Multi-microgrid system scheduling method, electronic equipment, storage medium and product

Abstract

The invention discloses a multi-microgrid system scheduling method, electronic equipment, a storage medium and a product. The method comprises the following steps: analyzing system operation parameters by using an electricity-hydrogen coupling multi-microgrid model, and constructing a multi-microgrid system topological structure under electricity-hydrogen multi-energy interaction; determining a hydrogen transport vehicle travel dynamic planning model based on system operation parameters and the multi-microgrid system topological structure; building a multi-microgrid flexible hydrogen transport model based on the system operation parameters, the multi-microgrid system topological structure and the hydrogen transport vehicle travel dynamic planning model; building a multi-microgrid system economic dispatching model based on the system operation parameters, the multi-microgrid system topological structure, the hydrogen transport vehicle travel dynamic planning model and the multi-microgrid flexible hydrogen transport model; and solving the economic dispatching model of the multi-microgrid system, and outputting a solving result of a dispatching cycle. According to the method, by introducing the inter-microgrid flexible hydrogen transport model, the economic operation level of the electricity-hydrogen coupling multi-microgrid can be effectively improved by using the flexible hydrogen transport model.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of power technology, and in particular to a multi-microgrid system scheduling method, electronic equipment, storage medium, and product. Background Art

[0002] The economic operation of multiple microgrids coupled with electricity and hydrogen is a key approach to achieving multi-energy synergy optimization and efficient regional energy allocation. This operating model integrates electricity and hydrogen energy carriers within and outside the microgrid, combining renewable energy generation, hydrogen production through water electrolysis, energy storage, and load-side management to create an energy system with self-balancing capabilities and external complementarity, thereby improving overall energy utilization efficiency and operational economics.

[0003] Against the backdrop of energy transformation and the rapid development of distributed functions, the existing electricity-hydrogen coupled multi-microgrid system has problems such as poor flexibility due to fixed hydrogen transmission methods and high operating costs. Summary of the Invention

[0004] The present invention provides a multi-microgrid system scheduling method, electronic equipment, storage medium and product to solve the problems of the existing electricity-hydrogen coupled multi-microgrid system, such as poor flexibility caused by the fixed hydrogen transmission method and high operating costs.

[0005] According to one aspect of the present invention, a multi-microgrid system scheduling method is provided, comprising:

[0006] Use the electricity-hydrogen coupled multi-microgrid model to analyze system operating parameters and construct the multi-microgrid system topology structure under the electricity-hydrogen multi-energy interaction;

[0007] Determine a hydrogen transport vehicle travel dynamic planning model based on the system operating parameters and the multi-microgrid system topology, wherein the hydrogen transport vehicle travel dynamic planning model is used to characterize the transportation behavior of the hydrogen transport vehicle;

[0008] Constructing a multi-microgrid flexible hydrogen transportation model based on the system operating parameters, the multi-microgrid system topology and the hydrogen transportation vehicle travel dynamic planning model;

[0009] Constructing a multi-microgrid system economic dispatch model based on the system operating parameters, the multi-microgrid system topology, the hydrogen transport vehicle travel dynamic planning model, and the multi-microgrid flexible hydrogen transport model;

[0010] The economic dispatch model of the multi-microgrid system is solved, and a solution result of a dispatch cycle is output.

[0011] According to another aspect of the present invention, a multi-microgrid system scheduling device is provided, comprising:

[0012] The analysis module is used to analyze the system operating parameters using the electricity-hydrogen coupled multi-microgrid model and construct the multi-microgrid system topology under the electricity-hydrogen multi-energy interaction;

[0013] A determination module is used to determine a dynamic planning model for hydrogen transport vehicle travel based on the system operating parameters and the multi-microgrid system topology, wherein the dynamic planning model for hydrogen transport vehicle travel is used to characterize the transportation behavior of the hydrogen transport vehicle;

[0014] A first construction module is configured to construct a multi-microgrid flexible hydrogen transportation model based on the system operating parameters, the multi-microgrid system topology, and the hydrogen transportation vehicle travel dynamic planning model;

[0015] The second construction module is used to construct an economic dispatch model of the multi-microgrid system based on the system operating parameters, the multi-microgrid system topology, the hydrogen transport vehicle travel dynamic planning model and the multi-microgrid flexible hydrogen transportation model;

[0016] The output module is used to solve the economic dispatch model of the multi-microgrid system and output the solution result of a dispatch cycle.

[0017] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising: at least one processor;

[0018] and a memory communicatively coupled to the at least one processor;

[0019] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the multi-microgrid system scheduling method described in any embodiment of the present invention.

[0020] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the multi-microgrid system scheduling method according to any embodiment of the present invention when executed.

[0021] According to another aspect of the present invention, a computer program product is provided. The computer program product includes a computer program. When the computer program is executed by a processor, the multi-microgrid system scheduling method according to any embodiment of the present invention is implemented.

[0022] The technical solution of the embodiment of the present invention solves the problems of the existing electricity-hydrogen coupled multi-microgrid system caused by the fixed hydrogen transmission method, such as poor flexibility and high operating costs, by introducing a flexible hydrogen transportation model between microgrids, and achieves the beneficial effect of effectively improving the economic operation level of the electricity-hydrogen coupled multi-microgrid.

[0023] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0025] Figure 1 A schematic flow chart of a multi-microgrid system scheduling method provided in Embodiment 1 of the present invention;

[0026] Figure 2 A schematic flow chart of a multi-microgrid system scheduling method provided in the second embodiment of the present invention;

[0027] Figure 3 A flowchart of a multi-microgrid system scheduling method provided in Embodiment 3 of the present invention;

[0028] Figure 4 A flowchart of a multi-microgrid system scheduling method provided in a fourth embodiment of the present invention;

[0029] Figure 5 A schematic diagram of the electricity-hydrogen balance results corresponding to scenario 3 provided in Example 4 of the present invention;

[0030] Figure 6 A schematic diagram of the flexible hydrogen transportation results between microgrids corresponding to Scenario 3 provided in Example 4 of the present invention;

[0031] Figure 7 A schematic structural diagram of a multi-microgrid system scheduling device provided in a fifth embodiment of the present invention;

[0032] Figure 8 A schematic structural diagram of an electronic device for multi-microgrid system scheduling according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only embodiments of a part of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present invention. It should be understood that the various steps described in the method implementation mode of the present invention can be performed in different orders and / or in parallel. In addition, the method implementation mode may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0034] As used herein, the term "including" and its variations are open-ended, i.e., "including but not limited to." The term "based on" means "based, at least in part, on." The term "one embodiment" means "at least one embodiment," the term "another embodiment" means "at least one additional embodiment," and the term "some embodiments" means "at least some embodiments." Other terms are defined in the following description.

[0035] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. 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 necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0036] It should be noted that the modifications of "one" and "multiple" mentioned in the present invention are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0037] The names of the messages or information exchanged between multiple devices in the embodiments of the present invention are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0038] Example 1

[0039] Figure 1This is a flow chart of a multi-microgrid system scheduling method provided in Example 1 of the present invention. The method is applicable to the operation scheduling of an electricity-hydrogen coupled multi-microgrid system. The method can be executed by a multi-microgrid system scheduling device, wherein the device can be implemented by software and / or hardware and is generally integrated on an electronic device. In this embodiment, the electronic device includes but is not limited to: computer equipment.

[0040] like Figure 1 As shown, a multi-microgrid system scheduling method provided by the first embodiment of the present invention includes the following steps:

[0041] S110. Use the electricity-hydrogen coupled multi-microgrid model to analyze the system operating parameters and construct the multi-microgrid system topology under the electricity-hydrogen multi-energy interaction.

[0042] In this embodiment, an electric-hydrogen coupled multi-microgrid model for multi-network collaborative operation is constructed based on the selected electric-hydrogen coupled multi-microgrid system, and a detailed analysis is conducted on the energy flow relationship and cost of each link such as hydrogen production, storage, transportation and utilization. Research is carried out around the multiple load demands of the area where the electric-hydrogen coupled multi-microgrid is located, and the system operation parameters are analyzed; the energy interaction mechanism between multiple microgrids is analyzed, and from the perspective of electric-hydrogen multi-energy interaction, the flexible and economic operation capability of the electric-hydrogen coupled multi-microgrid system under multi-energy collaboration is deeply explored, and the multi-microgrid system topology structure under electric-hydrogen multi-energy interaction is constructed.

[0043] Among them, the electric-hydrogen coupled multi-microgrid system is an advanced energy system that deeply combines hydrogen energy with power microgrids. Through the cross-temporal and spatial energy transfer characteristics of hydrogen energy, it improves the flexibility, reliability and low carbon nature of the coordinated operation of multiple microgrids.

[0044] Among them, the system operating parameters may include electricity load, hydrogen load and wind and photovoltaic power generation forecast values.

[0045] S120. Determine a dynamic planning model for hydrogen transport vehicle travel based on the system operating parameters and the multi-microgrid system topology, where the dynamic planning model for hydrogen transport vehicle travel is used to characterize the transportation behavior of the hydrogen transport vehicle.

[0046] Among them, according to the topological structure of the multi-microgrid system, the travel planning model of hydrogen transport vehicles based on the traffic road network is studied. By incorporating road congestion information into the road right analysis and considering the physical parameters of different road designs, a dynamic planning model for hydrogen transport vehicle travel is formed to achieve accurate characterization of the transportation behavior of hydrogen transport vehicles.

[0047] S130. Construct a multi-microgrid flexible hydrogen transportation model based on the system operating parameters, the multi-microgrid system topology and the hydrogen transportation vehicle travel dynamic planning model.

[0048] Among them, flexible hydrogen transportation among multiple microgrids is an important path to improve the coordinated operation capabilities of regional energy systems. It is particularly suitable for scenarios such as uneven hydrogen production and demand between different microgrids and spatiotemporal resource mismatches. By introducing hydrogen transport vehicles to achieve dynamic hydrogen transportation between microgrids, it not only breaks the spatial limitations of traditional hydrogen supply, but also enhances the system's responsiveness to fluctuations in renewable energy and its resource mutual assistance capabilities. This method relies on technical support such as on-board hydrogen storage, route planning, and scheduling optimization. During operation, it is necessary to coordinate and consider multiple factors such as the time-varying nature of hydrogen sources, differences in load demand, road traffic conditions, and vehicle scheduling strategies. The introduction of a flexible hydrogen transportation mechanism will help to build a spatiotemporal buffer mechanism for hydrogen supply, improve the efficiency of coordinated hydrogen supply among multiple microgrids, and improve the overall economy of the system.

[0049] In this embodiment, based on the spatiotemporal behavior characteristics of hydrogen transport vehicles in the traffic network, a flexible hydrogen transport scheduling model is constructed that can characterize transportation time constraints and path accessibility.

[0050] Among them, when there is a shortage of hydrogen energy supply in one or some microgrids, timely replenishment will be carried out from other microgrids through hydrogen transport vehicles to achieve hydrogen energy balance within different microgrids and enhance the collaborative support capabilities between microgrids.

[0051] S140. Construct an economic dispatch model for a multi-microgrid system based on the system operating parameters, the multi-microgrid system topology, the hydrogen transport vehicle travel dynamic planning model, and the multi-microgrid flexible hydrogen transport model.

[0052] In actual dispatch, different microgrids differ significantly in terms of electricity load, hydrogen load, resource endowment, and equipment composition, necessitating a flexible energy coordination mechanism to achieve a multi-objective balance. Especially in the context of increasing volatility in renewable energy and dynamic changes in hydrogen demand, coordinating the operational characteristics of the electricity-hydrogen system and inter-microgrid coordination strategies has become a key support for building a highly resilient, low-carbon energy system.

[0053] In this embodiment, the operation constraints of multi-link equipment in the electric-hydrogen coupled multi-microgrid, the transportation constraints of hydrogen vehicles, the system electric-hydrogen balance constraints and the distribution network flow constraints are comprehensively considered. With the goal of minimizing the sum of the electricity purchase cost, unit operation and maintenance cost and hydrogen energy transportation cost of the electric-hydrogen coupled multi-microgrid, an economic dispatch model of the multi-microgrid system under electric-hydrogen coupling is constructed. Through the mutual coordination of electric-hydrogen coupled equipment and the optimized operation of multiple links in the system, the efficiency of the electric-hydrogen coupled multi-microgrid system is improved.

[0054] S150: Solve the multi-microgrid system economic dispatch model and output a solution result for a dispatch cycle.

[0055] Among them, the Gurobi solver can be called to solve the economic dispatch model of the multi-microgrid system. The solution results can include the total operating cost of the electricity-hydrogen coupled multi-microgrid, the hydrogen energy interaction results between microgrids, etc.

[0056] A multi-microgrid system scheduling method is provided in a first embodiment of the present invention. First, an electric-hydrogen coupled multi-microgrid model is used to analyze system operating parameters, and a multi-microgrid system topology structure under electric-hydrogen multi-energy interaction is constructed; secondly, a hydrogen vehicle travel dynamic planning model is determined based on the system operating parameters and the multi-microgrid system topology structure, and the hydrogen vehicle travel dynamic planning model is used to characterize the transportation behavior of the hydrogen vehicle; then, a multi-microgrid flexible hydrogen transportation model is constructed based on the system operating parameters, the multi-microgrid system topology structure, and the hydrogen vehicle travel dynamic planning model; then, a multi-microgrid system economic scheduling model is constructed based on the system operating parameters, the multi-microgrid system topology structure, the hydrogen vehicle travel dynamic planning model, and the multi-microgrid flexible hydrogen transportation model; finally, the multi-microgrid system economic scheduling model is solved, and a solution result of a scheduling cycle is output. The above method is based on the spatiotemporal behavior characteristics of hydrogen transport vehicles in the traffic network, and constructs a flexible hydrogen transport scheduling model that can characterize transportation time constraints and path accessibility; considering the spatial distribution and dynamic transfer needs of hydrogen energy in the multi-microgrid system, a cross-microgrid flexible hydrogen transport model is established; considering the operation constraints of multiple links of equipment such as electrolysis hydrogen production, hydrogen storage, and fuel cell power generation within the microgrid, an economic scheduling model is constructed with the minimization of the sum of multi-microgrid electricity purchase costs, equipment operation and maintenance costs, and hydrogen transportation costs as the objective function, giving full play to the energy buffering and distribution capabilities of hydrogen transport vehicles between microgrids, and realizing the efficient application of hydrogen energy flexible scheduling mechanism in the electric-hydrogen coupled multi-microgrid system, thereby improving the system operation economy and resource allocation flexibility.

[0057] Example 2

[0058] Figure 2 This is a flow chart of a multi-microgrid system scheduling method provided by the second embodiment of the present invention. This second embodiment is optimized based on the above embodiments. For details not yet fully described in this embodiment, please refer to the first embodiment.

[0059] like Figure 2 As shown, a multi-microgrid system scheduling method provided by the second embodiment of the present invention includes the following steps:

[0060] S210. Use the electricity-hydrogen coupled multi-microgrid model to analyze the system operating parameters and construct the multi-microgrid system topology under the electricity-hydrogen multi-energy interaction.

[0061] S220. Determine a travel planning mode for hydrogen transport vehicles based on the traffic network according to the system operating parameters and the multi-microgrid system topology.

[0062] Hydrogen transport vehicle travel planning technology is a core component of building a flexible hydrogen energy distribution system. It is suitable for cross-regional transport and dynamic replenishment of hydrogen resources in distributed microgrid scenarios. By coordinating vehicle travel routes, timing, and hydrogen loading strategies, it can effectively improve hydrogen transportation efficiency, alleviate local supply and demand imbalances, and reduce system operating costs.

[0063] Furthermore, the corresponding formula for the hydrogen transport vehicle travel planning mode based on the traffic network is as follows:

[0064]

[0065] Where, Δt r represents the estimated travel time of road section r, t re represents the remaining time of the hydrogen truck arriving at node i, t ad represents the time that has passed since the hydrogen truck arrived at node j, l ij represents the distance from node i to node j, represents the driving speed of the hydrogen transport vehicle entering the road section r, and Δt represents the road flow observation time interval; Indicates the current time period. represents the time when the hydrogen truck leaves section r, represents the time when the hydrogen truck arrives at node j in road section r; represents the predicted speed of the hydrogen transport vehicle at node i on road section r, represents the design standard speed of section r, represents the real-time traffic flow of node i in road section r, represents the maximum designed carrying capacity of section r; They respectively represent the calculation parameters of the operating speed of hydrogen transport vehicles on different road grades.

[0066] S230. According to the hydrogen transport vehicle travel planning model based on the traffic network, road congestion information is incorporated into the road right analysis, and the physical parameters of different road designs are considered to determine a dynamic planning model for hydrogen transport vehicle travel.

[0067] Among them, hydrogen transportation between microgrids is a path planning problem for hydrogen vehicles based on road network information. Therefore, when studying the transportation behavior of hydrogen vehicles in the road network, it is necessary to incorporate road congestion information into the road right analysis to better characterize the transportation behavior of hydrogen vehicles in the road network.

[0068] S240. Construct a multi-microgrid flexible hydrogen transportation model based on the system operating parameters, the multi-microgrid system topology and the hydrogen transportation vehicle travel dynamic planning model.

[0069] S250. Construct a multi-microgrid system economic dispatch model based on the system operating parameters, the multi-microgrid system topology, the hydrogen transport vehicle travel dynamic planning model, and the multi-microgrid flexible hydrogen transport model.

[0070] S260: Solve the economic dispatch model of the multi-microgrid system and output a solution result for a dispatch cycle.

[0071] A multi-microgrid system scheduling method provided in a second embodiment of the present invention takes into account the impact of road network congestion information on the travel status of hydrogen transport vehicles, and considers incorporating congestion information into road right analysis, so that hydrogen transport vehicles can formulate efficient travel plans based on road network information, rather than using traditional fixed road network congestion information, which can make the travel plans of hydrogen transport vehicles more reasonable and efficient.

[0072] Example 3

[0073] Figure 3 This is a flow chart of a multi-microgrid system scheduling method provided by the third embodiment of the present invention. This third embodiment is optimized based on the above embodiments. For details not yet fully described in this embodiment, please refer to the first and second embodiments.

[0074] like Figure 3 As shown, a multi-microgrid system scheduling method provided by the third embodiment of the present invention includes the following steps:

[0075] S310. Use the electricity-hydrogen coupled multi-microgrid model to analyze the system operating parameters and construct the multi-microgrid system topology under the electricity-hydrogen multi-energy interaction.

[0076] S320. Determine a dynamic planning model for hydrogen transport vehicle travel based on the system operating parameters and the multi-microgrid system topology, where the dynamic planning model for hydrogen transport vehicle travel is used to characterize the transportation behavior of the hydrogen transport vehicle.

[0077] S330. Based on the system operating parameters, the multi-microgrid system topology and the dynamic planning model for hydrogen transport vehicle travel, a multi-microgrid economic operation model of energy complementarity and road network coordination is formed by mobilizing the flexible transfer of hydrogen transport vehicles among multi-microgrids and the electric-hydrogen coupled multi-microgrid multi-link operation model.

[0078] Furthermore, the multi-link operation model of the electricity-hydrogen coupled multi-microgrid includes an electrolyzer model, a compression-high-pressure storage model of the hydrogen storage tank, a hydrogen fuel cell mathematical model, and an electric energy storage model;

[0079] Among them, the hydrogen energy production link is mainly the electrolyzer using the overflow power of wind and solar power and low-cost electricity to electrolyze water to produce hydrogen. The corresponding formula of the electrolyzer model is as follows:

[0080]

[0081] In the above formula, represents the hydrogen production of the electrolyzer in microgrid i during period t, represents the operating power of the electrolyzer in microgrid i during period t, η EL Indicates the operating efficiency of the electrolytic cell, E HHV represents the high calorific value of hydrogen, η0 represents the unit conversion coefficient, ΔT represents the scheduling time interval, Indicates the maximum operating power of electrolyzer i in microgrid, μ EL Indicates the maximum climbing coefficient of the electrolytic cell;

[0082] The pressure at the hydrogen output end of the electrolyzer is generally 1-3 MPa, which cannot meet the needs of the user side. Therefore, the hydrogen pressure is usually increased by a compressor at the front end of the hydrogen storage tank and then stored in a high-pressure gas tank. The corresponding formula of the compression-high-pressure storage model of the hydrogen storage tank is as follows:

[0083]

[0084] In the above formula, represents the operating power of the compressor in microgrid i during period t, represents the hydrogen quality processed by the compressor during period t, η CP Indicates the operating efficiency of the compressor, C p,H represents the specific heat capacity of hydrogen, K CP Indicates the ambient temperature, Indicates the hydrogen gas pressure at the compressor input end, Indicates the hydrogen gas pressure at the compressor output end, It represents the specific heat ratio of hydrogen under standard conditions, represents the hydrogen reserve in the hydrogen storage tank in microgrid i during period t; represents the hydrogen input of the hydrogen storage tank in microgrid i during period t, represents the hydrogen output of the hydrogen storage tank in microgrid i during period t, η HST Indicates the input / output efficiency of the hydrogen storage tank, represents the maximum storage capacity of the hydrogen storage tank in microgrid i, Indicates the hydrogen filling flag of the hydrogen storage tank in microgrid i during period t. Indicates the hydrogen release flag of the hydrogen storage tank in microgrid i during period t;

[0085] Hydrogen fuel cells are accompanied by significant thermal effects during the process of generating electricity from hydrogen, and their heat-to-electricity ratio directly affects the output power of the fuel cell. The corresponding formula for the mathematical model of the fuel cell, which is a hydrogen-to-electricity conversion coupling element, is as follows:

[0086]

[0087] In the above formula, represents the output power of the hydrogen fuel cell in microgrid i during period t, represents the hydrogen consumption of the hydrogen fuel cell in period t, η FC represents the hydrogen-to-electricity conversion efficiency of the hydrogen fuel cell, k FC,min and k FC,max They represent the minimum and maximum values ​​of the thermoelectric ratio of a hydrogen fuel cell during hydrogen-electricity conversion. represents the maximum material input of the fuel cell in microgrid i, η0 represents the unit conversion coefficient, ΔT represents the scheduling time interval, E HHV Indicates the high calorific value of hydrogen;

[0088] In the microgrid, energy storage devices are used to store excess electrical energy and release the stored energy when the power supply is insufficient, thereby achieving redistribution and efficient utilization of electrical energy in time and space dimensions. The corresponding formula of the electrical energy storage model is as follows:

[0089]

[0090] In the above formula, represents the reserve capacity of the energy storage in microgrid i during period t, represents the energy input of the energy storage in microgrid i during period t, represents the energy output of the energy storage in microgrid i during period t, η ES represents the input and output efficiency of electric energy storage, ΔT represents the scheduling time interval, represents the maximum storage capacity of the electric energy storage in microgrid i, and Indicates the charging flag and discharging flag of the energy storage in microgrid i during period t.

[0091] S340. Construct a multi-microgrid flexible hydrogen transportation model based on the multi-microgrid economic operation mode.

[0092] Furthermore, the multi-microgrid flexible hydrogen transportation model includes hydrogen transportation vehicle transportation logic constraints, hydrogen transportation vehicle transportation time constraints, hydrogen transportation vehicle transportation capacity constraints and other constraints;

[0093] The corresponding formula for the hydrogen transport vehicle transportation logic constraint is as follows:

[0094]

[0095] In the above formula, Indicates the transport flag of hydrogen transport vehicle k from microgrid m to microgrid n during period t. It means that there is hydrogen transportation from microgrid m to microgrid n in this time period, otherwise it does not exist; Ω k represents the set of hydrogen transport vehicle numbers, Ω MG represents the microgrid collection, represents the maximum number of hydrogen transport vehicles in microgrid m;

[0096] The corresponding formula for the hydrogen transport vehicle transportation time constraint is as follows:

[0097]

[0098] In the above formula, represents the time when hydrogen transport vehicle k leaves microgrid m, represents the time when hydrogen truck k arrives at microgrid n, represents the time it takes for hydrogen transport vehicle k to travel from microgrid m to microgrid n, It represents the transport flag of hydrogen transport vehicle k from microgrid m to microgrid n in time period t, M represents a very large number, T s Indicates the start time of the optimized scheduling, T e Indicates the end time of optimized scheduling;

[0099] The corresponding formula for the hydrogen transport vehicle transport capacity constraint is as follows:

[0100]

[0101]

[0102] In the above formula, Indicates whether hydrogen truck k reaches microgrid m during period t. If If it arrives, It has not been reached; M represents a very large number, It represents the total amount of hydrogen energy transported outward by microgrid m during period t, represents the hydrogen transport capacity of hydrogen transport vehicle k in period t, Indicates whether the hydrogen transport vehicle is moving from microgrid m to microgrid n, represents the amount of hydrogen energy transported into microgrid m during period t, Indicates the maximum transport capacity of a single hydrogen transport vehicle, represents the time when hydrogen truck k arrives at microgrid m;

[0103] The corresponding formulas for the other constraints are as follows:

[0104]

[0105] In the above formula, Indicates whether the hydrogen transport vehicle arrives at microgrid n from microgrid m, Indicates that the hydrogen transport vehicle arrives at microgrid n from microgrid m, It means that hydrogen transport has not reached microgrid n from microgrid m; Indicates whether the hydrogen transport vehicle arrives at microgrid m from microgrid n, Indicates that the hydrogen transport vehicle arrives at microgrid m from microgrid n, It means that the hydrogen transport vehicle has not reached microgrid m from microgrid n; Indicates the input flag of microgrid m in period t, It means that hydrogen energy is transported into microgrid m during period t. It means that there is no hydrogen energy transported into microgrid m during period t; Indicates the output flag of microgrid m in period t, It means that microgrid m can transport hydrogen in time period t. It means that microgrid m has no hydrogen energy to transport out during period t.

[0106] S350. Construct a multi-microgrid system economic dispatch model based on the system operating parameters, the multi-microgrid system topology, the hydrogen transport vehicle travel dynamic planning model, and the multi-microgrid flexible hydrogen transport model.

[0107] S360: Solve the multi-microgrid system economic dispatch model and output a solution result for a dispatch cycle.

[0108] A multi-microgrid system scheduling method is provided in a third embodiment of the present invention. The method introduces a flexible hydrogen transportation model between microgrids, so that each microgrid can realize the direct transfer of hydrogen energy based on the road network with the help of hydrogen transportation vehicles, so as to effectively balance the source-load mismatch problem between different microgrids, and thus realize resource coordination on a larger scale. This flexible hydrogen transportation mode can effectively improve the economic operation level of the electric-hydrogen coupled multi-microgrid.

[0109] Example 4

[0110] Figure 4 This is a flowchart of a multi-microgrid system scheduling method provided by the fourth embodiment of the present invention. This fourth embodiment is optimized based on the above embodiments. For details not yet fully described in this embodiment, please refer to the above embodiments.

[0111] like Figure 4 As shown, a multi-microgrid system scheduling method provided by the fourth embodiment of the present invention includes the following steps:

[0112] S410. Use the electricity-hydrogen coupled multi-microgrid model to analyze the system operating parameters and construct the multi-microgrid system topology under the electricity-hydrogen multi-energy interaction.

[0113] S420. Determine a dynamic planning model for hydrogen transport vehicle travel based on the system operating parameters and the multi-microgrid system topology, where the dynamic planning model for hydrogen transport vehicle travel is used to describe the transportation behavior of the hydrogen transport vehicle.

[0114] S430: Construct a multi-microgrid flexible hydrogen transportation model based on the system operating parameters, the multi-microgrid system topology and the hydrogen transportation vehicle travel dynamic planning model.

[0115] S440. Based on the system operating parameters, the multi-microgrid system topology, the hydrogen transport vehicle travel dynamic planning model and the multi-microgrid flexible hydrogen transport model, combined with the multi-link equipment operation constraints of the electric-hydrogen coupled multi-microgrid and the system electric-hydrogen balance constraints, with the goal of minimizing the sum of the electricity purchase cost, unit operation and maintenance cost, hydrogen transport cost, etc. of the electric-hydrogen coupled multi-microgrid, an economic dispatch model of the multi-microgrid system is constructed.

[0116] Among them, the operation constraints of multi-link equipment in the electricity-hydrogen coupled multi-microgrid can be expressed as:

[0117]

[0118]

[0119] In the above formula, represents the hydrogen production of the electrolyzer in microgrid i during period t, represents the operating power of the electrolyzer in microgrid i during period t, η EL Indicates the operating efficiency of the electrolytic cell, E HHV represents the high calorific value of hydrogen, η0 represents the unit conversion coefficient, ΔT represents the scheduling time interval, Indicates the maximum operating power of electrolyzer i in microgrid, μ EL Indicates the maximum climbing coefficient of the electrolytic cell; represents the operating power of the compressor in microgrid i during period t, represents the hydrogen quality processed by the compressor during period t, η CP Indicates the operating efficiency of the compressor, C p,H represents the specific heat capacity of hydrogen, K CP Indicates the ambient temperature, Indicates the hydrogen gas pressure at the compressor input end, Indicates the hydrogen gas pressure at the compressor output end, It represents the specific heat ratio of hydrogen under standard conditions, represents the hydrogen reserve in the hydrogen storage tank in microgrid i during period t; represents the hydrogen input of the hydrogen storage tank in microgrid i during period t, represents the hydrogen output of the hydrogen storage tank in microgrid i during period t, η HST Indicates the input / output efficiency of the hydrogen storage tank, represents the maximum storage capacity of the hydrogen storage tank in microgrid i, Indicates the hydrogen filling flag of the hydrogen storage tank in microgrid i during period t. Indicates the hydrogen release flag of the hydrogen storage tank in microgrid i during period t; represents the output power of the hydrogen fuel cell in microgrid i during period t, represents the hydrogen consumption of the hydrogen fuel cell in period t, η FCrepresents the hydrogen-to-electricity conversion efficiency of the hydrogen fuel cell, k FC,min and k FC,max They represent the minimum and maximum values ​​of the thermoelectric ratio of a hydrogen fuel cell during hydrogen-electricity conversion. represents the maximum material input of the fuel cell in microgrid i, η0 represents the unit conversion coefficient, ΔT represents the scheduling time interval, E HHV Indicates the high calorific value of hydrogen; represents the reserve capacity of the energy storage in microgrid i during period t, represents the energy input of the energy storage in microgrid i during period t, represents the energy output of the energy storage in microgrid i during period t, η ES represents the input and output efficiency of electric energy storage, ΔT represents the scheduling time interval, represents the maximum storage capacity of the electric energy storage in microgrid i, and Indicates the charging flag and discharging flag of the energy storage in microgrid i during period t.

[0120] Among them, the multi-microgrid electricity-hydrogen balance constraint can be expressed as:

[0121]

[0122]

[0123] In the above formula, represents the amount of electricity purchased by microgrid i in period t, represents the actual value of wind power generation in microgrid i during period t, represents the predicted value of wind power generation of microgrid i in period t, represents the actual value of photovoltaic power generation of microgrid i during period t, represents the predicted value of photovoltaic power generation of microgrid i in period t, They represent the predicted values ​​of electricity and hydrogen load in the microgrid, represents the hydrogen input of the hydrogen storage tank in microgrid i during period t, It represents the hydrogen output of the hydrogen storage tank in microgrid i during period t.

[0124] Among them, the goal is to minimize the sum of electricity purchase costs, unit operation and maintenance costs, and hydrogen transportation costs of the electricity-hydrogen coupled multi-microgrid, which can be expressed as:

[0125] C cost =C pur +C om +C HT

[0126]

[0127] In the above formula, Ccost represents the total cost, C pur Indicates the cost of purchasing electricity, C HT represents the hydrogen transportation cost, represents the time-of-use electricity price, δ EL represents the unit operation and maintenance cost of the electrolyzer, δ CP represents the unit operation and maintenance cost of the compressor, δ ES represents the unit operation and maintenance cost of electric energy storage, δ HST represents the unit operation and maintenance cost of the hydrogen storage tank, δ FC represents the unit operation and maintenance cost of the fuel cell, Indicates the unit hydrogen transportation cost.

[0128] S450: Solve the multi-microgrid system economic dispatch model and output a solution result for a dispatch cycle.

[0129] In order to verify the superiority of the multi-microgrid system scheduling method proposed in the embodiment of this application, multiple scenarios are set for comparative analysis. Scenario 1 does not include the inter-microgrid hydrogen transportation model and the flexible hydrogen transportation model. Scenario 2 includes the inter-microgrid hydrogen transportation model but does not include the flexible hydrogen transportation model. Scenario 3 includes the inter-microgrid hydrogen transportation model and the flexible hydrogen transportation model. The operating results corresponding to the three scenarios are shown in Figure 1.

[0130] As shown in Table 1, Table 1 is a comparison table of optimization results in different scenarios.

[0131]

[0132]

[0133] Table 1

[0134] Figure 5 This is a schematic diagram of the electricity-hydrogen balance results corresponding to scenario 3 provided in Example 4 of the present invention. Figure 6 This is a schematic diagram of the flexible hydrogen transportation results between microgrids corresponding to scenario 3 provided in embodiment 4 of the present invention.

[0135] Compared to Scenario 1, Scenario 2 considers hydrogen transport between microgrids. As shown in Table 1, the overall cost of the electricity-hydrogen coupled multi-microgrid decreased by 1,855 yuan, a decrease of approximately 2.2%. Specifically, electricity purchase costs and equipment operation and maintenance costs decreased by 1,774 yuan and 688 yuan, decreases of 2.2% and 16.65%, respectively. This indicates that incorporating hydrogen into the inter-microgrid energy exchange system can reduce electricity purchase and equipment operation and maintenance costs to a certain extent. Although hydrogen transportation costs increase, the overall cost reduction is significant, thereby promoting the economic operation of the electricity-hydrogen coupled multi-microgrid.

[0136] Scenario 3 further introduces the dynamic management mode of hydrogen transport vehicles based on Scenario 2, namely the dynamic planning model of hydrogen transport vehicle travel. Figure 5The total cost of the electric-hydrogen coupled multi-microgrid has been further reduced by 758 yuan, a decrease of approximately 0.9%. This indicates that compared to traditional hydrogen transportation solutions, the dynamic planning model for hydrogen transport vehicles can develop more efficient hydrogen transportation plans based on traffic congestion, thereby promoting flexible hydrogen energy exchange between microgrids and further promoting the efficient and economic operation of the electric-hydrogen coupled multi-microgrid.

[0137] Combine Figure 5 and Figure 6 It can be seen that hydrogen energy transfer between microgrids primarily occurs through the transfer of hydrogen energy reserves within Microgrids 1 and 2 to Microgrid 3, with Microgrid 2 transferring the largest amount. Furthermore, the peak of hydrogen energy transfer occurs between 8:00 AM and 12:00 PM. During this period, Microgrid 2 boasts abundant photovoltaic power generation and a relatively balanced internal hydrogen energy load, resulting in relatively low load pressure on Microgrid 2. Conversely, during this period, wind turbine power generation in Microgrid 3 is almost negligible, while its hydrogen energy load is relatively high. Given that electricity purchase prices are at their peak during this period, the economic benefits of purchasing electricity for hydrogen production are low. Therefore, hydrogen energy is transported from Microgrids 2 and 1 to Microgrid 3 to alleviate the hydrogen energy supply pressure on Microgrid 3 during this period. Furthermore, since hydrogen energy transport between microgrids is based on the transportation network, the hydrogen energy transfer by hydrogen transport vehicles is subject to significant time delays. Except for certain periods, such as the period from 9:00 to 10:00 when hydrogen is transported from MG2 to microgrid 3, most of the hydrogen transportation in other periods can be completed within a scheduling time interval, thereby achieving an effective characterization of the transportation behavior of hydrogen vehicles.

[0138] Example 5

[0139] Figure 7 This is a structural schematic diagram of a multi-microgrid system scheduling device provided in Example 5 of the present invention. The device can be applied to the operation scheduling of an electricity-hydrogen coupled multi-microgrid system, wherein the device can be implemented by software and / or hardware and is generally integrated into an electronic device.

[0140] like Figure 7 As shown, the apparatus includes: an analyzing module 110 , a determining module 120 , a first constructing module 130 , a second constructing module 140 and an outputting module 150 .

[0141] The analysis module 110 is used to analyze the system operating parameters using the electricity-hydrogen coupled multi-microgrid model and construct the multi-microgrid system topology under the electricity-hydrogen multi-energy interaction;

[0142] A determination module 120 is configured to determine a dynamic travel planning model for hydrogen transport vehicles based on the system operating parameters and the multi-microgrid system topology, wherein the dynamic travel planning model for hydrogen transport vehicles is configured to describe the transport behavior of hydrogen transport vehicles;

[0143] A first construction module 130 is configured to construct a multi-microgrid flexible hydrogen transportation model based on the system operating parameters, the multi-microgrid system topology, and the hydrogen transportation vehicle travel dynamic planning model;

[0144] A second construction module 140 is configured to construct an economic dispatch model for the multi-microgrid system based on the system operating parameters, the multi-microgrid system topology, the hydrogen transport vehicle travel dynamic planning model, and the multi-microgrid flexible hydrogen transport model;

[0145] The output module 150 is used to solve the economic dispatch model of the multi-microgrid system and output the solution result of one dispatch cycle.

[0146] In this embodiment, the device first uses the electric-hydrogen coupled multi-microgrid model through the analysis module 110 to analyze the system operating parameters and construct the multi-microgrid system topology under the electric-hydrogen multi-energy interaction; secondly, the determination module 120 determines the hydrogen vehicle travel dynamic planning model based on the system operating parameters and the multi-microgrid system topology, and the hydrogen vehicle travel dynamic planning model is used to characterize the transportation behavior of the hydrogen vehicle; then, the first construction module 130 is used to construct a multi-microgrid flexible hydrogen transportation model based on the system operating parameters, the multi-microgrid system topology and the hydrogen vehicle travel dynamic planning model; then, the second construction module 140 is used to construct a multi-microgrid system economic dispatch model based on the system operating parameters, the multi-microgrid system topology, the hydrogen vehicle travel dynamic planning model and the multi-microgrid flexible hydrogen transportation model; finally, the multi-microgrid system economic dispatch model is solved through the output module 150, and the solution result of a dispatch cycle is output.

[0147] This embodiment provides a multi-microgrid system scheduling device, which can effectively improve the economic operation level of the electricity-hydrogen coupled multi-microgrid.

[0148] Furthermore, the determination module 120 includes:

[0149] A first determining unit is configured to determine a travel planning mode of a hydrogen transport vehicle based on a traffic network according to the system operating parameters and the multi-microgrid system topology;

[0150] The second determination unit is used to incorporate road congestion information into road right analysis according to the hydrogen transport vehicle travel planning mode based on the traffic network, consider the physical parameters of different road designs, and determine a dynamic planning model for hydrogen transport vehicle travel.

[0151] Based on the above optimization, the corresponding formula for the hydrogen transport vehicle travel planning mode based on the traffic network is as follows:

[0152]

[0153]

[0154] Where, Δt r represents the estimated travel time of road section r, t re represents the remaining time of the hydrogen truck arriving at node i, t ad represents the time that has passed since the hydrogen truck arrived at node j, l ij represents the distance from node i to node j, represents the driving speed of the hydrogen transport vehicle entering the road section r, and Δt represents the road flow observation time interval; Indicates the current time period. represents the time when the hydrogen truck arrives at node i in road section r; represents the time when the hydrogen truck leaves section r, represents the time when the hydrogen truck arrives at node j in road section r; represents the predicted speed of the hydrogen transport vehicle at node i on road section r, represents the design standard speed of section r, represents the real-time traffic flow of node i in road section r, represents the maximum designed carrying capacity of section r; They respectively represent the calculation parameters of the operating speed of hydrogen transport vehicles on different road grades; int() means rounding.

[0155] Furthermore, the first building block 130 includes:

[0156] A forming unit is configured to form a multi-microgrid economic operation mode of energy complementarity and road network coordination by mobilizing the flexible transfer of hydrogen transport vehicles among the multi-microgrids and the multi-link operation model of the electric-hydrogen coupled multi-microgrid according to the system operation parameters, the multi-microgrid system topology structure and the dynamic planning model of hydrogen transport vehicle travel;

[0157] A construction unit is used to construct a multi-microgrid flexible hydrogen transportation model according to the multi-microgrid economic operation mode.

[0158] Based on the above technical solution, the multi-microgrid flexible hydrogen transportation model includes hydrogen transportation vehicle transportation logic constraints, hydrogen transportation vehicle transportation time constraints, hydrogen transportation vehicle transportation capacity constraints and other constraints;

[0159] The corresponding formula for the hydrogen transport vehicle transportation logic constraint is as follows:

[0160]

[0161]

[0162] In the above formula, Indicates the transport flag of hydrogen transport vehicle k from microgrid m to microgrid n during period t, Ω krepresents the set of hydrogen transport vehicle numbers, Ω MG represents the microgrid collection, represents the maximum number of hydrogen transport vehicles in microgrid m;

[0163] The corresponding formula for the hydrogen transport vehicle transportation time constraint is as follows:

[0164]

[0165] In the above formula, represents the time when hydrogen transport vehicle k leaves microgrid m, represents the time when hydrogen truck k arrives at microgrid n, represents the time it takes for hydrogen transport vehicle k to travel from microgrid m to microgrid n, It represents the transport flag of hydrogen transport vehicle k from microgrid m to microgrid n in time period t, M represents the preset value, T s Indicates the start time of the optimized scheduling, T e Indicates the end time of optimized scheduling;

[0166] The corresponding formula for the hydrogen transport vehicle transport capacity constraint is as follows:

[0167]

[0168] In the above formula, Indicates whether hydrogen transport vehicle k reaches microgrid m in time period t, M represents the preset value, It represents the total amount of hydrogen energy transported outward by microgrid m during period t, represents the hydrogen transport capacity of hydrogen transport vehicle k in period t, Indicates whether the hydrogen transport vehicle is moving from microgrid m to microgrid n, represents the amount of hydrogen energy transported into microgrid m during period t, Indicates the maximum transport capacity of a single hydrogen transport vehicle, represents the time when hydrogen truck k arrives at microgrid m;

[0169] The corresponding formulas for the other constraints are as follows:

[0170]

[0171] In the above formula, Indicates whether the hydrogen transport vehicle is moving from microgrid m to microgrid n, Indicates whether the hydrogen transport vehicle is moving from microgrid n to microgrid m, Indicates the input flag of microgrid m in period t, Indicates the output flag of microgrid m in time period t.

[0172] Based on the above optimization, the multi-link operation model of the electric-hydrogen coupled multi-microgrid includes an electrolyzer model, a compression-high-pressure storage model of the hydrogen storage tank, a hydrogen fuel cell mathematical model, and an electric energy storage model;

[0173] The corresponding formula of the electrolytic cell model is as follows:

[0174]

[0175] In the above formula, represents the hydrogen production of the electrolyzer in microgrid i during period t, represents the operating power of the electrolyzer in microgrid i during period t, η EL Indicates the operating efficiency of the electrolytic cell, E HHV represents the high calorific value of hydrogen, η0 represents the unit conversion coefficient, ΔT represents the scheduling time interval, Indicates the maximum operating power of electrolyzer i in microgrid, μ EL Indicates the maximum climbing coefficient of the electrolytic cell;

[0176] The corresponding formula of the compression-high pressure storage model of the hydrogen storage tank is as follows:

[0177]

[0178] In the above formula, represents the operating power of the compressor in microgrid i during period t, represents the hydrogen quality processed by the compressor during period t, η CP Indicates the operating efficiency of the compressor, C p,H represents the specific heat capacity of hydrogen, K CP Indicates the ambient temperature, Indicates the hydrogen gas pressure at the compressor input end, Indicates the hydrogen gas pressure at the compressor output end, It represents the specific heat ratio of hydrogen under standard conditions, represents the hydrogen reserve in the hydrogen storage tank in microgrid i during period t; represents the hydrogen input of the hydrogen storage tank in microgrid i during period t, represents the hydrogen output of the hydrogen storage tank in microgrid i during period t, η HST Indicates the input / output efficiency of the hydrogen storage tank, represents the maximum storage capacity of the hydrogen storage tank in microgrid i, Indicates the hydrogen filling flag of the hydrogen storage tank in microgrid i during period t. Indicates the hydrogen release flag of the hydrogen storage tank in microgrid i during period t;

[0179] The corresponding formula of the fuel cell mathematical model is as follows:

[0180]

[0181] In the above formula, represents the output power of the hydrogen fuel cell in microgrid i during period t, represents the hydrogen consumption of the hydrogen fuel cell in period t, η FC represents the hydrogen-to-electricity conversion efficiency of the hydrogen fuel cell, k FC,min and k FC,max They represent the minimum and maximum values ​​of the thermoelectric ratio of a hydrogen fuel cell during hydrogen-electricity conversion. represents the maximum material input of the fuel cell in microgrid i, η0 represents the unit conversion coefficient, ΔT represents the scheduling time interval, E HHV Indicates the high calorific value of hydrogen;

[0182] The corresponding formula of the electric energy storage model is as follows:

[0183]

[0184] In the above formula, represents the reserve capacity of the energy storage in microgrid i during period t, represents the energy input of the energy storage in microgrid i during period t, represents the energy output of the energy storage in microgrid i during period t, η ES represents the input and output efficiency of electric energy storage, ΔT represents the scheduling time interval, represents the maximum storage capacity of the electric energy storage in microgrid i, and Indicates the charging flag and discharging flag of the energy storage in microgrid i during period t.

[0185] Furthermore, the second construction model 140 is specifically used to: based on the system operating parameters, the multi-microgrid system topology, the hydrogen transport vehicle travel dynamic planning model and the multi-microgrid flexible hydrogen transport model, combined with the multi-link equipment operation constraints of the electric-hydrogen coupled multi-microgrid and the system electric-hydrogen balance constraints, with the goal of minimizing the sum of the electric-hydrogen coupled multi-microgrid electricity purchase cost, unit operation and maintenance cost, hydrogen transportation cost, etc., to construct a multi-microgrid system economic dispatch model.

[0186] The multi-microgrid system scheduling device can execute the multi-microgrid system scheduling method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0187] Example 4

[0188] Figure 8A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0189] like Figure 8 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0190] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0191] The processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any other suitable processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the multi-microgrid system scheduling method.

[0192] In some embodiments, the multi-microgrid system scheduling method can be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the multi-microgrid system scheduling method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to execute the multi-microgrid system scheduling method in any other suitable manner (e.g., via firmware).

[0193] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0194] In some embodiments, the multi-microgrid system scheduling method can be implemented as a computer program, which is invisibly included in a computer program product. When executed by a processor, the computer program implements the multi-microgrid system scheduling method of the present invention. The computer program product can be understood as a software product that primarily implements its solution through the computer program. The computer program used to implement the method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when executed by the processor, the computer program implements the functions / operations specified in the flowcharts and / or block diagrams. The computer program can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0195] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0196] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0197] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0198] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0199] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0200] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A multi-microgrid system scheduling method, characterized in that: The method comprises: Use the electricity-hydrogen coupled multi-microgrid model to analyze system operating parameters and construct the multi-microgrid system topology structure under the electricity-hydrogen multi-energy interaction; Determine a hydrogen transport vehicle travel dynamic planning model based on the system operating parameters and the multi-microgrid system topology, wherein the hydrogen transport vehicle travel dynamic planning model is used to characterize the transportation behavior of the hydrogen transport vehicle; Constructing a multi-microgrid flexible hydrogen transportation model based on the system operating parameters, the multi-microgrid system topology and the hydrogen transportation vehicle travel dynamic planning model; Constructing a multi-microgrid system economic dispatch model based on the system operating parameters, the multi-microgrid system topology, the hydrogen transport vehicle travel dynamic planning model, and the multi-microgrid flexible hydrogen transport model; The economic dispatch model of the multi-microgrid system is solved, and a solution result of a dispatch cycle is output.

2. The method according to claim 1, characterized in that The method of determining a dynamic planning model for hydrogen transport vehicle travel based on the system operating parameters and the multi-microgrid system topology structure includes: Determining a travel planning mode for hydrogen transport vehicles based on a traffic network according to the system operating parameters and the multi-microgrid system topology; According to the hydrogen transport vehicle travel planning model based on the traffic road network, road congestion information is incorporated into the road right analysis, the physical parameters of different road designs are analyzed, and a dynamic planning model for hydrogen transport vehicle travel is determined.

3. The method according to claim 2, characterized in that The corresponding formula for the hydrogen transport vehicle travel planning mode based on the traffic network is as follows: Where Δt r represents the estimated travel time of road section r, t re represents the remaining time of the hydrogen truck arriving at node i, t ad represents the time that has passed since the hydrogen truck arrived at node j, l ij represents the distance from node i to node j, represents the driving speed of the hydrogen transport vehicle entering the road section r, and Δt represents the road flow observation time interval; Indicates the current time period. represents the time when the hydrogen truck arrives at node i in road section r; represents the time when the hydrogen truck leaves section r, represents the time when the hydrogen truck arrives at node j in road section r; represents the predicted speed of the hydrogen transport vehicle at node i on road section r, represents the design standard speed of section r, represents the real-time traffic flow of node i in road section r, represents the maximum designed carrying capacity of section r; They respectively represent the calculation parameters of the operating speed of hydrogen transport vehicles on different road grades; int() means rounding.

4. The method according to claim 1, wherein The multi-microgrid flexible hydrogen transportation model is constructed based on the system operating parameters, the multi-microgrid system topology, and the hydrogen transportation vehicle travel dynamic planning model, including: Based on the system operating parameters, the multi-microgrid system topology, and the dynamic planning model for hydrogen transport vehicle travel, a multi-microgrid economic operation model of energy complementarity and road network coordination is formed by mobilizing the flexible transfer of hydrogen transport vehicles between multi-microgrids and the multi-link operation model of the electric-hydrogen coupling multi-microgrid; A multi-microgrid flexible hydrogen transportation model is constructed based on the multi-microgrid economic operation mode.

5. The method according to claim 4, characterized in that The multi-microgrid flexible hydrogen transportation model includes hydrogen transportation vehicle transportation logic constraints, hydrogen transportation vehicle transportation time constraints, hydrogen transportation vehicle transportation capacity constraints and other constraints; The corresponding formula for the hydrogen transport vehicle transportation logic constraint is as follows: In the above formula, Indicates the transport flag of hydrogen transport vehicle k from microgrid m to microgrid n during period t, Ω k represents the set of hydrogen transport vehicle numbers, Ω MG represents the microgrid collection, represents the maximum number of hydrogen transport vehicles in microgrid m; The corresponding formula for the hydrogen transport vehicle transportation time constraint is as follows: In the above formula, represents the time when hydrogen transport vehicle k leaves microgrid m, represents the time when hydrogen truck k arrives at microgrid n, represents the time it takes for hydrogen transport vehicle k to travel from microgrid m to microgrid n, It represents the transport flag of hydrogen transport vehicle k from microgrid m to microgrid n in time period t, M represents the preset value, T s Indicates the start time of the optimized scheduling, T e Indicates the end time of the optimized scheduling; The corresponding formula for the hydrogen transport vehicle transport capacity constraint is as follows: In the above formula, Indicates whether hydrogen transport vehicle k reaches microgrid m in time period t, M represents the preset value, It represents the total amount of hydrogen energy transported outward by microgrid m during period t, represents the hydrogen transport capacity of hydrogen transport vehicle k in period t, Indicates whether the hydrogen transport vehicle is moving from microgrid m to microgrid n, represents the amount of hydrogen energy transported into microgrid m during period t, Indicates the maximum transport capacity of a single hydrogen transport vehicle, represents the time when hydrogen truck k arrives at microgrid m; The corresponding formulas for the other constraints are as follows: In the above formula, Indicates whether the hydrogen transport vehicle is moving from microgrid m to microgrid n, Indicates whether the hydrogen transport vehicle is moving from microgrid n to microgrid m, Indicates the input flag of microgrid m in period t, Indicates the output flag of microgrid m in time period t.

6. The method according to claim 1, characterized in that The multi-microgrid system economic dispatch model is constructed based on the system operating parameters, the multi-microgrid system topology, the hydrogen transport vehicle travel dynamic planning model, and the multi-microgrid flexible hydrogen transport model, including: According to the system operating parameters, the multi-microgrid system topology, the hydrogen transport vehicle travel dynamic planning model and the multi-microgrid flexible hydrogen transport model, combined with the multi-link equipment operation constraints of the electric-hydrogen coupled multi-microgrid and the system electric-hydrogen balance constraints, a multi-microgrid system economic dispatch model is constructed with the goal of minimizing the sum of the electricity purchase cost, unit operation and maintenance cost, hydrogen transportation cost, etc. of the electric-hydrogen coupled multi-microgrid.

7. The method according to claim 4, characterized in that The multi-link operation model of the electric-hydrogen coupled multi-microgrid includes an electrolyzer model, a compression-high-pressure storage model of the hydrogen storage tank, a hydrogen fuel cell mathematical model, and an electric energy storage model; The corresponding formula of the electrolytic cell model is as follows: In the above formula, represents the hydrogen production of the electrolyzer in microgrid i during period t, represents the operating power of the electrolyzer in microgrid i during period t, η EL Indicates the operating efficiency of the electrolytic cell, E HHV represents the high calorific value of hydrogen, η0 represents the unit conversion coefficient, ΔT represents the scheduling time interval, Indicates the maximum operating power of electrolyzer i in microgrid, μ EL Indicates the maximum climbing coefficient of the electrolytic cell; The corresponding formula of the compression-high pressure storage model of the hydrogen storage tank is as follows: In the above formula, represents the operating power of the compressor in microgrid i during period t, represents the hydrogen quality processed by the compressor during period t, η CP Indicates the operating efficiency of the compressor, C p,H represents the specific heat capacity of hydrogen, K CP Indicates the ambient temperature, Indicates the hydrogen gas pressure at the compressor input end, Indicates the hydrogen gas pressure at the compressor output end, It represents the specific heat ratio of hydrogen under standard conditions, represents the hydrogen reserve in the hydrogen storage tank in microgrid i during period t; represents the hydrogen input of the hydrogen storage tank in microgrid i during period t, represents the hydrogen output of the hydrogen storage tank in microgrid i during period t, η HST Indicates the input / output efficiency of the hydrogen storage tank, represents the maximum storage capacity of the hydrogen storage tank in microgrid i, Indicates the hydrogen filling flag of the hydrogen storage tank in microgrid i during period t. Indicates the hydrogen release flag of the hydrogen storage tank in microgrid i during period t; The corresponding formula of the fuel cell mathematical model is as follows: In the above formula, represents the output power of the hydrogen fuel cell in microgrid i during period t, represents the hydrogen consumption of the hydrogen fuel cell in period t, η FC represents the hydrogen-to-electricity conversion efficiency of the hydrogen fuel cell, k FC,min and k FC,max They represent the minimum and maximum values ​​of the thermoelectric ratio of a hydrogen fuel cell during hydrogen-electricity conversion. represents the maximum material input of the fuel cell in microgrid i, η0 represents the unit conversion coefficient, ΔT represents the scheduling time interval, E HHV Indicates the high calorific value of hydrogen; The corresponding formula of the electric energy storage model is as follows: In the above formula, represents the reserve capacity of the energy storage in microgrid i during period t, represents the energy input of the energy storage in microgrid i during period t, represents the energy output of the energy storage in microgrid i during period t, η ES represents the input and output efficiency of electric energy storage, ΔT represents the scheduling time interval, represents the maximum storage capacity of the electric energy storage in microgrid i, and Indicates the charging flag and discharging flag of the energy storage in microgrid i during period t.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the multi-microgrid system scheduling method according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the multi-microgrid system scheduling method according to any one of claims 1 to 7 when executed.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the computer program implements the multi-microgrid system scheduling method according to any one of claims 1 to 7.

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