Distributed energy processing method and device, computer device and storage medium

Abstract

The present application relates to train energy processing technical field, disclose a kind of distributed energy processing method, adjacent N energy storage devices are divided, at least one management interval is determined, wherein the management interval contains at least one the energy storage device, N is non-negative integer;Determine the running state of train located in the management interval, according to the first data of the energy storage device in the management interval, determine the predicted power value of the train corresponding the running state;According to the predicted power value, the charge and discharge threshold of the energy storage device in the interval is adjusted in real time, and the energy of the energy storage device is processed.The technical scheme provided by one or more embodiments disclosed in the present application can improve the stability of the whole system by dividing the management interval of the energy storage device, and the charge and discharge threshold can be adjusted by the predicted power value, without real-time acquisition of train operation data, to reduce the difficulty of data acquisition.

Description

Technical Field

[0001] This invention relates to the field of train energy processing technology, specifically to distributed energy processing methods, devices, computer equipment, and storage media. Background Technology

[0002] With the development of urban rail transit systems, regenerative braking technology has attracted much attention. This technology can recover the energy released during train braking, providing support for economic and environmental protection. Currently, there are three main technical routes for utilizing regenerative braking energy: train timetable optimization, inverter feedback technology, and energy storage technology. However, existing methods suffer from difficulties in data acquisition and low fault tolerance in energy processing architectures, necessitating better solutions. Summary of the Invention

[0003] In view of this, the present invention provides a distributed energy processing method, apparatus, computer equipment, and storage medium to solve the problems of low system architecture fault tolerance and high difficulty in data acquisition.

[0004] This invention provides a distributed energy processing method, comprising: dividing N adjacent stations equipped with energy storage devices into at least one management section; determining the no-load voltage corresponding to each station within the management section, wherein N is a non-negative integer; determining the operating status of a train located within the management section based on the no-load voltage; determining a predicted power value of the train corresponding to the operating status based on first data of the stations within the management section; the first data being used to characterize the operating status of the stations; and adjusting the charging threshold and / or discharging threshold of the energy storage device within the management section in real time based on the predicted power value, thereby processing the energy storage device.

[0005] In another aspect, the present invention provides a distributed energy processing device, the device comprising: a partitioning module, configured to partition N adjacent stations equipped with energy storage devices, determine at least one management section, and determine the no-load voltage corresponding to each station within the management section, wherein N is a non-negative integer; a first determining module, configured to determine the operating status of a train located within the management section based on the no-load voltage; a second determining module, configured to determine a predicted power value of the train corresponding to the operating status based on first data of the stations within the management section; the first data being used to characterize the operating status of the stations; and a management module, configured to adjust the charging threshold and / or discharging threshold of the energy storage devices within the management section in real time based on the predicted power value, and to perform energy processing on the energy storage devices.

[0006] In another aspect, the present invention provides a computer device comprising: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor implements the above-described distributed energy processing method by executing the computer instructions.

[0007] In another aspect, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to implement the above-described distributed energy processing method.

[0008] In another aspect, the present invention provides a computer program product comprising computer instructions for causing a computer to execute the above-described distributed energy processing method.

[0009] In this process, by adopting a distributed architecture and dividing the energy storage device into management zones, the load on individual points is reduced, and the overall robustness and fault tolerance of the system are improved. Furthermore, by determining the predicted power value corresponding to the train's operating status and adjusting the charging and discharging thresholds of the energy storage device in real time, it is possible to reduce the difficulty of data acquisition by eliminating the need for real-time measurement of the train's operating data. Attached Figure Description

[0010] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0011] Figure 1 A schematic flowchart of a distributed energy processing method provided in an embodiment of the present invention;

[0012] Figure 2 This is a schematic diagram of the management area architecture of a distributed energy processing method provided in an embodiment of the present invention;

[0013] Figure 3 A linear fitting diagram of train power and first voltage difference for a distributed energy processing method provided in an embodiment of the present invention;

[0014] Figure 4 A strategy flowchart of a distributed energy processing method provided in an embodiment of the present invention;

[0015] Figure 5 A comparison chart of substation output energy and energy storage discharge during peak hours for a distributed energy processing method provided in an embodiment of the present invention;

[0016] Figure 6 A comparison chart of substation output energy and energy storage discharge during off-peak hours for a distributed energy processing method provided in an embodiment of the present invention;

[0017] Figure 7 This is a schematic diagram of the structure of a distributed energy processing device provided in an embodiment of the present invention;

[0018] Figure 8 This is a schematic diagram of another distributed energy processing device provided in an embodiment of the present invention. Detailed Implementation

[0019] Existing methods for handling regenerative braking energy in trains primarily involve three approaches: train timetable optimization, inverter feedback technology, and energy storage technology. While train timetable optimization requires no additional hardware, its effectiveness is significantly affected by factors such as departure intervals and passenger flow, limiting its practical application. Inverter feedback technology, though simple to control and inexpensive, suffers from the impact on the AC power grid due to the pulsed nature of train track braking energy, and the feedback of braking energy to the grid does not save on electricity costs. Energy storage technology, on the other hand, can store braking energy locally and release it during train traction, thereby reducing traction energy consumption, and is now widely used.

[0020] Currently, energy management strategies (EMS) for energy storage systems are mainly divided into three categories: EMS based on traction grid voltage, EMS based on train operating status, and EMS based on optimization algorithms.

[0021] However, the above three methods have the following problems:

[0022] First, the difficulty in obtaining real-time train operation data is due to the need to acquire such data.

[0023] Second, the existing EMS method does not fully take into account the inaccuracy of data caused by the difference in no-load voltage at different stations;

[0024] Third, existing EMS methods are mainly validated in relatively fixed simulation environments, lacking quantitative analysis and feasibility demonstration through field tests.

[0025] To address at least one of the aforementioned problems, various embodiments of the present invention provide a distributed energy processing method, comprising: dividing N adjacent stations equipped with energy storage devices into at least one management section; determining the no-load voltage corresponding to each station within the management section, wherein N is a non-negative integer; determining the operating state of a train located within the management section based on the no-load voltage; determining a predicted power value of the train corresponding to the operating state based on first data of the stations within the management section; the first data being used to characterize the operating state of the stations; and adjusting the charging threshold and / or discharging threshold of the energy storage device within the management section in real time based on the predicted power value, thereby processing the energy storage device.

[0026] 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, 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.

[0027] According to an embodiment of the present invention, a distributed energy processing method is provided. Figure 1 This is a flowchart illustrating a distributed energy processing method provided in an embodiment of the present invention, as shown below. Figure 1 As shown, the process includes the following steps:

[0028] Step S101: Divide the N adjacent stations equipped with energy storage devices, determine at least one management section, and determine the no-load voltage corresponding to each station in the management section, where N is a non-negative integer;

[0029] Step S102: Determine the operating status of the train located within the management section based on the no-load voltage;

[0030] Step S103: Determine the predicted power value of the train corresponding to the operating state based on the first data of the station within the management interval; the first data is used to characterize the operating state of the station.

[0031] Step S104: Based on the predicted power value, adjust the charging threshold and / or discharging threshold of the energy storage device within the management range in real time to perform energy processing on the energy storage device.

[0032] In one possible implementation, adjacency may include, but is not limited to, physical proximity or transmission relationship in a circuit.

[0033] In one possible implementation, the energy storage device can be used to store the electrical energy generated when the train is braking and release the electrical energy when the train is in traction to provide traction force for the train.

[0034] For example, energy storage devices may include, but are not limited to, supercapacitors, flywheels, and batteries.

[0035] In one possible implementation, no-load voltage can refer to the output voltage of the station when it is not under any load.

[0036] Here, the load can refer to the train whose power is supplied by the traction substation installed in the station.

[0037] Furthermore, a traction substation can refer to a location that converts electrical energy from a power plant via power transmission lines into a voltage suitable for the train and distributes it to the traction network; the traction network can refer to the train power supply lines erected along the train tracks.

[0038] In one possible implementation, assuming there are k traction substations equipped with energy storage devices on a train line, these energy storage devices can be labeled as (S1, S2, S3, ..., S...). k-1 S k ); The energy storage devices of N adjacent traction substations can be divided into a management section, and there can be ceil(k / N) management sections in the train line.

[0039] Furthermore, the energy processing range of each management section can be set to n. Since the transmission distance of train energy is generally 2-3km, that is, the distance between an adjacent station, the energy processing range of each management section can be set to the first one of the energy storage device installation ranges, that is, n = N + 2.

[0040] In one possible implementation, N=2 can be set so that two adjacent stations form a management zone, which manages the energy within the four adjacent station zones.

[0041] For example, with Figure 2 For example, Figure 2 This is a schematic diagram of the management area architecture of a distributed energy processing method provided in an embodiment of the present invention. i To S i+5 For six adjacent stations, all equipped with energy storage devices, let N = 2, S i+1 and S i+2 The energy storage device can be a management zone, and the management range can be S. i To S i+3 The entire interval, S i+3 and S i+4 The energy storage device can be a management zone, and the management range can be S.i+2 To S i+5 The entire interval.

[0042] In one possible implementation, the traction or braking status of a train located within the management section is determined based on the no-load voltage of two stations within the management section.

[0043] Specifically, the working status of the train's internal components is determined based on the station's no-load voltage, thus determining whether the train is in traction or braking mode.

[0044] Here, traction state can refer to the traction system providing traction power to the train. The traction system converts the DC power provided by the traction network into three-phase AC power used by the traction motor. The traction motor works as an electric motor, converting electrical energy into mechanical energy to drive the train. Braking state can refer to the traction motor acting as a generator, converting mechanical braking energy into electrical energy, feeding it back to the traction network for use by other trains or dissipating it through the braking resistor to achieve the train's braking function. The traction system can refer to the core component that provides traction and braking force to the train. The braking resistor can be used for resistance braking. When the train is in braking state, if the energy storage device cannot absorb the energy generated by braking, the energy is converted into heat energy through the braking resistor and dissipated into the atmosphere.

[0045] In one possible implementation, the first data of two stations within the management section are exchanged, and the power corresponding to the train's current state is calculated based on the first data to predict the train's power.

[0046] Here, interaction can refer to determining the first data of two stations and sending the first data of one station to the other station; the first data can characterize the corresponding operating status of the station; the first data may include, but is not limited to: the station's no-load voltage, traction network voltage and the remaining energy (State of Charge, SOC) of the energy storage device.

[0047] In one possible implementation, the energy storage device is managed by adjusting its charging and / or discharging thresholds based on the predicted power value.

[0048] Here, the charging threshold and the discharging threshold can refer to preset voltage values. When the traction grid voltage is greater than the preset charging voltage value, the energy storage device enters the charging state and stores the electrical energy in the traction grid voltage in the energy storage device. When the traction grid voltage is less than the preset discharging voltage value, the energy storage device enters the discharging state and outputs the stored electrical energy to the outside.

[0049] By dividing the energy storage device into management zones using the above method, the energy of the energy storage system can be effectively utilized, improving the overall robustness and fault tolerance of the energy processing system. Setting N=2 minimizes the energy-saving impact on the entire system when a single point of failure occurs. By predicting the power value of the train, the charging threshold and / or discharging threshold of the energy storage device can be adjusted in real time. This real-time adjustment strategy is simple and feasible, making the energy processing strategy more flexible and efficient.

[0050] In some embodiments, the method further includes:

[0051] Determine the no-load voltage corresponding to multiple stations within the management section, sort the multiple stations within the management section by load according to the magnitude of the no-load voltage of the stations, and determine the high-voltage stations and low-voltage stations within the management section based on the load sorting results.

[0052] Specifically, the no-load voltage of two stations within the management area is determined, the load of the two stations is sorted, the two no-load voltage values ​​are compared, the station with the larger no-load voltage is identified as a high-voltage station, and the station with the smaller no-load voltage is identified as a low-voltage station.

[0053] The reasons for the different no-load voltages at different stations may include, but are not limited to: different grid voltage standards, different grid loads, and different power supply line lengths.

[0054] By using the above method, considering the different no-load voltages of different stations, the stations within the management section are divided into high-voltage stations and low-voltage stations. This ensures that the energy recovered by the train does not exceed the energy that the station can bear, keeps the traction network voltage stable, and improves system stability. Adjusting the charging and discharging thresholds while taking into account the no-load voltage can avoid energy waste and improve energy recovery efficiency.

[0055] In some embodiments, determining the operating status of trains located within the management section based on the no-load voltage includes:

[0056] If the traction network voltage of a high-voltage station within the management section is greater than the no-load voltage of the high-voltage station, the train is determined to be in a braking state.

[0057] If the traction network voltage of the high-voltage station within the management section is less than or equal to the no-load voltage of the high-voltage station, the train is determined to be in traction mode.

[0058] In one possible implementation, the no-load voltage of two stations within the management section is determined, and the operating status of the train within the management section is determined based on the difference in no-load voltage between the two stations.

[0059] Specifically, it is determined whether the voltage difference between the two stations is greater than a first preset value. If the voltage difference is greater than the first preset value, the voltage difference between the two stations is determined to be large, and the train's operating status is determined according to the first determination formula. If the voltage difference is less than or equal to the first preset value, the voltage difference between the two stations is determined to be small, and the train's operating status is determined according to the second determination formula.

[0060] Here, the first determination formula can mean that if the traction network voltage of a station with a relatively high unloaded voltage is greater than the unloaded voltage minus the second preset value, then the train is in a braking state; if the traction network voltage of a station with a relatively high unloaded voltage is less than or equal to the unloaded voltage minus the second preset value, then the train is in a traction state.

[0061] The second determination formula can be that if the traction network voltage of a station with a relatively high unloaded voltage is greater than the unloaded voltage, then the train is in a braking state; if the traction network voltage of a station with a relatively high unloaded voltage is less than or equal to the unloaded voltage, then the train is in a traction state.

[0062] The first preset value can be used to determine that the voltage difference between two stations is large, and the second preset value can be used to eliminate the error caused by the large voltage difference, thereby improving the accuracy of train status judgment.

[0063] For example, the first preset value can be 40, and the second preset value can be 10.

[0064] That is, the operating status of trains within the managed section can be determined using the following formula:

[0065]

[0066] Where ΔU0 can refer to the no-load voltage difference, u s1 It can refer to the traction network voltage of stations with relatively high no-load voltage, u o1 This can refer to the unloaded voltage of a station with a relatively high unloaded voltage. When the unloaded voltage difference ΔU0 between a high-voltage station and a low-voltage station is greater than 40, if the traction network voltage is greater than the unloaded voltage of the high-voltage station minus 10, the train is in braking mode. If the traction network voltage is less than or equal to the unloaded voltage of the high-voltage station minus 10, the train is in traction mode. When the unloaded voltage difference ΔU0 between a high-voltage station and a low-voltage station is less than or equal to 40, if the traction network voltage is greater than the unloaded voltage of the high-voltage station, the train is in braking mode. If the traction network voltage is less than or equal to the unloaded voltage of the high-voltage station, the train is in traction mode.

[0067] By using the above method, by first determining whether the voltage difference between the high-voltage station and the low-voltage station is too large, and then determining whether the train is in traction or braking state based on the relationship between the traction network voltage and the voltage at no-load, the accuracy of train status determination can be improved, and the operational efficiency of energy processing can be increased.

[0068] In some embodiments, determining the predicted power value of the train corresponding to the operating state based on the first data of the stations within the management interval includes:

[0069] When the train is in a braking state, if the first data meets the first preset power condition, the predicted braking power value of the train corresponding to the braking state is determined.

[0070] When the train is in traction mode, if the first data meets the second preset power condition, the predicted traction power value of the train corresponding to the traction mode is determined.

[0071] In one possible implementation, the difference between the traction network voltage and the no-load voltage of the high-voltage station can be defined as the first voltage difference, the difference between the no-load voltage of the high-voltage station and the low-voltage station can be defined as the second voltage difference, and the difference between the braking resistor starting voltage and the no-load voltage can be defined as the third voltage difference.

[0072] Here, the braking resistor starting voltage can refer to the braking resistor starting when the traction network voltage is greater than the braking resistor starting voltage, converting excess electrical energy in the traction network into heat energy.

[0073] Specifically, when the train is in traction mode, if the second voltage difference is less than the first preset value and the first voltage difference is less than or equal to 0, the predicted traction power value of the train is determined according to the traction prediction formula; if the second voltage difference is greater than or equal to the first preset value and the first voltage difference is less than or equal to the second preset value, the predicted traction power value of the train is determined according to the traction prediction formula.

[0074] When the train is braking, if the second voltage difference is less than the first preset value and the first voltage difference is greater than 0 and less than the third voltage difference, the predicted braking power value of the train is determined according to the first braking prediction formula; if the second voltage difference is greater than or equal to the first preset value and the first voltage difference is greater than the second preset value and less than the third voltage difference, the predicted braking power value of the train is determined according to the first braking prediction formula; if the first voltage difference is greater than or equal to the third voltage difference, the predicted braking power value of the train is determined according to the second braking prediction formula.

[0075] For example, such as Figure 3 For example, Figure 3A linear fitting diagram of train power and first voltage difference for a distributed energy processing method provided in an embodiment of the present invention is shown in the figure:

[0076] When the no-load voltage of the high-voltage station is 860V, the traction power has a linear relationship with the first voltage difference when the train is in traction mode; when the train is in braking mode, due to the influence of the braking resistor starting voltage of 900V, the linear relationship between the braking power and the first voltage difference has an inflection point when the third voltage difference is 40V.

[0077] Furthermore, the predicted traction power value and the predicted braking power value can be expressed using the following formulas:

[0078]

[0079] Among them, P tr P can represent the predicted traction power value. t It can represent the predicted braking power value, ΔU s-o This can represent the first voltage difference, ΔU o This can represent the second voltage difference, ΔU r This can represent the third voltage difference. The first preset value can be 40, and the second preset value can be 10. P tr =a0|ΔU|+b0 can represent the traction prediction formula, P t =a1|ΔU|+b1 can represent the first braking prediction formula, P t =a2|ΔU|+b2 can represent the second braking prediction formula.

[0080] Here, when the second voltage difference ΔU o When the value is greater than or equal to 40, the initial value of the traction prediction formula changes accordingly because the conditions for determining whether the train is in traction or braking state change.

[0081] By using the above method, taking into account the no-load voltage, the power of the train's current state can be predicted based on easily measurable data such as the first voltage difference, the second voltage difference, and the third voltage difference. This reduces the difficulty of data acquisition, eliminates the need for train modifications, lowers data acquisition costs, and improves ease of use.

[0082] In some embodiments, adjusting the charging threshold and / or discharging threshold of the energy storage device in real time within the management range based on the predicted power value to perform energy processing on the energy storage device includes:

[0083] Determine a first initial reference value and a first change slope for the charging threshold corresponding to the energy storage device within the management interval, and / or a second initial reference value and a second change slope for the discharging threshold corresponding to the energy storage device;

[0084] If the train is in a braking state within the management section, and the management section meets the first judgment condition, the charging threshold is corrected by adjusting the first change slope.

[0085] When the train is in traction within the management section, if the management section meets the second judgment condition, the discharge threshold is corrected by adjusting the second change slope.

[0086] Specifically, the reference values ​​for braking voltage at high-voltage stations and low-voltage stations are determined for when the train is braking and for when the train is traction.

[0087] For example, the braking voltage reference values ​​for high-voltage and low-voltage stations under braking conditions are expressed by the following formula:

[0088]

[0089] Among them, U 高压 U can represent the reference value of the braking voltage at a high-voltage substation. 低压 This can represent the reference value of the braking voltage at a low-voltage station, u. o1 K1 can represent the first initial reference value, K3 can represent the first slope, and P can represent the third slope. t It can represent the predicted braking voltage.

[0090] Here, the first slope of change can include the first slope and the third slope.

[0091] Furthermore, in order to limit the maximum value of the traction network voltage without causing circulating current, the first initial reference value needs to be decreased according to the first slope and the third slope.

[0092] Circulating current can refer to the situation where, when the reference voltage of a high-voltage substation is lower than the open-circuit voltage, a voltage difference is formed between the open-circuit voltage and the reference voltage, causing the open-circuit voltage to charge the energy storage device, which reduces the energy storage device's ability to recover braking energy.

[0093] The first initial reference value can be assumed to be the no-load voltage of the high-voltage station. The initial values ​​of the first slope and the third slope can be expressed by the following formula:

[0094]

[0095] The first slope has an initial value of 0, and the third slope has an initial value related to the critical voltage that generates the circulating current, P. tmax It can represent the train's maximum designed braking power.

[0096] The following formula represents the reference values ​​of traction voltage for high-voltage and low-voltage stations under traction conditions:

[0097]

[0098] Among them, U 高压 U can represent the reference value of traction voltage at high-voltage substations. 低压 This can represent the reference value of the traction voltage at a low-voltage station, u o1 K1 can represent the first initial reference value, K2 can represent the second slope, K4 can represent the fourth slope, and P... tr It can represent the predicted traction voltage.

[0099] Here, the second slope of change can include the second slope and the fourth slope, and the initial values ​​of the second slope and the fourth slope can be 0.

[0100] In one possible implementation, when the predicted braking power is greater than the actual braking power, the reference value of the charging threshold will be too low, resulting in circulating current; when the predicted braking power is less than the actual braking power, the reference value of the charging threshold will be too high, which is not conducive to absorbing the transmission of braking power from trains at a greater distance, resulting in the traction grid voltage exceeding the braking resistor starting voltage of 900V. Since it is impossible to detect whether circulating current is generated online, while the traction grid voltage can be detected in real time, the train braking power must be predicted based on a relatively small boundary.

[0101] When the predicted traction power is greater than the actual traction power, the baseline value of the discharge threshold will be too low, making it difficult for the energy storage device to release the stored energy. When the predicted traction power is less than the actual traction power, it will affect the effect of reducing the peak traction power. Therefore, the train traction power should also be predicted based on a relatively small boundary.

[0102] In one possible implementation, when the train is in a braking state, the charging threshold is determined based on the braking voltage reference value ± hysteresis voltage value; when the train is in a traction state, the discharging threshold is determined based on the traction voltage reference value ± hysteresis voltage value.

[0103] Here, the hysteresis voltage can be used to maintain voltage stability, and the hysteresis voltage value can be 5V.

[0104] By using the above method, the predicted traction power and predicted braking power are determined, and the initial reference values ​​of high-voltage stations and low-voltage stations are adjusted according to a certain downward slope, thereby adjusting the charging threshold and discharging threshold in real time. This real-time adjustment strategy is simple and feasible, making energy processing more flexible and efficient.

[0105] In some embodiments, when the train is in a braking state within the management section, if the management section meets a first judgment condition, the charging threshold is corrected by adjusting the first change slope, including:

[0106] When the traction network voltage of the high-voltage station in the management section is greater than the predetermined voltage value and the power of the energy storage device in the management section is less than the preset charging power, the first change slope of the first initial reference value is increased by a preset ratio.

[0107] When the charging and discharging time interval of the energy storage device is less than a preset interval time, the first change slope of the first initial reference value is reduced by a preset ratio.

[0108] Specifically, the adjustment of the first slope of change can be expressed by the following formula:

[0109]

[0110] Among them, u si It can represent the traction network voltage of a high-voltage substation; 900V can represent a predetermined voltage value; P sci P can represent the power of an energy storage device. sci-rate This can represent the preset charging power, Δt. dis-ch It can represent the charging and discharging time interval of the energy storage device, 1s can represent the preset interval time, and γ1 and γ2 can represent the preset proportions of the increase and decrease of the first change slope, respectively.

[0111] Here, when the traction grid voltage is greater than 900V and the energy storage device power is less than the preset charging power, it indicates that the charging threshold is too high during braking, the energy storage device absorbs too little energy, resulting in an excessively high traction grid voltage, which causes the braking resistor to activate and wastes braking energy. Therefore, it is necessary to increase the first change slope according to γ1 and reduce the charging threshold in real time. When the charging and discharging time interval of the energy storage device is too short, it indicates that the energy storage device starts charging immediately after discharging, which means that the traction grid voltage is too low at this time, resulting in the generation of circulating current. Therefore, it is necessary to decrease the first change slope according to γ2 and increase the charging threshold in real time.

[0112] By using the above method, based on easily measurable data such as traction grid voltage, energy storage device power, and charging and discharging time intervals, the charging threshold can be adjusted in real time by adjusting the rate of change of the slope. This can increase the peak-shaving effect of the energy storage device on the traction grid voltage peak and reduce energy waste caused by excessively high traction grid voltage.

[0113] In some embodiments, when the train is in traction within the management section, if the management section meets the second judgment condition, the discharge threshold is corrected by adjusting the second change slope, including:

[0114] If the initial remaining energy of the energy storage device in the management zone at the initial moment of traction is greater than the preset energy threshold, the second change slope of the second initial reference value is reduced by a preset ratio.

[0115] When the initial remaining energy of the energy storage device is less than the preset energy threshold during M consecutive charge-discharge cycles, the second change slope of the second initial reference value is increased by a preset ratio, where M is a non-negative integer.

[0116] Specifically, the adjustment of the second slope can be expressed using the following formula:

[0117]

[0118] Among them, u o2 E can represent the traction network voltage of a low-voltage station. sci E can represent the initial remaining energy of the energy storage device at the initial moment of traction. sci-min It can represent a preset energy threshold, t cha0 The time at which charging begins can be represented, and γ3 and γ4 can represent the preset proportions of the decrease and increase of the second slope, respectively.

[0119] Here, the remaining energy of the energy storage device can be detected at each braking and charging moment. If the remaining energy is greater than the preset energy threshold, the second change slope is reduced by γ3, thereby increasing the discharge threshold and allowing the energy storage device to release more energy. If the remaining energy is less than the preset energy threshold for N consecutive cycles, it indicates that the remaining energy in the energy storage device is insufficient. In this case, the second change slope is increased by γ4, thereby reducing the discharge threshold and causing the energy storage device to reduce the discharge ratio, thus increasing the remaining energy in the energy storage device.

[0120] By measuring the initial remaining energy of the energy storage device and adjusting the discharge threshold in real time during traction using the above method, the energy storage device can release more energy during traction, thereby improving its absorption of braking energy.

[0121] Figure 4 This is a flowchart illustrating the strategy of a distributed energy processing method provided in an embodiment of the present invention. In a specific application scenario, this embodiment of the present invention involves data exchange between high-voltage and low-voltage stations. The train status is determined based on the data. If the train is in a braking state, an initial reference u is set. o1 With the initial slope K 1,3 The slope optimization module adjusts the charging threshold in real time. When the traction network voltage is greater than the charging threshold, the energy storage device is controlled to charge. If the train is in traction, an initial reference value u is set. o1 With the initial slope K 2,4 The slope optimization module adjusts the discharge threshold in real time. When the traction network voltage is less than the discharge threshold, the energy storage device is controlled to discharge.

[0122] Figure 5This is a comparison chart of substation output energy and energy storage discharge during peak hours for a distributed energy processing method provided in an embodiment of the present invention. Figure 6 A comparison chart of substation output energy and energy storage discharge during off-peak hours for a distributed energy processing method provided in an embodiment of the present invention.

[0123] In a specific application scenario, this embodiment of the invention was tested on an actual route. During the same peak or off-peak period, with 15-minute intervals, the effects of different energy handling strategies were compared. The discharge volume of the energy storage devices and the output energy of the traction substations at two stations during peak periods were statistically analyzed. Figure 5 As shown:

[0124] Groups 1 and 2 represent the substation output energy and energy storage discharge amount at station A under the application of the station's no-load voltage strategy and the interval energy processing strategy, respectively. Groups 3 and 4 represent the substation output energy and energy storage discharge amount at station B under the same strategy. Overall, the statistical results show that while station B has a larger discharge amount under the station's no-load voltage strategy, resulting in a significant reduction in substation output energy consumption, much of its charging energy comes from traction trains and substation A. This leads to issues such as inability to charge during braking, high energy conversion losses, and shorter lifespan of energy storage devices. In contrast, the distributed energy processing method provided in this embodiment of the invention ensures more reasonable charging and discharging of energy storage devices at different no-load voltage stations, resulting in a higher overall energy saving rate.

[0125] Statistics on the discharge of energy storage devices and traction energy consumption at the two stations during off-peak hours are as follows: Figure 6 As shown in the figure. Overall, the statistical results indicate that during off-peak hours, the distributed energy processing method provided in this embodiment of the invention significantly reduces the output energy consumption of traction substations for both low-voltage and high-voltage substations.

[0126] In one possible implementation, to verify the energy-saving advantages of the embodiments of the present invention over a longer timescale, the equipment at both substations is continuously connected to the grid for three days on weekdays, from 6:00 AM to 11:00 PM. On the first day, the energy storage device is not activated; on the second day, the energy storage device is activated and the station's no-load voltage strategy is used throughout the day; and on the third day, the distributed energy processing method provided in the embodiments of the present invention is employed. The energy consumption data of the traction transformer cabinets within the substations is collected daily to compare the energy-saving performance of the energy storage device.

[0127] Considering that even on weekdays, the daily traction energy consumption may vary, and since the energy transmission range of a train is generally 2-3km, we collect the energy consumption data of the traction substations at the far end of the line that are beyond the energy transmission range, and then correct the traction energy consumption of the installed energy storage devices.

[0128] The final results are shown in Table 1:

[0129] In the table, E0, E1, and E2 represent the substation output energy consumption under the following conditions: no energy storage device is in operation, using the local no-load voltage strategy, and using the distributed energy processing method, respectively. Esc1 and Esc2 represent the discharge capacity of the energy storage system under the local no-load voltage strategy and the distributed energy processing method, respectively. R1 and R2 represent the energy saving rate under the local no-load voltage strategy and the distributed energy processing method, respectively. Rv1 and Rv2 represent the voltage regulation rate under the local no-load voltage strategy and the distributed energy processing method, respectively. K1-T and K... 1-C and K1-W represent the conversion factors for station C, station D, and the combined conversion factor on the day the station's no-load voltage strategy was adopted. K2-T, K2-C, and K2-W represent the conversion factors for station C, station D, and the combined conversion factor on the day the distributed energy processing method was adopted. E0* and E0** represent the substation output energy consumption without energy storage devices after conversion using the combined conversion factor. R1* and R2* represent the energy saving rates after conversion using the station's no-load voltage strategy and the distributed energy processing method, respectively.

[0130]

[0131] E0 * =E0(1+K) 1-W )

[0132] E0 ** =E0(1+K) 2-W )

[0133]

[0134]

[0135] Table 1

[0136] The statistical data analysis in Table 1 shows that after adopting the distributed energy processing method provided in this embodiment of the invention, the system has achieved significant improvements in both energy saving rate and voltage stability.

[0137] Specifically, based on the dynamic threshold control of the station's no-load voltage, the delayed start-up of the high-voltage station's energy storage system leads to frequent activation of the braking resistor. Therefore, after applying the distributed energy processing method provided in this embodiment of the invention, the energy saving rate of the high-voltage station is significantly improved, with an increase of 5%. For the low-voltage station, since its traction energy consumption is already low before the energy storage system is put into operation, the overall energy saving rate is higher.

[0138] Furthermore, under the distributed energy processing method provided in this embodiment of the invention, the charging and discharging quantities of energy storage devices at low-voltage and high-voltage stations are similar, and the power and energy distribution is more balanced, which is more beneficial to the operating life of the energy storage devices.

[0139] Figure 7 This is a schematic diagram of the structure of a distributed energy processing device provided in an embodiment of the present invention, as shown below. Figure 7 As shown, the device can be applied to intelligent electronic devices such as servers and computers; the device includes: a division module 701, a first determination module 702, a second determination module 703, and a management module 704;

[0140] The division module 701 is used to divide N adjacent stations equipped with energy storage devices, determine at least one management section, and determine the no-load voltage corresponding to each station in the management section, where N is a non-negative integer.

[0141] The first determining module 702 is used to determine the operating status of the train located in the management section based on the no-load voltage;

[0142] The second determining module 703 is used to determine the predicted power value of the train corresponding to the operating state based on the first data of the station within the management interval; the first data is used to characterize the operating state of the station;

[0143] The management module 704 is used to adjust the charging threshold and / or discharging threshold of the energy storage device in real time within the management range according to the predicted power value, and to perform energy processing on the energy storage device.

[0144] Specifically, the device further includes: a third determining module 705;

[0145] The third determining module 705 is used to determine the no-load voltage corresponding to multiple stations within the management section, sort the multiple stations within the management section by load according to the magnitude of the no-load voltage of the stations, and determine the high-voltage stations and low-voltage stations within the management section based on the load sorting results.

[0146] Specifically, the first determining module 702 is used to determine that the train is in a braking state when the traction network voltage of the high-voltage station in the management section is greater than the no-load voltage of the high-voltage station.

[0147] If the traction network voltage of the high-voltage station within the management section is less than or equal to the no-load voltage of the high-voltage station, the train is determined to be in traction mode.

[0148] Specifically, the second determining module 703 is used to determine the predicted braking power value of the train corresponding to the braking state if the first data meets the first preset power condition when the train is in a braking state.

[0149] When the train is in traction mode, if the first data meets the second preset power condition, the predicted traction power value of the train corresponding to the traction mode is determined.

[0150] Specifically, the management module 704 is used to determine a first initial reference value and a first change slope of the charging threshold corresponding to the energy storage device within the management interval, and / or a second initial reference value and a second change slope of the discharging threshold corresponding to the energy storage device.

[0151] If the train is in a braking state within the management section, and the management section meets the first judgment condition, the charging threshold is corrected by adjusting the first change slope.

[0152] When the train is in traction within the management section, if the management section meets the second judgment condition, the discharge threshold is corrected by adjusting the second change slope.

[0153] Specifically, the management module 704 is used to increase the first change slope of the first initial reference value by a preset ratio when the traction network voltage of the high-voltage station in the management section is greater than a predetermined voltage value and the power of the energy storage device in the management section is less than a preset charging power.

[0154] When the charging and discharging time interval of the energy storage device is less than a preset interval time, the first change slope of the first initial reference value is reduced by a preset ratio.

[0155] Specifically, the management module 704 is used to reduce the second change slope of the second initial reference value by a preset ratio when the initial remaining energy of the energy storage device at the initial moment of the traction state in the management interval is greater than a preset energy threshold.

[0156] When the initial remaining energy of the energy storage device is less than the preset energy threshold during M consecutive charge-discharge cycles, the second change slope of the second initial reference value is increased by a preset ratio, where M is a non-negative integer.

[0157] It should be noted that the distributed energy processing device provided in the above embodiments is only illustrated by the division of the above-described program modules when implementing the corresponding distributed energy processing method. In practical applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program modules to complete all or part of the processing described above. In addition, the device provided in the above embodiments and the corresponding Figure 1 The embodiments of the methods shown belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0158] To implement the method of the embodiments of the present invention, the embodiments of the present invention provide a distributed energy processing device, such as... Figure 8 As shown, the device includes: a processor 801 and a memory 802 for storing computer programs capable of running on the processor; wherein,

[0159] When the processor 801 runs the computer program, it performs the following actions: dividing N adjacent stations equipped with energy storage devices into sections, determining at least one management zone, and determining the no-load voltage corresponding to each station within the management zone, where N is a non-negative integer; determining the operating status of a train located within the management zone based on the no-load voltage; determining a predicted power value for the train corresponding to the operating status based on first data of the stations within the management zone; the first data being used to characterize the operating status of the stations; and adjusting the charging threshold and / or discharging threshold of the energy storage device within the management zone in real time based on the predicted power value, thereby performing energy processing on the energy storage device. Specifically, the device can perform the following actions: Figure 1 The method shown is the same as Figure 1 The distributed energy processing method embodiments shown belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0160] In practical applications, such as Figure 8 As shown, the device may further include at least one network interface 803. The various components in the distributed energy processing device are coupled together via a bus system 804. It is understood that the bus system 804 is used to implement communication between these components. In addition to a data bus, the bus system 804 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 8 All buses are labeled as bus system 804. The number of processors 801 can be at least one. Network interface 803 is used for wired or wireless communication between the distributed energy processing device and other devices.

[0161] The memory 802 in this embodiment of the invention is used to store various types of data to support the operation of the distributed energy processing device.

[0162] The methods disclosed in the above embodiments of the present invention can be applied to or implemented by processor 801. Processor 801 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 801 or by instructions in the form of software. The processor 801 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 801 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of the present invention can be directly manifested as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, which is located in memory 802. Processor 801 reads the information in memory 802 and combines its hardware to complete the steps of the aforementioned method.

[0163] In an exemplary embodiment, the distributed energy processing device may be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers (MCUs), microprocessors, or other electronic components to perform the aforementioned method.

[0164] This invention also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it performs the following actions: dividing N adjacent stations equipped with energy storage devices into sections, determining at least one management section, and determining the no-load voltage corresponding to each station within the management section, where N is a non-negative integer; determining the operating status of a train located within the management section based on the no-load voltage; determining a predicted power value for the train corresponding to the operating status based on first data of the stations within the management section; the first data being used to characterize the operating status of the stations; and adjusting the charging threshold and / or discharging threshold of the energy storage device within the management section in real time based on the predicted power value, thereby performing energy processing on the energy storage device. Specifically, the computer program can also perform actions such as... Figure 1 The method shown is the same as Figure 1 The method embodiments shown belong to the same concept, and their specific implementation process can be found in the method embodiments, which will not be repeated here.

[0165] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods, such as: multiple units or components can be combined, or integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the various components shown or discussed can be through some interfaces, and the indirect coupling or communication connection between devices or units can be electrical, mechanical, or other forms.

[0166] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected to achieve the purpose of this embodiment according to actual needs.

[0167] In addition, in the various embodiments of the present invention, each functional unit can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the integrated unit can be implemented in hardware or in the form of hardware plus software functional units.

[0168] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0169] Alternatively, if the integrated units of this invention are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this invention, or the parts that contribute to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0170] It should be noted that terms such as "first" and "second" are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0171] Furthermore, the technical solutions described in the embodiments of this application can be combined arbitrarily without conflict.

[0172] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A distributed energy processing method, characterized in that, The method includes: Divide the N adjacent stations equipped with energy storage devices into at least one management zone, and determine the no-load voltage of each station within the management zone, where N is a non-negative integer; Based on the unloaded voltage of each station within the management section, the stations within the management section are sorted by load, and the high-voltage and low-voltage stations within the management section are determined based on the load sorting results. Determining the operating status of a train located within the management section based on the no-load voltage includes: determining the no-load voltage difference between the high-voltage station and the low-voltage station; if the no-load voltage difference is greater than a first preset value, and the traction network voltage of the high-voltage station is greater than the no-load voltage of the high-voltage station minus a second preset value, then the train is determined to be in a braking state; if the traction network voltage of the high-voltage station is less than or equal to the no-load voltage of the high-voltage station minus the second preset value, then the train is determined to be in a traction state; if the no-load voltage difference is less than or equal to the first preset value, and the traction network voltage of the high-voltage station is greater than the no-load voltage of the high-voltage station, then the train is determined to be in a braking state; if the traction network voltage of the high-voltage station is less than or equal to the no-load voltage of the high-voltage station, then the train is determined to be in a traction state. Based on the first data of the stations within the management area, the predicted power value of the train corresponding to the operating state is determined; the first data is used to characterize the operating state of the station. Based on the predicted power value, the charging threshold and / or discharging threshold of the energy storage device within the management range are adjusted in real time to process the energy of the energy storage device.

2. The method according to claim 1, characterized in that, The step of determining the predicted power value of the train corresponding to the operating state based on the first data of the stations within the management interval includes: When the train is in a braking state, if the first data meets the first preset power condition, the predicted braking power value of the train corresponding to the braking state is determined. When the train is in traction mode, if the first data meets the second preset power condition, the predicted traction power value of the train corresponding to the traction mode is determined.

3. The method according to claim 2, characterized in that, The step of adjusting the charging threshold and / or discharging threshold of the energy storage device within the management range in real time based on the predicted power value, and performing energy processing on the energy storage device, includes: Determine a first initial reference value and a first change slope for the charging threshold corresponding to the energy storage device within the management interval, and / or a second initial reference value and a second change slope for the discharging threshold corresponding to the energy storage device; If the train is in a braking state within the management section, and the management section meets the first judgment condition, the charging threshold is corrected by adjusting the first change slope. When the train is in traction within the management section, if the management section meets the second judgment condition, the discharge threshold is corrected by adjusting the second change slope.

4. The method according to claim 3, characterized in that, When the train is in a braking state within the management section, if the management section meets the first judgment condition, the charging threshold is corrected by adjusting the first change slope, including: When the traction network voltage of the high-voltage station in the management section is greater than the predetermined voltage value and the power of the energy storage device in the management section is less than the preset charging power, the first change slope of the first initial reference value is increased by a preset ratio. When the charging and discharging time interval of the energy storage device is less than a preset interval time, the first change slope of the first initial reference value is reduced by a preset ratio.

5. The method according to claim 3, characterized in that, When the train is in traction within the management section, if the management section meets the second judgment condition, the discharge threshold is corrected by adjusting the second change slope, including: If the initial remaining energy of the energy storage device in the management zone at the initial moment of traction is greater than the preset energy threshold, the second change slope of the second initial reference value is reduced by a preset ratio. When the initial remaining energy of the energy storage device is less than the preset energy threshold during M consecutive charge-discharge cycles, the second change slope of the second initial reference value is increased by a preset ratio, where M is a non-negative integer.

6. A distributed energy processing device, characterized in that, The device includes: The partitioning module is used to partition N adjacent stations equipped with energy storage devices, determine at least one management zone, and determine the no-load voltage corresponding to each station in the management zone, where N is a non-negative integer; The first determining module is used to determine the operating status of a train located within the management section based on the no-load voltage. Specifically, the first determining module is used to determine the no-load voltage difference between a high-voltage station and a low-voltage station. If the no-load voltage difference is greater than a first preset value, and the traction network voltage of the high-voltage station is greater than the no-load voltage of the high-voltage station minus a second preset value, then the train is determined to be in a braking state; if the traction network voltage of the high-voltage station is less than or equal to the no-load voltage of the high-voltage station minus the second preset value, then the train is determined to be in a traction state. If the no-load voltage difference is less than or equal to the first preset value, and the traction network voltage of the high-voltage station is greater than the no-load voltage of the high-voltage station, then the train is determined to be in a braking state; if the traction network voltage of the high-voltage station is less than or equal to the no-load voltage of the high-voltage station, then the train is determined to be in a traction state. The second determining module is used to determine the predicted power value of the train corresponding to the operating state based on the first data of the station within the management interval; the first data is used to characterize the operating state of the station. The management module is used to adjust the charging threshold and / or discharging threshold of the energy storage device within the management range in real time according to the predicted power value, and to perform energy processing on the energy storage device. The device also includes a third determining module, which is used to sort the loads of multiple stations in the management section according to the magnitude of the no-load voltage corresponding to each station in the management section, and determine the high-voltage stations and low-voltage stations in the management section based on the load sorting results.

7. A computer device, characterized in that, include: A memory and a processor are communicatively connected, the memory stores computer instructions, and the processor executes the distributed energy processing method according to any one of claims 1 to 5 by executing the computer instructions.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the distributed energy processing method according to any one of claims 1 to 5.

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