Optimized scheduling method for electro-hydrogen-ammonia integrated energy system from full life cycle perspective

Abstract

The invention provides an optimized scheduling method of an electric hydrogen ammonia comprehensive energy system from a full life cycle perspective. The method comprises the following steps: S1, building an electric hydrogen ammonia comprehensive energy system model; s2, performing full-life-cycle carbon emission evaluation on the electro-hydrogen-ammonia comprehensive energy system, and accurately acquiring all carbon emission data of the system in the full cycle; s3, introducing the carbon emission coefficient obtained in S2 into a carbon transaction model, and building a reward and punishment step carbon transaction mechanism model; s4, by taking the minimum total operation cost as an objective function, setting constraint conditions, and constructing an optimized dispatching model of the electro-hydrogen-ammonia integrated energy system; s5, modeling is carried out on the characteristics and probability distribution of the historical data, a distribution rule is described, and scene generation and reduction are carried out; and S6, solving the scheduling model to obtain an optimal scheduling result. The carbon emission of the system is analyzed from the perspective of the full life cycle, the energy utilization efficiency and the application proportion of renewable energy sources can be effectively improved, and low-carbon and sustainable development of the energy system is promoted.

Description

Technical Field

[0001] The present invention relates to the technical field of energy scheduling, and specifically to a method for optimizing scheduling of an electric, hydrogen and ammonia integrated energy system from a full life cycle perspective. Background Art

[0002] With the continuous growth of global energy demand and the improvement of environmental protection awareness, building an efficient and sustainable energy system has become the focus of current research. Traditional energy systems usually operate independently and lack coordination and complementarity, resulting in low energy efficiency and waste of resources. In this context, coupled systems such as electricity, heat, hydrogen, and ammonia have emerged. As a new type of energy system, the electric-hydrogen-ammonia integrated energy system combines the production and use of electricity, hydrogen, and ammonia. Through multi-energy complementarity, it effectively improves energy efficiency and the proportion of renewable energy application.

[0003] In multi-energy coupling systems, accurate accounting of carbon emissions is a prerequisite for scheduling optimization. Traditional energy system scheduling methods often ignore carbon emissions issues throughout the system's life cycle and are unable to fully assess the system's environmental impact.

[0004] Therefore, there is an urgent need for an optimization scheduling method for the integrated electricity, hydrogen and ammonia energy system from a full life cycle perspective to solve the above problems. Summary of the invention

[0005] The purpose of the present invention is to overcome the above-mentioned shortcomings and provide an optimization scheduling method for an electric, hydrogen and ammonia integrated energy system from a full life cycle perspective to solve the problems raised in the background technology.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: a method for optimizing the dispatching of an electric hydrogen ammonia integrated energy system from a full life cycle perspective, comprising the following steps: S1. Build an integrated energy system model of electricity, hydrogen and ammonia; S2. Conduct a full life cycle carbon emission assessment on the electricity, hydrogen and ammonia integrated energy system. On the basis of obtaining carbon emission data from the equipment operation stage, further introduce carbon emission data from production and construction, decommissioning and other stages to accurately obtain all carbon emission data of the system throughout the entire cycle; S3, introduce the carbon emission coefficient obtained in S2 into the carbon trading model, and introduce reward factors and punishment factors to build a reward and punishment ladder carbon trading mechanism model; S4. Taking the minimum sum of energy purchase cost, operation and maintenance cost, and carbon trading cost as the objective function, and taking renewable energy constraints, energy purchase constraints, energy coupling equipment safe operation constraints, energy storage constraints, gas grid interaction balance constraints, and electricity and heat balance constraints as constraints, an optimization scheduling model is constructed to limit the carbon emissions of the system; S5. Model the characteristics and probability distribution of historical data, describe the distribution law, and generate and reduce scenarios; S6. Initialize the CPLEX environment, define variables, objective functions, and constraints, use MATLAB to call the CPLEX commercial solver to solve and analyze the model, and obtain the optimal scheduling result.

[0007] Preferably, the step S1 is specifically: Build a detailed model of the electric, hydrogen and ammonia integrated energy system, which mainly includes the electric hydrogen production system model and the ammonia production plant model. The electric, hydrogen and ammonia integrated energy system mainly includes: energy supply units, energy conversion equipment, energy storage equipment and loads; the energy supply units include wind turbines, photovoltaic arrays, upstream power grids, upstream gas grids and upstream hydrogen grids; energy conversion equipment includes cogeneration devices, electrolyzers, hydrogen fuel cells and ammonia production plants; energy storage equipment includes electricity, heat and hydrogen energy storage equipment; the loads mainly include electricity, heat and hydrogen loads.

[0008] Preferably, the electric hydrogen production system model mainly includes an electrolyzer model, a hydrogen fuel cell model and a hydrogen storage tank model; the energy conversion efficiency of the electrolyzer model is about 75% to 85%, and its expression is:

[0009] Where: , are the input and output power of the electrolyzer during period t, is the energy conversion efficiency of the electrolyzer; The hydrogen fuel cell can convert the energy generated by hydrogen combustion into electrical energy output, and the model expression is:

[0010] Where: , They are t The input and output power of hydrogen fuel cells at all times. The power generation efficiency of the fuel cell; The hydrogen storage tank is used to store hydrogen generated by electrolysis of water in an alkaline electrolyzer, and can also provide hydrogen for hydrogen fuel cells to improve the flexibility of the system. The model expression is:

[0011] Where: for t The energy stored in the hydrogen tank at all times; , are the efficiency of the electrolyzer input to the hydrogen storage tank and the hydrogen storage tank output to the hydrogen fuel cell respectively; The working efficiency of the hydrogen storage tank; The maximum input power of the electrolyzer and the maximum output power of the hydrogen fuel cell are limited by their capacity and the remaining energy storage capacity of the hydrogen storage tank, which can be expressed as:

[0012]

[0013] Where: , are the capacities of the alkaline electrolyzer and hydrogen fuel cell, , are the upper and lower limits of the energy storage capacity of the hydrogen storage tank, respectively. =0.85 , =0.15 .

[0014] Preferably, the ammonia production plant synthesizes ammonia by using the Haber reaction between the hydrogen produced by the electrolyzer and the nitrogen, and the model calculation formula is as follows:

[0015]

[0016]

[0017]

[0018] Where: for t The thermal power provided by the ammonia plant during the period, , for t Input and output power of the ammonia production plant during the time period, is the ammonia production efficiency, The proportion of heat released to heat the ammonia production equipment, is the heat power released per unit mass of ammonia, for t The mass of ammonia generated during the period, , They are the maximum and minimum input power of the ammonia plant respectively.

[0019] Preferably, the step S2 is specifically: S2.1. Define the system boundary. The boundary of the electricity, hydrogen and ammonia integrated energy system includes the following parts: electricity production, hydrogen production, ammonia synthesis, energy conversion and storage, transportation and distribution, and terminal use; S2.2. Data collection and analysis: Detailed data collection and analysis of carbon emissions at each stage, including data on direct carbon emissions and indirect carbon emissions; S2.3. Full life cycle analysis, including: life cycle inventory analysis, life cycle impact assessment, and result interpretation.

[0020] Preferably, the step S3 is specifically: S3.1. Determine carbon emission quotas and baselines, set the system's initial carbon emission quotas, and allocate them based on historical emission data or industry standards; S3.2, the introduction of carbon emission data, from the full life cycle carbon emission assessment in step S2, the carbon emission coefficients of each link in the system can be obtained, including the carbon emission coefficients of transportation and distribution, the carbon emission coefficients of electricity production, etc., so as to obtain the actual carbon emissions; S3.3. The reward-and-penalty tiered carbon trading mechanism divides carbon emission levels into several intervals, each of which corresponds to a different carbon emission price. It also introduces compensation coefficients and penalty coefficients to encourage companies to take different emission reduction measures at different carbon emission levels.

[0021] Preferably, the objective function in step S4 is:

[0022] Where: is the total system operating cost, , , They are system energy purchase cost, operation and maintenance cost, and carbon trading cost; The operating costs of each part are as follows:

[0023] Where: , They are t Moment Energy A The unit purchase price and purchase quantity; , They are t Time equipment B output power and unit operation and maintenance costs.

[0024] Preferably, the constraints in step S4 include renewable energy constraints, energy purchase constraints, energy coupling equipment safety operation constraints, energy storage constraints, gas grid interaction balance constraints, electricity and heat balance constraints, etc. The renewable energy constraint expression is as follows:

[0025] Where: , They are the upper limits of wind power and photovoltaic output power respectively; The energy purchase constraint expression is:

[0026] Where: , They are t The amount of electricity purchased at the moment and the upper limit of electricity purchase, , They are t The gas purchase volume and purchase limit at the moment, , They are t The amount of hydrogen purchased at the time and the upper limit of hydrogen purchase; The energy coupling equipment safety operation constraints mentioned above mainly involve: cogeneration units, ammonia plants, electrolyzers and hydrogen fuel cells. The output power of the coupling equipment must meet the equipment capacity constraints. At the same time, considering the response speed of the energy conversion process and the rapid power change that will lead to equipment operation safety problems, the output power must also meet the ramp constraint, which is expressed as follows:

[0027] Where: Energy coupling equipment i exist t The output power at the moment, For equipment i The output power limit is , Equipment i The upper and lower limits of climbing power; The energy storage constraint expression is as follows:

[0028] Where: express t The energy stored in the energy storage device at all times, , Respectively t The charging and discharging power of the energy storage device at all times, , Respectively represent the charging and discharging efficiency of the energy storage device, , are the energy stored in the energy storage device at the start and end of the scheduling period, , Respectively represent the upper and lower limits of charging power, , Indicates the upper and lower limits of the energy release power. Represents a 0-1 variable, when =1 indicates charging state. =0 indicates energy release state; The gas network balance constraint expression is as follows:

[0029] Where: for t Natural gas consumed by the cogeneration unit at any given moment; The hydrogen network balance constraint expression is as follows:

[0030] Where: for t The amount of hydrogen produced by the electrolyzer at the moment, for t The hydrogen consumption of hydrogen fuel cells at each moment, for t The hydrogen storage capacity of the hydrogen storage tank at any given moment, for t The hydrogen consumption of the ammonia plant system at any given moment; The electrical and thermal power balance constraint expressions are as follows:

[0031] Where: , They are electrical load and thermal load respectively.

[0032] Preferably, the step S5 is specifically as follows: by modeling the characteristics and probability distribution of historical data to describe its distribution law, and further generating typical scenarios through random sampling, and finally using the scenario reduction method to remove duplicate scenarios for optimization and scheduling.

[0033] The present invention has the following beneficial effects: 1. Based on the life cycle theory, the present invention takes the electric hydrogen ammonia integrated energy system as the research object, calculates the carbon emissions of the system throughout its life cycle, and combines it with the reward and punishment ladder carbon trading mechanism to further guide the carbon emissions of the system, thereby building an optimized scheduling model for the electric hydrogen ammonia integrated energy system, and then models the characteristics and probability distribution of historical data, generates and reduces scenarios, generates typical scheduling scenarios, and finally solves the model to obtain the optimal scheduling plan; 2. The present invention takes into account the carbon emissions during the production and construction, equipment operation, and decommissioning stages of the system from a full life cycle perspective, which can overcome the limitation of traditional methods that only consider the operation stage and accurately characterize the carbon emissions of the system; 3. The present invention combines the carbon emission coefficient of the system's entire life cycle with the reward and punishment ladder carbon trading mechanism, which can effectively guide the system's carbon emissions and achieve refined carbon management; 4. The present invention introduces an ammonia production plant into the traditional integrated energy system, which can realize the diversified utilization of hydrogen energy, effectively reduce the carbon emissions and total operating costs of the system, and realize the low-carbon economic operation of the electricity-hydrogen-ammonia integrated energy system. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a flow chart of the optimization scheduling method of the present invention; Figure 2 This is a structural block diagram of the electric hydrogen ammonia integrated energy system of the present invention; Figure 3 This is a flow chart of the full life cycle analysis of the electricity, hydrogen and ammonia integrated energy system of the present invention; Figure 4 Generate and reduce flow charts for the scenarios of the present invention; Figure 5 This is the electric power balance diagram of the present invention; Figure 6 This is the thermal power balance diagram of the present invention; Figure 7 This is a scheduling result analysis diagram of the present invention. DETAILED DESCRIPTION

[0035] The present invention will be further described below in conjunction with the accompanying drawings and embodiments: See also Figures 1 to 7 , an optimization scheduling method for an electric, hydrogen and ammonia integrated energy system from a full life cycle perspective, comprising the following steps: S1. Build an integrated energy system model of electricity, hydrogen and ammonia; S2. Conduct a full life cycle carbon emission assessment on the electricity, hydrogen and ammonia integrated energy system. On the basis of obtaining carbon emission data from the equipment operation stage, further introduce carbon emission data from production and construction, decommissioning and other stages to accurately obtain all carbon emission data of the system throughout the entire cycle; S3, introduce the carbon emission coefficient obtained in S2 into the carbon trading model, and introduce reward factors and punishment factors to build a reward and punishment ladder carbon trading mechanism model; S4. Taking the minimum sum of energy purchase cost, operation and maintenance cost, and carbon trading cost as the objective function, and taking renewable energy constraints, energy purchase constraints, energy coupling equipment safe operation constraints, energy storage constraints, gas grid interaction balance constraints, and electricity and heat balance constraints as constraints, an optimization scheduling model is constructed to limit the carbon emissions of the system; S5. Model the characteristics and probability distribution of historical data, describe the distribution law, and generate and reduce scenarios; S6. Initialize the CPLEX environment, define variables, objective functions, and constraints, use MATLAB to call the CPLEX commercial solver to solve and analyze the model, and obtain the optimal scheduling result.

[0036] Preferably, the step S1 is specifically: Construct a detailed model of an electric, hydrogen and ammonia integrated energy system, which mainly includes an electric hydrogen production system model and an ammonia production plant model. The electric, hydrogen and ammonia integrated energy system mainly includes: energy supply units, energy conversion equipment, energy storage equipment and loads; the energy supply units include wind turbines, photovoltaic arrays, upper-level power grids, upper-level gas grids and upper-level hydrogen grids; energy conversion equipment includes cogeneration devices, electrolyzers, hydrogen fuel cells and ammonia production plants; energy storage equipment includes energy storage equipment for electricity, heat and hydrogen; the loads mainly include electricity, heat and hydrogen loads. Step S1, construct an electric, hydrogen and ammonia integrated energy system including electric hydrogen production and ammonia production plants, which mainly includes wind turbines, photovoltaic arrays, cogeneration devices, energy storage equipment, electric hydrogen production and ammonia production plants, and construct mathematical models respectively; The output power of wind turbine generator mainly depends on the cut-in and cut-out wind speed, and its model calculation formula is as follows:

[0037] Where: is the output power of the fan, is the rated power of the fan, For the cut-in wind speed, To cut out the wind speed, V is the rated wind speed, for t The actual wind speed at the moment; The actual power generation of the photovoltaic panel at time t is mainly affected by the solar radiation intensity and ambient temperature. The model calculation model is as follows:

[0038] Where: is the number of photovoltaic panels in the photovoltaic array, is the rated power of a photovoltaic panel under standard conditions, is the attenuation coefficient, for t The actual light intensity at the moment, is the light intensity under standard environment, k is the power temperature coefficient, For photovoltaic panels t The actual temperature at the moment, is the standard ambient temperature; In addition, the actual temperature of the photovoltaic panel is determined by the ambient temperature and the actual light intensity, and its expression is as follows:

[0039] Where: is the actual ambient temperature; The model expression of the combined heat and power unit is as follows:

[0040]

[0041] Where: , for t The electrical power and thermal power output of CHP at any moment, , is the energy conversion efficiency and heat-to-electricity ratio of CHP, for t The power consumption of CHP natural gas at the moment; The energy storage system model expression is as follows:

[0042]

[0043] Where: for t The energy stored in electrical and thermal energy storage at all times, , are the charging and discharging power of electrical energy storage and thermal energy storage respectively, , are the charging and discharging efficiencies of electrical energy storage and thermal energy storage, respectively, which are both set to 90% in the present invention. is the time step, and the present invention takes 1h.

[0044] Preferably, the electric hydrogen production system model mainly includes an electrolyzer model, a hydrogen fuel cell model and a hydrogen storage tank model; the energy conversion efficiency of the electrolyzer model is about 75% to 85%, and its expression is:

[0045] Where: , are the input and output power of the electrolyzer during period t, is the energy conversion efficiency of the electrolyzer; The hydrogen fuel cell can convert the energy generated by hydrogen combustion into electrical energy output, and the model expression is:

[0046] Where: , They are t The input and output power of hydrogen fuel cells at all times. The power generation efficiency of the fuel cell; The hydrogen storage tank is used to store hydrogen generated by electrolysis of water in an alkaline electrolyzer, and can also provide hydrogen for hydrogen fuel cells to improve the flexibility of the system. The model expression is:

[0047] Where: for t The energy stored in the hydrogen tank at all times; , are the efficiency of the electrolyzer input to the hydrogen storage tank and the hydrogen storage tank output to the hydrogen fuel cell respectively; The working efficiency of the hydrogen storage tank; The maximum input power of the electrolyzer and the maximum output power of the hydrogen fuel cell are limited by their capacity and the remaining energy storage capacity of the hydrogen storage tank, which can be expressed as:

[0048]

[0049] Where: , are the capacities of the alkaline electrolyzer and hydrogen fuel cell, , are the upper and lower limits of the energy storage capacity of the hydrogen storage tank, respectively. =0.85 , =0.15 .

[0050] Preferably, the ammonia production plant synthesizes ammonia by using the Haber reaction between the hydrogen produced by the electrolyzer and the nitrogen, and the model calculation formula is as follows:

[0051]

[0052]

[0053]

[0054] Where: for t The thermal power provided by the ammonia plant during the period, , for t Input and output power of the ammonia production plant during the time period, is the ammonia production efficiency, The proportion of heat released to heat the ammonia production equipment, is the heat power released per unit mass of ammonia, for t The mass of ammonia generated during the period, , They are the maximum and minimum input power of the ammonia plant respectively.

[0055] Preferably, the step S2 is specifically: S2.1. Define the system boundary. The boundary of the electricity, hydrogen and ammonia integrated energy system includes the following parts: electricity production, hydrogen production, ammonia synthesis, energy conversion and storage, transportation and distribution, and terminal use; S2.2. Data collection and analysis: Detailed data collection and analysis of carbon emissions at each stage, including data on direct carbon emissions and indirect carbon emissions; S2.3. Full life cycle analysis, including: life cycle inventory analysis, life cycle impact assessment, and result interpretation. Analyze different energy chains of the electricity, hydrogen and ammonia integrated energy system and calculate the carbon emissions of the system: The carbon emission assessment model for the coal chain throughout its life cycle is as follows:

[0056]

[0057]

[0058]

[0059] Where: , , , They are the carbon emission coefficients of coal production, transportation, and combustion stages and the total carbon emission coefficient of coal-fired power generation. η is the coal conversion efficiency, , are the unit energy consumption and emission coefficient in the production stage, α is the raw coal loss rate per unit of electricity caused by natural factors during the production stage, β It indicates the raw coal loss rate per unit of electricity in the production process of raw coal washing, crushing, etc. I The main modes of coal transportation are railway, waterway and road. A collection of transportation fuels, mainly diesel, electricity, and gasoline. For transportation i Fuel used j The energy intensity of For transportation i Fuel used j Greenhouse gases produced k The carbon equivalent emission factor, To use fuel j No. i The proportion of mileage by mode of transport, , For the i Total coal transport volume and average transport mileage by type of transport, is the standard coal consumption per unit of electricity supply, The first k Carbon equivalent emission factors of greenhouse gases; The carbon emission model of the natural gas chain throughout its life cycle is as follows:

[0060]

[0061]

[0062]

[0063] Where: , , , They are the carbon emission coefficients of natural gas extraction, transportation, and use, and the total carbon emission coefficient of natural gas power generation. Greenhouse gas i The carbon emission conversion factor is Greenhouse gas i The emission intensity of is the natural gas escape rate during the production phase, is the carbon emission intensity of natural gas, , are the carbon emission coefficients of pipeline transportation and liquefied transportation, is the pipeline transport proportion; is the carbon emission coefficient per unit power supply of the cogeneration unit, is the conversion factor of heat to electricity, The carbon emission coefficient per unit heat supply of the gas unit; The carbon emission model of the new energy chain throughout its life cycle is as follows:

[0064]

[0065]

[0066] Where: , , They are the transportation stage, the carbon emission coefficient of production and construction, and the total carbon emission coefficient of new energy power generation. θ Conversion coefficient of unit standard electricity and energy consumption, Materials for the transport phase i The carbon intensity of transportation used, Materials for the transport phase i The energy intensity of transport, , Production stage materialsi Carbon emission intensity and energy content per unit, Materials for the construction phase i The loss coefficient, , Respectively j Materials required for the construction phase i Carbon emission intensity and energy content per unit.

[0067] Preferably, the step S3 is specifically: S3.1. Determine carbon emission quotas and baselines, set the system's initial carbon emission quotas, and allocate them based on historical emission data or industry standards; S3.2, the introduction of carbon emission data, from the full life cycle carbon emission assessment in step S2, the carbon emission coefficients of each link in the system can be obtained, including the carbon emission coefficients of transportation and distribution, the carbon emission coefficients of electricity production, etc., so as to obtain the actual carbon emissions; S3.3, the reward and punishment ladder carbon trading mechanism divides the carbon emission level into several intervals, each interval corresponds to a different carbon emission price, and introduces compensation coefficients and punishment coefficients to encourage enterprises to take different emission reduction measures at different carbon emission levels. The carbon emission sources in the carbon emission quota mainly include upstream power purchases and cogeneration devices, and it is assumed that the upstream power purchases all come from coal-fired power generation units. The calculation model is as follows:

[0068]

[0069]

[0070] Where: , , They are the initial carbon emission quotas for the integrated energy system, upstream power purchases, and cogeneration units. for t Purchase electricity at all times. , for t The efficiency of heat and electricity production in the cogeneration unit at all times, , are the carbon emission quotas per unit of electricity and per unit of heat, is the electrothermal conversion coefficient; The actual carbon emission accounting model is as follows:

[0071]

[0072]

[0073] Where: The actual carbon emissions of the electricity, hydrogen and ammonia integrated energy system. , , They are the actual carbon emissions of the coal chain, natural gas chain and new energy chain; The reward and punishment ladder carbon trading model is as follows:

[0074] Where: is the carbon trading cost, is the carbon trading base price, , are the compensation and punishment coefficients respectively, l is the length of the carbon emission interval.

[0075] Preferably, the objective function in step S4 is:

[0076] Where: is the total system operating cost, , , They are system energy purchase cost, operation and maintenance cost, and carbon trading cost; The operating costs of each part are as follows:

[0077] Where: , They are t Moment Energy A The unit purchase price and purchase quantity; , They are t Time equipment B output power and unit operation and maintenance costs.

[0078] Preferably, the constraints in step S4 include renewable energy constraints, energy purchase constraints, energy coupling equipment safety operation constraints, energy storage constraints, gas grid interaction balance constraints, electricity and heat balance constraints, etc. The renewable energy constraint expression is as follows:

[0079] Where: , They are the upper limits of wind power and photovoltaic output power respectively; The energy purchase constraint expression is:

[0080] Where: , They are t The amount of electricity purchased at the moment and the upper limit of electricity purchase, , They are t The gas purchase volume and purchase limit at the moment, , They are t The amount of hydrogen purchased at the time and the upper limit of hydrogen purchase; The energy coupling equipment safety operation constraints mentioned above mainly involve: cogeneration units, ammonia plants, electrolyzers and hydrogen fuel cells. The output power of the coupling equipment must meet the equipment capacity constraints. At the same time, considering the response speed of the energy conversion process and the rapid power change that will lead to equipment operation safety problems, the output power must also meet the ramp constraint, which is expressed as follows:

[0081] Where: Energy coupling equipment i exist t The output power at the moment, For equipment i The output power limit is , Equipment i The upper and lower limits of climbing power; The energy storage constraint expression is as follows:

[0082] Where: express t The energy stored in the energy storage device at all times, , Respectively t The charging and discharging power of the energy storage device at all times, , Respectively represent the charging and discharging efficiency of the energy storage device, , are the energy stored in the energy storage device at the start and end of the scheduling period, , Respectively represent the upper and lower limits of charging power, , Indicates the upper and lower limits of the energy release power. Represents a 0-1 variable, when =1 indicates charging state. =0 indicates energy release state; The gas network balance constraint expression is as follows:

[0083] Where: for t Natural gas consumed by the cogeneration unit at any given moment; The hydrogen network balance constraint expression is as follows:

[0084] Where: for t The amount of hydrogen produced by the electrolyzer at the moment, for t The hydrogen consumption of hydrogen fuel cells at each moment, for t The hydrogen storage capacity of the hydrogen storage tank at any time, for t The hydrogen consumption of the ammonia plant system at any given moment; The electrical and thermal power balance constraint expressions are as follows:

[0085] Where: , They are electrical load and thermal load respectively.

[0086] Preferably, the step S5 is specifically as follows: by modeling the characteristics and probability distribution of historical data to describe its distribution law, and further generating typical scenarios through random sampling, and finally using the scenario reduction method to remove duplicate scenarios for optimization and scheduling. Taking photovoltaics as an example, the specific method steps are as follows: S5.1. Construct a photovoltaic probability distribution model, and its calculation formula is as follows:

[0087] Where: is the solar intensity, , represents the shape parameter of the Beta distribution; S5.2. Model sampling, construct a typical scene model, generate n equidistant initial scenes, and the probability of each scene is set to 1 / n, indicating that the probability of each scene appearing is equal. The calculation formula is as follows:

[0088] Where: is the photovoltaic power output, is the radiation area of ​​the photovoltaic module, is the photoelectric conversion efficiency; S5.3, calculate the Euclidean distance between the scenes, construct a distance matrix, the distance matrix is ​​used to represent the distance relationship between each scene and other scenes, and find the sum of the probability distances between each scene and the remaining scenes, represented by Y; S5.4, scene reduction, judging whether the number of scenes currently remaining is greater than the predetermined number of scenes k; if yes, continuing to execute the step of scene reduction; if no, jumping to outputting the result; According to the weight of Y / k, find the scene with the smallest probability and merge its probability with the nearest neighbor scene. This step reduces the number of scenes by merging the scenes with the smallest probability. During the scenario reduction process, the probability of each remaining scenario is adjusted to ensure that the total probability sums to 1 and reflects the new probability distribution; When the number of scenarios is reduced to the predetermined number k, the final scenarios and their corresponding probabilities are output, and finally deleted and merged.

[0089] The above embodiments are only preferred technical solutions of the present invention and should not be regarded as limiting the present invention. The protection scope of the present invention shall be the technical solutions recorded in the claims, including equivalent replacement solutions of the technical features in the technical solutions recorded in the claims. That is, equivalent replacement improvements within this scope are also within the protection scope of the present invention.

Claims

1. A method for optimizing the dispatch of an integrated electricity, hydrogen and ammonia energy system from a full life cycle perspective, characterized by: The following steps are involved: S1. Build an electricity, hydrogen and ammonia integrated energy system model; S2. Conduct a full life cycle carbon emission assessment on the electricity, hydrogen and ammonia integrated energy system. On the basis of obtaining carbon emission data from the equipment operation stage, further introduce carbon emission data from production and construction, decommissioning and other stages to accurately obtain all carbon emission data of the system throughout the entire cycle; S3, introduce the carbon emission coefficient obtained in S2 into the carbon trading model, and introduce reward factors and punishment factors to build a reward and punishment ladder carbon trading mechanism model; S4. Taking the minimum sum of energy purchase cost, operation and maintenance cost, and carbon trading cost as the objective function, and taking renewable energy constraints, energy purchase constraints, energy coupling equipment safe operation constraints, energy storage constraints, gas grid interaction balance constraints, and electricity and heat balance constraints as constraints, an optimization scheduling model is constructed to limit the carbon emissions of the system; S5. Model the characteristics and probability distribution of historical data, describe the distribution law, and generate and reduce scenarios; S6. Initialize the CPLEX environment, define variables, objective functions, and constraints, use MATLAB to call the CPLEX commercial solver to solve and analyze the model, and obtain the optimal scheduling result.

2. According to the method for optimizing the dispatching of an electric-hydrogen-ammonia integrated energy system from a full life cycle perspective of claim 1, it is characterized by: The step S1 is specifically as follows: Build a detailed model of the electric, hydrogen and ammonia integrated energy system, which mainly includes the electric hydrogen production system model and the ammonia production plant model. The electric, hydrogen and ammonia integrated energy system mainly includes: energy supply units, energy conversion equipment, energy storage equipment and loads; the energy supply units include wind turbines, photovoltaic arrays, upstream power grids, upstream gas grids and upstream hydrogen grids; energy conversion equipment includes cogeneration devices, electrolyzers, hydrogen fuel cells and ammonia production plants; energy storage equipment includes electricity, heat and hydrogen energy storage equipment; the loads mainly include electricity, heat and hydrogen loads.

3. The method for optimizing and dispatching an electric, hydrogen and ammonia integrated energy system from a full life cycle perspective according to claim 2 is characterized by: The electric hydrogen production system model mainly includes an electrolyzer model, a hydrogen fuel cell model and a hydrogen storage tank model; the energy conversion efficiency of the electrolyzer model is about 75% to 85%, and its expression is: Where: , are the input and output power of the electrolyzer during period t, is the energy conversion efficiency of the electrolyzer; The hydrogen fuel cell can convert the energy generated by hydrogen combustion into electrical energy output, and the model expression is: Where: , They are t The input and output power of hydrogen fuel cells at all times. The power generation efficiency of the fuel cell; The hydrogen storage tank is used to store hydrogen generated by electrolysis of water in an alkaline electrolyzer, and can also provide hydrogen for hydrogen fuel cells to improve the flexibility of the system. The model expression is: Where: for t The energy stored in the hydrogen tank at all times; , are the efficiency of the electrolyzer input to the hydrogen storage tank and the hydrogen storage tank output to the hydrogen fuel cell respectively; The working efficiency of the hydrogen storage tank; The maximum input power of the electrolyzer and the maximum output power of the hydrogen fuel cell are limited by their capacity and the remaining energy storage capacity of the hydrogen storage tank, which can be expressed as: Where: , are the capacities of the alkaline electrolyzer and hydrogen fuel cell, , are the upper and lower limits of the energy storage capacity of the hydrogen storage tank, respectively. =0.85 , =0.15 .

4. The method for optimizing and dispatching an electric, hydrogen and ammonia integrated energy system from a full life cycle perspective according to claim 2 is characterized by: The ammonia production plant synthesizes ammonia by using the Haber reaction between the hydrogen produced by the electrolyzer and the nitrogen. The model calculation formula is as follows: Where: for t The thermal power provided by the ammonia plant during the period, , for t Input and output power of the ammonia production plant during the time period, is the ammonia production efficiency, The proportion of heat released to heat the ammonia production equipment, is the heat power released per unit mass of ammonia, for t The mass of ammonia generated during the period, , They are the maximum and minimum input power of the ammonia plant respectively.

5. The method for optimizing and dispatching an electric, hydrogen and ammonia integrated energy system from a full life cycle perspective according to claim 1 is characterized by: The step S2 is specifically as follows: S2.

1. Define the system boundary. The boundary of the electricity, hydrogen and ammonia integrated energy system includes the following parts: electricity production, hydrogen production, ammonia synthesis, energy conversion and storage, transportation and distribution, and terminal use; S2.

2. Data collection and analysis: Detailed data collection and analysis of carbon emissions at each stage, including data on direct carbon emissions and indirect carbon emissions; S2.

3. Full life cycle analysis, including: life cycle inventory analysis, life cycle impact assessment, and result interpretation.

6. The method for optimizing and dispatching an electric, hydrogen and ammonia integrated energy system from a full life cycle perspective according to claim 1 is characterized by: The step S3 is specifically as follows: S3.

1. Determine carbon emission quotas and baselines, set the system's initial carbon emission quotas, and allocate them based on historical emission data or industry standards; S3.2, the introduction of carbon emission data, from the full life cycle carbon emission assessment in step S2, the carbon emission coefficients of each link in the system can be obtained, including the carbon emission coefficients of transportation and distribution, the carbon emission coefficients of electricity production, etc., so as to obtain the actual carbon emissions; S3.

3. The reward-and-penalty tiered carbon trading mechanism divides carbon emission levels into several intervals, each of which corresponds to a different carbon emission price. It also introduces compensation coefficients and penalty coefficients to encourage companies to take different emission reduction measures at different carbon emission levels.

7. The method for optimizing and dispatching an electric, hydrogen and ammonia integrated energy system from a full life cycle perspective according to claim 1 is characterized by: The objective function in step S4 is: Where: is the total system operating cost, , , They are system energy purchase cost, operation and maintenance cost, and carbon trading cost; The operating costs of each part are as follows: Where: , They are t Moment Energy A The unit purchase price and purchase quantity; , They are t Time equipment B output power and unit operation and maintenance costs.

8. The method for optimizing and dispatching an electric, hydrogen and ammonia integrated energy system from a full life cycle perspective according to claim 1 is characterized by: The constraints in step S4 include renewable energy constraints, energy purchase constraints, energy coupling equipment safe operation constraints, energy storage constraints, gas grid interaction balance constraints, electricity and heat balance constraints, etc. The renewable energy constraint expression is as follows: Where: , They are the upper limits of wind power and photovoltaic output power respectively; The energy purchase constraint expression is: Where: , They are t The amount of electricity purchased at the moment and the upper limit of electricity purchase, , They are t The gas purchase volume and purchase limit at the moment, , They are t The amount of hydrogen purchased at the time and the upper limit of hydrogen purchase; The energy coupling equipment safety operation constraints mentioned above mainly involve: cogeneration units, ammonia plants, electrolyzers and hydrogen fuel cells. The output power of the coupling equipment must meet the equipment capacity constraints. At the same time, considering the response speed of the energy conversion process and the rapid power change that will lead to equipment operation safety problems, the output power must also meet the ramp constraint, which is expressed as follows: Where: Energy coupling equipment i exist t The output power at the moment, For equipment i The output power limit is , Equipment i The upper and lower limits of climbing power; The energy storage constraint expression is as follows: Where: express t The energy stored in the energy storage device at all times, , Respectively t The charging and discharging power of the energy storage device at all times, , Respectively represent the charging and discharging efficiency of the energy storage device, , are the energy stored in the energy storage device at the start and end of the scheduling period, , Respectively represent the upper and lower limits of charging power, , Indicates the upper and lower limits of the energy release power. Represents a 0-1 variable, when =1 indicates charging state. =0 indicates energy release state; The gas network balance constraint expression is as follows: Where: for t Natural gas consumed by the cogeneration unit at any given moment; The hydrogen network balance constraint expression is as follows: Where: for t The amount of hydrogen produced by the electrolyzer at the moment, for t The hydrogen consumption of hydrogen fuel cells at each moment, for t The hydrogen storage capacity of the hydrogen storage tank at any time, for t The hydrogen consumption of the ammonia plant system at any given moment; The electrical and thermal power balance constraint expressions are as follows: Where: , They are electrical load and thermal load respectively.

9. The method for optimizing and dispatching an electric, hydrogen and ammonia integrated energy system from a full life cycle perspective according to claim 1 is characterized by: The step S5 is specifically as follows: by modeling the characteristics and probability distribution of historical data to describe its distribution law, and further generating typical scenarios through random sampling, and finally using the scenario reduction method to remove duplicate scenarios for optimization and scheduling.

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