Model selection method and device of combined cooling heating and power system based on SOFC (Solid Oxide Fuel Cell)

Abstract

The embodiment of the invention provides a model selection method and device for a combined cooling heating and power system based on an SOFC (Solid Oxide Fuel Cell), and the method comprises the steps: constructing a combined cooling heating and power system framework based on the SOFC; a numerical model is constructed for key equipment in a combined cooling heating and power system frame, wherein the key equipment comprises at least one of an energy storage battery, an electrolytic bath or an SOFC; coupling the numerical model of the key equipment with a combined cooling heating and power system frame, and determining an energy efficiency index and a cost index of the combined cooling heating and power system frame; constructing a multi-objective optimization model by taking the capacity of the key equipment as an independent variable factor and taking energy efficiency index maximization and cost index minimization as solving objectives; and selecting the capacity of the key equipment based on a result obtained by solving the multi-objective optimization model. In this way, the system equipment capacity with the optimal economic and technical performance of the system is obtained, and theoretical guidance can be provided for system design and manufacturing of an SOFC combined cooling heating and power system producer.

Description

Technical Field

[0001] Embodiments of the present application relate to the technical field of combined heat and power systems, and in particular, to a method for selecting a combined heat and power system based on SOFC, a device for selecting a combined heat and power system based on SOFC, an electronic device, and a computer-readable storage medium. Background Art

[0002] In recent years, hydrogen energy has attracted widespread attention in industry and academia due to its significant advantages such as high enthalpy, zero carbon emissions, long-term storage and environmental friendliness. Samarium Doped Ceria (SDC) Solid Oxide Fuel Cell (SOFC) can convert hydrogen energy into electrical energy and thermal energy at an operating temperature of 500-800℃. It can be used in conjunction with heat exchangers, hot water storage tanks, absorption chillers and other equipment to cover the cooling, heating and electricity needs of buildings. Therefore, SOFC has been widely used in the combined cooling, heating and power (CCHP) system of building energy supply, and has far-reaching application prospects in promoting green and low-carbon building renovation.

[0003] In order to adapt to building application scenarios in a wide range of time domains, SOFC combined heat and power systems can be integrated with other auxiliary equipment to achieve long-term independent operation, including energy storage batteries, electrolyzers, photovoltaic panels, etc. The capacity size of key equipment in the combined heat and power system (such as SOFC, energy storage batteries, electrolyzers, etc.) not only determines the initial investment cost of the system, but also affects the working performance and service life of the equipment. Therefore, the capacity selection of key equipment in the SOFC combined heat and power system is an effective means to balance the economic performance and technical performance of the system. At the same time, compared with the field experimental method, numerical modeling and simulation analysis have the characteristics of high analysis efficiency and low operating cost, and are an effective method for capacity selection of SOFC combined heat and power systems. However, there are few related combined heat and power system selection methods published. Summary of the invention

[0004] Based on this, it is necessary to provide a selection method for a combined heat, cooling and power system based on SOFC, a selection device for a combined heat, cooling and power system based on SOFC, an electronic device and a computer-readable storage medium to address the above technical problems.

[0005] In a first aspect, an embodiment of the present application provides a method for selecting a combined heat and power system based on SOFC, the method comprising the following steps: Constructing a combined heat and power system framework based on SOFC, wherein the combined heat and power system framework includes a photovoltaic panel, an electrolyzer, an energy storage battery, a hydrogen storage tank, an air compressor, a SOFC, a burner, an electric energy supply mechanism, a cold supply mechanism, and a hot water supply mechanism, wherein the electrolyzer and the energy storage battery are respectively connected to the photovoltaic panel, the hydrogen storage tank is connected to the electrolyzer, the hydrogen storage tank and the air compressor are respectively connected to the SOFC, the SOFC is connected to the burner, the electric energy supply mechanism, the cold supply mechanism, and the hot water supply mechanism are respectively connected to the burner, and the electric energy supply mechanism is also connected to the energy storage battery; Constructing a numerical model for key equipment in the combined cooling, heating and power system framework, wherein the key equipment includes at least one of the following: the energy storage battery, the electrolyzer or the SOFC; coupling the numerical model of the key equipment with the combined cooling, heating and power system framework to determine energy efficiency indicators and cost indicators of the combined cooling, heating and power system framework; Taking the capacity of the key equipment as an independent variable factor, and taking maximizing the energy efficiency index and minimizing the cost index as solution objectives, a multi-objective optimization model is constructed; Based on the results obtained by solving the multi-objective optimization model, the capacity of the key equipment is selected.

[0006] In the embodiments of the present application, a method for selecting the equipment capacity of a SOFC combined heat and power system for optimizing technical and economic performance is proposed. By exploring the capacity adjustment of key equipment of the system (energy storage batteries, electrolyzers or SOFC, etc.), the system energy efficiency and cost are optimized, and the system equipment capacity with the best system economic and technical performance is obtained, which can provide theoretical guidance for the system design and manufacturing of SOFC combined heat and power system manufacturers.

[0007] In a possible implementation, constructing a numerical model of the energy storage battery includes: A battery capacity submodel of the energy storage battery and a performance decay submodel of the energy storage battery are constructed, wherein the battery capacity submodel is used to determine the effective total capacity of the energy storage battery based on the number of cells and the real-time relative capacity of the energy storage battery, and the performance decay submodel of the energy storage battery is used to determine the decay capacity of the energy storage battery based on the discharge depth of each charge and discharge cycle of the energy storage battery.

[0008] In a possible implementation, the discharge depth of each charge and discharge cycle of the energy storage battery is determined based on the maximum charge and the minimum charge of the charge and discharge cycle; Determining the attenuated capacity of the energy storage battery based on the discharge depth of each charge and discharge cycle of the energy storage battery includes: Determining a fitting coefficient based on the discharge depth of the charge and discharge cycle of the energy storage battery; The attenuated capacity of the energy storage battery is determined based on the fitting coefficient.

[0009] In a possible implementation, constructing a numerical model of the electrolytic cell includes: An electrochemical sub-model of the electrolyzer and a performance decay sub-model of the electrolyzer are constructed, wherein the electrochemical sub-model of the electrolyzer is used to determine the hydrogen production efficiency of the electrolyzer based on the number of electrolyzer cells and the voltage of the electrolyzer cells; and the performance decay sub-model of the electrolyzer is used to determine the decay voltage of the electrolyzer based on the number of electrolyzer cells and the decay rate of the electrolyzer voltage.

[0010] In a possible implementation, constructing a numerical model of the SOFC includes: An electrochemical sub-model of the SOFC and a performance decay sub-model of the SOFC are constructed, wherein the electrochemical sub-model of the SOFC is used to determine the electric power and thermal power of the SOFC based on the number of single-chips of the SOFC and the effective single-chip voltage of the SOFC; and the performance decay sub-model of the SOFC is used to determine the voltage decay rate of the SOFC based on the current density of the SOFC and the mass percentage of hydrogen.

[0011] In one possible implementation, the energy efficiency index is determined based on the system output electric power, the coefficient output thermal power and the system output cold power; the cost index is determined based on the cumulative decay capacity of the energy storage battery, the cumulative decay voltage of the electrolyzer and the cumulative decay voltage of the SOFC.

[0012] In a possible implementation, the result obtained by solving the multi-objective optimization model is a Pareto front solution set; and selecting the capacity of the key equipment based on the result obtained by solving the multi-objective optimization model includes: determining a normalized Euclidean distance based on the Pareto front solution set; The capacity of the key device is selected based on the normalized Euclidean distance.

[0013] In a second aspect, an embodiment of the present application provides a selection device for a combined heat and power system based on SOFC, the device comprising: A system construction module, for constructing a combined heat and power system framework based on SOFC, wherein the combined heat and power system framework includes a photovoltaic panel, an electrolyzer, an energy storage battery, a hydrogen storage tank, an air compressor, a SOFC, a burner, an electric energy supply mechanism, a cold supply mechanism, and a hot water supply mechanism, wherein the electrolyzer and the energy storage battery are respectively connected to the photovoltaic panel, the hydrogen storage tank is connected to the electrolyzer, the hydrogen storage tank and the air compressor are respectively connected to the SOFC, the SOFC is connected to the burner, the electric energy supply mechanism, the cold supply mechanism, and the hot water supply mechanism are respectively connected to the burner, and the electric energy supply mechanism is also connected to the energy storage battery; An equipment numerical model building module, used to build a numerical model for key equipment in the combined cooling, heating and power system framework, wherein the key equipment includes at least one of the following: the energy storage battery, the electrolyzer or the SOFC; An index determination module, used for coupling the numerical model of the key equipment with the combined cooling, heating and power system framework to determine the energy efficiency index and cost index of the combined cooling, heating and power system framework; A multi-objective optimization model building module is used to build a multi-objective optimization model with the capacity of the key equipment as an independent variable factor and with maximizing the energy efficiency index and minimizing the cost index as solution objectives; A solution module is used to select the capacity of the key equipment based on the result obtained by solving the multi-objective optimization model.

[0014] In a third aspect, an embodiment of the present application provides an electronic device, including: Memory, used to store programs; A processor is used to execute the program stored in the memory. When the processor executes the program stored in the memory, the processor is used to execute the method for selecting a combined cooling, heating and power system based on SOFC as described in the first aspect above.

[0015] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to execute the selection method of the SOFC-based combined heat and power system as described in the first aspect above.

[0016] The solutions provided in the second to fourth aspects are used to implement or cooperate with the selection method of the SOFC-based combined heat and power system provided in the first aspect, and can therefore achieve the same or corresponding beneficial effects as the first aspect, and will not be repeated here.

[0017] It should be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A schematic flow chart of a method for selecting a combined cooling, heating and power system based on SOFC provided in the first embodiment of the present application; Figure 2 A schematic diagram of a combined cooling, heating and power system framework based on SOFC provided in an embodiment of the present application; Figure 3 A schematic diagram of an implementation framework for selecting a combined cooling, heating and power system based on SOFC provided in an embodiment of the present application; Figure 4 A flow chart of a method for selecting a combined cooling, heating and power system based on SOFC provided in the second embodiment of the present application; Figure 5 A schematic diagram of a Pareto solution set of system total energy efficiency and system annual total cost under multi-objective optimization provided in an embodiment of the present application; Figure 6 A schematic diagram of a Pareto solution set of normalized system total energy efficiency and system annual total cost provided in an embodiment of the present application; Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical methods and advantages of this application more clear, the following is a further detailed description of this application in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain this application and are not used to limit this application.

[0020] It should be noted that the meaning of "multiple" (or multiple) involved in the description of the embodiments of the present application is more than two, "greater than", "less than", "exceed", etc. are understood as not including the number itself, and "above", "below", "within", etc. are understood as including the number itself. If there is a description of "first", "second", etc., it is only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0021] In the embodiments of the present application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the situation where A exists alone, A and B exist at the same time, and B exists alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b and c can mean: a exists alone, b exists alone, c exists alone, a and b exist at the same time, a and c exist at the same time, b and c exist at the same time, or a, b and c exist at the same time, wherein a, b, c can be single or multiple.

[0022] The terms "substantially", "about" and similar terms used in the embodiments of the present application are used as approximate terms rather than as terms of degree, and are intended to take into account the inherent deviations of measurements or calculations known to those of ordinary skill in the art. In addition, the use of "may" when describing the embodiments of the present application refers to "possible one or more embodiments". The terms "use", "using", and "used" used in the embodiments of the present application may be considered to be synonymous with the terms "utilize", "utilizing", and "utilized", respectively. In addition, the term "exemplary" is intended to refer to an example or illustration.

[0023] See also Figure 1 , is a flow chart of a method for selecting a combined cooling, heating and power system based on SOFC provided in the first embodiment of the present application, the method comprising the following steps: Step S101: construct a combined heat, cooling and power system framework based on SOFC, wherein the combined heat, cooling and power system framework includes photovoltaic panels, electrolyzers, energy storage batteries, hydrogen storage tanks, air compressors, SOFCs, burners, electric energy supply mechanisms, cold supply mechanisms, and hot water supply mechanisms, wherein the electrolyzers and energy storage batteries are respectively connected to the photovoltaic panels, the hydrogen storage tanks are connected to the electrolyzers, the hydrogen storage tanks and air compressors are respectively connected to the SOFCs, the SOFCs are connected to the burners, the electric energy supply mechanisms, cold supply mechanisms, and hot water supply mechanisms are respectively connected to the burners, and the electric energy supply mechanisms are also connected to the energy storage batteries.

[0024] For example, a solid oxide fuel cell combined heating and power system model framework can be designed and constructed on the TRNSYS simulation platform.

[0025] See also Figure 2, which is a schematic diagram of a SOFC-based combined heat and power system framework provided in an embodiment of the present application. The framework includes: photovoltaic panels, electrolyzers, energy storage batteries, hydrogen storage tanks, air compressors, SOFCs, burners, power supply mechanisms (including inverters), cold supply mechanisms (including generators, absorbers, condensers, throttle valves, evaporators, cooling coils, air heaters, etc.) and hot water supply mechanisms (including gas-liquid heat exchangers, liquid electric heaters, hot water storage tanks, diverters, mixers, etc.).

[0026] Figure 2 The working principle of the SOFC-based combined cooling, heating and power system framework shown is as follows: The photovoltaic panel stores the generated electricity in the energy storage battery (path 1), and then transmits the excess electricity to the electrolyzer for electrolytic hydrogen production (path 2). The hydrogen produced by the electrolyzer is stored in the gas tank (path 3). The air compressor and hydrogen storage tank then supply air and hydrogen respectively, and after double preheating by the gas heat exchanger and the gas electric heater, they are sent to the solid oxide fuel cell stack (paths 4-9). The air and hydrogen undergo an electrochemical reaction in the solid oxide fuel cell stack to generate electricity and heat energy, further increasing the gas temperature. The excess air and hydrogen are discharged into the burner and fully mixed and burned to form a high-temperature mixed gas (paths 10 and 11). The high-temperature mixed gas then passes through the gas heat exchangers of the cathode and anode in turn to preheat the air and hydrogen entering the stack (paths 12-14). When no cooling is required, the high-temperature mixed gas passes through paths 15 and 16 (path 26 valve is closed), enters the gas-liquid heat exchanger, and exchanges heat with the water circulation in the hot water storage tank (paths 18 and 19) to heat the domestic hot water in the hot water storage tank, and then discharges the system from path 17. The city tap water is divided into two parts by the diverter (path 20), one part enters the hot water storage tank for heating (path 21), and the other part is mixed in the mixer (paths 22 and 23) to achieve the effect of initially raising the water temperature. The hot water is then heated to the set value again by the liquid electric heater and transported to the building end (paths 24 and 25). When cooling the building, the high-temperature mixed gas discharged from the solid oxide fuel cell stack passes through path 26 (path 15 valve is closed) to heat the generator of the absorption refrigeration module, and then enters the gas-liquid heat exchanger to heat the hot water storage tank (path 27). After the aqueous solution in the generator is heated and evaporated, it forms water vapor that passes through the condenser, throttle valve and evaporator (paths 30 and 31) in turn, enters the absorber, combines with the lithium bromide solution for absorption again, and recirculates into the generator (paths 28 and 29). The cold energy generated by the evaporator is further extended to the cooling coil (paths 33 and 34) through the water circulation, cooling the natural air from the outside (paths 35 and 36). After the temperature and humidity of the cold air are adjusted by the air heater, it is sent to the building end (paths 37 and 38). At the same time, the electricity generated by the energy storage battery and the solid oxide fuel cell stack is rectified by the inverter and supplied to the auxiliary components of the building end and the system itself, realizing the independent operation of the grid of the whole system.

[0027] Step S102: constructing a numerical model for key equipment in the combined cooling, heating and power system framework, where the key equipment includes at least one of the following: energy storage battery, electrolyzer or SOFC.

[0028] In a possible implementation, a numerical model of an energy storage battery is constructed, including: A battery capacity submodel and a performance decay submodel of the energy storage battery are constructed, wherein the battery capacity submodel is used to determine the effective total capacity of the energy storage battery based on the number of single cells and the real-time relative capacity of the energy storage battery, and the performance decay submodel of the energy storage battery is used to determine the decay capacity of the energy storage battery based on the discharge depth of each charge and discharge cycle of the energy storage battery.

[0029] In a possible implementation, the discharge depth of each charge and discharge cycle of the energy storage battery is determined based on the maximum charge and the minimum charge of the charge and discharge cycle; The attenuation capacity of the energy storage battery is determined based on the discharge depth of each charge and discharge cycle of the energy storage battery, including: Determine the fitting coefficient based on the discharge depth of the energy storage battery charge and discharge cycle; The decay capacity of the energy storage battery is determined based on the fitting coefficients.

[0030] In a possible implementation, a numerical model of an electrolytic cell is constructed, including: An electrochemical sub-model of the electrolyzer and a performance decay sub-model of the electrolyzer are constructed, wherein the electrochemical sub-model of the electrolyzer is used to determine the hydrogen production efficiency of the electrolyzer based on the number of electrolyzer cells and the single-cell voltage of the electrolyzer; the performance decay sub-model of the electrolyzer is used to determine the decay voltage of the electrolyzer based on the number of electrolyzer cells and the decay rate of the electrolyzer voltage.

[0031] In a possible implementation, a numerical model of SOFC is constructed, including: The electrochemical sub-model of SOFC and the performance decay sub-model of SOFC are constructed. The electrochemical sub-model of SOFC is used to determine the electric power and thermal power of SOFC based on the number of SOFC cells and the effective cell voltage of SOFC; the performance decay sub-model of SOFC is used to determine the voltage decay rate of SOFC based on the current density of SOFC and the mass percentage of hydrogen.

[0032] Step S103: coupling the numerical model of the key equipment with the combined heating, cooling and power system framework to determine the energy efficiency index and cost index of the combined heating, cooling and power system framework.

[0033] Step S104: construct a multi-objective optimization model with the capacity of key equipment as the independent variable factor and the maximization of energy efficiency index and the minimization of cost index as the solution objectives.

[0034] Step S105: Based on the results obtained by solving the multi-objective optimization model, the capacity of key equipment is selected.

[0035] In one possible implementation, the energy efficiency index is determined based on the system output electric power, the coefficient output thermal power and the system output cold power; the cost index is determined based on the cumulative attenuation capacity of the energy storage battery, the cumulative attenuation voltage of the electrolyzer and the cumulative attenuation voltage of the SOFC.

[0036] In a possible implementation, the result obtained by solving the multi-objective optimization model is a Pareto front solution set; based on the result obtained by solving the multi-objective optimization model, the capacity of key equipment is selected, including: Determine the normalized Euclidean distance based on the Pareto front solution set; The capacity of key devices is selected based on normalized Euclidean distance.

[0037] In the embodiments of the present application, a method for selecting the equipment capacity of a SOFC combined heat and power system for optimizing technical and economic performance is proposed. By exploring the capacity adjustment of key equipment of the system (energy storage batteries, electrolyzers or SOFCs, etc.), the total energy efficiency and annual total cost of the system are taken as optimization objects, and the system equipment capacity with the best economic and technical performance of the system is obtained, which can provide theoretical guidance for the system design and manufacturing of SOFC combined heat and power system manufacturers.

[0038] See also Figure 3 , is a schematic diagram of an implementation framework for selecting a combined heat and power system based on SOFC provided in an embodiment of the present application. Figure 3As shown in the figure, when implementing the selection of the combined heat, cooling and power system based on SOFC, the framework configuration of the combined heat, cooling and power system of SOFC can be designed and constructed on the simulation platform first; then, the key equipment in the framework is numerically modeled, including: the construction of the battery capacity sub-model of the energy storage battery, the construction of the performance attenuation sub-model of the energy storage battery, the construction of the electrochemical sub-model of the electrolyzer, the construction of the performance attenuation sub-model of the electrolyzer, the construction of the electrochemical sub-model of the SOFC, and the performance attenuation sub-model of the SOFC; then, the numerical models of each key equipment are coupled to the combined heat, cooling and power system of SOFC, so as to obtain the mapping relationship between the capacity of the key equipment and the economic and technical evaluation indicators of the combined heat, cooling and power system of SOFC; further, the economic and technical evaluation indicators are constructed, including the total energy efficiency index of the system and The total annual cost index of the system; further, with the goal of maximizing the total energy efficiency index of the system and minimizing the total annual cost index of the system, a multi-objective optimization algorithm framework is constructed; the multi-objective optimization algorithm is solved. It should be understood that the multi-objective optimization algorithm is a type of algorithm used to solve optimization problems with multiple conflicting objectives. In the embodiment of the present application, the multi-objective optimization algorithm needs to solve the conflict between maximizing the total energy efficiency index of the system and minimizing the total annual cost index of the system. There is no single optimal solution for the multi-objective optimization algorithm, but a set of solutions (Pareto optimal solution set). These solutions provide different trade-offs between the two objectives of maximizing the total energy efficiency index of the system and minimizing the total annual cost index of the system. The embodiment of the present application ultimately adopts the equipment capacity determined based on the normalized Euclidean distance for selection decision.

[0039] It should be noted that the key equipment of the embodiment of the present application may include other equipment in addition to the energy storage battery, electrolyzer and SOFC; or may include only one or two of the energy storage battery, electrolyzer and SOFC. The embodiment of the present application does not make too many restrictions on the specific types of key equipment.

[0040] See also Figure 4 , is a flow chart of a method for selecting a combined heat and power system based on SOFC provided in the second embodiment of the present application, the method comprising the following steps: Step S201: Design and construct a solid oxide fuel cell (SOFC) combined cooling, heating and power (CCHP) system model framework model on the TRNSYS simulation platform.

[0041] It should be noted that the implementation of step S201 may refer to the relevant description of the previous step S101, which will not be repeated here.

[0042] Step S202: construct a numerical model of key equipment and couple it with the combined cooling, heating and power system.

[0043] In this embodiment, energy storage batteries, electrolyzers and SOFCs are taken as examples to illustrate the process of building numerical models of key equipment.

[0044] Step S202.1: construct a numerical model of the energy storage battery and couple it with the combined heating, cooling and power system.

[0045] The first step is to construct a battery capacity sub-model of the energy storage battery. The expression of the battery capacity of the energy storage battery is: (Formula 1) Among them, Caeff is the effective total capacity of the energy storage battery, Nba is the number of single energy storage batteries, Caini,cell is the initial single-cell capacity, RC is the real-time relative capacity, Pba is the net charge and discharge power, and tba is the operating time of the energy storage battery.

[0046] The expression of relative capacity of energy storage battery is: (Formula 2) Where n is the number of charge and discharge cycles, and ∆RC is the capacity decay per charge and discharge cycle.

[0047] The second step is to construct a performance attenuation sub-model of the energy storage battery to characterize the attenuation capacity of the energy storage battery. The expression is: (Formula 3) in It represents the attenuation capacity of each charge and discharge cycle. β1, β2, and β3 are fitting coefficients related to the depth of discharge and can be calculated as: (Formula 4) Where uj,i is the fitting coefficient (j=1, 2, 3; i=1, 2, 3, 4, 5, 6, 7, 8). The following Table 1 shows examples of the values ​​of the fitting coefficient uj,i for the discharge depth and the attenuation capacity.

[0048] Table 1

[0049] DOD is the depth of discharge and can be calculated as: (Formula 5) Where DOD is the depth of discharge, FSOCpeak,n is the maximum charge of the nth charge and discharge cycle, and FSOCvalley,n is the minimum charge of the nth charge and discharge cycle.

[0050] Step S202.2: construct a numerical model of the electrolyzer and couple it with the combined heating, cooling and power system.

[0051] The first step is to build an electrochemical model of the electrolyzer to characterize the hydrogen production rate. The hydrogen production rate of the electrolyzer can be calculated as: (Formula 6) in is the hydrogen production rate; is the input current; is the molar mass of hydrogen, 2×10-3 kg / mol; is the number of electrons carried by a hydrogen molecule, 2; F is the Faraday constant, 96485 C / mol.

[0052] The input current can be calculated as: (Formula 7) Where Pel is the input power, Nel is the number of electrolytic cells, and Eel is the voltage of the electrolytic cell.

[0053] The voltage of a single cell can be calculated as: (Formula 8) Where Eel,re is the reversible potential, Eel,act is the activation polarization of the electrolytic cell, Eel,ohm is the ohmic polarization of the electrolytic cell, and ∆Eel is the accumulated decay voltage of the electrolytic cell.

[0054] The reversible potential expression is: (Formula 9) Tel is the operating temperature of the electrolytic cell.

[0055] The activation polarization expression of the electrolytic cell is: (Formula 10) Where R is the gas constant, 8.314 J / (mol·K), Tel is the operating temperature of the electrolyzer, iel,a is the anode exchange current density, iel,c is the cathode exchange current density, and iel is the input current density.

[0056] The expression of anode exchange current density is: (Formula 11) in is the reference coefficient of anode current density, is the anode activation energy, 76 kJ / mol.

[0057] The cathode exchange current density expression is: (Formula 12) in is the cathode current density reference coefficient, is the cathode activation energy, 18 kJ / mol.

[0058] The ohmic polarization expression of the electrolytic cell is: (Formula 13) Where del is the thickness of the electrolytic cell membrane and θ(λ) is the membrane conductivity, which can be calculated as: (Formula 14) Where λ is the membrane water content.

[0059] The second step is to construct a performance attenuation sub-model of the electrolytic cell to characterize the attenuation voltage of the electrolytic cell. The expression is: (Formula 15) Where ∆Eel is the cumulative decay voltage of the electrolytic cell, Nel is the number of electrolytic cells, tm, tfl, tct, tfh, tcr are the operating time of the low-power stabilization stage (≤ 0.6 W / cm2), low-power cycling stage (0.6 – 4 W / cm2), constant power operation stage (4 W / cm2), high-power cycling stage (4 – 6 W / cm2) and high-power excess stage (6 W / cm2), respectively; φm, φfl, φct, φfh, φcr are the voltage decay rates corresponding to the above stages, which are 1.5, 50, 20, 66, 196 μV / h, respectively.

[0060] Step S202.3: construct a numerical model of SOFC and couple it with the combined cooling, heating and power system.

[0061] The first step is to build an electrochemical model of SOFC to characterize the electrical power and thermal power of SOFC.

[0062] The expression of SOFC electric power is: (Formula 16) in is the electrical power of the solid oxide fuel cell, is the effective single-chip voltage, is is the current density, As is the active area, and Ns is the number of single chips.

[0063] The SOFC thermal power expression is: (Formula 17) in is the thermal power of the solid oxide fuel cell.

[0064] The effective single chip voltage expression is: (Formula 18) in Solid oxide fuel cell single chip voltage, is the performance decay rate, is the running time.

[0065] The voltage of SOFC single chip is: (Formula 19) is the Nernst voltage, To activate polarization, is Ohmic polarization, It is concentration polarization.

[0066] The Nernst voltage expression is: (Formula 20) Where Ts is the operating temperature of the fuel cell, is the partial pressure of hydrogen, is the partial pressure of oxygen, is the partial pressure of water vapor, The activation polarization expression is: (Formula 21) Where is,a is the anode exchange current density and is,c is the cathode exchange current density.

[0067] The Ohmic polarization expression is: (Formula 22) Wherein da, dc, dele, and dint are the thicknesses of the anode, cathode, electrolyte, and connecting sheet of the solid oxide fuel cell, and κa, κc, κele, and κint are the electrical conductivities of the anode, cathode, electrolyte, and connecting sheet of the solid oxide fuel cell.

[0068] The concentration polarization expression is: (Formula 23) in , , is the limiting current density of hydrogen, oxygen and water vapor, , are the number of electrons in a single molecule of hydrogen and oxygen respectively.

[0069] The second step is to build a performance decay sub-model of SOFC to characterize the voltage decay rate of SOFC. The expression is: (Formula 24) in is the mass percentage of hydrogen.

[0070] Step S203: Constructing economic and technical evaluation indicators of the combined cooling, heating and power system, namely, the total energy efficiency of the system and the total annual cost of the system.

[0071] Step S203.1: The total energy efficiency of the combined cooling, heating and power system can be calculated as: (Formula 25) in is the total energy efficiency of the system, Output electrical power to the system, The thermal power output of the system is is the cooling power output of the system, is the solar radiation power density, is the photovoltaic panel area, is the number of photovoltaic panels, is the initial net output power of the energy storage battery, It is the initial net output hydrogen energy of the hydrogen storage tank.

[0072] The initial net output power of the energy storage battery is: (Formula 26) The initial net output hydrogen energy of the hydrogen storage tank is: (Formula 27) in , is the real-time hydrogen consumption and production rate, The lower calorific value of hydrogen is 1.21×108 J / kg.

[0073] Step S203.2: The total annual cost of the combined cooling, heating and power system can be calculated as: (Formula 28) Among them, Costini is the initial investment cost, CR is the capital recovery coefficient, Costmian is the annual maintenance cost, and Costdep is the annual depreciation cost.

[0074] The capital recovery factor can be calculated as: (Formula 29) Where r is the interest rate and L is the system operating life.

[0075] The annual maintenance cost can be calculated as: (Formula 30) Where ζ is the maintenance factor, 6%.

[0076] The annual depreciation cost can be calculated as: (Formula 31) in is the accumulated attenuation capacity of the energy storage battery, is the accumulated decay voltage of the electrolytic cell, is the solid oxide fuel cell cumulative decay voltage, is the maximum allowable attenuation capacity of the energy storage battery, is the maximum allowable attenuation voltage of the electrolytic cell, is the maximum allowable decay voltage of the solid oxide fuel cell, , , They are the initial investment costs of energy storage batteries, electrolyzers, and solid oxide fuel cells, respectively.

[0077] Step S204: Construct a multi-objective optimization algorithm framework based on the non-dominated solution sorting genetic algorithm (NSGA-Ⅱ), and take the capacity size of energy storage batteries, electrolyzers and SOFCs as adjustment objects, perform multi-objective optimization on the system total energy efficiency and the system annual total cost, and obtain the equipment capacity size with the best system economic and technical performance.

[0078] Exemplarily, the expression of the optimization algorithm is: (Formula 32) like Figure 5 , which is a schematic diagram of the Pareto solution set of the system total energy efficiency and the system annual total cost under the multi-objective optimization provided in an embodiment of the present application.

[0079] Step S205: Based on the Pareto front solution set obtained by multi-objective optimization, the optimal equipment capacity size is selected through normalized Euclidean distance determination. The normalized Euclidean distance can be calculated as: (Formula 33) Where Edis is the normalized Euclidean distance, n is the number of dimensions of the solution set, is the normalized solution set coordinate, is the normalized theoretical optimal solution set coordinate. The normalized solution set coordinate can be calculated as: (Formula 34) in , , They are respectively the current solution coordinates, the maximum coordinates of the solution set, and the minimum coordinates of the solution set.

[0080] It is understandable that the total energy efficiency and annual total cost of the system under multi-objective optimization can be normalized, and then the Pareto solution set can be obtained with the goal of maximizing the total energy efficiency and minimizing the annual total cost of the system. Figure 6As shown, it is the Pareto solution set of the normalized system total energy efficiency and the system annual total cost provided in the embodiment of the present application.

[0081] Based on the normalized Euclidean distance, the optimal 5 sets of equipment capacity selection results and their corresponding system total energy efficiency, system total annual cost and normalized Euclidean distance can be shown in Table 2 below.

[0082] Table 2

[0083] The embodiment of the present application is directed to the technical field of fuel cell cogeneration systems, and proposes a method for selecting equipment capacity for solid oxide fuel cell cogeneration systems that optimizes technical and economic performance. By exploring the capacity adjustment of key equipment in the system (energy storage batteries, electrolyzers, solid oxide fuel cells), the system's total energy efficiency and annual total cost are optimized, and the system equipment capacity with the best system economic and technical performance is obtained, which can provide theoretical guidance for system design and manufacturing by fuel cell cogeneration system manufacturers.

[0084] Exemplarily, the selection method of the combined heat and power system based on SOFC provided in the embodiment of the present application can be applied to the terminal, can also be applied to the server, and can also be software running in the terminal or the server. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server can be configured as an independent physical server, or a server cluster or distributed system composed of multiple physical servers, and can also be configured as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN) and big data and artificial intelligence platforms; the software can be an application that implements the selection method of the combined heat and power system based on SOFC, etc., but is not limited to the above forms.

[0085] Exemplarily, the embodiments of the present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld devices or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0086] The present application also provides a device for selecting a cooling, heating and power combined power system based on a solid oxide fuel cell SOFC, the device comprising: A system construction module, for constructing a combined heat and power system framework based on SOFC, wherein the combined heat and power system framework includes a photovoltaic panel, an electrolyzer, an energy storage battery, a hydrogen storage tank, an air compressor, a SOFC, a burner, an electric energy supply mechanism, a cold supply mechanism, and a hot water supply mechanism, wherein the electrolyzer and the energy storage battery are respectively connected to the photovoltaic panel, the hydrogen storage tank is connected to the electrolyzer, the hydrogen storage tank and the air compressor are respectively connected to the SOFC, the SOFC is connected to the burner, the electric energy supply mechanism, the cold supply mechanism, and the hot water supply mechanism are respectively connected to the burner, and the electric energy supply mechanism is also connected to the energy storage battery; An equipment numerical model building module is used to build a numerical model for key equipment in the framework of the combined cooling, heating and power system, where the key equipment includes at least one of the following: an energy storage battery, an electrolyzer or a SOFC; An index determination module is used to couple the numerical model of key equipment with the combined heat and power system framework to determine the energy efficiency index and cost index of the combined heat and power system framework; A multi-objective optimization model building module is used to build a multi-objective optimization model with the capacity of key equipment as the independent variable factor and the maximization of energy efficiency index and the minimization of cost index as the solution objectives; The solution module is used to select the capacity of key equipment based on the results obtained by solving the multi-objective optimization model.

[0087] It should be noted that the information interaction, execution process, etc. between the above-mentioned modules / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0088] See also Figure 7 The embodiment of the present application further provides an electronic device 300. The electronic device 300 may be a server or a terminal, and the internal structure of the electronic device 300 includes but is not limited to: A memory 310, used for storing programs; The processor 320 is used to execute the program stored in the memory 310. When the processor 320 executes the program stored in the memory 310, the processor 320 is used to execute the selection method of the combined cooling, heating and power system based on SOFC in any of the previous embodiments.

[0089] The processor 320 and the memory 310 may be connected via a bus or other means.

[0090] The memory 310 is a non-transient computer-readable storage medium that can be used to store non-transient software programs and non-transient computer executable programs, such as the method for selecting a combined cooling, heating and power system based on SOFC described in any embodiment of the present application. The processor 320 implements the method for selecting a combined cooling, heating and power system based on SOFC in any of the previous embodiments by running the non-transient software programs and instructions stored in the memory 310.

[0091] The memory 310 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store the method for selecting a combined heat and power system based on SOFC as described above. In addition, the memory 310 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 310 may optionally include a memory remotely disposed relative to the processor 320, and these remote memories may be connected to the processor 320 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0092] The non-transient software programs and instructions required to implement the above-mentioned method for selecting a combined heat, cooling and power system based on SOFC are stored in the memory 310. When executed by one or more processors 320, the method for selecting a combined heat, cooling and power system based on SOFC provided in any embodiment of the present application is executed.

[0093] The embodiment of the present application further provides a computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions are used to execute the above-mentioned method for selecting a combined cooling, heating and power system based on SOFC.

[0094] In one embodiment, the storage medium stores computer executable instructions, which are executed by one or more control processors, for example, by one or more processors 320 in the above-mentioned electronic device 300, so that the above-mentioned one or more processors 320 can execute the selection method of the SOFC-based combined heat and power system provided in any embodiment of the present application.

[0095] The above described embodiments are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0096] It will be appreciated by those skilled in the art that all or some of the steps and systems in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or transient medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically include computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0097] In addition, an embodiment of the present application further provides a computer program product, including a computer program, which, when executed by a processor, implements a method for selecting a combined cooling, heating and power system based on SOFC as in any of the previous embodiments.

[0098] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for the parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0099] It should also be understood that the various implementations provided in the embodiments of the present application can be combined arbitrarily to achieve different technical effects.

[0100] Finally, it should be noted that the embodiments described above are only specific implementation methods of the present application, which are used to illustrate the technical solution of the present application rather than to limit it. The protection scope of the present application is not limited thereto. Although the present application has been described in detail with reference to the aforementioned embodiments, ordinary technicians in this field should understand that any technician familiar with this technical field can still modify the technical solution recorded in the aforementioned embodiments within the technical scope disclosed in the present application, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solution deviate from the spirit and scope of the technical solution of the embodiments of the present application, and should all be covered by the protection scope of the present application.

Claims

1. A method for selecting a combined heat and power system based on SOFC, characterized in that: The method comprises the following steps: Constructing a combined heat and power system framework based on SOFC, wherein the combined heat and power system framework includes a photovoltaic panel, an electrolyzer, an energy storage battery, a hydrogen storage tank, an air compressor, a SOFC, a burner, an electric energy supply mechanism, a cold supply mechanism, and a hot water supply mechanism, wherein the electrolyzer and the energy storage battery are respectively connected to the photovoltaic panel, the hydrogen storage tank is connected to the electrolyzer, the hydrogen storage tank and the air compressor are respectively connected to the SOFC, the SOFC is connected to the burner, the electric energy supply mechanism, the cold supply mechanism, and the hot water supply mechanism are respectively connected to the burner, and the electric energy supply mechanism is also connected to the energy storage battery; Constructing a numerical model for key equipment in the combined cooling, heating and power system framework, wherein the key equipment includes at least one of the following: the energy storage battery, the electrolyzer or the SOFC; coupling the numerical model of the key equipment with the combined cooling, heating and power system framework to determine energy efficiency indicators and cost indicators of the combined cooling, heating and power system framework; Taking the capacity of the key equipment as an independent variable factor, and taking maximizing the energy efficiency index and minimizing the cost index as solution objectives, a multi-objective optimization model is constructed; Based on the results obtained by solving the multi-objective optimization model, the capacity of the key equipment is selected.

2. The method according to claim 1, characterized in that Constructing a numerical model of the energy storage battery, including: A battery capacity submodel of the energy storage battery and a performance decay submodel of the energy storage battery are constructed, wherein the battery capacity submodel is used to determine the effective total capacity of the energy storage battery based on the number of cells and the real-time relative capacity of the energy storage battery, and the performance decay submodel of the energy storage battery is used to determine the decay capacity of the energy storage battery based on the discharge depth of each charge and discharge cycle of the energy storage battery.

3. The method according to claim 2, characterized in that The discharge depth of each charge and discharge cycle of the energy storage battery is determined based on the maximum charge and minimum charge of the charge and discharge cycle; Determining the attenuated capacity of the energy storage battery based on the discharge depth of each charge and discharge cycle of the energy storage battery includes: Determining a fitting coefficient based on the discharge depth of the charge and discharge cycle of the energy storage battery; The attenuated capacity of the energy storage battery is determined based on the fitting coefficient.

4. The method according to claim 1, characterized in that Constructing a numerical model of the electrolytic cell, comprising: An electrochemical sub-model of the electrolyzer and a performance decay sub-model of the electrolyzer are constructed, wherein the electrochemical sub-model of the electrolyzer is used to determine the hydrogen production efficiency of the electrolyzer based on the number of electrolyzer cells and the voltage of the electrolyzer cells; and the performance decay sub-model of the electrolyzer is used to determine the decay voltage of the electrolyzer based on the number of electrolyzer cells and the decay rate of the electrolyzer voltage.

5. The method according to claim 1, characterized in that Constructing a numerical model of the SOFC, including: An electrochemical sub-model of the SOFC and a performance decay sub-model of the SOFC are constructed, wherein the electrochemical sub-model of the SOFC is used to determine the electric power and thermal power of the SOFC based on the number of single-chips of the SOFC and the effective single-chip voltage of the SOFC; and the performance decay sub-model of the SOFC is used to determine the voltage decay rate of the SOFC based on the current density of the SOFC and the mass percentage of hydrogen.

6. The method according to claim 1, characterized in that The energy efficiency index is determined based on the system output electric power, the coefficient output thermal power and the system output cold power; the cost index is determined based on the cumulative decay capacity of the energy storage battery, the cumulative decay voltage of the electrolyzer and the cumulative decay voltage of the SOFC.

7. The method according to claim 1, characterized in that The result obtained by solving the multi-objective optimization model is a Pareto front solution set; the capacity of the key equipment is selected based on the result obtained by solving the multi-objective optimization model, including: determining a normalized Euclidean distance based on the Pareto front solution set; The capacity of the key device is selected based on the normalized Euclidean distance.

8. A selection device for a combined heat and power system based on SOFC, characterized in that: The device comprises: A system construction module, for constructing a combined heat and power system framework based on SOFC, wherein the combined heat and power system framework includes a photovoltaic panel, an electrolyzer, an energy storage battery, a hydrogen storage tank, an air compressor, a SOFC, a burner, an electric energy supply mechanism, a cold supply mechanism, and a hot water supply mechanism, wherein the electrolyzer and the energy storage battery are respectively connected to the photovoltaic panel, the hydrogen storage tank is connected to the electrolyzer, the hydrogen storage tank and the air compressor are respectively connected to the SOFC, the SOFC is connected to the burner, the electric energy supply mechanism, the cold supply mechanism, and the hot water supply mechanism are respectively connected to the burner, and the electric energy supply mechanism is also connected to the energy storage battery; An equipment numerical model building module, used to build a numerical model for key equipment in the combined cooling, heating and power system framework, wherein the key equipment includes at least one of the following: the energy storage battery, the electrolyzer or the SOFC; An index determination module, used for coupling the numerical model of the key equipment with the combined cooling, heating and power system framework to determine the energy efficiency index and cost index of the combined cooling, heating and power system framework; A multi-objective optimization model building module is used to build a multi-objective optimization model with the capacity of the key equipment as an independent variable factor and with maximizing the energy efficiency index and minimizing the cost index as solution objectives; A solution module is used to select the capacity of the key equipment based on the result obtained by solving the multi-objective optimization model.

9. An electronic device, characterized in that: include: Memory, used to store programs; A processor, configured to execute the program stored in the memory. When the processor executes the program stored in the memory, the processor is configured to execute: a method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Computer executable instructions are stored, and the computer executable instructions are used to execute: the method according to any one of claims 1 to 7.

Images