CN115307054B - Hydrogen station equipment capacity optimization configuration method based on micro-grid surplus electricity hydrogen production - Google Patents
Hydrogen station equipment capacity optimization configuration method based on micro-grid surplus electricity hydrogen production Download PDFInfo
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- 229910052739 hydrogen Inorganic materials 0.000 title claims abstract description 504
- 239000001257 hydrogen Substances 0.000 title claims abstract description 504
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 title claims abstract description 481
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 132
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Abstract
The invention discloses a hydrogen station equipment capacity optimization configuration method based on micro-grid surplus electricity hydrogen production, which is used for researching an output model of a wind power unit, a photovoltaic unit and a small hydropower unit and a hydrogen production/storage model of an electrolytic tank, a hydrogen storage tank and a reformer; and providing an electric power dispatching strategy for residual electricity hydrogen production, so that the residual electricity of the distributed renewable unit is conveyed to a hydrogenation station for the electrolysis cell to produce green hydrogen and the hydrogen dispatching strategy in advance of the green hydrogen is preferentially used for the electrolysis cell to consume the green hydrogen produced by the residual electricity of the micro-grid to meet the hydrogen load, and the insufficient part is supplemented by the blue hydrogen produced by the reformer. And (3) establishing a capacity optimization configuration model of the hydrogen production/storage equipment of the hydrogen production station by considering the target of the minimum total net present value cost of the total life cycle of the hydrogen production station, and solving by applying an improved particle swarm algorithm. The invention solves the problems of wind discarding, light discarding and water discarding of the micro-grid and hydrogen load demand of the hydrogen production station in the park, reduces the total life cycle cost of hydrogen production by residual electricity and different places of the construction of the hydrogen production station, and has the capacity of large-scale residual electricity hydrogen production.
Description
Technical Field
The invention belongs to the technical field of hydrogen energy, and particularly relates to a hydrogen station equipment capacity optimization configuration method based on micro-grid surplus electricity hydrogen production.
Background
Hydrogen energy is a secondary energy source with rich sources, clean low carbon and wide application, and is becoming one of the important carriers for global energy transformation development gradually. In order to assist in achieving the targets of carbon peak and carbon neutralization and promote the high-quality development of the hydrogen energy industry, the renewable energy installation amount in China is first on the world at present, has great potential in green hydrogen supply, and is urgent to explore and establish a hydrogen energy production and supply storage sales system. However, because of the intermittence and uncertainty of the output of the microgrid distributed renewable unit, such as the fluctuation of wind speed, solar radiation day and night, seasonal fluctuation in the water-rich period and the water-withered period, and the limited peak regulation capacity of the power system, the phenomena of wind abandon, light abandon and water abandon are serious at present, so that the waste of energy and finance is caused, and the development of new energy is hindered. Therefore, the hydrogen energy storage device with certain capacity can be matched with the power grid peak shaving, the advantages of high energy density, rapid power regulation and the like are utilized, the movable load function is achieved, the full utilization of residual electricity of the distributed renewable unit is realized, and the safety, stability and economic operation of the micro-grid are ensured. However, this solution is challenged by the inherent space-time imbalance between renewable energy and hydrogen demand, and the technology in the literature has generally employed seasonal storage and inter-regional hydrogen supply chains to eliminate this imbalance, but long-distance hydrogen transportation is costly and uneconomical.
In order to solve the problem of high cost, in recent years, preliminary researches are carried out on the operation joint scheduling and capacity optimization configuration of the residual electricity hydrogen production multi-energy complementary micro-grid system at home and abroad. However, the existing research on the comprehensive system for residual electricity hydrogen production mainly has the following problems: firstly, the requirements of electricity and hydrogen load are not considered at the same time, namely, the hydrogen is used as an energy storage mode to couple the power grid peak shaving without considering the configuration of other hydrogen production equipment to supplement the hydrogen load deficiency; secondly, the residual electricity of the distributed renewable unit is mainly used for on-site hydrogen production at present, but the transportation cost of the hydrogen occupies a large amount in the selling price, and certain risks and losses exist in long-distance transportation, so the full life cycle cost and sensitivity analysis of the residual electricity off-site hydrogen production built by the hydrogen station are not perfect, and the capacity of future large-scale residual electricity hydrogen production is not provided.
Disclosure of Invention
In order to solve the problems, the invention provides a capacity optimization configuration method of hydrogen production equipment of a hydrogen addition station based on micro-grid residual electricity hydrogen, which solves the problems of 'wind discarding', 'light discarding', 'water discarding' of the micro-grid and hydrogen load demand of the hydrogen addition station of a park, and considers the hydrogen production of an electrolytic tank with a certain capacity to absorb the micro-grid residual electricity in the hydrogen addition station, stores the micro-grid residual electricity in a hydrogen storage tank, and simultaneously configures a reformer with a certain capacity to produce hydrogen to supplement green hydrogen without meeting the shortage of hydrogen load, thereby reducing the total life cycle cost of the hydrogen production of the residual electricity in different places including the construction of the hydrogen addition station and having the capacity of large-scale residual electricity hydrogen production.
In order to achieve the above purpose, the invention adopts the following technical scheme: a hydrogen station equipment capacity optimization configuration method based on micro-grid surplus electricity hydrogen production comprises the following steps:
s10, building output models of a wind turbine, a photovoltaic turbine and a hydroelectric turbine, and obtaining output power of the wind turbine, the photovoltaic turbine and the small hydroelectric turbine;
S20, establishing a power dispatching strategy for residual electricity hydrogen production according to the sum of the output power of the wind power unit, the photovoltaic unit and the small hydropower unit and the local electric load, conveying residual electricity of the distributed renewable unit to a hydrogenation station for preparing green hydrogen by an electrolytic cell, and calculating to obtain the input power of the electrolytic cell under various working conditions;
S30, calculating the hydrogen production rate of the electrolytic cell by using an electrolytic cell model according to the input power of the electrolytic cell; calculating a hydrogen storage tank model to obtain a hydrogen storage amount range of the hydrogen storage tank;
s40, a hydrogen scheduling strategy of green hydrogen advance is established according to the hydrogen storage amount and the comparison between the local hydrogen load and the hydrogen storage amount range of the hydrogen storage tank, green hydrogen prepared by using an electrolytic cell to consume micro-grid surplus electricity is used for meeting the hydrogen load, the deficient part is supplemented by blue hydrogen prepared by a reformer, and the hydrogen production rate of the reformer and the hydrogen output rate of the hydrogen storage tank are obtained;
s50, calculating the hydrogen storage amount based on the hydrogen production rate of the reformer and the hydrogen output rate of the hydrogen storage tank; substituting the fuel into a reformer hydrogen production model to obtain the fuel consumption rate of the reformer;
s60, establishing a capacity optimization configuration model of the hydrogen production-storage equipment of the hydrogen production station according to the target with the lowest total net present value cost of the total life cycle of the hydrogen production station and the constraints of the power balance, the hydrogen production rate and the hydrogen storage state, and solving by using an improved particle swarm algorithm to complete capacity optimization configuration.
Further, the method for constructing the output model of the wind turbine comprises the following steps:
Step 1: using wind speed conversion formula Substituting the wind speed V anem (t) of the wind meter, the wind turbine hub height Z hub, the wind meter height Z anem and the surface roughness alpha to calculate the wind speed V hub (t) of the wind turbine hub;
Step 2: using a wind turbine output model:
a＝PSTP/(Vr 3-Vci 3)，
b＝Vci 3/(Vr 3-Vci 3)；
Substituting the calculated hub wind speed V hub (t), the cut-in wind speed V ci, the rated wind speed V r, the cut-out wind speed V co and the rated output power P STP of the force turbine to calculate the output power P WT (t) of the wind turbine.
Further, the method for constructing the output model of the photovoltaic unit comprises the following steps:
Using a photovoltaic array output model:
Tc＝Ta+λGT；
Substituting a solar radiation value G T (T), an ambient temperature T a (T), a rated capacity P STC of the photovoltaic array, a derating factor f PV of the photovoltaic array, solar radiation G T.STC incident on the photovoltaic array under standard test conditions, a power temperature coefficient beta, a photovoltaic cell temperature T c of a current time step, a photovoltaic cell temperature T c.STC under standard test conditions and a radiation temperature coefficient lambda, and calculating the output power P PV (T) of the photovoltaic unit.
Further, the method for constructing the output model of the hydroelectric generating set comprises the following steps:
Using a water turbine output model:
Substituting the water diversion flow q (t), the water turbine efficiency eta hyd, the water tightness rho water, the gravity acceleration g and the water purification head h to calculate the output power P hyd (t) of the small hydroelectric generating set.
Further, the power scheduling strategy for residual electricity hydrogen production comprises the following steps:
Comparing the sum of the output power of the wind power unit, the photovoltaic unit and the small hydropower unit with a local electric load to ensure that the net electric load delta P (t) =P L(t)-[PWT(t)+PPV(t)+Phyd (t) ], and judging the positive and negative of the net electric load delta P (t) =P L(t)-[PWT(t)+PPV(t)+Phyd (t);
When deltap (t) =0, the local electric load is just matched with wind power, photovoltaic and hydroelectric power, and at the moment, water electrolysis hydrogen production and transaction with a power grid do not occur;
when delta P (t) >0, the part with insufficient local electric load demand is supplemented by purchasing electricity from the power grid;
when delta P (t) is less than 0, preferentially using an electrolytic tank to consume the redundant power generation amount of the distributed renewable unit; if the absolute value of the net electric load does not exceed the rated power of the electrolytic cell, the input power of the electrolytic cell is equal to the absolute value of the net electric load; if the absolute value of the net electric load exceeds the rated power of the electrolytic cell, the electrolytic cell absorbs electric energy according to the rated power, and the balance is consumed by selling electricity to a power grid;
and calculates the input power P el (t) of the electrolytic cell.
Further, the method is characterized in that an electrolyzer hydrogen production model H el＝ηel·Pel is substituted into the electrolyzer input power P el (t) and the electrolyzer electrolysis efficiency eta el to calculate the electrolyzer hydrogen production rate H el (t);
Hydrogen storage model adopting hydrogen storage tank The maximum hydrogen storage amount Q S.max and the minimum hydrogen storage amount Q S.min of the hydrogen storage tank are calculated by substituting the lower hydrogen storage state limit SSH min and the upper hydrogen storage state limit SSH max, the gas constant R S, the hydrogen storage tank temperature T S, the hydrogen storage tank volume V S, the hydrogen molecular weight N H2, and the maximum hydrogen storage tank pressure P S.max.
Further, comparing the hydrogen storage quantity Q S (t-deltat) of the last time step, the hydrogen load Q L (t) of the city A of the current time step with the calculated highest hydrogen storage quantity Q S.max and the calculated lowest hydrogen storage quantity Q S.min of the hydrogen storage tank;
when the green hydrogen stored in the hydrogen storage tank is enough to supply the hydrogen load of the current time step for use when the last time step is finished, the green hydrogen is completely supplied by the hydrogen storage tank without the participation of a reformer in hydrogen production;
When the green hydrogen stored in the hydrogen storage tank is insufficient for supplying the hydrogen load of the current time step for use at the end of the previous time step, the hydrogen storage tank needs to be subjected to the blue hydrogen preparation by reforming natural gas to supplement the deficiency;
Calculating the hydrogen production rate H ref (t) of the reformer at the current time step, and calculating the hydrogen output rate H So (t) of the hydrogen storage tank at the current time step;
Adopting a hydrogen storage quantity iteration update formula Q S(t)＝QS(t-Δt)+Hel(t)Δt+Href(t)Δt-HSo (t) delta t, substituting the hydrogen production rate H el (t) of the electrolytic cell, the hydrogen production rate H ref (t) of the current time step reformer and the hydrogen output rate H So (t) of the current time step hydrogen storage tank, and calculating the hydrogen storage quantity Q S (t) of the current time step;
obtaining the hydrogen storage quantity Qd S of the full-period hydrogen storage tank and the hydrogen production rate H ref of the full-period reformer through repeated iteration;
The reformer hydrogen production model H ref＝ηref·Gfuel was used to calculate the reformer fuel consumption rate G fuel by substituting the full period reformer hydrogen production rate H ref and the reformer operating efficiency η ref.
Further, according to the target with the lowest total net present value cost of the total life cycle of the hydrogen adding station and the constraints of the power balance, the hydrogen production rate and the hydrogen storage state, a capacity optimizing configuration model of hydrogen adding station hydrogen producing and storing equipment is established, and an improved particle swarm algorithm is used for solving, so that capacity optimizing configuration is completed.
Step 1: calculating initial construction cost C cs, annual cost C cos and annual income C in of the hydrogenation station according to the output power of the obtained wind turbine generator, photovoltaic turbine generator and hydroelectric turbine generator, the hydrogen production/storage amount of the electrolytic tank, the hydrogen storage tank and the reformer, electric hydrogen load data, turbine generator parameters, unit price, pollutant and environmental value parameters and government subsidies;
step 2: the total net present value cost calculation formula of the full life cycle is adopted:
Cann＝Ccos-Cin；
Substituting the initial construction cost C cs, the annual cost C cos, the annual income C in, the actual discount rate i, the life cycle annual y and the service life R proj of the hydrogen addition station to obtain the total net present value cost C npc of the total life cycle of the hydrogen addition station.
Further, the improved particle swarm algorithm is as follows:
Initial value c 2s and final value c 2e of maximum inertial weight ω max, initial value c 1s and final value c 1e,c2 of maximum number of iterations k max、c1 are substituted;
non-linear decrementing of the inertial weight ω:
Decrementing the learning factor c 1:
increment the learning factor c 2
Further, the capacity optimization configuration of the hydrogen making-storing equipment of the hydrogen adding station is carried out by adopting an improved particle swarm algorithm, and the method comprises the following steps:
setting the rated power P el of the electrolytic tank, the rated capacity Q S of the hydrogen storage tank and the rated hydrogen production rate H ref of the reformer as optimization variables, taking the minimum objective function value of the total net present value cost C npc of the total life cycle of the hydrogen addition station as a fitness function, and dynamically adjusting the inertia weight and the learning factor after obtaining individual and global optimal results so as to update the speed and the position of particles; the optimal capacity configuration result is obtained through multiple iterations of the distributed renewable unit output, the electric hydrogen load demand, the constraint condition and the electric hydrogen joint scheduling strategy; the specific calculation steps are shown in fig. 4.
Wherein, the constraint conditions are as follows:
Power balance ：PL(t)＝PWT(t)+PPV(t)+Phyd(t)-Pel(t)+Pgd(t),Pgd(t)＝μPbuy(t)-(1-μ)Psell(t),μ takes 0 or 1;
Cell power constraint: p el(t)≤Pel.max is more than or equal to 0;
Reformer hydrogen production constraint: h ref(t)≤Href.max is more than or equal to 0;
Hydrogen storage tank state constraints ：SSHmin≤SSH(t)≤SSHmax,QS(t)＝QS(t-Δt)+Hel(t)Δt+Href(t)Δt-HSo(t)Δt.
The beneficial effect of adopting this technical scheme is:
The invention establishes a mathematical model of a micro-grid-hydrogen adding station system, proposes an electro-hydrogen joint scheduling strategy of residual electro-hydrogen production-green hydrogen advance based on the output of a distributed renewable unit according to the maximum power, and establishes a capacity optimization configuration model of hydrogen producing/storing equipment with the minimum total net present value cost of the total life cycle of the hydrogen adding station as a target. The problems of 'wind discarding', 'light discarding', 'water discarding' of a micro-grid and hydrogen load demand of a hydrogen adding station in a park are solved, the hydrogen making of an electrolytic tank with a certain capacity is considered to be configured in the hydrogen adding station to consume the residual electricity of the micro-grid, the residual electricity is stored in a hydrogen storage tank, and meanwhile, a reformer with a certain capacity is configured to make hydrogen to supplement green hydrogen without meeting the shortage of hydrogen load, so that the total life cycle cost of the hydrogen making of the residual electricity containing hydrogen adding station construction in different places is reduced, and the hydrogen adding station has the capacity of large-scale residual electricity hydrogen making.
The electricity-hydrogen combined scheduling strategy provided by the invention can well utilize the residual electricity of the distributed renewable unit to prepare green hydrogen so as to avoid renewable resource waste, and the green hydrogen is preferentially used to meet hydrogen load demands, so that the emission of pollutants is reduced, the peak regulation effect of the electrolytic tank as a movable load is fully exerted, and the economy and environmental friendliness of the micro-grid-hydrogen station system are improved.
Compared with the traditional algorithm, the improved particle swarm algorithm is used for solving the calculation example, the improved particle swarm algorithm has better capability of controlling the particle speed and direction, improves the convergence of the algorithm, improves the searching capability of the algorithm, enables the objective function NPC to be the lowest, and verifies the rationality and the effectiveness of the capacity optimization configuration model built by the method.
Drawings
FIG. 1 is a schematic flow chart of a hydrogen station equipment capacity optimizing configuration method based on micro-grid surplus electricity hydrogen production;
FIG. 2 is a flow chart of a residual electricity hydrogen production scheduling strategy in an embodiment of the invention;
FIG. 3 is a flow chart of a green hydrogen advanced scheduling strategy in an embodiment of the invention;
FIG. 4 is a schematic flow chart of an improved particle swarm algorithm for solving a capacity optimization configuration of a hydrogen production/storage device of a hydrogen production station in an embodiment of the present invention;
FIG. 5 is a NPC life cycle curve of a hydrogen station in an embodiment of this invention;
FIG. 6 is a schematic diagram of annual average output of a distributed renewable unit according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of annual average hydrogen production in an electrolyzer in accordance with an embodiment of the present invention;
FIG. 8 is a graph showing the annual average hydrogen storage amount in the hydrogen storage tank according to the embodiment of the present invention;
FIG. 9 is a schematic diagram of annual average hydrogen production from a reformer in accordance with an embodiment of the present invention;
FIG. 10 is a schematic diagram illustrating a convergence process of the improved particle swarm algorithm and the conventional algorithm according to an embodiment of the present invention;
FIG. 11 is a schematic diagram showing the influence of the arrival price of electricity at a hydrogen station on the configuration result in an embodiment of the present invention;
FIG. 12 is a diagram illustrating the effect of hydrogen price on configuration results according to an embodiment of the present invention;
FIG. 13 is a diagram showing the effect of natural gas prices on configuration results in an embodiment of the present invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings, in order to make the objects, technical solutions and advantages of the present invention more apparent.
In this embodiment, referring to fig. 1, the invention provides a hydrogen station device capacity optimization configuration method based on micro-grid surplus electricity hydrogen production, which includes the steps of:
s10, building output models of a wind turbine, a photovoltaic turbine and a hydroelectric turbine, and obtaining output power of the wind turbine, the photovoltaic turbine and the small hydroelectric turbine;
S20, establishing a power dispatching strategy for residual electricity hydrogen production according to the sum of the output power of the wind power unit, the photovoltaic unit and the small hydropower unit and the local electric load, conveying residual electricity of the distributed renewable unit to a hydrogenation station for preparing green hydrogen by an electrolytic cell, and calculating to obtain the input power of the electrolytic cell under various working conditions;
S30, calculating the hydrogen production rate of the electrolytic cell by using an electrolytic cell model according to the input power of the electrolytic cell; calculating a hydrogen storage tank model to obtain a hydrogen storage amount range of the hydrogen storage tank;
s40, a hydrogen scheduling strategy of green hydrogen advance is established according to the hydrogen storage amount and the comparison between the local hydrogen load and the hydrogen storage amount range of the hydrogen storage tank, green hydrogen prepared by using an electrolytic cell to consume micro-grid surplus electricity is used for meeting the hydrogen load, the deficient part is supplemented by blue hydrogen prepared by a reformer, and the hydrogen production rate of the reformer and the hydrogen output rate of the hydrogen storage tank are obtained;
S50, calculating the hydrogen storage amount based on the hydrogen production rate of the reformer and the hydrogen output rate of the hydrogen storage tank; substituting the hydrogen production model of the reformer to obtain the fuel consumption rate of the reformer
S60, establishing a capacity optimization configuration model of the hydrogen preparation and storage equipment of the hydrogen addition station according to the minimum target of total net present value cost (NPC) of the total life cycle of the hydrogen addition station, the power balance, the hydrogen preparation rate and the hydrogen storage state constraint, and solving by using an improved particle swarm algorithm to complete capacity optimization configuration.
As the optimization scheme of the embodiment, the method for constructing the output model of the wind turbine comprises the following steps:
Step 1: using wind speed conversion formula Substituting the wind speed V anem (t) of the wind meter, the wind turbine hub height Z hub, the wind meter height Z anem and the surface roughness a to calculate the wind speed V hub (t) of the wind turbine hub;
Step 2: using a wind turbine output model:
a＝PSTP/(Vr 3-Vci 3)，
b＝Vci 3/(Vr 3-Vci 3)；
Substituting the calculated hub wind speed V hub (t), the cut-in wind speed V ci, the rated wind speed V r, the cut-out wind speed V co and the rated output power P STP of the force turbine to calculate the output power P WT (t) of the wind turbine.
The method for constructing the output model of the photovoltaic unit comprises the following steps:
Using a photovoltaic array output model:
Tc＝Ta+λGT；
Substituting a solar radiation value G T (T), an ambient temperature T a (T), a rated capacity P STC of the photovoltaic array, a derating factor f PV of the photovoltaic array, solar radiation G T.STC incident on the photovoltaic array under standard test conditions, a power temperature coefficient beta, a photovoltaic cell temperature T c of a current time step, a photovoltaic cell temperature T c.STC under standard test conditions and a radiation temperature coefficient lambda, and calculating the output power P PV (T) of the photovoltaic unit.
The method for constructing the output model of the hydroelectric generating set comprises the following steps:
Using a water turbine output model:
Substituting the water diversion flow q (t), the water turbine efficiency eta hyd, the water tightness rho water, the gravity acceleration g and the water purification head h to calculate the output power P hyd (t) of the small hydroelectric generating set.
As an optimization scheme of the above embodiment, as shown in fig. 2, a power scheduling strategy for residual electricity hydrogen production includes the steps of:
Comparing the sum of the output power of the wind power unit, the photovoltaic unit and the small hydropower unit with a local electric load to ensure that the net electric load delta P (t) =P L(t)-[PWT(t)+PPV(t)+Phyd (t) ], and judging the positive and negative of the net electric load delta P (t) =P L(t)-[PWT(t)+PPV(t)+Phyd (t);
When deltap (t) =0, the local electric load is just matched with wind power, photovoltaic and hydroelectric power, and at the moment, water electrolysis hydrogen production and transaction with a power grid do not occur;
when delta P (t) >0, the part with insufficient local electric load demand is supplemented by purchasing electricity from the power grid;
when delta P (t) is less than 0, preferentially using an electrolytic tank to consume the redundant power generation amount of the distributed renewable unit; if the absolute value of the net electric load does not exceed the rated power of the electrolytic cell, the input power of the electrolytic cell is equal to the absolute value of the net electric load; if the absolute value of the net electric load exceeds the rated power of the electrolytic cell, the electrolytic cell absorbs electric energy according to the rated power, and the balance is consumed by selling electricity to a power grid;
and calculates the input power P el (t) of the electrolytic cell.
As an optimization scheme of the embodiment, the hydrogen production model H el＝ηel·Pel of the electrolytic cell is substituted into the input power P el (t) of the electrolytic cell and the electrolytic efficiency eta el of the electrolytic cell, and the hydrogen production rate H el (t) of the electrolytic cell is calculated;
Hydrogen storage model adopting hydrogen storage tank The maximum hydrogen storage amount Q S.max and the minimum hydrogen storage amount Q S.min of the hydrogen storage tank are calculated by substituting the lower hydrogen storage state limit SSH min and the upper hydrogen storage state limit SSH max, the gas constant R S, the hydrogen storage tank temperature T S, the hydrogen storage tank volume V S, the hydrogen molecular weight N H2, and the maximum hydrogen storage tank pressure P S.max.
As shown in fig. 3, in the hydrogen scheduling strategy of green hydrogen advanced, the hydrogen storage amount Q S (t- Δt) of the previous time step, the a city remote hydrogen load Q L (t) of the current time step, and the calculated highest hydrogen storage amount Q S.max and lowest hydrogen storage amount Q S.min of the hydrogen storage tank are compared;
when the green hydrogen stored in the hydrogen storage tank is enough to supply the hydrogen load of the current time step for use when the last time step is finished, the green hydrogen is completely supplied by the hydrogen storage tank without the participation of a reformer in hydrogen production;
When the green hydrogen stored in the hydrogen storage tank is insufficient for supplying the hydrogen load of the current time step for use at the end of the previous time step, the hydrogen storage tank needs to be subjected to the blue hydrogen preparation by reforming natural gas to supplement the deficiency;
Calculating the hydrogen production rate H ref (t) of the reformer at the current time step, and calculating the hydrogen output rate H So (t) of the hydrogen storage tank at the current time step;
Adopting a hydrogen storage quantity iteration update formula Q S(t)＝QS(t-Δt)+Hel(t)Δt+Href(t)Δt-HSo (t) delta t, substituting the hydrogen production rate H el (t) of the electrolytic cell, the hydrogen production rate H ref (t) of the current time step reformer and the hydrogen output rate H So (t) of the current time step hydrogen storage tank, and calculating the hydrogen storage quantity Q S (t) of the current time step;
Obtaining the hydrogen storage quantity Q S of the full-period hydrogen storage tank and the hydrogen production rate H ref of the full-period reformer through repeated iteration;
The reformer hydrogen production model H ref＝ηref·Gfuel was used to calculate the reformer fuel consumption rate G fuel by substituting the full period reformer hydrogen production rate H ref and the reformer operating efficiency η ref.
As the optimization scheme of the embodiment, the capacity optimization configuration model of the hydrogen preparation-storage equipment of the hydrogen addition station is established according to the target with the lowest total net present value cost of the total life cycle of the hydrogen addition station and the constraints of the power balance, the hydrogen preparation rate and the hydrogen storage state, and the improved particle swarm algorithm is used for solving, so that the capacity optimization configuration is completed.
Step 1: calculating initial construction cost C cs, annual cost C cos and annual income C in of the hydrogenation station according to the output power of the obtained wind turbine generator, photovoltaic turbine generator and hydroelectric turbine generator, the hydrogen production/storage amount of the electrolytic tank, the hydrogen storage tank and the reformer, electric hydrogen load data, turbine generator parameters, unit price, pollutant and environmental value parameters and government subsidies;
Annual cost C cos includes annual replacement cost for hydrogen plant equipment C rp, annual operation maintenance cost C om, annual fuel cost C f, annual pollutant emission penalty cost C em, annual electricity consumption cost C con, and annual internet passing cost C pass;
The annual replacement cost and the annual operation and maintenance cost are based on the electrolytic tank, the reformer, the hydrogen storage tank and the hydrogen station supporting facilities, the replacement cost is set to be equal to the construction cost, the annual operation and maintenance cost is proportional to the construction cost, and the operation and maintenance coefficient is 0.02; annual fuel costs are generated by the consumption of natural gas by the reformer; annual pollutant emission is calculated according to the whole production flow of natural gas consumed by hydrogen production of a reformer in the steps of exploitation, pipeline transportation, scattered hydrogen production, compression of a gas station and sales; the electricity consumption cost of the hydrogenation station consists of an electrolytic tank, a reformer and high-pressure gas hydrogen storage electricity consumption; the annual grid-passing expense is the electric transmission expense charged by the power grid company to the hydrogen production department when the residual electricity of the distributed renewable unit is transmitted to the off-site hydrogen station through the power grid, and is charged in the form of electric transmission and distribution price, and generally, the higher the access voltage level is, the lower the electric transmission and distribution price is.
Annual revenue C in includes annual hydrogen sales revenue C H2 from the hydrogen plant, annual environmental value C env, government subsidies C gov, and equipment residue C sv.
The environmental value is generated by reducing the emission of natural gas reforming hydrogen production pollutants by the green hydrogen production by water electrolysis; meanwhile, the A city government supports the high-quality development of the hydrogen energy industry, and a certain proportion of one-time subsidy is provided for the construction and operation of the hydrogen station.
Hydrogen loading data, unit parameters, unit price, pollutant and environmental value parameters, and government subsidies are all existing parameters.
Step 2: the total net present value cost calculation formula of the full life cycle is adopted:
Cann＝Ccos-Cin；
Substituting the initial construction cost C cs, the annual cost C cos, the annual income C in, the actual discount rate i, the life cycle annual y and the service life R proj of the hydrogen addition station to obtain the total net present value cost C npc of the total life cycle of the hydrogen addition station.
As an optimization scheme of the above embodiment, the improved particle swarm algorithm is:
Initial value c 2s and final value c 2e of maximum inertial weight ω max, initial value c 1s and final value c 1e,c2 of maximum number of iterations k max、c1 are substituted;
non-linear decrementing of the inertial weight ω:
Decrementing the learning factor c 1:
increment the learning factor c 2
The capacity optimization configuration of the hydrogen station hydrogen preparation-storage equipment is carried out by adopting an improved particle swarm algorithm, and the method comprises the following steps:
setting the rated power P el of the electrolytic tank, the rated capacity Q S of the hydrogen storage tank and the rated hydrogen production rate H ref of the reformer as optimization variables, taking the minimum objective function value of the total net present value cost C npc of the total life cycle of the hydrogen addition station as a fitness function, and dynamically adjusting the inertia weight and the learning factor after obtaining individual and global optimal results so as to update the speed and the position of particles; the optimal capacity configuration result is obtained through multiple iterations of the distributed renewable unit output, the electric hydrogen load demand, the constraint condition and the electric hydrogen joint scheduling strategy; the specific calculation steps are shown in fig. 4.
Wherein, the constraint conditions are as follows:
Power balance ：PL(t)＝PWT(t)+PPV(t)+Phyd(t)-Pel(t)+Pgd(t),Pgd(t)＝μPbuy(t)-(1-μ)Psell(t),μ takes 0 or 1;
Cell power constraint: p el(t)≤Pel.max is more than or equal to 0;
reformer hydrogen production constraint: h ref(t)≤Href.max is more than or equal to 0;
Hydrogen storage tank state constraints ：SSHmin≤SSH(t)≤SSHmax,QS(t)＝QS(t-Δt)+Hel(t)Δt+Href(t)Δt-HSo(t)Δt.
The invention relies on the resource endowment advantages of great Sichuan clean energy provinces, is practical, responds to the government to construct a renewable energy electrolysis hydrogen production and storage integrated hydrogen station policy in a hydrogen energy leading industry functional area, and researches the hydrogen production of a distributed wind power unit, a photovoltaic unit and a small water motor unit in different places to meet the capacity optimization configuration problem of hydrogen production/storage equipment of a hydrogen station for a fuel cell bus in a city A, thereby avoiding the phenomena of 'wind abandon', 'light abandon' and 'water abandon' of a micro-grid and solving the hydrogen load demand. By researching a micro-grid-hydrogen adding station system, a residual electricity hydrogen making-green hydrogen advanced electricity hydrogen combined dispatching strategy is proposed on the basis of the output of a distributed renewable unit according to the maximum power, and a capacity optimizing configuration model of the hydrogen making/adding equipment with the aim of lowest total net present value cost of the total life cycle of the hydrogen adding station is established. Finally, the rationality and the effectiveness of the configuration model are verified by collecting the field machine set and the load data of the county B and the city A and carrying out the example simulation by using an improved particle swarm algorithm, and the sensitivity analysis of the price of electricity to home, hydrogen and natural gas of the hydrogen station is carried out.
Aiming at the phenomena of wind discarding, light discarding and water discarding of a micro-grid and the increasing hydrogen load demand, the invention considers that the hydrogen storage equipment with certain capacity is configured at the off-site hydrogen station to consume residual electricity of the distributed renewable unit. Firstly, researching a mathematical model of a micro-grid-hydrogenation station system on the basis of the output of a wind power unit, a photovoltaic unit and a small water motor unit and the hydrogen production/storage characteristics of an electrolytic tank, a hydrogen storage tank and a reformer; secondly, an electricity-hydrogen joint scheduling strategy is provided to coordinate electricity and hydrogen load demands, and constraints such as power balance, hydrogen production rate, hydrogen storage state and the like of a target with the lowest total net present value cost of the total life cycle of the hydrogen addition station are considered, so that a capacity optimizing configuration model of hydrogen production/storage equipment is established; and finally, carrying out example simulation by collecting the field units and load data of the county B and the city A. The calculation result shows that the electric-hydrogen joint scheduling strategy provided by the method can efficiently utilize residual electricity of the distributed renewable unit in the researched micro-grid-hydrogenation station system to prepare green hydrogen, thereby reducing renewable resource waste, reducing pollutant emission and obtaining additional hydrogen selling benefits; the established algorithm has higher convergence and searching capability, so that the objective function is minimized; meanwhile, as can be seen from sensitivity analysis, fluctuations in the price of electricity to home, hydrogen and natural gas from the hydrogen addition station can change the capacity configuration result and affect the total net present value cost and green hydrogen permeability of the total life cycle of the hydrogen addition station.
The sensitivity analysis of the invention finds that the fluctuation of the price of electricity to the house, hydrogen and natural gas from the hydrogenation station has a larger influence on the NPC and green hydrogen permeability of the hydrogenation station, and the slope of the increasing/decreasing curve of the NPC and green hydrogen permeability can be correspondingly changed due to the change of the capacity configuration result of the hydrogen preparation/storage equipment.
The research result of the invention can provide support for the configuration of the residual hydrogen production capacity of the micro-grid and the economic analysis.
The micro-grid-hydrogen adding station system is used as an analysis object, and is formed by a micro-grid-hydrogen adding station system consisting of a wind power unit, a photovoltaic unit, a small hydroelectric generating set, a local electric load of the B county, a hydrogen load of a fuel cell bus of the A city and hydrogen adding station manufacturing/hydrogen adding equipment, and electric power is transmitted through a power grid in two places. In the example simulation, average weather and hydrologic data of the year of the county B, a local electric load curve of the day of the county B and a hydrogen load curve of the day of the fuel cell bus of the city A in a certain park are obtained. The service life of the hydrogen adding station is 25 years, the actual survival rate is 6%, and the initial hydrogen storage state of the hydrogen storage tank is 0.5. The method comprises the steps of obtaining operation parameters of a distributed renewable unit in a system, fuel price and regional electricity price, pollutant emission produced by natural gas hydrogen production, punishment coefficient and environmental value of the pollutant emission, hydrogen production/storage equipment parameters, construction cost of a hydrogen station and government subsidy. In addition, according to literature, the efficiency of the water electrolysis hydrogen production apparatus increases rapidly with an increase in input power, and the peak value of the efficiency is about 0.6, and then gradually decreases to the vicinity of 0.5. The hydrogen density is 0.0899kg/m 3, and the electrolysis efficiency is 0.0175kg/kWh after calculation; the hydrogen production process of the natural gas reforming at the present stage needs to consume 0.48m 3 of raw material natural gas and 0.12m 3 of fuel natural gas for producing 1m 3 of hydrogen. The natural gas density is 0.7174kg/m3, and the working efficiency of the reformer is 0.21kg/kg after conversion.
(1) Capacity optimization configuration result:
TABLE 1 Capacity optimal configuration results
TABLE 2 cost benefit statement
The results of the capacity optimization configuration of the hydrogen station production/storage equipment are shown in table 1, and the cost benefit details are shown in table 2. After the life cycle of 25 years is finished, the net present cost is negative, namely the income of the representative project reaches more than 1 hundred million and 3 kilo-thousand yuan, which proves that the project has considerable economy and high return on investment. In the cost, the construction cost, the replacement cost and the natural gas hydrogen production emission penalty occupy larger amounts, and especially when equipment needs to be replaced, the government does not provide subsidy any more and the time node is closer to the service life of the hydrogen station, so that the present value of the time node is higher than the present value of the construction cost; of the benefits, the environmental value and the hydrogen selling benefits are considerable, because the current commercial hydrogen selling price is high, the policy and fund support is high, and the emission of pollutants is greatly reduced by using green hydrogen to meet the hydrogen load demand.
The change in the NPC of the hydrogenation station with the life cycle is shown in FIG. 5. With the advancement of life cycle, NPC is continuously reduced, and profitability is started in 8 th year, replacement costs are generated in 9 th and 18 th years due to the fact that the hydrogen production/storage equipment is required to be replaced due to the service life of the hydrogen production/storage equipment, but the residual value of the hydrogen production/storage equipment at the end of the life cycle of the hydrogen station can create benefits.
(2) Output condition of hydrogen production/storage equipment:
The annual average output curves of the distributed renewable units and the hydrogen production/storage equipment are shown in fig. 6, 7, 8 and 9. It can be seen that the output of the B county distributed renewable unit is in a state of more spring and summer and less autumn and winter due to the influence of wind speed, illumination intensity, temperature and water diversion flow of the hydropower station, so that the residual electricity hydrogen production of the electrolytic cell is also more spring and summer and less autumn and winter. Especially, when the power supply is changed in spring and summer, the power supply is in a high water period, the wind speed and the illumination intensity are also very abundant, and the output of the distributed renewable unit often exceeds the local electric load demand, so that an electrolytic tank with enough capacity is required to be arranged, and the residual electricity is fully utilized to prepare green hydrogen, and the green hydrogen is stored in a hydrogen storage tank with enough capacity; the autumn and winter season is in the dead water period, the illumination intensity and the temperature are also greatly reduced, the output of the distributed renewable unit and the residual electricity of the electrolytic tank are limited, and then the reformer with enough capacity is required to prepare blue hydrogen to supplement the hydrogen load shortage.
(3) Improved particle swarm algorithm convergence process:
as shown in fig. 10, the improved particle swarm algorithm is compared with the convergence process of the conventional algorithm, and it can be seen that by improving the inertia weight and the learning factor, the convergence of the algorithm is improved and the searching capability of the algorithm is improved compared with the conventional algorithm, so that the speed and direction of particles are better controlled, thereby avoiding sinking into local optimum, and the objective function value is truly minimized.
(4) Sensitivity analysis
In the micro-grid-hydrogen adding station system, the price of electricity to the home, hydrogen and natural gas of the hydrogen adding station are closely related to the total net present value cost and income of the total life cycle of the hydrogen adding station, so that the NPC and the green hydrogen permeability of the hydrogen adding station are affected. As the electrical load and hydrogen load demands change, changes in the hydrogen plant to home price, fluctuations in hydrogen and natural gas prices, and the resulting capacity configuration of the hydrogen production/storage facility must be considered. The invention controls the price of electricity to house, hydrogen and natural gas of the hydrogenation station to be adjusted between 0.5 to 1.5 times of the price standard of the annex, and the consequent change of NPC and green hydrogen permeability of the hydrogenation station is shown in figures 11, 12 and 13.
As can be seen from FIG. 11, as the household price increases, the NPC of the hydrogenation station increases and the green hydrogen permeability decreases, and the slope of the former curve decreases and the slope of the latter curve increases. This is due to the increased electricity costs of the hydrogen plant caused by fluctuations in the household price and the greater propensity of the hydrogen dispatch stage to use reformers to produce hydrogen to meet hydrogen loads, thereby reducing the electrolyzer and hydrogen storage tank capacity configurations.
As can be seen from fig. 12, as the hydrogen price increases, the NPC of the hydrogen station decreases and the green hydrogen permeability increases, and the slope of the former curve decreases and the slope of the latter curve increases. This is due to the increased sales of hydrogen due to fluctuations in hydrogen price and the increased capacity configuration of the electrolyzer and hydrogen storage tanks, which is more prone to green hydrogen production by the electrolyzer during the power dispatch stage and hydrogen dispatch stage using green hydrogen to meet hydrogen load.
As can be seen from fig. 13, as the price of natural gas increases, the NPC and green hydrogen permeability of the hydrogen addition station increase continuously, and the slope of the former curve decreases gradually and the slope of the latter curve increases gradually. This is due to the increased fuel costs caused by natural gas price fluctuations and the greater propensity of the hydrogen scheduling stage to use green hydrogen to meet hydrogen loading, thereby reducing reformer capacity configurations.
The foregoing has shown and described the basic principles and main features of the present invention and the advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (7)
1. A hydrogen station equipment capacity optimization configuration method based on micro-grid surplus electricity hydrogen production is characterized by comprising the following steps:
s10, building output models of a wind turbine, a photovoltaic turbine and a hydroelectric turbine, and obtaining output power of the wind turbine, the photovoltaic turbine and the small hydroelectric turbine;
S20, a power dispatching strategy for residual electricity hydrogen production is established according to the sum of the output power of the wind power unit, the photovoltaic unit and the small hydropower unit and the local electric load, residual electricity of the distributed renewable unit including the wind power unit, the photovoltaic unit and the small hydropower unit is conveyed to a hydrogenation station for preparing green hydrogen by an electrolytic tank, and the input power of the electrolytic tank under various working conditions is calculated and obtained;
S30, calculating the hydrogen production rate of the electrolytic cell by utilizing a hydrogen production model of the electrolytic cell according to the input power of the electrolytic cell; calculating a hydrogen storage model of the hydrogen storage tank to obtain a hydrogen storage quantity range of the hydrogen storage tank;
s40, a hydrogen scheduling strategy of green hydrogen advance is established according to the hydrogen storage amount and the comparison between the local hydrogen load and the hydrogen storage amount range of the hydrogen storage tank, green hydrogen prepared by using an electrolytic cell to consume micro-grid surplus electricity is used for meeting the hydrogen load, the deficient part is supplemented by blue hydrogen prepared by a reformer, and the hydrogen production rate of the reformer and the hydrogen output rate of the hydrogen storage tank are obtained;
s50, calculating the hydrogen storage amount based on the hydrogen production rate of the reformer and the hydrogen output rate of the hydrogen storage tank; substituting the fuel into a reformer hydrogen production model to obtain the fuel consumption rate of the reformer;
S60, establishing a capacity optimization configuration model of hydrogen production and storage equipment of the hydrogen production station according to the target with the lowest total net present value cost of the total life cycle of the hydrogen production station and the constraints of the power balance, the hydrogen production rate and the hydrogen storage state, and solving by using an improved particle swarm algorithm to finish capacity optimization configuration;
The method comprises the steps of substituting an electrolyzer hydrogen production model H el＝ηel·Pel into the electrolyzer input power P el (t) and the electrolyzer electrolysis efficiency eta el to calculate the electrolyzer hydrogen production rate H el (t);
Hydrogen storage model adopting hydrogen storage tank Substituting the lower limit SSH min and the upper limit SSH max of the hydrogen storage state, the gas constant R S, the temperature T S of the hydrogen storage tank, the volume V S of the hydrogen storage tank, the molecular weight N H2 of hydrogen and the pressure P S.max of the maximum hydrogen storage tank to calculate the highest hydrogen storage quantity Q S.max and the lowest hydrogen storage quantity Q S.min of the hydrogen storage tank;
Comparing the hydrogen storage quantity Q S (t-deltat) of the last time step, the hydrogen load Q L (t) of the city A of the current time step with the calculated highest hydrogen storage quantity Q S.max and the calculated lowest hydrogen storage quantity Q S.min of the hydrogen storage tank;
when the green hydrogen stored in the hydrogen storage tank is enough to supply the hydrogen load of the current time step for use when the last time step is finished, the green hydrogen is completely supplied by the hydrogen storage tank without the participation of a reformer in hydrogen production;
When the green hydrogen stored in the hydrogen storage tank is insufficient for supplying the hydrogen load of the current time step for use at the end of the previous time step, the hydrogen storage tank needs to be subjected to the blue hydrogen preparation by reforming natural gas to supplement the deficiency;
Calculating the hydrogen production rate H ref (t) of the reformer at the current time step, and calculating the hydrogen output rate H So (t) of the hydrogen storage tank at the current time step;
Adopting a hydrogen storage quantity iteration update formula Q S(t)＝QS(t-Δt)+Hel(t)Δt+Href(t)Δt-HSo (t) delta t, substituting the hydrogen production rate H el (t) of the electrolytic cell, the hydrogen production rate H ref (t) of the current time step reformer and the hydrogen output rate H So (t) of the current time step hydrogen storage tank, and calculating the hydrogen storage quantity Q S (t) of the current time step;
Obtaining the hydrogen storage quantity Q S of the full-period hydrogen storage tank and the hydrogen production rate H ref of the full-period reformer through repeated iteration;
The reformer hydrogen production model H ref＝ηref·Gfuel was used to calculate the reformer fuel consumption rate G fuel by substituting the full period reformer hydrogen production rate H ref and the reformer operating efficiency η ref.
2. The hydrogen station equipment capacity optimization configuration method based on micro-grid surplus electricity hydrogen production according to claim 1, which is characterized by comprising the following steps of:
Step 1: using wind speed conversion formula Substituting the wind speed V anem (t) of the wind meter, the wind turbine hub height Z hub, the wind meter height Z anem and the surface roughness a to calculate the wind speed V hub (t) of the wind turbine hub;
Step 2: using a wind turbine output model:
a＝PSTP/(Vr 3-Vci 3)，
b＝Vci 3/(Vr 3-Vci 3)；
Substituting the calculated hub wind speed V hub (t), the cut-in wind speed V ci, the rated wind speed V r, the cut-out wind speed V co and the rated output power P STP of the force turbine to calculate the output power P WT (t) of the wind turbine.
3. The hydrogen station equipment capacity optimization configuration method based on micro-grid surplus electricity hydrogen production as claimed in claim 1, wherein the construction of the output model of the photovoltaic unit comprises the following steps:
Using a photovoltaic array output model:
Tc＝Ta+λGT；
Substituting a solar radiation value G T (T), an ambient temperature T a (T), a rated capacity P STC of the photovoltaic array, a derating factor f PV of the photovoltaic array, solar radiation G T.STC incident on the photovoltaic array under standard test conditions, a power temperature coefficient beta, a photovoltaic cell temperature T c of a current time step, a photovoltaic cell temperature T c.STC under standard test conditions and a radiation temperature coefficient lambda, and calculating the output power P PV (T) of the photovoltaic unit.
4. The hydrogen station equipment capacity optimization configuration method based on micro-grid surplus electricity hydrogen production as claimed in claim 1, wherein the construction of the output model of the hydroelectric generating set comprises the following steps:
Using a water turbine output model:
Substituting the water diversion flow q (t), the water turbine efficiency eta hyd, the water tightness rho water, the gravity acceleration g and the water purification head h to calculate the output power P hyd (t) of the small hydroelectric generating set.
5. The hydrogen station equipment capacity optimization configuration method based on micro-grid residual electricity hydrogen production according to any one of claims 1-4, wherein the power scheduling strategy of residual electricity hydrogen production comprises the following steps:
Comparing the sum of the output power of the wind power unit, the photovoltaic unit and the small hydropower unit with a local electric load to ensure that the net electric load delta P (t) =P L(t)-[PWT(t)+PPV(t)+Phyd (t) ], and judging the positive and negative of the net electric load delta P (t) =P L(t)-[PWT(t)+PPV(t)+Phyd (t);
When deltap (t) =0, the local electric load is just matched with wind power, photovoltaic and hydroelectric power, and at the moment, water electrolysis hydrogen production and transaction with a power grid do not occur;
when delta P (t) >0, the part with insufficient local electric load demand is supplemented by purchasing electricity from the power grid;
when delta P (t) is less than 0, preferentially using an electrolytic tank to consume the redundant power generation amount of the distributed renewable unit; if the absolute value of the net electric load does not exceed the rated power of the electrolytic cell, the input power of the electrolytic cell is equal to the absolute value of the net electric load; if the absolute value of the net electric load exceeds the rated power of the electrolytic cell, the electrolytic cell absorbs electric energy according to the rated power, and the balance is consumed by selling electricity to a power grid;
and calculates the input power P el (t) of the electrolytic cell.
6. The hydrogen station equipment capacity optimization configuration method based on micro-grid surplus electricity hydrogen production, which is characterized by establishing a hydrogen station hydrogen production-storage equipment capacity optimization configuration model according to the target with the lowest total net present value cost of the total life cycle of the hydrogen station and the constraints of power balance, hydrogen production rate and hydrogen storage state, solving by using an improved particle swarm algorithm, and completing capacity optimization configuration;
step 1: calculating initial construction cost C cs, annual cost C cos and annual income C in of the hydrogenation station according to the output power of the obtained wind turbine generator, photovoltaic turbine generator and hydroelectric turbine generator, the hydrogen production/storage amount of the electrolytic tank, the hydrogen storage tank and the reformer, electric hydrogen load data, turbine generator parameters, unit price, pollutant and environmental value parameters and government subsidies;
step 2: the total net present value cost calculation formula of the full life cycle is adopted:
Cann＝Ccos-Cin；
Substituting the initial construction cost C cs, the annual cost C cos, the annual income C in, the actual discount rate i, the life cycle annual y and the service life R proj of the hydrogen addition station to obtain the total net present value cost C npc of the total life cycle of the hydrogen addition station.
7. The hydrogen station equipment capacity optimization configuration method based on micro-grid surplus electricity hydrogen production of claim 6, wherein the improved particle swarm algorithm is as follows:
Initial value c 2s and final value c 2e of maximum inertial weight ω max, initial value c 1s and final value c 1e,c2 of maximum number of iterations k max、c1 are substituted;
non-linear decrementing of the inertial weight ω:
Decrementing the learning factor c 1:
increment the learning factor c 2
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