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

Abstract

The invention discloses an electric energy dispatching method based on railway mobile energy storage, and relates to the field of rail transit power grids. The method comprises the following steps: acquiring an energy change parameter of each node in a power grid, wherein the energy change parameter comprises at least one of an energy injection amount and an energy output amount; according to the respective energy change parameters of the two adjacent nodes, energy interaction parameters between the two adjacent nodes are determined, so that the regional energy balance degree of the two adjacent nodes is obtained, and the larger the energy interaction parameters are, the higher the regional energy balance degree is; determining the regional frequency deviation degree of each node according to the energy injection amount and the energy output amount of each node; and based on the regional energy balance degree and the regional frequency deviation degree, obtaining starting and ending points of electric energy transportation in the power grid. The method can effectively improve the adaptability and stability of the power grid to renewable energy power generation volatility, and enhance the reliability of power supply.

Description

Technical Field

[0001] This application relates to the field of rail transit power grids, and particularly to a power scheduling method and system based on railway mobile energy storage. Background Art

[0002] With the rapid development of the global economy and the continuous growth of the population, the demand for electricity is constantly rising, and traditional energy sources are facing double challenges of resource shortage and environmental pollution. Renewable energy sources (such as solar energy and wind energy), due to their cleanliness and renewability, have become an important direction for energy transformation. Renewable energy power generation is intermittent and uncertain, and its output power is significantly affected by natural conditions. For example, solar power generation depends on sunlight intensity, and wind power generation is affected by wind speed. This volatility leads to instability of the grid frequency and voltage, increasing the complexity and difficulty of grid scheduling.

[0003] Grid scheduling mainly relies on relatively stable power sources such as fossil fuel power generation and large-scale hydropower generation, and balances supply and demand by adjusting the output power of generator sets. However, this method responds slowly when dealing with the rapid changes in renewable energy power generation and is difficult to achieve precise power regulation. In addition, the widespread application of distributed generation and energy storage systems, although improving energy utilization efficiency and power supply reliability to a certain extent, also makes the grid topology and power flow more complex, increasing the scheduling difficulty.

[0004] The stable operation of the grid requires real-time balance between the power generation side and the load side. The random fluctuations of the load and the uncertainty of renewable energy power generation pose great challenges to grid frequency control and power quality assurance. Existing grid scheduling systems often rely on short-term load forecasting and adjustment of power generation plans when dealing with these complex problems, but the forecasting accuracy is limited and it is difficult to adapt to the rapidly changing grid conditions. Summary of the Invention

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

[0006] To achieve the above purpose, this application adopts the following technical solutions: In the first aspect, this application provides a power scheduling method based on railway mobile energy storage, and this method includes: Obtain the energy change parameters of each node in the power grid, where the energy change parameters include at least one of the energy injection amount and the energy output amount; determine the energy interaction parameter between two adjacent nodes according to the respective energy change parameters of the two adjacent nodes, so as to obtain the regional energy balance degree between the two adjacent nodes. Among them, the larger the energy interaction parameter, the higher the regional energy balance degree; determine the regional frequency deviation degree of each node according to the energy injection amount and the energy output amount of each node; based on the regional energy balance degree and the regional frequency deviation degree, obtain the starting and ending points of the electric energy transportation in the power grid, where the starting and ending points include the starting node and the ending node of the electric energy transportation; control the train to transport the electric energy of the starting node to the ending node.

[0007] In one embodiment, obtaining the starting and ending points of the electric energy transportation in the power grid based on the regional energy balance degree and the regional frequency deviation degree includes: Obtain the regional energy balance degree and the regional frequency deviation degree of the 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 the set balance degree threshold, determine the first node as the starting node; obtain the regional energy balance degree and the regional frequency deviation degree of the 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, determine the second node as the ending node.

[0008] In one embodiment, the energy interaction parameter includes the electric energy transmission amount between the starting node and the ending node; before controlling the train to transport the electric energy of the starting node to the ending node, the method further includes: Determine the transmission distance between the starting node and the ending node and the electric energy capacity of the train; substitute the electric energy transmission amount and the transmission distance into a preset objective function to minimize the value of the objective function; obtain the decision variable when the value of the objective function is minimized, and judge whether the train transports the energy of the starting node to the ending node according to the decision variable. The objective function satisfies the following relationship: ; In the formula, min represents that the objective function takes the minimum value, represents the cost coefficient related to the transmission distance, represents the transmission distance, represents the decision variable, represents the electric energy transmission cost per unit distance from the starting node to the ending node, represents the electric energy capacity, represents the cost coefficient related to the electric energy capacity.

[0009] In one embodiment, the objective function satisfies the following constraint conditions: The node has no self - transportation demand; the electrical energy transmission volume of the starting node is less than or equal to the energy injection volume of the node; the electrical energy transmission volume of the ending node is equal to the energy demand volume of the node; only transportation from the starting node to the ending node is allowed; the electrical energy capacity of the train is associated with the transmission distance, and the electrical energy transmission volume does not exceed the electrical energy capacity.

[0010] In one embodiment, obtaining the energy change parameters of each node in the power grid, including: If the uncertainty of the energy output of the power generation system connected to the node per unit time satisfies a normal distribution, determining the electrical energy output uncertainty parameter 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 and the starting moment of the electrical energy output in each operating condition; obtaining the energy injection volume of the power generation system per unit time according to the electrical energy output uncertainty parameter, the output power under different operating conditions, and the starting moment of the electrical energy output in each operating condition.

[0011] In one embodiment, obtaining the energy change parameters of each node in the power grid, including: If the uncertainty of the energy demand of the load connected to the node per unit time satisfies a normal distribution, determining the power demand uncertainty parameter of the load based on a preset second probability function; obtaining the total load demand of the load per unit time based on the power demand uncertainty parameter and a preset power demand function; determining the energy output volume of the node according to the total load demand.

[0012] In one embodiment, obtaining the energy change parameters of each node in the power grid, including: If the state - of - charge deviation of the energy storage device connected to the node per unit time satisfies a normal distribution, determining the state - of - charge uncertainty parameter of the energy storage device based on a preset third probability function; obtaining the charge - discharge variable and charge - discharge power of the energy storage device per unit time; determining the state - of - charge of the energy storage device per unit time according to the charge - discharge variable, the charge - discharge power, and the state - of - charge uncertainty parameter, and the state - of - charge satisfies the following relational expression: ; In the formula, represents the state - of - charge, represents the energy dissipation coefficient, represents the state - of - charge uncertainty parameter, represents the charge - discharge variable, represents the energy conversion efficiency, represents the charge - discharge power.

[0013] In one embodiment, according to the respective energy change parameters of two adjacent nodes, determining the energy interaction parameter between the two adjacent nodes to obtain the regional energy balance degree of the two adjacent nodes, including: Obtain the first energy change parameter of the first node and the 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 degree between the first node and the second node, where the energy interaction parameter is characterized as 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 degree satisfies the following relational expression: ; In the formula, represents the regional energy balance degree, represents the first energy change parameter, represents the second energy change parameter, represents the energy interaction parameter.

[0014] In one embodiment, according to the energy injection amount and energy output amount of each node, determine the regional frequency deviation degree of each node, including: Based on the area control deviation method, determine whether the energy injection amount and energy output amount within the node meet the set balance standard, where the regional frequency deviation degree satisfies the following relational expression: ; In the formula, represents the regional frequency deviation degree, represents the sum of the actual powers 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, represents the rated value of the frequency deviation of the node.

[0015] In a second aspect, the present application also provides an electric energy scheduling system based on railway mobile energy storage, and the system includes: A data acquisition unit for acquiring the energy change parameters of each node in the power grid, where the energy change parameters include at least one of the energy injection amount and the energy output amount; A calculation unit for determining the energy interaction parameter between two adjacent nodes according to the energy change parameters of the two adjacent nodes respectively, so as to obtain the regional energy balance degree between the two adjacent nodes, where the larger the energy interaction parameter, the higher the regional energy balance degree; determine the regional frequency deviation degree of each node according to the energy injection amount and energy output amount of each node; based on the regional energy balance degree and the regional frequency deviation degree, obtain the starting and ending points of the electric energy transportation in the power grid, where the starting and ending points include the starting node and the ending node of the electric energy transportation; An execution unit for controlling the train to transport the electric energy of the starting node to the ending node.

[0016] The above-mentioned electric energy scheduling method based on railway mobile energy storage. This method obtains the energy change parameters (including energy injection and energy output) of each node in the power grid, determines the energy interaction parameters between adjacent nodes using the energy change parameters, and thus calculates the regional energy balance degree. The larger the energy interaction parameter, the more frequent the flow of energy between adjacent nodes, and the higher the regional energy balance degree. It can achieve accurate assessment of the energy balance state of the power grid by means of real-time monitoring and analysis of energy injection and output data, and then optimize the energy distribution of the power grid. At the same time, by analyzing the energy injection and output of each node, the regional frequency deviation degree is determined, which can reflect the stability of the power grid frequency and the power balance situation. This technical feature can effectively evaluate the stability of the power grid frequency by means of real-time monitoring of the power grid frequency and combining with energy injection and output data, and then improve the operation stability of the power grid. Based on the regional energy balance degree and the regional frequency deviation degree, the regions with excess and shortage of electric energy can be accurately located, the starting and ending points of electric energy transportation can be determined, and the train can be controlled to transport the electric energy from the starting node to the ending node. By optimizing the way of electric energy allocation, the utilization efficiency of the railway mobile energy storage system can be improved, the reliability and elasticity of the power grid can be enhanced, the electric energy transmission cost can be reduced, and finally the optimal allocation of energy can be realized. Description of the Drawings

[0017] Figure 1 It is a flowchart of the electric energy scheduling method based on railway mobile energy storage in an embodiment; Figure 2 It is a vehicle-grid collaborative operation framework in an embodiment; Figure 3 It is a flowchart of obtaining the starting and ending points of electric energy transportation in the power grid based on the regional energy balance degree and the regional frequency deviation degree in an embodiment; Figure 4 It is a flowchart of judging whether the train transports the energy of the starting node to the ending node according to the decision variable in an embodiment; Figure 5 It is a flowchart of obtaining the energy change parameters of each node in the power grid in the first embodiment; Figure 6 It is a flowchart of obtaining the energy change parameters of each node in the power grid in the second embodiment; Figure 7 It is a flowchart of obtaining the energy change parameters of each node in the power grid in the third embodiment; Figure 8 It is a flowchart of obtaining the regional energy balance degree between two adjacent nodes in an embodiment; Figure 9Schematic diagram of an electric energy scheduling system based on railway mobile energy storage in an embodiment. Specific implementation manners

[0018] In order to make the objectives, technical solutions and advantages of the present application clearer and more understandable, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. Unless otherwise defined, the technical terms or scientific terms involved in the present application should have the general meaning understood by those with ordinary skills in the technical field to which the present application belongs.

[0019] In this article, relational terms such as first and second are only used 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. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0020] In one embodiment, as Figure 1 shown, a method for electric energy scheduling based on railway mobile energy storage is provided, and the method includes: Step 101: Obtain the energy change parameters of each node in the power grid, where the energy change parameters include at least one of the energy injection amount and the energy output amount; The energy change parameters include at least one of the energy injection amount and the energy output amount. Among them, the energy injection amount refers to the total amount of energy input from an external power source (such as a power generation station, distributed energy, etc.) to a power grid node within a specific time, reflecting the power supply capacity of the node and the energy supply situation of the outside world to the power grid. The energy output amount represents the total amount of energy transmitted from the power grid node to the outside or provided to the user or the load side, reflecting the load demand of the node and the power supply situation of the power grid to the user.

[0021] Step 102: Determine the energy interaction parameter between two adjacent nodes according to the respective energy change parameters of the two adjacent nodes, so as to obtain the regional energy balance degree of the two adjacent nodes. Among them, the larger the energy interaction parameter, the higher the regional energy balance degree; It should be noted that each node in the power grid is effectively managed through regional division. Each region contains multiple nodes and must include at least one traction substation. The traction substation is the key link for energy transmission between the railway and the power grid. It is responsible for converting the high-voltage alternating current of the power grid into an electrical energy form suitable for railway trains, and at the same time supports bidirectional power transmission. The regenerative electric energy generated during train braking can be fed back to the power grid through the traction substation to achieve the recycling of energy.

[0022] The traction substation ensures the balance of power supply and demand within each region. On the one hand, the traction substation can supply electrical energy to railway trains; on the other hand, the traction substation can transmit the excess electrical energy to the power grid to optimize the power distribution. In addition, the traction substation adjusts the power transmission volume, reasonably distributes electrical energy according to the train operation requirements and the power grid conditions, and ensures the stable operation of the railway and the power grid.

[0023] In the coordinated operation of the power grid and the railway system, the regional division is centered around the traction substation to ensure the reasonable allocation of electrical energy within the region. The nodes within the region (such as the starting node, ending node, etc.) are connected to the power grid through the traction substation to achieve efficient power transmission and optimized configuration.

[0024] The regional energy balance degree can reflect the energy supply and demand balance state between two adjacent nodes, and can be evaluated by comparing the energy injection amount and the energy output amount of these two nodes.

[0025] Exemplarily, when calculating the regional energy balance degree, determine the respective energy change parameters of two adjacent nodes, which can be the energy injection amount or the output amount. Further, calculate the energy difference between two adjacent nodes, and the product of their respective total energy interactions with other nodes. Add these values to obtain a comprehensive index, and use this index as the numerator part. Further, calculate the denominator part, including the adjustment factor of the energy difference between nodes, and the smaller value of the total energy interactions of each node with other nodes. Finally, divide the numerator part by the denominator part to obtain the regional energy balance degree. The larger the regional energy balance degree, the more balanced the energy distribution between two adjacent nodes.

[0026] Step 103: Determine the regional frequency deviation degree of each node according to the energy injection amount and the energy output amount of each node; The regional frequency deviation degree can reflect the deviation between the actual frequency of the power grid and the rated frequency. To determine the regional frequency deviation degree of each node, it is necessary to monitor and record the energy injection amount and the energy output amount of each node.

[0027] Through the energy injection amount and energy output of each node, the power supply and demand balance state of the power grid can be understood in real time. For example, when the energy injection amount is greater than the output amount, the power grid frequency may increase; conversely, when the energy injection amount is less than the output amount, the power grid frequency may decrease.

[0028] Exemplarily, when calculating the regional frequency deviation degree, the difference between the total actual power and the total planned power needs to be considered, that is, the sum of the actual powers of all nodes in the power grid minus the sum of the planned powers. At the same time, the difference in electricity trading also needs to be considered, that is, the difference between the total electricity trading sum between nodes and other external nodes and the total planned trading sum. In addition, the influence of frequency response needs to be considered, that is, the deviation between the actual frequency and the rated frequency multiplied by the frequency response coefficient. Finally, these factors are comprehensively calculated to obtain the regional frequency deviation degree. This index is used to measure the stability of the power grid frequency and the power balance situation.

[0029] It should be noted that in different usage scenarios, special adjustment coefficients may be introduced according to the actual situation when calculating the regional frequency deviation degree. For example, in areas with a large number of distributed energy accesses, the influence of the volatility of distributed energy on the frequency may be considered; in scenarios where energy storage systems participate in regulation, the response speed and capacity factors of the energy storage systems may be added. The adjustment coefficient can be calibrated and adjusted based on historical data, real-time monitoring data, and power grid models to more accurately reflect the actual operating state of the power grid and improve the accuracy of dispatching decisions.

[0030] Step 104: Based on the regional energy balance degree and the regional frequency deviation degree, obtain the starting and ending points of the electric energy transportation in the power grid, where the starting and ending points include the starting node and the ending node of the electric energy transportation; In power grid dispatching and management, by comprehensively analyzing the regional energy balance degree and the regional frequency deviation degree, the starting and ending points of the electric energy transportation can be accurately determined, that is, the starting node and the ending node of the electric energy transportation are clarified. The regional energy balance degree reflects the energy interaction intensity and balance state between adjacent nodes. The larger the energy interaction parameter, the more frequent and balanced the energy flow between the two nodes, and the higher the regional energy balance degree. The regional frequency deviation degree reflects the stability of the power grid frequency and the power balance situation. It and the regional energy balance degree jointly affect the operating state of the power grid. When the regional energy balance degree of a certain area shows energy surplus and the regional frequency deviation degree indicates a high frequency, while another area shows energy shortage and a low frequency, the starting node of the electric energy transportation should be the area with energy surplus, and the ending node should be the area with energy shortage. Based on these two indicators, the power grid dispatching center can scientifically and reasonably plan the electric energy transportation path, realize the optimal allocation of electric energy, and ensure the stable operation of the power grid.

[0031] Step 105: Control the train to transport the electric energy at the starting node to the ending node.

[0032] Such as Figure 2As shown in the figure, after the central controller determines the starting node and the ending node, the central controller issues a transportation instruction to the train. After receiving the instruction, the train obtains electric energy from the traction substation at the starting node by using its on-board energy storage device. During the operation of the train, through the regenerative braking energy recovery system and other energy storage devices, the train recovers and stores energy. At the same time, during the operation of the train, it can also directly obtain electric energy from the traction substation at the starting node for charging. The train transports the stored electric energy to the ending node according to the predetermined operation route and timetable. At the ending node, the train releases the electric energy into the power grid through the traction substation to meet the electric energy demand in this area. During the whole process, the operation of the train is monitored and adjusted in real time by the central dispatching system to ensure the high efficiency, safety and timeliness of the electric energy transportation.

[0033] It should be noted that, as Figure 2 shown, this figure shows the system architecture of the vehicle-grid collaborative operation framework. Among them, the photovoltaic power generation equipment and the wind power generation equipment respectively convert solar energy and wind energy into electric energy through solar panels and wind turbines to meet the grid connection requirements. The power grid, as the main network for power transmission, transports electric energy from the power station to each load center, which is represented by the high-voltage transmission line icon. The distributed energy storage device is used to charge when the grid load is low and discharge when the grid load is high to balance the grid supply and demand. The AC bus is the main power transmission line in the power grid, connecting different power generation sources and energy storage devices. The central control layer can monitor the electric energy data of the power generation sources and energy storage devices in real time, determine the starting and ending nodes of the electric energy transportation after analysis and calculation, and generate scheduling instructions to coordinate the operation of the train. Among them, as Figure 2 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 from different power generation sources (such as photovoltaic power generation equipment and wind power generation equipment), the power grid, and the distributed energy storage device to 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 railway trains. The energy feedback device can feed back the electric energy to the power grid when the train brakes. The ground energy storage device can store the electric energy when the electric energy transported by the train to the traction substation is excessive, and release the electric energy when the electric energy of the power grid is in short supply. The converter can adjust the power quality and frequency to ensure the stable supply of electric energy. The up line and the down line are the two directions of the railway track. The up line refers to the track on which the train travels from the starting station to the terminal station, and the down line is the track on which the train returns from the terminal station to the starting station. In Figure 2 it, the up line and the down line show the running directions of the train, and the on-board energy storage device can store and release electric energy during the operation of the train to support the bidirectional transmission of electric energy.

[0034] As Figure 2As shown in the figure, taking one traction substation and one train as an example, the central control layer can supply power to the on-vehicle energy storage device of the train, obtain the running state of the train, and adjust the energy supply to the train based on the running state of the train. The central control layer can also supply power to the energy feedback device of the traction substation, obtain the running state and energy storage state of the traction substation, and adjust the energy supply to the traction substation based on the running state and energy storage state of the traction substation. The on-vehicle energy storage device can feed back the surplus electric energy to the energy feedback device.

[0035] In this embodiment, the method obtains the energy change parameters (including energy injection amount and energy output amount) of each node in the power grid, determines the energy interaction parameters between adjacent nodes by using the energy change parameters, and thus calculates the regional energy balance degree. The larger the energy interaction parameter is, the more frequent the energy flow between adjacent nodes is, and the higher the regional energy balance degree is. This technical feature can achieve accurate assessment of the power grid energy balance state by means of real-time monitoring and analysis of energy injection and output data, and then optimize the energy distribution of the power grid. At the same time, by analyzing the energy injection amount and output amount of each node, the regional frequency deviation degree is determined. The regional frequency deviation degree can reflect the stability of the power grid frequency and the power balance situation. This technical feature can achieve effective assessment of the power grid frequency stability by means of real-time monitoring of the power grid frequency and combining with energy injection and output data, and then improve the operation stability of the power grid. Based on the regional energy balance degree and the regional frequency deviation degree, the regions with surplus and shortage of electric energy can be accurately located, the starting and ending points of electric energy transportation can be determined, and the electric energy can be transported from the starting node to the ending node by controlling the train. This technical feature can improve the utilization efficiency of the railway mobile energy storage system, enhance the reliability and flexibility of the power grid, reduce the electric energy transmission cost, and finally realize the optimal allocation of energy.

[0036] In one embodiment, as Figure 3 shown, based on the regional energy balance degree and the regional frequency deviation degree, obtaining the starting and ending points of electric energy transportation in the power grid includes the following steps: Step 301: Obtain the regional energy balance degree and the regional frequency deviation degree of the first node; To obtain the regional energy balance degree and the regional frequency deviation degree of the first node, it is necessary to collect the data of the energy injection amount and the energy output amount of the first node. The regional energy balance degree can be determined by comparing the difference between the energy injection amount and the energy output amount between two adjacent nodes. Using the method of step 102 above, the regional energy balance degree of the first node can be calculated. Similarly, using the method of step 103 above, the regional frequency deviation degree of the first node can be calculated.

[0037] 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; 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, which means that the power generation exceeds the local demand and the grid frequency rises. At the same time, if the regional energy balance is lower than the set balance threshold, it means that the energy flow between the first node and the adjacent nodes is unbalanced and there is excess energy. At this time, the first node can be determined as the starting node, indicating that the first node is the starting point of power transportation, and the excess power can be transmitted to other nodes in need, helping the grid frequency to return to the rated value and enhancing the stability and reliability of the grid.

[0038] Step 303: Obtain the regional energy balance and regional frequency deviation of the second node; 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 of 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 of step 103 above.

[0039] 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.

[0040] 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 power 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 as the end node, indicating that the second node can be used as the destination for power transportation and receive excess power from other nodes to balance the supply and demand of the grid and stabilize the frequency.

[0041] 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 as 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 as the ending node. This method can accurately locate areas with excess and shortage of electric energy, realize efficient allocation of electric energy, reduce energy waste, and enhance the stability and reliability of the power grid.

[0042] In one embodiment,Figure 4 As 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 of the starting node to the ending node, the method further includes the following steps: Step 401: Determine the transmission distance between the starting node and the ending node and the electric energy capacity of the train; Determining the transmission distance between the starting node and the ending node and the electric energy capacity of the train is a key step to achieve efficient electric energy transportation. Among them, the transmission distance can be determined through a geographic information system (GIS) or a railway track database, and the transmission distance can affect the running time and energy consumption of the train.

[0043] It should be noted that the electric energy capacity of the train is determined by the specifications of its energy storage equipment, which determines the maximum amount of electric energy transported in a single trip. The train can also recover braking energy during transportation to increase the effective amount of electric energy transported.

[0044] Step 402: Substitute the electric energy transmission amount and the transmission distance into a preset objective function to minimize the value of the objective function; Substituting the electric energy transmission amount and the transmission distance into a preset objective function to minimize the value of the objective function means that in the electric energy transportation scheduling, an objective function including variables such as the electric energy transmission amount and the transmission distance is established, and through an optimization algorithm, a suitable transportation path and transportation volume are selected to make the objective function reach the minimum value.

[0045] Exemplarily, the objective function can be expressed as the transportation cost, where the transportation cost is proportional to the electric energy transmission amount and the transmission distance, and the proportionality coefficients are the transportation cost per unit of electric energy and the transportation cost per unit of distance respectively. By substituting the actual transmission amount and distance for calculation, the minimum cost path required to transport the electric energy can be determined.

[0046] Step 403: Obtain the decision variables when the value of the objective function is minimized, and determine whether the train transports the energy of the starting node to the ending node according to the decision variables. The objective function satisfies the following relationship: ; In the formula, min represents the minimum value of the objective function, represents the cost coefficient related to the transmission distance, represents the transmission distance, represents the decision variable, represents the electric energy transmission cost per unit distance from the starting node to the ending node, represents the electric energy capacity, represents the cost coefficient related to the electric energy capacity.

[0047] Exemplarily, assume there are three nodes (A, B, C) and two trains (K1, K2). The transmission distances between each node areD AB = 100 km, D AC = 150 km, D BC = 50 km. The electricity transmission cost per unit distance is successively c AB = 0.1 yuan / km·kWh, c AC = 0.15 yuan / km·kWh, c BC = 0.08 yuan / km·kWh. The electricity capacities of trains K1 and K2 are 500 kWh and 300 kWh respectively. The cost coefficients are set as w 1 = 0.5 and w 2 = 0.8.

[0048] Substitute the above data into the objective function and calculate through the optimization algorithm. Assume the optimal solution is Z ABK1 = 1 (train K1 from A to B), Z ABK2 = 1 (train K2 from B to C), and the remaining decision variables are 0. At this time, the value of the objective function is: min = 0.5×(100×1 + 50×1) + 0.8×(0.1×500×1 + 0.08×300×1) = 25 + 22.4 = 47.4 yuan.

[0049] The objective function can represent that under the premise of meeting the grid demand, the electricity transportation is optimized at the minimum cost.

[0050] In one embodiment, the objective function satisfies the following constraints: the node has no self - transportation demand; the electricity transmission volume of the starting node is less than or equal to the energy injection volume of the node; the electricity transmission volume of the ending node is equal to the energy demand volume of the node; only transportation from the starting node to the ending node is allowed; there is an associated constraint between the electricity capacity of the train and the transmission distance, and the electricity transmission volume does not exceed the electricity capacity.

[0051] Specifically, the node has no self - transportation demand, that is, the starting node and the ending node of the electricity transportation must be different nodes, and it is not allowed for a node to transport electricity to itself. The node having no self - transportation demand can be expressed by the formula: x ijk = 0, if i = j. x ijk The decision variable is expressed as the electricity capacity of train k transported from substation i to substation j.

[0052] The electricity transmission volume of the starting node cannot exceed its energy injection volume, ensuring that the electricity output from the starting node does not exceed the energy it obtains from the external power supply and avoiding energy shortage at the starting node. Each starting node s ∈ SThe total outgoing quantity is equal to its supply quantity: .

[0053] The power transmission quantity of the end node must be equal to its energy demand quantity to ensure that the power transported to the end node is sufficient to meet the load demand of this node and maintain the power supply - demand balance of the power grid. For each end node r ∈ R The total incoming quantity is equal to its demand quantity: .

[0054] 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. Only transportation from the starting node S to the end node R is allowed: .

[0055] There is an associated constraint between the power capacity of the train and the transmission distance. The power transmission quantity cannot exceed the power capacity of the train, and the impact of the transmission distance on power loss and transportation efficiency needs to be considered to ensure the economy and feasibility of power transportation. The associated constraint between capacity and path, the transportation quantity does not exceed the train capacity and is related to the path: .

[0056] In this embodiment, these constraint conditions jointly ensure the rationality of power 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.

[0057] In one embodiment, before each specific execution of the power grid dispatching scheme using train mobile energy storage as a distributed power source, it is necessary to compare the economy with other energy transfer methods. Since the train mobile energy storage relies on the existing railway lines for transportation and does not require additional investment in line construction, the variable costs mainly include transportation costs and operation and maintenance costs, as well as the fixed costs of installing energy storage devices such as large - capacity batteries.

[0058] The comprehensive cost of the specific full - day life cycle is expressed as: .

[0059] Among them, is the daily comprehensive cost of the train mobile energy storage system; and are the construction cost and operation and maintenance cost of the energy storage system during the configured period; is the operation and maintenance cost of fluctuating power generation; is the daily power purchase cost saved by the train mobile energy storage system during "peak - discharging and valley - storing", is the profit obtained by the train mobile energy storage system in the energy transportation.

[0060] In one embodiment, as Figure 5 shown, obtaining the energy change parameters of each node in the power grid includes the following steps: Step 501: If the uncertainty of the energy output of the power generation system connected to the node within a unit time satisfies a normal distribution, determine the uncertainty parameter of the electrical energy output of the power generation system under different working conditions based on a preset first probability function; Step 502: Obtain the output power of the power generation system under different working conditions, and the starting time of the electrical energy output in each working condition; Step 503: According to the uncertainty parameter of the electrical energy output, the output power under different working conditions, and the starting time of the electrical energy output in each working condition, obtain the energy injection amount of the power generation system within a unit time.

[0061] Specifically, the different working conditions of the power generation system can be divided into a wind power generation system and a photovoltaic power generation system.

[0062] Exemplarily, taking the wind power generation system as an example, the energy output of the wind power generation system is expressed as: ; In the formula, is the energy output of the wind power generation system within a unit time step; is the output power of the wind power generation system; is 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 parameter can be expressed as: ; In the formula, represents the energy injection amount of the wind power generation system considering uncertainty within a unit time; is the wind power output under the condition that the wind speed in the wind farm is higher than the cut-in wind speed and lower than the rated wind speed; is the wind power output under the condition that 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 the wind power output under the above two conditions respectively; , , , 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 respectively.

[0063] Assume that the uncertainty parameters of the energy output of each wind farm in the integrated energy power system follow a normal distribution per unit time, and the uncertainty parameters of wind power generation can be obtained and 's first probability function: ; In the formula, and are respectively the maximum uncertainty parameter values of wind power generation under different wind speed conditions.

[0064] Taking the photovoltaic power generation system as an example, the power output characteristics of the photovoltaic power generation system are coupled and affected by multiple factors such as the photoelectric conversion efficiency, irradiance distribution, and component thermodynamic parameters. Its energy output is expressed as: ; In the formula, is the energy output of the photovoltaic power generation system per unit time; is the output power of the photovoltaic power generation system; is the conversion efficiency between solar energy and electric energy; is the area of photovoltaic cells in the photovoltaic power station; is the sunlight irradiance intensity; is the ambient temperature of the photovoltaic power station. The photovoltaic energy output considering uncertainty is expressed as: ; In the formula, represents the energy injection amount of the photovoltaic power generation system per unit time considering uncertainty parameters; is the photovoltaic output power under the condition that the sunlight irradiance intensity in the photovoltaic power station is higher than the minimum requirement and lower than the rated intensity; is the photovoltaic output power under the condition that the sunlight irradiance intensity in the photovoltaic power station is higher than the rated intensity; and are respectively the uncertainties of the photovoltaic output power under the above two conditions; , , , are respectively the starting time when the light irradiance intensity in the photovoltaic power station is lower than the minimum requirement intensity, the starting time when the irradiance intensity is higher than the rated intensity, the starting time when the irradiance intensity is higher than the minimum requirement intensity, and the ending time when the irradiance intensity is higher than the rated intensity.

[0065] Assume that the uncertainty parameters of the energy output of each photovoltaic power station in the integrated energy power system follow a normal distribution per unit time. Then, the uncertainty parameters and of the photovoltaic power generation system can be obtained ; Wherein, and are respectively the maximum uncertainty parameter values of photovoltaic power generation under different irradiation conditions.

[0066] In one embodiment, as shown in Figure 6 , the energy change parameters of each node in the power grid are obtained, including the following steps: Step 601: If the uncertainty of the energy demand of the load connected to the node within a unit time satisfies a normal distribution, determine the power demand uncertainty parameter of the load based on a preset second probability function; Step 602: Based on the power demand uncertainty parameter and a preset power demand function, obtain the total load demand of the load within a unit time; Step 603: Determine the energy output of the node according to the total load demand.

[0067] In the operation of the power system, the random fluctuations of the load and the intermittency of renewable energy power generation have similar regulation challenges, both of which will have a significant impact on the scheduling strategy of the integrated energy system. When the actual electricity consumption deviates from the short-term or ultra-short-term load forecast curve, the power system needs to quickly start the standby capacity adjustment mechanism and ensure that the power supply-demand matching and frequency control indicators at different time dimensions meet the operation standards by dynamically optimizing the output distribution of the power generation units. The energy demand within a unit time can be expressed as: ; wherein, within a unit time, , and represent the start time and end time of the corresponding power demand function of the i-th load, represents the energy demand of the i-th load, represents the power demand function of the i-th load within a unit time, and respectively represent the minimum power and maximum power of the i-th load. The energy demand considering the load uncertainty parameter is expressed as: ; In the formula, represents the total load demand considering the uncertainty parameter, represents the total load power demand function considering the uncertainty, represents the total power demand uncertainty parameter. Similarly, assuming that the demand uncertainty of each load in the integrated energy power system within a unit time follows a normal distribution, then the probability distribution function of the load uncertainty parameter can be obtained: ; In the formula, Represents the maximum uncertain parameter value of the total load in the integrated energy power system.

[0068] In one embodiment, as Figure 7 shown, obtaining the energy change parameters of each node in the power grid includes the following steps: Step 701: If the state of charge deviation of the energy storage device connected to the node satisfies a normal distribution within a unit time, determine the state of charge uncertainty parameter of the energy storage device based on a preset third probability function; Step 702: Obtain the charge and discharge variables and charge and discharge power of the energy storage device within a unit time; Step 703: According to the charge and discharge variables, charge and discharge power, and state of charge uncertainty parameter, determine the state of charge of the energy storage device within a unit time, and the state of charge satisfies the following relational expression: ; In the formula, represents the state of charge, represents the energy dissipation coefficient, represents the state of charge uncertainty parameter, represents the charge and discharge variable, represents the energy conversion efficiency, represents the charge and discharge power.

[0069] Specifically, considering the uncertainty parameters of the energy storage device during the charge and discharge process, the state of charge of the energy storage device within a unit time can be obtained: ; In the formula, represents the state of charge of the energy storage device in the power system within a unit time, represents the energy dissipation coefficient, represents the uncertainty of the state of charge, represents the charge and discharge state variable of the energy storage device within a unit time, taking a positive value for charging and a negative value for discharging, represents the energy conversion efficiency, represents the charge and discharge power. Assuming that the state of charge deviation of the energy storage device within a unit time follows a normal distribution, then the third probability function of the energy storage state of charge uncertainty parameter can be obtained: ; In the formula, represents the maximum uncertain parameter value of the total load in the integrated energy power system.

[0070] In one embodiment, during the train operation, it is mainly affected by the combined action of three forces: traction force, braking force, and resistance. The traction force The torque output by the traction motor is transmitted to the driving wheels through the gear reducer, and then through the frictional force between the wheel and the rail, a tangential reaction force is generated by the rail on the wheel to drive the train to run. Specifically, it can be obtained from the following formula: ; Among them, represents the output torque of the traction motor, represents the mechanical reduction ratio between the output shaft of the traction motor and the driving wheels, represents the mechanical transmission efficiency between the output shaft of the traction motor and the driving wheels, is the diameter of the rolling circle of the driving wheel. In actual calculations, the traction characteristic curve is often used, which can reflect the change of the train traction force with speed.

[0071] Braking force is mainly divided into mechanical braking and electric braking, which is the longitudinal force acting on the rail surface by the wheel tread, and can be specifically expressed as: ; Among them, represents the pressure of each brake shoe, represents the brake shoe friction coefficient, represents the radius of the rolling circle of the wheel, represents the moment of inertia of the wheel set, represents the angular deceleration of the wheel set. In practical applications, the braking force can be calculated according to the known braking deceleration: ; Among them, represents the mass of the train, represents the gyroscopic mass coefficient calculated from the rotational inertia of the wheel set, represents the known braking deceleration, represents the train resistance. The calculation of the braking force often also considers the braking characteristic curve, which reflects the change of the train braking force with speed.

[0072] Resistance includes basic resistance and additional resistance . The basic resistance consists of the frictional resistance between the axle neck and the bearing, the rolling frictional resistance between the wheel and the rail, the sliding frictional resistance of the wheel on the rail, the impact and vibration resistance caused by track irregularities and wheel tread scuffing, and the air resistance. It is usually calculated using empirical formulas obtained from a large number of experiments. Generally, the formula for the unit basic resistance is: ; Among them represents the train running speed, 、 , is the coefficient of the Davis equation, which is determined by tests and varies with vehicle types.

[0073] Unit additional resistance is the resistance suffered by the train when running under specific conditions, including the additional resistance on slopes, the additional resistance on curves, and the additional resistance in tunnels. It is considered that the resistance suffered by the train during operation is mainly determined by the running speed and the running distance.

[0074] ; Among them, represents the additional resistance on slopes determined by the slope, represents the additional resistance on curves determined by the curve radius, represents the additional resistance in tunnels determined by the tunnel length. The total resistance of the train during operation is expressed as: ; where g is the gravitational constant.

[0075] In one embodiment, the train will experience condition transitions during the operation between stations. Generally, adopting the operation control strategy of traction - cruise - coasting - braking is more energy - saving. When the train is running on a flat section and the slope factor is not considered, assuming the resultant force suffered by the train is , which changes with time.

[0076] Traction condition: ; Cruise condition: ; Coasting condition: ; Braking condition: .

[0077] The electric power , consumed or regenerated by the high - speed train can be obtained from the electromechanical energy conversion relationship, and the expression with the mechanical power is shown as follows. is the coefficient of the regenerative braking energy utilization rate, is the conversion coefficient of mechanical energy to electric energy in other conditions except BR.

[0078] ; Thus, the energy demand of the train participating in demand response per unit time can be expressed as: ; In the formula, the satisfaction per unit time , and Are respectively represented as the start and end moments of the power demand function when train i does not participate in the grid demand response. And Are respectively represented as the start and end moments of the power demand function when train i participates in the grid demand response, and satisfy Is represented as the energy demand of the i-th train. Is represented as the power demand function when the i-th train cannot perform demand response and consumes electric energy per unit time. Is represented as the power demand function when the i-th train can perform demand response and feed back the regenerative braking energy per unit time. And Are respectively represented as the minimum and maximum powers when train i cannot respond to the grid dispatching. And Are respectively represented as the minimum and maximum powers when train i can respond to the grid dispatching. Its energy demand can be expressed as: ; In the formula, Is represented as the total load demand of the train group considering uncertainty. Is represented as the total load power demand function of the train group. Is represented as the total load power response function of the train group. Is represented as the uncertainty of the total power demand of the train group. Similarly, assuming that the demand uncertainty of the train group load in the integrated energy power system per unit time follows a normal distribution, then the load uncertainty parameter Probability function: ; In the formula, Is represented as the maximum uncertainty value of the train group load in the integrated energy power system.

[0079] In one embodiment, as Figure 8 Shown, determine the energy interaction parameter between two adjacent nodes according to the respective energy change parameters of the two adjacent nodes to obtain the regional energy balance degree of the two adjacent nodes, including the following steps: Step 801: Obtain the first energy change parameter of the first node and the second energy change parameter of the second node. The energy change parameter includes at least one of the energy injection amount and the energy output amount, reflecting the energy flow situation of the node per unit time. For the first node, the energy injection amount may come from power generation equipment, such as solar panels, wind turbines or traditional power plants; the energy output amount may be the electric energy transmitted by the node to the power grid. For the second node, the energy change parameter may involve the electric energy received from the power grid and the electric energy transmitted to users or other nodes. By monitoring and recording the energy change parameters, the energy flow state of the power grid can be grasped in real time, providing data support for power grid dispatching and optimization.

[0080] For example, if the power generation equipment of the first node generates 1000 kWh of electric energy within a certain period of time and transmits 800 kWh to the power grid at the same time, then its energy injection amount is 1000 kWh and its energy output amount is 800 kWh.

[0081] 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 degree between the first node and the second node, where the energy interaction parameter is characterized as 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 degree satisfies the following relational expression: ; In the formula, represents the regional energy balance degree, represents the first energy change parameter, represents the second energy change parameter, represents the energy interaction parameter.

[0082] Assume that the set of state variables of each partition network node is: ST = {Y1, Y2,..., YN}. The energy interaction parameter is characterized in that Yi represents the numerical value of energy injection or consumption within each node, and N represents the total number of nodes. represents the regional energy balance degree, represents the first energy change parameter, represents the second energy change parameter, represents the energy interaction parameter, and define the regional energy balance degree as: ; When the energy interaction between two adjacent first nodes m and second node n and node i is more, then the regional energy balance degree value between the first node m and the second node n is higher, and satisfies . At the same time, it is considered that when , the energy interaction between the first node m and the second node n is weak, the risk transmission is slow, and when , the energy interaction between the first node m and the second node n is strong, the risk transmission is fast, and the priority is high. Further, the balance matrix between adjacent nodes can be obtained as follows: .

[0083] In one embodiment, according to the energy injection amount and energy output amount of each node, the regional frequency deviation degree of each node is determined, including: Based on the area control deviation method, it is determined whether the energy injection amount and energy output amount within the node meet the set balance standard. Among them, the regional frequency deviation degree satisfies the following relational expression: ; In the formula, represents the regional frequency deviation degree, represents the sum of the actual powers 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, represents the rated value of the frequency deviation of the node.

[0084] Specifically, there is an Automatic Generation Control (AGC) system that conforms to its own system in each power grid area. The dispatching center of the power grid sends real-time signals to the AGC units in each area. After adding the train mobile energy storage as a distributed power source to the power grid dispatching, the AGC system is responsible for stabilizing the frequency within the standard range and allocating the power generation of each area to make the exchange value between areas stable within the rated range.

[0085] The degree of frequency deviation is related to the regulation coefficient of each system, the degree of load disturbance, and the regulation effect of the load. When a disturbance occurs in a system in a region, the impact on the overall interconnected system. Generally, the area control error (ACE) is used to judge the standard for whether the power generation power and the power consumption load in the control area are balanced, which means that the current power system is affected by factors such as load, power generation power, and frequency, resulting in a deviation between the actual value and the standard value. The area control error is expressed by the formula: ; Among them, represents the area control error, represents the sum of the actual powers 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, represents the rated value of the frequency deviation of the node.

[0086] Based on the same concept, as Figure 9 shown, the present application also provides an electric energy scheduling system based on railway mobile energy storage, and the system includes: A data acquisition unit 901, configured to acquire the energy change parameters of each node in the power grid, and the energy change parameters include at least one of the energy injection amount and the energy output amount; A calculation unit 902, configured to determine the energy interaction parameter between two adjacent nodes according to the respective energy change parameters of the two adjacent nodes, so as to obtain the regional energy balance degree of the two adjacent nodes, wherein the larger the energy interaction parameter, the higher the regional energy balance degree; determine the regional frequency deviation degree of each node according to the energy injection amount and the energy output amount of each node; based on the regional energy balance degree and the regional frequency deviation degree, obtain the starting and ending points of the electric energy transportation in the power grid, wherein the starting and ending points include the starting node and the ending node of the electric energy transportation; An execution unit 903, configured to control the train to transport the electric energy of the starting node to the ending node.

[0087] In one embodiment, the calculation unit 902 acquires the regional energy balance degree and the regional frequency deviation degree of the 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 the set balance degree threshold, then determine the first node as the starting node; acquire the regional energy balance degree and the regional frequency deviation degree of the 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.

[0088] In one embodiment, the energy interaction parameter of the calculation unit 902 includes the electric energy transmission amount between the starting node and the ending node; before controlling the train to transport the electric energy of 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 the decision variable when the value of the objective function is minimized, and judging whether the train transports the energy of the starting node to the ending node according to the decision variable, and the objective function satisfies the following relational expression: ; In the formula, min represents that the objective function takes the minimum value, represents the cost coefficient related to the transmission distance, represents the transmission distance, represents a decision variable, represents the electricity transmission cost per unit distance from the starting node to the ending node, represents the electricity capacity, represents the cost coefficient related to the electricity capacity.

[0089] In one embodiment, the objective function of the calculation unit 902 satisfies the following constraints: there is no self - transportation demand at the node; the electricity transmission volume at the starting node is less than or equal to the energy injection volume of the node; the electricity transmission volume at the ending node is equal to the energy demand volume of the node; only transportation from the starting node to the ending node is allowed; there is an associated constraint between the electricity capacity of the train and the transmission distance, and the electricity transmission volume does not exceed the electricity capacity.

[0090] In one embodiment, the data acquisition unit 901 acquires the energy change parameters of each node in the power grid. Specifically, if the uncertainty of the energy output of the power generation system connected to the node within a unit time satisfies a normal distribution, based on a preset first probability function, the uncertainty parameter of the electricity output of the power generation system under different working conditions is determined; the output power of the power generation system under different working conditions and the starting moment of the electricity output in each working condition are acquired; according to the electricity output uncertainty parameter, the output power under different working conditions, and the starting moment of the electricity output in each working condition, the energy injection volume of the power generation system within a unit time is obtained.

[0091] In one embodiment, the data acquisition unit 901 acquires the energy change parameters of each node in the power grid. Specifically, if the uncertainty of the energy demand of the load connected to the node within a unit time satisfies a normal distribution, based on a preset second probability function, the uncertainty parameter of the power demand of the load is determined; based on the power demand uncertainty parameter and a preset power demand function, the total load demand of the load within a unit time is obtained; according to the total load demand, the energy output volume of the node is determined.

[0092] In one embodiment, the data acquisition unit 901 acquires the energy change parameters of each node in the power grid. Specifically, if the deviation of the state of charge of the energy storage device connected to the node within a unit time satisfies a normal distribution, based on a preset third probability function, the uncertainty parameter of the state of charge of the energy storage device is determined; the charge - discharge variable and charge - discharge power of the energy storage device within a unit time are acquired; according to the charge - discharge variable, charge - discharge power, and the state - of - charge uncertainty parameter, the state of charge of the energy storage device within a unit time is determined, and the state of charge satisfies the following relationship: ; In the formula, represents the state of charge, represents the energy dissipation coefficient, represents the state - of - charge uncertainty parameter, represents the charge - discharge variable, represents the energy conversion efficiency, represents the charge and discharge power.

[0093] In one embodiment, the calculation unit 902 determines the energy interaction parameter between two adjacent nodes according to the respective energy change parameters of the two adjacent nodes, so as to obtain the regional energy balance degree between the two adjacent nodes. Specifically, it is used to: obtain the first energy change parameter of the first node and the 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 degree between the first node and the second node, where the energy interaction parameter is characterized as 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 degree satisfies the following relational expression: ; In the formula, represents the regional energy balance degree, represents the first energy change parameter, represents the second energy change parameter, represents the energy interaction parameter.

[0094] In one embodiment, the calculation unit 902 determines the regional frequency deviation degree of each node according to the energy injection amount and energy output amount of each node. Specifically, it is used to: determine whether the energy injection amount and energy output amount within the node meet the set balance standard based on the area control error method, where the regional frequency deviation degree satisfies the following relational expression: ; In the formula, represents the regional frequency deviation degree, represents the sum of the actual powers of all nodes in the power grid, represents the sum of the electricity 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, represents the rated value of the frequency deviation of the node.

[0095] It should be understood that for those of ordinary skill in the art, improvements or changes can be made according to the above description, and all such improvements and changes should fall within the protection scope of the appended claims of this application.

Claims

1. A method for electric energy scheduling based on railway mobile energy storage, characterized in that, The method includes: Obtaining energy change parameters of each node in the power grid, where the energy change parameters include at least one of an energy injection amount and an energy output amount; Determining an energy interaction parameter between two adjacent nodes according to the respective energy change parameters of the two adjacent nodes to obtain the regional energy balance degree between the two adjacent nodes. Among them, the larger the energy interaction parameter, the higher the regional energy balance degree; Determining the regional frequency deviation degree of each node according to the energy injection amount and the energy output amount of each node; Based on the regional energy balance degree and the regional frequency deviation degree, obtaining the starting and ending points of power transmission in the power grid, where the starting and ending points include a starting node and an ending node of power transmission; Controlling the train to transport the electric energy of the starting node to the ending node.

2. The method according to claim 1, characterized in that The obtaining the starting and ending points of power transmission in the power grid based on the regional energy balance degree and the regional frequency deviation degree includes: Obtaining 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, determining the first node as the starting node; Obtaining 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, determining the second node as the ending node.

3. The method according to claim 2, characterized in that The energy interaction parameter includes the electric energy transmission amount between the starting node and the ending node; before controlling the train to transport the electric energy of 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 the decision variable when the value of the objective function is minimized, and judging whether the train transports the energy of the starting node to the ending node according to the decision variable. The objective function satisfies the following relational expression: ； In the formula, min represents that the objective function takes the minimum value, represents the cost coefficient related to the transmission distance, represents the transmission distance, represents the decision variable, represents the power transmission cost per unit distance from the start node to the end node, represents the power capacity, represents the cost coefficient related to the power capacity.

4. The method according to claim 3, characterized in that The objective function satisfies the following constraint conditions: The node has no self-transportation demand; The electric energy transmission amount of the starting node is less than or equal to the energy injection amount of the node; The electric energy transmission amount of 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.

5. The method according to claim 1, characterized in that The obtaining energy change parameters of each node in the power grid includes: If the uncertainty of the energy output of the power generation system connected to the node within a unit time satisfies a normal distribution, determine the uncertainty parameter of the electric energy output of the power generation system under different working conditions based on a preset first probability function; Obtain the output power of the power generation system under different working conditions, and the starting moment of the electric energy output in each working condition; Based on the electric energy output uncertainty parameter, the output power under different working conditions, and the starting moment of the electric energy output in each working condition, obtain the energy injection amount of the power generation system within a unit time.

6. The method according to claim 1, wherein The obtaining of the energy change parameters of each node in the power grid includes: If the uncertainty of the energy demand of the load connected to the node within a unit time satisfies a normal distribution, determine the power demand uncertainty parameter of the load based on a preset second probability function; Based on the power demand uncertainty parameter and a preset power demand function, obtain the total load demand of the load within a unit time; Based on the total load demand, determine the energy output amount of the node.

7. The method according to claim 1, wherein The obtaining of the 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, determine the state of charge uncertainty parameter of the energy storage device based on a preset third probability function; Obtain the charge and discharge variables and charge and discharge power of the energy storage device within a unit time; Based on the charge and discharge variables, the charge and discharge power, and the state of charge uncertainty parameter, determine the state of charge of the energy storage device within a unit time, and the state of charge satisfies the following relational expression: ； Wherein, represents the state of charge, represents the energy dissipation coefficient, represents the state of charge uncertainty parameter, represents the charge and discharge variable, represents the energy conversion efficiency, represents the charge and discharge power.

8. The method according to claim 1, wherein The determining of the energy interaction parameter between two adjacent nodes according to the respective energy change parameters of the two adjacent nodes to obtain the regional energy balance degree of the two adjacent nodes includes: Obtain the first energy change parameter of the first node and the 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 degree 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 degree satisfies the following relational expression: ； In the formula, represents the regional energy balance degree, represents the first energy change parameter, represents the second energy change parameter, represents the energy interaction parameter.

9. The method according to claim 1, wherein The determining of the regional frequency deviation degree of each node according to the energy injection amount and the energy output amount of each node includes: Based on the area control error method, determine whether the energy injection amount and the energy output amount within the node satisfy a set balance standard, wherein the regional frequency deviation degree satisfies the following relational expression: ； In the formula, represents the regional frequency deviation degree, represents the sum of the actual powers of all the nodes in the power grid, represents the sum of the electricity 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, represents the rated value of the frequency deviation of the node.

10. An electric energy dispatching system based on railway mobile energy storage, characterized in that, The system includes: A data acquisition unit for acquiring energy change parameters of each node in the power grid, where the energy change parameters include at least one of the energy injection amount and the energy output amount; A calculation unit for determining an energy interaction parameter between two adjacent nodes based on the respective energy change parameters of the two adjacent nodes, so as to obtain the regional energy balance degree between the two adjacent nodes. Wherein, the greater the energy interaction parameter, the higher the regional energy balance degree; determining the regional frequency deviation degree of each node according to the energy injection amount and the energy output amount of each node; based on the regional energy balance degree and the regional frequency deviation degree, obtaining the starting and ending points of power transmission in the power grid, where the starting and ending points include the starting node and the ending node of power transmission; An execution unit for controlling the train to transport the electric energy of the starting node to the ending node.

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