Optimal configuration method of flywheel energy storage for regenerative braking energy recovery in urban rail transit

Abstract

The present invention provides a flywheel energy storage optimization configuration method for regenerative braking energy recovery in urban rail transit, comprising the following steps: Step S1: Modeling the traction power supply system according to a fixed energy-saving traction strategy, and constructing a power flow calculation model for the entire line's DC traction power supply system; Step S2: Constructing a flywheel energy storage economic model with the addition of a flywheel energy storage unit; Step S3: Solving the power flow calculation model based on the flywheel energy storage economic model to obtain a configuration plan for the flywheel energy storage unit. By constructing the flywheel energy storage economic model and optimizing and solving it in conjunction with the power flow calculation model, the optimal energy storage configuration plan can be determined, ensuring that investment and operating costs are minimized while meeting system performance requirements, thereby improving the overall economic benefits of the project.

Description

Technical Field

[0001] The present invention relates to the technical field of traction power supply for urban rail transit, and in particular to a flywheel energy storage optimization configuration method for regenerative braking energy recovery in urban rail transit. Background Art

[0002] Urban rail transit is characterized by short distances between stations and high vehicle density. The frequent starts and stops generate braking energy that can account for 30% or more of the traction energy. Under existing uncontrolled rectifier power supply methods, some of the regenerative braking energy is absorbed by nearby trains, while the remaining energy is dissipated by the braking resistors, resulting in wasted regenerative braking energy. Therefore, recycling regenerative braking energy from urban rail trains plays a crucial role in reducing energy consumption, suppressing overhead line voltage fluctuations, and improving power supply system stability.

[0003] Compared with electrochemical energy storage and supercapacitor energy storage, the flywheel energy storage system has a long service life, the storage capacity does not decrease throughout its entire life cycle, it is safe and environmentally friendly, and is very suitable for regenerative braking energy recovery in scenarios where urban rail transit frequently accelerates and decelerates.

[0004] The subway traction system involves energy interactions between multiple trains, multiple stations, and multiple energy storage systems, exhibiting strongly nonlinear time-varying characteristics in both time and space. Using mature commercial software to build detailed power flow models to calculate grid voltage and power variations presents an inflexible interface, making it difficult to conduct comparative analysis and optimize solutions for different energy storage capacity configurations. Summary of the Invention

[0005] The present invention proposes a flywheel energy storage optimization configuration method for regenerative braking energy recovery in urban rail transit, in order to solve the technical problems of the existing optimization configuration method, such as inflexible interfaces and difficulty in comparative analysis of capacity configuration during optimization.

[0006] To solve the above technical problems, the present invention provides a flywheel energy storage optimization configuration method for regenerative braking energy recovery in urban rail transit, comprising the following steps:

[0007] Step S1: Model the traction power supply system according to the fixed energy-saving traction strategy, and construct a power flow calculation model for the DC traction power supply system of the entire line;

[0008] Step S2: constructing a flywheel energy storage economic model when a flywheel energy storage unit is added;

[0009] Step S3: Based on the flywheel energy storage economic model, the power flow calculation model is solved to obtain a configuration scheme of the flywheel energy storage unit.

[0010] Preferably, in step S1, the expression for modeling the traction power supply system is:

[0011] ;

[0012] ;

[0013] ;

[0014] ;

[0015] Where, represents the train traction energy consumption, Indicates the train traction power, Indicates the train departure time. Indicates the time when train traction ends. Indicates the train arrival time. Indicates the train speed, Indicates the distance between stations. Indicates the running time between stations under the train operation diagram. Indicates the maximum train speed allowed between stations.

[0016] Preferably, in step S1, the method for constructing a power flow calculation model of the DC traction power supply system of the entire line includes: equating the rectifier unit to a voltage source with unidirectional current flow; equating the flywheel energy storage unit to two unidirectional current flow voltage sources; connecting the rectifier unit and the flywheel energy storage unit in parallel to construct a simplified substation model; equating the train to a current source; and associating the size of the up / down variable resistor and the rail resistance with the distance between the up / down train and the substation.

[0017] Preferably, the charging resistance of the flywheel energy storage unit after equivalent treatment is Satisfies the following expression:

[0018] ;

[0019] Where, Indicates the output voltage of the rectifier unit; Indicates the charging threshold voltage of the flywheel energy storage unit; Indicates the charging power of the flywheel energy storage unit.

[0020] Preferably, the discharge resistance of the flywheel energy storage unit after equivalent treatment is Satisfies the following expression:

[0021] ;

[0022] Where, Indicates the output voltage of the rectifier unit; Indicates the discharge threshold voltage of the flywheel energy storage unit; Indicates the discharge power of the flywheel energy storage unit.

[0023] Preferably, the train current after equivalent processing The expression is:

[0024] ;

[0025] Where, The train traction power is represented by Indicates the train traction voltage.

[0026] Preferably, in step S2, the expression of the flywheel energy storage economic model includes:

[0027] Cost recovery rate :

[0028]

[0029] Static recycling cycle F :

[0030] ;

[0031] Total Revenue Model :

[0032] ;

[0033] Objective function:

[0034] ;

[0035] ;

[0036] Constraints include:

[0037] The number of flywheel units at each site is an integer;

[0038] flywheel SOC Value range: ;

[0039] Static recovery cycle: no more than ;

[0040] Where, It represents the annual income from reducing the total grid electricity purchase cost; represents the investment cost; Indicates the design life of the flywheel; and represents the weight coefficient; Indicates flywheel SOC Lower limit of value; Indicates flywheel SOC Upper limit of value; Indicates the maximum static recycling period.

[0041] Preferably, when solving step S3, the sites are clustered and grouped according to the site spacing and the energy to be absorbed; then the grouping solution is performed to obtain the flywheel configuration solution.

[0042] Preferably, when clustering and grouping are performed, the energy transfer matrix between sites is analyzed to obtain the number of adjacent sites with energy transfer greater than a set threshold as the number of each group in clustering.

[0043] Preferably, the method for group solution includes: conducting parallel optimization of each group in the first round, selecting the Pareto optimal frontier of each group respectively, and on this basis, deleting one flywheel energy storage unit from the selected site of each group, conducting a second round of optimization calculation, gradually obtaining the frontier solution set, and finally obtaining the optimal flywheel energy storage unit configuration scheme.

[0044] The beneficial effects of the present invention include at least: the flywheel energy storage unit has a fast response capability, can provide or absorb power within milliseconds, and can adjust the voltage fluctuations in the traction power supply system in real time, thereby enhancing the stability and reliability of the system and ensuring the safety of train operation. The efficient energy recovery and reuse capabilities of the flywheel energy storage system help to reduce electricity procurement costs and lower operating expenses. By constructing an economic model of flywheel energy storage and combining it with a flow calculation model for optimization and solution, the optimal energy storage configuration scheme can be determined to ensure that investment and operating costs are minimized while meeting system performance requirements, thereby improving the overall economic benefits of the project. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 Schematic diagram of a method flow in an embodiment of the present invention;

[0046] Figure 2 A schematic diagram of an urban rail transit power supply system according to an embodiment of the present invention;

[0047] Figure 3 A schematic diagram of a power flow calculation simulation model according to an embodiment of the present invention;

[0048] Figure 4 This is a simplified model diagram of a traction power supply system according to an embodiment of the present invention;

[0049] Figure 5 Schematic diagram of a flywheel energy storage economic model according to an embodiment of the present invention;

[0050] Figure 6 This is a schematic diagram of site grouping based on the K-means clustering algorithm according to Example 2 of the present invention;

[0051] Figure 7 Schematic diagram of the solution process of Example 2 of the present invention. DETAILED DESCRIPTION

[0052] The following is a clear and complete description of the technical solutions in the embodiments of the present invention, in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts are within the scope of protection of the present invention.

[0053] Example 1

[0054] like Figure 1 As shown, an embodiment of the present invention provides a flywheel energy storage optimization configuration method for regenerative braking energy recovery in urban rail transit, comprising the following steps:

[0055] Step S1: According to the standard energy-saving traction strategy, the traction power supply system is modeled, and a power flow calculation model of the DC traction power supply system of the entire line is constructed.

[0056] like Figure 2 As shown in the figure, the subway power supply system can be divided into two parts: the AC power supply network and the DC traction network. The AC power supply network mainly includes a switchgear, a traction step-down substation, and a step-down substation. The switchgear receives medium-voltage AC power from the preceding medium-voltage AC substation. Typically, a switchgear is located at the beginning and end of each line. Each station is equipped with a traction step-down substation or a step-down substation. The traction step-down substation includes a traction substation and a step-down substation. The traction substation uses a rectifier transformer and a rectifier device to convert medium-voltage AC power to DC traction network voltage, which then supplies power to the DC traction network. The step-down substation converts medium-voltage AC power to low-voltage AC voltage using a transformer, which then supplies power to low-voltage loads such as lighting, elevators, and air conditioning. As can be seen, the urban rail transit power supply system is typically distributed.

[0057] like Figure 3 As shown in (a), the rectifier unit can be equivalent to a voltage source with unidirectional current flow, where is the no-load voltage of the rectifier unit, is the output current, is the equivalent resistance of the rectifier unit; the flywheel energy storage is equivalent to two unidirectional voltage sources, is the charging threshold voltage, is the charging resistor, is the discharge threshold voltage, is the discharge resistor; the train can be equivalent to a current source, is the train current, is the braking resistor action threshold, is the auxiliary energy consumption equivalent resistance. Figure 3(b) is the overall model of the urban rail traction power supply system. The rectifier unit and flywheel energy storage are connected in parallel to form a simplified substation model. The size of the up / down variable resistor and rail resistance depends on the distance between the up / down train and the substation.

[0058] like Figure 4 As shown, the rectifier unit provides energy, and the power of each site P Si It can be simulated by using a voltage node with internal resistance. When the train starts, the load of a certain train P Ti >0, the equivalent circuit is Figure 4 (a) in the figure; When the train brakes, the load of a certain train is P Ti <0, the equivalent circuit is as follows Figure 4 (b) in the.

[0059] In order to model and analyze the traction power supply system, it is first necessary to perform traction calculations to obtain the power curve during train operation. Using a timed energy-saving traction strategy, the mathematical model for trajectory planning when a single vehicle is running in a section can be expressed as:

[0060] ;

[0061] ;

[0062] ;

[0063] ;

[0064] in, represents the train traction energy consumption, Indicates the train traction power, Indicates the train departure time. Indicates the time when train traction ends. Indicates the train arrival time. Indicates the train speed, Indicates the distance between stations. Indicates the running time between stations under the train operation diagram. Indicates the maximum train speed allowed between stations.

[0065] The specific solution process can adopt a hierarchical optimization method: the first layer solves the qualified solution with mileage, time, and terminal speed as constraint targets. On this basis, in the second layer calculation process, the optimal solution is found among the qualified solutions with the goal of minimizing traction energy.

[0066] Then, according to the port characteristics of the main equipment in the line, such as the rectifier unit, train, flywheel energy storage, etc., the respective equivalent circuit models are established, and the single-station-single-vehicle-single-storage model is constructed first.

[0067] The rectifier unit can be equivalent to a voltage source with unidirectional current flow, where is the no-load voltage of the rectifier unit, is the output current, is the equivalent resistance of the rectifier unit; the flywheel energy storage is equivalent to two unidirectional voltage sources, is the charging threshold, is the charging resistor, and the output voltage of the rectifier unit is , the flywheel charging power is hour, Satisfies the following formula:

[0068] ;

[0069] is the discharge threshold, is the discharge resistor, and the output voltage of the rectifier unit is , the flywheel discharge power is hour, Satisfies the following formula:

[0070] ;

[0071] The rectifier unit is connected in parallel with the flywheel energy storage to form a simplified substation model.

[0072] The train can be equivalent to a current source. is the train current, is the braking resistor action threshold, is the auxiliary energy consumption equivalent resistance, Satisfies the following formula:

[0073] ;

[0074] Where, The train traction power is represented by Indicates the train traction voltage.

[0075] After verification and analysis, a power flow calculation model for the DC traction power supply system of the entire line was formed based on a modular modeling method. The size of the up / down variable resistors and rail resistance depends on the distance between the up / down trains and the substation.

[0076] Step S2: constructing a flywheel energy storage economic model when a flywheel energy storage unit is added.

[0077] Specifically, if Figure 5 As shown in Figure 2, the economic model of flywheel energy storage is established, which mainly includes three parts: cost model, income model and profit model. Among them, the cost model takes the rated power of the flywheel energy storage unit as PN , rated capacity is W N , the unit cost is recorded as ; Configuration m flywheel unit, the flywheel investment cost for:

[0078] ;

[0079] In addition, it is necessary to consider the related investment costs of supporting switchgear, secondary control and engineering design, construction, control system access, and operation and maintenance costs. The total cost is recorded as .

[0080] Compared with the original system solution without flywheel energy storage, the annual income of flywheel energy storage mainly includes reducing the total grid power purchase cost, and the annual income is recorded as .

[0081] Annual cost recovery rate model, the annual cost recovery rate is :

[0082] ;

[0083] The static recovery period (unit: year) is F :

[0084] ;

[0085] Total revenue model, flywheel design life is In the year, the total income is recorded as :

[0086] ;

[0087] The objective function is:

[0088] ;

[0089] ;

[0090] in, and is the weight coefficient.

[0091] Constraints:

[0092] The number of flywheel units at each site is an integer, less than num ;

[0093] flywheel SOC Value range: ;

[0094] Static recovery cycle: no more than .

[0095] in, Indicates flywheel SOC Lower limit of value; Indicates flywheel SOC Upper limit of value; Indicates the maximum static recycling period.

[0096] Step S3: Based on the flywheel energy storage economic model, the power flow calculation model is solved to obtain a configuration scheme of the flywheel energy storage unit.

[0097] Specifically, according to the objective function of the flywheel energy storage economic model, the static payback period and total revenue of each scheme are comprehensively considered, the Pareto frontier is calculated, and the scheme that takes both into account is selected.

[0098] Example 2

[0099] In this embodiment, based on the first embodiment, the sites are clustered and grouped, and then a solution is performed to obtain a configuration scheme of the flywheel energy storage unit.

[0100] Specifically, the sites are divided into several groups according to the site spacing and the energy to be consumed at each site when the flywheel energy storage unit is not added. Figure 6 As shown, when solving Figure 7 As shown, a parallel-serial step-by-step optimization method was used to optimize the scenarios in multiple steps. The static payback period and total revenue results for each scenario were obtained. The optimal configuration was then selected based on these two factors. In the first round, each group underwent parallel optimization, selecting the Pareto optimal frontier for each group. Based on this, one station was removed from each selected site in the second round of optimization calculations, gradually obtaining the frontier solution set. Finally, a comparison of the static payback period and total revenue for each scenario was obtained.

[0101] Example 3

[0102] Based on Example 2, this embodiment sets the size of the group through the energy transfer matrix in order to reduce the overall computational complexity of the optimization problem.

[0103] Specifically, based on the power flow calculation model, the energy transfer matrix between stations can be further extracted. For a station in the middle of the line, there are oncoming trains in both the upward and downward directions at the same time. Within the scope of this station, the track impedance between the two trains is ignored. During the deceleration process of the incoming train and the acceleration process of the outgoing train, the power time series of the two trains are summed to obtain the total power time series, that is: i The train power at the station is:

[0104] ;

[0105] Where, Indicates the power of the up train, Represents the down train power. The model in step S1 can be used to solve the up and down train power respectively. .

[0106] Specifically, the power interaction relationship between each station is represented by matrix A, and the power of each station is P S It can be expressed as:

[0107] P S =A P T ;

[0108] in, P S =[ P S1 P S2 …P SN ] T , P T =[ P T1 P T2 …P TN ] T .

[0109] Among them, P Si represents the output power of the rectifier unit at station i. Since the rectifier unit of the traction power supply system has a unidirectional conduction characteristic, the discussion is divided into two cases: train starting and train braking:

[0110] 1) P Ti >0, the train starts

[0111] The rectifier unit provides energy to each site P Si It can be simulated by a voltage node with internal resistance, the node voltage is the rectifier unit voltage, is the equivalent internal resistance of the rectifier unit.

[0112] The solution is:

[0113] ;

[0114] Apply separately , calculate the elements of each column, and then obtain the elements of the energy transfer matrix. Each station has a close energy transfer relationship with 2-3 adjacent stations. As the distance increases, the energy transfer relationship between stations weakens significantly.

[0115] 2) P Ti <0, that is, train braking

[0116] The train brakes, feeding energy into the traction network, the diode of the rectifier unit is cut off, and the energy storage or braking resistor is activated. P Si Available voltage node simulation, node voltage It is the braking resistor action threshold.

[0117] Apply separately , calculate the elements of each column, and then obtain the elements of the energy transfer matrix.

[0118] The final energy transfer matrix is ​​shown in Table 1.

[0119] Table 1

[0120]

[0121] As can be seen from Table 1, each station primarily has a close energy transfer relationship with two or three adjacent stations, with the value exceeding the set threshold. As distance increases, the energy transfer relationship between stations significantly weakens. Stations are categorized based on their energy transfer relationships. In this example, the number of groups is 22 / 3 = 7.3, resulting in eight clusters.

[0122] The technical features of the above embodiments may be combined in any manner. To simplify the description, not all possible combinations of the technical features in the above embodiments are described. Only preferred embodiments of the present invention are presented. While the description is relatively specific and detailed, it should not be construed as limiting the scope of the present invention. As long as there are no conflicts in the combination of these technical features, they should be considered to be within the scope of this specification.

[0123] It should be noted that, for those skilled in the art, various modifications and improvements can be made without departing from the scope of the present invention, and these modifications and improvements fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

Claims

1. A flywheel energy storage optimization configuration method for regenerative braking energy recovery in urban rail transit, characterized by: The following steps are involved: Step S1: Model the traction power supply system according to the fixed energy-saving traction strategy, and construct a power flow calculation model for the DC traction power supply system of the entire line; Step S2: constructing a flywheel energy storage economic model when a flywheel energy storage unit is added; Step S3: Based on the flywheel energy storage economic model, solving the power flow calculation model to obtain a configuration scheme of the flywheel energy storage unit; In step S2, the expression of the flywheel energy storage economic model includes: Cost recovery rate : Static recycling cycle F : ； Total Revenue Model : ； Objective function: ； ； Constraints include: The number of flywheel units at each site is an integer; flywheel SOC Value range: ; Static recovery cycle: no more than ; Where, It represents the annual income from reducing the total grid electricity purchase cost; represents the investment cost; Indicates the design life of the flywheel; and represents the weight coefficient; Indicates flywheel SOC Lower limit of value; Indicates flywheel SOC Upper limit of value; Indicates the maximum static recycling period.

2. The flywheel energy storage optimization configuration method for regenerative braking energy recovery in urban rail transit according to claim 1 is characterized in that: In step S1, the expression for modeling the traction power supply system is: ； ； ； ； Where, represents the train traction energy consumption, Indicates the train traction power, Indicates the train departure time. Indicates the time when train traction ends. Indicates the train arrival time. Indicates the train speed, Indicates the distance between stations. Indicates the running time between stations under the train operation diagram. Indicates the maximum train speed allowed between stations.

3. The flywheel energy storage optimization configuration method for regenerative braking energy recovery in urban rail transit according to claim 2 is characterized in that: In step S1, the method for constructing a power flow calculation model for the DC traction power supply system of the entire line includes: equating the rectifier unit to a voltage source with unidirectional current flow; equating the flywheel energy storage unit to two unidirectional voltage sources; connecting the rectifier unit and the flywheel energy storage unit in parallel to construct a simplified substation model; equating the train to a current source; and associating the size of the up / down variable resistor and the rail resistance with the distance between the up / down train and the substation.

4. The flywheel energy storage optimization configuration method for regenerative braking energy recovery in urban rail transit according to claim 3 is characterized in that: Charging resistance of the flywheel energy storage unit after equivalent processing Satisfies the following expression: ； Where, Indicates the output voltage of the rectifier unit; Indicates the charging threshold voltage of the flywheel energy storage unit; Indicates the charging power of the flywheel energy storage unit.

5. The flywheel energy storage optimization configuration method for regenerative braking energy recovery in urban rail transit according to claim 4 is characterized in that: Discharge resistance of the flywheel energy storage unit after equivalent treatment Satisfies the following expression: ； Where, Indicates the output voltage of the rectifier unit; Indicates the discharge threshold voltage of the flywheel energy storage unit; Indicates the discharge power of the flywheel energy storage unit.

6. The flywheel energy storage optimization configuration method for regenerative braking energy recovery in urban rail transit according to claim 5, characterized in that: Train current after equivalent processing The expression is: ； Where, The train traction power is represented by Indicates the train traction voltage.

7. The flywheel energy storage optimization configuration method for regenerative braking energy recovery in urban rail transit according to claim 1 is characterized in that: When solving the problem in step S3, the sites are clustered and grouped according to the site spacing and the energy to be absorbed; then the grouping solution is performed to obtain the flywheel configuration solution.

8. The flywheel energy storage optimization configuration method for regenerative braking energy recovery in urban rail transit according to claim 7, characterized in that: When clustering and grouping are performed, the energy transfer matrix between sites is analyzed to obtain the number of adjacent sites with energy transfer greater than a set threshold as the number of each group in clustering.

9. The flywheel energy storage optimization configuration method for regenerative braking energy recovery in urban rail transit according to claim 7, characterized in that: The group solution method includes: conducting parallel optimization for each group in the first round, selecting the Pareto optimal frontier of each group, and then deleting one flywheel energy storage unit from the selected site in each group, conducting a second round of optimization calculations, and gradually obtaining the frontier solution set to finally obtain the optimal flywheel energy storage unit configuration plan.

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