Energy feedback control method and system for high-voltage direct-current power supply of rail transit

Abstract

The present application relates to the field of rail transit power supply technology, and particularly relates to a rail transit high-voltage direct-current power supply energy feedback control method and system. The method obtains regenerative braking energy and network state, evaluates network energy receiving margin, determines energy distribution ratio of feedback network and vehicle-mounted energy storage according to the network energy receiving margin, and performs collaborative control. Meanwhile, network voltage fluctuation is monitored in real time, and the distribution ratio is dynamically corrected, so that the braking energy is effectively recovered, and the operation stability of the high-voltage direct-current power supply network is ensured.

Description

Technical Field

[0001] This invention relates to the field of rail transit power supply technology, and in particular to an energy feedback control method and system for high-voltage DC power supply in rail transit. Background Technology

[0002] In the field of vehicle braking energy recovery in high-voltage DC power supply systems for rail transit, current conventional practices typically employ centralized or decentralized energy absorption devices to handle regenerative braking energy. One common approach is to install resistive energy dissipation devices in traction substations to consume excess braking energy as heat. Another approach is to configure centralized energy storage systems within the power supply network, such as flywheel energy storage or supercapacitor energy storage devices, to absorb and temporarily store braking energy, releasing it back to the grid when needed. Additionally, some schemes attempt to directly feed braking energy back to the AC medium-voltage grid, which usually requires the installation of energy feed-in devices in substations.

[0003] These conventional practices have significant drawbacks. Resistive energy dissipation schemes directly convert valuable electrical energy into wasted heat, failing to achieve energy recovery and reducing the overall system energy efficiency. Furthermore, resistors generate substantial heat during frequent braking, placing an additional burden on the ventilation and cooling systems of tunnels or platforms, increasing operating costs. While centralized energy storage systems can recover some energy, their response speed and energy throughput are limited by the characteristics of the storage medium itself. In scenarios involving intensive train braking and rapid fluctuations in power demand, centralized energy storage devices may not be able to absorb all regenerated energy in a timely and sufficient manner, leading to excessively high DC grid voltage and still posing a risk of triggering protection mechanisms or wasting energy.

[0004] More critically, existing methods often treat energy feedback networks and energy storage absorption as two relatively independent control processes, lacking a refined assessment of the real-time status and acceptance capacity of the HVDC power supply network. Factors such as the network's own load conditions, the operating status of adjacent substations, and line impedance dynamically affect its ability to accept additional feedback energy. Conventional control strategies fail to adequately consider real-time changes in network conditions, making it difficult to achieve optimal dynamic allocation between energy feedback and energy transfer for storage. This leads to forced feedback when the grid's acceptance capacity is insufficient, causing grid voltage exceedances; or excessive use of energy storage when the grid has the capacity to accept it, increasing charging and discharging losses and lifespan degradation of energy storage devices. Summary of the Invention

[0005] The present invention provides an energy feedback control method and system for high-voltage DC power supply in rail transit, which can solve the problems in the prior art.

[0006] A first aspect of the present invention provides an energy feedback control method for high-voltage direct current power supply in rail transit, comprising: Acquire information on regenerative braking energy generated during the braking process of rail transit vehicles and the current operating status information of the high-voltage DC power supply network; Based on the current operating status information of the high-voltage direct current power supply network, the energy acceptance capacity of the high-voltage direct current power supply network is evaluated to obtain the network energy acceptance margin; Based on the regenerative braking energy information and the network energy acceptance margin, the distribution ratio of the regenerative braking energy between the first energy component fed back to the high-voltage DC power supply network and the second energy component transferred to the on-board energy storage device is determined, and an energy distribution command is obtained. Based on the energy distribution command, the power conversion device that feeds energy back to the high-voltage DC power supply network and the charging control device of the on-board energy storage device are controlled in a coordinated manner. The voltage fluctuation characteristics of the high-voltage DC power supply network during the process of receiving the first energy component are monitored in real time. The voltage fluctuation characteristics are compared with preset voltage stability constraints to generate an adjustment feedback signal. The adjustment feedback signal is used to dynamically correct the allocation ratio.

[0007] Based on the current operating status information of the high-voltage direct current (HVDC) power supply network, the energy acceptance capacity of the HVDC power supply network is evaluated to obtain the network energy acceptance margin, including: The current operating status information of the high-voltage direct current power supply network is analyzed to extract multi-dimensional state parameters characterizing the electrical operating characteristics of the high-voltage direct current power supply network; Based on the multidimensional state parameters, the transient voltage fluctuation trajectory and transient power transmission path of the high-voltage DC power supply network when receiving energy feedback are predicted, and the transient response prediction results are obtained. Based on the transient response prediction results and the operational safety constraints of the high-voltage direct current power supply network, the maximum upper limit of energy feedback power that the high-voltage direct current power supply network can accept while maintaining operational stability is calculated. The maximum energy feedback power limit is compared with the instantaneous power demand in the regenerative braking energy information to calculate the instantaneous energy acceptance margin of the high-voltage DC power supply network. Based on the time-series variation characteristics of the instantaneous energy capacity margin, the network energy capacity margin is generated through a preset margin assessment rule.

[0008] Based on the multidimensional state parameters, the transient voltage fluctuation trajectory and transient power transmission path of the high-voltage DC power supply network during energy feedback are predicted, resulting in transient response prediction results, including: Based on the multidimensional state parameters, the equivalent circuit topology model of the high-voltage DC power supply network is determined. The equivalent circuit topology model includes topological information characterizing the electrical connection relationship between power supply sections and impedance characteristic information characterizing the electrical characteristics of each power supply section. Based on the current location information of the rail transit vehicle in the high-voltage DC power supply network, the injection node location of the energy feedback is determined in the equivalent circuit topology model. Based on the topology information, all energy transfer branch paths originating from the injection node location are traced; For each energy transmission branch path, the energy feedback power change rate in the regenerative braking energy information is used as the excitation signal input. Combined with the impedance characteristic information on the energy transmission branch path, the voltage response time series and power distribution time series of each node are calculated during the propagation of the excitation signal along the energy transmission branch path. The transient voltage fluctuation trajectory of the entire network voltage distribution of the high voltage DC power supply network over time is obtained based on the voltage response time series of all energy transmission branch paths, and the transient power transmission path is obtained based on the power distribution time series of all energy transmission branch paths.

[0009] Based on the regenerative braking energy information and the network energy acceptance margin, the distribution ratio of the regenerative braking energy between the first energy component fed back to the high-voltage DC power supply network and the second energy component transferred to the on-board energy storage device is determined, resulting in an energy distribution command, including: The network energy acceptance margin is matched and compared with the total regenerative braking energy in the regenerative braking energy information to obtain a margin matching judgment result. The margin matching judgment result indicates whether the network energy acceptance margin is sufficient to accept the total regenerative braking energy. Based on the margin matching judgment result, the initial allocation value of the first energy component and the initial allocation value of the second energy component are determined by a preset allocation strategy rule; Obtain the current state of charge information of the vehicle-mounted energy storage device, and calculate the remaining rechargeable capacity of the vehicle-mounted energy storage device based on the current state of charge information; The feasibility of the initial allocation value of the second energy component is verified based on the remaining rechargeable capacity to obtain the energy storage capacity constraint correction coefficient; The initial allocation values ​​of the first energy component and the second energy component are corrected according to the energy storage capacity constraint correction coefficient, and the allocation ratio between the first energy component and the second energy component is calculated to obtain the energy allocation instruction.

[0010] Based on the energy distribution command, the power conversion device that feeds energy back to the high-voltage DC power supply network and the charging control device of the on-board energy storage device are coordinated and controlled, including: The energy allocation command is parsed to extract the network feedback power command value corresponding to the first energy component and the energy storage charging power command value corresponding to the second energy component. Based on the network feedback power command value and the energy storage charging power command value, the timing coordination constraints of the dual-path energy transmission are calculated. Based on the timing coordination constraints, a network feedback power trajectory is generated for the power conversion device and an energy storage charging power trajectory is generated for the charging control device. The network feedback power trajectory and the energy storage charging power trajectory satisfy the tracking consistency with the instantaneous power change curve of the regenerative braking energy in the time dimension. The feedback power tracking error is obtained by performing a differential calculation between the network feedback power trajectory and the real-time output power of the power conversion device, and the charging power tracking error is obtained by performing a differential calculation between the energy storage charging power trajectory and the real-time output power of the charging control device. Based on the feedback power tracking error, a feedback power adjustment command is generated for the power conversion device, and a charging power adjustment command is generated for the charging control device based on the charging power tracking error. The feedback power adjustment command and the charging power adjustment command are then sent to the power conversion device and the charging control device, respectively.

[0011] Based on the timing coordination constraints, the following steps are performed: generating a network feedback power trajectory for the power conversion device and an energy storage charging power trajectory for the charging control device, including: The timing coordination constraints are analyzed to extract the network feedback timing constraint information corresponding to the power conversion device and the energy storage charging timing constraint information corresponding to the charging control device. Based on the network feedback timing constraint information, the allowable time range and allowable rate range of power change of the power conversion device are determined, and the first energy component is mapped to the allowable time range of power change to obtain the network feedback energy time distribution; Based on the energy storage charging timing constraint information, the charging process start time node and the allowable rate range of charging power growth of the charging control device are determined, and the second energy component is mapped to the time range starting from the charging process start time node to obtain the energy storage charging time distribution. Based on the time distribution of the network feedback energy and the allowable rate range of power change, multiple network feedback power nodes are set on the time axis, and the multiple network feedback power nodes are connected to obtain the network feedback power trajectory; Based on the time distribution of the energy storage charging energy and the allowable rate range of the charging power growth, multiple energy storage charging power nodes are set on the time axis, and the multiple energy storage charging power nodes are connected to obtain the energy storage charging power trajectory.

[0012] Real-time monitoring of voltage fluctuation characteristics of the high-voltage DC power supply network during the reception of the first energy component, comparing the voltage fluctuation characteristics with preset voltage stability constraints to generate an adjustment feedback signal, including: During the process of the power conversion device injecting the first energy component into the high-voltage DC power supply network, the instantaneous voltage values ​​of multiple monitoring nodes in the high-voltage DC power supply network are collected in real time to obtain a voltage monitoring data sequence; Time-domain analysis is performed on the voltage monitoring data sequence to extract voltage fluctuation features that characterize the voltage fluctuation state of the high-voltage direct current power supply network. The voltage fluctuation features include voltage fluctuation amplitude information and voltage fluctuation frequency information. The voltage fluctuation characteristics are compared with the voltage stability constraints, which include an upper limit for the allowable voltage fluctuation amplitude and an upper limit for the allowable voltage fluctuation frequency, to obtain the voltage stability deviation. The adjustment feedback signal is generated based on the voltage stability deviation, and the adjustment feedback signal includes power adjustment indication information for the power conversion device.

[0013] A second aspect of the present invention provides an energy feedback control system for high-voltage direct current power supply in rail transit, comprising: The information acquisition unit is used to acquire information on regenerative braking energy generated during the braking process of rail transit vehicles and the current operating status information of the high-voltage DC power supply network. The network evaluation unit is used to evaluate the energy acceptance capability of the high-voltage DC power supply network based on the current operating status information of the high-voltage DC power supply network, and obtain the network energy acceptance margin. An energy distribution unit is used to determine the distribution ratio of the regenerative braking energy between the first energy component fed back to the high-voltage DC power supply network and the second energy component transferred to the on-board energy storage device based on the regenerative braking energy information and the network energy acceptance margin, and to obtain an energy distribution command. The collaborative control unit is used to coordinate the power conversion device that feeds energy back to the high-voltage DC power supply network and the charging control device of the on-board energy storage device based on the energy distribution command. The dynamic correction unit is used to monitor the voltage fluctuation characteristics of the high-voltage DC power supply network in real time during the process of receiving the first energy component, compare the voltage fluctuation characteristics with the preset voltage stability constraints, and generate an adjustment feedback signal. The adjustment feedback signal is used to dynamically correct the allocation ratio.

[0014] A third aspect of the present invention provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0015] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0016] This invention enables the efficient recovery and stable utilization of regenerative braking energy in rail transit. By assessing the energy acceptance capacity of the high-voltage DC power supply network, the network's energy acceptance margin is accurately obtained, providing a precise basis for energy allocation. Combined with regenerative braking energy information, the energy allocation ratio between feedback to the power supply network and transfer to onboard energy storage devices is dynamically determined, achieving optimized energy configuration. This method effectively avoids the impact of excess regenerative energy on the power grid and improves the overall efficiency of energy recovery.

[0017] This invention ensures reliable execution of energy distribution commands by coordinating the charging control of the power conversion device and the on-board energy storage device. Real-time monitoring of voltage fluctuations during energy reception by the power supply network and comparing them with stability constraints allows for timely detection of potential voltage instability risks. The generated adjustment feedback signal dynamically corrects the energy distribution ratio, enabling the system to have adaptive adjustment capabilities.

[0018] This invention significantly enhances the voltage stability of the high-voltage direct current power supply network when receiving regenerative braking energy through closed-loop dynamic correction of the allocation ratio. This suppresses voltage fluctuations caused by power surges, ensuring the safe and reliable operation of the traction power supply system. Simultaneously, it optimizes the charging and discharging process of the onboard energy storage device, extending its service life and reducing system maintenance costs.

[0019] This invention constructs an efficient, stable, and adaptive energy feedback control scheme, which not only maximizes the recovery and utilization of braking energy and improves energy utilization efficiency, but also improves the robustness and economy of the entire rail transit power supply system by actively maintaining grid voltage stability. Attached Figure Description

[0020] Figure 1 This is a flowchart illustrating the energy feedback control method for high-voltage DC power supply in rail transit according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the collaborative control process according to an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0023] Figure 1 This is a flowchart illustrating the energy feedback control method for high-voltage direct current power supply in rail transit according to an embodiment of the present invention, as shown below. Figure 1 As shown, the energy feedback control method for high-voltage direct current power supply in rail transit includes: Acquire information on regenerative braking energy generated during the braking process of rail transit vehicles and the current operating status information of the high-voltage DC power supply network; Based on the current operating status information of the high-voltage direct current power supply network, the energy acceptance capacity of the high-voltage direct current power supply network is evaluated to obtain the network energy acceptance margin; Based on the regenerative braking energy information and the network energy acceptance margin, the distribution ratio of the regenerative braking energy between the first energy component fed back to the high-voltage DC power supply network and the second energy component transferred to the on-board energy storage device is determined, and an energy distribution command is obtained. Based on the energy distribution command, the power conversion device that feeds energy back to the high-voltage DC power supply network and the charging control device of the on-board energy storage device are controlled in a coordinated manner. The voltage fluctuation characteristics of the high-voltage DC power supply network during the process of receiving the first energy component are monitored in real time. The voltage fluctuation characteristics are compared with preset voltage stability constraints to generate an adjustment feedback signal. The adjustment feedback signal is used to dynamically correct the allocation ratio.

[0024] Based on the current operating status information of the high-voltage direct current (HVDC) power supply network, the energy acceptance capacity of the HVDC power supply network is evaluated to obtain the network energy acceptance margin, including: The current operating status information of the high-voltage direct current power supply network is analyzed to extract multi-dimensional state parameters characterizing the electrical operating characteristics of the high-voltage direct current power supply network; Based on the multidimensional state parameters, the transient voltage fluctuation trajectory and transient power transmission path of the high-voltage DC power supply network when receiving energy feedback are predicted, and the transient response prediction results are obtained. Based on the transient response prediction results and the operational safety constraints of the high-voltage direct current power supply network, the maximum upper limit of energy feedback power that the high-voltage direct current power supply network can accept while maintaining operational stability is calculated. The maximum energy feedback power limit is compared with the instantaneous power demand in the regenerative braking energy information to calculate the instantaneous energy acceptance margin of the high-voltage DC power supply network. Based on the time-series variation characteristics of the instantaneous energy capacity margin, the network energy capacity margin is generated through a preset margin assessment rule.

[0025] In the application scenario of high-voltage direct current (HVDC) power supply for rail transit, accurate assessment of the network's energy acceptance capacity is a key prerequisite for achieving efficient regenerative braking energy feedback. After obtaining the current operating status information of the HVDC power supply network, this information needs to be structured and analyzed to extract multi-dimensional state parameters that can truly reflect the network's electrical operating characteristics. These multi-dimensional state parameters typically include the instantaneous value of the DC bus voltage, the current distribution of each feeder section of the traction power supply network, the load rate of the rectifier device in the traction substation, the impedance characteristic parameters of the contact network, and the energy flow direction of adjacent power supply sections. The analysis process adopts a hierarchical extraction mechanism. First, the raw electrical measurement values ​​are obtained through the data acquisition and monitoring system. Then, a filtering algorithm is used to eliminate measurement noise interference. Finally, feature mapping is used to convert the discrete measurement point data into a continuous state vector reflecting the overall network operating status.

[0026] After extracting the multidimensional state parameters, a transient analysis model of the high-voltage direct current (HVDC) power supply network is constructed. This model, based on the network topology and equipment electrical characteristics, uses the nodal voltage method to establish the network equations. For the operating condition of receiving energy feedback, energy injection disturbances are introduced into the model to simulate the electrical impact generated by regenerative braking energy feedback to the overhead contact line. By solving the transient network equations, the trajectory curves of voltage evolution at each node over time are obtained, the timing and amplitude of voltage peaks are identified, and the attenuation characteristics of voltage fluctuations are analyzed. Simultaneously, power transmission path tracing is performed, the distribution of energy feedback power in the network is calculated, and the proportions of power flowing to adjacent traction substations, to other electric vehicles, and consumed by network impedance are determined, thus obtaining complete transient response prediction results.

[0027] After obtaining the transient response prediction results, operational safety constraints need to be introduced for evaluation. These constraints include the allowable fluctuation range of DC bus voltage, feeder equipment thermal capacity limits, contact network voltage drop protection thresholds, and the power reverse transmission capability of the rectifier. The predicted transient voltage fluctuation trajectory is compared with the allowable voltage fluctuation range time-by-time to ensure that the bus voltage remains within the safe range during energy feedback. The peak current of each feeder section is checked to ensure it does not exceed the rated capacity of the equipment, preventing overload damage. The voltage of each contact network section is assessed to ensure it does not fall below the protection threshold, avoiding undervoltage protection triggering and causing power outages. The operating margin of the rectifier under reverse power conditions is verified to confirm its ability to feed energy back to the upstream grid. A multi-objective constraint optimization model is established, with maximizing the energy-accepting power as the optimization objective and the above safety constraints as limitations. The Lagrange multiplier method or sequential quadratic programming algorithm is used to solve the problem, calculating the maximum upper limit of the energy feedback power that the high-voltage DC power supply network can accept while maintaining operational stability.

[0028] Based on determining the maximum energy feedback power ceiling, a comparative analysis needs to be conducted in conjunction with the actual regenerative braking energy demand. An instantaneous power demand curve is extracted from the regenerative braking energy information; this curve reflects the changing trend of energy feedback power generated by the braking vehicle at different braking stages. The difference between the instantaneous power demand and the maximum energy feedback power ceiling is calculated. When the instantaneous power demand is lower than the ceiling, the difference represents the instantaneous energy acceptance margin of the high-voltage DC power supply network, indicating that the network has sufficient energy acceptance capacity. When the instantaneous power demand approaches or exceeds the ceiling, the instantaneous energy acceptance margin approaches zero or becomes negative, indicating that the network's energy acceptance capacity is limited, and some regenerative braking energy needs to be transferred to the on-board energy storage device. This calculation process is executed in a rolling manner with a fixed time step, forming time-series data of the instantaneous energy acceptance margin.

[0029] Feature analysis is performed on the time series of instantaneous energy acceptance margin to extract key information reflecting the dynamic changes in network energy acceptance capacity. Statistical features of the time series are calculated, including mean, variance, and gradient. The mean reflects the overall acceptance capacity level, the variance reflects the degree of fluctuation, and the gradient reflects the rate of increase or decrease in capacity. Extreme points and trend inflection points in the time series are identified to determine whether the network energy acceptance capacity is increasing, decreasing, or stable. A pre-defined margin assessment rule is constructed, based on historical operating data and safety margin setting principles, defining margin levels corresponding to different instantaneous energy acceptance margin levels. For example, when the instantaneous energy acceptance margin is higher than 30% of the expected feedback power, the network energy acceptance margin is considered sufficient; when the margin is between 10% and 30%, the margin is considered moderate; and when the margin is lower than 10%, the margin is considered tight. By matching time series characteristics with margin assessment rules, and comprehensively considering the current margin value, future short-term forecast trends, and historical fluctuation characteristics, a network energy acceptance margin index that can quantify the network's energy acceptance capacity is finally generated. This index can be output in numerical or hierarchical form, providing a basis for subsequent energy allocation decisions.

[0030] Based on the multidimensional state parameters, the transient voltage fluctuation trajectory and transient power transmission path of the high-voltage DC power supply network during energy feedback are predicted, resulting in transient response prediction results, including: Based on the multidimensional state parameters, the equivalent circuit topology model of the high-voltage DC power supply network is determined. The equivalent circuit topology model includes topological information characterizing the electrical connection relationship between power supply sections and impedance characteristic information characterizing the electrical characteristics of each power supply section. Based on the current location information of the rail transit vehicle in the high-voltage DC power supply network, the injection node location of the energy feedback is determined in the equivalent circuit topology model. Based on the topology information, all energy transfer branch paths originating from the injection node location are traced; For each energy transmission branch path, the energy feedback power change rate in the regenerative braking energy information is used as the excitation signal input. Combined with the impedance characteristic information on the energy transmission branch path, the voltage response time series and power distribution time series of each node are calculated during the propagation of the excitation signal along the energy transmission branch path. The transient voltage fluctuation trajectory of the entire network voltage distribution of the high voltage DC power supply network over time is obtained based on the voltage response time series of all energy transmission branch paths, and the transient power transmission path is obtained based on the power distribution time series of all energy transmission branch paths.

[0031] When predicting transient responses, it is first necessary to establish an equivalent circuit topology model that accurately reflects the current operating conditions based on the collected multidimensional state parameters. These multidimensional state parameters include the output voltage and current of each traction substation, voltage distribution data of each section of the contact network, measured line impedance, load current of each power supply arm, and the on / off status of sectionalizing switches. Through real-time analysis of these parameters, the actual electrical connection relationships between each power supply section in the high-voltage DC power supply network can be determined. The topology information is specifically embodied in the node association matrix of the power supply network, which describes the connection topology between traction substations, sectionalizing insulators, contact network sections, and return rails. The impedance characteristic information of each power supply section includes the resistance per unit length of the contact network, the inductance per unit length, the equivalent impedance of the return rail, and the actual length parameters of the power supply section. When establishing the equivalent circuit topology model, each power supply section is equivalent to an impedance branch containing resistive and inductive components, and the equivalent voltage source parameters of each traction substation are labeled in the model.

[0032] Determining the location of the energy feedback injection node is a crucial step in predicting the transient response. The current location information of the rail transit vehicle is obtained through an onboard positioning device, represented in kilometer markers to indicate the vehicle's precise position on the track. This vehicle location information is matched with the power supply segment division information in the equivalent circuit topology model to determine the current power supply segment number where the vehicle is located. In this equivalent circuit topology model, each power supply segment is discretized into several computational nodes, with a node spacing typically set to 100 to 200 meters. Based on the vehicle's relative position within the power supply segment, a linear interpolation method is used to determine the computational node closest to the vehicle's actual position, and this node is marked as the energy feedback injection node. This injection node is represented in the circuit model as a controlled current source, and its output characteristics are determined by the power variation law of the regenerative braking energy.

[0033] When tracing energy transmission branch paths starting from the injection node, the bidirectional power supply characteristics of the HVDC power supply network need to be considered. The tracing of energy transmission branch paths follows Kirchhoff's current law, expanding the search along all connected branches in the topology starting from the injection node. The tracing process uses a depth-first search algorithm, recording all possible paths from the injection node to each traction substation and adjacent power supply sections. Each energy transmission branch path is represented by an ordered sequence of nodes, with each node on the path corresponding to a computational node in the equivalent circuit topology model. During the tracing process, sections forming electrical islands need to be identified and eliminated, while considering the impact of the real-time status of sectionalizing switches on path connectivity. For complex power supply networks, five to eight main energy transmission branch paths can typically be traced, which constitute the main channels for the diffusion of regenerative braking energy into the power supply network.

[0034] When calculating the transient response for each energy transmission branch path, the energy feedback power change rate from the regenerative braking energy information is used as the excitation signal. This rate reflects the time-varying characteristics of the inverter output power during braking, typically increasing or decreasing by 50 to 150 kW per second. This power change rate is converted into the current change rate at the injection node and used as the excitation input for the equivalent circuit model. The impedance characteristics on the energy transmission branch path determine the propagation characteristics of the excitation signal. The voltage response of the k-th node on the path is affected by the accumulated impedance between that node and the injection node. A time-domain recursive method is used in the calculation, discretizing the path into several small time steps, each set to 1 to 5 milliseconds. At the n-th time step, the voltage value of the k-th node on the path is determined by the voltage value of that node in the previous time step, the change in current flowing through that node, and the node impedance. The calculation of the current change requires comprehensive consideration of the energy injection current from the injection node and the current distribution relationship between adjacent nodes.

[0035] The power allocation time series is calculated based on the voltage response and current distribution of each node along the energy transmission branch path. At each time step, the power transfer between adjacent nodes on the path is calculated; this power transfer is equal to the product of the voltage difference between the nodes and the current flowing through that branch. By recording the power transfer at all time steps, a power allocation time series describing the power flow characteristics along the path over time is formed. This time series reveals the diffusion rate and range of regenerative braking energy in the power supply network, providing a basis for assessing the impact of energy feedback on the power supply network.

[0036] By summarizing the calculation results of all energy transmission branch paths, the transient response characteristics of the entire HVDC power supply network can be obtained. The transient voltage fluctuation trajectory is obtained by extracting the voltage response time series of all nodes on each path throughout the transient process and spatially reconstructing these discrete node voltage values ​​according to the topological structure information. This trajectory is presented in three dimensions, with the horizontal axis representing the spatial coordinates of the power supply network, the vertical axis representing the time evolution process, and the vertical axis representing the voltage amplitude at each location. By observing the transient voltage fluctuation trajectory, dangerous areas where voltage exceeds limits and the duration of voltage fluctuations in the power supply network can be identified. The transient power transmission path integrates the power distribution time series on all energy transmission branch paths and displays the transmission direction and intensity of regenerative braking energy in the power supply network in the form of an energy flow diagram. This path information indicates which traction substations will receive feedback energy and the size of the power transmission load carried by each power supply section, providing accurate predictive basis for subsequent energy distribution decisions and coordinated control. The accuracy of transient response prediction directly affects the safety and economy of energy feedback control. Therefore, in practical applications, it is necessary to select the appropriate model granularity and calculation time step according to the complexity of the power supply network and the real-time requirements.

[0037] Based on the regenerative braking energy information and the network energy acceptance margin, the distribution ratio of the regenerative braking energy between the first energy component fed back to the high-voltage DC power supply network and the second energy component transferred to the on-board energy storage device is determined, resulting in an energy distribution command, including: The network energy acceptance margin is matched and compared with the total regenerative braking energy in the regenerative braking energy information to obtain a margin matching judgment result. The margin matching judgment result indicates whether the network energy acceptance margin is sufficient to accept the total regenerative braking energy. Based on the margin matching judgment result, the initial allocation value of the first energy component and the initial allocation value of the second energy component are determined by a preset allocation strategy rule; Obtain the current state of charge information of the vehicle-mounted energy storage device, and calculate the remaining rechargeable capacity of the vehicle-mounted energy storage device based on the current state of charge information; The feasibility of the initial allocation value of the second energy component is verified based on the remaining rechargeable capacity to obtain the energy storage capacity constraint correction coefficient; The initial allocation values ​​of the first energy component and the second energy component are corrected according to the energy storage capacity constraint correction coefficient, and the allocation ratio between the first energy component and the second energy component is calculated to obtain the energy allocation instruction.

[0038] Information on regenerative braking energy generated by rail transit vehicles during braking is acquired, including the total regenerative braking energy, instantaneous braking power, and the expected duration of energy generation. Simultaneously, the current operating status information of the high-voltage direct current (HVDC) power supply network is acquired. Based on this operating status information, the energy acceptance capacity of the HVDC power supply network is assessed, yielding the network energy acceptance margin. This network energy acceptance margin reflects the maximum energy value that the HVDC power supply network can safely accept under the current operating conditions. This value is influenced by a combination of factors, including the voltage level of the power supply network, line load conditions, the power transmission capacity of traction substations, and the power demand of other vehicles in the network.

[0039] The network energy acceptance margin is matched and compared with the total regenerative braking energy in the regenerative braking energy information. Specifically, let the network energy acceptance margin be... The total regenerative braking energy is The margin matching judgment result is obtained by comparing the numerical relationship between the two. When When the network's energy acceptance margin is sufficient to accept the total regenerative braking energy, the network has sufficient acceptance capacity; when... If the judgment result indicates that the network energy acceptance margin is insufficient to accept all the regenerative braking energy, then some energy needs to be transferred to the on-board energy storage device to avoid the dissipation of braking resistor or the decline in vehicle braking performance due to the inability to absorb the energy.

[0040] Based on the margin matching judgment results, the initial allocation values ​​of the first energy component and the second energy component are determined through preset allocation strategy rules. These rules set different allocation principles depending on different margin matching situations. When the network energy acceptance margin is sufficient, regenerative braking energy is preferentially fed back to the high-voltage DC power supply network. In this case, the initial allocation value of the first energy component is set to a larger proportion of the total regenerative braking energy, such as 80% to 100%, while the initial allocation value of the second energy component is set to a smaller proportion or zero. When the network energy acceptance margin is insufficient, the energy flow is rationally allocated according to the degree of insufficiency. In this case, the initial allocation value of the first energy component does not exceed the network energy acceptance margin, and the initial allocation value of the second energy component undertakes the remaining energy transfer task. The allocation strategy rules also consider the economics of feeding energy back to the power supply network, because the energy fed back to the network can be directly utilized by other vehicles on the line, reducing the power supply burden on the traction substation and thus improving overall energy utilization efficiency.

[0041] Obtain the current state of charge (SOC) information of the on-board energy storage device, which reflects the device's current charge level. SOC is typically expressed as a percentage, ranging from 0% to 100%, where 0% represents a fully discharged state and 100% represents a fully charged state. Calculate the remaining rechargeable capacity of the on-board energy storage device based on the current SOC information. Assume the rated total capacity of the on-board energy storage device is... If the current state of charge is SOC, then the remaining rechargeable capacity is... This is determined through the following relationship: The remaining rechargeable capacity represents the maximum amount of energy that the on-board energy storage device can still receive in the current state. This value is an important basis for verifying the feasibility of the initial allocation value of the second energy component.

[0042] A feasibility check is performed on the initial allocation value of the second energy component based on the remaining rechargeable capacity. The initial allocation value of the second energy component is compared with the remaining rechargeable capacity to determine whether the on-board energy storage device has sufficient capacity to receive the energy corresponding to the initial allocation value. If the initial allocation value of the second energy component is less than or equal to the remaining rechargeable capacity, it means the on-board energy storage device can fully receive the energy allocation, and the feasibility check passes. The energy storage capacity constraint correction coefficient is set to 1, indicating that no correction is needed to the initial allocation value. If the initial allocation value of the second energy component is greater than the remaining rechargeable capacity, it means the on-board energy storage device cannot fully receive the energy allocation, and the feasibility check fails. The energy storage capacity constraint correction coefficient needs to be calculated. Let the initial allocation value of the second energy component be... Energy storage capacity constraint correction factor Determined in the following manner: This correction factor is used to proportionally reduce the initial allocation value of the second energy component so that it does not exceed the actual acceptable capacity of the on-board energy storage device, thereby avoiding the risk of overcharging the energy storage device or causing energy to be unable to be transferred effectively.

[0043] The initial allocation values ​​of the first and second energy components are corrected based on the energy storage capacity constraint correction coefficient. This correction process ensures that the energy allocation scheme satisfies both the capacity constraints of the on-board energy storage device and guarantees a reasonable distribution of the total regenerative braking energy. The corrected value for the second energy component is... This value does not exceed the remaining rechargeable capacity. Since the total regenerative braking energy needs to be fully distributed between the first and second energy components, the corrected first energy component is set to [value missing]. During the correction process, it is also necessary to verify whether the corrected first energy component exceeds the network's energy acceptance margin. If it does, further adjustments to the allocation scheme are required, such as activating the braking resistor or adjusting the vehicle's braking strategy, to ensure the feasibility and safety of energy allocation.

[0044] The distribution ratio between the first energy component and the second energy component is calculated. The distribution ratio is determined by the ratio of the corrected energy distribution value to the total regenerative braking energy.

[0045] Figure 2 This is a schematic diagram of the collaborative control process according to an embodiment of the present invention, such as... Figure 2 As shown, based on the energy distribution command, the power conversion device that feeds energy back to the high-voltage DC power supply network and the charging control device of the on-board energy storage device are coordinated under control, including: The energy allocation command is parsed to extract the network feedback power command value corresponding to the first energy component and the energy storage charging power command value corresponding to the second energy component. Based on the network feedback power command value and the energy storage charging power command value, the timing coordination constraints of the dual-path energy transmission are calculated. Based on the timing coordination constraints, a network feedback power trajectory is generated for the power conversion device and an energy storage charging power trajectory is generated for the charging control device. The network feedback power trajectory and the energy storage charging power trajectory satisfy the tracking consistency with the instantaneous power change curve of the regenerative braking energy in the time dimension. The feedback power tracking error is obtained by performing a differential calculation between the network feedback power trajectory and the real-time output power of the power conversion device, and the charging power tracking error is obtained by performing a differential calculation between the energy storage charging power trajectory and the real-time output power of the charging control device. Based on the feedback power tracking error, a feedback power adjustment command is generated for the power conversion device, and a charging power adjustment command is generated for the charging control device based on the charging power tracking error. The feedback power adjustment command and the charging power adjustment command are then sent to the power conversion device and the charging control device, respectively.

[0046] Once the energy allocation command is generated, the charging control devices of the power conversion device and the on-board energy storage device need to be coordinated to achieve accurate allocation of regenerative braking energy between the two paths. First, the energy allocation command is parsed and processed, extracting the network feedback power command value and the energy storage charging power command value from the command data structure. The network feedback power command value represents the instantaneous power target to be fed back to the high-voltage DC power supply network, and its value range must be limited to the rated capacity range of the power conversion device. The energy storage charging power command value represents the charging power that the on-board energy storage device can receive, and this value must simultaneously consider the current state of charge of the energy storage device and the maximum allowable charging rate. After extracting these two power command values, the timing coordination constraint for dual-path energy transmission is calculated. This constraint ensures that the power conversion device and the charging control device maintain coordination in their action timing, avoiding energy superposition conflicts or response delays during the power allocation process. The calculation of the timing coordination constraint involves synchronizing the response time constant of the power conversion device with the control cycle of the charging control device. Typically, the control cycles of both are set to the same time interval, which can be set to 5 to 20 milliseconds to meet the tracking requirements of transient changes in regenerative braking energy.

[0047] After obtaining the timing coordination constraints, a network feedback power trajectory is generated for the power conversion device, and an energy storage charging power trajectory is generated for the charging control device. The network feedback power trajectory refers to the power output curve that the power conversion device should follow throughout the braking process. The design of this curve needs to consider the typical power characteristics of the braking process of rail transit vehicles, namely, the power rises rapidly in the initial stage of braking, maintains a steady-state output in the middle stage, and the power gradually decays at the end of braking. To ensure that the network feedback power trajectory can accurately track the instantaneous power change of regenerative braking energy, a piecewise linearization method is used to fit the braking power curve, dividing the entire braking process into several time windows. The power change within each time window is approximately linear, thereby simplifying the real-time calculation burden of the control algorithm. The generation of the energy storage charging power trajectory follows a similar principle, but additional constraints on the charging characteristics of the on-board energy storage device need to be considered, including the soft-start requirement in the initial stage of charging and the temperature rise limit during the charging process. Usually, a power ramp rate limit is introduced in the design of the energy storage charging power trajectory to avoid excessively rapid power changes causing impact damage to the energy storage cells. The network feedback power trajectory and the energy storage charging power trajectory must be consistent with the instantaneous power change curve of the regenerative braking energy in the time dimension. That is, at any time, the sum of the power values ​​of the two power trajectories should be equal to the instantaneous power value of the regenerative braking energy at that time, so as to achieve lossless energy transfer.

[0048] To ensure that the power conversion device and the charging control device can accurately track their respective power trajectories, a closed-loop feedback control mechanism is introduced. The target value of the network-feedback power trajectory is differentially calculated with the real-time output power of the power conversion device to obtain the feedback power tracking error. The real-time output power can be acquired by current and voltage sensors installed at the output of the power conversion device, with a sampling frequency typically set to over 1000 times per second to ensure the capture of rapidly changing power fluctuations. The feedback power tracking error is calculated using an instantaneous value comparison method; that is, within each control cycle, the target value of the power trajectory at the current moment is subtracted from the actual measured value. Similarly, the target value of the energy storage charging power trajectory is differentially calculated with the real-time output power of the charging control device to obtain the charging power tracking error. The real-time output power of the charging control device can be calculated by monitoring the current in the charging circuit and the terminal voltage of the energy storage device. It should be noted that since on-board energy storage devices are usually in the form of battery packs, their terminal voltage fluctuates with changes in state of charge. Therefore, the voltage measurement value needs to be filtered when calculating the charging power to eliminate the influence of high-frequency noise on the accuracy of the power calculation.

[0049] The feedback power tracking error is used to generate feedback power adjustment commands for the power converter. The generation of these commands employs a proportional-integral (PI) control strategy, which amplifies and integrates the tracking error to obtain the control adjustment amount for the power converter. The proportional coefficient needs to be tuned based on the dynamic response characteristics of the power converter, typically ranging from 0.5 to 2.0. A larger proportional coefficient can accelerate error convergence but may cause oscillations in the control output. The integral coefficient is used to eliminate steady-state errors, and its value is usually 1 / 10 to 1 / 5 of the proportional coefficient. After the feedback power adjustment command is output, it needs to be limited to ensure that the adjustment command does not exceed the safe operating range of the power converter. The upper limit is set to 105% to 110% of the rated power, and the lower limit is set to zero to avoid negative power output. The charging power tracking error is also used to generate charging power adjustment commands for the charging control device. The control strategy is similar to that of the power converter, but the electrochemical response delay characteristics of the energy storage device need to be considered during parameter tuning. Typically, the integral coefficient is set relatively small to prevent overshooting of the charging current. The charging power adjustment command also needs to be limited. The upper limit is determined based on the maximum allowable charging power of the energy storage device, and the lower limit is set to zero.

[0050] The generated feedback power adjustment command and charging power adjustment command are sent to the power conversion device and charging control device respectively. The command sending process is implemented using a high-speed communication interface. Commonly used communication protocols include the CA7 bus protocol or Ethernet communication protocol. The communication cycle must be consistent with the control cycle to ensure the real-time performance of the commands. After receiving the feedback power adjustment command, the power conversion device adjusts the duty cycle of its internal switching devices according to the command value, thereby changing the power output to the high-voltage DC power supply network. After receiving the charging power adjustment command, the charging control device adjusts the parameters of the current regulator in the charging circuit to control the charging current flowing into the energy storage device. Throughout the entire coordinated control process, the actions of the power conversion device and the charging control device remain synchronized and coordinated, jointly achieving precise allocation and efficient utilization of regenerative braking energy between the two paths.

[0051] Based on the timing coordination constraints, the following steps are performed: generating a network feedback power trajectory for the power conversion device and an energy storage charging power trajectory for the charging control device, including: The timing coordination constraints are analyzed to extract the network feedback timing constraint information corresponding to the power conversion device and the energy storage charging timing constraint information corresponding to the charging control device. Based on the network feedback timing constraint information, the allowable time range and allowable rate range of power change of the power conversion device are determined, and the first energy component is mapped to the allowable time range of power change to obtain the network feedback energy time distribution; Based on the energy storage charging timing constraint information, the charging process start time node and the allowable rate range of charging power growth of the charging control device are determined, and the second energy component is mapped to the time range starting from the charging process start time node to obtain the energy storage charging time distribution. Based on the time distribution of the network feedback energy and the allowable rate range of power change, multiple network feedback power nodes are set on the time axis, and the multiple network feedback power nodes are connected to obtain the network feedback power trajectory; Based on the time distribution of the energy storage charging energy and the allowable rate range of the charging power growth, multiple energy storage charging power nodes are set on the time axis, and the multiple energy storage charging power nodes are connected to obtain the energy storage charging power trajectory.

[0052] In the process of regenerative braking, transforming timing coordination constraints into specific power control trajectories is a key step in achieving safe energy feedback. Timing coordination constraints include multiple time-related restrictions on both the network feedback side and the energy storage charging side. These constraints need to be transformed into executable power change paths through a systematic analysis and mapping process.

[0053] The parsing process of timing coordination constraints first involves decomposing the constraint data structure, separating constraint information for different execution objects. The network feedback timing constraint information mainly includes parameters such as the power conversion device's start-up delay time, the upper limit of the power ramp-up rate, the continuous output time window, and the upper limit of the power decline rate. These parameters reflect the time-dimensional acceptance characteristics of the HVDC power supply network to external energy injection. For example, some power supply sections can accept a faster power ramp-up rate during off-peak hours, while a smoother power injection process is required during peak hours. The energy storage charging timing constraint information includes parameters such as the pre-charging preparation time required by the battery management system, the charging current growth slope limit, the battery temperature response time constant, and the charging power platform switching time. These parameters are jointly determined by the electrochemical and thermal management characteristics of the on-board energy storage device; the battery's ability to withstand charging power change rates varies significantly under different states of charge.

[0054] After extracting the network feedback timing constraint information, the operating time window of the power conversion device is determined. The lower bound of the allowable power change time range is jointly determined by the minimum response time of the power conversion device and the grid voltage stability margin, while the upper bound is constrained by the duration of the vehicle braking process. For example, when the grid voltage stability margin is large, energy feedback can be initiated within 0.1 seconds after the start of braking, while when the grid is in a voltage fluctuation sensitive state, the initiation time needs to be delayed to 0.3 seconds after the start of braking. The allowable power change rate range is determined by analyzing the grid impedance characteristics and load fluctuation characteristics, with a typical power ramp-up rate range of 50 kW / s to 200 kW / s. When mapping the first energy component to the allowable power change time range, the time distribution is calculated using the energy conservation principle, meaning that within the allowable time range, the area under the power curve is equal to the value of the first energy component.

[0055] The construction of the time distribution for grid-feedback energy needs to consider the dynamic characteristics of the grid voltage response. In the initial stage of braking, since the grid voltage has not yet established a stable feedback regulation, the energy feedback rate should be kept at a relatively low level. As the grid-side voltage regulating device responds, the energy feedback rate can be gradually increased to the allowable upper limit. This distribution strategy can avoid sudden shocks to the grid voltage during the energy feedback process. Specific time distribution curves can adopt various forms such as trapezoidal distribution, parabolic distribution, or piecewise linear distribution, selected according to the actual grid response characteristics.

[0056] The processing of energy storage charging timing constraints requires special attention to the state feedback of the battery management system. The charging start time depends not only on the braking start moment but also on the establishment time of the battery pre-charging circuit and the preparation time required for individual battery cell voltage equalization. For energy storage devices using lithium-ion batteries, when the battery temperature is below 10 degrees Celsius, the charging start time needs to be delayed until the battery heating device has completed preheating to avoid lithium deposition caused by low-temperature high-current charging. The allowable charging power increase rate is constrained by multiple factors such as battery internal resistance, electrolyte diffusion rate, and lithium intercalation rate of positive and negative electrode materials. The typical charging power increase rate is 20 kW to 80 kW per second, significantly lower than the power change rate on the network feedback side.

[0057] When mapping the second energy component to the energy storage charging time range, a dynamic correction mechanism for the battery's state of charge (SOC) needs to be introduced. When the SOC is low, a higher initial charging power can be used, with the charging rate gradually decreasing. However, when the SOC approaches 80%, the charging power needs to be significantly reduced to extend the battery's cycle life. The construction of the energy time distribution for energy storage charging also needs to consider the inconsistencies between individual battery cells. When there are cells with significant voltage differences within the battery pack, the rate of increase in charging power should be reduced accordingly to allow the battery management system sufficient time for active balancing control.

[0058] When setting up network feedback power nodes on the time axis, the node density distribution directly affects the control accuracy of the power trajectory. During periods of rapid power change, the node density needs to be increased to accurately characterize the power change process. A typical node interval is 0.05 seconds to 0.2 seconds. The value of each power node is obtained by dividing the energy distribution value at that moment by the node interval time. When connecting adjacent power nodes, straight-line connections or spline curve connections can be used. Straight-line connections are simple to control but may produce sudden power changes, while spline curve connections can achieve smooth power transitions but have higher computational complexity.

[0059] The setting of energy storage charging power nodes needs to match the inherent characteristics of the battery charging curve. In the early stages of charging, the power nodes can be set relatively sparsely. As the charging power approaches the battery's maximum capacity, the node density should be increased accordingly to achieve finer control. The energy storage charging power trajectory needs to reserve a buffer time for power reduction near the end of charging to avoid sudden interruptions in the charging process causing control disturbances to the battery management system.

[0060] The generated network feedback power trajectory and energy storage charging power trajectory exhibit complementary and synergistic characteristics on the time axis. In the initial stage of braking, energy storage charging power dominates, while as grid-side stability is established, network feedback power gradually increases and becomes the main path for energy recovery. This dynamically evolving dual-trajectory control mode can achieve efficient recovery and utilization of braking energy while ensuring grid stability and battery safety.

[0061] Real-time monitoring of voltage fluctuation characteristics of the high-voltage DC power supply network during the reception of the first energy component, comparing the voltage fluctuation characteristics with preset voltage stability constraints to generate an adjustment feedback signal, including: During the process of the power conversion device injecting the first energy component into the high-voltage DC power supply network, the instantaneous voltage values ​​of multiple monitoring nodes in the high-voltage DC power supply network are collected in real time to obtain a voltage monitoring data sequence; Time-domain analysis is performed on the voltage monitoring data sequence to extract voltage fluctuation features that characterize the voltage fluctuation state of the high-voltage direct current power supply network. The voltage fluctuation features include voltage fluctuation amplitude information and voltage fluctuation frequency information. The voltage fluctuation characteristics are compared with the voltage stability constraints, which include an upper limit for the allowable voltage fluctuation amplitude and an upper limit for the allowable voltage fluctuation frequency, to obtain the voltage stability deviation. The adjustment feedback signal is generated based on the voltage stability deviation, and the adjustment feedback signal includes power adjustment indication information for the power conversion device.

[0062] In the energy feedback control process, to ensure the stable operation of the high-voltage direct current (HVDC) power supply network when receiving regenerative braking energy, real-time monitoring and dynamic adjustment of network voltage fluctuations are required. When the power conversion device injects the first energy component into the HVDC power supply network, multiple voltage sensors are deployed at key locations in the power supply network. These sensors constitute monitoring nodes, typically including voltage sampling points at traction substation bus nodes, key contact wire sections, and load-concentrated areas. The voltage sensors collect instantaneous voltage values ​​from each monitoring node at a high sampling frequency, set to 1kHz to 10kHz, to ensure the capture of rapid voltage changes. The voltage data collected from each monitoring node is aggregated to the control center via a communication network, forming a voltage monitoring data sequence arranged in chronological order. This sequence records the dynamic changes in network voltage during the energy feedback process.

[0063] When performing time-domain analysis on voltage monitoring data sequences, the deviation of each monitoring node's voltage from the rated voltage is first calculated. The voltage change rate is then calculated using the voltage difference between adjacent sampling points. A sliding time window technique is applied to the voltage monitoring data sequence, with a window length ranging from 100ms to 500ms. Within each time window, the maximum, minimum, and average voltage values ​​are statistically analyzed. The voltage fluctuation amplitude is determined by the difference between the maximum and minimum values. The voltage fluctuation amplitude reflects the severity of the voltage deviation from the rated value. The percentage of voltage fluctuation amplitude is obtained by comparing the voltage fluctuation amplitude with the rated voltage. For extracting voltage fluctuation frequency information, a zero-crossing detection method is used to identify peaks and troughs in the voltage fluctuation curve. The number of fluctuations occurring per unit time is counted to obtain the voltage fluctuation frequency. Alternatively, a fast Fourier transform can be used to convert the voltage monitoring data sequence to the frequency domain to analyze the main frequency components of voltage fluctuations and identify characteristic frequencies that may cause system oscillations.

[0064] Voltage stability constraints are set according to the operating standards of high-voltage direct current power supply systems for rail transit. The upper limit of the allowable voltage fluctuation amplitude is usually set at 5% to 8% of the rated voltage. This limit is determined based on the allowable deviation range of the contact network voltage and the voltage withstand capability of the vehicle's electrical equipment. The upper limit of the allowable voltage fluctuation frequency is set at 5Hz to 10Hz. This parameter is used to prevent frequent and rapid fluctuations in the network voltage, avoiding impacts on power supply and consumption equipment. When comparing the extracted voltage fluctuation characteristics with the voltage stability constraints, firstly, it is determined whether the percentage of voltage fluctuation amplitude exceeds the upper limit of the allowable voltage fluctuation amplitude. If the percentage of voltage fluctuation amplitude exceeds the allowable range, it indicates that the network voltage stability is threatened. Then, it is determined whether the voltage fluctuation frequency exceeds the upper limit of the allowable voltage fluctuation frequency. If the voltage fluctuation frequency is too high, it indicates that the network voltage is in an unstable oscillating state.

[0065] The voltage stability deviation is obtained by calculating the difference between the voltage fluctuation characteristics and the constraints. The voltage stability deviation includes amplitude deviation and frequency deviation. Amplitude deviation is obtained by subtracting the upper limit of the allowable voltage fluctuation amplitude from the percentage of voltage fluctuation amplitude, and frequency deviation is obtained by subtracting the upper limit of the allowable voltage fluctuation frequency from the voltage fluctuation frequency. When the voltage stability deviation is negative, it indicates that the network voltage is operating within the stable region and no adjustment is needed. When the voltage stability deviation is positive, it indicates that the network voltage has deviated from the stable operating region and immediate adjustment measures are required. The magnitude of the voltage stability deviation reflects the severity of the voltage fluctuation; the larger the deviation, the stronger the adjustment required.

[0066] An adjustment feedback signal is generated based on the voltage stability deviation. This signal contains power adjustment instructions for the power converter, guiding it to adjust the amount of power injected into the HVDC power supply network, thereby controlling the feedback rate of the first energy component. When the amplitude deviation exceeds a threshold, the adjustment feedback signal instructs the power converter to reduce its output power, slowing down the energy feedback rate and bringing the network voltage fluctuation amplitude back to within the allowable range. When the frequency deviation exceeds a threshold, the adjustment feedback signal instructs the power converter to adjust its power conversion control strategy, increasing output power smoothing filtering to suppress voltage fluctuations caused by rapid power changes. The power adjustment instructions also include an adjustment step size parameter, which is dynamically determined based on the magnitude of the voltage stability deviation. Small step sizes are used when the deviation is small, and large step sizes are used when the deviation is large, achieving a balance between fast response and smooth control.

[0067] The adjustment feedback signal is transmitted to the controller of the power conversion device via the control bus. The controller modifies the operating parameters of the power conversion device according to the power adjustment instruction, including adjusting the duty cycle of the pulse width modulation signal, adjusting the on / off timing of the switching devices, and changing the parameter settings of the output filter. After responding to the adjustment command, the power injected into the high-voltage DC power supply network changes accordingly, thereby altering the actual feedback amount of the first energy component and gradually ensuring that the network voltage fluctuation characteristics meet the voltage stability constraints. Through continuous monitoring, comparison, feedback, and adjustment cycles, closed-loop control of the energy feedback process is achieved, ensuring that the high-voltage DC power supply network maintains voltage stability while receiving regenerative braking energy, thus guaranteeing the safe and reliable operation of the rail transit system.

[0068] A second aspect of the present invention provides an energy feedback control system for high-voltage direct current power supply in rail transit, comprising: The information acquisition unit is used to acquire information on regenerative braking energy generated during the braking process of rail transit vehicles and the current operating status information of the high-voltage DC power supply network. The network evaluation unit is used to evaluate the energy acceptance capability of the high-voltage DC power supply network based on the current operating status information of the high-voltage DC power supply network, and obtain the network energy acceptance margin. An energy distribution unit is used to determine the distribution ratio of the regenerative braking energy between the first energy component fed back to the high-voltage DC power supply network and the second energy component transferred to the on-board energy storage device based on the regenerative braking energy information and the network energy acceptance margin, and to obtain an energy distribution command. The collaborative control unit is used to coordinate the power conversion device that feeds energy back to the high-voltage DC power supply network and the charging control device of the on-board energy storage device based on the energy distribution command. The dynamic correction unit is used to monitor the voltage fluctuation characteristics of the high-voltage DC power supply network in real time during the process of receiving the first energy component, compare the voltage fluctuation characteristics with the preset voltage stability constraints, and generate an adjustment feedback signal. The adjustment feedback signal is used to dynamically correct the allocation ratio.

[0069] A third aspect of the present invention provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0070] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0071] This invention can be a method, apparatus, system, and / or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for performing various aspects of the invention.

[0072] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for energy feedback control of rail transit high-voltage direct current power supply, characterized in that, include: Acquire information on regenerative braking energy generated during the braking process of rail transit vehicles and the current operating status information of the high-voltage DC power supply network; Based on the current operating status information of the high-voltage direct current power supply network, the energy acceptance capacity of the high-voltage direct current power supply network is evaluated to obtain the network energy acceptance margin; Based on the regenerative braking energy information and the network energy acceptance margin, the distribution ratio of the regenerative braking energy between the first energy component fed back to the high-voltage DC power supply network and the second energy component transferred to the on-board energy storage device is determined, and an energy distribution command is obtained. Based on the energy distribution command, the power conversion device that feeds energy back to the high-voltage DC power supply network and the charging control device of the on-board energy storage device are controlled in a coordinated manner. The voltage fluctuation characteristics of the high-voltage DC power supply network during the process of receiving the first energy component are monitored in real time. The voltage fluctuation characteristics are compared with preset voltage stability constraints to generate an adjustment feedback signal. The adjustment feedback signal is used to dynamically correct the allocation ratio.

2. The method according to claim 1, characterized in that, Based on the current operating status information of the high-voltage direct current (HVDC) power supply network, the energy acceptance capacity of the HVDC power supply network is evaluated to obtain the network energy acceptance margin, including: The current operating status information of the high-voltage direct current power supply network is analyzed to extract multi-dimensional state parameters characterizing the electrical operating characteristics of the high-voltage direct current power supply network; Based on the multidimensional state parameters, the transient voltage fluctuation trajectory and transient power transmission path of the high-voltage DC power supply network when receiving energy feedback are predicted, and the transient response prediction results are obtained. Based on the transient response prediction results and the operational safety constraints of the high-voltage direct current power supply network, the maximum upper limit of energy feedback power that the high-voltage direct current power supply network can accept while maintaining operational stability is calculated. The maximum energy feedback power limit is compared with the instantaneous power demand in the regenerative braking energy information to calculate the instantaneous energy acceptance margin of the high-voltage DC power supply network. Based on the time-series variation characteristics of the instantaneous energy capacity margin, the network energy capacity margin is generated through a preset margin assessment rule.

3. The method according to claim 2, characterized in that, Based on the multidimensional state parameters, the transient voltage fluctuation trajectory and transient power transmission path of the high-voltage DC power supply network during energy feedback are predicted, resulting in transient response prediction results, including: Based on the multidimensional state parameters, the equivalent circuit topology model of the high-voltage DC power supply network is determined. The equivalent circuit topology model includes topological information characterizing the electrical connection relationship between power supply sections and impedance characteristic information characterizing the electrical characteristics of each power supply section. Based on the current location information of the rail transit vehicle in the high-voltage DC power supply network, the injection node location of the energy feedback is determined in the equivalent circuit topology model. Based on the topology information, all energy transfer branch paths originating from the injection node location are traced; For each energy transmission branch path, the energy feedback power change rate in the regenerative braking energy information is used as the excitation signal input. Combined with the impedance characteristic information on the energy transmission branch path, the voltage response time series and power distribution time series of each node are calculated during the propagation of the excitation signal along the energy transmission branch path. The transient voltage fluctuation trajectory of the entire network voltage distribution of the high voltage DC power supply network over time is obtained based on the voltage response time series of all energy transmission branch paths, and the transient power transmission path is obtained based on the power distribution time series of all energy transmission branch paths.

4. The method according to claim 1, characterized in that, Based on the regenerative braking energy information and the network energy acceptance margin, the distribution ratio of the regenerative braking energy between the first energy component fed back to the high-voltage DC power supply network and the second energy component transferred to the on-board energy storage device is determined, resulting in an energy distribution command, including: The network energy acceptance margin is matched and compared with the total regenerative braking energy in the regenerative braking energy information to obtain a margin matching judgment result. The margin matching judgment result indicates whether the network energy acceptance margin is sufficient to accept the total regenerative braking energy. Based on the margin matching judgment result, the initial allocation value of the first energy component and the initial allocation value of the second energy component are determined by a preset allocation strategy rule; Obtain the current state of charge information of the vehicle-mounted energy storage device, and calculate the remaining rechargeable capacity of the vehicle-mounted energy storage device based on the current state of charge information; The feasibility of the initial allocation value of the second energy component is verified based on the remaining rechargeable capacity to obtain the energy storage capacity constraint correction coefficient; The initial allocation values ​​of the first energy component and the second energy component are corrected according to the energy storage capacity constraint correction coefficient, and the allocation ratio between the first energy component and the second energy component is calculated to obtain the energy allocation instruction.

5. The method according to claim 1, characterized in that, Based on the energy distribution command, the power conversion device that feeds energy back to the high-voltage DC power supply network and the charging control device of the on-board energy storage device are coordinated and controlled, including: The energy allocation command is parsed to extract the network feedback power command value corresponding to the first energy component and the energy storage charging power command value corresponding to the second energy component. Based on the network feedback power command value and the energy storage charging power command value, the timing coordination constraints of the dual-path energy transmission are calculated. Based on the timing coordination constraints, a network feedback power trajectory is generated for the power conversion device and an energy storage charging power trajectory is generated for the charging control device. The network feedback power trajectory and the energy storage charging power trajectory satisfy the tracking consistency with the instantaneous power change curve of the regenerative braking energy in the time dimension. The feedback power tracking error is obtained by performing a differential calculation between the network feedback power trajectory and the real-time output power of the power conversion device, and the charging power tracking error is obtained by performing a differential calculation between the energy storage charging power trajectory and the real-time output power of the charging control device. Based on the feedback power tracking error, a feedback power adjustment command is generated for the power conversion device, and a charging power adjustment command is generated for the charging control device based on the charging power tracking error. The feedback power adjustment command and the charging power adjustment command are then sent to the power conversion device and the charging control device, respectively.

6. The method according to claim 5, characterized in that, Based on the timing coordination constraints, the following steps are performed: generating a network feedback power trajectory for the power conversion device and an energy storage charging power trajectory for the charging control device, including: The timing coordination constraints are analyzed to extract the network feedback timing constraint information corresponding to the power conversion device and the energy storage charging timing constraint information corresponding to the charging control device. Based on the network feedback timing constraint information, the allowable time range and allowable rate range of power change of the power conversion device are determined, and the first energy component is mapped to the allowable time range of power change to obtain the network feedback energy time distribution; Based on the energy storage charging timing constraint information, the charging process start time node and the allowable rate range of charging power growth of the charging control device are determined, and the second energy component is mapped to the time range starting from the charging process start time node to obtain the energy storage charging time distribution. Based on the time distribution of the network feedback energy and the allowable rate range of power change, multiple network feedback power nodes are set on the time axis, and the multiple network feedback power nodes are connected to obtain the network feedback power trajectory; Based on the time distribution of the energy storage charging energy and the allowable rate range of the charging power growth, multiple energy storage charging power nodes are set on the time axis, and the multiple energy storage charging power nodes are connected to obtain the energy storage charging power trajectory.

7. The method according to claim 1, characterized in that, Real-time monitoring of voltage fluctuation characteristics of the high-voltage DC power supply network during the reception of the first energy component, comparing the voltage fluctuation characteristics with preset voltage stability constraints to generate an adjustment feedback signal, including: During the process of the power conversion device injecting the first energy component into the high-voltage DC power supply network, the instantaneous voltage values ​​of multiple monitoring nodes in the high-voltage DC power supply network are collected in real time to obtain a voltage monitoring data sequence; Time-domain analysis is performed on the voltage monitoring data sequence to extract voltage fluctuation features that characterize the voltage fluctuation state of the high-voltage direct current power supply network. The voltage fluctuation features include voltage fluctuation amplitude information and voltage fluctuation frequency information. The voltage fluctuation characteristics are compared with the voltage stability constraints, which include an upper limit for the allowable voltage fluctuation amplitude and an upper limit for the allowable voltage fluctuation frequency, to obtain the voltage stability deviation. The adjustment feedback signal is generated based on the voltage stability deviation, and the adjustment feedback signal includes power adjustment indication information for the power conversion device.

8. An energy feedback control system for high-voltage direct current power supply in rail transit, used to implement the method as described in any one of claims 1-7, characterized in that, include: The information acquisition unit is used to acquire information on regenerative braking energy generated during the braking process of rail transit vehicles and the current operating status information of the high-voltage DC power supply network. The network evaluation unit is used to evaluate the energy acceptance capability of the high-voltage DC power supply network based on the current operating status information of the high-voltage DC power supply network, and obtain the network energy acceptance margin. An energy distribution unit is used to determine the distribution ratio of the regenerative braking energy between the first energy component fed back to the high-voltage DC power supply network and the second energy component transferred to the on-board energy storage device based on the regenerative braking energy information and the network energy acceptance margin, and to obtain an energy distribution command. The collaborative control unit is used to coordinate the power conversion device that feeds energy back to the high-voltage DC power supply network and the charging control device of the on-board energy storage device based on the energy distribution command. The dynamic correction unit is used to monitor the voltage fluctuation characteristics of the high-voltage DC power supply network in real time during the process of receiving the first energy component, compare the voltage fluctuation characteristics with the preset voltage stability constraints, and generate an adjustment feedback signal. The adjustment feedback signal is used to dynamically correct the allocation ratio.

9. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1 to 7.

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