A static-mobile energy storage collaborative space-time flexible regulation method

Abstract

The present application relates to a kind of static-mobile energy storage collaborative space-time flexible regulation method, it relates to a kind of energy storage optimization scheduling method, the method includes the following steps: (1) the distribution of regional integrated energy system new energy, load access characteristic and consumption demand are analyzed, and surplus model of renewable energy is constructed;(2) according to the source and load characteristics of regional integrated energy system, static energy storage charging and discharging scheduling model is constructed;(3) according to surplus model of renewable energy, the space-time scheduling strategy of mobile energy storage is proposed;(4) according to static energy storage charging and discharging scheduling model and the space-time scheduling strategy of mobile energy storage, the queuing model of static-mobile energy storage charging and discharging strategy is constructed;(5) according to the queuing model of static-mobile energy storage charging and discharging strategy, based on improved Lyapunov optimization, static-mobile energy storage collaborative dynamic scheduling is realized.The method of the present application provides support for the collaborative consumption of distributed renewable energy between regional integrated energy system.

Description

Technical Field

[0001] This invention relates to an energy storage optimization scheduling method, and more particularly to a spatiotemporal flexible control method for static-mobile energy storage coordination. Background Technology

[0002] Renewable energy is influenced by natural conditions, introducing randomness and volatility. Applying energy storage systems can effectively promote the use of renewable energy and ensure energy supply. Traditional energy storage systems are mostly static, only capable of peak shaving and valley filling within specific regions. However, due to the randomness of distributed energy generation and the mismatch between source and load capacity, wind and solar power curtailment or insufficient power supply frequently occur in regional power grids. Furthermore, limitations in transmission channel capacity make it difficult to achieve coordinated absorption of distributed renewable energy across regional power grids. Mobile energy storage systems, leveraging the capacity of urban transportation networks, can transfer electricity on both temporal and spatial scales, expanding the spatial scope of energy optimization and dispatching, and enabling coordinated absorption of distributed renewable energy across regional integrated energy systems.

[0003] Furthermore, the spatiotemporal coordinated scheduling of static and mobile energy storage systems requires consideration of complex decision-making problems involving multiple types of equipment and multiple time scales. Given the temporal coupling characteristics of static and mobile energy storage decisions, existing research typically employs Markov decision chains or dynamic optimization models to optimize their control strategies. These methods have high requirements for prior information on stochastic processes and also involve high computational complexity. Lyapunov optimization methods can solve the spatiotemporal coupling problem in energy storage decision-making, dynamically adjusting system behavior to balance multi-objective optimization and system stability. Therefore, introducing Lyapunov optimization to achieve spatiotemporal optimization control of coordinated static and mobile energy storage is of significant value for improving the operational efficiency and widespread application of energy storage systems, as well as enhancing the regional capacity for the coordinated absorption of distributed renewable energy. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a spatiotemporally flexible control method for static-mobile energy storage coordination.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] A spatiotemporally flexible control method for static-mobile energy storage coordination, comprising the following steps:

[0007] (1) Analyze the characteristics of distributed new energy sources, load access and consumption demand of regional integrated energy system, and construct a surplus model of renewable energy in regional power grid;

[0008] (2) Based on the source-load characteristics of the regional integrated energy system, propose control strategies for battery energy storage and hydrogen energy storage in the static energy storage system, and construct a static energy storage charging and discharging scheduling model;

[0009] (3) Based on the surplus of renewable energy in the regional integrated energy system, propose a time-space scheduling strategy for mobile energy storage systems;

[0010] (4) Based on the static energy storage charging and discharging scheduling model and the time-space scheduling strategy of mobile energy storage, a queuing model for the static-mobile energy storage charging and discharging strategy is constructed.

[0011] (5) Based on the queuing model of static-mobile energy storage charging and discharging strategy, static-mobile energy storage collaborative dynamic scheduling is realized based on improved Lyapunov optimization.

[0012] Step (1) specifically involves: analyzing the characteristics of distributed new energy sources, load access, and consumption demand of the regional integrated energy system, and calculating the surplus calculation formula of the renewable energy system, which can be specifically described as:

[0013]

[0014] In the formula, It is the duration of charging / discharging. It is a region a In the j Hourly renewable energy generation It is a region a In the j Total electricity demand per hour For the region a Renewable energy capacity.

[0015] Based on the constraints of thermal and electrical power balance, the model is constructed with the objective of minimizing the operating cost of the integrated energy system, specifically as follows:

[0016] (101) Electric boilers generate heat energy by consuming electricity. When heat load is required, waste heat is recovered and released, realizing the sustainable use of energy. The specific model of an electric boiler is as follows:

[0017]

[0018] In the formula, G EB ( t )and P EB ( t These represent the thermal power and power consumption of the electric boiler, respectively. EB It's the efficiency of the electric boiler. G EB.max ( t () is the maximum heat output of the electric boiler. G ice ( t) is the recovered waste heat. ice It is the system's waste heat recovery efficiency;

[0019] (102) Gas-fired boilers provide heat by consuming gas. The specific model of a gas-fired boiler is as follows:

[0020]

[0021] In the formula, G Q ( t This refers to the waste heat recovery efficiency of a gas-fired boiler. Q ( t ) is at time t The amount of gas at any given time. Q It refers to gas heating efficiency. G Qmax ( t () is the maximum heat production. G Load ( t ) is in t Calorie requirements at any given time;

[0022] (103) The power balance constraints of the integrated energy system are as follows:

[0023]

[0024] In the formula, It is photovoltaic power generation. It is wind power generation. It is the demand load of the integrated energy system, and the electric boiler and hydrogen storage system are coupling devices between the power system and the thermal system;

[0025] (104) The operating cost of the integrated energy system is specifically described as follows:

[0026]

[0027] In the formula, f 1 (t) is the cost of hydrogen energy trading. f 2 ( t This is the cost of natural gas trading. f 3 ( t The cost of electricity trading is... f 4 ( t This is to reduce the total cost of wind and solar power generation.

[0028] Step (2) specifically involves: constructing a static energy storage charging and discharging scheduling model based on the battery energy storage and hydrogen energy storage control strategies in static energy storage, so as to realize peak shaving and valley filling of electricity.

[0029] (201) The specific model of charging and discharging of the battery energy storage system can be described as follows:

[0030]

[0031] In the formula, E B ( t )yes t The capacity of the battery energy storage system at all times. It is the capacity decay rate. P B.D ( t )and P B.C ( t At any moment t Discharge and charge power, B.D and B.C It refers to discharge and charge efficiency.

[0032] (202) The scheduling model for hydrogen energy storage in a static energy storage system is as follows:

[0033] The electrolyzer produces hydrogen by consuming electricity and water. Specifically, the hydrogen produced by the electrolyzer is:

[0034]

[0035]

[0036] In the formula, It is the electrolytic cell in t The amount of hydrogen produced at any given time EL It's the hydrogen production efficiency. It is the power of the electrolytic cell. and These represent the maximum and minimum power of the electrolytic cell, respectively.

[0037] The amount of hydrogen produced by the hydrogen storage system is as follows:

[0038]

[0039] In the formula, HS m ( t ) is in t Hydrogen quantity at any time Indicates in t The amount of hydrogen consumed at any given time. and This represents the volume of hydrogen traded.

[0040] Step (3) specifically involves: Mobile energy storage, through a comprehensive assessment of the renewable energy levels in both the origin and destination regions, proposing a time-space scheduling strategy for mobile energy storage. A key part of this strategy is determining the charging and discharging power, which is determined by the following four conditions:

[0041] (301) Both regions experienced a surplus of renewable energy, i.e., when The mobile energy storage system charges in the current area. The charging capacity of the mobile energy storage system can be specifically described as follows:

[0042]

[0043]

[0044] In the formula, the first term is the remaining energy storage capacity of the mobile energy storage system based on the remaining renewable energy production. E Mtravel It refers to the amount of electricity used when mobile energy storage is moved from one region to another. C M It refers to the capacity of mobile energy storage systems. c It refers to the battery capacity of the mobile energy storage system. It is the state of charge of the mobile energy storage system at its current location.

[0045] The charging state of the target area can be described as follows:

[0046]

[0047] In the formula, This is the minimum requirement for charging batteries in mobile energy storage systems.

[0048] (302) There is a surplus of renewable energy production in the current region, but there is no surplus of renewable energy production in the next region, i.e. The mobile energy storage system charges in the current area. The charging capacity of the mobile energy storage system can be specifically described as follows:

[0049]

[0050] In the formula, the first term assesses the regional... a To the area b The required power and the state of charge of the target area are estimated by the formula above (301).

[0051] (303) The next region has a surplus of renewable energy, but the current region does not have a surplus of renewable energy, i.e. The mobile energy storage system charging in the next area indicates that the mobile energy storage system can discharge in the current area. The discharge capacity of the mobile energy storage system can be specifically described as follows:

[0052]

[0053]

[0054] In the formula, the first term evaluates the need to obtain information from the location. b Delivery to location a The amount of electricity, C Mi This refers to the initial amount of electricity stored by the mobile energy storage system when it arrives at the current area. The target charge state at the current location can be calculated using the following formula:

[0055]

[0056] (304) Neither region has a surplus of renewable energy production, i.e. The mobile energy storage system discharges at its current location. The discharge capacity of the mobile energy storage system can be specifically described as follows:

[0057]

[0058] In the formula, the first term indicates that the available energy storage in the mobile energy storage system will be allocated proportionally to the power generation based on the lack of renewable energy generation, and the target charge state of the current area is calculated by the formula in (303).

[0059] The constraints of mobile energy storage systems can be specifically described as follows:

[0060]

[0061]

[0062]

[0063]

[0064] In the formula, e ev,n , e min and e max These represent the minimum and maximum charging and discharging power, respectively.

[0065] Step (4) specifically involves: constructing a queuing model for the static-mobile energy storage charging and discharging strategy, and establishing a virtual queuing model for energy storage to represent the energy storage status for time coupling constraints.

[0066] The queuing model for the static-mobile energy storage charging and discharging strategy can be specifically represented as follows:

[0067]

[0068] In the formula, A ( t ), Z ( t )and V ( t This indicates the energy change of an energy storage device. , and Often used to ensure HS m ( t ), E ( t )and It is a non-negative constant.

[0069] In step (5), the Lyapunov function is defined. L ( t The degree of crowding in a queue can be described using the following terms:

[0070]

[0071] based on L ( t Function creation ( t The drift of the queue is represented by ) when L ( t When the deviation is small, the queue stability is good. To ensure the stability of the queuing model, the deviation must be minimized. ( t ):

[0072]

[0073] Therefore, the definition J It represents a trade-off between two objectives. J A larger value indicates that minimizing cost takes precedence over minimizing drift. J A smaller value means that minimizing cost is a lower priority than minimizing drift.

[0074] For battery energy storage systems, hydrogen energy storage systems, and mobile energy storage systems, considering capacity constraints under the Lyapunov variable case, the specific details are as follows:

[0075]

[0076]

[0077]

[0078]

[0079] In the formula, when At that time, the capacity constraints of battery energy storage systems, hydrogen energy storage systems, and mobile energy storage systems will always be met.

[0080] Based on improved Lyapunov optimization, dynamic scheduling of static and mobile energy storage is achieved. This involves rationally allocating and scheduling static and mobile energy storage systems within each time period to maximize energy utilization. The objective function can be equivalent to a stochastic network optimization problem.

[0081]

[0082] In the formula, C 1( t () represents the total cost, including the costs of natural gas trading, electricity trading, and wind and solar power generation reductions.

[0083] Compared with existing technologies, the present invention has the following advantages: a control strategy model for static-mobile energy storage coordination is established based on the control strategies of mobile energy storage and static energy storage under different conditions; based on the improved Lyapunov optimization method, the static energy storage system and the mobile energy storage system are rationally allocated and scheduled in each time period to maximize the utilization rate of renewable energy. Attached Figure Description

[0084] Figure 1 This is a flowchart of a spatiotemporal flexible control method for static-mobile energy storage coordination in this invention;

[0085] Figure 2 This test scenario examines the power differences between renewable energy generation and load in three regions.

[0086] Figure 3 The test scenario measures the charging and discharging power of electrochemical energy storage and mobile energy storage in three regions. Detailed Implementation

[0087] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0088] Implementation, for example Figure 1 As shown, a spatiotemporally flexible control method for static-mobile energy storage synergy is proposed, which includes the following steps:

[0089] Step 1: Analyze the access type and power generation characteristics of regional new energy sources, collect new energy power generation data, and also collect and analyze relevant data on load access characteristics and consumption demand.

[0090] Step 2: By analyzing regional new energy and load-related data, the formula for calculating the renewable energy surplus in the regional power grid can be specifically described as follows:

[0091]

[0092] In the formula, It is the duration of charging / discharging. It is a region a In the j Hourly renewable energy generation It is a region a In the j Total electricity demand per hour For the region a Renewable energy capacity.

[0093] Step 3: Based on the constraints of thermal and electrical power balance, model the system with the objective of minimizing the operating cost of the integrated energy system. Specifically:

[0094] Electric boilers generate heat by consuming electricity. When a heat load is needed, waste heat is recovered and released, achieving sustainable energy utilization. The specific model of an electric boiler is as follows:

[0095]

[0096] In the formula, G EB ( t )and P EB ( t These represent the thermal power and power consumption of the electric boiler, respectively. EB It's the efficiency of the electric boiler. G EB.max ( t () is the maximum heat output of the electric boiler. G ice ( t ) is the recovered waste heat. ice It refers to the system's waste heat recovery efficiency.

[0097] Gas-fired boilers provide heat by consuming natural gas. A specific model of a gas-fired boiler is as follows:

[0098]

[0099] In the formula, G Q ( t This refers to the waste heat recovery efficiency of a gas-fired boiler. Q ( t ) is at time t The amount of gas at any given time. Q It is the gas heating efficiency. G Qmax ( t () is the maximum heat production. G Load ( t ) is in t Calorie requirements at any given time;

[0100] The power balance constraints of the integrated energy system are as follows:

[0101]

[0102] In the formula, It is photovoltaic power generation. It is wind power generation. It is the demand load of the integrated energy system, and the electric boiler and hydrogen storage system are coupling devices between the power system and the thermal system;

[0103] The operating costs of an integrated energy system are specifically described as follows:

[0104]

[0105] In the formula, f 1 (t) is the cost of hydrogen energy trading. f 2 ( t This is the cost of natural gas trading. f 3 ( t The cost of electricity trading is... f 4 ( t This is to reduce the total cost of wind and solar power generation.

[0106] Step 4: The battery energy storage system in the static energy storage system is specifically designed to meet electricity demand. The specific model of the battery energy storage system can be described as follows:

[0107]

[0108]

[0109]

[0110]

[0111] In the formula, E B ( t )yes t The capacity of the battery energy storage system at all times. It is the capacity decay rate. P B.D ( t )and P B.C ( t At any moment t Discharge and charge power, B.D and B.C It refers to discharge and charge efficiency. P B ( t (This refers to the rated power.) I B,C ( t )and I B,D ( t () is a binary variable for charging and discharging; it must not be charged and discharged simultaneously. C B It is the maximum capacity of the battery energy storage system. D That is the maximum emission depth.

[0112] The hydrogen energy storage system model in a static energy storage system can be specifically described as follows:

[0113]

[0114]

[0115]

[0116]

[0117]

[0118]

[0119] In the formula, HS m ( t ) is in t Hydrogen quantity at any time Indicates in t The amount of hydrogen consumed at any given time. and This represents the volume of hydrogen traded. HS min and HS max These are the minimum and maximum hydrogen storage capacities, respectively. It is the electrolytic cell in t The amount of hydrogen produced at any given time and These are the maximum and minimum hydrogen consumption rates, respectively. and That is the maximum trading value of hydrogen. and It is a binary variable and cannot be charged and discharged simultaneously.

[0120] Step 5: Mobile energy storage proposes a time-based scheduling strategy by comprehensively assessing the levels of renewable energy in both the origin and destination regions. A key part of this strategy is determining the charging and discharging power, which is determined by the following four conditions:

[0121] Both regions are experiencing a surplus of renewable energy, that is, when The mobile energy storage system charges in the current area. The charging capacity of the mobile energy storage system can be specifically described as follows:

[0122]

[0123]

[0124] In the formula, the first term is the remaining energy storage capacity of the mobile energy storage system based on the remaining renewable energy production. E Mtravel It refers to the amount of electricity used by mobile energy storage to move from one region to another. C M It refers to the capacity of the mobile energy storage system. c It refers to the battery capacity of the mobile energy storage system. It is the state of charge of the mobile energy storage system at its current location.

[0125] The charging state of the target area can be described as follows:

[0126]

[0127] In the formula, SoCa Mlow This is the minimum requirement for charging batteries in mobile energy storage systems.

[0128] The current region has a surplus of renewable energy production, but the next region will not have a surplus of renewable energy production. The mobile energy storage system charges in the current area. The charging capacity of the mobile energy storage system can be specifically described as follows:

[0129]

[0130] In the formula, the first term assesses the regional... a To the area b The required power and the state of charge of the target area are estimated based on the first case above.

[0131] The next region will have a surplus of renewable energy, but the current region will not have a surplus of renewable energy. The mobile energy storage system charging in the next area indicates that the mobile energy storage system can discharge in the current area. The discharge capacity of the mobile energy storage system can be specifically described as follows:

[0132]

[0133]

[0134] In the formula, the first term evaluates the need to obtain information from the location. b Delivery to location a The amount of electricity, C Mi This refers to the initial amount of electricity stored by the mobile energy storage system when it arrives at the current area. The target charge state at the current location can be calculated using the following formula:

[0135]

[0136] Neither region has a surplus of renewable energy production. The mobile energy storage system discharges at its current location. The discharge capacity of the mobile energy storage system can be specifically described as follows:

[0137]

[0138] In the formula, the first term indicates that the available energy storage in the mobile energy storage system will be allocated proportionally to the amount of electricity generated based on the lack of renewable energy generation, and the target charge state of the current region is calculated by the formula in the third region.

[0139] Step 6: The queuing model for the static-mobile energy storage charging and discharging strategy can be specifically represented as follows:

[0140]

[0141] In the formula, A ( t ), Z ( t )and V ( t This indicates the energy change of an energy storage device. , and Often used to ensure HS m ( t ), E ( t )and It is a non-negative constant.

[0142] Step 7: Define the Lyapunov function L ( tThe degree of crowding in a queue can be described using the following terms:

[0143]

[0144] based on L ( t Function creation ( t The drift of the queue is represented by ) when L ( t When the deviation is small, the queue stability is good. To ensure the stability of the queuing model, the deviation must be minimized. ( t ):

[0145]

[0146] Therefore, the definition J It represents a trade-off between two objectives. J A larger value indicates that minimizing cost takes precedence over minimizing drift. J A smaller value means that minimizing cost is a lower priority than minimizing drift.

[0147] Step 8: Considering capacity constraints in the Lyapunov variable case for battery energy storage systems, hydrogen energy storage systems, and mobile energy storage systems, specifically:

[0148]

[0149]

[0150]

[0151]

[0152] In the formula, when At that time, the capacity constraints of battery energy storage systems, hydrogen energy storage systems, and mobile energy storage systems will always be met.

[0153] Based on improved Lyapunov optimization, dynamic scheduling of static and mobile energy storage is achieved. This involves rationally allocating and scheduling static and mobile energy storage systems within each time period to maximize energy utilization. The objective function can be equivalent to a stochastic network optimization problem.

[0154]

[0155] In the formula, C 1( t () represents the total cost, including the costs of natural gas trading, electricity trading, and wind and solar power generation reductions.

[0156] This embodiment is based on the 2022 power generation statistics of Shanghai, including renewable energy wind and solar power generation, and the difference between renewable energy power generation and demand. It uses three regions within an integrated energy system, where these regions are entirely self-sufficient in wind and solar power generation. Region 1 is characterized by high wind power capacity; Region 2 by high load demand; and Region 3 by a more balanced generation and consumption, with higher load demand only during specific peak periods. The integrated energy system includes three mobile energy storage systems. Each mobile energy storage system has a rated power of 20kW and a rated capacity of 60kWh. Moving a mobile energy storage system from one region to another consumes 1kWh, and the initial state of charge (SOC) of the mobile energy storage system is 0.2. This invention's method can quantify the spatiotemporal flexibility of static-mobile energy storage synergy, and the power differences between renewable energy generation and load, such as... Figure 2 As shown; the charge and discharge power of electrochemical energy storage and mobile energy storage in the three regions, as follows: Figure 3 As shown.

[0157] The application scenarios of this embodiment are as follows: providing technical support for complex regional energy systems of static-mobile energy storage systems, maximizing energy utilization based on improved Lyapunov optimization; providing technical support for achieving spatiotemporal power balance of regional energy, and promoting the utilization of renewable energy.

Claims

1. A spatiotemporally flexible control method for static-mobile energy storage coordination, characterized in that, The method includes the following steps: (1) Analyze the characteristics of distributed new energy sources, load access and consumption demand of regional integrated energy system, and construct a surplus calculation model of renewable energy in regional power grid; (2) Based on the source-load characteristics of the regional integrated energy system, propose control strategies for battery energy storage and hydrogen energy storage in the static energy storage system, and construct a static energy storage charging and discharging scheduling model; (3) Based on the surplus of renewable energy in the regional integrated energy system, propose a time-space scheduling strategy for mobile energy storage systems; (4) Based on the static energy storage charging and discharging scheduling model and the time-space scheduling strategy of mobile energy storage, a queuing model for the static-mobile energy storage charging and discharging strategy is constructed. (5) Based on the queuing model of static-mobile energy storage charging and discharging strategy, static-mobile energy storage collaborative dynamic scheduling is realized based on improved Lyapunov optimization.

2. The spatiotemporal flexible control method for static-mobile energy storage coordination according to claim 1, characterized in that, In step (1): By analyzing the characteristics of distributed new energy sources, load access, and consumption demand of the regional integrated energy system, the surplus calculation formula of renewable energy in the regional power grid is calculated, specifically as follows: In the formula, It is the duration of charging / discharging. It is a region a In the j Hourly renewable energy generation It is a region a In the j Total electricity demand per hour For the region a Renewable energy capacity.

3. The spatiotemporal flexible control method for static-mobile energy storage coordination according to claim 2, characterized in that, In step (1), the model is built based on the constraints of thermal power and electrical power balance, with the goal of minimizing the operating cost of the integrated energy system. Specifically: (101) Electric boilers generate heat energy by consuming electricity. When heat load is required, waste heat is recovered and released, realizing the sustainable use of energy. The specific model of an electric boiler is as follows: In the formula, G EB ( t )and P EB ( t These represent the thermal power and power consumption of the electric boiler, respectively. EB It's the efficiency of the electric boiler. G EB.max ( t () is the maximum heat output of the electric boiler. G ice ( t ) is the recovered waste heat. ice It is the system's waste heat recovery efficiency; (102) Gas-fired boilers provide heat by consuming gas. The specific model of a gas-fired boiler is as follows: In the formula, G Q ( t This refers to the waste heat recovery efficiency of a gas-fired boiler. Q ( t ) is at time t The amount of gas at any given time. Q It is the gas heating efficiency. G Qmax ( t () is the maximum heat production. G Load ( t ) is in t Calorie requirements at any given time; (103) The power balance constraints of the integrated energy system are as follows: In the formula, It is photovoltaic power generation. It is wind power generation. It is the demand load of the integrated energy system, and the electric boiler and hydrogen storage system are coupling devices between the power system and the thermal system; (104) The operating cost of the integrated energy system is specifically described as follows: In the formula, f 1 (t) is the cost of hydrogen energy trading. f 2 ( t This is the cost of natural gas trading. f 3 ( t The cost of electricity trading is... f 4 ( t This is to reduce the total cost of wind and solar power generation.

4. The spatiotemporal flexible control method for static-mobile energy storage coordination according to claim 3, characterized in that, In step (2), the scheduling model for battery energy storage in the static energy storage system is as follows: In the formula, E B ( t )yes t The capacity of the battery energy storage system at all times. It is the capacity decay rate. P B.D ( t )and P B.C ( t At any moment t Discharge and charge power, B.D and B.C It refers to discharge and charge efficiency.

5. The spatiotemporal flexible control method for static-mobile energy storage coordination according to claim 4, characterized in that, In step (2), the scheduling model for hydrogen energy storage in the static energy storage system is as follows: The electrolyzer produces hydrogen by consuming electricity and water. Specifically, the hydrogen produced by the electrolyzer is: In the formula, It is the electrolytic cell in t The amount of hydrogen produced at any given time It's the hydrogen production efficiency. It is the power of the electrolytic cell. and These represent the maximum and minimum power of the electrolytic cell, respectively. The amount of hydrogen produced by the hydrogen storage system is as follows: In the formula, HS m ( t ) is in t Hydrogen quantity at any time Indicates in t The amount of hydrogen consumed at any given time. and This represents the volume of hydrogen traded.

6. The spatiotemporal flexible control method for static-mobile energy storage coordination according to claim 5, characterized in that, Step (3) is as follows: (301) If both regions experience a surplus of renewable energy, i.e. when The mobile energy storage system charges in the current area. The charging capacity of the mobile energy storage system is specifically described as follows: In the formula, the first term is the remaining energy storage capacity of the mobile energy storage system based on the remaining renewable energy production. E Mtravel It refers to the amount of electricity used when mobile energy storage is moved from one region to another. C M It refers to the capacity of mobile energy storage systems. c It refers to the battery capacity of the mobile energy storage system. It is the state of charge of the mobile energy storage system when it arrives at its current location; The charging status of the target area is described as follows: In the formula, This is the minimum requirement for charging batteries in mobile energy storage systems; (302) If there is a surplus of renewable energy production in the current region, but no surplus of renewable energy production in the next region, i.e. The mobile energy storage system charges in the current area. The charging capacity of the mobile energy storage system is specifically described as follows: In the formula, the first term assesses the regional... a To the area b The required power and the state of charge of the target area are estimated by the formula in step (301); (303) If the next region has a surplus of renewable energy, but the current region does not have a surplus of renewable energy, i.e. The mobile energy storage system charging in the next area indicates that the mobile energy storage system can discharge in the current area. The discharge capacity of the mobile energy storage system is specifically described as follows: In the formula, the first term evaluates the need to obtain information from the location. b Delivery to location a The amount of electricity, C Mi It is the initial amount of electricity stored when the mobile energy storage system arrives at the current area. The target charge state at the current location is calculated by the following formula: ； (304) If neither region has a surplus of renewable energy production, i.e. The mobile energy storage system discharges at its current location. The discharge capacity of the mobile energy storage system is specifically described as follows: In the formula, the first term indicates that the available energy storage in the mobile energy storage system will be allocated proportionally to the power generation based on the lack of renewable energy generation, and the target charge state of the current area is calculated by the formula in step (303). The constraints of mobile energy storage systems are specifically described as follows: In the formula, e min and e max These represent the minimum and maximum charging and discharging power, respectively.

7. The spatiotemporal flexible control method for static-mobile energy storage coordination according to claim 6, characterized in that, In step (4), the queuing model for the static-mobile energy storage charging and discharging strategy is as follows: In the formula, A ( t ), Z ( t )and V ( t This indicates the energy change of an energy storage device. , and Often used to ensure HS m ( t ), E ( t )and It is a non-negative constant.

8. The spatiotemporal flexible control method for static-mobile energy storage coordination according to claim 7, characterized in that, In step (5), the Lyapunov function is defined. L ( t (), to describe the congestion level of the queue, specifically: based on L ( t Function creation ( t To represent queue drift and minimize deviation ( t ): definition J This indicates a trade-off between two objectives. J A larger value indicates that minimizing cost takes precedence over minimizing drift. J A smaller value means that minimizing cost is a lower priority than minimizing drift.

9. A spatiotemporally flexible control method for static-mobile energy storage coordination according to claim 8, characterized in that, In step (5), under the Lyapunov variable case of battery energy storage system, hydrogen energy storage system and mobile energy storage system, capacity constraints are considered, specifically as follows: In the formula, when At that time, the capacity constraints of battery energy storage systems, hydrogen energy storage systems, and mobile energy storage systems will always be met.

10. The spatiotemporal flexible control method for static-mobile energy storage coordination according to claim 9, characterized in that, In step (5), based on improved Lyapunov optimization, dynamic scheduling of static-mobile energy storage is achieved. Static and mobile energy storage systems are rationally allocated and scheduled in each time period to maximize energy utilization. Specifically: This objective function is equivalent to a stochastic network optimization problem: In the formula, C 1( t The total cost is represented by , which includes electricity trading costs and the costs of wind and solar power generation reductions.

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