Comprehensive energy system optimization scheduling method considering carbon emission and hydrogen energy multi-stage utilization

Abstract

The invention discloses a comprehensive energy system optimal scheduling method considering carbon emission and hydrogen energy multi-stage utilization, which comprises the following steps: establishing a carbon emission multi-stage utilization model and a hydrogen energy multi-stage utilization model according to a comprehensive energy system architecture; according to the carbon emission multi-stage utilization model and the hydrogen energy multi-stage utilization model, a comprehensive energy system optimization scheduling model considering carbon emission and hydrogen energy multi-stage utilization is established; the comprehensive energy system optimal scheduling model considering carbon emission and hydrogen energy multi-stage utilization comprises an objective function and constraint conditions with the comprehensive operation cost of the comprehensive energy system as the minimum; and solving the comprehensive energy system optimal scheduling model considering carbon emission and hydrogen energy multi-stage utilization. According to the invention, flexible management of IES carbon emission and hydrogen energy is realized, and the operation cost is reduced at the same time.

Description

Technical Field

[0001] The present invention relates to an integrated energy system optimization scheduling method taking into account carbon emissions and multi-level utilization of hydrogen energy, and belongs to the field of integrated energy system scheduling. Background Art

[0002] In recent years, environmental pollution caused by carbon emissions has become increasingly serious, leading to the establishment of carbon peak and carbon neutrality goals. As a major source of carbon emissions, the energy industry urgently needs to achieve low-carbonization through both low-carbon policies and technologies.

[0003] As a crucial component of the energy industry, the integrated energy system (IES) integrates multiple energy sources for joint supply, meeting the diverse energy demands of end users. However, IES have a high proportion of traditional energy, resulting in significantly higher carbon emission intensity than renewable energy systems. Existing research has largely focused on optimizing IES economics, with insufficient attention paid to carbon reduction targets. This could lead to a further shift in IES toward high-carbon technologies, exacerbating climate change risks. Therefore, further promoting the decarbonization of IES is necessary. The coordinated implementation of low-carbon technologies and low-carbon markets to achieve multi-level utilization of carbon emissions and hydrogen energy is crucial for optimizing the low-carbon economy of IES and promoting the low-carbon transition of the energy industry.

[0004] In view of this, the present invention is proposed. Summary of the Invention

[0005] The present invention provides an integrated energy system optimization scheduling method that takes into account carbon emissions and multi-level utilization of hydrogen energy, which is used to construct an integrated energy system optimization scheduling model that takes into account carbon emissions and multi-level utilization of hydrogen energy, and uses a solver to solve the problem to obtain an IES optimization scheduling strategy that takes into account carbon emissions and multi-level utilization of hydrogen energy.

[0006] The technical solution of the present invention is:

[0007] According to a first aspect of the present invention, a method for optimizing and scheduling an integrated energy system taking into account carbon emissions and multi-stage utilization of hydrogen energy is provided, comprising: establishing a carbon emission multi-stage utilization model and a hydrogen energy multi-stage utilization model based on the integrated energy system architecture; establishing an optimized scheduling model for an integrated energy system taking into account carbon emissions and multi-stage utilization of hydrogen energy based on the carbon emission multi-stage utilization model and the hydrogen energy multi-stage utilization model; the optimized scheduling model for an integrated energy system taking into account carbon emissions and multi-stage utilization of hydrogen energy includes an objective function and constraints taking the comprehensive operating cost of the integrated energy system as the minimum; and solving the optimized scheduling model for an integrated energy system taking into account carbon emissions and multi-stage utilization of hydrogen energy.

[0008] Furthermore, the establishment of the multi-level utilization model of carbon emissions is specifically as follows: establishing a CCS model; determining the mass of CO2 captured by carbon capture in the CCS model based on the established carbon utilization and carbon storage model; calculating the number of green certificates participating in the green certificate market based on the number of green certificates required by IES and the number of green certificates obtained by IES; establishing a ladder green certificate trading model based on the number of green certificates participating in the green certificate market; constructing a ladder carbon-green certificate coupling trading mechanism based on the number of green certificates required by IES and the mass of CO2 captured by carbon capture, and obtaining the carbon emission rights to re-participate in the carbon trading market after considering green certificates-carbon offset; establishing a ladder carbon trading model; trading the carbon emission rights to re-participate in the carbon trading market after considering green certificates-carbon offset based on the ladder carbon trading model, and obtaining the carbon trading cost of the integrated energy system.

[0009] Furthermore, according to the quantity of green certificates required by IES and the quality of CO2 captured by carbon capture, a step-by-step carbon-green certificate coupling trading mechanism is constructed to obtain the carbon emission rights to re-participate in the carbon trading market after considering the green certificate-carbon offset. Specifically, according to the quantity of green certificates required by IES, the green certificate carbon offset amount is obtained; according to the quality of CO2 captured by the carbon capture, the carbon emission rights to participate in carbon trading are obtained; according to the carbon emission rights to participate in carbon trading and the green certificate carbon offset amount, the carbon emission rights to re-participate in the carbon trading market after considering the green certificate-carbon offset are obtained.

[0010] Furthermore, the establishment of the multi-stage hydrogen energy utilization model is specifically as follows:

[0011] The power-to-gas (PtG) system in the integrated energy system is divided into two stages: the electrolyzer (EL) and the methane reactor (MR). One stage generates natural gas through the MR, and the other stage meets the hydrogen blending requirements of the gas-fired unit. The multi-stage hydrogen utilization model for PtG specifically includes:

[0012] P2G two-stage model:

[0013]

[0014] Gas turbine GT hydrogen blending model:

[0015]

[0016]

[0017] Gas boiler GB hydrogen blending model:

[0018]

[0019]

[0020] Where, and is the hydrogen production power and power consumption of the electrolyzer at time t; is the hydrogen consumption power of the methane reactor at time t; is the gas production power of MR at time t; η EL ,η MR are the conversion efficiencies of EL and MR, respectively; and are the electrical and thermal output power of the gas turbine (GT) at time t, respectively; and are the electrical and thermal efficiencies of GT, respectively; and are the natural gas and hydrogen power consumed by GT at time t, respectively; is the hydrogen doping ratio of GT at time t; is the calorific value of natural gas; is the calorific value of hydrogen; is the total output of GT at time t; They are the upper and lower limits of GT power output respectively; The upper and lower limits of GT thermal output; They are the upper and lower limits of GT output climbing respectively; is the heat generation power of GB at time t; is the hydrogen doping ratio of GB at time t; η GB is the heat generation efficiency of GB; are the hydrogen and natural gas power consumption of GB at time t, respectively; and is the relative molecular mass of hydrogen and natural gas; is the hydrogen doping ratio of GB at time t; The upper and lower limits of GB heat generation power; They are the upper and lower limits of GB heat generation power ramping respectively; is the density of CH4; is the density of H2.

[0021] Furthermore, the operating costs involved in the objective function include: carbon trading costs, green certificate trading costs, carbon sequestration costs, start-up and shutdown costs of coal-fired units, coal consumption costs of coal-fired units, gas purchase costs, and wind curtailment costs; the constraints include: electric power balance constraints, wind power supply constraints, and coal-fired unit ramp-up and output constraints.

[0022] According to a second aspect of the present invention, a comprehensive energy system optimization and scheduling system taking into account carbon emissions and multi-level utilization of hydrogen energy is provided, including a module of any one of the above-mentioned comprehensive energy system optimization and scheduling methods taking into account carbon emissions and multi-level utilization of hydrogen energy.

[0023] According to a third aspect of the present invention, a processor is provided, characterized in that the processor is used to execute an operation, and the operation includes executing any one of the above-mentioned integrated energy system optimization scheduling methods taking into account carbon emissions and multi-level utilization of hydrogen energy.

[0024] The beneficial effects of the present invention are:

[0025] This invention focuses on the low-carbonization demand of IES under the "dual carbon" goal and proposes a multi-level utilization mechanism of carbon emissions and hydrogen energy. On the one hand, the resource utilization of CO2 is realized through carbon utilization and carbon storage technologies, forming a "capture-utilization-storage" closed loop, and a coordinated mechanism of ladder carbon trading and ladder green certificate trading is designed. The carbon emission constraints are strengthened through interval pricing and reward and punishment factors, and the green certificate-carbon offset mechanism is used to improve the economic efficiency of new energy consumption; on the other hand, in response to the low efficiency of the traditional power-to-gas (P2G) process, P2G is refined into a two-stage process of power-to-hydrogen and methanation, and hydrogen blending technology for gas turbines is introduced to reduce natural gas consumption and carbon emissions by dynamically adjusting the hydrogen blending ratio; the above mechanism reduces IES carbon emissions through carbon sequestration, carbon utilization, carbon trading, carbon offset, and hydrogen blending and methanation (MR) to generate natural gas, realizing flexible management of IES carbon emissions and hydrogen energy while reducing its operating costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a flow chart of the present invention;

[0027] Figure 2 This is the IES architecture diagram;

[0028] Figure 3 is the total cost and actual carbon emissions of IES under different hydrogen blending ratios;

[0029] Figure 4 is the carbon emissions of gas-fired units and thermal power units at different hydrogen blending ratios;

[0030] Figure 5 The green certificate trading income under different hydrogen blending ratios of GB;

[0031] Figure 6 The changes in IES total cost under different green certificate trading interval lengths and green certificate quota coefficients;

[0032] Figure 7 The changes in IES carbon emissions under different green certificate trading interval lengths;

[0033] Figure 8 The changes in IES carbon emissions under different green certificate quota coefficients;

[0034] Figure 9 Carbon emissions and wind power consumption rates under different green certificate basic transaction prices. DETAILED DESCRIPTION

[0035] To make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. It should be noted that, in the absence of conflict, the embodiments in this application and the features in the embodiments can be combined with each other in any way.

[0036] Example 1: Figures 1-9 As shown, according to the first aspect of an embodiment of the present invention, a method for optimizing and scheduling an integrated energy system taking into account carbon emissions and multi-stage utilization of hydrogen energy is provided, including: establishing a carbon emission multi-stage utilization model and a hydrogen energy multi-stage utilization model based on the integrated energy system architecture; establishing an optimized scheduling model for an integrated energy system taking into account carbon emissions and multi-stage utilization of hydrogen energy based on the carbon emission multi-stage utilization model and the hydrogen energy multi-stage utilization model; the optimized scheduling model for an integrated energy system taking into account carbon emissions and multi-stage utilization of hydrogen energy includes an objective function and constraints with the comprehensive operating cost of the integrated energy system as the minimum; solving the optimized scheduling model for an integrated energy system taking into account carbon emissions and multi-stage utilization of hydrogen energy.

[0037] Furthermore, the establishment of the multi-level utilization model of carbon emissions is specifically as follows: establishing a CCS model; determining the mass of CO2 captured by carbon capture in the CCS model based on the established carbon utilization and carbon storage model; calculating the number of green certificates participating in the green certificate market based on the number of green certificates required by IES and the number of green certificates obtained by IES; establishing a ladder green certificate trading model based on the number of green certificates participating in the green certificate market; constructing a ladder carbon-green certificate coupling trading mechanism based on the number of green certificates required by IES and the mass of CO2 captured by carbon capture, and obtaining the carbon emission rights to re-participate in the carbon trading market after considering green certificates-carbon offset; establishing a ladder carbon trading model; trading the carbon emission rights to re-participate in the carbon trading market after considering green certificates-carbon offset based on the ladder carbon trading model, and obtaining the carbon trading cost of the integrated energy system.

[0038] Furthermore, according to the quantity of green certificates required by IES and the quality of CO2 captured by carbon capture, a step-by-step carbon-green certificate coupling trading mechanism is constructed to obtain the carbon emission rights to re-participate in the carbon trading market after considering the green certificate-carbon offset. Specifically, according to the quantity of green certificates required by IES, the green certificate carbon offset amount is obtained; according to the quality of CO2 captured by the carbon capture, the carbon emission rights to participate in carbon trading are obtained; according to the carbon emission rights to participate in carbon trading and the green certificate carbon offset amount, the carbon emission rights to re-participate in the carbon trading market after considering the green certificate-carbon offset are obtained.

[0039] Furthermore, the establishment of the multi-stage hydrogen energy utilization model is specifically as follows:

[0040] The power-to-gas (PtG) system in the integrated energy system is divided into two stages: the electrolyzer (EL) and the methane reactor (MR). One stage generates natural gas through the MR, and the other stage meets the hydrogen blending requirements of the gas-fired unit. The multi-stage hydrogen utilization model for PtG specifically includes:

[0041] P2G two-stage model:

[0042]

[0043] Gas turbine GT hydrogen blending model:

[0044]

[0045]

[0046] Gas boiler GB hydrogen blending model:

[0047]

[0048]

[0049] Where, and is the hydrogen production power and power consumption of the electrolyzer at time t; is the hydrogen consumption power of the methane reactor at time t; is the gas production power of MR at time t; η EL ,η MR are the conversion efficiencies of EL and MR, respectively; and are the electrical and thermal output power of the gas turbine (GT) at time t, respectively; and are the electrical and thermal efficiencies of GT, respectively; and are the natural gas and hydrogen power consumed by GT at time t, respectively; is the hydrogen doping ratio of GT at time t; is the calorific value of natural gas; is the calorific value of hydrogen; is the total output of GT at time t; They are the upper and lower limits of GT power output respectively; The upper and lower limits of GT thermal output; They are the upper and lower limits of GT output climbing respectively; is the heat generation power of GB at time t; is the hydrogen doping ratio of GB at time t; η GB is the heat generation efficiency of GB; are the hydrogen and natural gas power consumption of GB at time t, respectively; and is the relative molecular mass of hydrogen and natural gas; is the hydrogen doping ratio of GB at time t; The upper and lower limits of GB heat generation power; They are the upper and lower limits of GB heat generation power ramping respectively; is the density of CH4; is the density of H2.

[0050] Furthermore, the operating costs involved in the objective function include: carbon trading costs, green certificate trading costs, carbon sequestration costs, start-up and shutdown costs of coal-fired units, coal consumption costs of coal-fired units, gas purchase costs, and wind curtailment costs; the constraints include: electric power balance constraints, wind power supply constraints, and coal-fired unit ramp-up and output constraints.

[0051] According to the second aspect of an embodiment of the present invention, there is provided a comprehensive energy system optimization and scheduling system taking into account carbon emissions and multi-level utilization of hydrogen energy, including modules of any one of the above-mentioned comprehensive energy system optimization and scheduling methods taking into account carbon emissions and multi-level utilization of hydrogen energy. Specifically comprising: a first module for establishing a carbon emission multi-level utilization model and a hydrogen energy multi-level utilization model based on the comprehensive energy system architecture; a second module for establishing a comprehensive energy system optimization and scheduling model taking into account carbon emissions and multi-level utilization of hydrogen energy based on the carbon emission multi-level utilization model and the hydrogen energy multi-level utilization model; a third module for solving the comprehensive energy system optimization and scheduling model taking into account carbon emissions and multi-level utilization of hydrogen energy. Each module in the above-mentioned comprehensive energy system optimization and scheduling system taking into account carbon emissions and multi-level utilization of hydrogen energy can be implemented in whole or in part by software, hardware and a combination thereof. For the parts not described in detail in each module, please refer to the relevant description of this embodiment.

[0052] According to a third aspect of an embodiment of the present invention, a processor is provided, characterized in that the processor is used to execute an operation, and the operation includes executing any one of the above-mentioned integrated energy system optimization scheduling methods taking into account carbon emissions and multi-level utilization of hydrogen energy.

[0053] Example 2: The following optional embodiments of the present invention are described as follows:

[0054] A comprehensive energy system optimization scheduling method taking into account carbon emissions and multi-level hydrogen energy utilization, comprising:

[0055] Step 1: Establish a multi-level carbon emission utilization model based on the integrated energy system architecture;

[0056] Step 2: Establish a multi-level hydrogen energy utilization model;

[0057] Step 3: Based on the carbon emission multi-level utilization model and the hydrogen energy multi-level utilization model, establish an integrated energy system optimization scheduling model that considers carbon emission and hydrogen energy multi-level utilization;

[0058] Step 4. Use Matlab's CPLEX solver to solve the integrated energy system optimization scheduling model considering carbon emissions and multi-level utilization of hydrogen energy.

[0059] Furthermore, the Step 1 includes:

[0060] S1.1: Build a CCS model

[0061]

[0062] Where: P fix They are the total power consumption, operating power consumption and fixed power consumption of CCS respectively; e c is the unit energy consumption of CCS; is the mass of CO2 captured by carbon capture at time t; They are the upper and lower limits of the total power consumption of CCS respectively.

[0063] S1.2: Establish a carbon utilization and carbon storage model. Carbon utilization is achieved by combining the CO2 discharged from the IES in the methane reactor (MR) with hydrogen produced by electrolysis of water in the electrolyzer (EL) to produce natural gas. The unused CO2 is stored through carbon storage. The CO2 expression required by the MR is as follows:

[0064]

[0065]

[0066] Where: is the mass of CO2 used by MR at time t; is the gas production power of MR at time t; is the calorific value of natural gas; is the density of CO2; is the mass of CO2 stored; is the mass of CO2 captured by carbon capture at time t.

[0067] S1.3: Establish a green certificate-carbon offset model. According to the renewable energy quota mechanism, a portion of the electricity generation and consumption of enterprises or users must come from renewable energy. The calculation formula for the number of green certificates required by IES is as follows:

[0068]

[0069] Where: The number of green certificates required for IES; γ GCT IES green certificate quota coefficient; is the IES load during period t.

[0070] The conversion relationship between green certificates and green electricity is that one green certificate is equivalent to 1MW of green electricity. The number of green certificates obtained by IES is as follows:

[0071]

[0072] Where: The number of green certificates obtained for IES; is the actual output of IES wind power during period t.

[0073] The number of green certificates participating in the green certificate market is calculated as follows:

[0074]

[0075] Where: The trading volume of green certificates in the green certificate market; It is the green certificate quota indicator required by IES; The number of green certificates obtained by IES.

[0076] Similar to the incentive principle of ladder carbon trading, the more green certificates a company holds, the higher the unit price when it is sold; conversely, the greater the demand for green certificates, the higher the unit price. Based on the above analysis, the ladder green certificate trading model is as follows:

[0077]

[0078] Where: is the transaction cost of IES green certificate at time t; GCT is the base price of green certificate transaction; α is the compensation coefficient when the quota of new energy of the government is exceeded; κ is the penalty coefficient when the quota of new energy of the government is less than the quota of new energy of the government; L GCT The length of the green certificate trading range; The green certificate trading volume of participants in the green certificate market.

[0079] The traditional carbon trading market (CET) cannot use green certificate trading to obtain carbon emission rights. In order to further improve the flexibility of IES operation and market transactions, this paper constructs a ladder carbon-green certificate coupling trading mechanism based on the green certificate-carbon offset mechanism. Its model can be expressed as follows:

[0080]

[0081]

[0082] Where: is the carbon offset amount of green certificates; γ is the carbon offset coefficient per unit green certificate; The number of green certificates obtained for IES; To consider the carbon emission rights of re-participating in CET after Green Certificate-carbon offset; Carbon emission rights for participating in carbon trading; is the actual carbon emissions of IES; is the IES carbon allowance amount; is the mass of CO2 captured by carbon capture at time t.

[0083] S1.4: Based on the carbon emission rights of re-participating in CET after considering green certificate-carbon offset, a ladder carbon trading model is established. Based on the traditional unified carbon price mechanism, this paper proposes a ladder carbon trading pricing strategy based on emission zoning. Referring to the pricing idea of ​​ladder electricity price, this mechanism divides the difference between actual carbon emissions and carbon quotas into different intervals and implements differentiated pricing. For the excess emissions, a segmented cumulative pricing method is adopted, and the carbon price is gradually increased as the carbon emissions increase; for the surplus of emission reductions, the income from the sale of carbon rights is enhanced by introducing an incentive coefficient. The ladder carbon trading model is as follows:

[0084]

[0085] Where: is the IES carbon trading cost at time t; χ is the carbon trading base price; δ is the incentive coefficient; L is the length of the carbon emission interval; θ is the carbon price growth rate.

[0086] Furthermore, the Step 2 is described as follows:

[0087] To fully leverage the low-carbon benefits of hydrogen, this invention breaks down power-to-gas (P2G) into two stages: EL and MR. This allows for multi-stage utilization of P2G hydrogen, with one portion used to meet the hydrogen blending needs of gas turbines (GT and GB), while the other portion is used to generate natural gas through MR. The specific P2G model is as follows:

[0088]

[0089] Where: and is the hydrogen production power and power consumption of the electrolyzer (EL) at time t; is the hydrogen consumption power of the methane reactor (MR) at time t; is the gas production power of MR at time t; η EL ,η MR are the conversion efficiencies of EL and MR, respectively.

[0090] Hydrogen doping in a gas turbine (GT) involves mixing hydrogen and natural gas in a specific ratio before entering the combustion chamber to drive the turbine for safe and stable power generation. This paper uses a variable hydrogen doping ratio to optimize the optimal hydrogen doping ratio during scheduling. The specific model is as follows:

[0091]

[0092] Where: and are the electrical and thermal output power of the gas turbine (GT) at time t, respectively; and are the electrical and thermal efficiencies of GT, respectively; and are the natural gas and hydrogen power consumed by GT at time t, respectively; is the hydrogen doping ratio of GT at time t; is the calorific value of natural gas; is the calorific value of hydrogen; is the total output of GT at time t; They are the upper and lower limits of GT power output respectively; The upper and lower limits of GT thermal output; They are the upper and lower limits of GT output climbing respectively.

[0093] The hydrogen doping of gas boilers (GB) is similar to that of GT. The relevant standards require that the hydrogen doping ratio be kept within the range of 2% to 20%. The model is as follows:

[0094]

[0095] Where: is the heating power of the gas boiler (GB) at time t; is the hydrogen doping ratio of GB at time t; η GB is the heat generation efficiency of GB; are the hydrogen and natural gas power consumption of GB at time t, respectively; and is the relative molecular mass of hydrogen and natural gas; is the hydrogen doping ratio of GB at time t; The upper and lower limits of GB heat generation power; They are the upper and lower limits of GB heat generation power ramping respectively; is the density of CH4; is the density of H2.

[0096] Furthermore, the Step 3 includes:

[0097] S3.1: Objective function. The present invention optimizes the IES comprehensive operating cost F by minimizing it as the objective function:

[0098]

[0099] in, is the carbon trading cost, F GCT is the transaction cost of green certificates, F f is the carbon sequestration cost, F th1 is the start-up and shutdown cost of the coal-fired unit, F th2 is the coal consumption cost of the coal-fired unit, F buy is the gas purchase cost, F cw is the cost of wind curtailment, as detailed below:

[0100]

[0101] Where: is the IES carbon trading cost at time t; is the IES green certificate transaction cost at time t; is the amount of CO2 stored; c f Cost coefficient for storing unit mass of CO2; T is the scheduling period; c S is the start-up and shutdown cost coefficient of the coal-fired unit; is a binary variable at time t; is the power generation of the coal-fired unit at time t; a th 、b th and c th is the coal consumption cost coefficient of the coal-fired unit; c cw is the penalty cost per unit of wind curtailment; is the amount of wind curtailment at time t; c g,buy is the price per unit of natural gas purchased; is the natural gas power purchased by IES at time t.

[0102] S3.2: Constraints

[0103] 1) Electric power balance constraints

[0104]

[0105] Where: is the power generation of the coal-fired unit at time t; and are the electrical and thermal power output of GT at time t respectively; is the actual output of IES wind power in period t; is the power consumption of EL at time t; and is the heat and electricity demand on the load side at time t; are the power consumption and heat generation of EB at time t respectively; are the charging and discharging power of the energy storage at time t respectively; is the natural gas power purchased by IES at time t; is the gas production power of MR at time t; and are the natural gas and hydrogen power consumed by GT at time t, respectively; are the hydrogen and natural gas power consumption of GB at time t, respectively; and is the relative molecular mass of hydrogen and natural gas; is the heating power of the gas boiler (GB) at time t; are the charging and releasing powers of the thermal energy storage at time t respectively; is the hydrogen consumption power of the methane reactor (MR) at time t; is the hydrogen production power of EL at time t.

[0106] In the above, the power consumption and heat generation of EB satisfy the following formula:

[0107]

[0108] Where η EB is the heat generation efficiency of EB.

[0109] 2) Wind power supply constraints

[0110]

[0111] Where: is the predicted output of the wind turbine at time t; is the actual output of IES wind power in period t; is the wind power abandoned by the wind turbine at time t.

[0112] 3) Coal-fired unit ramp-up and output constraints

[0113]

[0114] Where: is a binary variable at time t; is the power generation of the coal-fired unit at time t; The upper and lower limits of the power output of coal-fired units; These are the upper and lower limits of the ramp rate for coal-fired units.

[0115] The following analysis takes a certain IES as an example. The IES structure is as follows Figure 2As shown. The integrated energy system (IES) constructed by the present invention includes a wind turbine, an electric heating boiler model (electrode boiler, EB), a gas turbine (gas turbine, GT), a coal-fired unit, a gas boiler (gas boiler, GB), a two-stage power-to-gas, a carbon capture system (CCS), an electric storage and a heat storage device. Among them, electric storage, heat storage and two-stage power-to-gas serve as flexibility resources in IES, and effectively smooth the volatility of renewable energy power generation through time-shifted energy supply. The IES energy management platform optimizes and coordinates the operating strategies of various energy supply equipment based on renewable energy power generation forecasts and load demand data, and maximizes economic benefits while ensuring the safe and stable operation of IES. The time-of-use electricity price information is shown in Table 1, and the relevant parameters are shown in Table 2. Ladder green certificate trading parameter settings: λ GCT 50 yuan / MW; α and κ are both 10%; L GCT The tiered carbon trading parameters are: χ = 215 yuan / t; δ and θ = 25%; and L = 50t.

[0116] Table 1 Time-of-use electricity prices

[0117] Time <![CDATA[Electricity price / [yuan·(kWh -1 )]]]> 01:00—07:00、23:00—24:00 0.40 08:00—11:00、15:00—18:00 0.75 12:00—14:00、19:00—22:00 1.20

[0118] Table 2 Related parameters

[0119]

[0120] Furthermore, in order to verify the effectiveness of the strategy proposed in this invention, four case scenarios are set for comparative analysis: Scenario 1 is under the ladder carbon trading mechanism, without considering carbon offset Trading with Ladder Green Certificates Scenario 2 is based on Scenario 1 and does not consider hydrogen blending for gas turbines. Scenario 3 is based on a tiered carbon trading and green certificate trading mechanism and does not consider carbon offsets. Scenario 4 is based on a tiered trading mechanism and considers the IES optimization scheduling of the strategy proposed in this invention. All of the above scenarios, except Scenario 2, consider variable hydrogen blending ratios.

[0121] 1) Analysis of optimized scheduling results of integrated energy system considering carbon emissions and multi-level utilization of hydrogen energy

[0122] Table 3 shows the optimized dispatch results for different scenarios. As shown in Table 3, Scenario 2 has higher total costs, carbon emissions, and wind power absorption rate than Scenario 1. This is because Scenario 2 does not incorporate a hydrogen blending strategy, resulting in less hydrogen production from EL electrolysis. Consequently, wind power absorption is lower than in Scenario 1, while carbon emissions are higher. Comparing Scenario 3 with Scenario 1, Scenario 3's total costs are 122,600 yuan lower than in Scenario 1. This is because Scenario 3 incorporates a tiered green certificate trading mechanism that incorporates incentives and penalties, increasing the economic value of green electricity compared to Scenario 1. Consequently, IES operating economics improves while increasing wind power absorption rate by 1.01%. Scenario 4, due to its multi-tiered carbon emission utilization (carbon offsetting, carbon utilization and storage, carbon capture), as well as hydrogen energy utilization, has lower total costs and carbon emissions than the other three scenarios, while also having a higher wind power absorption rate. This demonstrates the effectiveness and economic viability of the proposed strategy.

[0123] Table 3 Scheduling results for different scenarios

[0124]

[0125] 2) Analysis of hydrogen blending benefits at different hydrogen blending ratios

[0126] The total cost of IES and actual carbon emissions under different hydrogen blending ratios of gas turbines are as follows: Figure 3 As shown in the figure, as the hydrogen blending ratio increases, the total IES cost shows a trend of first decreasing and then leveling off. When the hydrogen blending ratio of the gas turbine is less than 15%, the total IES cost decreases significantly. The main reason is that hydrogen replaces part of the natural gas, which reduces fuel costs and reduces the carbon trading costs caused by carbon emissions. When the hydrogen blending ratio reaches 15%, the rate of total cost decline slows down. This is because further increasing the hydrogen blending ratio requires more electrolytic hydrogen production, resulting in increased electricity consumption, which partially offsets the fuel cost savings. Actual carbon emissions decrease with increasing hydrogen blending ratio, but after the hydrogen blending ratio exceeds 15%, the emission reduction effect tends to level off and then increase. This is because at high hydrogen blending ratios, the energy consumption of electrolytic hydrogen production increases, indirectly increasing the output demand of coal-fired units, thereby partially offsetting the emission reduction effect of hydrogen blending.

[0127] The carbon emissions of gas-fired units (GT, GB) and coal-fired units (thermal power units) under different hydrogen blending ratios are as follows: Figure 4 shown. Figure 4 Comparing the carbon emissions of gas-fired and coal-fired units at different hydrogen blending ratios, the carbon emissions of gas-fired units decreased significantly with increasing hydrogen blending ratios. Increasing the hydrogen blending ratio from 10% to 20% reduced carbon emissions from gas-fired units by approximately 12%. This is because hydrogen combustion does not produce CO2, directly reducing the carbon emission intensity of gas-fired units. Carbon emissions from coal-fired units decreased slightly at low hydrogen blending ratios but increased slightly at high hydrogen blending ratios. This is due to the increased energy consumption of hydrogen electrolysis, which increases the IES's reliance on coal-fired units and thus increases its carbon emissions.

[0128] Green certificate income with different hydrogen blending ratios is as follows Figure 5 As shown in Figure 2, as the hydrogen blending ratio of GB increases, the returns from green certificate trading show an upward and then stable trend. When the hydrogen blending ratio is between 10% and 15%, green certificate returns grow rapidly, primarily due to the increased wind power absorption rate. However, when the hydrogen blending ratio exceeds 18%, the growth of green certificate returns slows. This is because the electricity demand for hydrogen production by electrolysis at high hydrogen blending ratios approaches the maximum output limit of wind power, and further increasing the hydrogen blending ratio has limited effect on promoting wind power absorption.

[0129] comprehensive Figures 3 to 5 Results show that when the hydrogen blending ratio is between 15% and 18% for gas turbines and 14% and 16% for gas boilers, IES can achieve a good balance between economy and low carbon performance. This results in lower total costs, significantly reduced carbon emissions, and higher green certificate returns. However, when the hydrogen blending ratio exceeds 18%, further increases in the ratio have limited economic benefits and emission reduction effects, and may even be counterproductive due to increased electricity consumption. Therefore, the hydrogen blending ratio in gas turbines and gas boilers must be strictly controlled within a safe range to avoid unstable combustion and reduced equipment efficiency.

[0130] 3) Analysis of Tiered Green Certificate Trading Parameters Taking into Account the Reward and Punishment Characteristics

[0131] The changes in IES total cost and carbon emissions under different green certificate trading interval lengths and green certificate quota coefficients are as follows: Figure 6-Figure 8 As shown. Figure 6 It can be seen that when the ladder transaction length is short, the IES total cost is more sensitive to changes in the green certificate trading volume. A smaller interval length will accelerate the triggering of penalties or rewards, prompting IES to more strictly control the green certificate trading volume to avoid high penalties. At this time, the total cost shows a fluctuating downward trend. When the ladder transaction length increases, the IES total cost gradually stabilizes. A larger interval length reduces the frequency of penalties, providing IES with a more relaxed adjustment space, but may weaken the emission reduction incentive effect. Figure 7 This shows that IES carbon emissions are lowest when the green certificate trading interval length is 60. Figure 6 and Figure 8 It can be seen that when the quota coefficient is low, IES has less demand for green certificates, limited trading returns, and higher total costs. In this scenario, the system relies more heavily on traditional energy, resulting in relatively high carbon emissions. As the quota coefficient increases, IES can increase the issuance of green certificates by increasing wind power consumption. This significantly increases trading returns and reduces total costs, but IES carbon emissions tend to rise. Analysis shows that a green certificate trading interval of 60MW and a green certificate quota coefficient of 0.4 are ideal for achieving a balance between economic efficiency and emission reduction goals.

[0132] Taking scenario 4 as an example, the carbon emissions and wind power consumption rates under different green certificate basic transaction prices are as follows: Figure 9 As shown in the figure. When the price of Green Certificates was low (30 yuan / MW), the IES system was less enthusiastic about trading Green Certificates, preferring to pay carbon emission penalties, resulting in higher carbon emissions. As the price rose to 70 yuan / MW, the economics of purchasing Green Certificates increased, and the IES reduced carbon emissions by increasing wind power consumption or Green Certificate trading. When the price reached 50 yuan / MW, carbon emissions dropped to approximately 2,847 tons. The price of Green Certificates was positively correlated with the wind power consumption rate. When the price increased from 30 yuan / MW to 50 yuan / MW, the wind power consumption rate increased from 89% to 90.56%. After the price exceeded 60 yuan / MW, the consumption rate stabilized.

[0133] Applying the above technical solution, it can be seen that by refining P2G into a two-stage process of P2H and methanation, IES not only avoids the problem of low overall efficiency of traditional P2G, but also reduces natural gas consumption and carbon emissions by directly adding hydrogen to gas turbines and boilers. When the hydrogen blending ratio of the gas turbine is optimized to 15% to 18%, its carbon emissions are reduced by about 12%, and the total cost is reduced by 5.3%, verifying the low carbon and economic benefits of hydrogen blending; the synergy of the step-by-step green certificate trading mechanism and carbon offset that takes into account the reward and punishment characteristics further converts carbon emission constraints into economic benefits. In scenario 4, the green certificate trading income reaches 105,700 yuan. At the same time, the carbon emissions are offset by green certificates, which significantly reduces the carbon trading cost. This shows that the method proposed in the present invention improves the economic efficiency and carbon emission level of IES operation while improving the operational flexibility of the hydrogen-containing integrated energy system.

[0134] The specific embodiments of the present invention are described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Various changes can be made within the knowledge of ordinary technicians in this field without departing from the scope of the present invention.

Claims

1. A method for optimizing and scheduling an integrated energy system taking into account carbon emissions and multi-level utilization of hydrogen energy, characterized in that: include: Based on the integrated energy system architecture, establish a multi-level carbon emission utilization model and a multi-level hydrogen energy utilization model; Based on the carbon emission multi-stage utilization model and the hydrogen energy multi-stage utilization model, an integrated energy system optimization scheduling model considering the carbon emission and hydrogen energy multi-stage utilization is established; the integrated energy system optimization scheduling model considering the carbon emission and hydrogen energy multi-stage utilization includes an objective function and constraints that minimize the comprehensive operating cost of the integrated energy system; Solve the optimal scheduling model of the integrated energy system considering carbon emissions and multi-level utilization of hydrogen energy.

2. The method for optimizing and scheduling an integrated energy system taking into account carbon emissions and multi-level utilization of hydrogen energy according to claim 1, characterized in that: The establishment of the multi-level carbon emission utilization model is specifically as follows: Establish a CCS model; determine the mass of CO2 captured by carbon capture in the CCS model based on the established carbon utilization and carbon storage model; Based on the number of green certificates required by IES and the number of green certificates obtained by IES, the number of green certificates participating in the green certificate market is calculated; based on the number of green certificates participating in the green certificate market, a ladder green certificate trading model is established; based on the number of green certificates required by IES and the quality of CO2 captured by carbon capture, a ladder carbon-green certificate coupling trading mechanism is constructed to obtain carbon emission rights to re-participate in the carbon trading market after considering green certificate-carbon offset; Establish a ladder carbon trading model; based on the ladder carbon trading model, trade the carbon emission rights that re-participate in the carbon trading market after considering green certificate-carbon offset, and obtain the carbon trading cost of the comprehensive energy system.

3. The method for optimizing and scheduling an integrated energy system taking into account carbon emissions and multi-level utilization of hydrogen energy according to claim 2, characterized in that: According to the number of green certificates required by IES and the quality of CO2 captured by carbon capture, a step-by-step carbon-green certificate coupling trading mechanism is constructed to obtain the carbon emission rights to re-participate in the carbon trading market after considering green certificates-carbon offset. Specifically: according to the number of green certificates required by IES, the green certificate carbon offset amount is obtained; according to the quality of CO2 captured by the carbon capture, the carbon emission rights to participate in carbon trading are obtained; according to the carbon emission rights to participate in carbon trading and the green certificate carbon offset amount, the carbon emission rights to re-participate in the carbon trading market after considering green certificates-carbon offset are obtained.

4. The method for optimizing and scheduling an integrated energy system taking into account carbon emissions and multi-level utilization of hydrogen energy according to claim 1, characterized in that: The establishment of the multi-stage hydrogen energy utilization model is specifically as follows: The power-to-gas (PtG) system in the integrated energy system is divided into two stages: the electrolyzer (EL) and the methane reactor (MR). One stage generates natural gas through the MR, and the other stage meets the hydrogen blending requirements of the gas-fired unit. The multi-stage hydrogen utilization model for PtG specifically includes: P2G two-stage model: Gas turbine GT hydrogen blending model: Gas boiler GB hydrogen blending model: Where, and is the hydrogen production power and power consumption of the electrolyzer at time t; is the hydrogen consumption power of the methane reactor at time t; is the gas production power of MR at time t; η EL ,η MR are the conversion efficiencies of EL and MR, respectively; and are the electrical and thermal output power of the gas turbine (GT) at time t, respectively; and are the electrical and thermal efficiencies of GT, respectively; and are the natural gas and hydrogen power consumed by GT at time t, respectively; is the hydrogen doping ratio of GT at time t; is the calorific value of natural gas; is the calorific value of hydrogen; is the total output of GT at time t; They are the upper and lower limits of GT power output respectively; The upper and lower limits of GT thermal output; They are the upper and lower limits of GT output climbing respectively; is the heat generation power of GB at time t; is the hydrogen doping ratio of GB at time t; η GB is the heat generation efficiency of GB; are the hydrogen and natural gas power consumption of GB at time t, respectively; and is the relative molecular mass of hydrogen and natural gas; is the hydrogen doping ratio of GB at time t; The upper and lower limits of GB heat generation power; They are the upper and lower limits of GB heat generation power ramping respectively; is the density of CH4; is the density of H2.

5. The method for optimizing and scheduling an integrated energy system taking into account carbon emissions and multi-level utilization of hydrogen energy according to claim 1, characterized in that: The operating costs involved in the objective function include: carbon trading costs, green certificate trading costs, carbon sequestration costs, start-up and shutdown costs of coal-fired units, coal consumption costs of coal-fired units, gas purchase costs, and wind curtailment costs; the constraints include: electric power balance constraints, wind power supply constraints, and coal-fired unit ramp-up and output constraints.

6. An integrated energy system optimization and scheduling system taking into account carbon emissions and multi-level utilization of hydrogen energy, characterized in that: A module comprising a method for optimizing and scheduling an integrated energy system taking into account carbon emissions and multi-level utilization of hydrogen energy as described in any one of claims 1-5.

7. A processor, characterized in that: The processor is used to execute operations, including executing the integrated energy system optimization scheduling method taking into account carbon emissions and multi-level utilization of hydrogen energy according to any one of claims 1-5.

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