Energy control method and system for a metro or maglev energy storage system

Abstract

The application is suitable for the field of energy control, and provides a metro or maglev energy storage system energy control method and system.The method comprises the following steps: monitoring a target electric energy parameter in the running process of a metro or maglev train, wherein the target electric energy parameter comprises train regenerative braking energy data and train traction energy demand data; collecting charge and discharge state information of a corresponding power grid of the metro or maglev train and an energy storage system; acquiring an energy balance state parameter based on a real-time running state of the train, generating an energy control strategy based on the target electric energy parameter and the energy balance state parameter, and executing an energy storage system energy control method based on the energy control strategy; and monitoring energy interaction between the energy storage system, the train and the power grid, and generating a dynamic adjustment strategy for dynamic adjustment and optimization of the energy control strategy, thereby avoiding energy waste caused by consumption of a traditional braking resistor.

Description

Technical Field

[0001] This invention belongs to the field of energy control, and in particular relates to an energy control method and system for subway or magnetic levitation energy storage systems. Background Technology

[0002] With the rapid development of urban transportation, subways and maglev trains, as efficient and convenient public transportation modes, are playing an increasingly important role in urban transportation systems. However, subway and maglev systems face some energy utilization challenges during operation.

[0003] During the braking phase of subway and maglev trains, a significant amount of regenerative braking energy is generated. Due to the intermittent nature of train operation and the uneven distribution of trains on the line, this regenerative braking energy is difficult to be fully absorbed and utilized by the same train or other trains at the same time. Simultaneously, subway and maglev systems require substantial electrical energy from the power grid during startup, acceleration, and peak operating demand, placing high demands on the grid's power supply capacity and power quality. Insufficient or unstable grid power supply may affect the normal operation of trains and even lead to malfunctions in the entire transportation system. Furthermore, the flexible allocation capability during the aforementioned energy utilization process is limited. Therefore, there is an urgent need to develop an energy control method and system for subway or maglev energy storage systems to address these issues. Summary of the Invention

[0004] The purpose of this invention is to provide an energy control method and system for subway or magnetic levitation energy storage systems, aiming to solve the problems mentioned in the background art.

[0005] This invention is implemented as follows: On one hand, an energy control method for a subway or magnetic levitation energy storage system, the method comprising:

[0006] Monitoring targeted electrical energy parameters during the operation of subway or maglev trains, including train regenerative braking energy data and train traction energy demand data; Collect charging and discharging demand status information of the power grid and energy storage system corresponding to the subway or maglev train. The charging and discharging demand status information includes the real-time demand value of the energy storage system, the real-time stored power of the energy storage system, and the real-time remaining power of the energy storage system. Based on the real-time operating status of the train, obtain energy balance state parameters; Based on the targeted electrical energy parameters and energy balance state parameters, an energy control strategy is generated, and based on the energy control strategy, an energy control method for the energy storage system is executed. Monitor the energy interaction between energy storage systems, trains, and the power grid, and generate dynamic adjustment strategies for the dynamic adjustment and optimization of energy control strategies.

[0007] As a further aspect of the present invention, obtaining the energy balance state parameters based on the real-time operating status of the train specifically includes: If the train is in regenerative braking mode, calculate the total regenerative braking energy under the current regenerative braking mode; Obtain real-time demand values ​​for energy storage systems; If the train is in traction operation, obtain the real-time stored power value of the energy storage system and the real-time power supply pressure value of the corresponding power grid.

[0008] As a further aspect of the present invention, the generation of the energy control strategy based on the energy balance state parameters specifically includes: Under the train regenerative braking state, the total regenerative braking energy value in the train regenerative braking energy data is obtained; Determine whether the total regenerative braking energy is greater than the real-time demand of the energy storage system; If the total regenerative braking energy is greater than the real-time demand of the energy storage system, a charging control strategy is generated. When the charging control strategy is activated, the charging current and charging voltage are calculated based on the current state of the energy storage system, and the energy storage system is controlled to charge at the maximum power factor.

[0009] As a further aspect of the present invention, the energy control strategy based on the energy balance state further includes: Under train traction operation, determine whether the real-time stored power of the energy storage system is greater than the energy storage system's stored power threshold; If the real-time stored electricity of the energy storage system is greater than the energy storage system's stored electricity threshold, determine whether the real-time power supply pressure value of the power grid corresponding to the train is greater than the power supply pressure threshold. If the real-time power supply pressure value of the power grid corresponding to the train is greater than the power supply pressure threshold, a discharge control strategy is generated. When the discharge control strategy is activated, the system acquires data on train traction energy demand, real-time power grid supply pressure, and real-time remaining power of the energy storage system. It then calculates the discharge power and discharge current of the energy storage system and controls the system to discharge according to an optimized discharge curve.

[0010] As a further aspect of the present invention, the optimized discharge curve in the discharge control strategy is set according to the train's operating speed curve, acceleration curve, and track gradient information.

[0011] As a further aspect of the present invention, another option is an energy control system for a subway or magnetic levitation energy storage system, the system comprising: The first monitoring module is used to monitor the target electrical energy parameters during the operation of the subway or maglev train; The data acquisition module is used to collect charging and discharging demand status information of the power grid and energy storage system corresponding to the subway or maglev train. The acquisition module is used to acquire energy balance state parameters based on the real-time operating status of the train. The first generation module is used to generate an energy control strategy based on the target electrical energy parameters and energy balance state parameters, and to execute the energy control method of the energy storage system based on the energy control strategy. The second monitoring module monitors the energy interaction between the energy storage system, the train, and the power grid. The second generation module is used to generate dynamic adjustment strategies for the dynamic adjustment and optimization of energy control strategies.

[0012] As a further aspect of the present invention, the acquisition module specifically includes: The first calculation unit is used to calculate the total regenerative braking energy under the current regenerative braking state if the train is in a regenerative braking state. The first acquisition unit is used to acquire the real-time demand value of the energy storage system; The second acquisition unit is used to acquire the real-time stored power value of the energy storage system and the real-time power supply pressure value of the power grid corresponding to the train when the train is in traction operation.

[0013] As a further aspect of the present invention, the first generation module includes: The third acquisition unit is used to acquire the total value of regenerative braking energy in the train regenerative braking energy data when the train is in regenerative braking state. The first judgment unit determines whether the total regenerative braking energy is greater than the real-time demand of the energy storage system. The first generation unit is used to generate a charging control strategy if the total regenerative braking energy is greater than the real-time demand of the energy storage system. The first matching calculation unit is used to match and calculate the charging current and charging voltage according to the current state of the energy storage system, and control the energy storage system to charge at the maximum power factor.

[0014] As a further aspect of the present invention, the second generation module includes: The second judgment unit is used to determine whether the real-time stored electricity of the energy storage system is greater than the energy storage system's stored electricity threshold when the train is in traction operation. The third judgment unit is used to determine whether the real-time power supply pressure value of the power grid corresponding to the train is greater than the power supply pressure threshold if the real-time stored power of the energy storage system is greater than the energy storage system stored power threshold. The second generation unit is used to generate a discharge control strategy if the real-time power supply pressure value of the power grid corresponding to the train is greater than the power supply pressure threshold. The third acquisition unit is used to acquire train traction energy demand data, real-time power grid supply pressure value, and real-time remaining power of the energy storage system. The second matching calculation unit is used to match and calculate the discharge power and discharge current of the energy storage system, and control the energy storage system to discharge according to the optimized discharge curve.

[0015] This invention provides an energy control method and system for subway or maglev energy storage systems. In terms of energy recovery and utilization, it effectively recovers and stores the previously wasted regenerative braking energy of trains, avoiding energy waste, increased investment and maintenance costs for heat dissipation equipment, and other problems associated with traditional braking resistors. This significantly improves the energy utilization efficiency of subway and maglev systems, achieving energy recycling. Regarding system operation assurance, the reasonable discharge of the energy storage system during train traction effectively alleviates the power grid's supply pressure during peak demand periods, reducing the impact of insufficient or unstable power grid supply on train operation. This enhances the reliability and stability of the entire subway and maglev transportation system, ensuring the efficient and orderly operation of urban rail transit. Attached Figure Description

[0016] Figure 1 This is a main flowchart of an energy control method for a subway or magnetic levitation energy storage system.

[0017] Figure 2 This is a flowchart illustrating the process of obtaining energy balance state parameters based on the real-time operating status of a train in an energy control method for a subway or magnetic levitation energy storage system.

[0018] Figure 3 This is a flowchart of the first embodiment of an energy control strategy based on energy balance state parameters in an energy control method for a subway or magnetic levitation energy storage system.

[0019] Figure 4 This is a flowchart of the second embodiment of an energy control strategy based on energy balance state generation in an energy control method for a subway or magnetic levitation energy storage system.

[0020] Figure 5 This is a main structural diagram of the energy control system for a subway or magnetic levitation energy storage system.

[0021] Figure 6 This is a structural block diagram of an energy acquisition module in the energy control system of a subway or magnetic levitation energy storage system.

[0022] Figure 7 This is a structural block diagram of a first embodiment of the first generation module in the energy control system of a subway or magnetic levitation energy storage system.

[0023] Figure 8 This is a structural block diagram of a second embodiment of the first generation module in the energy control system of a subway or magnetic levitation energy storage system. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the invention 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 merely illustrative and not intended to limit the invention.

[0025] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0026] The present invention provides an energy control method and system for subway or magnetic levitation energy storage systems, which solves the technical problems in the background art.

[0027] like Figure 1 The diagram shown is a main flowchart of an energy control method for a subway or magnetic levitation energy storage system according to an embodiment of the present invention. The energy control method for a subway or magnetic levitation energy storage system includes: Step S100: Monitor the target electrical energy parameters during the operation of the subway or maglev train; The targeted electrical energy parameters include train regenerative braking energy data and train traction energy demand data. Step S200: Collect the charging and discharging demand status information of the power grid and energy storage system corresponding to the subway or maglev train; the charging and discharging demand status information includes the real-time demand value of the energy storage system, the real-time stored power of the energy storage system, and the real-time remaining power of the energy storage system. Step S300: Obtain energy balance state parameters based on the real-time operating status of the train; Step S400: Based on the target electrical energy parameters and energy balance state parameters, generate an energy control strategy, and based on the energy control strategy, execute the energy control method of the energy storage system; Step S500: Monitor the energy interaction between the energy storage system, the train, and the power grid, and generate a dynamic adjustment strategy for the dynamic adjustment and optimization of the energy control strategy; In this embodiment, the targeted electrical energy parameters of the subway or maglev train during operation are first precisely monitored, mainly including train regenerative braking energy data and train traction energy demand data. Simultaneously, comprehensive data on the charging and discharging demand status of the corresponding power grid and energy storage system is collected. This charging and discharging demand status information includes the real-time demand value of the energy storage system, the real-time stored capacity of the energy storage system, and the real-time remaining capacity of the energy storage system. This data forms the key basis for subsequent judgments and decisions. Through in-depth analysis of the train regenerative braking energy data and train traction energy demand data, the current energy state of the train can be accurately determined, clarifying whether the train is in a stage where regenerative braking generates excess energy or in a stage where traction operation requires supplemental energy. Based on the targeted electrical energy parameters and the train's precise current energy state, a matching energy control strategy is generated, and based on the energy control strategy, the energy control method of the energy storage system is executed. When the train is under regenerative braking and the braking energy exceeds the system's immediate needs, the energy storage system's charging control strategy will be activated. The appropriate charging current and voltage will be calculated according to the characteristics of the energy storage system, and maximum power factor correction technology will be used to perform safe and stable charging operations. When the train is in traction operation and the energy storage system has sufficient power while the power grid is under pressure, the energy storage system's discharge control strategy will be activated. The discharge power and current will be determined based on the train's traction power requirements, the power grid's power supply capacity, and the remaining power in the energy storage system. The discharge curve will be preset and dynamically corrected and optimized based on the train's operating speed, acceleration, and track gradient information, so that the energy output of the energy storage system accurately matches the train's traction needs.

[0028] Throughout the energy control process, the energy interaction between the energy storage system, the train, and the power grid is continuously monitored. A pre-set algorithm is used to learn and analyze a large amount of historical and real-time operational data to generate dynamic adjustment strategies. These strategies are then used for dynamic adjustment and optimization of the energy control strategy, achieving adaptive optimization. When a large influx of regenerative braking energy into the train is predicted in the short term and the energy storage system has sufficient capacity, the charging power limit is increased based on the state of charge and temperature of the energy storage equipment, always kept within a safe threshold to prevent overheating and overcharging, and to accelerate energy recovery. If the energy storage system approaches full charge or the equipment is in poor condition, the power is reduced and trickle charging mode is switched, thus dynamically adjusting the charging control strategy. When the power grid is critically overloaded, the energy storage discharge can be increased and the proportion of power drawn from the grid by the train can be reduced to maintain the safe operating boundary of the power grid, thereby dynamically adjusting the discharge control strategy. This method and system offer several significant technological advantages. In terms of energy recovery and utilization, it effectively recovers and stores previously wasted regenerative braking energy from trains, avoiding energy waste, increased investment and maintenance costs for cooling equipment, and other problems associated with traditional braking resistors. This greatly improves the energy utilization efficiency of subway and maglev systems, achieving energy recycling. Regarding system operation assurance, the energy storage system's efficient discharge during train traction effectively alleviates the power grid's pressure during peak demand periods, reducing the impact of insufficient or unstable grid power supply on train operation. This enhances the reliability and stability of the entire subway and maglev transportation system, ensuring the efficient and orderly operation of urban rail transit.

[0029] like Figure 2 As shown, in a preferred embodiment of the present invention, obtaining the energy balance state parameters based on the real-time operating status of the train specifically includes: Step S301: If the train is in regenerative braking state, calculate the total regenerative braking energy under the current regenerative braking state; Step S302: Obtain the real-time demand value of the energy storage system; Step S303: If the train is in traction operation, obtain the real-time stored power value of the energy storage system and the real-time power supply pressure value of the corresponding power grid. In this embodiment, when the train is in regenerative braking mode, the total regenerative braking energy is calculated to obtain the real-time demand value of the energy storage system. Subsequently, when the train is in regenerative braking mode and the braking energy exceeds the system's immediate demand, the charging control strategy of the energy storage system is activated. The appropriate charging current and voltage are calculated according to the characteristics of the energy storage system, and the maximum power factor correction technology is used to perform safe and stable charging operations. When the train is in traction operation mode, the real-time stored energy value of the energy storage system and the real-time power supply pressure value of the corresponding power grid are obtained, and the discharge control strategy of the energy storage system is activated. The discharge power and current are determined based on the train's traction power demand, the power grid's power supply capacity, and the remaining energy of the energy storage system.

[0030] like Figure 3 As shown, in a preferred embodiment of the present invention, the generation of an energy control strategy based on energy balance state parameters specifically includes: Step S401: Under the train regenerative braking state, obtain the total regenerative braking energy value in the train regenerative braking energy data; Step S402: Determine whether the total regenerative braking energy is greater than the real-time demand of the energy storage system; Step S403: If the total regenerative braking energy is greater than the real-time demand of the energy storage system, generate a charging control strategy; Step S404: When the charging control strategy is activated, the charging current and charging voltage are calculated according to the current state of the energy storage system, and the energy storage system is controlled to charge at the maximum power factor. In this embodiment, during train regenerative braking, the total regenerative braking energy value in the train regenerative braking energy data is obtained. It is then determined whether the total regenerative braking energy value is greater than the real-time demand value of the energy storage system. If the total regenerative braking energy value is greater than the real-time demand value of the energy storage system, a charging control strategy is generated. When the charging control strategy is activated, the charging current and charging voltage are matched and calculated according to the current state of the energy storage system. The matching calculation method can be calculated using a fuzzy logic control algorithm to control the energy storage system to charge at the maximum power factor, so as to prevent overcharging from damaging the energy storage device and ensure the safety and stability of the charging process.

[0031] like Figure 4 As shown, in a preferred embodiment of the present invention, the energy control strategy generated based on the energy balance state further includes: Step S411: Under train traction operation, determine whether the real-time stored power of the energy storage system is greater than the energy storage system's stored power threshold. Step S412: If the real-time stored power of the energy storage system is greater than the energy storage system's stored power threshold, determine whether the real-time power supply pressure value of the power grid corresponding to the train is greater than the power supply pressure threshold. Step S413: If the real-time power supply pressure value of the power grid corresponding to the train is greater than the power supply pressure threshold, generate a discharge control strategy; Step S414: When the discharge control strategy is activated, acquire the train traction energy demand data, the real-time power supply pressure value of the power grid, and the real-time remaining power of the energy storage system, match and calculate the discharge power and discharge current of the energy storage system, and control the energy storage system to discharge with an optimized discharge curve.

[0032] It should be understood that the energy storage system has preset thresholds for both stored energy and power supply pressure. When the train is in traction operation, it is determined whether the real-time stored energy of the energy storage system exceeds the threshold. If so, it is then determined whether the real-time power supply pressure of the corresponding power grid exceeds the threshold. If so, this dual conditional judgment generates a discharge control strategy. When the discharge control strategy is activated, the train's traction energy demand data, the real-time power supply pressure of the power grid, and the real-time remaining energy of the energy storage system are acquired. The discharge power and discharge current of the energy storage system are then calculated using a fuzzy logic control algorithm. This calculation optimizes the discharge curve of the energy storage system, enabling it to discharge more efficiently. The energy storage system can effectively supplement the train's traction needs, reducing the power grid's burden. When the train is starting uphill, the required traction power is higher; while during constant speed travel or downhill, the traction power demand is relatively lower. Simultaneously, the power grid's supply capacity must be closely monitored. If the grid is experiencing peak demand and supply is relatively tight, the energy storage system should be relied upon more to discharge and meet the train's traction needs, thus alleviating grid pressure. If the grid supply is sufficient, the energy storage system's discharge power can be appropriately reduced, prioritizing grid power and using the energy storage system as an auxiliary or emergency power source. Furthermore, the remaining power of the energy storage system must be accurately monitored. Power monitoring sensors are installed inside the energy storage device to obtain real-time information on the remaining power. When the remaining power is high, a larger discharge power and current can be output; as the remaining power decreases, to ensure the energy storage system's lifespan and subsequent emergency capabilities, the discharge power and current need to be gradually reduced.

[0033] In a preferred embodiment of the present invention, the optimized discharge curve in the discharge control strategy is set according to the train's operating speed curve, acceleration curve, and track gradient information.

[0034] In this embodiment, the optimized discharge curve is pre-designed based on extensive train operation data, grid characteristic data, and energy storage system performance data, and continuously optimized during actual operation. During train acceleration, the discharge curve should rapidly increase discharge power and current to meet the train's high traction power requirements; during constant speed travel, discharge power and current remain relatively stable; as the train decelerates or approaches a station, discharge power and current gradually decrease until discharge ceases. Furthermore, throughout the entire discharge process, the optimized discharge curve needs to be dynamically adjusted according to real-time grid fluctuations to ensure that the energy storage system's output power can smoothly and effectively supplement the train's traction needs, minimizing the grid's power supply burden and achieving efficient management and optimized utilization of energy in subway and maglev systems.

[0035] like Figure 5 As shown, in another preferred embodiment of the present invention, an energy control system for a subway or magnetic levitation energy storage system is provided, the system comprising: The first monitoring module 100 is used to monitor the target electrical energy parameters during the operation of the subway or maglev train; The data acquisition module 200 is used to collect charging and discharging demand status information of the power grid and energy storage system corresponding to the subway or maglev train. The acquisition module 300 is used to acquire energy balance state parameters based on the real-time operating status of the train. The first generation module 400 is used to generate an energy control strategy based on the target electrical energy parameters and energy balance state parameters, and to execute the energy control method of the energy storage system based on the energy control strategy. The second monitoring module 500 monitors the energy interaction between the energy storage system, the train, and the power grid. The second generation module 600 is used to generate dynamic adjustment strategies for the dynamic adjustment and optimization of energy control strategies.

[0036] In this embodiment, the first monitoring module 100 monitors the targeted electrical energy parameters during the operation of the subway or maglev train, the acquisition module 200 acquires the charging and discharging demand status information of the corresponding power grid and energy storage system of the subway or maglev train, the acquisition module 300 acquires the energy balance status parameters based on the real-time operation status of the train, the first generation module 400 generates an energy control strategy based on the targeted electrical energy parameters and the energy balance status parameters, and the energy control method of the energy storage system is executed based on the energy control strategy, the second monitoring module 500 monitors the energy interaction between the energy storage system, the train and the power grid, and the second generation module 600 generates a dynamic adjustment strategy for the dynamic adjustment and optimization of the energy control strategy.

[0037] like Figure 6 As shown, in another preferred embodiment of the present invention, the acquisition module 300 specifically includes: The first calculation unit 301 is used to calculate the total regenerative braking energy under the current regenerative braking state if the train is in a regenerative braking state. The first acquisition unit 302 is used to acquire the real-time demand value of the energy storage system; The second acquisition unit 303 is used to acquire the real-time stored power value of the energy storage system and the real-time power supply pressure value of the power grid corresponding to the train when the train is in traction operation.

[0038] In this embodiment, if the train is in regenerative braking state, the first calculation unit 301 calculates the total regenerative braking energy value under the current regenerative braking state, and the first acquisition unit 302 acquires the real-time demand value of the energy storage system. If the train is in traction operation state, the second acquisition unit 303 acquires the real-time stored power value of the energy storage system and the real-time power supply pressure value of the power grid corresponding to the train.

[0039] like Figure 7 As shown, in another preferred embodiment of the present invention, the first generation module 400 includes: The third acquisition unit 401 is used to acquire the total value of regenerative braking energy in the train regenerative braking energy data when the train is in regenerative braking state. The first judgment unit 402 determines whether the total value of regenerative braking energy is greater than the real-time demand value of the energy storage system. The first generation unit 403 is used to generate a charging control strategy if the total value of regenerative braking energy is greater than the real-time demand value of the energy storage system. The first matching calculation unit 404 is used to match and calculate the charging current and charging voltage according to the current state of the energy storage system, and control the energy storage system to charge at the maximum power factor. In this embodiment, during the train's regenerative braking state, the third acquisition unit 401 acquires the total regenerative braking energy value from the train's regenerative braking energy data. The first judgment unit 402 determines whether the total regenerative braking energy value is greater than the real-time demand value of the energy storage system. If the total regenerative braking energy value is greater than the real-time demand value of the energy storage system, the first generation unit 403 generates a charging control strategy. Based on the current state of the energy storage system, the first matching calculation unit 404 matches and calculates the charging current and charging voltage, and controls the energy storage system to charge at the maximum power factor.

[0040] like Figure 8 As shown, in another preferred embodiment of the present invention, the first generation module 400 further includes: The second judgment unit 411 is used to determine whether the real-time stored power of the energy storage system is greater than the energy storage system's stored power threshold when the train is in traction operation. The third judgment unit 412 is used to determine whether the real-time power supply pressure value of the power grid corresponding to the train is greater than the power supply pressure threshold if the real-time stored power of the energy storage system is greater than the energy storage system stored power threshold. The second generation unit 413 is used to generate a discharge control strategy if the real-time power supply pressure value of the power grid corresponding to the train is greater than the power supply pressure threshold. The third acquisition unit 414 is used to acquire train traction energy demand data, real-time power grid supply pressure value and real-time remaining power of energy storage system. The second matching calculation unit 415 is used to match and calculate the discharge power and discharge current of the energy storage system, and control the energy storage system to discharge with an optimized discharge curve.

[0041] In this embodiment, when the train is in traction operation, the second judgment unit 411 judges whether the real-time stored power of the energy storage system is greater than the energy storage system's stored power threshold. If the real-time stored power of the energy storage system is greater than the energy storage system's stored power threshold, the third judgment unit 412 judges whether the real-time power supply pressure value of the power grid corresponding to the train is greater than the power supply pressure threshold. If the real-time power supply pressure value of the power grid corresponding to the train is greater than the power supply pressure threshold, the second generation unit 413 generates a discharge control strategy, the third acquisition unit 414 acquires the train's traction energy demand data, the real-time power supply pressure value of the power grid, and the real-time remaining power of the energy storage system, and the second matching calculation unit 415 matches and calculates the discharge power and discharge current of the energy storage system, and controls the energy storage system to discharge with an optimized discharge curve.

[0042] The above embodiments of the present invention provide an energy control method for a subway or maglev energy storage system, and an energy control system for the same system. First, it accurately monitors the targeted electrical parameters during the operation of the subway or maglev train, mainly including train regenerative braking energy data and train traction energy demand data. Simultaneously, it comprehensively collects the charging and discharging demand status information of the corresponding power grid and energy storage system. This data information forms the key basis for subsequent judgments and decisions. Through in-depth analysis of the train regenerative braking energy data and train traction energy demand data, it is possible to accurately determine the current energy state of the train, clarifying whether the train is in a stage where regenerative braking generates excess energy or in a stage where traction operation requires supplemental energy. Based on the train's precise current energy state, a matching energy control strategy is then generated. When the train is under regenerative braking and the braking energy exceeds the system's immediate needs, the energy storage system's charging control strategy is activated. Appropriate charging current and voltage are calculated based on the energy storage system's characteristics, and maximum power factor correction technology is used for safe and stable charging. Conversely, when the train is in traction operation and the energy storage system has sufficient power while the grid supply pressure is high, the energy storage system's discharging control strategy is activated. The discharging power and current are determined based on the train's traction power requirements, the grid's power supply capacity, and the remaining power in the energy storage system. The discharging curve is pre-set and dynamically adjusted based on the train's speed, acceleration, and track gradient information, ensuring that the energy storage system's output precisely matches the train's traction needs. Throughout the entire energy control process, the energy interaction between the energy storage system, the train, and the grid is continuously monitored. A preset algorithm learns and analyzes a large amount of historical and real-time operational data to generate a dynamic adjustment strategy, thereby achieving adaptive optimization of the energy control strategy. This method and system have several significant and beneficial technical effects. In terms of energy recovery and utilization, the system effectively recovers and stores the regenerative braking energy of trains that would otherwise be wasted, avoiding energy waste, increased investment and maintenance costs for cooling equipment, and other problems associated with traditional braking resistors. This significantly improves the energy utilization efficiency of subway and maglev systems, achieving energy recycling. Regarding system operation, the system effectively alleviates the power grid's supply pressure during peak demand periods through the reasonable discharge of energy storage during train traction. This reduces the impact of insufficient or unstable power supply on train operation, enhances the reliability and stability of the entire subway and maglev transportation system, and ensures the efficient and orderly operation of urban rail transit.

[0043] In order for the above methods and systems to operate smoothly, the system may include more or fewer components than those described above, or combine certain components, or different components, in addition to the various modules mentioned above. For example, it may include input / output devices, network access devices, buses, processors, and memory.

[0044] The processor can be a central processing unit, or other general-purpose processors, digital signal processors, application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (OPGs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. This processor is the control center of the system, connecting various parts via various interfaces and lines.

[0045] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0046] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0047] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An energy control method for a subway or magnetic levitation energy storage system, characterized in that, The method includes: Monitoring targeted electrical energy parameters during the operation of subway or maglev trains, including train regenerative braking energy data and train traction energy demand data; Collect charging and discharging demand status information of the power grid and energy storage system corresponding to the subway or maglev train; the charging and discharging demand status information includes the real-time demand value of the energy storage system, the real-time stored power of the energy storage system, and the real-time remaining power of the energy storage system. Based on the real-time operating status of the train, obtain energy balance state parameters; Based on the targeted electrical energy parameters and energy balance state parameters, an energy control strategy is generated, and based on the energy control strategy, an energy control method for the energy storage system is executed. Monitor the energy interaction between energy storage systems, trains, and the power grid, and generate dynamic adjustment strategies for the dynamic adjustment and optimization of energy control strategies.

2. The energy control method for a subway or magnetic levitation energy storage system according to claim 1, characterized in that, The acquisition of energy balance state parameters based on the real-time operation status of the train specifically includes: If the train is in regenerative braking mode, calculate the total regenerative braking energy under the current regenerative braking mode; Obtain real-time demand values ​​for energy storage systems; If the train is in traction operation, obtain the real-time stored power value of the energy storage system and the real-time power supply pressure value of the corresponding power grid.

3. The energy control method for a subway or magnetic levitation energy storage system according to claim 1, characterized in that, The energy generation control strategy specifically includes: Under the train regenerative braking state, the total regenerative braking energy value in the train regenerative braking energy data is obtained; Determine whether the total regenerative braking energy is greater than the real-time demand of the energy storage system; If the total regenerative braking energy is greater than the real-time demand of the energy storage system, a charging control strategy is generated. When the charging control strategy is activated, the charging current and charging voltage are calculated based on the current state of the energy storage system, and the energy storage system is controlled to charge at the maximum power factor.

4. The energy control method for a subway or magnetic levitation energy storage system according to claim 1, characterized in that, The energy generation control strategy also includes: Under train traction operation, determine whether the real-time stored power of the energy storage system is greater than the energy storage system's stored power threshold; If the real-time stored electricity of the energy storage system is greater than the energy storage system's stored electricity threshold, determine whether the real-time power supply pressure value of the power grid corresponding to the train is greater than the power supply pressure threshold. If the real-time power supply pressure value of the power grid corresponding to the train is greater than the power supply pressure threshold, a discharge control strategy is generated. When the discharge control strategy is activated, the system acquires data on train traction energy demand, real-time power grid supply pressure, and real-time remaining power of the energy storage system. It then calculates the discharge power and discharge current of the energy storage system and controls the system to discharge according to an optimized discharge curve.

5. The energy control method for a subway or magnetic levitation energy storage system according to claim 4, characterized in that, The optimized discharge curve in the discharge control strategy is set based on the train's operating speed curve, acceleration curve, and track gradient information.

6. An energy control system for a subway or magnetic levitation energy storage system, characterized in that, The energy control method for a subway or magnetic levitation energy storage system as described in any one of claims 1-5, wherein the system comprises: The first monitoring module is used to monitor the target electrical energy parameters during the operation of the subway or maglev train; The data acquisition module is used to collect charging and discharging demand status information of the power grid and energy storage system corresponding to the subway or maglev train. The acquisition module is used to acquire energy balance state parameters based on the real-time operating status of the train. The first generation module is used to generate an energy control strategy based on the target electrical energy parameters and energy balance state parameters, and to execute the energy control method of the energy storage system based on the energy control strategy. The second monitoring module monitors the energy interaction between the energy storage system, the train, and the power grid. The second generation module is used to generate dynamic adjustment strategies for the dynamic adjustment and optimization of energy control strategies.

7. The energy control system for a subway or magnetic levitation energy storage system according to claim 6, characterized in that, The acquisition module specifically includes: The first calculation unit is used to calculate the total regenerative braking energy under the current regenerative braking state if the train is in a regenerative braking state. The first acquisition unit is used to acquire the real-time demand value of the energy storage system; The second acquisition unit is used to acquire the real-time stored power value of the energy storage system and the real-time power supply pressure value of the power grid corresponding to the train when the train is in traction operation.

8. The energy control system for a subway or magnetic levitation energy storage system according to claim 6, characterized in that, The first generation module includes: The third acquisition unit is used to acquire the total value of regenerative braking energy in the train regenerative braking energy data when the train is in regenerative braking state. The first judgment unit determines whether the total regenerative braking energy is greater than the real-time demand of the energy storage system. The first generation unit is used to generate a charging control strategy if the total regenerative braking energy is greater than the real-time demand of the energy storage system. The first matching calculation unit is used to match and calculate the charging current and charging voltage according to the current state of the energy storage system, and control the energy storage system to charge at the maximum power factor.

9. The energy control system for a subway or magnetic levitation energy storage system according to claim 6, characterized in that, The first generation module includes: The second judgment unit is used to determine whether the real-time stored electricity of the energy storage system is greater than the energy storage system's stored electricity threshold when the train is in traction operation. The third judgment unit is used to determine whether the real-time power supply pressure value of the power grid corresponding to the train is greater than the power supply pressure threshold if the real-time stored power of the energy storage system is greater than the energy storage system stored power threshold. The second generation unit is used to generate a discharge control strategy if the real-time power supply pressure value of the power grid corresponding to the train is greater than the power supply pressure threshold. The third acquisition unit is used to acquire train traction energy demand data, real-time power grid supply pressure value, and real-time remaining power of the energy storage system. The second matching calculation unit is used to match and calculate the discharge power and discharge current of the energy storage system, and control the energy storage system to discharge according to the optimized discharge curve.

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