Shared energy storage optimal configuration method and device for shared energy storage structure of railway traction station

Abstract

The invention relates to a shared energy storage optimal configuration method and device for a shared energy storage structure of a railway traction station, and belongs to the technical field of energy storage optimal configuration. Establishing a micro energy network agent operation benefit model; establishing an energy mutual aid operation benefit model of the shared energy storage structure, wherein an objective function is the sum of operation benefit objective functions of all micro-energy network agents; setting constraint conditions of the energy mutual aid operation benefit model of the shared energy storage structure; and in combination with the shared energy storage structure energy mutual aid operation benefit model and the shared energy storage operation benefit model, carrying out shared energy storage configuration optimization, and obtaining the storage capacity configured for each micro energy network agent by the shared energy storage. According to the invention, energy interconnection among the micro-energy network agents is carried out through shared energy storage, the energy utilization efficiency of the railway traction system is improved, and energy supply self-balance of the railway traction station and the peripheral micro-energy network groups is realized to a great extent.

Description

Technical Field

[0001] This invention relates to a method and apparatus for optimizing the configuration of shared energy storage in a railway traction substation shared energy storage structure, belonging to the field of energy storage optimization configuration technology. Background Technology

[0002] With the dual pressures of the global energy crisis and environmental protection, the energy efficiency and green development of railway traction systems have received widespread attention. During operation, especially during train braking, railway traction systems generate a significant amount of regenerative braking energy. If this energy is not utilized, it will be lost as heat, resulting in energy waste. Therefore, braking energy recovery technology has become an important means to improve the energy efficiency of railway systems and achieve green development.

[0003] However, the utilization of regenerative braking energy faces technical challenges. Due to the single-phase and highly impulsive nature of regenerative braking power, the power grid typically handles it by either ignoring or even positively counting the return flow, resulting in low utilization rates. Furthermore, regenerative braking power can easily raise the traction network voltage, potentially leading to braking failure during long downhill braking maneuvers and increasing safety risks for railway operations.

[0004] To address these issues, shared energy storage technology has emerged. Through centralized and unified construction, shared energy storage facilitates standardized management of construction standards, equipment parameters, and safety performance, effectively reducing problems such as inconsistent quality, unreliable technical performance, and significant safety risks associated with self-contained energy storage equipment from new energy sources. Shared energy storage power stations are typically 100 megawatts or larger in scale, with a configuration duration of at least 2 hours, which aids in grid dispatch management and offers multiple advantages, including more efficient dispatch operations, more controllable safety and quality, and more prominent economic benefits. However, most existing technologies adopt a resource-separated integrated energy grid architecture, neglecting energy interaction between micro-energy grids and only considering the interaction between micro-energy grid groups and the integrated energy distribution network with external energy sources, resulting in a strong dependence on the main grid. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the prior art and provide a method for optimizing the configuration of shared energy storage in railway traction substations. By establishing shared electrochemical energy storage devices in multiple micro-energy grid groups, energy mutual assistance and optimized allocation are achieved, solving the problem that existing micro-energy grids do not interact with each other and are highly dependent on the main grid.

[0006] To achieve the above objectives, the present invention is implemented using the following technical solution:

[0007] In a first aspect, the present invention provides a method for optimizing the configuration of shared energy storage for a railway traction substation shared energy storage structure, wherein the railway traction substation shared energy storage structure includes: shared energy storage and several micro-energy networks for electricity, cooling and heating; the railway traction substation is located in each micro-energy network, and each micro-energy network has an agent; the shared energy storage and each micro-energy network are respectively connected to the power grid.

[0008] The shared energy storage optimization configuration method includes: establishing a shared energy storage operation benefit model with the goal of maximizing the periodic benefits of shared energy storage; establishing a microgrid agent operation benefit model with the goal of minimizing the periodic operation cost of the microgrid; establishing a shared energy storage structure energy mutual benefit operation benefit model based on the microgrid agent operation benefit model with the goal of minimizing the total periodic operation cost of all microgrid agents; the objective function of the shared energy storage structure energy mutual benefit operation benefit model is the sum of the objective functions of the operation benefits of each microgrid agent; setting constraints on the shared energy storage structure energy mutual benefit operation benefit model, including: energy balance constraints and a set of shared energy storage operation constraints; and combining the shared energy storage structure energy mutual benefit operation benefit model and the shared energy storage operation benefit model to optimize the shared energy storage configuration and obtain the storage capacity of shared energy storage configured for each microgrid agent.

[0009] Furthermore, the shared energy storage operation benefit model considers power cost, capacity cost, and periodic maintenance cost, as well as the charging and discharging fees charged to each microgrid agent. Its objective function is specifically:

[0010] ;

[0011] ;

[0012] ;

[0013] In the formula, To share the lifecycle benefits of energy storage, To share the cyclical benefits of energy storage, The overall lifecycle cost of shared energy storage, This represents the unit capacity price of shared energy storage leasing services; K is the total number of microgrid agents; T represents the operating cycle of shared energy storage leasing. These represent the storage and discharge power of the shared energy storage used by microgrid agent k during time period t; For shared energy storage leasing operation periods, These are the unit price per unit of power and the unit price per unit of capacity for shared energy storage, respectively. These are the power limit and rated capacity of shared energy storage, respectively. Indicates the lifespan of shared energy storage; This represents the periodic operation and maintenance costs of shared energy storage.

[0014] Furthermore, the microgrid agent operation benefit model considers the cost of purchased electricity, the cost of shared thermal storage capacity and power usage, the cost of main grid gas transmission, the operating cost of units within the microgrid, and the revenue from power supply, gas supply, and heating within the shared energy storage structure. Its objective function is specifically as follows:

[0015] ;

[0016] In the formula, These represent the costs of electricity purchased by microgrid agent k, the costs of using shared energy storage capacity and power, the costs of gas transmission from the main grid, and the operating costs of units within the microgrid, respectively; T represents the operating cycle of the shared energy storage lease. These represent the revenue from electricity, gas, and heat supply within the shared energy storage structure, respectively. These represent the unit prices for purchasing electricity and gas from the main grid, respectively. These represent the unit prices for selling electricity, gas, and heat to the main grid, respectively. and These represent the electricity and natural gas purchased by microgrid agent k from the main grid at time t, respectively. These are the unit price per unit of power and the unit price per unit of capacity for shared energy storage, respectively. Indicates the lifespan of shared energy storage; This represents the periodic operation and maintenance cost of shared energy storage; These represent the shared energy storage power and capacity allocated to microgrid agent k, respectively. These represent the electricity, natural gas, and heat sold by microgrid agent k to the main grid at time t. This indicates the power consumption of the power-to-gas generator unit during operation. The coefficient for carbon dioxide consumption during the electricity-to-gas conversion; This indicates the price of the carbon source during the operation of the power-to-gas generator unit; This represents the actual output value of wind power. Forecast wind power output; For wind power grid connection price; These represent the natural gas production of the power-to-gas unit and the gas consumption of the combined heat and power unit, respectively.

[0017] Furthermore, the energy balance constraints of the shared energy storage structure energy mutual assistance operation benefit model are specifically as follows:

[0018] ;

[0019] ;

[0020] ;

[0021] In the formula, Let them represent the electrical quantity, gas quantity, and heat generated by the energy interaction between microgrids k and l at time t, respectively. Let these represent the electrical load, gas load, and heat load of the microgrid k at time t, respectively. A collection of micro-energy network agents; These represent the gas production of the k-type power-to-gas generator unit in the microgrid and the gas consumption of the combined heat and power generation at time t, respectively. The heat input from the microgrid k cogeneration to the shared energy storage at time t; The heat input from the microgrid's k-electricity-to-gas generator unit to the shared energy storage at time t; These represent the heat released by the shared energy storage and the supercapacitor device that works in conjunction with the railway traction station's energy storage at time t to the micro-energy grid k.

[0022] Furthermore, the set of shared energy storage operation constraints includes:

[0023] Constraints on shared energy storage sources:

[0024] ;

[0025] Shared energy storage lumped constraints:

[0026] ;

[0027] ;

[0028] ;

[0029] Quantitative constraints on the relationship between actual storage / discharge power and rated capacity of shared energy storage:

[0030] ;

[0031] In the formula, For time t, microgrid agent k uses shared energy storage power; The shared energy storage is input into the traction station system respectively; To provide shared energy storage power to new energy generator sets; These are the power limit and rated capacity of shared energy storage, respectively. These are the upper limits of the shared energy storage power and the upper limit of the discharge power that microgrid agent k can use; The upper limit of the storage capacity allocated to microgrid agent k for shared energy storage; This represents the storage / discharge coefficient.

[0032] Furthermore, the set of shared energy storage operation constraints also includes:

[0033] Shared energy storage storage / deployment nonsimultaneity constraint:

[0034] ;

[0035] ;

[0036] Shared energy storage periodic storage / discharge balance constraints:

[0037] ;

[0038] ;

[0039] In the formula, Let be the storage / release state variable of microgrid agent k at time t, with a value of 0 or 1; For microgrid agent k, the shared energy storage discharge power is used at time t; The capacity status of shared energy storage at time t; This is the power loss factor; These represent the initial and final capacities of the shared energy storage within a single cycle.

[0040] Furthermore, the set of shared energy storage operation constraints also includes: the capacity constraints faced by the microgrid k when using shared energy storage.

[0041] ;

[0042] ;

[0043] In the formula, The capacity of shared energy storage used by microgrid agent k at time t; These are the shared energy storage efficiency and the energy release efficiency, respectively.

[0044] Furthermore, the constraints of the shared energy storage structure energy mutual benefit operation model also include the constraints of non-simultaneous storage / discharge of supercapacitors and periodic storage / discharge balance constraints.

[0045] In a second aspect, the present invention provides a shared energy storage optimization configuration device for a shared energy storage structure of a railway traction substation, comprising: a memory storing a computer processing program thereon; and a processor for executing the computer processing program in the memory to implement the shared energy storage optimization configuration method for a shared energy storage structure of a railway traction substation as described in the first aspect.

[0046] Compared with the prior art, the beneficial effects achieved by the present invention are as follows:

[0047] (1) This invention enables energy interconnection between various micro-energy network agents through shared energy storage, improves the energy utilization efficiency of railway traction system, and achieves energy supply self-balancing of railway traction station and surrounding micro-energy network group to a large extent. It can be used to guide the configuration of hybrid energy storage system and energy management scheme selection of electrified railway, and provide technical support and solutions for the green development and energy-efficient utilization of railway system.

[0048] (2) This invention can promote the effective recovery of braking energy of railway traction stations, the optimized utilization of photovoltaic energy and the efficient integration of energy storage systems, thereby achieving optimized energy allocation and reduced economic costs. Through the "grid-source-storage-vehicle" collaborative energy supply technology system, it can realize the organic integration of information, transportation, energy and society, and improve the cross-regional and cross-time utilization level of energy. Attached Figure Description

[0049] Figure 1 A flowchart of the shared energy storage optimization configuration method for shared energy storage structures in railway traction substations provided by the present invention;

[0050] Figure 2 A schematic diagram of the interconnected operation framework for a shared energy storage structure in a railway traction substation;

[0051] Figure 3 Forecast wind power output and user power load diagrams for microgrids 1, 2, and 3;

[0052] Figure 4 For users in microgrids 1, 2, and 3;

[0053] Figure 5 The heat load curves for users within microgrids 1, 2, and 3 are shown.

[0054] Figure 6 This is a typical daily braking power curve for a railway traction substation;

[0055] Figure 7 For the situation of purchased electricity in the context of resource separation and energy sharing;

[0056] Figure 8 For the purchase of natural gas in the context of resource separation and energy sharing;

[0057] Figure 9 This section describes the changes in shared energy storage capacity under resource separation and energy sharing scenarios, as well as the changes in shared energy storage capacity used by Micro Energy Network 2. Detailed Implementation

[0058] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not necessarily limited to those explicitly listed, but may include other steps or units not explicitly listed or inherent to such process, method, product, or apparatus. The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them.

[0059] Example 1

[0060] According to a first aspect of the present invention, this embodiment provides a method for optimizing the configuration of shared energy storage for railway traction substation shared energy storage structures.

[0061] like Figure 2 As shown, the interconnected operation framework of the railway traction substation shared energy storage structure includes shared energy storage and several micro-energy networks for electricity, cooling, and heating; the railway traction substation is located in each micro-energy network, and each micro-energy network has an agent; the shared energy storage and each micro-energy network are respectively connected to the power grid.

[0062] like Figure 1 As shown, the optimized configuration method for shared energy storage includes:

[0063] Step 1: Establish a shared energy storage operation benefit model with the goal of maximizing the cycle benefits of shared energy storage.

[0064] In some specific embodiments, the shared energy storage operation benefit model considers power cost, capacity cost, and periodic maintenance cost, as well as the charging and discharging fees charged to each microgrid agent. Its objective function is specifically:

[0065] ;

[0066] ;

[0067] ;

[0068] In the formula, To share the lifecycle benefits of energy storage, To share the cyclical benefits of energy storage, The overall lifecycle cost of shared energy storage, This represents the unit capacity price of shared energy storage leasing services; K is the total number of microgrid agents; T represents the operating cycle of shared energy storage leasing. These represent the storage and discharge power of the shared energy storage used by microgrid agent k during time period t; For shared energy storage leasing operation periods, These are the unit price per unit of power and the unit price per unit of capacity for shared energy storage, respectively. These are the power limit and rated capacity of shared energy storage, respectively. Indicates the lifespan of shared energy storage; This represents the periodic operation and maintenance costs of shared energy storage.

[0069] Step 2: Establish a microgrid agent operation efficiency model with the goal of minimizing the cycle operating cost of the microgrid.

[0070] In some specific embodiments, the microgrid agent operation benefit model considers the cost of purchased electricity, the cost of shared thermal storage capacity and power usage, the cost of main grid gas transmission, the operating cost of units within the microgrid, and the revenue from power supply, gas supply, and heating within the shared energy storage structure. Its objective function is specifically as follows:

[0071] ;

[0072] In the formula, These represent the costs of electricity purchased by microgrid agent k, the costs of using shared energy storage capacity and power, the costs of gas transmission from the main grid, and the operating costs of units within the microgrid, respectively; T represents the operating cycle of the shared energy storage lease. These represent the revenue from electricity, gas, and heat supply within the shared energy storage structure, respectively. These represent the unit prices for purchasing electricity and gas from the main grid, respectively. These represent the unit prices for selling electricity, gas, and heat to the main grid, respectively. and These represent the electricity and natural gas purchased by microgrid agent k from the main grid at time t, respectively. These are the unit price per unit of power and the unit price per unit of capacity for shared energy storage, respectively. Indicates the lifespan of shared energy storage; This represents the periodic operation and maintenance cost of shared energy storage; These represent the shared energy storage power and capacity allocated to microgrid agent k, respectively. These represent the electricity, natural gas, and heat sold by microgrid agent k to the main grid at time t. This indicates the power consumption of the power-to-gas generator unit during operation. The coefficient for carbon dioxide consumption during the electricity-to-gas conversion; This indicates the price of the carbon source during the operation of the power-to-gas generator unit; This represents the actual output value of wind power. Forecast wind power output; For wind power grid connection price; These represent the natural gas production of the power-to-gas unit and the gas consumption of the combined heat and power unit, respectively.

[0073] Step 3: Based on the microgrid agent operation efficiency model, establish a shared energy storage structure energy mutual assistance operation efficiency model with the objective of minimizing the total cycle operation cost of all microgrid agents.

[0074] Specifically, the objective function of the shared energy storage structure energy mutual benefit operation efficiency model is the sum of the operational efficiency objective functions of each microgrid agent, and its constraints include: energy balance constraints, and a set of shared energy storage operation constraints.

[0075] In some embodiments, the energy balance constraint is specifically:

[0076] ;

[0077] ;

[0078] ;

[0079] In the formula, Let them represent the electrical quantity, gas quantity, and heat generated by the energy interaction between microgrids k and l at time t, respectively. Let these represent the electrical load, gas load, and heat load of the microgrid k at time t, respectively. A collection of micro-energy network agents; These represent the gas production of the k-type power-to-gas generator unit in the microgrid and the gas consumption of the combined heat and power generation at time t, respectively. The heat input from the microgrid k cogeneration to the shared energy storage at time t; The heat input from the microgrid's k-electricity-to-gas generator unit to the shared energy storage at time t; These represent the heat released by the shared energy storage and the supercapacitor device that works in conjunction with the railway traction station's energy storage at time t to the micro-energy grid k.

[0080] In some embodiments, the set of shared energy storage operation constraints includes:

[0081] Constraints on shared energy storage sources:

[0082] ;

[0083] Shared energy storage lumped constraints:

[0084] ;

[0085] ;

[0086] ;

[0087] Quantitative constraints on the relationship between actual storage / discharge power and rated capacity of shared energy storage:

[0088] ;

[0089] In the formula, For time t, microgrid agent k uses shared energy storage power; The shared energy storage is input into the traction station system respectively; To provide shared energy storage power to new energy generator sets; These are the power limit and rated capacity of shared energy storage, respectively. These are the upper limits of the shared energy storage power and the upper limit of the discharge power that microgrid agent k can use; The upper limit of the storage capacity allocated to microgrid agent k for shared energy storage; This represents the storage / discharge coefficient.

[0090] In some specific embodiments, the set of shared energy storage operation constraints also includes:

[0091] Shared energy storage storage / discharge nonsimultaneity constraint:

[0092] ;

[0093] ;

[0094] Shared energy storage periodic storage / discharge balance constraints:

[0095] ;

[0096] ;

[0097] In the formula, Let be the storage / release state variable of microgrid agent k at time t, with a value of 0 or 1; For microgrid agent k, the shared energy storage discharge power is used at time t; The capacity status of shared energy storage at time t; This is the power loss factor; These represent the initial and final capacities of the shared energy storage within a single cycle.

[0098] Capacity constraints faced by microgrid k when using shared energy storage:

[0099] ;

[0100] ;

[0101] In the formula, The capacity of shared energy storage used by microgrid agent k at time t; These are the shared energy storage efficiency and the energy release efficiency, respectively.

[0102] As is well known, most electrified railway traction substations currently use supercapacitor devices for regenerative energy recovery. Therefore, in embodiments that configure supercapacitor devices, the constraints of the energy mutual assistance operation benefit model of the shared energy storage structure should also include the constraints of the non-simultaneity of supercapacitor storage / discharge and the periodic storage / discharge balance constraints.

[0103] Step 5: Combining the shared energy storage structure energy mutual benefit operation benefit model and the shared energy storage operation benefit model, optimize the shared energy storage configuration to obtain the storage capacity of shared energy storage configured for each micro energy grid agent.

[0104] The shared energy storage optimization configuration method for railway traction substation shared energy storage structures provided in this embodiment achieves energy interconnection between various micro-energy network agents through shared energy storage, taking into account both the periodic benefits of shared energy storage and the periodic operating costs of micro-energy networks, and to a large extent realizes energy mutual assistance and optimized allocation of railway traction substations and surrounding micro-energy network groups.

[0105] Example 2

[0106] This embodiment demonstrates the application of the present invention in a specific scenario comprising three regional microgrids.

[0107] Microgrids 1, 2, and 3 are each equipped with wind turbines, combined heat and power (CHP) units, power-to-gas (EPG) units, and railway traction substations. The unit parameters for the three areas are shown in Table 1.

[0108] surface Unit configuration within the integrated energy distribution network

[0109] Unit rated capacity RIES1 RIES2 RIES3 Fan 1500kW 650kW 900kW Cogeneration units 200kW 500kW 400kW Electrolysis cell (electric to gas conversion) 400kW 500kW 600kW

[0110] Each microgrid fully considers renewable energy fluctuations and surpluses under high renewable energy penetration conditions to meet normal electricity loads and electricity-to-gas loads. When there is an energy shortage within the integrated energy distribution network, energy is purchased from external sources.

[0111] It should be noted that, considering the regional nature of heating, no external entity provides direct heating services to the various microgrids within the integrated energy park.

[0112] The pricing parameters are set as follows: the price of CO2, the raw material for electricity-to-gas conversion, is 60 yuan / t; the main grid electricity purchase price adopts time-of-use pricing, with a price of 0.54 yuan / kWh during normal hours (23:00-6:00) and 0.67 yuan / kWh during peak hours; the main grid electricity sales price is 0.15 yuan / kWh; the main grid gas supply price for the three regions is 2.74 yuan / m³. 3 2.54 yuan / m 3 2.42 yuan / m 3 The main grid gas price is 2.2 yuan / m³. 3 .

[0113] For shared energy storage, the initial energy storage capacity for each microgrid is set at 50% of the capacity leased from the shared energy storage. The ratio of the rated capacity to the power limit of the shared energy storage is set at 0.4. The unit cost of storage / discharge is set at 0.12 yuan / kWh, the capacity cost is set at 450 yuan / kW, and the power cost is set at 420 yuan / kW. The daily maintenance cost is 65 yuan, and the lifespan is 10 years.

[0114] The predicted wind power output and the load curves for electricity, gas, and heat users within microgrids 1, 2, and 3 are shown in the attached figures. Figure 3 , 4 As shown in Figure 5, a typical daily braking power curve for a railway traction substation is as follows. Figure 6 As shown.

[0115] To more intuitively demonstrate the technical effects of the present invention, based on the above parameters, this embodiment compares the operation of the existing resource-separated integrated energy network and the energy-sharing micro-energy network group proposed in this invention, which is oriented towards the shared energy storage structure of railway traction substations.

[0116] It should be noted that in the resource-separated integrated energy network, energy interaction between micro-energy networks is not considered; only the micro-energy network cluster and the interaction between the integrated energy distribution network and external energy sources are considered.

[0117] In contrast, this invention utilizes shared energy storage to achieve electrical energy exchange by dynamically allocating capacity to various microgrid agents. For microgrid agents, their energy management scheme is primarily based on achieving self-balancing energy supply within their respective service areas, while simultaneously selling surplus energy externally. For shared energy storage agents, their energy management scheme involves thermal energy exchange with microgrid agents, benefiting from the storage / discharge fees paid by these agents. For the operation and dispatching agency, its primary role in energy management is to coordinate the overall energy supply and demand balance of the integrated energy distribution network, and to assume responsibility for supplementing energy shortages to external energy distribution networks and selling surplus energy. Therefore, when optimizing capacity configuration, shared energy storage operators must consider the actual electrical energy storage capacity required by each microgrid agent during different time periods within their operational cycle, ultimately achieving the optimal configuration.

[0118] Table 2 shows the operational benefits under the two scenarios.

[0119]

[0120] As shown in Table 2, in the scenario of resource separation, the power purchases by the power distribution network dispatching agency are significantly higher than in the scenario of energy sharing. This indicates that energy sharing can significantly reduce the dependence of microgrids on the external power grid.

[0121] The results of electricity trading between the integrated power distribution network and external energy networks, such as Figure 7 As shown, without considering energy sharing, the distribution network dispatching agency purchases significantly more electricity from the main grid, indicating that energy sharing can significantly reduce the microgrid's dependence on the external grid. Due to the coupling between electricity, gas, and heat networks, heat / gas shortages can also lead to power shortages.

[0122] Results of natural gas trading between integrated energy distribution networks and external energy networks, such as Figure 8 As shown, the dependence of natural gas on pipeline supply can be seen in both scenarios. Since the electricity-to-gas conversion cannot facilitate natural gas sharing, the pipeline supply is slightly higher in the resource-separated scenario than in the shared scenario.

[0123] Figure 9 The figure illustrates the changes in shared energy storage capacity and the changes in shared energy storage capacity used by microgrid 2 under two scenarios. As shown in the figure, the capacity requirements for shared energy storage are higher in the resource-separated scenario. However, considering energy sharing, the utilization rate of shared energy storage significantly increases, with its capacity decreasing from 967.1 kW to 502.0 kW. Clearly, the allocated capacity of shared energy storage to microgrid 2 decreases, indicating energy interaction between the microgrid groups.

[0124] Example 3

[0125] According to a second aspect of the present invention, the present invention provides a shared energy storage optimization configuration device for a shared energy storage structure of a railway traction substation, comprising: a memory having a computer processing program stored thereon; and a processor for executing the computer processing program in the memory to implement the shared energy storage optimization configuration method for a shared energy storage structure of a railway traction substation as described in Embodiment 1 or Embodiment 2.

[0126] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them; those skilled in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or make equivalent substitutions for some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for optimizing the configuration of shared energy storage in a railway traction substation shared energy storage structure, characterized in that, The shared energy storage structure for the railway traction substation includes: shared energy storage and several micro-energy networks containing the railway traction substation; each micro-energy network has an agent; the shared energy storage and each micro-energy network are respectively connected to the power grid; The shared energy storage optimization configuration method includes: A shared energy storage operation benefit model is established with the goal of maximizing the cycle benefits of shared energy storage; A microgrid agent operation efficiency model is established with the goal of minimizing the cycle operating cost of the microgrid; Based on the aforementioned microgrid agent operation efficiency model, a shared energy storage structure energy mutual assistance operation efficiency model is established with the objective of minimizing the total cycle operation cost of all microgrid agents. The objective function of the shared energy storage structure energy mutual assistance operation efficiency model is the sum of the operation efficiency objective functions of each microgrid agent; The constraints of the energy balance operation efficiency model of the shared energy storage structure are set, including: energy balance constraints and a set of shared energy storage operation constraints; By combining the shared energy storage structure energy mutual benefit operation efficiency model and the shared energy storage operation efficiency model, the shared energy storage configuration is optimized to obtain the storage capacity of shared energy storage configured for each micro energy grid agent.

2. The method for optimizing the configuration of shared energy storage for railway traction substation shared energy storage structures according to claim 1, characterized in that, The shared energy storage operation benefit model considers power cost, capacity cost, and periodic maintenance cost, as well as the charging and discharging fees charged to each microgrid agent. Its objective function is as follows: ； ； ； In the formula, To share the lifecycle benefits of energy storage, To share the cyclical benefits of energy storage, The overall lifecycle cost of shared energy storage, This represents the unit capacity price of shared energy storage leasing services; K is the total number of microgrid agents; T represents the operating cycle of shared energy storage leasing. These represent the storage and discharge power of the shared energy storage used by microgrid agent k during time period t; For shared energy storage leasing operation periods, These are the unit price per unit of power and the unit price per unit of capacity for shared energy storage, respectively. These are the power limit and rated capacity of shared energy storage, respectively. Indicates the lifespan of shared energy storage; This represents the periodic operation and maintenance costs of shared energy storage.

3. The method for optimizing the configuration of shared energy storage for railway traction substation shared energy storage structures according to claim 1, characterized in that, The microgrid agent operation benefit model considers the cost of purchased electricity, the cost of shared thermal storage capacity and power usage, the cost of main grid gas transmission, the operating cost of units within the microgrid, and the revenue from power supply, gas supply, and heating within the shared energy storage structure. Its objective function is as follows: ； In the formula, These represent the costs of electricity purchased by microgrid agent k, the costs of using shared energy storage capacity and power, the costs of gas transmission from the main grid, and the operating costs of units within the microgrid, respectively; T represents the operating cycle of the shared energy storage lease. These represent the revenue from electricity, gas, and heat supply within the shared energy storage structure, respectively. These represent the unit prices for purchasing electricity and gas from the main grid, respectively. These represent the unit prices for selling electricity, gas, and heat to the main grid, respectively. and These represent the electricity and natural gas purchased by microgrid agent k from the main grid at time t, respectively. These are the unit price per unit of power and the unit price per unit of capacity for shared energy storage, respectively. Indicates the lifespan of shared energy storage; This represents the periodic operation and maintenance cost of shared energy storage; These represent the shared energy storage power and capacity allocated to microgrid agent k, respectively. These represent the electricity, natural gas, and heat sold by microgrid agent k to the main grid at time t. This indicates the power consumption of the power-to-gas generator unit during operation. The coefficient for carbon dioxide consumption during the electricity-to-gas conversion; This indicates the price of the carbon source during the operation of the power-to-gas generator unit; This represents the actual output value of wind power. Forecast wind power output; For wind power grid connection price; These represent the natural gas production of the power-to-gas unit and the gas consumption of the combined heat and power unit, respectively.

4. The method for optimizing the configuration of shared energy storage for railway traction substation shared energy storage structures according to claim 3, characterized in that, The energy balance constraints of the shared energy storage structure energy mutual assistance operation benefit model are as follows: ； ； ； In the formula, Let them represent the electrical quantity, gas quantity, and heat generated by the energy interaction between microgrids k and l at time t, respectively. Let these represent the electrical load, gas load, and heat load of the microgrid k at time t, respectively. A collection of micro-energy network agents; These represent the gas production of the k-type power-to-gas generator unit in the microgrid and the gas consumption of the combined heat and power generation at time t, respectively. The heat input from the microgrid k cogeneration to the shared energy storage at time t; The heat input from the microgrid's k-electricity-to-gas generator unit to the shared energy storage at time t; These represent the heat released by the shared energy storage and the supercapacitor device that works in conjunction with the railway traction station's energy storage at time t to the micro-energy grid k.

5. The method for optimizing the configuration of shared energy storage for railway traction substation shared energy storage structures according to claim 4, characterized in that, The set of shared energy storage operation constraints includes: Constraints on shared energy storage sources: ； Shared energy storage lumped constraints: ； ； ； Quantitative constraints on the relationship between actual storage / discharge power and rated capacity of shared energy storage: ； In the formula, For time t, microgrid agent k uses shared energy storage power; The shared energy storage is input into the traction station system respectively; To provide shared energy storage power to new energy generator sets; These are the power limit and rated capacity of shared energy storage, respectively. These are the upper limits of the shared energy storage power and the upper limit of the discharge power that microgrid agent k can use; The upper limit of the storage capacity allocated to microgrid agent k for shared energy storage; This represents the storage / discharge coefficient.

6. The method for optimizing the configuration of shared energy storage for railway traction substation shared energy storage structures according to claim 5, characterized in that, The set of shared energy storage operation constraints also includes: Shared energy storage storage / deployment nonsimultaneity constraint: ； ； Shared energy storage periodic storage / discharge balance constraints: ； ； In the formula, Let be the storage / release state variable of microgrid agent k at time t, with a value of 0 or 1; For microgrid agent k, the shared energy storage discharge power is used at time t; The capacity status of shared energy storage at time t; This is the power loss factor; These represent the initial and final capacities of the shared energy storage within a single cycle.

7. The method for optimizing the configuration of shared energy storage for railway traction substation shared energy storage structures according to claim 6, characterized in that, The set of shared energy storage operation constraints also includes: Capacity constraints faced by microgrid k when using shared energy storage: ； ； In the formula, The capacity of shared energy storage used by microgrid agent k at time t; These are the shared energy storage efficiency and the energy release efficiency, respectively.

8. The method for optimizing the configuration of shared energy storage for railway traction substation shared energy storage structures according to claim 1, characterized in that, The constraints of the shared energy storage structure energy mutual assistance operation benefit model also include the constraints of non-simultaneous storage / discharge of supercapacitors and periodic storage / discharge balance constraints.

9. A shared energy storage optimization configuration device for railway traction substation shared energy storage structures, characterized in that, include: A memory that stores computer processing programs; A processor for executing a computer processing program in memory to implement the shared energy storage optimization configuration method for shared energy storage structures in railway traction substations as described in any one of claims 1-8.

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