Energy monitoring method and system based on train operation trajectory

Abstract

The present application relates to the technical field of rail transit power supply control, and more particularly to an energy monitoring method and system based on train operation trajectory. The present application provides an energy monitoring method based on train operation trajectory, comprising the following steps: a data acquisition step: collecting first operation data of a train and second operation data of a power supply system based on a data alignment algorithm; a model construction step: constructing a train operation trajectory model based on the first operation data; constructing an interval power flow distribution model based on the first operation data, the second operation data and the train operation trajectory model; a human-computer interface display step: performing real-time display of an interval power flow distribution diagram based on the interval power flow distribution model by means of the acquired first real-time operation data and second real-time operation data.

Description

Technical Field

[0001] This invention relates to the field of power supply control technology for rail transit, and more specifically, to a method and system for energy monitoring based on train trajectory. Background Technology

[0002] Urban rail energy management systems are a crucial component of urban rail transit, involving the real-time monitoring and management of power supply, distribution, and consumption to ensure train operation stability and efficient energy use. While existing urban rail energy management systems have achieved some degree of monitoring and management of train operation energy, several problems remain to be addressed.

[0003] Existing urban rail energy management systems often face data synchronization issues when processing data from different subsystems. Because the large amount of data generated by train operation needs to be transmitted and processed between multiple systems, data timestamps may not match, affecting the accuracy of data analysis results. Furthermore, existing urban rail energy management systems lack intuitiveness; complex data display methods may make it difficult for operators to quickly grasp the real-time status of trains and energy flow information.

[0004] Therefore, there is an urgent need to develop an energy monitoring method and system based on train trajectory to overcome the above-mentioned defects. Summary of the Invention

[0005] This invention provides an energy monitoring method and system based on train trajectory, which at least solves the problems of poor data synchronization, insufficient real-time performance, and lack of intuitiveness in existing train energy monitoring systems.

[0006] To achieve the above objectives, the present invention provides an energy monitoring method based on train trajectory, characterized by comprising the following steps:

[0007] Data acquisition steps: Collect the first operating data of the train and the second operating data of the power supply system based on the data alignment algorithm;

[0008] Model construction steps: Construct a train trajectory model based on the first operating data; construct a section power flow distribution model based on the first operating data, the second operating data, and the train trajectory model;

[0009] Human-machine interface display steps: Based on the acquired first real-time operating data and second real-time operating data, the interval power flow distribution map is displayed in real time.

[0010] Furthermore, the data acquisition steps include:

[0011] Acquire real-time operating data of each train and power supply system, and filter operating data within a preset period based on the first timestamp corresponding to the latest data in the real-time operating data of each train.

[0012] If any train fails to acquire operational data within the preset period, the next preset period will begin acquiring operational data, and this process will continue until all train operational data is successfully acquired, at which point the second timestamp will be obtained.

[0013] The first operating data of the train and the second operating data of the power supply system are obtained based on the second timestamp.

[0014] Furthermore, the model construction steps include:

[0015] The train trajectory is obtained from the human-machine interface based on the track layout, and the coordinate information of the trajectory points is output.

[0016] Based on the first operating data, obtain the mapping relationship between the train's operating trajectory through the human-machine interface and the train's actual position and direction;

[0017] A train trajectory model is constructed based on the first running data, the trajectory point coordinate information, and the mapping relationship.

[0018] Furthermore, the model construction step further includes:

[0019] The train trajectory model is divided into several power supply zones. Based on the power supply zones, the first and second operating data are associated with the train trajectory model to complete the construction of the section power flow distribution model.

[0020] Furthermore, the first operating data of the train includes: train direction data, train time data, train position data, train current data, and train voltage data;

[0021] The second operating data of the power supply system includes: power operation data, signal subsystem operation data, and bidirectional converter equipment operation data.

[0022] Furthermore, it also includes a feedback approval step:

[0023] Based on the first and second operating data corresponding to the start and end positions of the power supply zone, it is determined whether there is a power feedback error. If there is a power feedback error, an alarm is triggered to perform error analysis.

[0024] Furthermore, the present invention provides an energy monitoring system based on train trajectory, which applies the above-mentioned energy monitoring method based on train trajectory, including:

[0025] Data acquisition module: Collects the first operating data of the train and the second operating data of the power supply system based on a data alignment algorithm;

[0026] Model building module: Constructs a train trajectory model based on the first operating data; constructs a power flow distribution model for the section based on the first operating data, the second operating data, and the train trajectory model;

[0027] Human-machine interface display module: Based on the acquired first real-time operating data and second real-time operating data, the module displays the interval power flow distribution map in real time.

[0028] Furthermore, the data acquisition module includes:

[0029] Acquire real-time operating data of each train and power supply system, and filter operating data within a preset period based on the first timestamp corresponding to the latest data in the real-time operating data of each train.

[0030] If any train fails to acquire operational data within the preset period, the next preset period will begin acquiring operational data, and this process will continue until all train operational data is successfully acquired, at which point the second timestamp will be obtained.

[0031] The first operating data of the train and the second operating data of the power supply system are obtained based on the second timestamp.

[0032] Furthermore, the model building module includes:

[0033] The train trajectory is obtained from the human-machine interface based on the track layout, and the coordinate information of the trajectory points is output.

[0034] Based on the first operating data, obtain the mapping relationship between the train's operating trajectory through the human-machine interface and the train's actual position and direction;

[0035] A train trajectory model is constructed based on the first running data, the trajectory point coordinate information, and the mapping relationship.

[0036] Furthermore, the model building module further includes:

[0037] The train trajectory model is divided into several power supply zones. Based on the power supply zones, the first and second operating data are associated with the train trajectory model to complete the construction of the section power flow distribution model.

[0038] Compared with the prior art, the advantages and positive effects of the present invention are as follows: The present invention provides an energy monitoring method and system based on train running trajectory. Through the mapping and display method of the actual running position of the train and the position of the human-machine interface, in energy systems with high real-time requirements, the train position, train energy flow information, bidirectional converter energy flow information, etc. can be displayed in real time, effectively improving the intuitiveness and on-site control of urban rail energy management.

[0039] This invention uses an alignment algorithm based on train data for data acquisition, which can effectively solve the problem of timestamp alignment of data sections from multiple train subsystems, improve data validity, provide reliable section data for subsequent applications, and enhance the accuracy and effectiveness of energy monitoring systems based on train operation trajectories. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the energy monitoring method based on train trajectory according to the present invention;

[0041] Figure 2 This is a schematic diagram of the cross-section data alignment algorithm based on train data according to an embodiment of the present invention;

[0042] Figure 3 This is a schematic diagram of the train trajectory calculation process according to an embodiment of the present invention;

[0043] Figure 4 This is a schematic diagram of the energy feedback approval process according to an embodiment of the present invention;

[0044] Figure 5 This is a schematic diagram of the energy monitoring system based on train trajectory according to the present invention.

[0045] In the above image:

[0046] 100. Data acquisition module; 200. Model building module; 300. Human-computer interface display module. Detailed Implementation

[0047] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0048] In the description of this application, it should be understood that the terms "center," "upper," "lower," "front," "rear," "left," "right," "vertical," "level," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0049] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0050] Example 1

[0051] like Figure 1 As shown, the present invention provides an energy monitoring method based on train trajectory, comprising the following steps:

[0052] Data acquisition step S100: Acquire the first operating data of the train and the second operating data of the power supply system based on the data alignment algorithm;

[0053] Model construction step S200: Construct a train trajectory model based on the first operating data; construct a section power flow distribution model based on the first operating data, the second operating data, and the train trajectory model;

[0054] Human-machine interface display step S300: Based on the acquired first real-time running data and second real-time running data, the interval power flow distribution map is displayed in real time.

[0055] The following is combined Figures 2-4 This document details each step of the energy monitoring method based on train trajectory.

[0056] Preferably, the data acquisition step S200 includes:

[0057] Acquire real-time operating data of each train and power supply system, and filter operating data within a preset period based on the first timestamp corresponding to the latest data in the real-time operating data of each train.

[0058] If any train fails to acquire operational data within the preset period, the next preset period will begin acquiring operational data, and this process will continue until all train operational data is successfully acquired, at which point the second timestamp will be obtained.

[0059] The first operating data of the train and the second operating data of the power supply system are obtained based on the second timestamp.

[0060] like Figure 2 As shown, in some embodiments, the specific process of the above-mentioned cross-section data alignment algorithm based on train data is as follows:

[0061] Retrieve the latest data T1DT from each train's cache m1 T2DT m1 ,…,T n DT m1 ; Calculate and extract the latest data T from each train's data based on the timestamp. x DT m1 According to the latest data T x D's timestamp T m1 Calculate the T value between each train's buffer and train X in sequence. m1 The time tolerance is within T200. Data from each train within a 200ms time tolerance is retrieved. If a train fails to acquire data within the tolerance time, the cross-section acquisition is considered a failure, and the process proceeds to the next cycle. If the train cross-section acquisition is successful, the cross-section data timestamp is T. x DT m1 Train data is {T1DT} mx T2DT mx ,…,T x DT m1 ,…,T n DT mx}; Based on the data timestamp DT of train X m1 The process sequentially calculates and acquires cross-sectional data for the power supply, signaling subsystems, and bidirectional converter equipment. If the calculation is successful, the cross-sectional data acquisition for that cycle is successful; otherwise, it proceeds to the next cross-sectional data calculation and acquisition cycle. The final timestamp is T. x DT m1D The cross-sectional data set of each subsystem and device is {D1, D2, ..., D...} n}

[0062] Preferably, the model building step S200 includes:

[0063] The train's trajectory is obtained from the track layout and the coordinates of the trajectory points are output. Specifically, the train's trajectory is drawn based on the track layout, including both upward and downward trajectories, and the positions of stations on the human-machine interface graphic are clearly defined. The train's trajectory can only consist of straight lines. After drawing, the starting point of the trajectory, the intersection points of each straight line, and the location information of the stations are output.

[0064] Based on the first operational data, the mapping relationship between the train's trajectory in the human-machine interface and the train's actual position and direction is obtained; specifically, the actual operating position and direction information of the train corresponding to the starting point, handover point, and station in the human-machine interface are obtained.

[0065] A train trajectory model is constructed based on the initial operating data, trajectory point coordinate information, and mapping relationships.

[0066] like Figure 3 As shown, in some embodiments, the train trajectory algorithm is specifically as follows:

[0067] Obtain train direction information from real-time train data; parse the train trajectory model and filter train trajectory data with the same direction; store it in the train trajectory calculation cache; iterate through the train trajectory calculation cache, retrieving the Kth and K+1th trajectory data from the beginning of the data; retrieve the train's current position information and determine if the current position matches the position of the Kth trajectory data. If so, retrieve the corresponding X / Y coordinate trajectory data of the train's human-machine interface; if not, calculate whether the current position Poscur matches the (K+1)th position POSK+1. If so, retrieve the corresponding human-machine interface trajectory data of the train. The system retrieves the trajectory data of the train's X / Y coordinates. If not, it calculates whether the current position is before position K and K+1. If so, it calculates the X / Y coordinates using the algorithm (((current position - position K)) / ((position K+1 - position K)))*(X / Y coordinates of the human-machine interface corresponding to position K+1 - X / Y coordinates of the human-machine interface corresponding to position K), and returns the trajectory data of the train's corresponding human-machine interface X / Y coordinates. If not, it increments K and loops through the calculation. If the train's coordinates are still not found when the calculation reaches the last position, the system cannot calculate the train's trajectory and sets the train to a hidden state in the human-machine interface.

[0068] Preferably, the model building step S200 further includes:

[0069] The train trajectory model is divided into several power supply zones. Based on the power supply zones, the first and second operating data are associated with the train trajectory model to complete the construction of the section power flow distribution model.

[0070] Specifically, the inter-station power flow distribution model can display real-time current data, inflow and outflow directions of the train in each power supply zone, real-time current data, inflow and outflow directions of the bidirectional converter equipment, and substation operating status based on the train's running trajectory.

[0071] Preferably, the first operating data of the train includes: train direction data, train time data, train position data, train current data, and train voltage data;

[0072] The second set of operating data for the power supply system includes: power operation data, signal subsystem operation data, and bidirectional converter equipment operation data.

[0073] Preferably, it further includes an energy feedback approval step:

[0074] Based on the first and second operating data corresponding to the start and end positions of the power supply zone, it is determined whether there is a power feedback error. If there is a power feedback error, an alarm is triggered to perform error analysis.

[0075] like Figure 4 As shown, in some embodiments, the energy feedback approval step specifically includes:

[0076] A certain power supply zone G i The starting position of the coordinates is (XG) i Starting with YG i The start and end positions are (XG) i Finally, YG i (Finally), collect the power supply current I of N trains in both the up and down directions. CR1 I CR2 …I CRN The sum of I CRT N trains can feed current I CK1 I CK2 …I CKN The sum of I CKT The feeder current I of the two bidirectional converters in this power supply zone was collected. SR1 I SR2 The power supply current for this power supply zone is calculated as: I SR1 +I sR2 =I SR I can be obtained from the calculation. CRT =I SR The received power feed current I from two bidirectional converters in this power supply zone is collected. SK1 I SK2 Calculate the received energy feed current of this power supply zone as I. SK1 +I SK2 =I SK I can be obtained from the calculation. CKT =I SKIf the calculation satisfies the above formula, the real-time current value, flow direction, and outflow direction of the bidirectional converter will be displayed on the human-machine interface; otherwise, an alarm will be generated.

[0077] Human-machine interface display step S300: Based on the acquired first and second real-time operating data, the section power flow distribution map is displayed in real time using the section power flow distribution model. Specifically, this includes: train operating energy flow and trajectory, bidirectional converter equipment energy flow, and substation operating status.

[0078] Example 2

[0079] like Figure 5 As shown, the present invention provides an energy monitoring system based on train trajectory, which applies the above-mentioned energy monitoring method based on train trajectory, including:

[0080] Data acquisition step 100: Acquire the first operating data of the train and the second operating data of the power supply system based on the data alignment algorithm;

[0081] Model construction step 200: Construct a train trajectory model based on the first operating data; construct a section power flow distribution model based on the first operating data, the second operating data, and the train trajectory model;

[0082] Human-machine interface display step 300: Based on the acquired first real-time running data and second real-time running data, the interval power flow distribution map is displayed in real time.

[0083] Preferably, the data acquisition module 100 includes:

[0084] Acquire real-time operating data of each train and power supply system, and filter operating data within a preset period based on the first timestamp corresponding to the latest data in the real-time operating data of each train.

[0085] If any train fails to acquire operational data within the preset period, the next preset period will begin acquiring operational data, and this process will continue until all train operational data is successfully acquired, at which point the second timestamp will be obtained.

[0086] The first real-time operation data of the train and the second real-time data of the power supply system are obtained based on the second timestamp.

[0087] Preferably, the model building module 200 includes:

[0088] The train trajectory is obtained from the human-machine interface based on the track layout, and the coordinate information of the trajectory points is output.

[0089] Based on the first operational data, the mapping relationship between the train's trajectory through the human-machine interface and the train's actual position and direction is obtained;

[0090] A train trajectory model is constructed based on the initial operating data, trajectory point coordinate information, and mapping relationships.

[0091] Preferably, the model building module 200 further includes:

[0092] The train trajectory model is divided into several power supply zones. Based on the power supply zones, the first real-time operation data and the second real-time operation data are associated with the train trajectory model to complete the construction of the section power flow distribution model.

[0093] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments for application in other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. An energy monitoring method based on train trajectory, characterized in that, Includes the following steps: Data acquisition steps: Collect the first operating data of the train and the second operating data of the power supply system based on the data alignment algorithm; Model construction steps: Construct a train trajectory model based on the first operating data; construct a section power flow distribution model based on the first operating data, the second operating data, and the train trajectory model; Human-machine interface display steps: Based on the acquired first real-time operating data and second real-time operating data, the interval power flow distribution map is displayed in real time. The data acquisition steps include: Acquire real-time operating data of each train and power supply system, and filter operating data within a preset period based on the first timestamp corresponding to the latest data in the real-time operating data of each train. If any train fails to acquire operational data within the preset period, the next preset period will begin acquiring operational data, and this process will continue until all train operational data is successfully acquired, at which point the second timestamp will be obtained. The first operating data of the train and the second operating data of the power supply system are obtained based on the second timestamp. The model construction steps include: The train trajectory is obtained from the human-machine interface based on the track layout, and the coordinate information of the trajectory points is output. Based on the first operating data, obtain the mapping relationship between the train's operating trajectory through the human-machine interface and the train's actual position and direction; A train trajectory model is constructed based on the first running data, the trajectory point coordinate information, and the mapping relationship.

2. The energy monitoring method based on train trajectory according to claim 1, characterized in that, The model construction steps further include: The train trajectory model is divided into several power supply zones. Based on the power supply zones, the first and second operating data are associated with the train trajectory model to complete the construction of the section power flow distribution model.

3. The energy monitoring method based on train trajectory according to claim 1, characterized in that, The first operating data of the train includes: train direction data, train time data, train position data, train current data, and train voltage data; The second operating data of the power supply system includes: power operation data, signal subsystem operation data, and bidirectional converter equipment operation data.

4. The energy monitoring method based on train trajectory according to claim 2, characterized in that, It also includes an energy feed approval step: Based on the first and second operating data corresponding to the start and end positions of the power supply zone, it is determined whether there is a power feedback error. If there is a power feedback error, an alarm is triggered to perform error analysis.

5. An energy monitoring system based on train trajectory, characterized in that, The method for implementing energy monitoring based on train trajectory as described in any one of claims 1-4 includes: Data acquisition module: Collects the first operating data of the train and the second operating data of the power supply system based on a data alignment algorithm; Model building module: Constructs a train trajectory model based on the first operating data; constructs a power flow distribution model for the section based on the first operating data, the second operating data, and the train trajectory model; Human-machine interface display module: Based on the acquired first real-time operating data and second real-time operating data, the module displays the interval power flow distribution map in real time using the interval power flow distribution model. The data acquisition module includes: Acquire real-time operating data of each train and power supply system, and filter operating data within a preset period based on the first timestamp corresponding to the latest data in the real-time operating data of each train. If any train fails to acquire operational data within the preset period, the next preset period will begin acquiring operational data, and this process will continue until all train operational data is successfully acquired, at which point the second timestamp will be obtained. The first operating data of the train and the second operating data of the power supply system are obtained based on the second timestamp. The model building module includes: The train trajectory is obtained from the human-machine interface based on the track layout, and the coordinate information of the trajectory points is output. Based on the first operating data, obtain the mapping relationship between the train's operating trajectory through the human-machine interface and the train's actual position and direction; A train trajectory model is constructed based on the first running data, the trajectory point coordinate information, and the mapping relationship.

6. The energy monitoring system based on train trajectory according to claim 5, characterized in that, The model building module further includes: The train trajectory model is divided into several power supply zones. Based on the power supply zones, the first and second operating data are associated with the train trajectory model to complete the construction of the section power flow distribution model.

Images