Energy system construction method and system including hydrogen energy router in multiple scenarios

Abstract

This invention discloses a method and system for constructing an energy system including a hydrogen energy router under multiple scenarios. This method, pertaining to the field of electrical engineering, includes: utilizing an energy hub matrix modeling method to establish an input-output correlation matrix for the energy system including the hydrogen energy router, and linearizing the input-output correlation matrix; establishing an optimization model based on the goal of minimizing the sum of the energy system's investment and construction costs and its operating costs, combining equipment capacity constraints, input-output constraints defined by the linearized input-output correlation matrix, operational constraints for electricity, oxygen, and hydrogen storage, and energy conversion capacity constraints; and solving the optimization model to determine the topological structure and capacity of the energy system under different scenarios in the upper, middle, and lower reaches of a river basin. This method, based on multiple scenarios, provides a standard structural design paradigm for an energy-quality coupling system that integrates multiple renewable energy inputs with multiple energy-carrying chemicals for output.

Description

Technical Field

[0001] The present invention belongs to the field of electrical engineering, and more specifically, relates to a method and system for constructing an energy system including a hydrogen energy router in multiple scenarios. Background Art

[0002] The high-quality development of renewable energy is a pressing need for low-carbon energy transition, climate governance, and environmental protection. Hydrogen, with its high energy density and flexible conversion, is recognized as an ideal secondary energy source. Chemical production requires over 30 million tons of hydrogen annually, currently primarily derived from the decomposition of fossil fuels. To achieve decarbonization in chemical production, the comprehensive adoption of green hydrogen is necessary. Green hydrogen chemistry is a new type of productive force supporting the low-carbon transition of the energy and chemical industries.

[0003] Green hydrogen chemical industry provides a new approach to the high-quality development of renewable energy, and at the same time realizes zero-carbonization of fuels in the field of energy consumption, which has broad application prospects. However, how to flexibly and efficiently convert hydropower, wind power, and solar power into hydrogen, and further synthesize energy-carrying chemicals such as methanol, methane, and ammonia, still faces many challenges. Previous research on electric-hydrogen coupling systems has mainly focused on the energy balance of electricity-hydrogen conversion, but there are still deficiencies in the research on the mass-energy balance matching of the "electricity-green hydrogen-chemical" coupling system. The current structural design is only for a single scenario, and lacks a flexible topology design process and method for coupling systems that can adapt to multiple scenarios, which is in urgent need of improvement. Summary of the Invention

[0004] In response to the defects of the existing technology and the need for improvement, the present invention provides a method and system for constructing an energy system including a hydrogen energy router in multiple scenarios. Its purpose is to reduce the energy storage buffer demand of the coupled electric hydrogen production section and the chemical synthesis section, improve the conversion efficiency of electricity-hydrogen-energy-carrying chemicals, and enrich the application scenarios of the electricity-hydrogen-energy-carrying chemicals coupling system.

[0005] To achieve the above-mentioned objectives, according to one aspect of the present invention, a method for constructing an energy system including a hydrogen energy router in multiple scenarios is provided, including: using the energy hub matrix modeling method to establish an input-output correlation matrix for the energy system including the hydrogen energy router, and linearizing the input-output correlation matrix; with the goal of minimizing the sum of the investment and construction cost and the operating cost of the energy system, an optimization model is established in combination with equipment capacity constraints, input and output constraints defined by the linearized input-output correlation matrix, electricity, oxygen, and hydrogen storage operation constraints, and energy conversion capacity constraints; solving the optimization model to obtain the topological structure and capacity of the energy system in different scenarios in the upper, middle, and lower reaches of the basin.

[0006] Furthermore, the energy hub matrix modeling method is used to establish an input-output association matrix for the energy system including the hydrogen energy router, specifically including: searching all branches in the energy system; for each branch, if the starting sequence and the ending sequence of the branch are not adjacent, adding a virtual node at the missing node between the starting sequence and the ending sequence; splitting the energy system into multiple energy routers, and constructing a topological association matrix for each of the energy routers according to the energy conversion and node sequence in the energy system after adding the virtual node, so as to form the input-output association matrix.

[0007] Furthermore, the energy system is divided into N energy routers, where N ≥ 3; the input-output equation of the first energy router is:

[0008] L1=C1P input

[0009] The input-output equation of the nth energy router is:

[0010] L n =C n L n-1

[0011] The input-output equation of the Nth energy router is:

[0012] L out =C N L N-1

[0013] Where n = 2, 3, ..., N-1, L1 is the output of the first energy router, L n , L n-1 , L N-1 are the outputs of the nth, n-1th, and N-1th energy routers respectively. C1 is the topological association matrix of the first energy router. n 、C N are the topological association matrices of the nth and Nth energy routers, P input is the input of the energy system, L out is the output of the energy system.

[0014] Furthermore, the input-output correlation matrix is:

[0015] C total =C N ×C N-1 ...×C1

[0016] Among them, C total is the input-output association matrix.

[0017] Furthermore, the investment and construction cost is:

[0018]

[0019] κ=r(1+r) n / ((1+r) n -1)

[0020] Among them, F inv is the investment and construction cost, κ is the annual cost conversion coefficient, z WE 、z BG 、z ES 、z OS 、z HS 、z PSA 、z CCU 、z AS 、z SML 、z SM 、z SA 0-1 variables indicating whether a water electrolysis device, biomass gasification device, power storage device, oxygen storage device, hydrogen storage device, pressure swing adsorption device, carbon capture device, air separation device, methanol synthesis device, methane synthesis device, and ammonia synthesis device are installed. The unit capacity investment costs of water electrolysis device, biomass gasification device, electricity storage device, oxygen storage device, hydrogen storage device, pressure swing adsorption device, carbon capture device, air separation device, methanol synthesis device, methane synthesis device, and ammonia synthesis device are respectively, c WE 、c BG 、c ES 、c OS 、c HS 、c PSA 、c CCU 、c AS 、c SML 、c SM 、c SA They are the planned capacities of water electrolysis device, biomass gasification device, electricity storage device, oxygen storage device, hydrogen storage device, pressure swing adsorption device, carbon capture device, air separation device, synthetic methanol device, synthetic methane device, and synthetic ammonia device, r is the interest rate, and n is the investment recovery period.

[0021] Furthermore, the operating cost is:

[0022] F ope =F main +F raw

[0023]

[0024]

[0025]

[0026] Among them, F ope is the operating cost, F main is the operation and maintenance cost, F raw is the raw material cost, ν is the number of days in a year, s is the scenario, t is the time, ω(s) is the probability of scenario s, They are the unit operation and maintenance costs of photovoltaic, hydropower, wind power, water electrolysis device, biomass gasification device, power storage device, oxygen storage device, hydrogen storage device, pressure swing adsorption device, carbon capture device, air separation device, synthetic methanol device, synthetic methane device, and synthetic ammonia device. are the photovoltaic output, hydropower output, and wind power output at time t under scenario s, is the electric power consumed by the water electrolysis device at time t in scenario s, are the energy storage charging and discharging power at time t under scenario s, are the charging and discharging flow rates of the oxygen storage device at time t under scenario s, are the charging and discharging flow rates of the hydrogen storage device at time t under scenario s, are the prices of biomass, nitrogen, and carbon dioxide at time t under scenario s, are the electric power consumed by the pressure swing adsorption unit, methanol synthesis unit, methane synthesis unit, and ammonia synthesis unit at time t under scenario s, are the prices of biomass, nitrogen, and carbon dioxide per unit at time t in scenario s, respectively.

[0027] Furthermore, the electricity storage, oxygen storage, and hydrogen storage operation constraints include: electricity storage operation constraints:

[0028]

[0029]

[0030]

[0031]

[0032]

[0033]

[0034] Oxygen storage operation constraints:

[0035]

[0036]

[0037]

[0038]

[0039]

[0040]

[0041] Hydrogen storage operation constraints:

[0042]

[0043]

[0044]

[0045]

[0046]

[0047]

[0048] in, is the capacity of the power storage device at time t under scenario s, η ES_in ,η ES_out are the energy storage charging and discharging efficiency, are the energy storage charging and discharging power at time t under scenario s, Configure the capacity of the storage device under scenario s, are the capacities of the storage device at the initial and final moments under scenario s, is the change in energy storage power at time t under scenario s, ε ES is the storage and discharge power coefficient, is the capacity of the oxygen storage device at time t under scenario s, are the charging and discharging flow rates of the oxygen storage device at time t under scenario s, k2 is the unit conversion coefficient, Δt is the time interval, Configure the capacity of the oxygen storage device under scenario s, are the capacities of the oxygen storage device at the initial and final moments under scenario s, is the change in oxygen storage at time t under scenario s, ε OS is the oxygen storage and release power coefficient, is the capacity of the hydrogen storage device at time t under scenario s, The charging and discharging flow rates of the hydrogen storage device at time t under scenario s are respectively Configure the capacity of the hydrogen storage device under scenario s, are the capacities of the hydrogen storage device at the initial and final moments under scenario s, is the change in hydrogen storage at time t under scenario s, ε HSis the hydrogen storage and release power coefficient.

[0049] According to another aspect of the present invention, a system for constructing an energy system including a hydrogen energy router in multiple scenarios is provided, comprising: a processor; and a memory storing a computer executable program, which, when executed by the processor, enables the processor to execute the method for constructing an energy system including a hydrogen energy router in multiple scenarios as described above.

[0050] According to another aspect of the present invention, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, the method for constructing an energy system including a hydrogen energy router in multiple scenarios as described above is implemented.

[0051] In general, the above technical solutions conceived by the present invention can achieve the following beneficial effects: a method for constructing an energy system including a hydrogen energy router in multiple scenarios is provided, and an input-output correlation matrix is ​​established for the energy system including the hydrogen energy router using the energy hub matrix modeling method. When establishing the optimization objectives and optimization constraints, the data in different scenarios in the upper, middle and lower reaches of the river basin are taken into account. Therefore, the final designed topology can provide a standard design paradigm for an energy-quality coupling system with multiple renewable energy inputs and multiple energy-carrying chemicals outputs, which can reduce the system's demand for energy storage devices, and through the complementary use of oxygen, improve the system's energy conversion efficiency, and support the large-scale application of green hydrogen chemical industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A flowchart of a method for constructing an energy system including a hydrogen energy router in multiple scenarios provided by an embodiment of the present invention;

[0053] Figure 2 A diagram showing the steps for modeling the standardized topology of a hydrogen energy router in an energy system according to an embodiment of the present invention;

[0054] Figure 3 An energy system structure diagram of a hydrogen energy router provided in an embodiment of the present invention;

[0055] Figure 4 This is a system diagram after arranging the order of real nodes and virtual nodes provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0056] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the present invention and are not intended to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.

[0057] In the present invention, the terms "first", "second", etc. (if any) in the present invention and the drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0058] Example 1

[0059] A method for constructing an energy system including a hydrogen energy router in multiple scenarios. Figures 1-4 , a method for constructing an energy system including a hydrogen energy router in multiple scenarios in this embodiment is described in detail, the method includes operations S1-S3, such as Figure 1 shown.

[0060] Operation S1, using the energy hub matrix modeling method, establishes an input-output correlation matrix for the energy system including the hydrogen energy router, and linearizes the input-output correlation matrix.

[0061] According to an embodiment of the present invention, an energy hub matrix modeling method is used to establish an input-output association matrix for an energy system including a hydrogen energy router, specifically including the following sub-operations S11 to S13.

[0062] In sub-operation S11 , all branches in the energy system are searched.

[0063] In sub-operation S12, for each branch, if the starting sequence and the ending sequence of the branch are not adjacent, a virtual node is added at the node missing between the starting sequence and the ending sequence.

[0064] In sub-operation S13, the energy system is split into multiple energy routers, and a topological association matrix is ​​constructed for each energy router according to energy conversion and node sequence in the energy system after adding virtual nodes to form an input-output association matrix.

[0065] Specifically, the energy system is divided into N energy routers, N ≥ 3. The input-output equation of the first energy router is:

[0066] L1=C1P input

[0067] The input-output equation of the nth energy router is:

[0068] L n =C n L n-1

[0069] The input-output equation of the Nth energy router is:

[0070] L out =C N L N-1

[0071] Where n = 2, 3, ..., N-1, L1 is the output of the first energy router, L n , L n-1 , L N-1 are the outputs of the nth, n-1th, and N-1th energy routers respectively. C1 is the topological association matrix of the first energy router. n 、C N are the topological association matrices of the nth and Nth energy routers, P input is the input of the energy system, L out The output of the energy system.

[0072] The input-output correlation matrix is:

[0073] C total =C N ×C N-1 ...×C1

[0074] Among them, C total is the input-output correlation matrix.

[0075] The specific process of establishing the input-output correlation matrix is ​​as follows Figure 2 As shown. First, search each branch in the energy system of the hydrogen energy router to find the starting sequence (sequence M) and the ending sequence (sequence N) of the branch; check whether the starting and ending node sequences of each branch are adjacent. If not, add virtual nodes at the missing locations. Specifically, if NM>1, insert (NM-1) virtual nodes in the branch until all branches are modified. Secondly, draw a directed graph to arrange the order of energy conversion and aggregation points in the energy system of the hydrogen energy router. Finally, split the energy system of the hydrogen energy router into multiple energy routers, define the topological association matrix of each energy router, and then obtain the input-output association matrix of the entire energy system.

[0076] by Figure 3 The energy system shown in Figure 1 is used as an example to illustrate the modeling process of the input-output correlation matrix. The energy system model includes photovoltaic (PV), wind power (WT), hydropower (HP), water electrolysis (WE), biomass gasification (BG), pressure swing adsorption (PSA), electricity storage (ES), oxygen storage (OS), hydrogen storage (HS), carbon capture unit (CCU), air separation unit (AS), synthetic methanol unit (SML), synthetic methane unit (SM), and synthetic ammonia unit (SA).

[0077] according to Figure 3 After adding virtual nodes and arranging the order of real nodes and virtual nodes, Figure 4 As shown. Figure 4It can be seen from the figure that the energy storage is negative and positive in the charging and discharging modes respectively, and can be regarded as additional input energy. The node order of the energy system containing the hydrogen energy router is as follows: Figure 4 shown. Figure 4 In the example, V1-V54 are virtual nodes, and their efficiency is 1. In addition, the total sequence number of the energy system is 10.

[0078] After arranging the order of the different nodes, the energy system model containing the hydrogen energy router is converted into 10 energy router models. Within each energy router model, there is no coupling between the nodes. Therefore, the input and output equations of these 10 energy router models can be easily listed and converted into linear models using the variable substitution method. The correlation matrix is ​​constructed as follows.

[0079] The input-output equations of the first energy router model are:

[0080] L1=C1P input

[0081]

[0082] Among them, L m correspond Figure 4 The output at m, such as L 10 correspond Figure 4 Output at 10; P HP 、P PV 、P WT 、P ES They are the input power of hydropower, photovoltaic power, wind power and storage power; N OS 、N HS are the flow rates of oxygen storage and hydrogen storage input systems respectively.

[0083] The input-output equations of the second energy router model are:

[0084] L2=C2L1

[0085]

[0086] Among them, x1, x2, ...., x7 are the dispatching factors of D2 respectively, and D2 is the electrical bus.

[0087] The input-output equations of the third energy router model are:

[0088] L3=C3L2

[0089]

[0090] in, are the coefficients of hydrogen and oxygen production by water electrolysis; η CCUis the power consumption coefficient of the carbon capture device; are the correlation coefficients of oxygen and nitrogen obtained from the air separation unit and power consumption.

[0091] The input-output equations of the fourth energy router model are:

[0092] L4=C4L3

[0093]

[0094] Among them, x8 and x9 are the dispatch factors of D4 respectively, and D4 is the carbon dioxide bus.

[0095] The input-output equations of the fifth energy router model are:

[0096] L5=C5L4

[0097]

[0098] Among them, η BG is the hydrogen production coefficient of the biomass gasification device.

[0099] The input-output equations of the sixth energy router model are:

[0100] L6=C6L5

[0101]

[0102] Among them, η PSA_E 、 They are the power consumption coefficient and adsorption efficiency of the pressure swing adsorption device respectively. The input-output equation of the seventh energy router model is:

[0103] L7=C7L6

[0104]

[0105] The input-output equations of the 8th energy router model are:

[0106] L8=C8L7

[0107]

[0108] The input-output equations of the 9th energy router model are:

[0109] L9=C9L8

[0110]

[0111] The input-output equations of the 10th energy router model are:

[0112] Lout =C 10 L9

[0113]

[0114] Therefore, the correlation matrix of the entire energy system can be expressed as follows:

[0115] L out =C total P input

[0116] C total =C 10 ×C9×C8...×C1

[0117] The input-output correlation matrix established above is nonlinear, which makes calculations difficult. Therefore, the input-output correlation matrix is ​​linearized to facilitate the construction of the mixed integer linear optimization model later.

[0118] Still Figure 3 and Figure 4 Taking the energy system shown in the figure as an example, the linearization of the correlation matrix of the 2nd, 4th, and 9th energy router models is performed as follows:

[0119] x1+x2+x3+x4+x5+x6+x7=1

[0120] 0≤x1,x2,x3,x4,x5,x6,x7≤1

[0121]

[0122]

[0123]

[0124]

[0125]

[0126]

[0127]

[0128]

[0129]

[0130]

[0131]

[0132]

[0133]

[0134]

[0135]

[0136]

[0137]

[0138] 0≤x8,x9≤1

[0139]

[0140]

[0141]

[0142]

[0143]

[0144]

[0145] x 10 +x 11 +x 12 +x 13 =1

[0146] 0≤x 10 ,x 11 ,x 12 ,x 13 ≤1

[0147]

[0148]

[0149]

[0150]

[0151]

[0152]

[0153]

[0154]

[0155]

[0156]

[0157] Operation S2 aims to minimize the sum of the investment and construction costs and the operating costs of the energy system, and establishes an optimization model by combining equipment capacity constraints, input and output constraints defined by the linearized input-output correlation matrix, electricity, oxygen, and hydrogen storage operation constraints, and energy conversion capacity constraints.

[0158] Before executing operation S2, it is necessary to collect water, wind, and light resource data and electricity, hydrogen, and chemical demand data for different scenarios in the upper, middle, and lower reaches of the basin, and process and analyze the collected data for subsequent establishment of an optimization model.

[0159] Wind and solar resource data acquisition: Based on the wind speed, irradiance, temperature, and other data obtained at the research site, wind speed-power and irradiance-power physical models were established to simulate wind power and photovoltaic output power, which served as input to the optimization model. Furthermore, when conducting short-term optimization scheduling studies, it is difficult to analyze the long series of wind and solar output generated by direct simulation one by one. Therefore, scenario reduction technology was used to select representative typical daily output scenarios.

[0160] Acquisition of hydropower station data: Through planning data or cooperation, collect the installed capacity and main operating parameters of hydropower stations that have been built and are to be planned in different regions of the basin.

[0161] The objective function of the optimization model is:

[0162] minF inv +F ope

[0163] Investment and construction cost F inv for:

[0164]

[0165] Among them, κ is the annual cost conversion coefficient, z WE 、z BG 、z ES 、z OS 、z HS 、z PSA 、z CCU 、z AS 、z SML 、z SM 、z SA 0-1 variables indicating whether a water electrolysis device, biomass gasification device, power storage device, oxygen storage device, hydrogen storage device, pressure swing adsorption device, carbon capture device, air separation device, methanol synthesis device, methane synthesis device, and ammonia synthesis device are installed. The unit capacity investment costs of water electrolysis device, biomass gasification device, electricity storage device, oxygen storage device, hydrogen storage device, pressure swing adsorption device, carbon capture device, air separation device, methanol synthesis device, methane synthesis device, and ammonia synthesis device are respectively, c WE 、c BG 、c ES 、c OS 、c HS 、c PSA 、c CCU 、c AS 、c SML 、c SM 、c SA They are the planned capacities of water electrolysis device, biomass gasification device, electricity storage device, oxygen storage device, hydrogen storage device, pressure swing adsorption device, carbon capture device, air separation device, synthetic methanol device, synthetic methane device, and synthetic ammonia device, r is the interest rate, and n is the investment recovery period.

[0166] Running cost F ope for:

[0167] F ope =F main +F raw

[0168]

[0169]

[0170]

[0171] Among them, F main is the operation and maintenance cost, F raw is the raw material cost, ν is the number of days in a year, s is the scenario, t is the time, ω(s) is the probability of scenario s, They are the unit operation and maintenance costs of photovoltaic, hydropower, wind power, water electrolysis device, biomass gasification device, power storage device, oxygen storage device, hydrogen storage device, pressure swing adsorption device, carbon capture device, air separation device, synthetic methanol device, synthetic methane device, and synthetic ammonia device. are the photovoltaic output, hydropower output, and wind power output at time t under scenario s, is the electric power consumed by the water electrolysis device at time t in scenario s, are the energy storage charging and discharging power at time t under scenario s, are the charging and discharging flow rates of the oxygen storage device at time t under scenario s, are the charging and discharging flow rates of the hydrogen storage device at time t under scenario s, are the prices of biomass, nitrogen, and carbon dioxide at time t under scenario s, are the electric power consumed by the pressure swing adsorption unit, methanol synthesis unit, methane synthesis unit, and ammonia synthesis unit at time t under scenario s, are the prices of biomass, nitrogen, and carbon dioxide per unit at time t in scenario s, respectively.

[0172] The equipment capacity constraint is:

[0173] z WE c WE_min ≤c WE ≤z WE c WE_max

[0174] z BG c BG_min ≤c BG ≤z BG c BG_max

[0175] z ES c ES w min ≤c ES ≤z ES c ES_max

[0176] z OS c OS_min ≤c OS ≤z OS c OS_max

[0177] z HS c HS_min ≤c HS ≤z HS c HS_max

[0178] z PSA c PSA_min ≤c PSA ≤z PSA c PSA_max

[0179] z CCU c CCU_min ≤c CCU ≤z CCU c CCU_max

[0180] z AS c AS_min ≤c AS ≤z AS c AS_max

[0181] z SML c SML_min ≤c SML ≤zSML c SML_max

[0182] z SM c SM_min ≤c SM ≤z SM c SM_max

[0183] z SA c SA_min ≤c SA ≤z SA c SA_max

[0184] Among them, c X_min 、c X_max Configure the minimum and maximum capacity for device X respectively, where X is WE, BG, ES, OS, HS, PSA, CCU, AS, SML, SM, or SA.

[0185] The electricity, oxygen and hydrogen storage operation constraints include: electricity storage operation constraints, oxygen storage operation constraints and hydrogen storage operation constraints.

[0186] The operation constraints of power storage are:

[0187]

[0188]

[0189]

[0190]

[0191]

[0192]

[0193] The oxygen storage operation constraints are:

[0194]

[0195]

[0196]

[0197]

[0198]

[0199]

[0200] The hydrogen storage operation constraints are:

[0201]

[0202]

[0203]

[0204]

[0205]

[0206]

[0207] in, is the capacity of the power storage device at time t under scenario s, η ES_in ,η ES_out are the energy storage charging and discharging efficiency, are the energy storage charging and discharging power at time t under scenario s, Configure the capacity of the storage device under scenario s, are the capacities of the storage device at the initial and final moments under scenario s, is the change in energy storage power at time t under scenario s, ε ES is the storage and discharge power coefficient, is the capacity of the oxygen storage device at time t under scenario s, are the charging and discharging flow rates of the oxygen storage device at time t under scenario s, k2 is the unit conversion coefficient, Δt is the time interval, Configure the capacity of the oxygen storage device under scenario s, are the capacities of the oxygen storage device at the initial and final moments under scenario s, is the change in oxygen storage at time t under scenario s, ε OS is the oxygen storage and release power coefficient, is the capacity of the hydrogen storage device at time t under scenario s, The charging and discharging flow rates of the hydrogen storage device at time t under scenario s are respectively Configure the capacity of the hydrogen storage device under scenario s, are the capacities of the hydrogen storage device at the initial and final moments under scenario s, is the change in hydrogen storage at time t under scenario s, ε HS is the hydrogen storage and release power coefficient.

[0208] The energy conversion capacity constraint is:

[0209]

[0210]

[0211]

[0212]

[0213]

[0214]

[0215]

[0216]

[0217] in, is the electric power consumed by the water electrolysis device at time t in scenario s, is the material flow rate entering the pressure swing adsorption device, is the methanol demand at time t under scenario s, is the methane demand at time t under scenario s, is the demand for synthetic ammonia at time t under scenario s.

[0218] In operation S3, the optimization model is solved to obtain the topological structure and capacity of the energy system under different scenarios in the upper, middle and lower reaches of the basin.

[0219] Specifically, for example, the optimization model is solved using the commercial software GUROBI based on the MATLAB platform to obtain the topological structure and capacity of the energy system in different scenarios in the upper, middle and lower reaches of the basin, so as to build the energy system based on the obtained topological structure and capacity.

[0220] Taking the scenario of the lower reaches of the Yalong River Basin in 2035 as an example, the topology construction and capacity configuration of the energy system are carried out. Table 1 shows the investment parameters of each device. The maximum planned capacity of the water electrolysis device, biomass gasification device, power storage device, oxygen storage device, hydrogen storage device, pressure swing adsorption device, carbon capture device, air separation device, synthetic methanol device, synthetic methane device, and synthetic ammonia device are 5000MW, 600000kg / h, 2000MWh, and 100000Nm respectively. 3 , 800000Nm 3 , 900000Nm 3 / h、5000000Nm 3 / h、3000000Nm 3 / h、1000000Nm 3 / h、4000000Nm 3 / h、3000000Nm 3 / h.

[0221] Table 1

[0222] Device invest Device invest electrolyzed water 615000$ / MW Carbon capture device 60$ / ton Biomass gasification 7789$ / kg / h Air separation unit <![CDATA[2000$ / m 3 ]]> Energy Storage 232160$ / MWh Synthetic methanol unit 800$ / ton Oxygen storage <![CDATA[200$ / m 3 ]]> Synthetic methane unit 1000$ / ton gas storage <![CDATA[167$ / m 3 ]]> Ammonia synthesis unit 1200$ / ton Pressure Swing Adsorption <![CDATA[500$ / m 3 ]]> — —

[0223] Taking the Yalong River Basin as an example, the development of wind and solar power in the Yalong River Basin is still in its infancy. At present, only a few pilot projects have been built in the lower reaches of the Yalong River. The measured data of wind and solar power are not sufficient to support the research on the multi-energy complementary operation mode. Therefore, this embodiment will obtain numerical simulation data of wind and solar power through a data platform with high recognition in the industry (Xihe Big Data Platform), and conduct research on multi-energy complementarity in the basin based on this.

[0224] Data acquisition of hydropower stations: According to the Yalong River Basin planning data, the upper reaches have been planned to have Wenbosi (installed capacity 60,000 kilowatts), Munenda (installed capacity 220,000 kilowatts), Geni (installed capacity 220,000 kilowatts), Muluo (installed capacity 160,000 kilowatts), Renda (installed capacity 400,000 kilowatts), Linda (installed capacity 144,000 kilowatts), Le'an (installed capacity 99,000 kilowatts), Xinlong (installed capacity 220,000 kilowatts), Gongke (installed capacity 400,000 kilowatts), Jiaxi (installed capacity 360,000 kilowatts), a total of 10 cascade hydropower stations with a total output of 2.283 million kilowatts; the middle reaches have been planned to have Lianghekou (installed capacity 3 million kilowatts), Yagen I (installed capacity 3 million kilowatts), and Yagen II (installed capacity 3 million kilowatts). The Yalong River downstream project includes six cascade hydropower stations, including the Jinping I (3.6 million kilowatts), Jinping II (4.8 million kilowatts), Guandi (2.4 million kilowatts), Ertan (3.3 million kilowatts), and Tongzilin (600,000 kilowatts), with a total output of 14.7 million kilowatts. This method was used to determine the structure and configuration of the downstream Yalong River scenario.

[0225] Example 2

[0226] A system for constructing an energy system in multiple scenarios, including a hydrogen energy router, includes: a processor; and a memory storing a computer-executable program. When executed by the processor, the program causes the processor to execute the method for constructing an energy system in multiple scenarios, including a hydrogen energy router. The related technical solutions are the same as those in Example 1 and will not be repeated here.

[0227] Example 3

[0228] A computer-readable storage medium stores a computer program that, when executed by a processor, implements the aforementioned method for constructing an energy system including a hydrogen energy router in multiple scenarios. The related technical solutions are the same as those in Example 1 and will not be described in detail here.

[0229] It will be easily understood by those skilled in the art that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for constructing an energy system including a hydrogen energy router in multiple scenarios, characterized in that: include: Using the energy hub matrix modeling method, an input-output correlation matrix is ​​established for the energy system including the hydrogen energy router, and the input-output correlation matrix is ​​linearized; An optimization model is established with the goal of minimizing the sum of the investment and construction costs and the operating costs of the energy system, combining equipment capacity constraints, input and output constraints defined by a linearized input-output correlation matrix, operational constraints for electricity, oxygen, and hydrogen storage, and energy conversion capacity constraints. Solving the optimization model to obtain the topological structure and capacity of the energy system under different scenarios in the upper, middle and lower reaches of the basin; The electricity, oxygen and hydrogen storage operation constraints include: Power storage operation constraints: Oxygen storage operation constraints: Hydrogen storage operation constraints: in, is the capacity of the storage device at time t under scenario s, 、 are the energy storage charging and discharging efficiency, 、 are the energy storage charging and discharging power at time t under scenario s, Configure the capacity of the storage device under scenario s, 、 are the capacities of the storage device at the initial and final moments under scenario s, is the change in energy storage power at time t under scenario s, is the storage and discharge power coefficient, is the capacity of the oxygen storage device at time t under scenario s, 、 are the charging and discharging flow rates of the oxygen storage device at time t under scenario s, is the unit conversion factor, is the time interval, Configure the capacity of the oxygen storage device under scenario s, 、 are the capacities of the oxygen storage device at the initial and final moments under scenario s, is the change in oxygen storage at time t under scenario s, is the oxygen storage and release power coefficient, is the capacity of the hydrogen storage device at time t under scenario s, 、 The charging and discharging flow rates of the hydrogen storage device at time t under scenario s are respectively Configure the capacity of the hydrogen storage device under scenario s, 、 are the capacities of the hydrogen storage device at the initial and final moments under scenario s, is the change in hydrogen storage at time t under scenario s, is the hydrogen storage and release power coefficient.

2. The method for constructing an energy system including a hydrogen energy router in multiple scenarios according to claim 1, characterized in that: The energy hub matrix modeling method is used to establish an input-output correlation matrix for the energy system including the hydrogen energy router, specifically including: Search all branches in the energy system; For each branch, if the starting sequence and the ending sequence of the branch are not adjacent, a virtual node is added at the missing node between the starting sequence and the ending sequence; The energy system is split into a plurality of energy routers, and a topological association matrix is ​​constructed for each of the energy routers according to energy conversion and node sequence in the energy system after adding virtual nodes, so as to form the input-output association matrix.

3. The method for constructing an energy system including a hydrogen energy router in multiple scenarios according to claim 2, characterized in that: Splitting the energy system into N energy routers, where N ≥ 3; The input-output equation of the first energy router is: The input-output equation of the nth energy router is: The input-output equation of the Nth energy router is: Where n=2, 3, ..., N-1, is the output of the first energy router, 、 、 are the outputs of the nth, n-1th, and N-1th energy routers respectively, is the topological association matrix of the first energy router, 、 are the topological association matrices of the nth and Nth energy routers respectively, is the input of the energy system, is the output of the energy system.

4. The method for constructing an energy system including a hydrogen energy router in multiple scenarios according to claim 3, characterized in that: The input-output correlation matrix is: in, is the input-output association matrix.

5. The method for constructing an energy system including a hydrogen energy router in multiple scenarios according to any one of claims 1 to 4, characterized in that: The investment and construction costs are: in, is the investment and construction cost, is the annual cost conversion coefficient, 、 、 、 、 、 、 、 、 、 、 0-1 variables indicating whether a water electrolysis device, biomass gasification device, power storage device, oxygen storage device, hydrogen storage device, pressure swing adsorption device, carbon capture device, air separation device, methanol synthesis device, methane synthesis device, and ammonia synthesis device are installed. 、 、 、 、 、 、 、 、 、 、 The unit capacity investment costs of the water electrolysis device, biomass gasification device, power storage device, oxygen storage device, hydrogen storage device, pressure swing adsorption device, carbon capture device, air separation device, synthetic methanol device, synthetic methane device, and synthetic ammonia device are respectively: 、 、 、 、 、 、 、 、 、 、 They are the planned capacities of water electrolysis unit, biomass gasification unit, electricity storage unit, oxygen storage unit, hydrogen storage unit, pressure swing adsorption unit, carbon capture unit, air separation unit, methanol synthesis unit, methane synthesis unit, and ammonia synthesis unit. is the interest rate, The investment recovery period.

6. The method for constructing an energy system including a hydrogen energy router in multiple scenarios according to any one of claims 1 to 4, characterized in that: The operating costs are: in, is the operating cost, For operation and maintenance costs, is the raw material cost, is the number of days in a year, For the scene, For time, is the probability of scene s, 、 、 、 、 、 、 、 、 、 、 、 、 、 They are the unit operation and maintenance costs of photovoltaic, hydropower, wind power, water electrolysis device, biomass gasification device, power storage device, oxygen storage device, hydrogen storage device, pressure swing adsorption device, carbon capture device, air separation device, synthetic methanol device, synthetic methane device, and synthetic ammonia device. 、 、 are the photovoltaic output, hydropower output, and wind power output at time t under scenario s, is the electric power consumed by the water electrolysis device at time t in scenario s, 、 are the energy storage charging and discharging power at time t under scenario s, 、 are the charging and discharging flow rates of the oxygen storage device at time t under scenario s, 、 are the charging and discharging flow rates of the hydrogen storage device at time t under scenario s, 、 、 are the prices of biomass, nitrogen, and carbon dioxide at time t under scenario s, 、 、 、 are the electric power consumed by the pressure swing adsorption unit, methanol synthesis unit, methane synthesis unit, and ammonia synthesis unit at time t under scenario s, 、 、 are the prices of biomass, nitrogen, and carbon dioxide per unit at time t in scenario s, respectively.

7. A system for constructing an energy system including a hydrogen energy router in multiple scenarios, characterized in that: include: processor; A memory storing a computer executable program, which, when executed by the processor, enables the processor to execute the method for constructing an energy system including a hydrogen energy router in multiple scenarios as described in any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for constructing an energy system including a hydrogen energy router in multiple scenarios according to any one of claims 1 to 6 is implemented.

Images