An OLTC-based railway vehicle network system full-period stability optimization method

Abstract

The application discloses a kind of railway car network system full-time period stability optimization methods based on OLTC, specifically for: the data of planning railway car network system is collected, then, train operation diagram is divided into multiple time points, the position, quantity, operating power and operating condition of vehicle in system are determined at each specified time point;Based on multi-vehicle co-network system stability analysis method, the stability of car network system under all time points is analyzed in turn;Based on the stability analysis result of multi-vehicle co-network system, the OLTC tap position is adjusted, and the stability of car network system is re-evaluated until all car network systems meet the stability margin requirement at all times;Test on hardware-in-the-loop platform to evaluate the stability of railway car network system.The algorithm of the application is simple, low in cost, and improves the stability of the system.

Description

Technical Field

[0001] This invention belongs to the field of rail transit traction power supply system, and particularly relates to a method for all-time stability optimization of railway vehicle network system based on OLTC. Background Technology

[0002] With the rapid development of high-speed electrified railways, more and more traction power electronic converters are being connected to the railway network system. Especially when multiple cars simultaneously raise their pantographs to connect to the traction network, low-frequency oscillation (LFO) often occurs. This can lead to traction lockout because the traction network voltage and current may oscillate at 2Hz for an extended period. A schematic diagram of the network system structure under multi-car shared network conditions and the LFO waveform occurring on actual lines are shown below. Figure 1 As shown.

[0003] To elucidate the mechanism of oscillations in railway vehicle-network systems, existing research has established various vehicle impedance models in different coordinate systems, and impedance-based frequency domain stability analysis has been widely discussed. However, these models can only be linearized at a single operating point and cannot capture changes in vehicle impedance distribution as the operating point changes. To overcome this limitation, it is necessary to evaluate the system's stability over a wide range of operating points. Impedance models based on the vehicle-network system are used, employing different stability analysis methods, such as the forbidden zone criterion, the Generalized Nyquist Stability Criterion (GNSC), and Bode plots, to evaluate system stability. However, these studies only consider the integration of vehicles and the traction network at a single point of connection (PoC), neglecting the line impedance or autotransformer impedance between different vehicles.

[0004] To optimize the stability of railway vehicle network systems, two widely used methods exist: (1) using advanced vehicle traction converter control technology to eliminate the negative damping characteristics of vehicle impedance. However, the algorithmic complexity of this method may make it difficult to apply to traction converter controllers. (2) modifying the impedance characteristics of the traction power supply system by increasing the capacity of the traction transformer or installing active compensation devices in the traction substation. However, this method is expensive and is generally limited to hub-type traction substations.

[0005] The technical problem addressed by this invention is the oscillation issue caused by electrical mismatch between the Electric Multiple Unit (EMU) and the traction network. Due to the numerous operating points and varied operating modes of the EMU, ensuring stability between the EMU and the traction network is challenging. Current methods, such as utilizing advanced controllers or adding active compensation devices, while effectively improving system stability, suffer from high algorithm complexity or cost, hindering widespread application. Summary of the Invention

[0006] To address the aforementioned problems, this invention provides a method for optimizing the stability of a railway vehicle network system throughout all time periods based on an on-load tap changer (OLTC).

[0007] The present invention provides a method for all-time stability optimization of a railway vehicle network system based on OLTC, comprising the following steps:

[0008] Step 1: Collect data on the planned railway network system, including the railway power supply system, vehicle characteristics, and system operating conditions; then, divide the train operation schedule into multiple time points, and at each specified time point, determine the location, quantity, operating power, and operating conditions of the vehicles in the system.

[0009] Step 2: Based on the stability analysis method of multi-vehicle network system, analyze the stability of the vehicle network system at all time points in sequence; if the system is stable, complete the system stability assessment at that time point and execute the stability analysis at the next time point; otherwise, record the stability results at that time point and execute Step 3.

[0010] Step 3: Based on the stability analysis results of the multi-vehicle network system, adjust the OLTC tap position and re-evaluate the stability of the vehicle network system until all vehicle network systems meet the stability margin requirements at all times.

[0011] Step 4: Conduct tests on the hardware-in-the-loop platform to evaluate the stability of the railway vehicle network system.

[0012] Furthermore, step 2 specifically involves:

[0013] S2.1 divides the railway vehicle network system into active and passive subsystems through multiple vehicle access nodes; for the passive subsystem, the impedance matrix Z of the traction network subsystem is constructed based on the track distance between different vehicles. NS For active subsystems, based on the vehicle's operating point, the vehicle admittance is modeled or measured in the dq coordinate system, and the vehicle subsystem admittance matrix Y is constructed. VS .

[0014] S2.2 Establish the system back-comparison matrix L of the two subsystems rThe system stability was analyzed using GNSC; if the system stability margin met the operational requirements, the system stability analysis at that time point was completed; then, the system stability at the next time point was analyzed based on the train operation diagram; otherwise, if L r If there are unstable or critically stable eigenvalue trajectories, it is necessary to optimize the system stability by changing the OLTC tap position.

[0015] Furthermore, step 3 specifically involves:

[0016] S3.1 Determine the current OLTC tap position. Based on the system power flow analysis results, identify the lowest and highest voltage nodes for vehicles in the system to ensure that the vehicle voltage does not exceed its maximum or minimum operating voltage range.

[0017] S3.2 Based on the relationship between vehicle operating power, grid-side voltage and system stability, gradually increase the current OLTC tap position.

[0018] S3.3 Reassess the stability of the vehicle network system at this point in time and observe whether the system is stable at this time. If the system stability margin still does not meet the requirements, continue to gradually increase the current OLTC tap position and repeat the stability analysis until the system is stable at this point in time.

[0019] The beneficial technical effects of this invention are as follows:

[0020] The stability analysis method and stability margin index of the multi-vehicle access vehicle network system proposed in this invention can accurately analyze the system stability of vehicles at multiple operating points and with various vehicle configurations, and can evaluate the stability of the vehicle network system at all times based on the driving operation diagram.

[0021] The proposed method for enhancing the stability of railway vehicle network system based on optimizing the position of the OLTC tap is to increase the traction network voltage and change the impedance characteristics of the vehicle simply by adjusting the position of the OLTC tap position, thereby improving system stability.

[0022] This invention presents a case study on the stability of a multi-car network system based on actual railway train operation schedules, and verifies the effectiveness of the proposed method through hardware-in-the-loop analysis. This analysis reveals the causes and mechanisms of low-frequency oscillations in multi-car network systems and helps in developing effective suppression measures. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of a multi-car railway network system.

[0024] Figure 2This is the actual operation arrangement of the railway network system on the line. (a) Train operation diagram; (b) Changes in vehicle operating conditions and power at different locations on the line.

[0025] Figure 3 This is the equivalent circuit diagram of the railway vehicle network system at a certain moment.

[0026] Figure 4 This is an equivalent block diagram of the vehicle-to-everything (V2X) system.

[0027] Figure 5 The results show the stability analysis of the railway vehicle network system at multiple vehicle operating points. (a) Three-dimensional stability results diagram; (b) Stability boundary diagram; (c) Critical stability results.

[0028] Figure 6 The results show the stability analysis of the railway network system under multi-car mixed operation. (a) Three-dimensional stability result diagram; (b) Stability boundary diagram; (c) Critical stability results.

[0029] Figure 7 This relates the output voltage of the OLTC to the tap position.

[0030] Figure 8 A flowchart for optimizing the stability of a railway vehicle network system based on OLTC.

[0031] Figure 9 This presents the stability analysis and optimization results of the railway vehicle network system at multiple time points.

[0032] Figure 10 The waveforms of the vehicle's grid-side voltage, current, and DC-side voltage are shown in Cases 1-6. (a) Case 1; (b) Case 2; (c) Case 3; (d) Case 4; (e) Case 5; (f) Case 6. Detailed Implementation

[0033] The present invention will be further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0034] This invention presents a full-time stability optimization method for railway vehicle network systems based on OLTC (Optimal Traction Control Center), revealing the influence mechanism of vehicle operating point, operating condition, and power on system stability. Furthermore, it proposes a novel method to improve the stability of the railway vehicle network system by optimizing the tap position of the OLTC, which alters the vehicle's impedance characteristics by increasing the traction network voltage. Finally, to verify the effectiveness of the proposed stability analysis and optimization method, a case study of a multi-vehicle network system was designed based on actual railway train operation diagrams, validating the accuracy of the theoretical analysis results on a hardware-in-the-loop platform. The specific steps include:

[0035] Step 1: Collect data on the planned railway network system, including the railway power supply system (traction substations, traction network), vehicle characteristics (vehicle type, number of vehicles, etc.), and system operating conditions (train timetable, power supply arrangement). To account for changes in vehicle operating points as vehicles travel, the train timetable is divided into multiple time points (m in total). At each specified time point, the location, number, operating power, and operating conditions of vehicles in the system are determined, such as... Figure 2 As shown.

[0036] Step 2: Based on the stability analysis method of multi-vehicle network system, analyze the stability of the vehicle network system at all time points in sequence; if the system is stable, complete the system stability assessment at that time point and execute the stability analysis at the next time point; otherwise, record the stability results at that time point and execute Step 3.

[0037] At time t i The equivalent circuit of the vehicle-to-everything (V2X) system is as follows: Figure 3 As shown, based on the location of the connected vehicles, the vehicle-to-everything (V2X) system can be divided into a source-side traction network subsystem and a load-side vehicle subsystem. Node i represents the location of the i-th vehicle connected to the network, Z... i (i = 1, 2, ..., n) represents the traction network impedance between node i-1 and node i, and the input voltage and current of the i-th vehicle are represented by u. i and i i express.

[0038] according to Figure 3 The following relationship can be derived.

[0039]

[0040] In the formula, u g Z represents the secondary voltage of the traction transformer. g This represents the equivalent impedance of the traction substation.

[0041] Then, the above equation can be transformed into the dq coordinate system to derive the corresponding small-signal model. In the dq coordinate system, the multi-order network impedance matrix Z... NS as follows:

[0042]

[0043] in, It is the input voltage vector. It is the input current vector. Z gdq This represents the equivalent impedance of the traction substation under the DQ framework.

[0044] Similarly, the admittance matrix of the vehicle-side subsystem can be constructed as follows.

[0045]

[0046] In the formula, Y Vndq Let DQ represent the vehicle's admittance, where n represents the nth vehicle.

[0047] Both the traction network and the vehicle subsystem have DQ impedance models of order 2n, where n depends on the number of nodes connected to the vehicle system. Figure 4 This represents an interconnected multivariable feedback system, where the traction network voltage u gdq (s) is the input, and the network current i dq (s) is the output. The closed-loop transfer matrix of the system can be expressed as:

[0048] G ui =Y VS (I 2n +Z NS Y VS ) -1

[0049] Among them, L r =Z NS Y VS Defined as the impedance return ratio matrix of the system, I 2n It is a 2n-order identity matrix.

[0050] Furthermore, the generalized Nyquist criterion can be used to analyze the stability of the vehicle-network system. When L rotates counterclockwise around the point (-1,j0)... r The number of cycles of all characteristic root trajectories is equal to L r The system is stable when the number of poles in the right half-plane is zero. Since the source subsystem and load subsystem are stable when operating independently, Z... NS and Y VS The number of poles in the right half-plane is zero, therefore L r The number of extrema in the right half-plane is also zero. At this point, the stability condition of the vehicle-to-network system is that all L... r The characteristic root locus rotates counterclockwise around the point (-1, j0) zero times. Furthermore, to visualize the impact of the vehicle's operating point on system stability, the minimum value X of the intersection point of the characteristic root locus and the real axis is used. min Defined as the system stability margin. If the eigenvalue locus contains the point (-1, j0), then X... min A value less than -1 indicates that the system is unstable. Conversely, if X... min If the value is greater than -1, then the characteristic root locus does not contain the point (-1,j0), indicating that the system is stable.

[0051] Based on the proposed vehicle-to-everything (V2X) system stability analysis method and stability margin index, the impact of multiple operating points and vehicle configurations on system stability was studied. Figure 5 In (a), the vehicle operating power P and the line-side voltage E are recorded.in The stability of the vehicle-to-grid system was studied when the power output varied between -720kW and 720kW and between 1800V and 2000V. To better observe the system stability boundaries and critical stability conditions, Figure 5 The stability characteristic diagram in (a) can be projected onto X. min = on the -1 plane. When X min A stable region greater than -1 is visible; otherwise, an unstable region will dominate. Any deviation of the vehicle's operating point from this boundary can affect the system's stability. For example, ... Figure 5 As shown in (b), if E in Fixed at 1870V, the vehicle's operating power should not exceed 129.6kW to maintain system stability. Furthermore, Figure 5 (b) indicates that the larger line-side voltage E in Lower vehicle operating power P contributes to improved system stability. Furthermore, the vehicle's stability performance under regenerative braking conditions surpasses that under traction conditions. Therefore, modifying the traction network voltage by changing the OLTC tap position, thereby optimizing the vehicle's impedance characteristics, is a practical method for improving system stability, which will be discussed in detail in the next step.

[0052] Figure 6 The results show that the system's stability margin changes as the number of vehicles varies between traction and standby conditions. If the number of vehicles in the standby condition is constant, increasing the number of vehicles in the traction condition leads to a gradual decrease in the system's stability margin. Similarly, if the number of vehicles in the traction condition is constant, system stability decreases as the number of vehicles in the standby condition increases. Furthermore, vehicles in the traction condition have a greater impact on system stability than vehicles in the standby condition. (This is achieved by...) Figure 6 (a) Mapping to X min The plane with a value of -1 can be obtained. Figure 6 (b) reveals the stability boundaries of the system under various vehicle configurations. If all three vehicles are in a stationary, ready-to-go condition, the number of vehicles in the traction condition should not exceed two to ensure system stability. Figure 6 In (c), we further analyzed the system stability results under the critically stable vehicle configuration, where four vehicle access nodes need to be considered. Based on the backpropagation matrix, the system model order is 8, resulting in 8 eigenvalue trajectories in the stability analysis. However, only eigenvalue trajectory 1 has a significant impact on system stability because it is closest to the critical point (-1, j0).

[0053] Step 3: When the vehicle-to-grid system becomes unstable or critically unstable at a certain point in time, adjust the OLTC tap position based on the stability analysis results of the multi-vehicle shared network system, and re-evaluate the stability of the vehicle-to-grid system until all vehicle-to-grid systems meet the stability margin requirements at all times.

[0054] like Figure 7 As shown, the output voltage of the OLTC can be adjusted by changing the tap position T, which has an adjustable range of 2kΩ. The OLTC controller adjusts the output voltage u according to the desired output voltage. k Switch the tap position to adjust the traction network voltage.

[0055] according to Figure 7 The control functions of OLTC are as follows:

[0056]

[0057] Where g(u) i ) is the OLTC control function, where k represents the OLTC speed setting. The OLTC has a total of 2k speed settings. When adjusted to the k-th speed setting, the OLTC output voltage u is at u... oltc_k ~u oltc_k+1 Within the range.

[0058] Figure 8 This paper demonstrates the process of optimizing railway vehicle network system stability based on OLTC (On-Line Traction Control), including three main steps: system data collection, system stability analysis, and OLTC-based system stability optimization. In step 3, the current location of the OLTC tap changer is first determined. Next, based on the system power flow analysis results, the lowest and highest voltage nodes of the vehicles in the system are found to ensure that the vehicle voltage does not exceed its maximum or minimum operating voltage range. Then, based on the relationship between vehicle operating power, network-side voltage, and system stability (e.g., ...), the optimization is performed on the OLTC-based system stability. Figure 5 (b) As shown, the tap position of the currently operating OLTC is gradually increased. This causes the traction network voltage to change accordingly with the change in the OLTC tap position, thus affecting the vehicle input voltage in the system. At this time, the vehicle's operating point changes, leading to changes in the vehicle's impedance characteristics and system stability. Finally, the vehicle-to-network system stability at this point in time is reassessed, and it is observed whether the system is stable. If the system stability margin still does not meet the requirements, the tap position of the currently operating OLTC is gradually increased, and the stability analysis is repeated until the system stabilizes at this point in time.

[0059] Step 4: Conduct tests on the hardware-in-the-loop platform to evaluate the stability of the railway vehicle network system.

[0060] according to Figure 2 The 15 time points divided in (a) Figure 9The stability and optimization results of the vehicle-to-everything (V2X) system at multiple time points are presented. The results show that at t5, t6, t7, and t... 11 At these times, the system becomes unstable due to the large number of vehicles in the system, most of which are under high-power traction conditions. To address the instability at these times, the OLTC tap position is adjusted upwards by three positions at t5 and t7, and upwards again at t6 and t7. 11 Adjusting the OLTC gear positions upwards by four levels increased the traction network voltage by 7.5% and 10%, respectively. Subsequently, system power flow calculations were performed to assess the voltage of each vehicle in the system and to evaluate system stability. The results show that optimizing the OLTC gear positions improved system stability at all four time points, transitioning the system from an unstable to a stable region.

[0061] To verify the stability analysis and optimization methods of the vehicle-to-everything (V2X) system at different time points, we provide the following six case studies. Case studies 1-3 aim to verify the stability analysis results of the V2X system at different time points, while cases studies 4-6 aim to demonstrate the effectiveness of the stability enhancement method based on optimizing the OLTC tap position.

[0062] Case 1: Vehicle network system configuration at time point t5, where the power of the five vehicles are 720kW, 720kW, 720kW, 450kW and -720kW respectively.

[0063] Case 2: Vehicle network system configuration at time point t6, where the power of the five vehicles are 720kW, 700kW, 400kW, 10kW and 10kW respectively.

[0064] Case 3: Vehicle-to-everything (V2X) system configuration at time point t7, where the power of the five vehicles are 720kW, 720kW, 720kW, -100kW and 200kW respectively.

[0065] Case 4: Based on Case 1, the position of the OLTC tap changer was raised by three stops, resulting in a 7.5% increase in traction network voltage.

[0066] Case 5: Based on Case 2, the position of the OLTC tap changer was raised by four stops, resulting in a 10% increase in traction network voltage.

[0067] Case 6: Based on Case 3, the position of the OLTC tap changer was raised by three stops, resulting in a 7.5% increase in traction network voltage.

[0068] Figure 10Figures (a)-(f) show the results of hardware-in-the-loop platform testing of the vehicle-to-everything (V2X) systems in Cases 1-6. These figures illustrate the waveforms of the AC side voltage and current of the vehicles, as well as the DC circuit voltage. When multiple vehicles are connected sequentially, the oscillation amplitude and frequency of the DC circuit voltage can be used to observe system stability. Figure 10 In (a)-(c), it can be seen that the system voltage oscillates with different amplitudes and frequencies below 2Hz, indicating system instability and exhibiting typical low-frequency oscillation characteristics. These waveform results are consistent with the stability analysis results, verifying the accuracy of the stability analysis method. Furthermore, to improve system stability, we increased the traction network voltage by changing the position of the OLTC tap changer. In Cases 1 and 3, the results after increasing the traction network voltage by 7.5% are as follows: Figure 10 As shown in (d) and (f), it can be observed that increasing the traction grid voltage improves system stability and reduces the amplitude of the oscillation voltage. In Case 2, the result after increasing the traction grid voltage by 10% is as follows... Figure 10 As shown in (e), the system stability has been improved.

Claims

1. A method for all-time stability optimization of a railway vehicle network system based on OLTC, characterized in that, Includes the following steps: Step 1: Collect data on the planned railway network system, including the railway power supply system, vehicle characteristics, and system operating conditions; then, divide the train operation schedule into multiple time points, and at each specified time point, determine the location, quantity, operating power, and operating conditions of the vehicles in the system; Step 2: Based on the stability analysis method of multi-vehicle network system, analyze the stability of the vehicle network system at all time points in sequence; If the system is stable, complete the system stability assessment at this point in time and perform the stability analysis at the next point in time; otherwise, record the stability results at this point in time and proceed to step 3. S2.1: The railway vehicle network system is divided into active and passive subsystems through multiple vehicle access nodes; for the passive subsystem, the impedance matrix Z of the traction network subsystem is constructed based on the track distance between different vehicles. NS For active subsystems, based on the vehicle's operating point, the vehicle admittance is modeled or measured in the dq coordinate system, and the vehicle subsystem admittance matrix Y is constructed. VS ; S2.2: Establish the system back-comparison matrix L of the two subsystems r The system stability was analyzed using GNSC; if the system stability margin met the operational requirements, the system stability analysis at that time point was completed; then, the system stability at the next time point was analyzed based on the train operation diagram; otherwise, if L r If there are unstable or critically stable eigenvalue trajectories, it is necessary to optimize the system stability by changing the OLTC tap position. Step 3: Based on the stability analysis results of the multi-vehicle network system, adjust the OLTC tap position and re-evaluate the stability of the vehicle network system until all vehicle network systems meet the stability margin requirements at all times; S3.1 Determine the current OLTC tap position; based on the system power flow analysis results, find the lowest and highest voltage nodes of the vehicles in the system to ensure that the vehicle voltage does not exceed its maximum or minimum voltage operating range; S3.2 Based on the relationship between vehicle operating power, grid-side voltage, and system stability, gradually increase the current OLTC tap position; S3.3 Reassess the stability of the vehicle network system at this point in time and observe whether the system is stable at this time. If the system stability margin still does not meet the requirements, continue to gradually increase the current OLTC tap position and repeat the stability analysis until the system is stable at this point in time. Step 4: Conduct tests on the hardware-in-the-loop platform to evaluate the stability of the railway vehicle network system.

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