Dynamic planning optimization method and system for regional hydrogen energy storage and transportation infrastructure

Abstract

The invention discloses a regional hydrogen energy storage and transportation infrastructure dynamic planning optimization method and system. The method comprises the following steps: defining system parameters of the polymorphic hydrogen energy region storage and transportation system; constructing a target function of the polymorphic hydrogen energy region storage and transportation system, wherein the target function is used for minimizing the total cost of polymorphic hydrogen storage and transportation; establishing constraint conditions of the polymorphic hydrogen energy region storage and transportation system, including production operation constraints of a form conversion link, a storage link and a transportation link, and supply and demand equilibrium constraints of hydrogen in various forms; and carrying out dynamic planning optimization on the regional hydrogen energy storage and transportation infrastructure by utilizing the system parameters, the objective function and the constraint conditions. According to the method, a complete constraint system including a form transformation constraint, a storage constraint, a transportation constraint and a supply and demand balance constraint is constructed, and the planning scheme is ensured to meet technical requirements and actual requirements.

Description

Technical Field

[0001] The present invention generally relates to the field of dynamic programming. More specifically, the present invention relates to a dynamic programming optimization method for regional hydrogen energy storage and transportation infrastructure considering morphological transformation. Background Art

[0002] With the in-depth promotion of the global energy transformation and carbon neutrality strategy, the importance of hydrogen energy as a clean energy carrier has been continuously increasing. The International Energy Agency predicts that China's hydrogen production will increase from 30 million tons in 2020 to 90 million tons in 2060. China's northwest region is rich in renewable energy resources (such as wind and solar), while the regions with large-scale hydrogen demand are mainly the economically developed and densely populated southeast regions, that is, the potential of wind and solar hydrogen production does not match the hydrogen demand in terms of spatial distribution. In the next few decades, China not only needs to layout and construct large-scale green hydrogen production infrastructure, but also needs to layout large-scale green hydrogen storage and transportation network channel infrastructure. During the process of regional hydrogen energy utilization, hydrogen energy can exist in various forms such as gaseous hydrogen, liquid hydrogen, organic liquid hydrogen, and ammonia. The conversion between different forms and the construction planning of storage and transportation facilities directly affect the economic efficiency and environmental benefits of hydrogen energy utilization.

[0003] In the prior art, there are the following types of technical solutions in the planning of hydrogen energy storage and transportation systems: 1. In terms of hydrogen refueling station planning technology, for example, Chinese Patent CN112381325B discloses "a hydrogen refueling station planning method", which establishes an objective function of maximizing the construction demand of hydrogen refueling stations and minimizing the unit hydrogen usage cost, and considers constraint conditions such as raw material balance and CO2 balance. Although this method considers environmental benefits, it is only limited to the planning of a single facility of the hydrogen refueling station. 2. Hydrogen refueling behavior analysis technology, for example, Chinese Patent CN117194929B proposes "a fuel cell vehicle hydrogen refueling behavior analysis method based on a big data platform". This method guides the layout planning of hydrogen refueling stations by analyzing the hydrogen refueling characteristics of fuel cell vehicles, but does not consider the conversion process between various hydrogen energy forms. 3. Multi-energy complementary system planning technology, for example, Chinese Patent CN111242806B proposes "a planning method for an electric-thermal-hydrogen multi-energy system considering uncertainty", which establishes a mathematical model including hydrogen production equipment, hydrogen storage equipment, and hydrogen usage equipment, and optimizes the system with the goal of minimizing economic cost. However, this method mainly focuses on the internal energy balance of the system and does not consider the flow and morphological transformation of hydrogen energy between regions. 4. Hydrogen production system planning technology, for example, Chinese Patent CN106786764B proposes "a hydrogen production capacity optimization configuration method for utilizing a hydrogen production system to absorb abandoned wind power of a wind farm", which determines the hydrogen production system capacity based on the characteristics of abandoned wind power of the wind farm. However, this method only focuses on the hydrogen production link and does not consider the optimization of the whole process of hydrogen energy storage and transportation.

[0004] In summary, in the prior art, there is a lack of systematic consideration of the hydrogen energy form conversion process. The storage and transportation planning mainly focuses on a specific form of hydrogen energy, such as the pipeline network planning of gaseous hydrogen or the transportation planning of liquid hydrogen. The conversion process between various forms such as gaseous hydrogen, liquid hydrogen, organic liquid hydrogen, and ammonia and their costs are not systematically considered, making it difficult to achieve the overall optimization of the regional hydrogen energy system. The dynamic evolution characteristics of storage and transportation infrastructure are not considered. Most use static planning methods, without considering the dynamic processes of construction and decommissioning of storage and transportation infrastructure during the planning period, nor the dynamic changes in the utilization rates of various facilities, resulting in the planning scheme being difficult to adapt to the development and changes of hydrogen energy demand. There is a lack of quantitative analysis of form conversion efficiency. When conducting hydrogen energy storage and transportation planning, the quantitative relationship between form conversion efficiency and system operation cost is not established, and the economic and environmental benefits of different form conversion paths cannot be accurately evaluated, affecting the scientific nature of the planning scheme. A complete cost optimization model is not established. The capital cost, operation and maintenance cost, operation cost, and environmental cost of the form conversion link are not comprehensively considered. The mapping relationship between the scale of storage and transportation infrastructure and system cost is not established. There is a lack of quantitative analysis of carbon emission cost, and the economic impact caused by efficiency loss is not considered. The constraint condition system is incomplete. The prior art mainly considers equipment capacity and supply-demand balance in terms of constraint conditions, and a complete constraint system including form conversion constraints, storage constraints, transportation constraints, and supply-demand balance constraints cannot be established, making it difficult to ensure the feasibility of the planning scheme. Summary of the Invention

[0005] In order to at least solve the technical problems described in the above background art section, the present invention proposes a dynamic planning and optimization method and system for regional hydrogen energy storage and transportation infrastructure considering form conversion, which can meet the requirements of large-scale hydrogen energy applications for an efficient, economic, and environmentally friendly storage and transportation system. In view of this, the present invention provides solutions in the following aspects.

[0006] In a first aspect of the present invention, a dynamic planning and optimization method for regional hydrogen energy storage and transportation infrastructure includes: defining system parameters of a multi-form hydrogen energy regional storage and transportation system, where the multi-form hydrogen energy includes gaseous hydrogen, liquid hydrogen, organic liquid hydrogen, and ammonia; constructing an objective function of the multi-form hydrogen energy regional storage and transportation system, where the objective function is used to minimize the total cost of multi-form hydrogen storage and transportation, including the capital cost, repair cost, operation cost, and environmental cost of the form conversion link, storage link, and transportation link; establishing constraint conditions of the multi-form hydrogen energy regional storage and transportation system, including production and operation constraints of the form conversion link, storage link, and transportation link, and supply-demand equilibrium constraints of each form of hydrogen; and using the system parameters, objective function, and constraint conditions to perform dynamic planning and optimization of regional hydrogen energy storage and transportation infrastructure.

[0007] In one embodiment, the system parameters defining the multi-modal hydrogen energy regional storage and transportation system include: basic set definition, core variable definition, non-negative decision variable definition, virtual decision variable definition, and integer decision variable definition.

[0008] In one embodiment, the objective function for constructing the multi-modal hydrogen energy regional storage and transportation system includes the capital cost, maintenance cost, operation cost, and environmental cost of the hydrogen conversion (HC), hydrogen storage (HS), and hydrogen transportation (HT) links. The specific calculation formulas are as follows:

[0009] Capital cost of the hydrogen conversion link:

[0010] CaCost HC = ∑ t∈T ∑ r∈R ∑ p∈P (CaCost t,r,p ·C new,t,r,p ) (1)

[0011] Maintenance cost of the hydrogen conversion link:

[0012] MaCost HC = ∑ t∈T ∑ r∈R ∑ p∈P (MaCost t,r,p ·C t,r,p ) (2)

[0013] Operation cost of the hydrogen conversion link:

[0014] OpCost HC = ∑ t∈T ∑ r∈R ∑ p∈P (OpCost t,r,p ·Q in,t,r,p ) (3)

[0015] Carbon emission cost of the hydrogen conversion link:

[0016] EmCost HC = ∑ t∈T ∑ r∈R ∑ p∈P (Emission t,p ·Q in,t,r,p ·CarbonPrice t,r ) (4)

[0017] Capital cost of the hydrogen storage link

[0018] CaCostHS = ∑ t∈T Σ r∈R ∑ s∈S (C new,t,r,s ·CaCost t,r,s ) (5)

[0019] Storage link maintenance cost:

[0020] MaCost HS = ∑ t∈T ∑ r∈R ∑ s∈S (C t,r,s ·MaCost t,r,s ) (6)

[0021] Storage link operation cost:

[0022] OpCost HS = ∑ t∈T ∑ r∈R ∑ s∈S (Q stored,t,r,s ·OpCost t,r,s + Q charge,t,r,s ·OpCost charge,t,r,s + Q discharge,t,r,s ·OpCos tdischarge,t,r,s ) (7)

[0023] Storage link efficiency loss cost:

[0024]

[0025] Transport link capital cost:

[0026]

[0027] Transport link maintenance cost:

[0028]

[0029] Transport link operation cost:

[0030]

[0031] Transport link carbon emission cost:

[0032]

[0033] In one embodiment, the constraints for establishing the multi - form hydrogen energy regional storage and transportation system include the following formula:

[0034] Production capacity and transfer volume constraints during the form conversion process:

[0035] Qin,t,r,p ≤C t,r,p for t∈T, p∈P, r∈R (13)

[0036] (2) Efficiency constraint in the morphological conversion process:

[0037] Q out,t,r,p = Q in,t,r,p ·Efficiency t,r,p for t∈T, p∈P, r∈R (14)

[0038] (3) Production capacity update constraint in the morphological conversion process:

[0039] C t,r,p = C t-1,r,p + C new,t,r,p - C retire,t,r,p for t∈T, p∈P, r∈R (15)

[0040] (4) Upper and lower limit constraints on newly added production capacity and retired production capacity in the morphological conversion process:

[0041] CapNewMin t,r,P ≤C new,t,r,p for t∈T, p∈P, r∈R (16)

[0042] C new,t,r,p ≤CapNewMax t,r,p for t∈T, p∈P, r∈R (17)

[0043] CapRetireMin t,r,p ≤C retire,t,r,p for t∈T, p∈P, r∈R (18)

[0044] C retire,t,r,p ≤CapRetireMax t,r,p for t∈T, p∈P, r∈R (19)

[0045] (5) Storage capacity update constraint:

[0046] C t,r,s = C t-1,r,s + C new,t,r,s - C retire,t,r,s for t∈T, s∈S, r∈R (20)

[0047] (6) Constraint on the relationship between storage capacity and actual storage volume:

[0048] CapMin t,r,s ·C t,r,s ≤Q stored,t,r,s for t∈T, s∈S, r∈R (21)

[0049] Q stored,t,r,s ≤ CapMax t,r,s · C t,r,s for all \(t\in T\), \(s\in S\), \(r\in R\) (22)

[0050] (7) New and retired storage capacity upper bound constraint:

[0051] C new,t,r,s ≤ CapNewMax t,r,s for all \(t\in T\), \(s\in S\), \(r\in R\) (23)

[0052] C retire,t,r,s ≤ CapRetireMax t,r,s for all \(t\in T\), \(s\in S\), \(r\in R\) (24)

[0053] (8) Geological resource - limited storage capacity upper bound constraint:

[0054] C t,r,s ≤ CapMax t,r,s for all \(t\in T\), \(s\in\{SCT, DOGR, AWL\}\), \(r\in R\) (25)

[0055] (9) Actual storage quantity update constraint:

[0056] Q stored,t+1,r,s = Q stored,t,r,s + Q charge,t,r,s - Q discharge,t,r,s for all \(t\in T\), \(s\in S\), \(r\in R\) (26)

[0057] (10) Constraint on the total energy release of storage methods in each region and each year**

[0058]

[0059] (11) Constraint on the pipeline transportation relationship between two locations:

[0060]

[0061] (12) Compressor station quantity update constraint:

[0062] N t,r,j = N t-1,r,j + NewN t,r,j for all \(r,j\in R\); \(j\neq r\) (29)

[0063] (13) Constraint on the relationship between compressor station quantity and transportation distance:

[0064]

[0065]

[0066] (14) Pipeline transportation capacity update constraint:

[0067]

[0068] (15) Constraint on the relationship between pipeline transportation capacity and transportation volume:

[0069]

[0070]

[0071] (16) Constraint on the relationship between pipeline transportation capacity between two places and whether pipeline transportation is carried out between the two places:

[0072]

[0073]

[0074] (17) Constraint on the relationship between the number of vehicles and transportation volume:

[0075]

[0076]

[0077]

[0078] fix represents taking the integer;

[0079] (18) Supply - demand balance constraint of gaseous hydrogen in each region and each year:

[0080] Q consume,t,r +∑ p1 Q in,t,r,p1 =Q produce,t,r +∑ p2 Q out,t,r,p2

[0081] p1∈P1, P1 = {GTHC, HGLQ, HCHS, HTAS}

[0082] p2∈P2, P2 = {HPRN, LGHG, LOHR, ACGH} (40)

[0083] (19) Supply - demand balance constraint of high - pressure hydrogen in each region and each year:

[0084]

[0085] (20) Supply - demand balance constraint of liquid hydrogen in each region and each year:

[0086]

[0087] (21) Supply - demand balance constraint of organic liquid hydrogen in each region and each year:

[0088]

[0089] (22) Ammonia supply-demand balance constraints for each year and each region:

[0090]

[0091] The second aspect of the present invention provides a dynamic planning optimization system for considering regional hydrogen energy storage and transportation infrastructure, using any of the above-mentioned dynamic planning optimization methods for considering regional hydrogen energy storage and transportation infrastructure.

[0092] The present invention realizes the overall optimization of the system by establishing mathematical models for the morphological conversion subsystem, storage subsystem, and transportation subsystem, and integrating the conversion between different forms of hydrogen energy and its costs into the optimization framework. The present invention introduces infrastructure renewal constraints, and realizes the dynamic planning optimization of storage and transportation facilities by establishing dynamic mathematical models for facility construction and decommissioning and combining the mixed-integer linear programming method. The present invention establishes a mathematical model including conversion efficiency loss, storage efficiency loss, and transportation efficiency loss, and realizes the quantitative relationship between morphological conversion efficiency and system cost by introducing efficiency loss cost. The present invention establishes a full-life cycle cost model including capital cost, operation and maintenance cost, operation cost, environmental cost, and efficiency loss cost, and minimizes the total system cost through linear programming. The present invention constructs a complete constraint system including morphological conversion constraints, storage constraints, transportation constraints, and supply-demand balance constraints to ensure that the planning scheme meets technical requirements and actual needs. Brief Description of the Drawings

[0093] By referring to the following detailed description with reference to the drawings, the above and other objects, features, and advantages of the exemplary embodiments of the present invention will become readily understandable. In the drawings, several embodiments of the present invention are shown in an exemplary rather than restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0094] Figure 1 shows an optimization planning method for a multi-form hydrogen energy regional storage and transportation system according to an embodiment of the present invention;

[0095] Figure 2 shows a structural diagram of an optimization model according to an embodiment of the present invention. Detailed Embodiments

[0096] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0097] It should be understood that the terms "first", "second", "third", "fourth", etc. in the claims, the description and the drawings of the present invention are used to distinguish different objects, rather than to describe a specific order. The terms "comprising" and "including" used in the description and claims of the present invention indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their combinations.

[0098] It should also be understood that the terms used in the description of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the description and claims of the present invention, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms. It should be further understood that the term "and / or" used in the description and claims of the present invention refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0099] As used in this specification and the claims, the term "if" can be interpreted as "when", "once", "in response to determining" or "in response to detecting" depending on the context. Similarly, the phrase "if determined" or "if [the described condition or event] is detected" can be interpreted as meaning "once determined", "in response to determining", "once [the described condition or event] is detected" or "in response to detecting [the described condition or event]" depending on the context.

[0100] The specific embodiments of the present invention will be described in detail below with reference to the drawings.

[0101] In a first aspect of the present invention, an optimization planning method for a multi-modal hydrogen energy regional storage and transportation system is provided. Figure 1 It is a schematic diagram showing the optimization planning method for a hydrogen energy regional storage and transportation system according to an embodiment of the present invention. The optimization planning method for a hydrogen energy regional storage and transportation system of the present invention includes:

[0102] Step S100: Define the system parameters of the multi-modal hydrogen energy regional storage and transportation system, where the multi-modal hydrogen energy includes gaseous hydrogen, liquid hydrogen, organic liquid hydrogen, and ammonia;

[0103] Step S200: Construct the objective function of the multi-modal hydrogen energy regional storage and transportation system, where the objective function is used to minimize the total cost of multi-modal hydrogen storage and transportation, including the capital cost, maintenance cost, operation cost, and environmental cost of the form conversion link, storage link, and transportation link;

[0104] Step S300: Establish the constraint conditions for the multi-modal hydrogen energy regional storage and transportation system, including the production and operation constraints of the form conversion link, storage link, and transportation link, as well as the supply-demand balance constraints of each form of hydrogen.

[0105] Step S400: Use the system parameters, objective function, and constraint conditions to dynamically plan and optimize the regional hydrogen energy storage and transportation infrastructure.

[0106] The present invention establishes a complete mathematical model for form conversion, storage, and transportation, realizes the collaborative optimization among various forms such as gaseous hydrogen, liquid hydrogen, organic liquid hydrogen, and ammonia, and improves the overall efficiency of the system. Specifically, it can accurately calculate the efficiency and cost of different form conversion paths; realizes the reasonable layout and scale configuration of storage and transportation facilities; and improves the overall economy of the system.

[0107] The present invention realizes the dynamic adjustment of the system scale by establishing a dynamic optimization model for facility construction and decommissioning, and improves the adaptability of the planning scheme. Specifically, it can dynamically adjust the facility scale according to demand changes; realizes the phased construction of facility investment; and reduces the system investment risk.

[0108] The present invention establishes a full-life cycle cost model including capital cost, operation and maintenance cost, operation cost, and environmental cost, and realizes the precise quantification of the system cost. Specifically, it accurately evaluates the influence of various costs; realizes the balance between economic benefits and environmental benefits; and reduces the total system cost.

[0109] The present invention ensures the feasibility of the planning scheme in engineering practice by establishing a complete constraint condition system. Specifically, it meets various technical constraint requirements; ensures the system supply-demand balance; and improves the implementability of the scheme.

[0110] In the preferred embodiment of the present invention, the above steps are specifically as follows:

[0111] Step 100: System parameter definition

[0112] (1) Basic set definition

[0113] Define the form conversion process set P: gaseous hydrogen compression (GTHC); hydrogen liquefaction (HGLQ); hydrogen chemical storage (HCHS); hydrogen to ammonia (HTAS); high-pressure hydrogen release (HPRN); liquid hydrogen gasification (LGHG); organic hydrogen release (LOHR); ammonia cracking to hydrogen (ACGH), with a total of N_p conversion processes

[0114] Define the storage method set S: high-pressure storage tank (HPHT); salt cavern (SCT); depleted oil and gas reservoir (DOGR); aquifer (AWL); liquid hydrogen storage tank (LHT); organic liquid storage tank (OLHT); liquid ammonia storage tank (AMT)

[0115] Define the transportation modes: pt represents the pipeline type, and the set of pipeline types PT: {gaseous hydrogen pipeline (H2P), liquid ammonia pipeline (AMP), organic liquid hydrogen pipeline (LHP)}; vt represents the vehicle type, and the set of vehicle types VT: {gaseous hydrogen trailer (H2GT), liquid hydrogen tanker (H2LT), liquid ammonia tanker (AMTA), organic liquid hydrogen tanker (LHOT)}

[0116] Others: gaseous hydrogen (GH); high-pressure hydrogen (HPH); liquid hydrogen (LH); organic liquid hydrogen (LOH); ammonia (AM);

[0117] r represents different regions, and R is the set of regions; t represents the time year, and T is the set of years;

[0118] (2) Definition of core variables

[0119] CaCost t,r,p Represents the capital cost per unit production capacity construction in the p conversion process in region r in year t.

[0120] MaCost t,r,p Represents the maintenance cost per unit production capacity in the p conversion process in region r in year t.

[0121] OpCost t,r,p Represents the operating cost per unit production in the p conversion process in region r in year t.

[0122] Efficiency t,r,p Represents the conversion efficiency in the p conversion process in region r in year t.

[0123] CapNewMin t,r,p Represents the minimum value of the newly added production capacity in the p conversion process in region r in year t.

[0124] CapNewMax t,r,p Represents the maximum value of the newly added production capacity in the p conversion process in region r in year t.

[0125] CapRetireMin t,r,p Represents the minimum value of the retired production capacity in the p conversion process in region r in year t.

[0126] CapRetireMax t,r,p Represents the maximum value of the retired production capacity in the p conversion process in region r in year t.

[0127] CapNewMax t,r,s Represents the maximum newly added storage capacity of the storage mode s in region r in year t.

[0128] CapRetireMax t,r,sRepresents the maximum decommissioning storage capacity of storage method s in region r in year t.

[0129] SCapMax t,r,s Represents the upper limit of the geological storage capacity of storage method s in region r in year t.

[0130] CaCost t,r,s Represents the capital cost per unit storage capacity of storage method s in region r in year t.

[0131] MaCost t,r,s Represents the maintenance cost per unit storage capacity of storage method s in region r in year t.

[0132] OpCost t,r,s Represents the operating cost per unit storage volume of storage method s in region r in year t.

[0133] Efficiency charge,t,r,s Represents the charging efficiency of storage method s in region r in year t.

[0134] Efficiency discharge,t,r,s Represents the discharging efficiency of storage method s in region r in year t.

[0135] CapMin t,r,s Represents the minimum utilization rate of storage method s in region r in year t.

[0136] CapMax t,r,s Represents the maximum utilization rate of storage method s in region r in year t.

[0137] OpCost charge,t,r,s Represents the operating cost of charging per unit storage volume of storage method s in region r in year t.

[0138] OpCost discharge,t,r,s Represents the operating cost of discharging per unit storage volume of storage method s in region r in year t.

[0139] D r,j Represents the distance from region r to region j.

[0140] Represents the unit distance cost coefficient of pipeline pt.

[0141] Represents the unit scale cost coefficient of pipeline pt.

[0142] Represents the cost coefficient of the interaction between the distance and cost of pipeline pt.

[0143] Represents the operating cost per unit distance of pipeline pt.

[0144] Represents the annual maintenance cost per unit distance of the pt pipeline.

[0145] CapMinR pt Represents the minimum utilization rate of the pt pipeline.

[0146] CapMaxR pt Represents the maximum utilization rate of the pt pipeline.

[0147] Represents the minimum transportation capacity that the pt pipeline can be built with.

[0148] Represents the maximum transportation capacity that the pt pipeline can be built with.

[0149] Represents the transportation loss rate of the pt pipeline.

[0150] Represents the single loading / unloading cost and operating cost of the vt vehicle. The operating cost includes fuel, labor, toll, etc.

[0151] Represents the annual maintenance cost of a single vt vehicle.

[0152] Represents the transportation loss rate of the vt vehicle.

[0153] VCap vt Represents the single transportation volume of the vt vehicle.

[0154] VSpeed vt Represents the speed per hour of the vt vehicle.

[0155] WHours vt Represents the working hours of the vt vehicle in a year.

[0156] Represents the price of the vt vehicle.

[0157] CT CS Represents the construction cost of a single pressurization station.

[0158] Represents the annual operating cost of a single pressurization station.

[0159] Represents the annual maintenance cost of a single pressurization station.

[0160] CDist represents the working distance of the pressurization station.

[0161] Q consume,t,r Represents the gaseous hydrogen consumption of each region in the r region in t years.

[0162] Q AMconsume,t,r represents the consumption of ammonia in region r in year t.

[0163] Q produce,t,r represents the production of gaseous hydrogen in region r in year t.

[0164] CarbonPrice t,r represents the carbon market price in region r in year t.

[0165] Price t,r represents the price of hydrogen in region r in year t

[0166] Emission p,t represents the carbon emissions per unit output of the p conversion process in year t.

[0167] represents the carbon emissions per round trip of unit transport distance of vt vehicles in year t.

[0168] represents the carbon emissions of a single pressurization station operating for one year in year t.

[0169] RHS represents the storage configuration coefficient

[0170] (3) Definition of non - negative decision variables

[0171] C t,r,p represents the production capacity of the p conversion process in region r in year t.

[0172] C new,t,r,p represents the newly built production capacity of the p conversion process in region r in year t.

[0173] C retire,t,r,p represents the retired production capacity of the p conversion process in region r in year t.

[0174] Q in,t,r,p represents the input of the p conversion process in region r in year t.

[0175] Q out,t,r,p represents the output transferred out of the p conversion process in region r in year t.

[0176] C t,r,s represents the storage capacity of storage method s in region r in year t.

[0177] C new,t,r,s represents the newly built storage capacity of storage method s in region r in year t.

[0178] C retire,t,r,s represents the retired storage capacity of storage method s in region r in year t.

[0179] Q stored,t,r,s represents the storage volume of storage method s in region r in year t

[0180] Q charge,t,r,s and Q discharge,t,r,s respectively represent the charging energy and discharging energy of the storage method s in region r in year t.

[0181] Represents the newly built transportation capacity of the pt pipeline from region r to region j in year t.

[0182] Represents the transportation capacity of the pt pipeline from region r to region j in year t.

[0183] and respectively represent the hydrogen transportation volumes using the pt pipeline and vt vehicles from region r to region j in year t.

[0184] (4) Definition of virtual decision variables

[0185] Represents whether to newly build a pt - type pipeline from region r to region j in year t. 1 indicates existence, and 0 indicates non - existence.

[0186] Represents whether there is a pt - type pipeline from region r to region j in year t. 1 indicates existence, and 0 indicates non - existence.

[0187] (5) Definition of integer decision variables

[0188] Represents the number of newly added vt vehicles for transporting hydrogen from region r to region j in year t.

[0189] Represents the number of vt vehicles for transporting hydrogen from region r to region j in year t.

[0190] Represents the number of transportation trips of vt vehicles from region r to region j in year t.

[0191] N t,r,j Represents the number of pressure stations from region r to region j in year t.

[0192] NewN t,r,j Represents the number of newly built pressure stations from region r to region j in year t.

[0193] Step 200: Construction of the objective function

[0194] The objective function is to minimize the total cost of hydrogen storage and transportation, including the hydrogen conversion link (Hydrogen Conversion, HC), the hydrogen storage link (Hydrogen Storage, HS), and the transportation link

[0195] (Hydrogen Transportation, HT)'s capital cost, maintenance cost, operating cost, and environmental cost, and the specific calculation formulas are as follows.

[0196] (1) Capital cost in the form conversion link:

[0197] CaCost HC =∑ t∈T ∑ r∈R ∑ p∈P (CaCost t,r,p ·C new,t,r,p ) (1)

[0198] (2) Maintenance cost in the form conversion link:

[0199] MaCost HC =∑ t∈T ∑ r∈R ∑ p∈P (MaCost t,r,p ·C t,r,p ) (2)

[0200] (3) Operating cost in the form conversion link:

[0201] OpCost HC =∑ t∈T ∑ r∈R ∑ p∈P (OpCost t,r,p ·Q in,t,r,p ) (3)

[0202] (4) Carbon emission cost in the form conversion link:

[0203] EmCost HC =∑ t∈T ∑ r∈R ∑ p∈P (Emission t,p ·Q in,t,r,p ·CarbonPrice t,r ) (4)

[0204] (5) Capital cost in the storage link

[0205] CaCost HS =Σ t∈T ∑ r∈R ∑ s∈S (C new,t,r,s ·CaCost t,r,s ) (5)

[0206] (6) Maintenance cost in the storage link:

[0207] MaCostHS = ∑ t∈T ∑ r∈R ∑ s∈S (C t,r,s · MaCost t,r,s ) (6)

[0208] (7) Storage link operation cost:

[0209] OpCost HS = ω t∈T ∑ e∈R ∑ s∈S (Q stored,t,r,s · OpCost t,r,s + Q charge,t,r,s · OpCost charge,t,r,s + Q discharge,t,r,s · OpCost discharge,t,r,s ) (7)

[0210] (8) Storage link efficiency loss cost:

[0211]

[0212] (9) Transportation link capital cost:

[0213]

[0214] (10) Transportation link maintenance cost:

[0215]

[0216] (11) Transportation link operation cost:

[0217]

[0218] (12) Transportation link carbon emission cost:

[0219]

[0220] Step 3: Establishment of constraint conditions

[0221] The constraint conditions include 4 parts, namely the production and operation constraints of the form conversion link, storage link and transportation link, as well as the supply - demand balance constraints of various forms of hydrogen.

[0222] (1) Production capacity and transfer volume constraints in the form conversion process:

[0223] Q in,t,r,p ≤ C t,r,p t ∈ T, p ∈ P, r ∈ R (13)

[0224] (2) Efficiency constraints in the form conversion process:

[0225] Q out,t,r,p = Q in,t,r,p · Efficiency t,r,p for t ∈ T, p ∈ P, r ∈ R (14)

[0226] (3) Production capacity update constraint during the morphological conversion process:

[0227] C t,r,p = C t-1,r,p + C new,t,r,p - C retire,t,r,p for t ∈ T, p ∈ P, r ∈ R (15)

[0228] (4) Upper and lower limit constraints for newly added production capacity and retired production capacity during the morphological conversion process:

[0229] CapNewMin t,r,P ≤ C new,t,r,p for t ∈ T, p ∈ P, r ∈ R (16)

[0230] C new,t,r,p ≤ CapNewMax t,r,p for t ∈ T, p ∈ P, r ∈ R (17)

[0231] CapRetireMin t,r,p ≤ C retire,t,r,p for t ∈ T, p ∈ P, r ∈ R (18)

[0232] C retire,t,r,p ≤ CapRetireMax t,r,p for t ∈ T, p ∈ P, r ∈ R (19)

[0233] (5) Storage capacity update constraint:

[0234] C t,r,s = C t-1,r,s + C new,t,r,s - C retire,t,e,s for t ∈ T, s ∈ S, r ∈ R (20)

[0235] (6) Constraint on the relationship between storage capacity and actual storage volume:

[0236] CapMin t,r,s · C t,r,s ≤ Q stored,t,r,s for t ∈ T, s ∈ S, r ∈ R (21)

[0237] Q stored,t,r,d ≤ CapMax t,r,s · C t,r,s for t ∈ T, s ∈ S, r ∈ R (22)

[0238] (7) Constraints on the upper limits of new and retired storage capacities:

[0239] C new,t,r,s ≤CapNewMax t,r,s for t∈T, s∈S, r∈R (23)

[0240] C retire,t,r,s ≤CapRetireMax t,r,s for t∈T, s∈S, r∈R (24)

[0241] (8) Constraints on the upper limit of storage capacity due to geological resource limitations:

[0242] C t,r,s ≤CapMax t,r,s for t∈T, s∈{SCT, DOGR, AWL}, r∈R (25)

[0243] (9) Constraints on the update of the actual storage volume:

[0244] Q stored,t+1,r,s =Q stored,t,r,s +Q charge,t,r,s -Q discharge,t,r,s for t∈T, s∈S, r∈R (26)

[0245] (10) Constraints on the total energy release of storage methods in each region and each year **

[0246]

[0247] (11) Constraints on the relationship of whether pipeline transportation is carried out between two places:

[0248]

[0249] (12) Constraints on the update of the number of booster stations:

[0250] N t,r,j =N t-1,r,j +NewN t,r,j for r,j∈R; j≠r (29)

[0251] (13) Constraints on the relationship between the number of booster stations and the transportation distance:

[0252]

[0253]

[0254] (14) Constraints on the update of pipeline transportation capacity:

[0255]

[0256] (15) Constraint on the relationship between pipeline transportation capacity and transportation volume:

[0257]

[0258]

[0259] (16) Constraint on the relationship between pipeline transportation capacity between two places and whether pipeline transportation is carried out between the two places:

[0260]

[0261]

[0262] (17) Constraint on the relationship between the number of vehicles and transportation volume:

[0263]

[0264]

[0265]

[0266] fix represents taking the integer.

[0267] (18) Constraint on the balance between supply and demand of gaseous hydrogen in each year and each region:

[0268] Q consume,t,r +∑ p1 Q in,t,r,p1 =Q produce,t,r +Σ p2 Q out,t,r,p2

[0269] p1∈P1, P1 = {GTHC, HGLQ, HCHS, HTAS}

[0270] p2∈P2, P2 = {HPRN, LGHG, LOHR, ACGH} (40)

[0271] (19) Constraint on the balance between supply and demand of high-pressure hydrogen in each year and each region:

[0272]

[0273] (20) Constraint on the balance between supply and demand of liquid hydrogen in each year and each region:

[0274]

[0275] (21) Constraint on the balance between supply and demand of organic liquid hydrogen in each year and each region:

[0276]

[0277] (22) Constraint on the balance between supply and demand of ammonia in each year and each region:

[0278]

[0279] Figure 2 Shows the optimized model structure diagram according to the present invention. As can be seen from the attached Figure 2 figures, the following are disclosed in the present invention:

[0280] 1. Unified cost optimization model for multi-modal hydrogen energy conversion. A complete cost model for the conversion link is established through formulas (1)-(4) in step 2, including capital cost, maintenance cost, operation cost, and environmental cost; the constraint relationship between conversion efficiency and production capacity is realized based on formulas (13)-(14) in step 3; a dynamic update mechanism for conversion facilities is constructed using formulas (15)-(19) in step 3.

[0281] 2. Cooperative optimization method for multi-level storage systems. A full-cost model for the storage link is established through formulas (5)-(8) in step 2; dynamic constraints on storage capacity and charging / discharging energy efficiency are realized based on formulas (20)-(26) in step 3; the dynamic balance of the storage system meeting regional demands is ensured using formula (27) in step 3.

[0282] 3. Network optimization method for multi-mode transportation systems. A cost optimization model for the transportation link is established through formulas (9)-(12) in step 2; the cooperative optimization of pipeline transportation and vehicle transportation is realized based on formulas (28)-(39) in step 3; a coupling relationship between the layout of pressurization stations and pipeline network pressure is constructed.

[0283] 4. Dynamic constraint system for regional supply-demand balance. A regional balance constraint for gaseous hydrogen is established through formula (40) in step 3, and a regional balance constraint for high-pressure hydrogen is established based on formula (41) in step 3; regional balance constraints for liquid hydrogen, organic liquid hydrogen, and ammonia are realized using formulas (42)-(44) in step 3.

[0284] The second aspect of the present invention discloses a dynamic planning optimization system for regional hydrogen energy storage and transportation infrastructure. The above-disclosed dynamic planning optimization method for regional hydrogen energy storage and transportation infrastructure is utilized. Although this specification has shown and described multiple embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided only by way of example. Those skilled in the art will think of many changes, alterations, and alternative ways without departing from the spirit and idea of the present invention. It should be understood that various alternative embodiments of the present invention described herein can be adopted in the process of practicing the present invention. The appended claims are intended to define the protection scope of the present invention and thus cover the module compositions, equivalents, or alternative solutions within the scope of these claims.

Claims

1. A dynamic planning and optimization method for regional hydrogen energy storage and transportation infrastructure, characterized in that, Including: Defining system parameters for a multi-modal hydrogen energy regional storage and transportation system, where the multi-modal hydrogen energy includes gaseous hydrogen, liquid hydrogen, organic liquid hydrogen, and ammonia; Constructing an objective function for the multi-modal hydrogen energy regional storage and transportation system, which is used to minimize the total cost of multi-modal hydrogen storage and transportation, including capital costs, maintenance costs, operating costs, and environmental costs in the form conversion link, storage link, and transportation link; Establishing constraint conditions for the multi-modal hydrogen energy regional storage and transportation system, including production and operation constraints in the form conversion link, storage link, and transportation link, as well as supply-demand balance constraints for each form of hydrogen; Using the system parameters, objective function, and constraint conditions to perform dynamic planning and optimization of regional hydrogen energy storage and transportation infrastructure.

2. The dynamic planning optimization method for regional hydrogen energy storage and transportation infrastructure according to claim 1, characterized in that The system parameters for defining the multi-modal hydrogen energy regional storage and transportation system include: Basic set definition, core variable definition, non-negative decision variable definition, virtual decision variable definition, integer decision variable definition.

3. The dynamic planning and optimization method for regional hydrogen energy storage and transportation infrastructure according to claim 1, characterized in that Constructing the objective function of the multi-modal hydrogen energy regional storage and transportation system includes capital costs, maintenance costs, operating costs, and environmental costs in the form conversion link (Hydrogen Conversion, HC), storage link (Hydrogen Storage, HS), and transportation link (Hydrogen Transportation, HT). The specific calculation formulas are as follows: Capital cost of the form conversion link: CaCost HC = ∑ t∈T ∑ r∈R ∑ p∈P (CaCost t,r,p ·C new,t,r,p ) (1) Maintenance cost of the form conversion link: MaCost HC = ∑ t∈T ∑ r∈R ∑ p∈P (MaCost t,r,p · C t,r,p ) (2) Operating cost of the form conversion link: OpCost HC = Σ t∈T Σ r∈R Σ p∈P (OpCost t,r,p · Q in,t,r,p ) (3) Carbon emission cost of the form conversion link: EmCost HC = Σ t∈T ∑ r∈R ∑ p∈P (Emission t,p ·Q in,t,r,p ·CarbonPrice t,r ) (4) Capital cost of the storage link CaCost HS = ∑ t∈T ∑ r∈R Σ s∈S (C new,t,r,s ·CaCost t,r,s ) (5) Maintenance cost of the storage link: MaCost HS = ∑ t∈T ∑ r∈R ∑ s∈S (C t,r,s ·MaCost t,r,s ) (6) Operating cost of the storage link: OpCost HS = ∑ t∈T ∑ r∈R ∑ s∈S (Q stored,t,r,s · OpCost t,r,s + Q charge,t,r,s · OpCost charge,t,r,s + Q discharge,t,r,s · OpCost discharge,t,r,s ) (7) Efficiency loss cost of the storage link: Capital cost of the transportation link: Maintenance cost of the transportation link: Operating cost of the transportation link: Carbon emission cost of the transportation link:

4. The dynamic planning optimization method for hydrogen energy storage and transportation infrastructure in the considered area according to claim 1, characterized in that The constraint conditions established for the multi-modal hydrogen energy regional storage and transportation system include the following formulas: Constraint on production capacity and transferred quantity during the form conversion process: Q in,t,r,p ≤C t,r,p for t ∈ T, p ∈ P, r ∈ R (13) (2) Efficiency constraint during the form conversion process: Q out,t,r,p = Q in,t,r,p · Efficiency t,r,p for t ∈ T, p ∈ P, r ∈ R (14) (3) Constraint on production capacity update during the form conversion process: C t,r,p = C t-1,r,p + C new,t,r,p - C retire,t,r,p where \(t\in T\), \(p\in P\), \(r\in R\) (15) (4) Upper and lower limit constraints on newly added production capacity and retired production capacity during the form conversion process: CapNewMin t,r,p ≤C new,t,r,p for all t ∈ T, p ∈ P, r ∈ R (16) C new,t,r,p ≤CapNewMax t,r,p for all t ∈ T, p ∈ P, r ∈ R (17) CapRetireMin t,r,p ≤C retire,t,r,p for all t ∈ T, p ∈ P, r ∈ R (18) C retire,t,r,p ≤ Maximum Retirement Capital t,r,p for all t in T, p in P, r in R (19) (5) Constraint on storage capacity update: C t,r,s = C t-1,r,s + C new,t,r,s - C retire,t,r,s for t ∈ T, s ∈ S, r ∈ R (20) (6) Constraint on the relationship between storage capacity and actual storage quantity: CapMin t,r,s ·°C t,r,s ≤Q stored,t,r,s for t ∈ T, s ∈ S, r ∈ R (21) Q stored,t,r,s ≤ CapMax t,r,s ·C t,r,s for t ∈ T, s ∈ S, r ∈ R (22) (7) Upper limit constraint on newly added and retired storage capacity: C new,t,r,s ≤ CapNewMax t,r,s for all t ∈ T, s ∈ S, r ∈ R (23)C retire,t,r,s ≤ CapRetireMax t,r,s for all t ∈ T, s ∈ S, r ∈ R (24) (8) Upper limit constraint on geological resource-limited storage capacity: C t,r,s ≤ CapMax t,r,s where \(t\in T\), \(S\in\{SCT, DOGR, AWL\}\), \(r\in R\) (25) (9) Constraint on actual storage quantity update: Q stored,t+1,r,s = Q stored,t,r,s + Q charge,t,r,s - Q discharge,t,r,s t ∈ T, s ∈ S, r ∈ R (26) (10) Constraint on the total energy release of storage methods in each region and each year** (11) Constraint on the relationship of whether pipeline transportation is carried out between two places: (12) Constraint on the update of the number of pressurization stations: N t,r,j = N t-1,r,j + NewN t,r,j r, j ∈ R; j ≠ r (29) (13) Constraint on the relationship between the number of pressurization stations and the transportation distance: (14) Constraint on the update of pipeline transportation capacity: (15) Constraint on the relationship between pipeline transportation capacity and transportation volume: (16) Constraint on the relationship between pipeline transportation capacity between two places and whether pipeline transportation is carried out between two places: (17) Constraint on the relationship between the number of vehicles and transportation volume: fix represents taking an integer; (18) Constraint on the supply-demand balance of gaseous hydrogen in each region and each year: Q consume,t,r +∑ p1 Q in,t,r,p1 =Q produce,t,r +∑ p2 Q out,t,r,p2 p1 ∈ P1, P1 = {GTHC, HGLQ, HCHS, HTAS} p2 ∈ P2, P2 = {HPRN, LGHG, LOHR, ACGH} (40) (19) Constraint on the supply-demand balance of high-pressure hydrogen in each region and each year: (20)Liquid hydrogen supply and demand balance constraints for each year and each region: (21)Supply and demand balance constraints for organic liquid hydrogen for each year and each region: (22)Supply and demand balance constraints for ammonia for each year and each region:

5. A dynamic programming optimization system for regional hydrogen energy storage and transportation infrastructure, characterized in that, Use the dynamic programming optimization method for regional hydrogen energy storage and transportation infrastructure as described in any one of claims 1-4.

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