and the energy output amount of each of the nodes; Based on the regional energy balance and the regional frequency deviation, the starting and ending points of the electric energy transport in the power grid are obtained, wherein the starting and ending points include a start node and an end node of the electric energy transport. The process of determining the starting and ending points includes the following steps: Obtaining the regional energy balance and the regional frequency deviation of the first node; if the regional frequency deviation of the first node is greater than 0 and the regional energy balance of the first node is lower than a set balance threshold, determining the first node as the starting node; Obtaining the regional energy balance and the regional frequency deviation of the second node; if the regional frequency deviation of the second node is less than 0 and the regional energy balance of the second node is higher than the balance threshold, determining the second node as the end node; The train is controlled to transport the electric energy from the starting node to the ending node.

2. The method according to claim 1, characterized in that The energy interaction parameter includes the amount of electric energy transmitted between the starting node and the ending node; before the control train transports the electric energy from the starting node to the ending node, the method further includes: determining a transmission distance between the starting node and the ending node and an electrical energy capacity of the train; Substituting the electric energy transmission amount and the transmission distance into a preset objective function to minimize the value of the objective function; Obtain a decision variable that minimizes the value of the objective function, and determine whether the train transports the energy of the starting node to the ending node based on the decision variable, wherein the objective function satisfies the following relationship: ； In the formula, min means that the objective function takes the minimum value, represents the cost coefficient associated with the transmission distance, represents the transmission distance, represents the decision variable, represents the power transmission cost per unit distance from the starting node to the ending node, represents the electrical energy capacity, Represents the cost coefficient associated with the electrical energy capacity.

3. The method according to claim 2, characterized in that The objective function satisfies the following constraints: The node does not have its own transportation needs; The power transmission amount of the starting node is less than or equal to the energy injection amount of the node; The amount of electric energy transmitted to the end node is equal to the energy demand of the node; Only allow delivery from the starting node to the ending node; The electric energy capacity of the train is constrained by an association constraint with the transmission distance, and the amount of electric energy transmitted does not exceed the electric energy capacity.

4. The method according to claim 1, wherein The obtaining of energy change parameters of each node in the power grid includes: If the uncertainty of energy output per unit time of the power generation system connected to the node satisfies a normal distribution, determining uncertainty parameters of power output of the power generation system under different operating conditions based on a preset first probability function; Obtaining the output power of the power generation system under different operating conditions, as well as the starting time of power output under each operating condition; The energy injection amount of the power generation system per unit time is obtained according to the electric energy output uncertainty parameter, the output power under different working conditions and the starting time of the electric energy output in each working condition.

5. The method according to claim 1, wherein The obtaining of energy change parameters of each node in the power grid includes: If the uncertainty of the energy demand per unit time of the load connected to the node satisfies a normal distribution, determining a power demand uncertainty parameter of the load based on a preset second probability function; Obtaining a total load demand of the load per unit time based on the power demand uncertainty parameter and a preset power demand function; The energy output of the node is determined according to the total load demand.

6. The method according to claim 1, characterized in that The obtaining of energy change parameters of each node in the power grid includes: If the state of charge deviation of the energy storage device connected to the node within a unit time satisfies a normal distribution, determining a state of charge uncertainty parameter of the energy storage device based on a preset third probability function; Obtaining the charge and discharge variables and charge and discharge power of the energy storage device per unit time; The state of charge of the energy storage device per unit time is determined based on the charge and discharge variables, the charge and discharge power, and the state of charge uncertainty parameter, wherein the state of charge satisfies the following relationship: ； Where, represents the state of charge, represents the energy dissipation coefficient, represents the state of charge uncertainty parameter, represents the charge and discharge variables, represents the energy conversion efficiency, Indicates the charge and discharge power.

7. The method according to claim 1, characterized in that Determining the energy interaction parameter between the two adjacent nodes based on the respective energy change parameters of the two adjacent nodes to obtain the regional energy balance degree of the two adjacent nodes includes: Obtaining a first energy change parameter of the first node and a second energy change parameter of the second node; The regional energy balance between the first node and the second node is obtained based on the first energy change parameter, the second energy change parameter, and the energy interaction parameter between the first node and the second node, wherein the energy interaction parameter represents the energy value injected or consumed by the first node, or the energy value injected or consumed by the second node, and the regional energy balance satisfies the following relationship: ； Where, Indicates the energy balance of the region, represents the first energy change parameter, represents the second energy change parameter, represents the energy interaction parameter.

8. The method according to claim 1, characterized in that The determining, based on the energy injection amount and the energy output amount of each node, the regional frequency deviation of each node includes: Determine whether the energy injection amount and the energy output amount in the node meet a set balance standard based on a regional control deviation method, wherein the regional frequency deviation satisfies the following relationship: ； Where, represents the frequency deviation of the region, represents the sum of the actual powers of all the nodes in the power grid, represents the sum of the electric energy transactions between the node and other nodes other than the node, represents the frequency response coefficient of the node, represents the actual frequency of the node, represents the rated frequency of the node, Indicates the nominal value of the frequency deviation of the node.

9. An electric energy dispatching system based on railway mobile energy storage, characterized in that: The system comprises: a data acquisition unit, configured to acquire energy change parameters of each node in the power grid, wherein the energy change parameters include at least one of energy injection amount and energy output amount; a calculation unit, configured to determine an energy interaction parameter between two adjacent nodes based on the respective energy change parameters of the two adjacent nodes, so as to obtain a regional energy balance degree of the two adjacent nodes, wherein the larger the energy interaction parameter, the higher the regional energy balance degree; determine a regional frequency deviation degree of each node based on the energy injection amount and the energy output amount of each node; obtain a starting and ending point of electric energy transportation in the power grid based on the regional energy balance degree and the regional frequency deviation degree, wherein the starting and ending points include a starting node and an ending node of the electric energy transportation; the calculation unit is configured to obtain the regional energy balance degree and the regional frequency deviation degree of a first node; if the regional frequency deviation degree of the first node is greater than 0 and the regional energy balance degree of the first node is lower than a set balance degree threshold, then determine the first node as the starting node; the calculation unit is further configured to obtain the regional energy balance degree and the regional frequency deviation degree of a second node; if the regional frequency deviation degree of the second node is less than 0 and the regional energy balance degree of the second node is higher than the balance degree threshold, then determine the second node as the ending node; The execution unit is used to control the train to transport the electric energy from the starting node to the ending node.

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