Hydrogen integrated energy dispatching method and system integrating green certificate and carbon emission trading

Abstract

The present invention provides a hydrogen integrated energy dispatching method and system integrating green certificate and carbon emission trading, comprising: building a day-ahead price type demand response model and an alternative demand response model on the basis of the composition and operation characteristics of a hydrogen integrated energy system; building a stepped carbon emission trading model and a stepped green certificate trading model; building an integrated mechanism of green certificate trading and carbon emission trading; and building an optimized dispatching model of the hydrogen integrated energy system on the basis of the energy purchase cost, the green certificate trading income, and the carbon emission trading cost. By building a mechanism integrating stepped green certificate trading and stepped carbon emission trading, a dispatching strategy method of the hydrogen integrated energy system under the mechanism is further provided, which reduces the carbon emission level and improves the operation economy.

Description

A hydrogen-containing integrated energy scheduling method and system integrating green certificates and carbon trading Technical Field

[0001] The present invention relates to the field of energy scheduling technology, and in particular to a hydrogen-containing integrated energy scheduling method and system that integrates green certificates and carbon trading. Background Art

[0002] A hydrogen integrated energy system (HIES) integrates electricity, heat, and power-to-gas (P2G) equipment into a single system, capable of meeting diverse terminal load requirements. HIES, characterized by cleanliness and efficiency, is an effective approach to building new power systems, boasting promising application prospects and attracting widespread academic attention. To further reduce carbon emissions, the carbon emissions trading scheme (ETS) has been established. HIES can trade carbon emission rights through the carbon emission trading market (CET). The counterpart to CET is the tradable green certificate (TGC). HIES generates or consumes green electricity to obtain green certificates, which can be sold to generate revenue, provided that quotas are met by relevant departments. In the context of new power system development, integrating carbon trading with green certificate trading is a future development trend. Current research on the optimal operation of hydrogen-based IES focuses primarily on steady-state energy flow relationships, hybrid equipment modeling, and energy utilization. Most studies explore the optimal operation of hydrogen-based IES using different modeling methods and operation strategies. However, it only focuses on the economic efficiency of system operation and ignores the impact of environmental benefits such as carbon emissions on IES optimal scheduling.

[0003] In view of this, the present invention proposes a hydrogen-containing integrated energy scheduling method and system that integrates green certificates and carbon trading. By constructing a mechanism that integrates step-by-step green certificate trading with step-by-step carbon trading, a scheduling strategy method for the hydrogen-containing integrated energy system (HIES) under this mechanism is proposed, thereby reducing carbon emissions and improving operational economy.

[0004] Summary of the Invention

[0005] The purpose of the present invention is to provide a hydrogen-containing integrated energy scheduling method that integrates green certificates and carbon trading, including: constructing a day-ahead price demand response model and an alternative demand response model based on the composition and operating characteristics of the hydrogen-containing integrated energy system; constructing a step-by-step carbon emission trading model and a step-by-step green certificate trading model; constructing a fusion mechanism that integrates green certificate trading and carbon trading; and constructing an optimized scheduling model for the hydrogen-containing integrated energy system based on energy purchase costs, green certificate trading income and carbon trading costs.

[0006] Furthermore, the day-ahead price-based demand response model is constructed based on electricity prices; the electricity prices at least include peak and valley electricity prices; the expression of the day-ahead price-based demand response model is:

[0007] Where m is the electricity price elasticity index; L is the electricity consumption before load response; ΔL is the load response amount before load response; c p is the peak-valley electricity price; Δc p The difference between the peak and valley electricity price and the fixed electricity price; (*) -1 Indicates inversion.

[0008] Furthermore, the expression of the alternative demand response model is:

[0009] in, is the amount of replaceable electrical load; is the amount of heat load that can be replaced; ε e,h is the electricity-to-heat substitutability coefficient, where the negative sign indicates that a decrease in the replaceable electrical load corresponds to an increase in the replaced heat load; is the maximum value of the replaceable electric load; is the minimum value of the replaceable electric load; is the maximum value of the replaceable heat load; It is the minimum value of replaceable heat load.

[0010] Furthermore, the expression of the tiered carbon emissions trading model is:

[0011] Among them, for expression 1, E c -v <E p ≤E c ; For expression 2, E c <E p ≤E c +v; for expression 3, E c +v <E p ≤E c +2v; for expression 4, E c +2v <Ep ≤E c +3v; for expression 5, E c +3v <E p ; Carbon trading costs for carbon emission sources; is the increase in the ladder transaction price; ν is the length of the carbon emission ladder interval; is the basic transaction price in the carbon trading market; E c Carbon emission quotas allocated free of charge by the government; E P is the total carbon emission from various sources.

[0012] Furthermore, the expression of the step-by-step green certificate trading model is: N green =N own -N gov

[0013] Where, for Formula 6, 3l <N green ; For formula 7, 2l <N green ≤3l; for formula 8, l <N green ≤2l; for formula 9, 0 <N green ≤l; for formula 10, -l≤N green <0; for Formula 11, -2l≤N green <-l;f green Profits from selling green certificates for enterprises; c green is the basic transaction price in the green certificate trading market; α green and λ green are the increment of green certificate ladder transaction price when the quota index is exceeded or insufficient respectively; l is the length of green certificate ladder interval; N grenn The number of green certificates sold or purchased; N own The number of green certificates generated for the enterprise; N gov is the number of government quota indicators.

[0014] Furthermore, the construction of an integration mechanism for the integration of green certificate trading and carbon trading includes: calculating the carbon emission reduction represented by green certificates; calculating the carbon emission rights required for the hydrogen-containing integrated energy system; determining the conversion coefficient between carbon emission trading and green certificate trading based on the carbon emission trading price and the green certificate trading price; recalculating the number of green certificates and carbon emission rights of the enterprise; and re-participating in the tiered trading of the carbon emission trading market and the green certificate trading market after obtaining the new number of green certificates and carbon emission rights.

[0015] Furthermore, the expression of the conversion coefficient is:

[0016] Where k is the conversion coefficient; c greenThe basic transaction price in the green certificate trading market; It is the basic transaction price in the carbon trading market.

[0017] Furthermore, the expression for recalculating the number of green certificates and carbon emission rights of an enterprise is:

[0018] N′ green =N green -N tra

[0019] E′ p =E p -kN tra -μN′ green

[0020] Among them, N′ green N is the number of green certificates of the enterprise after recalculation; green The number of green certificates sold or purchased; N tra is the number of green certificates participating in the conversion; E′ p is the recalculated amount of carbon emission rights of the enterprise; k is the conversion coefficient; μ is the carbon emission reduction coefficient represented by the green certificate.

[0021] Furthermore, the construction of an optimization scheduling model for a hydrogen-containing integrated energy system includes:

[0022] Construct an optimization scheduling objective function; the expression of the optimization scheduling objective function is:

[0023] Among them, min(*) is the minimum value; is the carbon trading cost of carbon emission sources; f green Profits from selling green certificates to enterprises; buy The cost of purchased energy;

[0024] Construct optimal dispatch constraints; the optimal dispatch constraints include grid interaction power constraints, wind power output constraints, photovoltaic output constraints, electric power balance constraints, thermal power balance constraints, hydrogen power balance constraints, gas power balance constraints, and green certificate constraints for participating in conversion:

[0025] The expression of the grid interaction power constraint is:

[0026] Among them, P grid (t) represents the power interacting with the upper grid at time t; The maximum power for interaction with the upper grid;

[0027] The expression of wind power output constraint is:

[0028] Among them, Pwind,buy (t) is the wind power purchased at time t; To purchase wind power cap;

[0029] The expression of the photovoltaic output constraint is:

[0030] Among them, P pv,buy (t) is the photovoltaic power purchased at time t; To purchase PV power cap;

[0031] The expression of the electric power balance constraint is:

[0032] Among them, P grid (t) is the electric power balance constraint; is the electric load power at time t; P is the electric power output of the cogeneration device at time t; wind,buy (t) is the wind power purchased at time t; P pv,buy (t) is the photovoltaic power purchased at time t; is the electrical power output by the heat pump at time t; is the electric power output of the electrolytic cell at time t; is the electric power output of the hydrogen fuel cell at time t;

[0033] The expression of the thermal power balance constraint is:

[0034] Where: is the heat load power at time t; is the heat storage power of the heat storage device at time t; is the thermal power output of the cogeneration device at time t; is the thermal power output by the heat pump at time t; is the thermal power output of the hydrogen fuel cell at time t; is the heat release power of the heat storage device at time t; is the thermal power output of the gas boiler at time t;

[0035] The expression of the hydrogen power balance constraint is:

[0036] in, is the hydrogen energy output by the electrolyzer at time t; is the hydrogen energy consumed by the methane reactor at time t; is the hydrogen energy consumed by the hydrogen fuel cell at time t; are the charging and discharging power of the hydrogen storage device at time t respectively;

[0037] The expression of the gas power balance constraint is:

[0038] Where: P g,buy (t) is the gas power purchased from the upper gas network at time t; is the natural gas power output by the methane reactor at time t; The natural gas power consumed by the gas boiler at time t; is the natural gas power input to CHP at time t;

[0039] The expression of the green certificate constraint participating in the conversion is: 0≤N tra ≤N green

[0040] Among them, N tra N is the number of green certificates participating in the conversion; green The number of green certificates sold or purchased.

[0041] The object of the present invention is to provide a hydrogen-containing integrated energy scheduling system that integrates green certificates and carbon trading, including a demand response model construction module, a trading model construction module, a fusion mechanism construction module and an optimization scheduling model construction module; the demand response model construction module is used to construct a day-ahead price demand response model and an alternative demand response model based on the composition and operation characteristics of the hydrogen-containing integrated energy system; the trading model construction module is used to construct a step-by-step carbon emission trading model and a step-by-step green certificate trading model; the fusion mechanism construction module is used to construct a fusion mechanism that integrates green certificate trading and carbon trading; the optimization scheduling model construction module is used to construct an optimization scheduling model for the hydrogen-containing integrated energy system based on energy purchase costs, green certificate trading income and carbon trading costs.

[0042] The technical solutions of the embodiments of the present invention have at least the following advantages and beneficial effects:

[0043] The present invention uses the green certificate-carbon trading integration mechanism to reduce system operating costs while increasing the proportion of green electricity by 2.4%, making it more energy-efficient and environmentally friendly.

[0044] The algorithm proposed in the present invention is more sensitive to the transaction information of the carbon trading market in determining whether the green certificate and carbon emission rights are converted, thereby improving the accuracy of the conversion. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] FIG1 is an exemplary flow chart of a hydrogen-containing integrated energy scheduling method integrating green certificates and carbon trading, provided in some embodiments of the present invention;

[0046] FIG2 is an exemplary schematic diagram of constructing a fusion mechanism according to some embodiments of the present invention;

[0047] Figure 3 is an exemplary module diagram of a hydrogen-containing integrated energy scheduling system that integrates green certificates and carbon trading, provided in some embodiments of the present invention. DETAILED DESCRIPTION

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0049] FIG1 is an exemplary flow chart of a hydrogen-containing integrated energy scheduling method that integrates green certificates and carbon trading, provided in some embodiments of the present invention. In some embodiments, process 100 can be executed by system 200. As shown in FIG1 , process 100 includes the following contents:

[0050] Step 110 : Based on the structure and operating characteristics of the hydrogen-containing integrated energy system, a day-ahead price demand response model and a substitutable demand response model are constructed. In some embodiments, step 110 may be executed by the demand response model construction module 310 .

[0051] Demand response (DR) is a key approach to achieving HIES energy balance. DR involves energy suppliers using pricing or incentives to encourage users to change their energy usage patterns during specific periods, reducing or shifting load during those periods to achieve energy supply and demand balance. Based on the load response characteristics, DR can be categorized as day-ahead price-based demand response and substitutable demand response.

[0052] In some embodiments, the day-ahead price-based demand response model is constructed based on electricity prices; the electricity prices include at least peak and valley electricity prices; the expression of the day-ahead price-based demand response model is:

[0053] Where m is the electricity price elasticity index; L is the electricity consumption before load response; ΔL is the load response amount; c p is the peak-valley electricity price; Δc p The difference between the peak and valley electricity price and the fixed electricity price; (*) -1 Indicates inversion.

[0054] In some embodiments, an electricity quantity and price elasticity matrix can be established based on the ratio of the time-of-use electricity price to the fixed electricity price:

[0055] Among them, M e is the electricity quantity and price elasticity matrix; M iiis the elastic coefficient; M ij is the cross elastic coefficient; L i , ΔL i are the power consumption of the user in period i and its change; c pi 、c pj and Δc pi , Δc pj are the electricity prices and their changes in time periods i and j respectively.

[0056] According to the elastic matrix M e , the user load change (i.e., load response ΔL) can be obtained as:

[0057] Where: L e,0,f , L e,0,p , L e,0,g are the electricity consumption in peak, flat and valley periods before the implementation of time-of-use electricity price in price-based demand response; c e,p0,f 、c e,p0,p 、c e,p0,g and Δc e,pf , Δc e,pp , Δc e,pg They respectively represent the price when peak and valley electricity prices are not implemented and the difference between the price and the peak, flat and valley electricity prices.

[0058] Some embodiments of the present invention, by introducing peak-valley electricity prices and guiding the demand side to reasonably change its own energy consumption through electricity prices, can reduce the impact of excessive peak-valley differences on the power grid.

[0059] For some loads that can be supplied by electricity or heat, according to the peak and valley electricity prices, electricity can be used when the electricity price is low, and heat can be used when the electricity price is high, thereby achieving mutual substitution of heat and electricity. In some embodiments, the expression of the substitutable demand response model is:

[0060] in, is the amount of replaceable electrical load; is the amount of heat load that can be replaced; ε e,h is the electricity-to-heat substitutability coefficient, where the negative sign indicates that a decrease in the replaceable electrical load corresponds to an increase in the replaced heat load; is the maximum value of the replaceable electric load; is the minimum value of the replaceable electric load; is the maximum value of the replaceable heat load; It is the minimum value of replaceable heat load.

[0061] Step 120 , constructing a tiered carbon emissions trading model and a tiered green certificate trading model. In some embodiments, step 120 may be performed by the trading model construction module 320 .

[0062] The carbon trading mechanism involves obtaining legal carbon emission rights through relevant departments and trading them as commodities on CET. The government first allocates carbon emission rights to individual carbon emission sources. Internationally, these allocations are often paid or free, while my country currently uses free allocation. When a carbon emission source's actual emissions exceed the allocated free quota, it must purchase carbon emission rights on CET. Otherwise, it can sell the remaining carbon emission rights on CET.

[0063] In some embodiments, in order to better control the total carbon emissions of carbon emission source enterprises, a tiered carbon emissions trading model is constructed. The greater the amount of carbon emission sources exceeding the free allocation, the higher the carbon trading price in the corresponding interval. The expression of the tiered carbon emissions trading model is:

[0064] Among them, for expression 1, E c -v <E p ≤E c ; For expression 2, E c <E p ≤E c +v; for expression 3, E c +v <E p ≤E c +2v; for expression 4, E c +2v <E p ≤E c +3v; for expression 5, E c +3v <E p ; Carbon trading costs for carbon emission sources; is the increase in the ladder transaction price; ν is the length of the carbon emission ladder interval; is the basic transaction price in the carbon trading market; E c Carbon emission quotas allocated free of charge by the government; E P is the total emissions from carbon emission sources. E Z The total carbon emissions of electricity purchased from the grid, CHP units and GB, E MR is the amount of CO2 absorbed by the methane reactor equipment.

[0065] To better implement the renewable energy quota system, the TGC was proposed. Power generation companies that generate electricity through renewable energy can obtain a certain number of green certificates. Similarly, electricity users that use green electricity can also obtain a certain number of green certificates. If a company's green certificates exceed its quota, it can sell them on the TGC to generate revenue. Otherwise, it must purchase green certificates on the market or face fines.

[0066] In some embodiments, in order to better integrate the carbon trading mechanism with the green certificate trading mechanism, the more green certificates an enterprise has, the higher the price at which it sells them. Conversely, the more green certificates an enterprise needs to purchase, the higher the price. The expression of the step-by-step green certificate trading model is: N green =N own -N gov

[0067] Where, for Formula 6, 3l <N green ; For formula 7, 2l <N green ≤3l; for formula 8, l <N green ≤2l; for formula 9, 0 <N green ≤l; for formula 10, -l≤N green <0; for Formula 11, -2l≤N green <-l;f green Profits from selling green certificates for enterprises; c green is the basic transaction price in the green certificate trading market; α green and λ green are the increment of green certificate ladder transaction price when the quota index is exceeded or insufficient respectively; l is the length of green certificate ladder interval; N grenn The number of green certificates sold or purchased; N own The number of green certificates generated for the enterprise; N gov is the number of government quota indicators.

[0068] Step 130 , constructing a fusion mechanism for integrating green certificate trading with carbon trading. In some embodiments, step 130 may be performed by the fusion mechanism construction module 330 .

[0069] Since green certificates contain all the information on the generation and consumption of new energy, and the carbon emission reductions of new energy supply can be quantitatively calculated, green certificates can be used to integrate the green certificate market and the carbon trading market, and the conversion relationship can be determined by the average trading price of green certificates and carbon emission rights. For more information on building a fusion mechanism, see Figure 2 and its related description.

[0070] Step 140 : Based on the energy purchase cost, green certificate trading income, and carbon trading cost, an optimized scheduling model for the hydrogen-containing integrated energy system is constructed. In some embodiments, step 140 may be executed by the optimized scheduling model construction module 340 .

[0071] In some embodiments, constructing the HIES optimization scheduling model includes:

[0072] Construct an optimization scheduling objective function; the expression of the optimization scheduling objective function is:

[0073] Among them, min(*) is the minimum value; is the carbon trading cost of carbon emission sources; f green Profits from selling green certificates to enterprises; buy The cost of purchased energy;

[0074] Construct optimal dispatch constraints; the optimal dispatch constraints include grid interaction power constraints, wind power output constraints, photovoltaic output constraints, electric power balance constraints, thermal power balance constraints, hydrogen power balance constraints, gas power balance constraints, and green certificate constraints for participating in conversion:

[0075] The expression of the grid interaction power constraint is:

[0076] Among them, P grid (t) represents the power interacting with the upper grid at time t; The maximum power for interaction with the upper grid;

[0077] The expression of wind power output constraint is:

[0078] Among them, P wind,buy (t) is the wind power purchased at time t; To purchase wind power cap;

[0079] The expression of the photovoltaic output constraint is:

[0080] Among them, P pv,buy (t) is the photovoltaic power purchased at time t; To purchase PV power cap;

[0081] The expression of the electric power balance constraint is:

[0082] Among them, P grid (t) is the electric power balance constraint; is the electric load power at time t; P is the electric power output of the cogeneration device at time t; wind,buy (t) is the wind power purchased at time t; P pv,buy (t) is the photovoltaic power purchased at time t; is the electrical power output by the heat pump at time t; is the electric power output of the electrolytic cell at time t; is the electric power output of the hydrogen fuel cell at time t;

[0083] The expression of the thermal power balance constraint is:

[0084] Where: is the heat load power at time t; is the heat storage power of the heat storage device at time t; is the thermal power output of the cogeneration device at time t; is the thermal power output by the heat pump at time t; is the thermal power output of the hydrogen fuel cell at time t; is the heat release power of the heat storage device at time t; is the thermal power output of the gas boiler at time t;

[0085] The expression of the hydrogen power balance constraint is:

[0086] in, is the hydrogen energy output by the electrolyzer at time t; is the hydrogen energy consumed by the methane reactor at time t; is the hydrogen energy consumed by the hydrogen fuel cell at time t; are the charging and discharging power of the hydrogen storage device at time t respectively;

[0087] The expression of the gas power balance constraint is:

[0088] Where: P g,buy (t) is the gas power purchased from the upper gas network at time t; is the natural gas power output by the methane reactor at time t; The natural gas power consumed by the gas boiler at time t; is the natural gas power input to CHP at time t;

[0089] The expression of the green certificate constraint participating in the conversion is: 0≤N tra ≤N green

[0090] Among them, N tra N is the number of green certificates participating in the conversion; greenThe number of green certificates sold or purchased.

[0091] Figure 2 is an exemplary schematic diagram of building a fusion mechanism provided by some embodiments of the present invention. As shown in Figure 2, the fusion mechanism for building a fusion of green certificate trading and carbon trading includes:

[0092] Calculate the carbon emission reduction represented by the Green Certificate. For example, compare the CO2 emission equivalents generated by thermal power generation and renewable energy power generation to determine the carbon emission reduction represented by the Green Certificate. Based on the carbon emission reduction represented by the Green Certificate, the company determines the number of Green Certificates it has obtained by producing or consuming renewable energy power through a hydrogen-containing integrated energy system.

[0093] Calculate the carbon emission rights required for a hydrogen-containing integrated energy system. For example, the CO2 emissions generated in the HIES can be calculated using methods such as carbon footprint or carbon emission flow, and converted into carbon emission rights. At the same time, the number of government free quotas can be subtracted to obtain the required carbon emission rights.

[0094] Based on the carbon emission trading price and the green certificate trading price, the conversion coefficient of carbon emission trading and green certificate trading is determined. In some embodiments, the expression of the conversion coefficient is:

[0095] Where k is the conversion coefficient; c green The basic transaction price in the green certificate trading market; It is the basic transaction price in the carbon trading market.

[0096] Recalculate the number of green certificates and carbon emission rights of the enterprise. In some embodiments, the expression for recalculating the number of green certificates and carbon emission rights of the enterprise is: N' green =N green -N tra E′ p =E p -kN tra -μN′ green

[0097] Among them, N′ green N is the number of green certificates of the enterprise after recalculation; green The number of green certificates sold or purchased; N tra is the number of green certificates participating in the conversion; E′ p is the recalculated amount of carbon emission rights of the enterprise; k is the conversion coefficient; μ is the carbon emission reduction coefficient represented by the green certificate.

[0098] After obtaining new green certificates and carbon emission rights, re-participate in the tiered trading of carbon emission trading market and green certificate trading market.

[0099] In some embodiments, the CPLEX solver can be called through the YALMIP toolkit in the MATLAB platform to solve the optimization scheduling model.

[0100] To validate the effectiveness of the proposed model, we set the carbon emission ladder interval length to 15, the unit carbon emission right trading price to 50 yuan per unit, the green certificate ladder interval length to 10, and the unit green certificate trading price to 50 yuan per unit. We also set the day-ahead price demand response to account for 35% of the total electricity load, and the alternative electricity and heat demand response to account for 5% of the total electricity and heat loads respectively. We then conducted a comparative analysis of the four scenarios.

[0101] Scenario 1: Considering demand response under the green certificate-carbon trading mechanism;

[0102] Scenario 2: Considering only demand response

[0103] Scenario 3: Considering only green certificates and carbon trading mechanisms

[0104] Scenario 4: The green certificate-carbon trading mechanism is not considered and the green certificate-carbon trading mechanism is not considered.

[0105] Simulation results analysis of various scheduling results are:

[0106] For scenario 1, the total operating cost is 251,493.47 yuan; the carbon trading cost is 4,200 yuan; the green certificate trading income is 1,647.77 yuan; and the proportion of green electricity is 32.85%.

[0107] For scenario 2, the total operating cost is 252,410.65 yuan; the carbon trading cost is 8,094.03 yuan; the green certificate trading income is 4,624.62 yuan; and the proportion of green electricity is 30.45%.

[0108] For scenario 3, the total operating cost is 258,032.46 yuan; the carbon trading cost is 2,400 yuan; the green certificate trading income is 0 yuan; and the proportion of green electricity is 33.26%.

[0109] For scenario 4, the total operating cost is 258,883.17 yuan; the carbon trading cost is 7,818.86 yuan; the green certificate trading income is 4,624.62 yuan; and the proportion of green electricity is 30.63%.

[0110] Compared to Scenario 2, while Scenario 1's green certificate trading revenue decreased by 2,976.85 yuan, its carbon trading costs decreased by 3,894.03 yuan, reducing total system operating costs by 917.18 yuan and increasing the proportion of green electricity by 2.4%. This is because Scenario 1, through the proposed "green certificate-carbon trading integration mechanism," converts green certificates into carbon emission rights, resulting in lower carbon trading costs and revenue, demonstrating the effectiveness of the proposed mechanism in promoting the green transformation of the system. Compared to Scenario 3, Scenario 1's total system operating costs decreased by 6,538.99 yuan. This is due to the inclusion of demand response, which reduces peak load and increases off-peak load. Furthermore, the use of P2G devices reduces electricity purchases during peak periods. Compared to Scenarios 1, 2, and 3, Scenario 4 does not incorporate either demand response or the green certificate-carbon trading integration mechanism. Therefore, with a low proportion of green electricity, the system's total operating costs are the highest, which is detrimental to the system's green development.

[0111] Figure 3 is an exemplary module diagram of a hydrogen-containing integrated energy scheduling system that integrates green certificates and carbon trading, provided in some embodiments of the present invention. As shown in Figure 3, system 300 includes a demand response model construction module 310, a transaction model construction module 320, a fusion mechanism construction module 330, and an optimization scheduling model construction module 340.

[0112] The demand response model construction module 310 is used to construct a day-ahead price demand response model and a substitutable demand response model based on the structure and operating characteristics of the hydrogen-containing integrated energy system. For more information about the demand response model construction module 310, see Figure 1 and its related description.

[0113] The trading model construction module 320 is used to construct a tiered carbon emissions trading model and a tiered green certificate trading model. For more information about the trading model construction module 320, see Figure 1 and its related description.

[0114] The integration mechanism construction module 330 is used to construct a fusion mechanism for integrating green certificate trading with carbon trading. For more information about the integration mechanism construction module 330, see Figure 1 and its related description.

[0115] The optimization scheduling model construction module 340 is used to construct an optimization scheduling model for the hydrogen-containing integrated energy system based on energy purchase costs, green certificate trading income, and carbon trading costs. For more information about the optimization scheduling model construction module 340, see Figure 1 and its related description.

[0116] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A hydrogen-containing comprehensive energy scheduling method integrating green certificates and carbon trading, characterized in that: include: Based on the composition and operation characteristics of the hydrogen-containing integrated energy system, a day-ahead price-based demand response model and a substitutable demand response model are constructed; Construct a tiered carbon emission trading model and a tiered green certificate trading model; Establish a fusion mechanism for integrating green certificate trading with carbon trading; Based on energy purchase costs, green certificate trading income and carbon trading costs, an optimal scheduling model for a hydrogen-containing integrated energy system is constructed.

2. The hydrogen-containing integrated energy scheduling method integrating green certificates and carbon trading according to claim 1 is characterized in that: The day-ahead price-based demand response model is constructed based on the electricity price; the electricity price at least includes the peak and valley electricity price; the expression of the day-ahead price-based demand response model is: Where m is the electricity price elasticity index; L is the electricity consumption before load response; ΔL is the load response before load response; c p is the peak-valley electricity price; Δc p The difference between the peak and valley electricity price and the fixed electricity price; (*) -1 Indicates inversion.

3. The hydrogen-containing comprehensive energy scheduling method integrating green certificates and carbon trading according to claim 1 is characterized in that: The expression of the alternative demand response model is: in, is the amount of replaceable electrical load; is the replaceable heat load; e,h is the electricity-to-heat substitutability coefficient, where the negative sign indicates that a decrease in the replaceable electrical load corresponds to an increase in the replaced heat load; is the maximum value of the replaceable electrical load; is the minimum value of replaceable electrical load; is the maximum value of replaceable heat load; It is the minimum value of replaceable heat load.

4. The hydrogen-containing integrated energy scheduling method integrating green certificates and carbon trading according to claim 1 is characterized in that: The expression of the tiered carbon emission trading model is: Among them, for expression 1, E c -v <E p ≤E c ; For expression 2, E c <E p ≤E c +v; for expression 3, E c +v <E p ≤E c +2v; for expression 4, E c +2v <E p ≤E c +3v; for expression 5, E c +3v <E p ; Carbon trading costs for carbon emission sources; is the increase of the ladder transaction price; ν is the length of the carbon emission ladder interval; is the basic transaction price in the carbon trading market; E c Carbon emission quotas allocated free of charge by the government; P is the total emissions from carbon emission sources.

5. The hydrogen-containing comprehensive energy scheduling method integrating green certificates and carbon trading according to claim 1 is characterized in that: The expression of the step-by-step green certificate trading model is: N green =N own -N gov Where, for Formula 6, 3l <N green ; For formula 7, 2l <N green ≤3l; for formula 8, l <N green ≤2l; for formula 9, 0 <N green ≤l; for formula 10, -l≤N green <0; for formula 11, -2l≤N green <-l;f green Proceeds from selling green certificates for enterprises; green is the basic transaction price in the green certificate trading market; α green and λ green are the growth rates of green certificate ladder transaction prices when they exceed or fall short of the government quota indicators; l is the length of the green certificate ladder interval; N grenn The number of green certificates sold or purchased; N own The number of green certificates generated for the enterprise; N gov is the number of government quota indicators.

6. The hydrogen-containing comprehensive energy scheduling method integrating green certificates and carbon trading according to claim 1 is characterized in that: The integration mechanism of green certificate trading and carbon trading includes: Calculate the carbon emission reduction represented by the green certificate; Calculate the carbon emission rights required for an integrated energy system containing hydrogen; Based on the carbon emission trading price and green certificate trading price, determine the conversion coefficient of carbon emission trading and green certificate trading; Recalculate the number of green certificates and carbon emission rights of enterprises; After obtaining a new number of green certificates and carbon emission rights, we will re-participate in the tiered trading of the carbon emission trading market and the green certificate trading market.

7. The hydrogen-containing integrated energy scheduling method integrating green certificates and carbon trading according to claim 6 is characterized in that: The expression of the conversion coefficient is: Where k is the conversion coefficient; c green It is the basic transaction price in the green certificate trading market; It is the basic transaction price in the carbon trading market.

8. The hydrogen-containing integrated energy scheduling method integrating green certificates and carbon trading according to claim 4 is characterized in that: The expression for recalculating the number of green certificates and carbon emission rights of an enterprise is: N′ green =N green -N tra HAVE BEEN' p =E p -kN tra -μN′ green Among them, N′ green N is the number of green certificates of the enterprise after recalculation; green The number of green certificates sold or purchased; N tra is the number of green certificates involved in the conversion; E′ p is the number of carbon emission rights of the enterprise after recalculation; k is the conversion coefficient; μ is the carbon emission reduction coefficient represented by the green certificate.

9. The hydrogen-containing integrated energy scheduling method integrating green certificates and carbon trading according to claim 1 is characterized in that: The construction of the optimization scheduling model of the hydrogen-containing integrated energy system includes: Construct an optimization scheduling objective function; the expression of the optimization scheduling objective function is: Among them, min(*) is the minimum value; is the carbon trading cost of carbon emission sources; green Proceeds from selling green certificates for enterprises; buy The cost of purchasing energy; Construct optimal dispatch constraints; the optimal dispatch constraints include grid interaction power constraints, wind power output constraints, photovoltaic output constraints, electric power balance constraints, thermal power balance constraints, hydrogen power balance constraints, gas power balance constraints and green certificate constraints for participating in conversion: The expression of the grid interaction power constraint is: Among them, P grid (t) represents the power interacting with the upper grid at time t; The maximum power for interaction with the upper grid; The expression of wind power output constraint is: Among them, P wind,buy (t) is the wind power purchased at time t; To purchase wind power cap; The expression of the photovoltaic output constraint is: Among them, P pv,buy (t) is the photovoltaic power purchased at time t; To purchase the PV power cap; The expression of the electric power balance constraint is: Among them, P grid (t) is the electric power balance constraint; is the electric load power at time t; P is the electric power output of the cogeneration device at time t; wind,buy (t) is the wind power purchased at time t; P pv,buy (t) is the photovoltaic power purchased at time t; is the electrical power output of the heat pump at time t; is the electric power output of the electrolytic cell at time t; is the electric power output of the hydrogen fuel cell at time t; The expression of the thermal power balance constraint is: Where: is the heat load power at time t; is the heat storage power of the heat storage device at time t; is the thermal power output of the cogeneration device at time t; is the thermal power output of the heat pump at time t; is the thermal power output of the hydrogen fuel cell at time t; is the heat release power of the heat storage device at time t; is the thermal power output of the gas boiler at time t; The expression of the hydrogen power balance constraint is: in, is the hydrogen energy output by the electrolyzer at time t; is the hydrogen energy consumed by the methane reactor at time t; is the hydrogen energy consumed by the hydrogen fuel cell at time t; They are the charging and discharging power of the hydrogen storage device at time t respectively; The expression of the gas power balance constraint is: Where: P g,buy (t) is the gas power purchased from the upper gas network at time t; is the natural gas power output by the methane reactor at time t; The natural gas power consumed by the gas boiler at time t; is the natural gas power input to CHP at time t; The expression of the green certificate constraint participating in the conversion is: 0≤N tra ≤N green Among them, N tra N is the number of green certificates participating in the conversion; green The number of green certificates sold or purchased.

10. A hydrogen-containing integrated energy dispatching system integrating green certificates and carbon trading, characterized in that: It includes demand response model building module, transaction model building module, fusion mechanism building module and optimization scheduling model building module; The demand response model building module is used to build a day-ahead price demand response model and a substitutable demand response model based on the composition and operation characteristics of the hydrogen-containing integrated energy system; The trading model building module is used to build a tiered carbon emission trading model and a tiered green certificate trading model; The integration mechanism building module is used to build an integration mechanism for integrating green certificate trading and carbon trading; The optimization scheduling model building module is used to build an optimization scheduling model for a hydrogen-containing integrated energy system based on energy purchase costs, green certificate trading income and carbon trading costs.

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