Tidal flow through type traction power supply system energy management method, equipment and storage medium

Abstract

The invention discloses a power flow through type traction power supply system energy management method, and the method comprises the steps: obtaining the load process data and photovoltaic output data of a traction substation: building a target function of an optimization model based on the local electric charge parameter data, the load process data of the traction substation and the photovoltaic output data; establishing constraint conditions of the optimization model, and linearizing the constraint conditions of the optimization model; and based on constraint conditions of the optimization model of objective function linearization of the optimization model, a mixed integer programming model is established and solved, and energy management optimization of the power flow through type traction power supply system is completed. The invention further discloses equipment for energy management of the tidal current through type traction power supply system and a storage medium. According to the energy management method for the power flow through type traction power supply system, the mixed integer linear programming model is established and solved to obtain the resource configuration parameters, and compared with a traditional non-power flow through method, the battery aging rate and the total operation cost are remarkably reduced.

Description

Technical Field

[0001] The present application relates to the technical field of rail transit traction power supply systems, and more specifically, to an energy management method, device and storage medium for a power flow-through traction power supply system. Background Art

[0002] The power quality problems of the rail transit traction power supply system, mainly the negative sequence, and the phase separation link seriously restrict its safe, high-quality and efficient operation. The ideal solution is to adopt the "bilateral power supply" technology to achieve the elimination of the phase separation in the partition and the improvement of the power supply capacity under the premise of ensuring that the balanced current meets the requirements. Due to the limitations of the current management mode of "high-voltage ring network, low-voltage network separation, and tree-like power supply" in my country's power system, the "bilateral power supply" technology has not yet been applied in engineering.

[0003] The existing technical solution is to install parallel power transfer devices (PTD) between traction substations based on fully controlled power electronic devices to achieve power flow connection and energy management between adjacent traction substations. However, in actual use, if multiple traction substations are used, there are differences in traction loads and new energy outputs of different traction substations, and it is necessary to actively adjust the differences between different substations. How to improve the active control capability of the traction power supply system for impact loads and the utilization efficiency of power supply resources with the guidance of system economic operation is an urgent problem to be solved in the existing traction power supply system. Summary of the invention

[0004] In response to at least one defect or improvement need in the prior art, the present invention provides an energy management method, device, equipment and storage medium for a flow-through traction power supply system, which can overcome the above-mentioned problems in the prior art and significantly reduce the battery aging rate and total operating cost.

[0005] To achieve the above object, according to a first aspect of the present invention, a method for energy management of a power flow-through traction power supply system is provided, the method comprising:

[0006] Obtain traction substation load process data and photovoltaic output data:

[0007] Establishing an objective function of an optimization model based on local electricity fee parameter data, the load process data of the traction substation and the photovoltaic output data;

[0008] Obtain the power capacity parameters of the hybrid energy storage system, the power parameters of the photovoltaic system, the power parameters of the power flow controller, the power parameters of the power flow transfer device, and the national standard parameters of three voltage imbalances, and establish the constraints of the optimization model based on the load process data of the traction substation and the typical light intensity scene, and linearize the constraints of the optimization model;

[0009] Establishing a mixed integer programming model based on the objective function of the optimization model and the constraints of the linearized optimization model;

[0010] The mixed integer programming model is solved to obtain the optimal charging and discharging power of the hybrid energy storage device, the optimal photovoltaic grid-connected power, the optimal power flow power of the back-to-back converter in the power flow controller and the power flow transfer device, and complete the energy management optimization of the power flow-through traction power supply system.

[0011] Furthermore, the energy management method of the power flow-through traction power supply system further includes:

[0012] The objective function of the optimization model is:

[0013]

[0014] Among them, f is the objective function, which represents the daily operating cost of the traction substation, I is the set of traction substations, i represents the i-th traction substation, T is the set of time periods, t represents the t-th time period, Δt is the unit time period, is the load demand power of the traction substation, It is the electric power purchased by the traction substation from the power grid. is the electric energy power fed back to the grid, is the photovoltaic output power, is the discharge power of the battery, is the charging power of the battery, is the discharge power of the supercapacitor, is the charging power of the supercapacitor; is the photovoltaic operation and maintenance cost price, is the battery operation and maintenance cost price, is the supercapacitor operation and maintenance cost price, c dem is the demand electricity price; is the electricity purchase price of the same-phase traction substation, It is the price charged for the electricity fed back to the grid;

[0015] in,

[0016]

[0017] N T The total number of time periods in a day.

[0018] Furthermore, the energy management method of the power flow through traction power supply system further includes:

[0019] The constraints of the optimization model include system flow constraints, hybrid energy storage system constraints, public grid power constraints, photovoltaic power generation constraints, flow controller constraints, flow transfer device constraints and three-phase voltage imbalance constraints.

[0020] Furthermore, the energy management method of the power flow through traction power supply system further includes:

[0021] The system power flow constraints include:

[0022]

[0023] in, is the active power flow of the traction transformer, is the active power flow of the α phase of the back-to-back converter of the power flow controller, is the active power flow of the β phase of the back-to-back converter of the power flow controller, is the reactive power flow of the β phase of the back-to-back converter of the power flow controller, is the active traction load, is the reactive traction load, is the active component of the regenerative braking power, is the reactive component of the regenerative braking power, It is the maximum limit of the interactive power between the same-phase traction substation and the power grid;

[0024] is a binary variable for the power direction of the same-phase traction substation and the grid, Indicates that the interactive power flows from the grid to the same-phase traction substation, It indicates that the interactive power is fed back to the grid from the same-phase traction substation;

[0025] is the active power of the power flow transfer device, is the reactive power of the power transfer device, a i，j is a binary parameter, a i，j =1 means that traction substations i and j are adjacent, a i，j =0 means that traction substations i and j are not adjacent.

[0026] Furthermore, the energy management method of the power flow through traction power supply system further includes:

[0027] The hybrid energy storage constraints include:

[0028]

[0029] in, is the electrical energy stored in the battery at time t, is the energy stored in the supercapacitor at time t, η b，ch is the battery charging efficiency, η b，dis is the battery discharge efficiency, η c，ch is the supercapacitor charging efficiency, η c，dis is the supercapacitor discharge efficiency, ε b is the battery self-discharge rate, ε c is the supercapacitor self-discharge rate, is the upper limit of the battery state of charge. SOC b is the lower limit of the battery state of charge, is the upper limit of the supercapacitor state of charge, SOC c It is the lower limit of the supercapacitor charge state. is the rated power of the battery, is the rated power of the supercapacitor;

[0030] is the amount of energy stored in the battery during the initial period of each day, It is the electric energy stored in the battery at the end of each day. is the initial state of charge of the battery, is the rated capacity of the battery, is the energy stored in the supercapacitor during the initial period of each day, It is the energy stored in the supercapacitor at the end of each day. is the initial charge state of the supercapacitor, is the rated capacity of the supercapacitor, and are binary variables, Indicates that the battery and supercapacitor are in a discharging state. Indicates that the battery and supercapacitor are in charging state.

[0031] Furthermore, the energy management method of the power flow-through traction power supply system further includes:

[0032] The photovoltaic output constraint condition is:

[0033]

[0034] in, is the upper limit of photovoltaic output power;

[0035] The power flow controller constraints include:

[0036]

[0037] in, is the rated capacity of the α-phase converter of the back-to-back converter in the power flow controller of the i-th traction substation, is the rated capacity of the β-phase converter of the back-to-back converter in the power flow controller of the i-th traction substation;

[0038] The constraints of the power flow transfer device include:

[0039]

[0040] in, is the rated capacity of the flow transfer device, is the active power of the power flow transfer device flowing from the i-th traction substation to the j-th traction substation, is the active power of the power flow transfer device flowing from the jth traction substation to the i-th traction substation, is the reactive power of the power flow transfer device flowing from the i-th traction substation to the j-th traction substation, It is the reactive power of the power flow transfer device flowing from the jth traction substation to the i-th traction substation.

[0041] Furthermore, the energy management method of the power flow-through traction power supply system further includes:

[0042] The three-phase voltage unbalance constraint condition includes:

[0043]

[0044]

[0045] Among them, ε u is the three-phase voltage unbalance degree on the grid side of the traction substation, U s is the grid-side line voltage, S cap is the short-circuit capacity of the grid side line, It is the upper limit of the three-phase voltage unbalance in the national standard, I t (-) is the negative sequence current on the grid side, U T is the voltage at the outlet of the traction transformer, U α is the voltage at the α phase outlet of the back-to-back converter, N1 is the single-phase traction transformer ratio, N2 is the high-voltage matching transformer ratio, and a is the complex operator e j120° , is the voltage and current phase angle difference of the single-phase traction transformer, is the voltage and current phase angle difference of the α phase of the back-to-back converter, I T is the traction transformer current, I α is the current in the α phase of the back-to-back converter.

[0046] Furthermore, the energy management method of the power flow-through traction power supply system further includes:

[0047] The linearizing of the constraint conditions of the optimization model specifically includes:

[0048] Will The function is linearized to

[0049] max(P t dem )=P dem,max

[0050]

[0051] Among them, P dem，max It is an auxiliary variable representing the maximum demand value in a day;

[0052] Based on the constraints of the power flow controller and the power flow transfer device, it is linearized as

[0053]

[0054] Among them, N P is the number of equally divided sectors of the PQ semicircle, satisfying Q ≥ 0, Δθ is the sector angle, (P k , Q k ) is the coordinate of the dividing point between the sector and the PQ semicircle;

[0055] Based on the three-phase voltage unbalance constraint, it is linearized as

[0056]

[0057] in, and are auxiliary variables. is a binary variable.

[0058] According to the second aspect of the present invention, there is also provided a flow-through traction power supply system energy management device, which includes at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program, and when the computer program is executed by the processing unit, the processing unit executes the steps of any one of the above-mentioned methods.

[0059] According to the third aspect of the present invention, a storage medium is also provided, which stores a computer program that can be executed by a power flow-through traction power supply system energy management device. When the computer program runs on the power flow-through traction power supply system energy management device, the power flow-through traction power supply system energy management device executes the steps of any one of the above-mentioned methods.

[0060] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects compared with the prior art:

[0061] (1) The present invention provides an energy management method for a power flow-through traction power supply system, which establishes an optimal operation model of the traction power supply system with photovoltaic output, hybrid energy storage device charging and discharging strategy, power flow controller and power flow transfer device as decision variables. By linearizing the nonlinear constraints in the original optimization model, a mixed integer linear programming model is obtained and solved, and the energy management configuration parameters of the traction power supply system can be obtained, which significantly reduces the battery aging rate and the total operating cost.

[0062] (2) Compared with the traditional non-trend through-type method, the energy management method of the traction power supply system provided by the present invention improves the photovoltaic penetration rate and reduces the abandoned photovoltaic power. In addition, the load differences between different traction substations are balanced, the battery aging rate and the overall operating cost of the traction substation are significantly reduced, and the active control capability of the traction power supply system for impact loads and the utilization efficiency of power supply resources are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0064] Figure 1 A flow chart of an energy management method for a power flow-through traction power supply system provided in an embodiment of the present application;

[0065] Figure 2 A schematic structural diagram of a flow-through traction power supply system including three traction substations provided in an embodiment of the present application. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0067] The terms "first", "second", "third", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices.

[0068] Figure 1 A flow chart of an energy management method for a power flow-through traction power supply system provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, the method comprises the following steps:

[0069] Step 101: Obtain traction substation load process data and photovoltaic output data.

[0070] Specifically, the load process data of the traction substation is the load process data generated during the operation of the traction substation, including the load power data of a traction substation in a certain operating period, the electric power data purchased by the traction substation from the power grid, the electric power data fed back to the power grid, the charging power data of the battery, the discharging power data of the battery, the operating and maintenance cost price data of the battery, the charging power data of the supercapacitor, the discharging power data of the supercapacitor, the operating and maintenance cost price data of the supercapacitor and other data. It is necessary to obtain the process load data of all traction substations in all operating periods of the traction power supply system within a day.

[0071] Photovoltaic output data includes photovoltaic output power data, photovoltaic operation and maintenance cost price and other data.

[0072] Step 102: Establish an objective function of the optimization model based on local electricity price parameter data, traction substation load process data and photovoltaic output data.

[0073] Specifically, the local electricity price parameter data is the electricity price parameter data traded with the local power grid organization, including the purchase price of electricity at the traction transformer substation and the fee price for feeding back the electricity to the power grid.

[0074] Based on local electricity price parameter data, traction substation load process data and photovoltaic output data, the objective function of the optimization model is established.

[0075] Step 103: Obtain the power capacity parameters of the hybrid energy storage system, the power parameters of the photovoltaic system, the power parameters of the power flow controller, the power parameters of the power flow transfer device, and the national standard parameters of three voltage imbalances, and establish the constraints of the optimization model based on the load process data of the traction substation and the typical light intensity scene, and linearize the constraints of the optimization model.

[0076] Specifically, the power capacity parameters of the hybrid energy storage system, the power parameters of the photovoltaic system, the power parameters of the power flow controller, and the power parameters of the power flow transfer device can be obtained through the nameplate or operating conditions of the corresponding device or system. The national standard parameters of the three voltage imbalances can be obtained by querying relevant materials. The specific acquisition method will not be repeated here. Local typical light intensity data can be obtained based on local public data.

[0077] Based on the above parameters, the constraints of the optimization model are established and the constraints of the optimization model are linearized.

[0078] Step 104: Establish a mixed integer programming model based on the constraints of the optimization model based on the linearization of the objective function of the optimization model.

[0079] Step 105, solve the mixed integer programming model, obtain the optimal charging and discharging power of the hybrid energy storage device, the optimal photovoltaic grid-connected power, the optimal power flow power of the back-to-back converter in the power flow controller and the power flow transfer device, and complete the energy management optimization of the power flow through traction power supply system.

[0080] Specifically, the optimization software can be used to solve the mixed integer programming model to obtain the optimal charging and discharging power of the hybrid energy storage device, the optimal photovoltaic grid-connected power, the optimal power flow power of the back-to-back converter in the power flow controller and the power flow transfer device, and the traction power supply system can be optimized based on the above data.

[0081] An embodiment of the present invention provides an energy management method for a flow-through traction power supply system, which establishes an optimal operation model of the traction power supply system with photovoltaic output, hybrid energy storage device charging and discharging strategy, flow controller and flow transfer device as decision variables. By linearizing the nonlinear constraints in the original optimization model, a mixed integer linear programming model is obtained and solved, and the energy management configuration parameters of the traction power supply system can be obtained, which can significantly reduce the battery aging rate and the total operating cost.

[0082] Optionally, in one embodiment of the present invention, the objective function of the optimization model is:

[0083]

[0084] Among them, f is the objective function, which represents the daily operating cost of the traction substation, I is the set of traction substations, i represents the i-th traction substation, T is the set of time periods, t represents the t-th time period, Δt is the unit time period, is the load demand power of the traction substation, It is the electric power purchased by the traction substation from the power grid. is the electric energy power fed back to the grid, is the photovoltaic output power, is the discharge power of the battery, is the charging power of the battery, is the discharge power of the supercapacitor, is the charging power of the supercapacitor; is the photovoltaic operation and maintenance cost price, is the battery operation and maintenance cost price, is the supercapacitor operation and maintenance cost price, c dem is the demand electricity price; is the electricity purchase price of the same-phase traction substation, It is the price charged for the electricity fed back to the grid;

[0085] in,

[0086]

[0087] N T The total number of time periods in a day.

[0088] Optionally, in one embodiment of the present invention, the constraints of the optimization model include system flow constraints, hybrid energy storage system constraints, public grid power constraints, photovoltaic power generation constraints, flow controller constraints, flow transfer device constraints and three-phase voltage imbalance constraints.

[0089] Optionally, in one embodiment of the present invention, the system power flow constraint condition includes:

[0090]

[0091] in, is the active power flow of the traction transformer, is the active power flow of the α phase of the back-to-back converter of the power flow controller, is the active power flow of the β phase of the back-to-back converter of the power flow controller, is the reactive power flow of the β phase of the back-to-back converter of the power flow controller, is the active traction load, is the reactive traction load, is the active component of the regenerative braking power, is the reactive component of the regenerative braking power, It is the maximum limit of the interactive power between the same-phase traction substation and the power grid;

[0092] is a binary variable for the power direction of the same-phase traction substation and the grid, Indicates that the interactive power flows from the grid to the same-phase traction substation, It indicates that the interactive power is fed back to the grid from the same-phase traction substation;

[0093] is the active power of the power flow transfer device, is the reactive power of the power transfer device, a i，j is a binary parameter, a i，j =1 means that traction substations i and j are adjacent, a i，j =0 means that traction substations i and j are not adjacent.

[0094] Optionally, in one embodiment of the present invention, the hybrid energy storage constraint condition includes:

[0095]

[0096]

[0097] in, is the electrical energy stored in the battery at time t, is the energy stored in the supercapacitor at time t, η b，ch is the battery charging efficiency, η b，dis is the battery discharge efficiency, η c，ch is the supercapacitor charging efficiency, η c，dis is the supercapacitor discharge efficiency, ε b is the battery self-discharge rate, ε c is the supercapacitor self-discharge rate, is the upper limit of the battery state of charge. SOC b is the lower limit of the battery state of charge, is the upper limit of the supercapacitor state of charge, SOC c It is the lower limit of the supercapacitor charge state. is the rated power of the battery, is the rated power of the supercapacitor;

[0098] is the amount of energy stored in the battery during the initial period of each day, It is the electric energy stored in the battery at the end of each day. is the initial state of charge of the battery, is the rated capacity of the battery, is the energy stored in the supercapacitor during the initial period of each day, It is the energy stored in the supercapacitor at the end of each day. is the initial charge state of the supercapacitor, is the rated capacity of the supercapacitor, and are binary variables, Indicates that the battery and supercapacitor are in a discharging state. Indicates that the battery and supercapacitor are in charging state.

[0099] Optionally, in one embodiment of the present invention, the photovoltaic output constraint condition is:

[0100]

[0101] in, It is the upper limit of photovoltaic output power.

[0102] Optionally, in one embodiment of the present invention, the power flow controller constraint condition includes:

[0103]

[0104] in, is the rated capacity of the α-phase converter of the back-to-back converter in the power flow controller of the i-th traction substation, is the rated capacity of the β-phase converter of the back-to-back converter in the power flow controller of the i-th traction substation;

[0105] Constraints of the power flow transfer device include:

[0106]

[0107] in, is the rated capacity of the flow transfer device, is the active power of the power flow transfer device flowing from the i-th traction substation to the j-th traction substation, is the active power of the power flow transfer device flowing from the jth traction substation to the i-th traction substation, is the reactive power of the power flow transfer device flowing from the i-th traction substation to the j-th traction substation, It is the reactive power of the power flow transfer device flowing from the jth traction substation to the i-th traction substation.

[0108] Optionally, in one embodiment of the present invention, the three-phase voltage unbalance constraint condition includes:

[0109]

[0110] Among them, ε uis the three-phase voltage unbalance degree on the grid side of the traction substation, U s is the grid-side line voltage, S cap is the short-circuit capacity of the grid side line, It is the upper limit of the three-phase voltage unbalance in the national standard, I t (-) is the negative sequence current on the grid side, U T is the voltage at the outlet of the traction transformer, U α is the voltage at the α phase outlet of the back-to-back converter, N1 is the single-phase traction transformer ratio, N2 is the high-voltage matching transformer ratio, and a is the complex operator e j120° , is the voltage and current phase angle difference of the single-phase traction transformer, is the voltage and current phase angle difference of the α phase of the back-to-back converter, I T is the traction transformer current, I α is the current in the α phase of the back-to-back converter.

[0111] Optionally, in one embodiment of the present invention, linearizing the constraints of the optimization model specifically includes:

[0112] Will The function is linearized to

[0113] max(P t dem )=P dem,max

[0114]

[0115] Among them, P dem，max It is an auxiliary variable representing the maximum demand value in a day;

[0116] Based on the constraints of the power flow controller and the power flow transfer device, it is linearized as

[0117]

[0118] Among them, N P is the number of equally divided sectors of the PQ semicircle, satisfying Q ≥ 0, Δθ is the sector angle, (P k , Q k ) is the coordinate of the dividing point between the sector and the PQ semicircle;

[0119] Based on the three-phase voltage unbalance constraint, it is linearized as

[0120]

[0121] in, and are auxiliary variables. is a binary variable.

[0122] The following is a specific example of an energy management method for a power flow-through traction power supply system provided by the present application.

[0123] In the embodiment of the present invention, a flow-through traction power supply system including three traction substations is taken as an example. Figure 2 As shown, the energy storage system parameters of the system are shown in Table 1, the traction substation parameters are shown in Table 2, and the grid electricity price parameters are shown in Table 3.

[0124] Table 1 Hybrid energy storage system parameters

[0125]

[0126] Table 2 Traction substation parameters

[0127]

[0128] Table 3 Time-of-use electricity price parameters

[0129]

[0130] The operation and maintenance costs of the system's photovoltaic, battery and supercapacitor are all 0.1￥ / kWh, and the feedback power billing is c fed =-0.8c buy , the capacity of the power flow transfer device is 5MVA.

[0131] The power flow through type traction power supply system provided by the embodiment of the present invention is compared with the energy management method of the traditional non-through type traction power supply system. The comparison results are shown in Table 4:

[0132] Table 4 Comparison of daily cycle count and aging rate of traction substation batteries

[0133]

[0134] The classic algorithm rain flow counting method based on battery cycle calculation calculates the daily cycle times of the batteries of each traction substation under the two methods, as shown in Table 4. Under the flow through mode of the flow through traction power supply system provided by the embodiment of the present invention, the battery cycle times and daily aging rate are significantly reduced compared with the traditional method. Among them, the reduction rates of the daily aging rates of the three traction substations are 69.46%, 42.03% and 22.48% respectively, indicating that the addition of the flow transfer device PTD can effectively balance the differences in traction loads among the three traction substations, reduce the differences in battery operation modes of the three traction substations, and extend the battery cycle life.

[0135] The economic operation results of the traction substation of the power flow through type traction power supply system provided by the embodiment of the present invention are compared with the energy management method of the traditional non-through type traction power supply system. The comparison results are shown in Table 5:

[0136] Table 5 Comparison of economic operation results of traction substation

[0137]

[0138] It can be seen from Table 5 that in the flow-through traction power supply system provided by the embodiment of the present invention, the total operating costs of traction substations 1 and 3 have a slight increase of 7.46% and 8.53% compared with the traditional method. The main reason is the substantial increase in electricity charges, which are 26.87% and 16.73% respectively; and thanks to the flow transfer effect of the flow transfer device between adjacent traction substations, the total operating cost of traction substation 2 is greatly reduced, with a reduction of 30.84%, among which the cost items such as electricity charges and demand charges are significantly reduced.

[0139] When comprehensively considering the overall operating costs of the three traction substations, the operating costs under the traditional method are 248,500.87 yuan, while the operating costs of the flow-through traction power supply system provided by the embodiment of the present invention are 220,187.86 yuan, with a saving rate of 11.39%. Therefore, the present invention actually "shares" the traction load demand of traction substation 2 with traction substation 1 and traction substation 3, thereby achieving the goal of minimizing the overall operating costs of the three traction substations.

[0140] Compared with the traditional non-power flow penetration method, the present invention improves the photovoltaic penetration rate and reduces the abandoned light. In addition, the load differences between different traction substations are balanced, the battery aging rate and the overall operating cost of the traction substation are significantly reduced, and the traction power supply system's active control capability of impact loads and the utilization efficiency of power supply resources are improved.

[0141] The present application also provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the steps of the above method are implemented. The computer-readable storage medium may include, but is not limited to, any type of disk, including a floppy disk, an optical disk, a DVD, a CD-ROM, a micro drive, and a magneto-optical disk, a ROM, a RAM, an EPROM, an EEPROM, a DRAM, a VRAM, a flash memory device, a magnetic card or an optical card, a nanosystem (including a molecular memory IC), or any type of medium or device suitable for storing instructions and / or data.

[0142] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present application.

[0143] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0144] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0145] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0146] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0147] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a memory, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM), random access memory (RAM), mobile hard disk, disk or optical disk and other media that can store program code.

[0148] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, which can include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0149] The above is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure cannot be limited thereto. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the specification and practicing the disclosure here, those skilled in the art will easily think of the implementation scheme of the present disclosure. This application is intended to cover any modification, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure. The description and examples are regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

[0150] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0151] It will be easily understood by those skilled in the art that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for energy management of a power flow-through traction power supply system, characterized in that: include: Obtain traction substation load process data and photovoltaic output data: Establishing an objective function of an optimization model based on local electricity fee parameter data, the load process data of the traction substation and the photovoltaic output data; Obtain the power capacity parameters of the hybrid energy storage system, the power parameters of the photovoltaic system, the power parameters of the power flow controller, the power parameters of the power flow transfer device, and the national standard parameters of three voltage imbalances, and establish the constraints of the optimization model based on the load process data of the traction substation and the typical light intensity scene, and linearize the constraints of the optimization model; Establishing a mixed integer programming model based on the objective function of the optimization model and the constraints of the linearized optimization model; The mixed integer programming model is solved to obtain the optimal charging and discharging power of the hybrid energy storage device, the optimal photovoltaic grid-connected power, the optimal power flow power of the back-to-back converter in the power flow controller and the power flow transfer device, and complete the energy management optimization of the power flow-through traction power supply system.

2. The energy management method of the power flow through traction power supply system according to claim 1, characterized in that: The objective function of the optimization model is: Among them, f is the objective function, which represents the daily operating cost of the traction substation, I is the set of traction substations, i represents the i-th traction substation, T is the set of time periods, t represents the t-th time period, Δt is the unit time period, is the load demand power of the traction substation, It is the electric power purchased by the traction substation from the power grid. is the electric energy power fed back to the grid, is the photovoltaic output power, is the discharge power of the battery, is the charging power of the battery, is the discharge power of the supercapacitor, is the charging power of the supercapacitor; is the photovoltaic operation and maintenance cost price, is the battery operation and maintenance cost price, is the supercapacitor operation and maintenance cost price, c dem is the demand electricity price; is the electricity purchase price of the same-phase traction substation, It is the price charged for the electricity fed back to the grid; in, N T The total number of time periods in a day.

3. The energy management method of the power flow through traction power supply system according to claim 2, characterized in that: The constraints of the optimization model include system flow constraints, hybrid energy storage system constraints, public grid power constraints, photovoltaic power generation constraints, flow controller constraints, flow transfer device constraints and three-phase voltage imbalance constraints.

4. The energy management method of the power flow through traction power supply system according to claim 3, characterized in that: The system power flow constraints include: in, is the active power flow of the traction transformer, is the active power flow of the α phase of the back-to-back converter of the power flow controller, is the active power flow of the β phase of the back-to-back converter of the power flow controller, is the reactive power flow of the β phase of the back-to-back converter of the power flow controller, is the active traction load, is the reactive traction load, is the active component of the regenerative braking power, is the reactive component of the regenerative braking power, It is the maximum limit of the interactive power between the same-phase traction substation and the power grid; is a binary variable for the power direction of the same-phase traction substation and the grid, Indicates that the interactive power flows from the grid to the same-phase traction substation, It indicates that the interactive power is fed back to the grid from the same-phase traction substation; is the active power of the power flow transfer device, is the reactive power of the power transfer device, a i，j is a binary parameter, a i，j =1 means that traction substations i and j are adjacent, a i，j =0 means that traction substations i and j are not adjacent.

5. The energy management method of the power flow through traction power supply system according to claim 4, characterized in that: The hybrid energy storage constraints include: in, is the electrical energy stored in the battery at time t, is the energy stored in the supercapacitor at time t, η b，ch is the battery charging efficiency, η b，dis is the battery discharge efficiency, η c，ch is the supercapacitor charging efficiency, η c，dis is the supercapacitor discharge efficiency, ε b is the battery self-discharge rate, ε c is the supercapacitor self-discharge rate, is the upper limit of the battery state of charge. SOC b is the lower limit of the battery state of charge, is the upper limit of the supercapacitor state of charge, SOC c It is the lower limit of the supercapacitor charge state. is the rated power of the battery, is the rated power of the supercapacitor; is the amount of energy stored in the battery during the initial period of each day, It is the electric energy stored in the battery at the end of each day. is the initial state of charge of the battery, is the rated capacity of the battery, is the energy stored in the supercapacitor during the initial period of each day, It is the energy stored in the supercapacitor at the end of each day. is the initial charge state of the supercapacitor, is the rated capacity of the supercapacitor, and are binary variables, Indicates that the battery and supercapacitor are in a discharging state. Indicates that the battery and supercapacitor are in charging state.

6. The energy management method of the power flow through traction power supply system according to claim 5, characterized in that: The photovoltaic output constraint condition is: in, is the upper limit of photovoltaic output power; The power flow controller constraints include: in, is the rated capacity of the α-phase converter of the back-to-back converter in the power flow controller of the i-th traction substation, is the rated capacity of the β-phase converter of the back-to-back converter in the power flow controller of the i-th traction substation; The constraints of the power flow transfer device include: in, is the rated capacity of the flow transfer device, is the active power of the power flow transfer device flowing from the i-th traction substation to the j-th traction substation, is the active power of the power flow transfer device flowing from the jth traction substation to the i-th traction substation, is the reactive power of the power flow transfer device flowing from the i-th traction substation to the j-th traction substation, It is the reactive power of the power flow transfer device flowing from the jth traction substation to the i-th traction substation.

7. The energy management method of the power flow through traction power supply system according to claim 6, characterized in that: The three-phase voltage unbalance constraint condition includes: Among them, ε u is the three-phase voltage unbalance degree on the grid side of the traction substation, U s is the grid-side line voltage, S cap is the short-circuit capacity of the grid side line, It is the upper limit of the three-phase voltage unbalance in the national standard, I t (-) is the negative sequence current on the grid side, U T is the voltage at the outlet of the traction transformer, U α is the voltage at the α phase outlet of the back-to-back converter, N1 is the single-phase traction transformer ratio, N2 is the high-voltage matching transformer ratio, and a is the complex operator e j120° , is the voltage and current phase angle difference of the single-phase traction transformer, is the voltage and current phase angle difference of the α phase of the back-to-back converter, I T is the traction transformer current, I α is the current in the α phase of the back-to-back converter.

8. The energy management method of the power flow through traction power supply system according to claim 7, characterized in that: The linearizing of the constraint conditions of the optimization model specifically includes: Will The function is linearized to Among them, P dem , max It is an auxiliary variable representing the maximum demand value in a day; Based on the constraints of the power flow controller and the power flow transfer device, it is linearized as Among them, N P is the number of equally divided sectors of the PQ semicircle, satisfying Q ≥ 0, Δθ is the sector angle, (P k , Q k ) is the coordinate of the dividing point between the sector and the PQ semicircle; Based on the three-phase voltage unbalance constraint, it is linearized as in, and are auxiliary variables. is a binary variable.

9. A power flow through traction power supply system energy management device, characterized in that: The method comprises at least one processing unit and at least one storage unit, wherein the storage unit stores a computer program, and when the computer program is executed by the processing unit, the processing unit executes the steps of the method according to any one of claims 1 to 8.

10. A storage medium, characterized in that: It stores a computer program that can be executed by a power flow-through traction power supply system energy management device. When the computer program runs on the power flow-through traction power supply system energy management device, the power flow-through traction power supply system energy management device executes the steps of the method described in any one of claims 1 to 8.

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