CN113327180B - Low-carbon economic dispatching method and system for electric power system considering hydrogen energy application - Google Patents
Low-carbon economic dispatching method and system for electric power system considering hydrogen energy application Download PDFInfo
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- 229910052739 hydrogen Inorganic materials 0.000 title claims abstract description 238
- 239000001257 hydrogen Substances 0.000 title claims abstract description 238
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 title claims abstract description 237
- 229910052799 carbon Inorganic materials 0.000 title claims abstract description 181
- 238000000034 method Methods 0.000 title claims abstract description 79
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 claims abstract description 135
- 238000003860 storage Methods 0.000 claims abstract description 135
- 238000012544 monitoring process Methods 0.000 claims abstract description 74
- 239000000446 fuel Substances 0.000 claims abstract description 48
- 230000008569 process Effects 0.000 claims abstract description 47
- 238000006243 chemical reaction Methods 0.000 claims abstract description 41
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims abstract description 31
- 238000010248 power generation Methods 0.000 claims description 21
- 238000005868 electrolysis reaction Methods 0.000 claims description 20
- 238000009826 distribution Methods 0.000 claims description 19
- 238000005265 energy consumption Methods 0.000 claims description 9
- 238000004519 manufacturing process Methods 0.000 claims description 8
- 238000004364 calculation method Methods 0.000 claims description 5
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 26
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 12
- 229910002092 carbon dioxide Inorganic materials 0.000 description 6
- 230000005611 electricity Effects 0.000 description 6
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- 238000004458 analytical method Methods 0.000 description 3
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- 150000002431 hydrogen Chemical class 0.000 description 3
- 239000003345 natural gas Substances 0.000 description 3
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- 238000011161 development Methods 0.000 description 1
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- 239000002803 fossil fuel Substances 0.000 description 1
- 239000013067 intermediate product Substances 0.000 description 1
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- 238000006386 neutralization reaction Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000000284 resting effect Effects 0.000 description 1
- 230000009919 sequestration Effects 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
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- H02J15/00—Systems for storing electric energy
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
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- H02J3/381—Dispersed generators
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- H—ELECTRICITY
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
- H02J3/466—Scheduling the operation of the generators, e.g. connecting or disconnecting generators to meet a given demand
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- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
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- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2300/00—Systems for supplying or distributing electric power characterised by decentralized, dispersed, or local generation
- H02J2300/20—The dispersed energy generation being of renewable origin
- H02J2300/28—The renewable source being wind energy
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Abstract
The invention relates to a low-carbon economic dispatching method and a system of an electric power system considering hydrogen energy application, wherein the method comprises the following steps: the method aims at the minimum total running cost of the system, and aims at an electrolyzed water process model, a space-time network model, state variables of each time span of a transport vehicle, a carbon capture power plant model, a carbon storage device model and a methanation reaction model, a fuel cell power and hydrogen consumption relation model and monitoring point atmosphere CO caused by a thermal power plant 2 And determining a low-carbon economic dispatch model by taking the concentration as a constraint condition. The invention can improve the utilization efficiency of new energy and realize the low carbon property of the power system.
Description
Technical Field
The invention relates to the field of low-carbon economic dispatching of electric power systems, in particular to a low-carbon economic dispatching method and system of an electric power system considering hydrogen energy application.
Background
The 'carbon reaching peak, carbon neutralization' targets lead and accelerate the energy revolution, and the electric power becomes a main terminal energy source for supporting economic development and civil improvement, and in the future, the continuous improvement of the new energy duty ratio, energy conservation and emission reduction are important work in the electric power industry for a long time. At present, thermal power generation is still a main power generation mode in China, and CO generated by burning fossil fuel 2 Has bad influence on climate and environment. Under the background, searching for clean energy carriers and exploring a low-carbon economic dispatching method of an electric power system has important significance.
The increasing energy demand in the future will be met by higher energy utilization efficiency and more clean renewable energy sources such as wind energy, solar energy. However, the intermittent nature of renewable energy sources causes power supply and demand mismatch, which presents challenges for grid economic operation. Taking wind power as an example, the peak period of output power of a wind power plant generally occurs at night, and the power system is in the period of low electricity consumption, so that the supply and demand time is longThe mismatch of (2) results in a significant amount of wind curtailment in the system. The prior art proposes to convert surplus wind power into natural Gas by using an electric Gas conversion technology (Powerto Gas, ptG), which provides an effective way for the absorption of wind power, but omits PtG technology to be divided into 2 stages, wherein the first stage generates hydrogen by electrolyzing water, and the second stage is a methanation process, namely generating hydrogen and CO from the electrolyzed water under the action of a catalyst 2 The reaction produces methane and water. The electrolysis efficiency can reach 85%, the efficiency of the whole process of converting wind power into natural gas is not higher than 60%, the energy utilization efficiency is indirectly reduced by directly converting wind power into natural gas, and the methanation raw material CO is not considered in the prior art 2 Resulting in higher reaction costs and poorer technical economics. The energy saving and emission reduction potential of the intermediate product hydrogen of the PtG technology is not fully utilized, and the low carbon property of the technology is insufficient. In addition, the existing low-carbon economic dispatching research is often optimized from the angle of reducing the total carbon emission, such as considering the carbon emission quota of a thermal power plant, setting carbon emission punishment in economic cost, and establishing a single-target economic dispatching model or taking carbon emission as an optimization target to form a multi-target low-carbon dispatching model. But CO of thermal power plant 2 The effect of emissions on the environment is not only related to the total amount of emissions, but also to CO 2 Diffusion process in atmosphere and CO for different environments 2 The concentration bearing capacity is related to the fact that insufficient or excessive control of the generator set is easily generated only from the standpoint of controlling the total amount of carbon emission, and the low carbon property of the system is also one-sided.
Disclosure of Invention
The invention aims to provide a low-carbon economic dispatching method and system for an electric power system, which consider the application of hydrogen energy, so as to improve the utilization efficiency of new energy and realize the low-carbon property of the electric power system.
In order to achieve the above object, the present invention provides the following solutions:
a low-carbon economic dispatch method for an electric power system considering hydrogen energy application, comprising:
Generating hydrogen by utilizing wind power electrolysis water in a wind power plant, and determining an electrolysis water process model;
modeling the transportation process of the hydrogen by adopting a space-time network model, and determining the state variable of each time span of the transportation vehicle;
scheduling a carbon capture system and a methanation device according to the state variable of each time span of the transport vehicle, and determining a carbon capture power plant model, a carbon storage device model and a methanation reaction model;
generating power by using a fuel cell according to the state variable of each time span of the transport vehicle, and determining a relation model of the power generated by the fuel cell and hydrogen consumption;
acquiring the atmospheric CO of the monitoring point caused by the thermal power plant within the set monitoring time 2 Concentration;
the method aims at the minimum total running cost of the system, and aims at the electrolyzed water process model, the space-time network model, the state variable of each time span of the transport vehicle, the carbon capture power plant model, the carbon storage device model, the methanation reaction model, the relation model of the power generation and hydrogen consumption of the fuel cell and the monitoring point atmospheric CO caused by the thermal power plant 2 And determining a low-carbon economic dispatch model by taking the concentration as a constraint condition.
Optionally, the modeling the transportation process of the hydrogen by using a space-time network model, after determining the state variable of each time span of the transportation vehicle, further includes:
And determining a hydrogen storage model of the hydrogen storage station according to the state variable of each time span of the transport vehicle.
Optionally, the hydrogen storage model of the hydrogen storage station is:
wherein ,for the volume of hydrogen stored in hydrogen storage station i at time t,/>For t-1 time in hydrogen station iHydrogen volume of>For the hydrogen storage station i hydrogen storage volume maximum at time t,/->The hydrogen storage volume of the hydrogen storage station i at the moment t is the minimum value;for the transport at time t, the volume of hydrogen in hydrogen storage station i is varied, < >>An upper limit value for enabling the hydrogen volume in the hydrogen storage station i to be transported once for the transportation at the moment t; />The rate of hydrogen generation for the electrolyzer in the hydrogen storage station i at time t,/>For the rate of consumption of hydrogen by the methanation device in the hydrogen storage station i at time t,/-, is provided>For the hydrogen consumption rate of the fuel cell unit in the hydrogen storage station i at time t, Δt is the scheduling time interval, +.>For the connection of the transport vehicle k to the hydrogen storage station i over the time span s.
Optionally, the acquiring monitoring point is in the monitoring time, and the monitoring point is atmospheric CO caused by the thermal power plant 2 The concentration specifically comprises:
acquiring CO caused by a thermal power unit within a set monitoring time of a monitoring point 2 Concentration space-time distribution;
according to CO caused by the thermal power generating unit 2 When the concentration time-space distribution condition determines that the monitoring points are set to discharge in the set time Setting the sum of concentration contributions discharged by the thermal power unit;
determining the atmospheric CO of the monitoring point caused by the thermal power plant according to the sum of concentration contributions of the thermal power unit discharged by the monitoring point in the set time and the set discharge period 2 Concentration.
Optionally, the water electrolysis process model is:
wherein ,electric power is input to the electrolyzer at time t +.>The volume of hydrogen generated at the moment of the electrolytic tank t; />Representing a wind power output predicted value; η (eta) EL Electrolysis efficiency, < >>Is the power-to-volume conversion coefficient of hydrogen.
Optionally, a calculation formula of the state variable of each time span of the transport vehicle is as follows:
wherein i and j represent the serial numbers of different hydrogen storage stations, k is the serial number of the transport vehicle, s is the time span, ij represents the space-time network arcs from i station to j station, A is the set of arcs in TSN,for the set of arcs starting from station i, +.>NS is the total number of time spans, which is the set of arcs ending at station i; />Representing the connection state of transport vehicle k to arc ij over time span s, +.>For the connection state of transport vehicle k to arc ij over time span s+1, +.>For the connection state of transport vehicle k with arc ij on time span 1, +.>Representing the initial state of a kth transport vehicle in the station i; />Indicating the final status of the kth transport vehicle in the station +. >The connection state of the transport vehicle k to the arc ij is scheduled for the last time span NS in the scheduling period.
Optionally, the carbon capture power plant model is:
wherein ,for the original output power of the thermal power plant u at the time t, namely, the output power of the thermal power plant before introducing CCS, < ->Net output of plant u at time t for carbon capture,/->The method comprises the steps that the energy consumption of carbon capture equipment of a carbon capture power plant u at a moment t is basically reduced; />CO at time t for carbon capture plant u 2 Production amount (amount of production)>CO at time t of carbon capture power plant u 2 Trapping amount(s)>CO at time t for carbon capture plant u 2 Net emissions; alpha is the trapping unit CO 2 Energy consumption, e is unit power CO of power plant 2 Emission intensity, gamma is CO of carbon capture power plant 2 The trapping rate of (2) is in the range of (0, 1).
A low-carbon economic dispatch system for an electrical power system that considers hydrogen energy applications, comprising:
the water electrolysis process model determining module is used for generating hydrogen by utilizing wind power electrolysis water in the wind power plant and determining a water electrolysis process model;
the state variable determining module is used for modeling the transportation process of the hydrogen by adopting a space-time network model and determining the state variable of each time span of the transport vehicle;
the carbon capture power plant model, the carbon storage device model and the methanation reaction model determining module is used for scheduling a carbon capture system and a methanation device according to the state variable of each time span of the transport vehicle to determine the carbon capture power plant model, the carbon storage device model and the methanation reaction model;
The fuel cell power generation and hydrogen consumption relation model determining module is used for generating power by using a fuel cell according to the state variable of each time span of the transport vehicle and determining a fuel cell power generation and hydrogen consumption relation model;
the acquisition module is used for acquiring the monitoring point at the set monitoring timeIn, the atmosphere CO at the monitoring point caused by the thermal power plant 2 Concentration;
the low-carbon economic dispatch model determining module is used for aiming at the minimum total running cost of a system, and aiming at the electrolyzed water process model, the space-time network model, the state variable of each time span of the transport vehicle, the carbon capture power plant model, the carbon storage device model, the methanation reaction model, the relation model of the power generation power and the hydrogen consumption of the fuel cell and the monitoring point atmospheric CO caused by the thermal power plant 2 And determining a low-carbon economic dispatch model by taking the concentration as a constraint condition.
Optionally, the method further comprises:
and the hydrogen storage station hydrogen storage model determining module is used for determining a hydrogen storage station hydrogen storage model according to the state variable of each time span of the transport vehicle.
Optionally, the acquiring module specifically includes:
CO caused by thermal power generating unit 2 A concentration space-time distribution condition acquisition unit for acquiring CO caused by the thermal power generating unit in the set monitoring time of the monitoring points 2 Concentration space-time distribution;
a sum determining unit for setting concentration contribution of thermal power unit emission by setting emission period of monitoring point in set time, which is used for determining CO caused by the thermal power unit 2 Determining the sum of concentration contributions of the monitoring points in the set time, which is set in the set emission period, and the thermal power unit emission;
monitoring point atmosphere CO caused by thermal power plant 2 A concentration determining unit for determining the atmospheric CO of the monitoring point caused by the thermal power plant according to the sum of concentration contributions of the thermal power unit discharged by the monitoring point in the set time for setting the discharge period 2 Concentration.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a low-carbon economic dispatching method of an electric power system considering hydrogen energy application, which takes hydrogen generated by surplus wind power in the system as a flexible energy carrier to coordinate and dispatch wind power output, carbon capture, methanation and fuel electricityIn the step of generating power in a pool, the level of the renewable energy consumption and the energy utilization efficiency are improved, and the atmospheric CO is utilized 2 Concentration is one of the most limiting conditions to reduce CO 2 The concentration is harmful to the environment of the monitoring point, thereby realizing the low-carbon operation of the power system.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a low-carbon economic dispatching method of an electric power system considering hydrogen energy application;
fig. 2 is a schematic diagram of a low-carbon economic dispatching system of an electric power system considering hydrogen energy application.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a low-carbon economic dispatching method and system for an electric power system, which consider the application of hydrogen energy, so as to improve the utilization efficiency of new energy and realize the low-carbon property of the electric power system.
The economic dispatch means that under the condition of meeting the electricity demand of customers, various technical measures and management measures are adopted to ensure that the power production equipment is in the optimal working state, thereby achieving the lowest cost of the power system.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
As shown in fig. 1, the low-carbon economic dispatching method for the electric power system considering the application of hydrogen energy provided by the invention comprises the following steps:
step 101: and (3) utilizing wind power to electrolyze water to generate hydrogen in the wind power plant, and determining an electrolyzed water process model.
Wherein, the water electrolysis process model is:
wherein ,electric power is input to the electrolyzer at time t +.>The volume of hydrogen generated at the moment of the electrolytic tank t; />Representing a wind power output predicted value; η (eta) EL Electrolysis efficiency, < >>Is the power-to-volume conversion coefficient of hydrogen.
Step 102: modeling the transportation process of the hydrogen by adopting a space-time network model, and determining the state variable of each time span of the transportation vehicle. The calculation formula of the state variable of each time span of the transport vehicle is as follows:
wherein i and j represent the serial numbers of different hydrogen storage stations, k is the serial number of the transport vehicle, s is the time span, ij represents the space-time network arcs from i station to j station, A is the set of arcs in TSN, For the set of arcs starting from station i, +.>NS is the total number of time spans, which is the set of arcs ending at station i; />Representing the connection state of transport vehicle k to arc ij over time span s, +.>For the connection state of transport vehicle k to arc ij over time span s+1, +.>For the connection state of transport vehicle k with arc ij on time span 1, +.>Representing the initial state of a kth transport vehicle in the station i; />Indicating the final status of the kth transport vehicle in the station +.>The time span is the connection state of the transport vehicle k and the arc ij on the NS, and specifically the last time span NS in the scheduling period.
Step 103: and scheduling the carbon capture system and the methanation device according to the state variable of each time span of the transport vehicle, and determining a carbon capture power plant model, a carbon storage device model and a methanation reaction model. Wherein, the carbon capture power plant model is:
wherein ,for the original output power of the thermal power plant u at the time t, namely, the output power of the thermal power plant before introducing CCS, < ->Net output of plant u at time t for carbon capture,/->The method comprises the steps that the energy consumption of carbon capture equipment of a carbon capture power plant u at a moment t is basically reduced; />CO at time t for carbon capture plant u 2 Production amount (amount of production)>CO at time t of carbon capture power plant u 2 Trapping amount(s) >CO at time t for carbon capture plant u 2 Net emissions; alpha is the trapping unit CO 2 Energy consumption, e is unit power CO of power plant 2 Emission intensity, gamma is CO of carbon capture power plant 2 The trapping rate of (2) is in the range of (0, 1).
Step 104: and generating power by using a fuel cell according to the state variable of each time span of the transport vehicle, and determining a relation model of the power generated by the fuel cell and hydrogen consumption.
Step 105: acquiring the atmospheric CO of the monitoring point caused by the thermal power plant within the set monitoring time 2 Concentration. Step 105 specifically includes:
acquiring CO caused by a thermal power unit within a set monitoring time of a monitoring point 2 Concentration space-time distribution.
According to CO caused by the thermal power generating unit 2 And determining the concentration time-space distribution condition, wherein the concentration time-space distribution condition determines the sum of concentration contributions of the thermal power unit discharged by the monitoring points in the set time and the set discharge period.
Setting discharge in a set time according to the monitoring pointDetermining the atmosphere CO of a monitoring point caused by a thermal power plant by setting the sum of concentration contributions discharged by a thermal power unit in a time period 2 Concentration.
Step 106: the method aims at the minimum total running cost of the system, and aims at the electrolyzed water process model, the space-time network model, the state variable of each time span of the transport vehicle, the carbon capture power plant model, the carbon storage device model, the methanation reaction model, the relation model of the power generation and hydrogen consumption of the fuel cell and the monitoring point atmospheric CO caused by the thermal power plant 2 And determining a low-carbon economic dispatch model by taking the concentration as a constraint condition.
In practical application, the modeling the transportation process of the hydrogen by adopting the space-time network model, after determining the state variable of each time span of the transportation vehicle, further comprises:
and determining a hydrogen storage model of the hydrogen storage station according to the state variable of each time span of the transport vehicle.
Wherein, the hydrogen storage station hydrogen storage model is:
wherein ,for the volume of hydrogen stored in hydrogen storage station i at time t,/>For the volume of hydrogen stored in the hydrogen storage station i at time t-1, +.>For the hydrogen storage station i hydrogen storage volume maximum at time t,/->The hydrogen storage volume of the hydrogen storage station i at the moment t is the minimum value;for the transport at time t, the volume of hydrogen in hydrogen storage station i is varied, < >>An upper limit value for enabling the hydrogen volume in the hydrogen storage station i to be transported once for the transportation at the moment t; />The rate of hydrogen generation for the electrolyzer in the hydrogen storage station i at time t,/>For the rate of consumption of hydrogen by the methanation device in the hydrogen storage station i at time t,/-, is provided>For the hydrogen consumption rate of the fuel cell unit in the hydrogen storage station i at time t, Δt is the scheduling time interval, +.>For the connection of the transport vehicle k to the hydrogen storage station i over the time span s. The invention takes green hydrogen generated by surplus wind power in the system as a flexible energy carrier to coordinate and schedule links such as wind power output, carbon capture, methanation, fuel cell power generation and the like, and provides a low-carbon economic scheduling model of the power system considering hydrogen energy application. In addition, taking into account the position of the emission source and the change in meteorological conditions (wind speed, wind direction, etc.), a consideration of CO is constructed 2 Constraints on spatiotemporal distribution to reduce CO 2 The method fully digs the advantage of hydrogen as a flexible energy carrier, and improves the level of renewable energy consumption and the energy utilization efficiency. Furthermore, based on the position of the thermal power plant and CO 2 Analysis of diffusion paths and dynamic atmospheric conditions, accurate CO limitation at critical monitoring points 2 The space-time distribution of the concentration ensures the low-carbon operation of the system.
The invention also provides a specific step of the low-carbon economic dispatching method of the electric power system considering the application of hydrogen energy in practical application:
step 1: hydrogen is produced and transported to different hydrogen storage stations based on a space-time network model: the green hydrogen is generated by utilizing surplus wind power electrolyzed water in the system and stored in the hydrogen storage tank, and the green hydrogen is transported to different hydrogen stations by the hydrogen transportation vehicle, so that the hydrogen can participate in scheduling at different places at different times, and the space-time transfer endowment of the hydrogen energy is fully exerted.
Firstly, hydrogen is generated by utilizing surplus wind power electrolyzed water in a system near a wind power plant, and a mathematical model of the electrolyzed water process can be expressed as follows:
in the formula,Inputting electric power and the generated hydrogen volume into the electrolyzer t at the moment; />Representing a wind power output predicted value; η (eta) EL ，/>Power-to-volume conversion coefficients for electrolysis efficiency and hydrogen; the first term in equation (1) represents the conversion relationship between the input electric power and the output hydrogen volume in the electrolyzer; the second term indicates that the electric energy required for electrolysis is entirely supplied by wind power, which can ensure the low carbon nature of the hydrogen gas produced itself.
The hydrogen is concentrated near the wind farm and then stored in a hydrogen storage tank, then transported to other different hydrogen storage stations by a transport truck, and a Time-Space Network (TSN) model is used for modeling the hydrogen transportation process. The space-time network model determines the hourly status of the transport vehicle, which time period is on the way of transport from one hydrogen storage station to another, which time period remains at a hydrogen station for loading or unloading of hydrogen.
Wherein i, j respectively represent the serial numbers of different hydrogen storage stations, k is the serial number of a transport vehicle, s is the time span, ij represents the space-time network arcs from i station to j station, A is the set of arcs in TSN,for the set of arcs starting from station i, +.>NS is the total number of time spans, which is the set of arcs ending at station i; / >Representing the connection state of the transport vehicle k to the arc ij over the time span s,representing that the transport vehicle k is on the arc ij over the time span s, and the corresponding physical system represents that the transport vehicle k is traveling from the hydrogen storage station i to the hydrogen storage station j over the time span s; />Indicating that transport vehicle k is not on arc ij over time span s; />Indicating the initial status of the kth transport vehicle in the station +.>Indicating that the kth transport vehicle is initially at hydrogen storage station i, -, a->Indicating that the kth transport vehicle is not at the hydrogen storage station i at the initial moment; />Indicating the final status of the kth transport vehicle in the station +.>Indicating that the kth transport vehicle is at hydrogen storage station i,/at the final moment>Indicating that the kth transport vehicle is not at the hydrogen storage station i, < >>For the connection state of transport vehicle k with arc ij on time span 1, +.>The time span is the connection state of the transport vehicle k and the arc ij on the NS. The first term in equation (2) represents the vehicle k state constraints, i.e., each vehicle k can only lie on one arc in the time span s; the second term represents the transport vehicle k connection constraint, at the end of the time span s, transport vehicle k in station i is located in node (i, s) of the TSN, and in the next time span s+1 transport vehicle k must be located in an arc starting from node (i, s), meaning that the inflow and outflow of each node in the TSN must be equal; the third term represents the first time span, the outflow of each station being equal to the initial state of the transport vehicle k; the last term indicates that the inflow per station is equal to the final state of the transport vehicle k in the last time span NS.
Equation (2) is used to determine the state of the transporter, which corresponds to determining the path of the transporter and the stopping information at different hydrogen stations. This model is finalized and />Value of->Applied in formula (3), only +.>Indicating that the transport vehicle is resting at the hydrogen storage station i to be able to deliver hydrogen to or from the hydrogen storage station. />The 4 th formula of the formula (13) is used in the transportation cost of the step 4.
The TSN model can obtain the state variable of each time span of the transport vehicle ifIndicating that transport vehicle k is traveling from hydrogen storage station i to hydrogen storage station j over time span s, if +.>It means that the transport vehicle k stays at the ith hydrogen storage station for loading or unloading hydrogen gas all the time over the time span s. The hydrogen storage station hydrogen storage model may be expressed as:
in the formula,the hydrogen storage station i stores the maximum value and the minimum value of the hydrogen volume for the hydrogen volume stored in the hydrogen storage station i at the moment t; />The variation of the hydrogen volume in the hydrogen storage station i is realized for the transportation at the moment t, and the upper limit value of single transportation is realized; />The hydrogen generation rate of the electrolysis device in the hydrogen storage station i at the time t, the hydrogen consumption rate of the methanation device and the fuel cell are representedThe unit consumes hydrogen rate. The first term of the formula (3) represents the hydrogen volume change condition at the adjacent moment of the hydrogen storage station; the second term represents the upper and lower limit constraints of the hydrogen storage volume of the hydrogen storage station; the last item indicates the condition for exchanging hydrogen energy between the hydrogen storage station and the hydrogen carrier, i.e. at time t, the hydrogen tank can be loaded or unloaded only if the carrier k stays at the hydrogen station i, and the volume of the transported hydrogen should not exceed the allowable maximum value, when ∈ - >The time indicates that the transport vehicle is carrying hydrogen into the hydrogen storage station i,/->Indicating that the transport vehicle is carrying hydrogen from the hydrogen storage station i.
Step 2: and the hydrogen is used as an energy carrier to coordinate and schedule the carbon capture system, the methanation device and the fuel cell unit, so that the flexibility of the system is fully exerted: introducing a carbon trapping system into a traditional thermal power plant, and trapping CO discharged by the thermal power plant by the carbon trapping system when the thermal power unit works 2 Trapped CO 2 Part of the raw materials are stored in carbon storage equipment to provide raw materials for subsequent methanation reaction; methane plant utilizes electrolytically generated hydrogen and CO stored in a carbon storage facility or captured in the atmosphere 2 Performing methanation reaction to realize a negative carbon effect; during peak system electrical load, the fuel cell converts hydrogen energy to electrical energy for supplying a portion of the electrical load. The hydrogen generated and transported in step 1 participates in two processes in step 2, one with CO 2 Takes part in methanation reaction together, the reaction is completed in a methanation device, wherein the raw material CO of the methanation reaction 2 CO captured by a carbon capture system of a thermal power plant 2 And CO captured from the atmosphere 2 This process may coordinate the scheduling of the carbon capture system and methanation devices; and secondly, during the peak period of the electric load of the system, the fuel cell converts hydrogen energy into electric energy to provide clean electric power for the system. The carbon capture system and the methanation device can cooperatively operate to meet the requirements of low-carbon economy of the power system, and CO captured by the carbon capture system 2 Is used for methanation reaction process, reduces CO 2 Raw material cost, also canReduction of trapped CO 2 The sealing quantity is reduced, thereby reducing CO 2 Sealing and storing cost; the fuel cell power generation can replace part of thermal power, so that the power generation cost is reduced, and the carbon emission is also indirectly reduced. According to the principle of realizing low-carbon economic dispatching of the system, the two processes can be carried out at the same time. The following are respectively constructed as a carbon capture process, a methanation process and a mathematical model of the fuel cell unit:
the carbon capture system (Carbon Capture System, CCS) includes a carbon capture power plant (Carbon Capture Power Plant, CCPP) by introducing CCS in a conventional thermal power plant using 3 processes of capture and sequestration. The carbon trapping process may be somewhat independent of the power generation process, and the trapping efficiency of the carbon trapping device is no longer limited to only one proportion but one range. Before carbon capture, the original output power still accords with the conventional thermal power characteristics, and a conventional power plant can be regarded as a carbon capture power plant with the carbon capture efficiency of 0. Before introducing CCS, the thermal power plant unit output constraint can be expressed by a formula (4):
in the formula,for the original output power of the thermal power plant u at the time t, namely, the output power of the thermal power plant before introducing CCS, < - >For the original output power of thermal power plant u at t-1, < > of>The upper limit and the lower limit of the output power are respectively; RD (RD) u ，RU u The maximum downward landslide rate and the maximum upward climbing rate of the thermal power unit u are represented. The first term of the formula (4) represents upper and lower limit constraints of output power of the thermal power generating unit; the second term represents the climbing constraint of the thermal power generating unit.
After introducing CCS, the model of CCPP can be expressed as:
in the formula,the method comprises the steps of dividing the net output power of a carbon capture power plant u at the time t, and basically consuming energy by carbon capture equipment;CO at time t for carbon capture plant u 2 Production, capture and net emissions; alpha is the trapping unit CO 2 Energy consumption, e is unit power CO of power plant 2 Emission intensity, gamma is CO of carbon capture power plant 2 The trapping rate of (2) is in the range of (0, 1). The first term of equation (5) represents a carbon capture plant power balance constraint; the second term represents carbon capture plant CO 2 The relation between the generated quantity and the output power; the third term represents CO 2 The trapping amount should not exceed the maximum amount that can be trapped; the last term represents carbon capture plant CO 2 The net emissions are equal to the difference between the generated and captured amounts.
CO captured by the carbon capture system 2 Part of the CO is temporarily stored in the carbon storage device, and the CO in the carbon storage device is stored when needed 2 Can be reacted with hydrogen in a methanation unit to form methane. The purpose of introducing the carbon storage device is CO 2 The capture process may occur throughout the dispatch period, while methane is only synthesized when there is excess wind power in the system, so CO 2 Time mismatch of generation and consumption by introducing CO 2 The storage facility can solve the problem and ensure the CO required by methanation reaction 2 Partially or fully provided by the carbon capture system, reduces CO 2 The raw material cost also improves the utilization level of the wind power of the system. The model of the carbon storage device is as follows:
in the formula,CO in the carbon storage device at the moment t respectively 2 Storage volume, CO in carbon storage device 2 Maximum, minimum storage; />CO is provided for the carbon capture system at the moment t to the carbon storage device 2 The rate, the carbon storage device supplies CO of methanation reaction 2 Rate and carbon storage device for supplying methanation CO 2 Maximum rate. />CO in carbon storage device at t-1 moment 2 The first term of equation (6) represents the adjacent time CO in the carbon storage device 2 A volume change relationship; the second term represents CO in the carbon storage device 2 The volume should not exceed the upper and lower limits of the capacity of the carbon storage device; the third term represents the CO provided by the carbon capture system to the carbon storage device 2 The amount of CO captured by the carbon capture system should not be exceeded 2 An amount of; the last item represents the carbon storage device supplying CO for methanation reaction 2 The rate of the carbon dioxide is not greater than the maximum CO of the carbon storage device 2 And an output rate.
CO stored in a carbon storage device by a carbon capture system 2 Or CO trapped from the atmosphere 2 Together with the hydrogen in the hydrogen storage station, the hydrogen consumed by the process is supplied by the hydrogen storage station in the step 1 transportation model, and the methanation reaction mathematical model can be expressed as:
in the formula,hydrogen and CO consumed by methanation reaction at time t respectively 2 A rate of methane formation; />η ME ，/>Hydrogen and CO in methanation process respectively 2 Reaction coefficient ratio, methane generator conversion efficiency, methane power volume conversion coefficient; />CO captured from the atmosphere during methanation at time t, respectively 2 Rate, maximum hydrogen input rate. The first term of equation (7) represents hydrogen and CO that participate in the methanation reaction 2 Volume relation; the second term represents the volume of hydrogen consumed by the methanation reaction in relation to the volume of methane produced, wherein +.>The first term of equation (3) is presented; the third item represents the CO consumed by the methanation process 2 CO captured by carbon capture process and from the atmosphere 2 Two-part composition, wherein->The first term of equation (6) is presented; the fourth term represents CO captured from the atmosphere 2 The volume is more than or equal to 0; the last term means that the hydrogen input rate to the methanation unit should not be greater than the maximum hydrogen input rate allowed by the methanation unit.
The fuel cell unit is arranged at a node close to the electricity load center, when the system has a load peak, the electricity load can be supplied to the part through the electricity generation of the fuel cell, so that the electricity generation amount of a part of the thermal power unit can be reduced, the carbon emission caused by thermal power generation is reduced, and the hydrogen consumed by the fuel cell unit is supplied by the hydrogen storage station in the transportation model in the step 1. The relationship between the fuel cell power generation and the hydrogen consumption is as follows:
in the formula,the power generation power and the hydrogen consumption rate of the fuel cell at the moment t are respectively; η (eta) FC ，/>Fuel cell conversion efficiency, and maximum hydrogen input rate, respectively. The first term of equation (8) represents the relationship between the fuel cell hydrogen consumption rate and the electric energy generation rate; the second term indicates that the fuel cell hydrogen input rate should not exceed the maximum rate allowed.
Step 3: construction of critical monitoring points CO 2 Concentration constraint conditions, and situations of insufficient control or excessive control of the system on the generator set are avoided: CO discharged by the thermal power plant is considered by the condition changes such as the position, the wind speed, the wind direction and the like of the thermal power plant 2 Analysis of CO discharged from a thermal power plant by influence of diffusion paths in the atmosphere 2 Distribution in atmosphere and construction of CO at key monitoring points 2 And the concentration constraint condition is used for avoiding the condition that the system is in insufficient control or excessive control on the generator set. This step is the last term of equation (5) in analysis step 2, carbon capture plant CO 2 Net emissionsSpace-time distribution in the atmosphere and its CO in the atmosphere 2 The influence of the concentration can effectively control the carbon emission of the thermal power plant.
Firstly, calculating a monitoring point (x, y, z) and monitoring time t, and CO caused by a thermal power unit u 2 Concentration space-time distribution conditions:
in the formula,Mu,net (t ') represents CO discharged by u in t' period of thermal power plant 2 Amount of C u Representing the CO of the thermal power plant to the atmosphere 2 Concentration contribution, G u For distribution functions, ψ is an intermediate variable set for convenience of presentation, σ x (t’,t)，σ y (t’,t)，σ z (t ', t) represents CO discharged at time t', respectively 2 Diffusion parameters in x, y, z axis direction in t period, x u (t’,t)，y u (t’,t)，z u (t', t) is CO discharged at time t 2 At the center coordinates of the t period, (x u,0 ,y u,0 ) For the coordinate position of the generator u, z u,0 For its effective emission source height, [ v ] x (t)v y (t)v z (t)]For wind velocity vector, subscript μ represents x, y, z axis, a μ (t)、b μ (t) are constants related to the atmospheric stability level, respectively. t ' is a variable set for convenience in distinction from t, and t ' is not less than t, indicating the scheduling time after t ' is t. The first term of the formula (9) is used for calculating the emission quality M of the thermal power plant u in the period t net CO of (t') 2 CO at time period t for monitoring point (x, y, z) 2 Concentration contribution, where M net (t') is represented in the last term of equation (5).
Second item G u Is CO 2 A distribution function calculation formula in the atmosphere; thirdly, a calculation formula of an intermediate variable ψ; fourth term for calculating CO emissions 2 Center coordinates, which relate to discharge time and wind speed, wind direction; the last term is used for calculating CO 2 Diffusion parameters in air.
With CO emitted 2 The concentration of the smoke mass in the atmosphere is continuously reduced until the concentration is negligible, the concentration of a monitoring point is not influenced after W emission periods are released by the smoke mass, a NG station thermal power unit is arranged in the system, and the CO of the monitoring point j at the moment t is considered 2 The concentration is the sum of the concentration contributions of the discharge of the NG station thermal power generating unit in the first W discharge periods:
monitoring point atmosphere CO caused by emission of thermal power plant 2 The concentration constraint can be expressed as:
in the formula,for region j to CO 2 Concentration tolerance capability.
Step 4: constructing a low-carbon economic dispatching model of the electric power system considering hydrogen energy application: at the total operation cost of the system (including the fuel cost of the thermal power unit, the operation cost of the methanation process, the punishment cost of the system in wind disposal, the transportation cost of hydrogen and CO) 2 Transportation and storage costs) are minimum as an optimization target, and the related mathematical models constructed in the steps 1,2 and 3 are constraint conditions, namely, the formulas (1) and (11) are constraint conditions, so that the low-carbon economic operation of the system is realized.
The low-carbon economic dispatch model may be expressed as:
in the formula,Ctotal ，C fuel ，C ME ,C cur ,C tran ,Respectively representing the total operation cost of the system, the fuel cost of the thermal power unit, the operation cost of the methanation process, the wind disposal punishment cost, the hydrogen transportation cost and the storage cost after trapping;the method comprises the steps of respectively representing the output electric power of a carbon capture power plant u at the moment t, the actual power supply of a wind power plant w, the output electric power of a fuel cell unit f and the load of a load node d; n (N) CCPP ,N w ,N FC ,N D The number of carbon capture power plants, the number of wind farms, the number of fuel cell units and the number of load nodes in the system are respectively represented. P (P) ij,min For the minimum active power flow of the line ij,P ij for the active power flow of line ij, P ij,max Is the maximum active power flow of line ij. The constraint conditions comprise the third system power balance constraint in the formula (12) and the last line active power flow constraint besides the formulas (1) - (11).
The detailed expression of each term cost in the first project label function of the formula (12) is:
in the formula,au ，b u ，c u Is a fuel cost coefficient of a thermal power plant; c air ，c g ，λ e ，c k,ij ，c cs To capture the cost of CO2 per unit volume from the atmosphere, the benefit of selling methane per unit volume, the penalty of per unit power wind disposal, the cost of hydrogen single transport, and the cost of CO2 transport and storage per unit volume.CO2 rate and methane rate generated by methanation device m from the atmosphere at time t respectively, +. > The u CO2 capture amount of the carbon capture power plant at time t and the CO2 amount supplied to the methanation device are respectively.
As shown in fig. 2, the low-carbon economic dispatching system of the electric power system considering hydrogen energy application provided by the invention comprises:
an electrolyzed water process model determining module 201, configured to generate hydrogen by using wind power electrolyzed water in a wind farm, and determine an electrolyzed water process model;
the state variable determining module 202 of each time span of the transport vehicle is configured to model the transportation process of the hydrogen by using a space-time network model, and determine the state variable of each time span of the transport vehicle;
the carbon capture power plant model, the carbon storage device model and the methanation reaction model determining module 203 is used for scheduling a carbon capture system and a methanation device according to the state variable of each time span of the transport vehicle to determine a carbon capture power plant model, a carbon storage device model and a methanation reaction model;
the fuel cell power generation and hydrogen consumption relation model determining module 204 is configured to determine a fuel cell power generation and hydrogen consumption relation model by generating power by using a fuel cell according to a state variable of each time span of the transport vehicle;
an acquisition module 205 for acquiring the atmospheric CO of the monitoring point caused by the thermal power plant in the set monitoring time 2 Concentration;
a low-carbon economic dispatch model determining module 206, configured to target a minimum total running cost of the system, and target the electrolyzed water process model, the space-time network model, the state variable of each time span of the transport vehicle, the carbon capture power plant model, the carbon storage device model, the methanation reaction model, the relation model of the power generated by the fuel cell and the hydrogen consumption, and the monitoring point atmospheric CO caused by the thermal power plant 2 And determining a low-carbon economic dispatch model by taking the concentration as a constraint condition.
In practical application, the method further comprises the following steps:
and the hydrogen storage station hydrogen storage model determining module is used for determining a hydrogen storage station hydrogen storage model according to the state variable of each time span of the transport vehicle.
In practical application, the obtaining module 205 specifically includes:
CO caused by thermal power generating unit 2 A concentration space-time distribution condition acquisition unit for acquiring CO caused by the thermal power generating unit in the set monitoring time of the monitoring points 2 Concentration space-time distribution;
a sum determining unit for setting concentration contribution of thermal power unit emission by setting emission period of monitoring point in set time, which is used for determining CO caused by the thermal power unit 2 Determining concentration time-space distribution condition, and setting emission time period of concentration time-space distribution condition monitoring points in set time to set concentration of thermal power unit emission Sum of the degree contributions;
monitoring point atmosphere CO caused by thermal power plant 2 A concentration determining unit for determining the atmospheric CO of the monitoring point caused by the thermal power plant according to the sum of concentration contributions of the thermal power unit discharged by the monitoring point in the set time for setting the discharge period 2 Concentration.
Aiming at the problems of energy conservation and emission reduction of the electric power system and safe and economic operation of the electric power system caused by new energy power fluctuation, the method provided by the invention takes green hydrogen generated by surplus wind power in the system as a flexible energy carrier, carries out transportation and optimal configuration through a transportation network, coordinates and schedules a carbon capture system, a methanation device and a fuel cell power generation unit, comprehensively considers the position of an emission source and the change of weather conditions to CO 2 Influence of concentration space-time distribution, accurate limit of CO at key monitoring points 2 Concentration, ensure the low-carbon operation of the system. The method fully digs the advantage of taking hydrogen as a flexible energy carrier, improves the absorption level and the energy utilization efficiency of new energy, and ensures the low carbon property and the economy of the system.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (4)
1. A low-carbon economic dispatch method for an electric power system considering hydrogen energy application, comprising:
generating hydrogen by utilizing wind power electrolysis water in a wind power plant, and determining an electrolysis water process model;
modeling the transportation process of the hydrogen by adopting a space-time network model, and determining the state variable of each time span of the transportation vehicle;
scheduling a carbon capture system and a methanation device according to the state variable of each time span of the transport vehicle, and determining a carbon capture power plant model, a carbon storage device model and a methanation reaction model;
generating power by using a fuel cell according to the state variable of each time span of the transport vehicle, and determining a relation model of the power generated by the fuel cell and hydrogen consumption;
acquiring the atmospheric CO of the monitoring point caused by the thermal power plant within the set monitoring time 2 Concentration;
the method aims at the minimum total running cost of the system, and aims at the electrolyzed water process model, the space-time network model, the state variable of each time span of the transport vehicle, the carbon capture power plant model, the carbon storage device model, the methanation reaction model, the relation model of the power generation and hydrogen consumption of the fuel cell and the monitoring point atmospheric CO caused by the thermal power plant 2 Determining a low-carbon economic dispatch model by taking the concentration as a constraint condition;
modeling the transportation process of the hydrogen by adopting a space-time network model, and determining the state variable of each time span of the transportation vehicle further comprises the following steps:
determining a hydrogen storage model of a hydrogen storage station according to the state variable of each time span of the transport vehicle;
the hydrogen storage model of the hydrogen storage station is as follows:
wherein ,for the volume of hydrogen stored in hydrogen storage station i at time t,/>For the volume of hydrogen stored in the hydrogen storage station i at time t-1, +.>For the hydrogen storage station i hydrogen storage volume maximum at time t,/->The hydrogen storage volume of the hydrogen storage station i at the moment t is the minimum value; />For the transport at time t, the volume of hydrogen in hydrogen storage station i is varied, < >>An upper limit value for enabling the hydrogen volume in the hydrogen storage station i to be transported once for the transportation at the moment t; />The rate of hydrogen generation for the electrolyzer in the hydrogen storage station i at time t,/ >For the rate of consumption of hydrogen by the methanation device in the hydrogen storage station i at time t,/-, is provided>For the hydrogen consumption rate of the fuel cell unit in the hydrogen storage station i at time t, Δt is the scheduling time interval, +.>The connection state of the transport vehicle k and the hydrogen storage station i is over the time span s;
the acquisition monitoring point is in the monitoring time, and the atmospheric CO of the monitoring point is caused by the thermal power plant 2 The concentration specifically comprises:
acquiring the monitoring point at the set monitoring pointIn the time, CO caused by the thermal power generating unit 2 Concentration space-time distribution;
according to CO caused by the thermal power generating unit 2 Determining the sum of concentration contributions of the monitoring points in the set time, which is set in the set emission period, and the thermal power unit emission;
determining the atmospheric CO of the monitoring point caused by the thermal power plant according to the sum of concentration contributions of the thermal power unit discharged by the monitoring point in the set time and the set discharge period 2 Concentration;
the water electrolysis process model is as follows:
wherein ,electric power is input to the electrolyzer at time t +.>The volume of hydrogen generated at the moment of the electrolytic tank t; />Representing a wind power output predicted value; η (eta) EL Electrolysis efficiency, < >>Is the power-to-volume conversion coefficient of hydrogen;
the calculation formula of the state variable of each time span of the transport vehicle is as follows:
wherein i and j represent serial numbers of different hydrogen storage stations, k is serial number of a transport vehicle, s is time span, ij represents space-time network arc line from i station to j station, and A is The set of arcs in the TSN,for the set of arcs starting from station i, +.>NS is the total number of time spans, which is the set of arcs ending at station i; />Representing the connection state of transport vehicle k to arc ij over time span s, +.>For the connection state of transport vehicle k to arc ij over time span s+1, +.>For the connection state of transport vehicle k with arc ij on time span 1, +.>Representing the initial state of a kth transport vehicle in the station i; />Indicating the final status of the kth transport vehicle in the station +.>The connection state of the transport vehicle k and the arc ij on the time span NS;
the carbon capture power plant model is:
wherein ,for the original output power of the thermal power plant u at the time t, namely, the output power of the thermal power plant before introducing CCS, < ->Net output of plant u at time t for carbon capture,/->The method comprises the steps that the energy consumption of carbon capture equipment of a carbon capture power plant u at a moment t is basically reduced; />CO at time t for carbon capture plant u 2 Production amount (amount of production)>CO at time t of carbon capture power plant u 2 Trapping amount(s)>CO at time t for carbon capture plant u 2 Net emissions; alpha is the trapping unit CO 2 Energy consumption, e is unit power CO of power plant 2 Emission intensity, gamma is CO of carbon capture power plant 2 The trapping rate of (2) is in the range of (0, 1).
2. The electric power system low-carbon economic dispatching system considering hydrogen energy application is characterized in that the electric power system low-carbon economic dispatching system considering hydrogen energy application applies the electric power system low-carbon economic dispatching method considering hydrogen energy application according to claim 1, and the electric power system low-carbon economic dispatching system considering hydrogen energy application comprises:
The water electrolysis process model determining module is used for generating hydrogen by utilizing wind power electrolysis water in the wind power plant and determining a water electrolysis process model;
the state variable determining module is used for modeling the transportation process of the hydrogen by adopting a space-time network model and determining the state variable of each time span of the transport vehicle;
the carbon capture power plant model, the carbon storage device model and the methanation reaction model determining module is used for scheduling a carbon capture system and a methanation device according to the state variable of each time span of the transport vehicle to determine the carbon capture power plant model, the carbon storage device model and the methanation reaction model;
the fuel cell power generation and hydrogen consumption relation model determining module is used for generating power by using a fuel cell according to the state variable of each time span of the transport vehicle and determining a fuel cell power generation and hydrogen consumption relation model;
the acquisition module is used for acquiring the atmospheric CO of the monitoring point caused by the thermal power plant in the set monitoring time of the monitoring point 2 Concentration;
the low-carbon economic dispatch model determining module is used for aiming at the minimum total running cost of a system, and aiming at the electrolyzed water process model, the space-time network model, the state variable of each time span of the transport vehicle, the carbon capture power plant model, the carbon storage device model, the methanation reaction model, the relation model of the power generation power and the hydrogen consumption of the fuel cell and the monitoring point atmospheric CO caused by the thermal power plant 2 And determining a low-carbon economic dispatch model by taking the concentration as a constraint condition.
3. The hydrogen energy application considered power system low-carbon economic dispatch system of claim 2, further comprising:
and the hydrogen storage station hydrogen storage model determining module is used for determining a hydrogen storage station hydrogen storage model according to the state variable of each time span of the transport vehicle.
4. The low-carbon economic dispatch system for an electric power system considering hydrogen energy application of claim 2, wherein the obtaining module specifically comprises:
CO caused by thermal power generating unit 2 A concentration space-time distribution condition acquisition unit for acquiring CO caused by the thermal power generating unit in the set monitoring time of the monitoring points 2 Concentration space-time distributionA situation;
a sum determining unit for setting concentration contribution of thermal power unit emission by setting emission period of monitoring point in set time, which is used for determining CO caused by the thermal power unit 2 Determining the sum of concentration contributions of the monitoring points in the set time, which is set in the set emission period, and the thermal power unit emission;
monitoring point atmosphere CO caused by thermal power plant 2 A concentration determining unit for determining the atmospheric CO of the monitoring point caused by the thermal power plant according to the sum of concentration contributions of the thermal power unit discharged by the monitoring point in the set time for setting the discharge period 2 Concentration.
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