Electro-hydrogen comprehensive energy system low-carbon scheduling method considering alcohol transportation and related device

Abstract

The invention discloses an electricity-hydrogen comprehensive energy system low-carbon scheduling method considering alcohol transportation and a related device, and relates to the technical field of electricity-hydrogen coupling scheduling, the method comprises the steps that a double-layer low-carbon scheduling model is established and solved, the double-layer low-carbon scheduling model comprises an upper-layer optimization scheduling model and a lower-layer optimization scheduling model, and the upper-layer optimization scheduling model comprises an upper-layer optimization scheduling model and a lower-layer optimization scheduling model; the upper-layer optimization scheduling model takes the minimum comprehensive operation cost of an electricity-hydrogen comprehensive energy system as a target function, takes the equipment operation constraint of a hydrogen supply chain, the wind and light abandoning constraint of new energy and the power flow constraint of a power distribution network as constraint conditions, and the lower-layer optimization scheduling model takes the minimum low-carbon demand response electricity-carbon comprehensive subsidy cost as a target function; the demand response constraint of the power distribution network and the power adjustment constraint of the methanol reforming hydrogen production equipment in the hydrogen supply chain are taken as constraint conditions, the carbon emission responsibility of the user side of the power distribution network can be considered, the carbon dioxide emission for transportation by taking methanol as a hydrogen carrier is reduced, and the low-carbon scheduling of the electricity-hydrogen comprehensive energy system is realized.

Description

Technical Field

[0001] The present application relates to the technical field of electricity-hydrogen coupling scheduling, and in particular to a low-carbon scheduling method and related devices for an electricity-hydrogen integrated energy system taking alcohol transportation into consideration. Background Art

[0002] As a new type of clean and pollution-free energy, hydrogen energy provides an effective solution for the green energy transformation of the transportation system. In modern cities, the production and use of hydrogen are usually distributed in different locations. Hydrogen needs to be transported from the production point to the consumer side such as hydrogen refueling stations. Therefore, the hydrogen supply chain is indispensable. The electric hydrogen integrated energy system with integrated hydrogen transportation is composed of the hydrogen supply chain and the distribution network. The hydrogen supply chain includes: production, storage, transportation and consumption. In terms of transportation, the use of long-tube trailers is more economical than pipeline transportation for medium and short distances, and the current long-tube trailer transportation technology is relatively mature, but the gaseous hydrogen storage density is low, the storage and transportation capacity is limited, and the liquid hydrogen storage is poor in economic efficiency, and there are problems such as flammability, explosion and poor safety. In contrast, methanol has a mature and economical storage and transportation system, which can realize large-scale long-distance economic storage and transportation, and methanol and hydrogen can achieve efficient two-way conversion. Compared with hydrogen, methanol has a higher volumetric energy density. Methanol is used as a hydrogen carrier for transportation and is considered to be a promising hydrogen carrier and energy carrier. Therefore, the electric hydrogen integrated energy system considering alcohol transportation came into being.

[0003] However, existing research ignores the additional generation of carbon dioxide when using methanol reforming to produce hydrogen, and focuses on direct carbon emissions from fossil energy on the power generation side, without considering the phenomenon that carbon emission responsibility will be transferred from the power generation side to the user side with the flow of current. Summary of the invention

[0004] The purpose of this application is to provide a low-carbon scheduling method and related devices for an electric-hydrogen integrated energy system that takes into account alcohol transportation, consider the carbon emission responsibility of the user side of the distribution network, reduce carbon dioxide emissions from transporting methanol as a hydrogen carrier, and achieve low-carbon scheduling of the electric-hydrogen integrated energy system.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a low-carbon scheduling method for an electric-hydrogen integrated energy system considering alcohol transportation, and the low-carbon scheduling method for an electric-hydrogen integrated energy system considering alcohol transportation comprises:

[0007] A double-layer low-carbon dispatch model for low-carbon dispatch of an electric-hydrogen integrated energy system is established; the double-layer low-carbon dispatch model includes an upper-layer optimization dispatch model and a lower-layer optimization dispatch model, the upper-layer optimization dispatch model takes the minimum comprehensive operation cost of the electric-hydrogen integrated energy system as the objective function, takes the equipment operation constraints of the hydrogen supply chain, the wind and solar abandonment constraints of new energy, and the power flow constraints of the distribution network as constraints, and optimizes the operation parameters of each device in the hydrogen supply chain and the operation parameters of each device in the new energy; the lower-layer optimization dispatch model takes the minimum low-carbon demand response electricity-carbon comprehensive subsidy cost as the objective function, takes the demand response constraints of the distribution network and the power adjustment constraints of the methanol reforming hydrogen production equipment in the hydrogen supply chain as constraints, and optimizes the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the distribution network and the power adjustment amount of the methanol reforming hydrogen production equipment; wherein the hydrogen supply chain includes a hydrogen production plant and a hydrogenation station, the hydrogen production plant includes a water electrolysis hydrogen production equipment, a carbon capture power plant, a hydrogen production methanol equipment, an alcohol storage tank and a long-tube trailer, the hydrogenation station includes a methanol reforming hydrogen production equipment, and the new energy includes a photovoltaic generator set and a wind generator set;

[0008] The two-layer low-carbon scheduling model is solved to obtain a low-carbon scheduling plan for the electric-hydrogen integrated energy system; the low-carbon scheduling plan includes the operating parameters of each device in the hydrogen supply chain, the operating parameters of each device in the new energy, and the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the distribution network.

[0009] In a second aspect, the present application provides a low-carbon dispatching device for an electric-hydrogen integrated energy system considering alcohol transportation, wherein the low-carbon dispatching device for an electric-hydrogen integrated energy system considering alcohol transportation comprises:

[0010] A model building module is used to establish a double-layer low-carbon dispatch model for low-carbon dispatch of the electric-hydrogen integrated energy system; the double-layer low-carbon dispatch model includes an upper-layer optimization dispatch model and a lower-layer optimization dispatch model, the upper-layer optimization dispatch model takes the minimum comprehensive operation cost of the electric-hydrogen integrated energy system as the objective function, takes the equipment operation constraints of the hydrogen supply chain, the wind and solar abandonment constraints of new energy, and the power flow constraints of the distribution network as constraints, and optimizes the operation parameters of each equipment in the hydrogen supply chain and the operation parameters of each equipment in the new energy; the lower-layer optimization dispatch model takes the low-carbon demand The objective function is to minimize the comprehensive subsidy cost of electricity and carbon, and the demand response constraints of the distribution network and the power adjustment constraints of the methanol reforming hydrogen production equipment in the hydrogen supply chain are used as constraints to optimize the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the distribution network and the power adjustment amount of the methanol reforming hydrogen production equipment; wherein, the hydrogen supply chain includes a hydrogen production plant and a hydrogen refueling station, the hydrogen production plant includes a water electrolysis hydrogen production equipment, a carbon capture power plant, a hydrogen to methanol equipment, an alcohol storage tank and a long tube trailer, the hydrogen refueling station includes a methanol reforming hydrogen production equipment, and the new energy includes a photovoltaic generator set and a wind turbine generator set;

[0011] The model solving module is used to solve the two-layer low-carbon scheduling model to obtain a low-carbon scheduling plan for the electric-hydrogen integrated energy system; the low-carbon scheduling plan includes the operating parameters of each device in the hydrogen supply chain, the operating parameters of each device in the new energy, and the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the distribution network.

[0012] In a third aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-mentioned low-carbon scheduling method for an electric-hydrogen integrated energy system taking into account alcohol transportation.

[0013] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned low-carbon scheduling method for an electric-hydrogen integrated energy system taking into account alcohol transportation.

[0014] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above-mentioned low-carbon scheduling method for an electric-hydrogen integrated energy system taking into account alcohol transportation.

[0015] According to the specific embodiments provided in this application, this application has the following technical effects:

[0016] The present application provides a low-carbon scheduling method and related devices for an electric-hydrogen integrated energy system considering alcohol transportation, establishes and solves a double-layer low-carbon scheduling model for low-carbon scheduling of the electric-hydrogen integrated energy system, and obtains a low-carbon scheduling plan for the electric-hydrogen integrated energy system. Since the constructed double-layer low-carbon scheduling model includes an upper-layer optimization scheduling model and a lower-layer optimization scheduling model, the upper-layer optimization scheduling model takes the minimum comprehensive operating cost of the electric-hydrogen integrated energy system as the objective function, and takes the equipment operation constraints of the hydrogen supply chain, the wind and solar abandonment constraints of new energy, and the power flow constraints of the distribution network as constraints. The lower-layer optimization scheduling model takes the minimum low-carbon demand response electricity-carbon comprehensive subsidy cost as the objective function, and takes the demand response constraints of the distribution network and the power adjustment constraints of the methanol reforming hydrogen production equipment in the hydrogen supply chain as constraints. At this time, the established double-layer low-carbon scheduling model can consider the carbon emission responsibility of the user side of the distribution network and the additional carbon dioxide emissions generated when methanol reforming hydrogen is produced. Therefore, the obtained low-carbon scheduling plan can also consider the carbon emission responsibility of the user side of the distribution network, reduce the carbon dioxide emissions transported using methanol as a hydrogen carrier, and thus achieve low-carbon scheduling of the electric-hydrogen integrated energy system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 This is an application environment diagram of a low-carbon scheduling method for an electric-hydrogen integrated energy system taking into account alcohol transportation provided in Example 1 of the present application.

[0019] Figure 2 A flow chart of a low-carbon scheduling method for an electric-hydrogen integrated energy system taking into account alcohol transportation is provided in Example 1 of the present application.

[0020] Figure 3 A schematic diagram of a technical route for a low-carbon scheduling method for an electric-hydrogen integrated energy system taking into account alcohol transportation provided in Example 1 of the present application.

[0021] Figure 4 Schematic diagram of energy flow in the electric-hydrogen integrated energy system provided in Example 1 of the present application.

[0022] Figure 5 A schematic diagram of the functional modules of a low-carbon scheduling device for an electric-hydrogen integrated energy system taking into account alcohol transportation provided in Example 2 of the present application.

[0023] Figure 6 A schematic diagram of the structure of a computer device provided in Example 3 of the present application. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0025] Example 1

[0026] The low-carbon scheduling method of the electric-hydrogen integrated energy system considering alcohol transportation provided in the embodiment of the present application can be applied to Figure 1In the application environment shown. Among them, the terminal communicates with the server through the network. The data storage system can store data that the server needs to process. The data storage system can be set up separately, integrated on the server, or placed on the cloud or other servers. The terminal can send the pending low-carbon scheduling request to the server. After the server receives the pending low-carbon scheduling request, for the pending low-carbon scheduling request, the server establishes a two-layer low-carbon scheduling model for low-carbon scheduling of the electric-hydrogen integrated energy system; solves the two-layer low-carbon scheduling model to obtain a low-carbon scheduling plan for the electric-hydrogen integrated energy system. The server can feedback the obtained low-carbon scheduling plan for the low-carbon scheduling request to the terminal.

[0027] In addition, in some embodiments, the low-carbon scheduling method of the electric-hydrogen integrated energy system considering alcohol transportation can also be implemented independently by a server or a terminal. For example, the terminal can directly process the pending low-carbon scheduling request, or the server can obtain the pending low-carbon scheduling request from the data storage system and process the pending low-carbon scheduling request.

[0028] The terminals may be, but are not limited to, various desktop computers, laptops, smart phones, tablet computers, IoT devices and portable wearable devices. IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server may be implemented as an independent server or a server cluster consisting of multiple servers, or a cloud server.

[0029] In an exemplary embodiment, Figure 2 and Figure 3 As shown, a low-carbon scheduling method for an electric-hydrogen integrated energy system considering alcohol transportation is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1 The following steps are used to illustrate the server in the example.

[0030] Step S1, establish a double-layer low-carbon dispatch model for low-carbon dispatch of the electric-hydrogen integrated energy system; the double-layer low-carbon dispatch model includes an upper-layer optimization dispatch model and a lower-layer optimization dispatch model, the upper-layer optimization dispatch model takes the minimum comprehensive operation cost of the electric-hydrogen integrated energy system as the objective function, takes the equipment operation constraints of the hydrogen supply chain, the wind and solar power abandonment constraints of new energy and the power flow constraints of the distribution network as constraints, and optimizes the operation parameters of each equipment in the hydrogen supply chain and the operation parameters of each equipment in the new energy; the lower-layer optimization dispatch model takes the low-carbon demand response as the minimum Taking the minimization of the comprehensive electricity-carbon subsidy cost as the objective function, and the demand response constraints of the distribution network and the power adjustment constraints of the methanol reforming hydrogen production equipment in the hydrogen supply chain as constraints, the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the distribution network and the power adjustment amount of the methanol reforming hydrogen production equipment are optimized; among them, the hydrogen supply chain includes hydrogen production plants and hydrogen refueling stations. The hydrogen production plants include water electrolysis hydrogen production equipment, carbon capture power plants, hydrogen to methanol equipment, alcohol storage tanks and long-tube trailers. The hydrogen refueling stations include methanol reforming hydrogen production equipment. New energy includes photovoltaic generators and wind generators.

[0031] Step S2, solving the two-layer low-carbon scheduling model to obtain a low-carbon scheduling plan for the electric-hydrogen integrated energy system; the low-carbon scheduling plan includes the operating parameters of each device in the hydrogen supply chain, the operating parameters of each device in the new energy, and the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the distribution network.

[0032] By implementing the above-mentioned steps S1 to S2, this embodiment establishes a double-layer low-carbon scheduling model for low-carbon scheduling of the electric-hydrogen integrated energy system. The double-layer low-carbon scheduling model includes an upper-layer optimization scheduling model and a lower-layer optimization scheduling model. By introducing the lower-layer optimization scheduling model, the phenomenon that the carbon emission responsibility will be transferred from the power generation side to the user side with the flow of the tide and the phenomenon that additional carbon dioxide emissions will be generated when methanol reforming to produce hydrogen are taken into account. Subsequently, the double-layer low-carbon scheduling model is solved to obtain a low-carbon scheduling plan for the electric-hydrogen integrated energy system, which can achieve low-carbon scheduling of the electric-hydrogen integrated energy system.

[0033] In view of the low-carbon emission problem of the electric-hydrogen integrated energy system considering alcohol transportation, this embodiment proposes a low-carbon scheduling method that considers the carbon emission responsibility of the distribution network user side, such as Figure 3As shown in the figure, it is mainly divided into four steps: (1) Collect the traffic network structure (i.e., road information), distribution network topology, photovoltaic and wind power output forecast information, and hydrogen demand forecast information of hydrogen refueling stations to model the hydrogen supply chain; (2) Consider the carbon emission responsibility of the distribution network user side and formulate a low-carbon scheduling strategy for distribution network demand response; (3) Establish a two-layer low-carbon scheduling model of electricity and hydrogen coupling, in which the upper-layer optimization scheduling model executes the distribution network optimization scheduling, and the lower-layer optimization scheduling model executes the hydrogen refueling station and demand response optimization scheduling; (4) Solve the two-layer low-carbon scheduling model to obtain a low-carbon scheduling plan.

[0034] (1) Modeling of each unit in the hydrogen supply chain, including production, storage, transportation, and consumption

[0035] This embodiment collects the traffic network structure and distribution network topology, predicts the photovoltaic and wind power output and the hydrogen demand of hydrogen refueling stations, and models the hydrogen supply chain. Figure 4 As shown, in this embodiment, methanol is used as a hydrogen carrier for transportation, and the hydrogen production side equipment (i.e., the equipment of the hydrogen production plant) includes: water electrolysis hydrogen production equipment (i.e. Figure 4 Electrolyzer in the Figure 4 The equipment for hydrogen consumption (i.e. the equipment for hydrogen refueling station) includes: methanol reforming hydrogen production equipment (i.e. Figure 4 The alcohol-to-hydrogen equipment in the hydrogen supply chain) includes hydrogen-to-methanol equipment and methanol reforming hydrogen production equipment, which are the hubs connecting the distribution network and the hydrogen supply chain. The operation of the two in the distribution network requires power support, and the two are the beginning and end of the hydrogen supply chain respectively.

[0036] This embodiment further constructs models of each unit of hydrogen energy production, storage, transportation, and consumption, as follows:

[0037] 1) Water electrolysis hydrogen production equipment

[0038]

[0039] In formula (1), is the mass of hydrogen produced by the water electrolysis hydrogen production equipment at time t; ε H P is the conversion factor of electricity to produce hydrogen; t EL It is the electrical power used by the water electrolysis hydrogen production equipment to produce hydrogen at time t.

[0040] The hydrogen produced by the water electrolysis hydrogen production equipment will be consumed as raw material in the hydrogen to methanol equipment, as follows:

[0041]

[0042] In formula (2), The mass of hydrogen required for the hydrogen-to-methanol equipment to produce methanol at time t.

[0043] 2) Carbon capture power plants

[0044] Carbon capture plants produce the following carbon dioxide:

[0045]

[0046] In formula (3), is the amount of carbon dioxide produced by the carbon capture power plant at time t; μ CCS is the carbon emission coefficient of the carbon capture power plant; P t CCS is the power generation capacity of the carbon capture power plant at time t.

[0047] The net power output of a carbon capture plant can be expressed as follows:

[0048]

[0049] In formula (4), is the net output power of the carbon capture power plant at time t; P is the power consumption of the carbon capture power plant at time t; fiix The fixed electrical power consumption of the carbon capture plant.

[0050] The carbon capture power plant is also used to capture carbon dioxide. The carbon dioxide captured by the carbon capture power plant can be supplied to the hydrogen-to-methanol equipment as follows:

[0051]

[0052] In the above formula, The energy consumption factor for treating a unit of carbon dioxide for the carbon capture power plant; is the amount of carbon dioxide captured by the carbon capture power plant at time t; The amount of carbon dioxide used in the hydrogen-to-methanol plant; The amount of carbon dioxide not used by the hydrogen-to-methanol equipment.

[0053] 3) Hydrogen to Methanol Equipment

[0054] The hydrogen generated by the water electrolysis hydrogen production equipment is chemically reacted with the carbon dioxide captured by the carbon capture power plant to produce methanol, as follows:

[0055]

[0056]

[0057]

[0058] In the above formula, P tME is the power consumption of the hydrogen-to-methanol equipment at time t; ε ME is the unit energy consumption coefficient of hydrogen to alcohol; is the quality of methanol produced by the hydrogen-to-methanol equipment at time t; η MEH The efficiency of hydrogen to methanol in hydrogen-to-methanol equipment; is the mass of hydrogen required for the hydrogen-to-methanol equipment to produce methanol at time t; η MEC The efficiency of converting carbon dioxide to methanol in hydrogen-to-methanol equipment; The mass of carbon dioxide required for the hydrogen-to-methanol equipment to produce methanol at time t.

[0059] Part of the methanol produced by the hydrogen-to-methanol plant can be loaded into a long tube trailer, and part can be stored in a methanol storage tank, as follows:

[0060]

[0061] In formula (10), is the mass of methanol loaded from the hydrogen-to-methanol plant to the tube trailer at time t; is the mass of methanol loaded into the methanol storage tank from the hydrogen-to-methanol equipment at time t.

[0062] 4) Alcohol storage tank

[0063] The methanol balance in the alcohol storage tank is as follows:

[0064]

[0065] In formula (11), is the methanol mass in the alcohol storage tank at time t; is the methanol mass in the alcohol storage tank at time t-1; is the mass of methanol loaded from the methanol storage tank into the tube trailer at time t.

[0066] The upper and lower limits of alcohol storage tank capacity are as follows:

[0067]

[0068] In formula (12), They are respectively the lower limit and upper limit of the alcohol storage tank capacity.

[0069] 5) Long tube trailer

[0070] The modeling of the tube trailer needs to take into account various links such as loading methanol into the tube trailer and unloading the tube trailer to the hydrogen refueling station.

[0071] The methanol loading balance for all tube trailers is as follows:

[0072]

[0073] In formula (13), E is the total number of long tube trailers; is the mass of methanol loaded into the long tube trailer e by the hydrogen-to-methanol equipment at time t; is the methanol mass loaded from the alcohol storage tank to the tube trailer e at time t; is the mass of methanol loaded on the tube trailer e at time t.

[0074] The time when the tube trailer left the hydrogen production plant and the quality of methanol loaded when leaving the hydrogen production plant are as follows:

[0075]

[0076]

[0077] In the above formula, is the time when the long tube trailer e leaves the hydrogen production plant; M is a very large positive number; B t,e is a binary variable, B t,e is 1, indicating that the long tube trailer e leaves the hydrogen production plant at time t, B t,e is 0, indicating that the long tube trailer e did not leave the hydrogen production plant at time t; M o e is the mass of methanol loaded on the tube trailer e when it leaves the hydrogen production plant.

[0078] The update of the methanol mass in the tube trailer as it changes with position is as follows:

[0079]

[0080] In formula (16), M is the remaining methanol mass when the long tube trailer e leaves the hydrogenation station j; i e is the remaining methanol mass when the long tube trailer e leaves the hydrogenation station i; is the mass of methanol unloaded by the long tube trailer e at the hydrogenation station j; X ije is a binary variable, X ije is 1, indicating that there is a long-tube trailer e traveling between hydrogen refueling station i and hydrogen refueling station j, X ije It is 0, indicating that there is no long-tube trailer e traveling between hydrogen refueling station i and hydrogen refueling station j.

[0081] When the long tube trailer transports methanol to the destination, each long tube trailer cannot repeatedly visit any hydrogen refueling station during transportation, as follows:

[0082]

[0083]

[0084] Formula (17) means that it can only be reached from one path, and formula (18) means that it can only start from one path. F A collection of hydrogen refueling stations.

[0085] The movement of the tube trailer e ensures that the vehicle will not return to the same hydrogen filling station, forming a sub-loop as follows:

[0086]

[0087] In formula (19), u(i) and u(j) are the order in which the long-tube trailer e arrives at hydrogen refueling station i and hydrogen refueling station j respectively; N A is the total number of hydrogen production plants and hydrogen refueling stations.

[0088] The long tube trailer must start from the hydrogen production plant and eventually return to the hydrogen production plant as follows:

[0089]

[0090] In formula (20), X 0je is a binary variable, X 0je is 1, indicating that there is a long-tube trailer e traveling between the hydrogen production plant and the hydrogen refueling station j, X 0je is 0, indicating that there is no long-tube trailer e traveling between the hydrogen production plant and the hydrogen refueling station j; i0e is a binary variable, X i0e is 1, indicating that there is a long-tube trailer e traveling between hydrogen refueling station i and hydrogen production plant, X i0e It is 0, indicating that there is no long-tube trailer e traveling between hydrogen refueling station i and hydrogen production plant.

[0091] The time it takes for a tube trailer to complete the transport task is as follows:

[0092]

[0093] In formula (21), is the time it takes for the long-tube trailer e to travel from hydrogen refueling station i to hydrogen refueling station j; T i rel The time consumed by the long tube trailer to unload at hydrogen refueling station i; is the time when the long tube trailer e arrives at the hydrogen refueling station j; is the time when the tube trailer e arrives at the hydrogen refueling station i.

[0094] The relationship between the travel time, route length, and transportation speed of a tube trailer is as follows:

[0095]

[0096] In formula (22), γ ij is the distance between hydrogen refueling station i and hydrogen refueling station j; v ijeis the driving speed of the long tube trailer e from hydrogen station i to hydrogen station j.

[0097] The upper and lower limits of the transportation time for tube trailers are as follows:

[0098]

[0099] In formula (23), They are respectively the left window (i.e. the earliest time) and the right window (i.e. the latest time) of the acceptable service of hydrogen refueling station j.

[0100] Since the hydrogen production scheduling time scale in the distribution network is 1 hour, but the time for the long-tube trailer to travel on any path is a continuous time scale, the time for the long-tube trailer to arrive at the hydrogen refueling station is rounded up and can be expressed as follows after linearization:

[0101]

[0102] In formula (24), is the time it takes for the tube trailer e to arrive at the hydrogen refueling station j at a discrete time scale of 1 hour.

[0103] The quality of methanol unloaded by all long tube trailers received by hydrogenation station j at time t can be expressed as:

[0104]

[0105] In formula (25), is the methanol mass unloaded by all long tube trailers received by hydrogenation station j at time t; t,j,e is a binary variable, δ t,j,e is 1, indicating that the long-tube trailer e arrives at the hydrogen refueling station j at time t, δ t,j,e is 0, indicating that the long-tube trailer e has not arrived at the hydrogen refueling station j at time t, which satisfies the following formula:

[0106]

[0107] 6) Methanol reforming hydrogen production equipment

[0108] Each hydrogenation station is equipped with methanol reforming hydrogen production equipment, as follows:

[0109]

[0110]

[0111]

[0112] In the above formula, is the power consumption of the methanol reforming hydrogen production equipment at hydrogenation station j at time t; ε reHis the energy consumption coefficient of methanol reforming hydrogen production equipment; is the mass of hydrogen produced by the methanol reforming hydrogen production equipment at hydrogenation station j at time t; η reH The efficiency of methanol to hydrogen in methanol reforming hydrogen production equipment; The mass of methanol required for the production of hydrogen by the methanol reforming hydrogen production equipment at hydrogenation station j at time t; is the carbon dioxide emissions generated by the methanol reforming hydrogen production equipment at hydrogenation station j at time t; η reC It is the efficiency of converting methanol to carbon dioxide in methanol reforming hydrogen production equipment.

[0113] Carbon dioxide is absorbed during the production of methanol, which helps reduce carbon emissions. However, existing studies have ignored the fact that additional carbon dioxide is produced when methanol is reformed to produce hydrogen. This embodiment takes this into account and can better perform low-carbon scheduling.

[0114] The hydrogen balance of the hydrogen refueling station is balanced by the original hydrogen in the hydrogen refueling station, the hydrogen produced by the methanol reforming hydrogen production equipment, and the hydrogen load, as follows:

[0115]

[0116] In formula (30), is the mass of hydrogen stored at hydrogen refueling station j at time t; is the mass of hydrogen stored at hydrogen refueling station j at time t-1; is the hydrogen load demand of hydrogen refueling station j at time t.

[0117] (2) Considering the carbon emission responsibility of users on the distribution network side, establish a comprehensive electricity-carbon subsidy price, guide users to respond to low-carbon demand, and formulate a low-carbon dispatching strategy for distribution network demand response.

[0118] Since existing research has mostly focused on direct carbon emissions from fossil energy on the power generation side, without considering the carbon emission responsibility of the distribution network user side, and without considering the phenomenon that demand response resources are driven by carbon responsibility to adjust the temporal and spatial distribution of loads to reduce carbon emissions, this embodiment will consider the carbon emission responsibility of the distribution network user side based on the carbon emission flow theory, design a low-carbon demand response strategy, and study a low-carbon scheduling scheme that meets the hydrogen load demand and the low-carbon emission goals of the distribution network, thereby improving the overall carbon emission reduction benefits.

[0119] This embodiment first calculates the node carbon potential of each node in the distribution network as follows:

[0120] Carbon emission flow is a virtual network flow attached to the power flow, which is used to represent the carbon dioxide generated by maintaining the power network flow. In the process of power production, thermal power generation burns fossil energy such as coal, which will produce a large amount of greenhouse gases during the combustion process, thus bringing carbon emissions. The production of electricity serves the consumption of electricity. The carbon emission flow in the power system determines its flow state according to the flow distribution. Therefore, the factors that affect the flow will also affect the carbon emission flow. In the distribution network, the flow of carbon emission flow is affected by factors such as the location of the generator set and the grid structure. Although users do not directly emit carbon dioxide, they indirectly consume the power generated by thermal power units. Therefore, there are also carbon dioxide emissions on the user side. The node carbon potential is used to represent the carbon emission value equivalent to the power generation side caused by the unit electricity consumption at the node. The node carbon potential can be expressed as: the sum of the carbon flow rate flowing into the upstream branch connected to the node and the carbon flow rate injected by the generator set at this node divided by the sum of the node injection power. The calculation formula is as follows:

[0121]

[0122] In formula (31), e t,j is the node carbon potential of node j at time t; Ω b,j is the set of branches where active power flows into node j; P t l is the active power of branch l at time t; is the carbon flow density of branch l at time t; is the active power of the power source connected to node j at time t, and the power source includes new energy; is the equivalent power generation carbon intensity of node j at time t.

[0123] The carbon potential calculation formula obtained by sorting out the node carbon potential of all nodes is:

[0124]

[0125] In formula (32), E N is the carbon potential matrix of the distribution network nodes; P N is the node active power flow matrix; P E is the branch power flow distribution matrix; P G Inject distribution matrix into system units; E G is the carbon emission intensity vector of the unit.

[0126] This embodiment further formulates the electricity-carbon comprehensive subsidy as follows:

[0127] This embodiment uses the electricity-carbon comprehensive subsidy to clarify the carbon emission responsibility of each load in the distribution network, guide the user side to respond and participate in the power system dispatch, and encourage the methanol reforming hydrogen production equipment in the hydrogenation station to actively adjust the energy consumption strategy to reduce the carbon emissions in the distribution network. The carbon emission flow model is used to transfer the carbon emission responsibility from the power generation side to the user side. After calculating the node carbon potential of each node in the distribution network, the carbon price is used to establish the relationship between the electricity-carbon comprehensive subsidy and the node carbon potential. The calculation formula of the electricity-carbon comprehensive subsidy is as follows:

[0128]

[0129] In formula (33), is the electricity-carbon comprehensive subsidy of node j at time t; is the electricity price at time t; δ c For carbon tax.

[0130] After formulating the electricity-carbon comprehensive subsidy, the user side responds according to the node carbon potential issued by the distribution network, adjusts the temporal and spatial distribution of the load under the electricity-carbon comprehensive subsidy mechanism, reduces the processing demand for traditional high-carbon emission intensity power generation units during peak electricity consumption periods, and participates in the user-side electricity-carbon market to obtain benefits, which is specifically accomplished through the lower-level optimization scheduling model.

[0131] (3) Two-layer low-carbon dispatch model of electricity and hydrogen coupling

[0132] This embodiment establishes a two-layer low-carbon scheduling model for low-carbon scheduling of the electric-hydrogen integrated energy system. The two-layer low-carbon scheduling model includes an upper-layer optimization scheduling model and a lower-layer optimization scheduling model.

[0133] (3.1) Upper-layer optimization scheduling model

[0134] 1) Objective function

[0135] This embodiment aims to minimize the comprehensive operating cost of the electric-hydrogen integrated energy system. The comprehensive operating cost of the electric-hydrogen integrated energy system is the sum of the distribution network operating cost, the distribution network tiered carbon trading cost, the source side wind and solar abandonment penalty cost, the hydrogen station dissatisfaction penalty cost and the long-tube trailer transportation cost. The specific calculation formula is as follows:

[0136]

[0137] In formula (34), F s is the comprehensive operating cost of the electric-hydrogen integrated energy system; ope The operating cost of the distribution network; is the tiered carbon trading cost of the distribution network; f pun f is the penalty cost for abandoning wind and solar power at the source side; HFS Penalty cost for dissatisfaction with hydrogen refueling stations; f trans The shipping cost is for a tube trailer.

[0138] 1.1) Distribution network operation costs

[0139] The calculation formula of distribution network operation cost is as follows:

[0140] f ope =f g +f on +f EL +f ME +f CCS +f reH

[0141]

[0142] In formula (35), f g is the operating cost of the carbon capture power plant; on is the start-up and shutdown cost of the carbon capture power plant; EL is the operating cost of the water electrolysis hydrogen production equipment; ME is the operating cost of hydrogen-to-methanol equipment; CCS The carbon capture cost of the carbon capture power plant; reH is the operating cost of methanol reforming hydrogen production equipment; T is the scheduling period; a m , b m 、c m are the operating cost coefficients of carbon capture power plants; c g is the start-up and shutdown cost coefficient of the carbon capture power plant; u t-1 is the start and stop status of the carbon capture power plant at time t-1; u t is the start and stop status of the carbon capture power plant at time t; c EL is the operating cost coefficient of the water electrolysis hydrogen production equipment; c ME is the operating cost coefficient of hydrogen-to-methanol equipment; c CCS is the operating cost coefficient of the carbon capture power plant; c reH is the operating cost coefficient of methanol reforming hydrogen production equipment.

[0143] 1.2) Distribution network tiered carbon trading costs

[0144] The direct sources of carbon dioxide emissions in the electric-hydrogen integrated energy system include: carbon emissions from long-tube trailer transportation, carbon emissions from methanol reforming hydrogen production equipment in hydrogenation stations, and carbon emissions from integrated energy microgrids (including equivalent carbon emissions captured by carbon capture power plants and equivalent carbon emissions from electricity purchased from distribution networks). The specific calculation formula is as follows:

[0145] E real =E trans +E reH +E PH +E buy (36)

[0146] In formula (36), E real is the actual carbon emissions; E trans Carbon emissions from tube trailer transportation; E reH E is the carbon emission of methanol reforming hydrogen production equipment in hydrogen refueling station; PH E is the equivalent carbon emissions captured by the carbon capture power plant; buy Equivalent carbon emissions from purchasing electricity for the distribution grid.

[0147] The calculation formula for carbon emissions from tube trailer transportation is as follows:

[0148]

[0149] In formula (37), N E For the collection of long tube trailers; N A It is a collection of hydrogen production plants and hydrogen refueling stations; X ije is a binary variable; ij is the distance between hydrogen refueling station i and hydrogen refueling station j; f coal is the amount of fuel per unit distance traveled; e emi It is the carbon dioxide emission per unit energy consumption of fuel vehicles.

[0150] The calculation formula for carbon emissions from methanol reforming hydrogen production equipment in a hydrogenation station is as follows:

[0151]

[0152] In formula (38), is the carbon dioxide emissions generated by the methanol reforming hydrogen production equipment at hydrogenation station i at time t.

[0153] The calculation formula for equivalent carbon emissions captured by a carbon capture power plant is as follows:

[0154]

[0155] The calculation formula for the equivalent carbon emissions generated by purchasing electricity from the distribution network is as follows:

[0156]

[0157] In formula (40), a, b, and c are carbon emission coefficients; P t,buy is the power purchase amount of the distribution network at time t.

[0158] The trading share of the electric-hydrogen integrated energy system in the carbon trading market is the difference between the free carbon quota and the actual carbon emissions, as follows:

[0159] E tr =E q -E real (41)

[0160] In formula (41), E tr is the transaction share; E q For free carbon quota.

[0161] The tiered carbon trading mechanism stipulates the trading range for the electric-hydrogen integrated energy system to participate in carbon trading and the unit carbon trading price in different trading ranges. As carbon emissions increase, the unit carbon trading price λ CO2 The coefficient α increases step by step. When the actual carbon emissions are lower than the free carbon quota, the electric hydrogen integrated energy system sells carbon emission quotas through the carbon trading market at a price of unit carbon trading price λ CO2 , adding a step-by-step carbon trading factor to the electric-hydrogen integrated energy system can further limit the carbon emissions of the electric-hydrogen integrated energy system and increase environmental benefits. The step-by-step carbon trading cost of the distribution network can be expressed as the following piecewise function:

[0162]

[0163] 1.3) Penalty costs for abandoning wind and solar power at the source side

[0164] The calculation formula for the penalty cost of abandoned wind and solar power on the source side is as follows:

[0165]

[0166] In formula (43), J1 is the total number of photovoltaic power generation units; c pv is the penalty coefficient of the photovoltaic generator set; is the predicted output of photovoltaic generator set j at time t; is the actual output of photovoltaic generator set j at time t; J2 is the total number of wind turbine generator sets; c wind is the penalty coefficient of the wind turbine generator set; is the predicted output of wind turbine j at time t; is the actual output of wind turbine j at time t.

[0167] 1.4) Penalty cost for dissatisfaction with hydrogen refueling stations

[0168] The number of times a hydrogen refueling station accepts unloading, the time waiting for delivery, and the abundance of hydrogen in the station affect the service quality and satisfaction of the hydrogen refueling station accepting delivery. In order to ensure the efficiency of long-tube trailer delivery, a hydrogen refueling station acceptance and delivery service quality evaluation function is established to guide long-tube trailers to provide high-quality services to hydrogen refueling stations. Under the specific acceptance and delivery service window of the hydrogen refueling station, the shorter the time the hydrogen refueling station waits for delivery, the higher the satisfaction of the hydrogen refueling station. The more times the hydrogen refueling station accepts hydrogen unloading from long-tube trailers, the more corresponding human and material labor is required. This behavior is related to the economy of hydrogen refueling station operation. The lower the satisfaction of the hydrogen refueling station, the more hydrogen the station hopes to have sufficient hydrogen in the station to prevent a sudden increase in hydrogen demand. Therefore, the remaining amount of hydrogen in the station also affects the hydrogen refueling station's evaluation of the long-tube trailer service quality. Considering the time the hydrogen refueling station waits for delivery, the number of times it accepts unloading, and the abundance of hydrogen in the station, the hydrogen refueling station acceptance and delivery service quality evaluation function can be obtained, that is, the calculation formula of the dissatisfaction penalty cost of the hydrogen refueling station is:

[0169] f HFS =C HFS (μ 1 f T +μ 2 f N +μ 3 f r )(44)

[0170] In formula (44), f HFS Penalty cost for dissatisfaction with hydrogen refueling station; C HFS is the dissatisfaction penalty coefficient of the hydrogen refueling station; μ 1 is the first weight coefficient; f T Dissatisfaction with the waiting time for delivery at hydrogen refueling stations; μ 2 is the second weight coefficient; f N The number of unloading times accepted by the hydrogen refueling station is not satisfactory; μ 3 is the third weight coefficient; f r The hydrogen supply level at the hydrogen refueling station is not satisfactory.

[0171] The calculation formula for dissatisfaction with the waiting time for delivery at hydrogen refueling stations is as follows:

[0172]

[0173] In formula (45), A T N is the first adjustment coefficient of dissatisfaction of hydrogen refueling station; F is the collection of hydrogen refueling stations; T is the first proportional adjustment coefficient; T i,start T is the time when the hydrogen refueling station starts waiting for delivery; i,end This is the time that the hydrogen refueling station stops waiting for delivery.

[0174] The calculation formula for the dissatisfaction of the number of unloading times accepted by the hydrogen refueling station is as follows:

[0175]

[0176] In formula (46), A N is the second adjustment coefficient of dissatisfaction with hydrogen refueling stations; κ N is the second proportional adjustment coefficient; N accept The number of times the tube trailer is unloaded.

[0177] The power function is used to represent the relationship between the service quality evaluation of the hydrogen refueling station and the remaining amount of hydrogen in the station. As the amount of hydrogen in the station decreases, the satisfaction becomes lower. That is, the calculation formula for the dissatisfaction of the hydrogen abundance of the hydrogen refueling station is as follows:

[0178]

[0179] In formula (47), is the hydrogen storage capacity of hydrogen refueling station j; is the critical hydrogen storage capacity of the hydrogen refueling station. When the hydrogen storage capacity of hydrogen refueling station j is less than The dissatisfaction with hydrogen abundance at hydrogen refueling stations will gradually increase; R max The maximum dissatisfaction of hydrogen abundance at the hydrogen refueling station, which is generally set to 1; The maximum hydrogen storage capacity of a hydrogen refueling station.

[0180] 1.5) Transportation cost of long tube trailer

[0181] The calculation formula for the tube trailer transportation cost is as follows:

[0182]

[0183] In formula (48), c run is the transportation cost per kilometer of the long tube trailer; c fix is the fixed transportation cost of the tube trailer.

[0184] 2) Constraints

[0185] 2.1) Equipment operation constraints of the hydrogen supply chain

[0186] In addition to the constraints on the hydrogen production and transportation process mentioned in step (1), the equipment operation constraints of the hydrogen supply chain also include:

[0187] a) Upper and lower limits on the power generation capacity of carbon capture power plants

[0188]

[0189] In formula (49), They are respectively the lower and upper limits of the power generation capacity of the carbon capture power plant.

[0190] b) Carbon capture power plant ramping constraints

[0191]

[0192] In formula (50), They are the lower and upper limits of the ramp rate of the carbon capture power plant, respectively; is the power generation capacity of the carbon capture power plant at time t-1.

[0193] c) Upper and lower limits of output of each device

[0194]

[0195] In the above formula, They are the lower limit and upper limit of the power consumption of the water electrolysis hydrogen production equipment respectively; They are respectively the lower and upper limits of the power consumption of hydrogen-to-methanol equipment.

[0196] 2.2) Constraints on wind and solar power abandonment

[0197] The constraints on wind and solar curtailment are as follows:

[0198]

[0199] 2.3) Power flow constraints of distribution network

[0200] This embodiment introduces the Distflow power flow constraint. The Distflow branch power flow model does not need to consider the phase difference between voltage and current and is applicable to radial networks. However, the Distflow branch power flow model is difficult to solve due to its non-convexity. The nonlinear terms of voltage and current can be relaxed by the second-order cone to facilitate rapid solution. The standard second-order cone form is as follows:

[0201]

[0202] In formula (54), P j,t is the active power injected into node j at time t; Ω s,j is the set of all first nodes with node j as the end; P ij,t is the active power flowing from node i to node j at time t; is the square of the current amplitude of branch ij at time t; r ij is the resistance of branch ij; Ω e,j is the set of all tail nodes starting with node j; P jk,t is the active power flowing from node j to node k at time t; Q j,t is the reactive power injected into node j at time t; Qij,t is the reactive power flowing from node i to node j at time t; x ij is the reactance of branch ij; Q jk,t is the reactive power flowing from node j to node k at time t; is the square of the voltage amplitude of node i at time t; is the square of the voltage amplitude at node j at time t; is the square of the current amplitude at node i at time t.

[0203] For the node where the hydrogen production plant is located, the node injection power can be expressed by the following formula:

[0204]

[0205] For the node where the hydrogen refueling station is located, the node injection power can be expressed by the following formula:

[0206]

[0207] For the node where the photovoltaic generator set is located, the node injection power can be expressed by the following formula:

[0208]

[0209] In formula (57), is the load of node j at time t; Ω pv It is the set of nodes where the photovoltaic generators are located.

[0210] For the node where the wind turbine generator set is located, the node injection power can be expressed as follows:

[0211]

[0212] In formula (58), Ω wind It is the set of nodes where wind turbines are located.

[0213] The node voltage and branch current constraints are as follows:

[0214]

[0215] In formula (59), are the lower and upper limits of the voltage amplitude of node i, respectively; They are the lower and upper limits of the current amplitude of branch ij respectively.

[0216] (3.2) Lower-level optimization scheduling model

[0217] 1) Objective function

[0218] This embodiment aims to minimize the cost of low-carbon demand response electricity-carbon comprehensive subsidy. The calculation formula of low-carbon demand response electricity-carbon comprehensive subsidy cost is as follows:

[0219]

[0220] In formula (60), f DR is the comprehensive subsidy cost of electricity-carbon for low-carbon demand response; T is the dispatch period; Ω DR is a set of nodes participating in low-carbon demand response in the distribution network, which is predetermined; is the electricity-carbon comprehensive subsidy of node j at time t; is the low-carbon demand response of node j at time t; N F A collection of hydrogen refueling stations; is the power adjustment of methanol reforming hydrogen production equipment j at time t.

[0221] It should be noted that Multiplication Represents the electricity-carbon comprehensive subsidy of node j connected to methanol reforming hydrogen production equipment j at time t.

[0222] 2) Constraints

[0223] 2.1) Demand response constraints

[0224] The demand response constraints are as follows:

[0225]

[0226]

[0227] In the above formula, is the minimum demand response amount of node j; is the maximum demand response amount of node j; is the load of node j after demand response at time t; is the load of node j before demand response at time t.

[0228] 2.2) Power adjustment constraints of methanol reforming hydrogen production equipment

[0229] The power adjustment constraints are as follows:

[0230]

[0231]

[0232] In the above formula, is the power consumption of methanol reforming hydrogen production equipment j after demand response at time t; is the power consumption of methanol reforming hydrogen production equipment j before demand response at time t; is the minimum power adjustment of methanol reforming hydrogen production equipment j; It is the maximum power adjustment of methanol reforming hydrogen production equipment j.

[0233] (4) Solution of the two-layer low-carbon scheduling model

[0234] This embodiment solves the two-layer low-carbon scheduling model to obtain a low-carbon scheduling plan for the electric-hydrogen integrated energy system. The low-carbon scheduling plan includes the operating parameters of each device in the hydrogen supply chain, the operating parameters of each device in the new energy, and the low-carbon demand response amount of the nodes in the distribution network participating in the low-carbon demand response.

[0235] This embodiment takes into account the interests of the distribution network entity and the load and the responsibility for carbon emissions, and designs a two-layer low-carbon scheduling model. The two-layer low-carbon scheduling model is based on a long time scale and continuously optimizes for 24 hours at a time interval of 1 hour. The predicted data of wind power and photovoltaics, the predicted data of hydrogen demand at hydrogen refueling stations, and the transportation network and distribution network topology are used as inputs. The upper-layer optimization scheduling model formulates a scheduling strategy with the goal of minimizing the overall operating cost, calculates the flow, carbon flow and node carbon potential, and passes the node carbon potential to the lower-layer optimization scheduling model. The lower-layer optimization scheduling model updates the electricity-carbon comprehensive subsidy price according to the node carbon potential, optimizes the low-carbon demand response, adjusts the spatiotemporal distribution of the load, and passes the load value after the demand response to the upper-layer optimization scheduling model. The variables are updated through continuous iteration of the upper and lower layers, and the iteration is cyclic until the convergence condition (i.e., the iteration termination condition) is reached.

[0236] Among them, both the upper-level optimization scheduling model and the lower-level optimization scheduling model can be solved using the commercial solver Gurobi.

[0237] At this time, in this embodiment, the two-layer low-carbon scheduling model is solved to obtain a low-carbon scheduling plan for the electric-hydrogen integrated energy system, which specifically includes:

[0238] 1) Randomly set the load of each node in the initial distribution network and the power consumption of the methanol reforming hydrogen production equipment.

[0239] 2) Taking the load of each node in the initial distribution network and the power consumption of the methanol reforming hydrogen production equipment as input, the upper-level optimization scheduling model is solved to obtain the operating parameters of each device in the current iteration of the hydrogen supply chain and the operating parameters of each device in the new energy.

[0240] Solving the upper-level optimization scheduling model, specifically including: using the commercial solver Gurobi to solve the upper-level optimization scheduling model.

[0241] The operating parameters of each device in the hydrogen supply chain include P t EL , P t CCS , P t ME , B t,e , X ije ,u(i),u(j),X 0je , X i0e , T i rel , δ t,j,e , The operating parameters of each device in the new energy include

[0242] 3) Based on the operating parameters of each device in the current iteration of the hydrogen supply chain and the operating parameters of each device in the new energy, the node carbon potential of each node in the distribution network is calculated, and based on the node carbon potential of each node in the distribution network, the electricity-carbon comprehensive subsidy for each node in the distribution network is calculated.

[0243] The calculation formula for the node carbon potential is formula (31), and the calculation formula for the electricity-carbon comprehensive subsidy is formula (33).

[0244] 4) Taking the comprehensive electricity-carbon subsidy of each node in the distribution network as input, the lower-level optimization scheduling model is solved to obtain the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the current iteration of the distribution network and the power adjustment amount of the methanol reforming hydrogen production equipment. Based on the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the current iteration of the distribution network and the power adjustment amount of the methanol reforming hydrogen production equipment, the load of each node in the current iteration of the distribution network and the power consumption of the methanol reforming hydrogen production equipment are calculated.

[0245] Solving the lower-level optimization scheduling model, specifically including: using the commercial solver Gurobi to solve the lower-level optimization scheduling model.

[0246] The low-carbon demand response amount of the nodes participating in the low-carbon demand response in the distribution network is The power adjustment of methanol reforming hydrogen production equipment is

[0247] The load of nodes participating in the low-carbon demand response is determined through the lower-level optimization scheduling model, and the load of nodes not participating in the low-carbon demand response remains the original load, so the load of each node in the distribution network can be determined.

[0248] 5) Determine whether the iteration termination condition is reached.

[0249] The iteration termination condition is:

[0250]

[0251] In formula (65), is the low-carbon demand response electricity-carbon comprehensive subsidy cost of the current iteration k+1; is the low-carbon demand response electricity-carbon comprehensive subsidy cost of the previous iteration k; δ is the preset threshold.

[0252] 6) If so, stop the iteration and use the operating parameters of each device in the current iteration of the hydrogen supply chain, the operating parameters of each device in the new energy source, and the low-carbon demand response of the nodes participating in the low-carbon demand response in the distribution network as the low-carbon scheduling plan for the electric-hydrogen integrated energy system.

[0253] 7) If not, continue iterating, taking the load of each node in the current iteration of the distribution network and the power consumption of the methanol reforming hydrogen production equipment as the load of each node in the initial distribution network and the power consumption of the methanol reforming hydrogen production equipment, and return to the step of "taking the load of each node in the initial distribution network and the power consumption of the methanol reforming hydrogen production equipment as input, solving the upper-level optimization scheduling model, and obtaining the operating parameters of each device in the current iteration of the hydrogen supply chain and the operating parameters of each device in the new energy".

[0254] In this embodiment, methanol is used as a hydrogen carrier for transportation. Aiming at the carbon emission problems in each link of production, transportation and consumption, a two-layer low-carbon scheduling model is designed. The upper optimization scheduling model uses a step-by-step carbon trading mechanism to calculate the carbon emission trading cost, optimize the transportation route of the long-tube trailer and the output plan of each equipment, and transmits the 24-hour node carbon potential to the lower optimization scheduling model. The lower optimization scheduling model updates the electricity-carbon comprehensive subsidy price and adjusts the spatiotemporal distribution of energy consumption of methanol reforming hydrogen production equipment and other demand response resources at the hydrogen filling station. In this embodiment, the carbon emission responsibility of the distribution network nodes is quantified by the node carbon potential, a low-carbon scheduling strategy for demand response resources is designed, and an electricity-carbon comprehensive subsidy price is formulated. This solves the problem of excessive carbon emissions when methanol is used as a hydrogen carrier for transportation and methanol reforming hydrogen production, and achieves the purpose of low-carbon emissions in the distribution network, thereby realizing low-carbon emissions in the electricity-hydrogen integrated energy system.

[0255] This embodiment designs a hydrogen station dissatisfaction penalty cost in the double-layer low-carbon scheduling model, which can not only effectively evaluate the service quality of the long-tube trailer, but also guide the distribution behavior of the long-tube trailer, optimize the transportation route and transportation process, and improve the overall quality of the distribution service received by the hydrogen station while meeting the load demand of the hydrogen station.

[0256] The present application also provides an application scenario, which applies the above-mentioned low-carbon scheduling method for an electric-hydrogen integrated energy system considering alcohol transportation. Specifically, the low-carbon scheduling method for an electric-hydrogen integrated energy system considering alcohol transportation provided in this embodiment can be applied in a low-carbon scheduling scenario. The low-carbon scheduling scenario includes a planning link and an operation link. The planning link is used to obtain a low-carbon scheduling plan, and the operation link is used to make the electric-hydrogen integrated energy system operate in a low-carbon manner according to the low-carbon scheduling plan. The low-carbon scheduling method for an electric-hydrogen integrated energy system considering alcohol transportation provided in this embodiment belongs to the planning link.

[0257] Example 2

[0258] Based on the same inventive concept, the embodiment of the present application also provides a low-carbon dispatching device for an electric-hydrogen integrated energy system considering alcohol transportation for realizing the low-carbon dispatching method for an electric-hydrogen integrated energy system considering alcohol transportation involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more embodiments of the low-carbon dispatching device for an electric-hydrogen integrated energy system considering alcohol transportation provided below can refer to the limitations of the low-carbon dispatching method for an electric-hydrogen integrated energy system considering alcohol transportation above, and will not be repeated here.

[0259] In an exemplary embodiment, Figure 5 As shown, a low-carbon dispatching device for an electric-hydrogen integrated energy system considering alcohol transportation is provided, and the low-carbon dispatching device for an electric-hydrogen integrated energy system considering alcohol transportation comprises:

[0260] The model building module M1 is used to establish a double-layer low-carbon dispatching model for low-carbon dispatching of the electric-hydrogen integrated energy system; the double-layer low-carbon dispatching model includes an upper-layer optimization dispatching model and a lower-layer optimization dispatching model. The upper-layer optimization dispatching model takes the minimum comprehensive operating cost of the electric-hydrogen integrated energy system as the objective function, takes the equipment operation constraints of the hydrogen supply chain, the wind and solar power abandonment constraints of new energy, and the power flow constraints of the distribution network as constraints, and optimizes the operating parameters of each device in the hydrogen supply chain and the operating parameters of each device in the new energy; the lower-layer optimization dispatching model takes the low-carbon The objective function is to minimize the comprehensive electricity-carbon subsidy cost for demand response. The demand response constraints of the distribution network and the power adjustment constraints of the methanol reforming hydrogen production equipment in the hydrogen supply chain are used as constraints. The low-carbon demand response amount of the nodes participating in the low-carbon demand response in the distribution network and the power adjustment amount of the methanol reforming hydrogen production equipment are optimized. Among them, the hydrogen supply chain includes hydrogen production plants and hydrogen refueling stations. The hydrogen production plants include water electrolysis hydrogen production equipment, carbon capture power plants, hydrogen to methanol equipment, alcohol storage tanks and long-tube trailers. The hydrogen refueling stations include methanol reforming hydrogen production equipment. New energy includes photovoltaic generators and wind generators.

[0261] The model solving module M2 is used to solve the two-layer low-carbon scheduling model to obtain a low-carbon scheduling plan for the electric-hydrogen integrated energy system; the low-carbon scheduling plan includes the operating parameters of each device in the hydrogen supply chain, the operating parameters of each device in the new energy, and the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the distribution network.

[0262] Example 3

[0263] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 6 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a low-carbon scheduling method for an electric hydrogen integrated energy system considering alcohol transportation is implemented.

[0264] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0265] In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the low-carbon scheduling method of the electric-hydrogen integrated energy system considering alcohol transportation in Example 1 is implemented.

[0266] Example 4

[0267] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, which, when executed by a processor, implements the low-carbon scheduling method of the electric-hydrogen integrated energy system considering alcohol transportation in Example 1.

[0268] Example 5

[0269] In an exemplary embodiment, a computer program product is provided, including a computer program, which, when executed by a processor, implements the low-carbon scheduling method of the electric-hydrogen integrated energy system considering alcohol transportation in Example 1.

[0270] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0271] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0272] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A low-carbon dispatching method for an electric-hydrogen integrated energy system considering alcohol transportation, characterized in that: The low-carbon dispatching method of the electric-hydrogen integrated energy system considering alcohol transportation includes: A double-layer low-carbon dispatch model for low-carbon dispatch of an electric-hydrogen integrated energy system is established; the double-layer low-carbon dispatch model includes an upper-layer optimization dispatch model and a lower-layer optimization dispatch model, the upper-layer optimization dispatch model takes the minimum comprehensive operation cost of the electric-hydrogen integrated energy system as the objective function, takes the equipment operation constraints of the hydrogen supply chain, the wind and solar abandonment constraints of new energy, and the power flow constraints of the distribution network as constraints, and optimizes the operation parameters of each device in the hydrogen supply chain and the operation parameters of each device in the new energy; the lower-layer optimization dispatch model takes the minimum low-carbon demand response electricity-carbon comprehensive subsidy cost as the objective function, takes the demand response constraints of the distribution network and the power adjustment constraints of the methanol reforming hydrogen production equipment in the hydrogen supply chain as constraints, and optimizes the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the distribution network and the power adjustment amount of the methanol reforming hydrogen production equipment; wherein the hydrogen supply chain includes a hydrogen production plant and a hydrogenation station, the hydrogen production plant includes a water electrolysis hydrogen production equipment, a carbon capture power plant, a hydrogen production methanol equipment, an alcohol storage tank and a long-tube trailer, the hydrogenation station includes a methanol reforming hydrogen production equipment, and the new energy includes a photovoltaic generator set and a wind generator set; The two-layer low-carbon scheduling model is solved to obtain a low-carbon scheduling plan for the electric-hydrogen integrated energy system; the low-carbon scheduling plan includes the operating parameters of each device in the hydrogen supply chain, the operating parameters of each device in the new energy, and the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the distribution network.

2. The low-carbon dispatching method of the electric-hydrogen integrated energy system considering alcohol transportation according to claim 1 is characterized in that: The comprehensive operating cost of the electric-hydrogen integrated energy system is the sum of the distribution network operating cost, the distribution network tiered carbon trading cost, the source-side wind and solar power abandonment penalty cost, the hydrogen station dissatisfaction penalty cost, and the long-tube trailer transportation cost. The calculation formula for the dissatisfaction penalty cost of hydrogen refueling stations is: f HFS =C HFS (μ1f T +μ2f N +μ3f r ); Among them, f HFS Penalty cost for dissatisfaction with hydrogen refueling station; C HFS is the dissatisfaction penalty coefficient of the hydrogen refueling station; μ1 is the first weight coefficient; f T is the dissatisfaction of waiting time for delivery at hydrogen refueling station; μ2 is the second weight coefficient; f N is the number of unloading dissatisfaction of the hydrogen refueling station; μ3 is the third weight coefficient; f r Dissatisfaction with the hydrogen abundance of hydrogen refueling stations; Among them, A T N is the first adjustment coefficient of dissatisfaction of hydrogen refueling station; F is the collection of hydrogen refueling stations; T is the first proportional adjustment coefficient; T i,start T is the time when the hydrogen refueling station starts waiting for delivery; i,end The time it takes for a hydrogen refueling station to stop waiting for delivery; Among them, A N is the second adjustment coefficient of dissatisfaction with hydrogen refueling stations; κ N is the second proportional adjustment coefficient; N accept The number of times the tube trailers are unloaded; in, is the critical hydrogen storage capacity of the hydrogen refueling station; is the hydrogen storage capacity of hydrogen refueling station j; is the maximum hydrogen storage capacity of the hydrogen refueling station; R max The maximum dissatisfaction level of hydrogen abundance at the hydrogen refueling station.

3. The low-carbon dispatching method of the electric-hydrogen integrated energy system considering alcohol transportation according to claim 1 is characterized in that: The calculation formula for the low-carbon demand response electricity-carbon comprehensive subsidy cost is: Among them, f DR is the comprehensive subsidy cost of electricity-carbon for low-carbon demand response; T is the dispatch period; Ω DR It is the collection of nodes participating in low-carbon demand response in the distribution network; is the electricity-carbon comprehensive subsidy of node j at time t; is the low-carbon demand response of node j at time t; N F A collection of hydrogen refueling stations; is the power adjustment of methanol reforming hydrogen production equipment j at time t; The demand response constraints are: in, is the minimum demand response amount of node j; is the maximum demand response amount of node j; is the load of node j after demand response at time t; is the load of node j before demand response at time t; The power adjustment constraint is: in, is the power consumption of methanol reforming hydrogen production equipment j after demand response at time t; is the power consumption of methanol reforming hydrogen production equipment j before demand response at time t; is the minimum power adjustment of methanol reforming hydrogen production equipment j; It is the maximum power adjustment of methanol reforming hydrogen production equipment j.

4. The low-carbon dispatching method of the electric-hydrogen integrated energy system considering alcohol transportation according to claim 1 is characterized in that: The two-layer low-carbon dispatch model is solved to obtain a low-carbon dispatch scheme for the electric-hydrogen integrated energy system, which specifically includes: The load of each node in the initial distribution network and the power consumption of the methanol reforming hydrogen production equipment are randomly set; Taking the load of each node in the initial distribution network and the power consumption of the methanol reforming hydrogen production equipment as input, the upper-level optimization scheduling model is solved to obtain the operating parameters of each equipment in the current iteration of the hydrogen supply chain and the operating parameters of each equipment in the new energy source; Based on the operating parameters of each device in the current iteration of the hydrogen supply chain and the operating parameters of each device in the new energy, the node carbon potential of each node in the distribution network is calculated, and based on the node carbon potential of each node in the distribution network, the electricity-carbon comprehensive subsidy of each node in the distribution network is calculated; Taking the electricity-carbon comprehensive subsidy of each node in the distribution network as input, the lower-level optimization scheduling model is solved to obtain the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the current iteration of the distribution network and the power adjustment amount of the methanol reforming hydrogen production equipment; based on the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the current iteration of the distribution network and the power adjustment amount of the methanol reforming hydrogen production equipment, the load of each node in the current iteration of the distribution network and the power consumption of the methanol reforming hydrogen production equipment are calculated; Determine whether the iteration termination condition is reached; If yes, then the iteration is stopped, and the operating parameters of each device in the hydrogen supply chain of the current iteration, the operating parameters of each device in the new energy source, and the low-carbon demand response of the nodes participating in the low-carbon demand response in the distribution network are used as the low-carbon scheduling plan of the electric-hydrogen integrated energy system; If not, continue to iterate, taking the load of each node in the current iteration of the distribution network and the power consumption of the methanol reforming hydrogen production equipment as the load of each node in the initial distribution network and the power consumption of the methanol reforming hydrogen production equipment, and return to the step of "taking the load of each node in the initial distribution network and the power consumption of the methanol reforming hydrogen production equipment as input, solving the upper-level optimization scheduling model, and obtaining the operating parameters of each device in the current iteration of the hydrogen supply chain and the operating parameters of each device in the new energy".

5. The low-carbon dispatching method of the electric-hydrogen integrated energy system considering alcohol transportation according to claim 4 is characterized in that: The calculation formula of the node carbon potential is: Among them, e t,j is the node carbon potential of node j at time t; Ω b,j is the set of branches where active power flows into node j; P t l is the active power of branch l at time t; is the carbon flow density of branch l at time t; is the active power of the power source connected to node j at time t, and the power source includes new energy; is the equivalent power generation carbon intensity of node j at time t; The calculation formula for the electricity-carbon comprehensive subsidy is: in, is the electricity-carbon comprehensive subsidy of node j at time t; is the electricity price at time t; δ c For carbon tax.

6. The low-carbon dispatching method of the electric-hydrogen integrated energy system considering alcohol transportation according to claim 4 is characterized in that: The iteration termination condition is: in, is the low-carbon demand response electricity-carbon comprehensive subsidy cost of the current iteration k+1; is the low-carbon demand response electricity-carbon comprehensive subsidy cost of the previous iteration k; δ is the preset threshold; Solving the upper-level optimization scheduling model specifically includes: solving the upper-level optimization scheduling model using a commercial solver Gurobi; Solving the lower-level optimization scheduling model specifically includes: solving the lower-level optimization scheduling model using the commercial solver Gurobi.

7. A low-carbon dispatching device for an electric-hydrogen integrated energy system considering alcohol transportation, characterized in that: The low-carbon dispatching device of the electric-hydrogen integrated energy system considering alcohol transportation includes: A model building module is used to establish a double-layer low-carbon dispatch model for low-carbon dispatch of the electric-hydrogen integrated energy system; the double-layer low-carbon dispatch model includes an upper-layer optimization dispatch model and a lower-layer optimization dispatch model, the upper-layer optimization dispatch model takes the minimum comprehensive operation cost of the electric-hydrogen integrated energy system as the objective function, takes the equipment operation constraints of the hydrogen supply chain, the wind and solar abandonment constraints of new energy, and the power flow constraints of the distribution network as constraints, and optimizes the operation parameters of each equipment in the hydrogen supply chain and the operation parameters of each equipment in the new energy; the lower-layer optimization dispatch model takes the low-carbon demand The objective function is to minimize the comprehensive subsidy cost of electricity and carbon, and the demand response constraints of the distribution network and the power adjustment constraints of the methanol reforming hydrogen production equipment in the hydrogen supply chain are used as constraints to optimize the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the distribution network and the power adjustment amount of the methanol reforming hydrogen production equipment; wherein, the hydrogen supply chain includes a hydrogen production plant and a hydrogen refueling station, the hydrogen production plant includes a water electrolysis hydrogen production equipment, a carbon capture power plant, a hydrogen to methanol equipment, an alcohol storage tank and a long tube trailer, the hydrogen refueling station includes a methanol reforming hydrogen production equipment, and the new energy includes a photovoltaic generator set and a wind turbine generator set; The model solving module is used to solve the two-layer low-carbon scheduling model to obtain a low-carbon scheduling plan for the electric-hydrogen integrated energy system; the low-carbon scheduling plan includes the operating parameters of each device in the hydrogen supply chain, the operating parameters of each device in the new energy, and the low-carbon demand response amount of the nodes participating in the low-carbon demand response in the distribution network.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the low-carbon scheduling method for an electric-hydrogen integrated energy system taking into account alcohol transportation as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the low-carbon scheduling method for an electric-hydrogen integrated energy system taking into account alcohol transportation as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, it implements the low-carbon scheduling method for an electric-hydrogen integrated energy system taking into account alcohol transportation as described in any one of claims 1-6.

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