Comprehensive energy system low-carbon scheduling method considering electricity-to-ammonia and demand response

Abstract

The invention relates to an integrated energy system low-carbon scheduling method considering electricity-to-ammonia and demand response. The electricity-to-ammonia operation mechanism is subjected to refined modeling, and a multi-energy coupling model of thermal power utilization and ammonia-coal co-combustion in the electricity-to-ammonia conversion process is discussed. Meanwhile, a comprehensive demand response model is established according to transferable and interruptible characteristics of the electric heating load in order to excavate the response capability of demand side resources. In addition, in order to improve the low-carbon characteristic of the system, a stepped carbon transaction mechanism is introduced to reflect the environmental protection characteristic of the integrated energy system, and a low-carbon scheduling model of the integrated energy system is constructed by taking the minimum comprehensive cost as the target. According to the method, the collaborative carbon reduction capacity of the two sides of the source and the load is fully exerted, the wind and light absorption capacity can be further improved by introducing an electro-ammonia conversion mechanism, and collaborative optimization of low carbon and economical efficiency is achieved.

Description

Technical Field

[0001] The present invention belongs to the field of low-carbon operation optimization of integrated energy systems, and particularly relates to a low-carbon scheduling method for integrated energy systems considering power-to-ammonia and demand response. Background Technique

[0002] With the substantial increase in the access amount of wind and solar power generation, the volatility and randomness of its output limit the system's consumption of renewable energy, resulting in a large amount of wind and solar resources being wasted during low load periods. In this context, using green electricity to produce ammonia and combining it with the ammonia-coal co-firing technology is of great significance for reducing the integrated energy system's dependence on fossil fuels and promoting the decarbonization process.

[0003] "Green ammonia" has inestimable potential in stabilizing wind and solar fluctuations, participating in the demand management of the source side of integrated energy systems, and solving the difficult problems of hydrogen storage and transportation for power-to-hydrogen. Through the collaborative optimization of ammonia energy with demand-side resources and the carbon trading mechanism, and by fully and precisely utilizing the ammonia energy and thermal energy in the power-to-ammonia process, the operation flexibility of the integrated energy system can be improved, and its energy-saving and emission-reduction potential can be fully exerted.

[0004] Integrated demand response guides users to participate in load regulation through energy price signals, which can effectively promote the consumption of renewable energy and reduce carbon dioxide emissions, and plays an important role in promoting the transformation of integrated energy systems towards sustainable development. By fully exploring the coordination and cooperation between the demand side and the source side, good interaction between the source and the load can be promoted.

[0005] To improve the environmental sustainability of integrated energy systems, introducing a stepped carbon trading mechanism to quantify carbon emission rights as a schedulable resource with economic value can fully tap the emission reduction potential and serve as an effective economic means to incentivize environmental protection production strategies.

[0006] Existing research on ammonia energy utilization mostly focuses on the analysis of energy flow characteristics, lacking the collaborative optimization of ammonia energy with demand-side resources and the carbon trading mechanism, and not fully and precisely utilizing the ammonia energy and thermal energy in the power-to-ammonia process, resulting in limited system flexibility and difficulty in exerting its low-carbon potential. Therefore, from the perspectives of promoting the consumption of renewable energy, improving the energy structure, and promoting system energy conservation and emission reduction, it is of great significance to establish a low-carbon operation model for integrated energy systems considering power-to-ammonia and demand response. Summary of the Invention

[0007] The present invention proposes a low-carbon scheduling method for integrated energy systems considering power-to-ammonia and demand response. A low-carbon scheduling model integrating power-to-ammonia, demand response, and the carbon trading mechanism is constructed. Through the refined modeling of power-to-ammonia, the utilization of the thermal power of ammonia synthesis, ammonia-coal co-firing, and the response of electric and thermal loads, the collaborative utilization of ammonia energy and demand-side resources is optimized, the energy conversion efficiency, system flexibility, and the consumption capacity of renewable energy are improved, and the collaborative optimization of low-carbon and economy is achieved.

[0008] The beneficial effects of the present invention are as follows: The low-carbon scheduling method involved in the present invention gives full play to the collaborative carbon reduction capabilities on both the source and load sides, and the introduction of the power-to-ammonia mechanism can further improve the accommodation capacity of wind and solar power, effectively enhancing the economic efficiency and environmental friendliness of the operation of the integrated energy system. Description of the Drawings

[0009] Figure 1 It is a flowchart of the low-carbon scheduling method for the integrated energy system considering power-to-ammonia and demand response of the present invention.

[0010] Figure 2 It is a framework diagram of the integrated energy system considering power-to-ammonia and demand response of the present invention.

[0011] Figure 3 It is a prediction curve graph of wind power output, photovoltaic power output, electrical load and heat load of the present invention.

[0012] Figure 4 It is a graph of the power energy scheduling results of the three scenarios set by the present invention.

[0013] Figure 5 It is a graph of the heat energy scheduling results of the three scenarios set by the present invention.

[0014] Figure 6 It is an analysis graph of the sensitivity of the carbon emission price of the present invention. Detailed Embodiments

[0015] A low-carbon scheduling method for an integrated energy system considering power-to-ammonia and demand response. The low-carbon scheduling method described in the technical solution of the present invention constructs an operation framework of an integrated energy system containing ammonia energy, models the ammonia synthesis system of electrolytic water hydrogen production, air separation nitrogen production, power-to-ammonia, and ammonia-coal co-fired units, and constructs a mathematical model in combination with the characteristics of energy conversion equipment and energy storage equipment. At the same time, analyzes the response characteristics of demand-side resources and constructs a combined heat and power integrated demand response model to maximize the regulation ability of the load side. In addition, a stepped carbon trading mechanism is introduced to construct a source-load low-carbon economic scheduling model with the goal of minimizing the comprehensive cost. Through scheme comparison, the effectiveness of the collaborative optimization of the power-to-ammonia, combined heat and power IDR model and the stepped carbon trading mechanism proposed by the present invention for the low-carbon and economic operation of the integrated energy system is verified.

[0016] As Figure 1 shown, the flowchart of the low-carbon scheduling method for the integrated energy system considering power-to-ammonia and demand response proposed by the present invention specifically includes the following steps: 1) Construct a refined power-to-ammonia model and an ammonia-coal co-firing model, and establish models for other energy conversion equipment and energy storage equipment; 2) Establish a combined heat and power integrated demand response model according to the transferable and interruptible characteristics of the electrical load and heat load, and introduce a stepped carbon trading mechanism; 3) Establish a low-carbon optimal scheduling model for an integrated energy system considering power-to-ammonia and demand response; 4) Obtain the equipment and operation parameters of the integrated energy system, as well as the predicted values of wind, light, and load; 5) Solve the established low-carbon optimal scheduling model for the ammonia-integrated energy system to obtain the optimal scheduling plan.

[0017] The implementation method is specifically elaborated as follows.

[0018] Operation framework and model construction of an integrated energy system considering power-to-ammonia.

[0019] This paper constructs an integrated energy system coupled with power-to-ammonia, and its overall framework is as Figure 2 shown. The energy supply side includes wind and light generating units, coal-fired units, and natural gas sources. Energy conversion equipment includes P2A, CHP, GB, and WHB. Energy storage equipment includes electrical energy storage, thermal energy storage, and ammonia energy storage. Electrical load is supplied by wind and light generating units, coal-fired units, CHP, and electrical energy storage, and thermal load is supplied by GB, WHB, and thermal energy storage.

[0020] The power-to-ammonia module proposed in this paper mainly includes EL hydrogen production, ASU nitrogen production, and P2A links, and is modeled according to the characteristics of its equipment.

[0021] EL model: The electrolytic water hydrogen production link usually consists of multiple hydrogen production machines. Advanced control strategies and unit combinations can be used to improve the flexible adjustment ability of the electrolytic hydrogen production equipment, so as to better adapt to the volatility of renewable energy power generation. Its model is as follows:

[0022] In the formula: is the t hydrogen production in period ; is the t electrical energy consumption of electrolytic hydrogen production in period ; is the efficiency of electrolytic hydrogen production; , are respectively t the upper and lower limits of the input power of electrolytic hydrogen production in period ; , are respectively the maximum allowable upper and lower ramp powers of electrolytic hydrogen production.

[0023] ASU model:

[0024] In the formula: is the t nitrogen production in period ; , are respectively tPower consumption and unit power consumption of the ASU during a period; 、 are respectively t the upper and lower limits of the power input of the ASU during a period.

[0025] P2A model: In the electro-ammonia conversion stage, the produced hydrogen and nitrogen are mixed in proportion and ammonia is synthesized through the Haber-Bosch process. Heat is released during the ammonia synthesis process, and the generated heat can be provided to the heat load. The P2A model is as follows:

[0026] In the formula: is t the ammonia production during a period; is t the power consumption of P2A during a period; is the efficiency of P2A; is t the heat power provided to the system during the ammonia synthesis process in a period; is the heat release efficiency of the heat power provided by P2A; is the heat effect coefficient released per unit of ammonia synthesis; the volume ratio of ammonia, nitrogen, and hydrogen is 2:1:3; 、 are respectively the upper and lower limits of the power input of P2A; 、 are respectively the upper and lower limits of the ramp power of P2A.

[0027] Ammonia-co-firing model of a coal-fired unit: In a coal-fired unit retrofitted with ammonia-co-firing technology, ammonia replaces a certain proportion of the heat of pulverized coal in the boiler, making it have better furnace temperature control. The actual coal consumption of ammonia-co-firing is as follows:

[0028] In the formula: 、 are respectively t the coal consumption and ammonia consumption of the coal-fired unit during a period; is t the power generation of the coal-fired unit during a period; 、 and are respectively the fuel coefficients of coal; 、 are respectively the unit calorific values of coal and ammonia under standard conditions; is t the ammonia doping rate of the coal-fired unit during a period; 、 are respectivelyt The maximum and minimum power generations of the coal-fired unit during the time period; 、 are respectively the upper and lower limits of the ramping power of the coal-fired unit; 、 are respectively t the maximum and minimum ammonia doping rates of the coal-fired unit during the time period.

[0029] CHP model:

[0030] In the formula: is t the natural gas consumption of CHP during the time period; is t the power generation of CHP during the time period; 、 and are respectively the fuel coefficients of CHP; is t the thermal power released by CHP during the time period; 、 are respectively the efficiency and heat loss coefficient of CHP; 、 are respectively t the upper and lower limits of the electric power output of CHP during the time period; 、 are respectively the upper and lower limits of the ramping power of CHP.

[0031] GB model:

[0032] In the formula: is t the natural gas consumption of GB during the time period; is t the calorific value of GB during the time period; is the efficiency of GB; 、 are respectively t the upper and lower limits of the electric power output of GB during the time period; 、 are respectively the upper and lower limits of the ramping power of GB.

[0033] WHB model:

[0034] In the formula: is t the power generation of WHB during the time period; is the efficiency of WHB; and are respectivelyt The upper and lower limits of the power output of the WHB during a time period; and are respectively the upper and lower limits of the ramping power of the WHB.

[0035] Energy storage device modeling: (1) The electrical energy storage model considering the operating state is as follows:

[0036] In the formula: and are respectively the 0 / 1 integer variables of the charging and discharging states of the electrical energy storage; and are respectively t the charging and discharging powers of the electrical energy storage during a time period; and are respectively the maximum values of the charging and discharging powers of the electrical energy storage to the outside; and are respectively the charging and discharging efficiencies of the electrical energy storage; is the installed capacity of the electrical energy storage; and are respectively the upper and lower limits of the state of charge of the electrical energy storage; the state of charge should be equal at the beginning and end of an optimization period T.

[0037] (2) The thermal energy storage model considering its own heat loss is as follows:

[0038] In the formula: and are respectively the 0-1 variables of the charging and discharging states of the thermal energy storage; and are respectively t the charging and discharging energy powers of the thermal energy storage during a time period; and are respectively the maximum values of the charging and discharging energy powers of the thermal energy storage to the outside; and are respectively the charging and discharging energy efficiencies of the thermal energy storage; is the self-discharging energy coefficient of the thermal energy storage; is the installed capacity of the thermal energy storage; and are respectively the upper and lower limits of the load state of the thermal energy storage; the load state should be equal at the beginning and end of an optimization period T.

[0039] (3) The ammonia energy storage model is as follows:

[0040] In the formula: and are respectively tCharging and discharging power of ammonia energy storage during a period; and are respectively t 0-1 variables of the charging and discharging states of ammonia energy storage during a period; and are respectively the maximum values of the charging and discharging power of ammonia energy storage; is t the total power of ammonia energy storage during a period; is the gas constant of ammonia; is the ambient temperature; is t the load state of ammonia energy storage during a period; is the installed capacity of ammonia energy storage; and are respectively the upper and lower limits of the load state of ammonia energy storage.

[0041] Demand-side management strategy According to the characteristics of the demand-side load, the electric load is divided into fixed load, shiftable load and interruptible load. After implementing incentive-based demand response on the electric load, the actual electric load is as follows:

[0042] In the formula: , , and are respectively t the actual electric load, predicted electric load, shiftable electric load and interruptible electric load during a period.

[0043] Due to the subjectivity of user thermal comfort, changes within the comfortable temperature range will not significantly affect user satisfaction, thus enhancing the adjustability of flexible loads. After integrating the thermal load demand response, the actual thermal load is as follows:

[0044] In the formula: , , and are respectively t the actual thermal load, predicted thermal load, shiftable thermal load and interruptible thermal load during a period.

[0045] Trading model of the stepped carbon trading mechanism The carbon trading mechanism requires authorized emission right exchanges between designated entities to effectively supervise carbon emissions and reduce the overall carbon emissions of the integrated energy system. In this paper, a stepped carbon trading mechanism is introduced to limit the carbon emissions of the integrated energy system.

[0046] During a settlement period of the stepped carbon trading mechanism, the trading share of the system participating in the carbon trading market is:

[0047] Wherein: is the carbon emission; is the actual carbon emission quota of the integrated energy system; is the carbon emission quota of the integrated energy system.

[0048] If the carbon emission is lower than the quota, the enterprise will receive a subsidy and can sell the remaining quota; if the emission exceeds the quota, they must purchase emission rights, and the higher the emission, the higher the cost. This model processes the actual emissions through piecewise linearization to calculate the carbon cost, specifically as follows:

[0049] Wherein: is the carbon trading cost; is the benchmark price of carbon trading; is the growth rate of the carbon trading price; is the interval length of carbon emissions.

[0050] Environmental Emission Cost Model There is a risk of nitrogen oxide emissions in the co - combustion of ammonia and coal, but it can be effectively controlled through technologies such as air staging and combustion organization. Therefore, this paper assumes that the calculation of nitrogen oxide emissions from ammonia - coal co - combustion coal - fired units is the same as that under pure coal combustion conditions. The actual emissions of nitrogen oxides are calculated based on the consumption of electricity, natural gas, and ammonia, specifically as follows:

[0051] Wherein: is the pollutant emission; , and are the pollutant emissions generated by the consumption of coal, natural gas, and ammonia respectively; , and are the pollutant emission factors of coal, natural gas, and ammonia respectively.

[0052] The calculation formula of the environmental cost is as follows:

[0053] Wherein: is the pollutant emission cost; is the tax amount payable per unit of pollution equivalent; is the conversion coefficient of the pollutant; is the emission standard value of the pollutant.

[0054] Low - carbon Operation Scheduling Model of Integrated Energy System Objective function: Taking the minimum system operation cost as the objective function, and on this basis, converting the wind and light curtailment amounts and carbon trading volumes into penalty costs and including them in the system operation cost. The scheduling plan model is as follows:

[0055] In the formula: is the total cost of the integrated energy system; is the energy procurement cost of the integrated energy system; is the operation and maintenance cost of the scheduling units in the integrated energy system; is the start-stop cost of coal-fired units, CHP, and GB in the integrated energy system; is the penalty cost for wind and light curtailment in the integrated energy system; is the carbon emission and environmental cost in the integrated energy system; is the IDR cost of the integrated energy system.

[0056]

[0057] In the formula: is the coal purchase cost coefficient; is t the gas purchase cost coefficient in period; is the unit operation and maintenance cost coefficient of the is t the output of the unit in period; , and are binary variables, which are the t operating states of coal-fired units, CHP, and GB in period (1 for startup, 0 for shutdown); , and are the start-stop costs of coal-fired units, CHP, and GB respectively; and are the unit cost coefficients of wind and light curtailment respectively; and are t the wind and light curtailment amounts in period; and are the economic compensation coefficients of interruptible electricity and heat loads respectively.

[0058] Constraint conditions: (1) Power balance constraint 1) Electric power balance constraint

[0059] 2) Thermal power balance constraint

[0060] In the formula: and are respectively t the electric and heat load powers during the time period.

[0061] (2) Wind and solar power output constraints

[0062] In the formula: and are the wind and solar power outputs at time t; and[[ID=...]] are the upper limits of wind and solar power outputs.

[0063] (3) Demand response constraints 1) Electric load demand response constraints

[0064] In the formula: is the maximum interruptible electric load power.

[0065] 2) Heat load demand response constraints

[0066] In the formula: is the maximum interruptible heat load power.

[0067] Solve the established low-carbon optimal scheduling model of the ammonia-integrated energy system to obtain the optimal scheduling plan.

[0068] (1) Parameter setting: In this paper, a certain integrated energy demonstration area in the north is selected as the research object for example simulation, and its system structure is as Figure 2 shown. The predicted values of wind power output, photovoltaic power output, electric load, and heat load within the integrated energy system are as Figure 3 shown. The time-of-use electricity price, time-of-use natural gas price, and equipment parameters of each device in the integrated energy system are shown in Tables 1 to 3. The penalty cost for wind and light curtailment is 300 yuan / MW×h.

[0069] Table 1 Time-of-use electricity price table Time period Electricity price (yuan / kW·h) 00:00-05:00，22:00-24:00 0.358 05:00-09:00，13:00-17:00 0.741 09:00-13:00，17:00-22:00 1.031

[0070] Table 2 Time-of-use natural gas price table Time period <![CDATA[Gas price (yuan / m 3 )]]> 09:00-13:00，16:00-22:00 2.37 04:00-09:00，13:00-16:00 2.96 00:00-04:00，22:00-24:00 3.52

[0071] Table 3 Equipment parameter table of the integrated energy system Equipment Capacity / MW Efficiency / % Ramp constraint / % PEM 200 80 30 P2A 150 67 20 CHP 150 38 20 GB 200 92 20 WHB 100 90 20 Electric energy storage 50 90 30 Thermal energy storage 50 95 30 Ammonia energy storage 100 95 30

[0072] (2) Analysis of the scheduling results of the integrated energy system: It should be noted that in the provided text, there is an ellipsis in the translation of line 24 which should be adjusted according to the actual content. Also, the 7-digit tags are preserved as per the requirement. To verify the effectiveness of the low-carbon optimal scheduling of the integrated energy system considering power-to-ammonia conversion and demand response, the following three optimization schemes are set for comparative analysis: Scheme 1: Only consider the stepped carbon trading, without considering the influence of P2A and IDR; Scheme 2: On the basis of Scheme 1, consider the participation of P2A, and take into account the influence of the heat supply power of P2A and ammonia-coal co-firing; Scheme 3: Consider P2A and IDR simultaneously to verify their influence on the low-carbon operation of the integrated energy system.

[0073] The optimal scheduling results of the above three schemes are shown in Table 4. Figure 4 Figure 4 shows the electric energy scheduling results of the three schemes. Figure 5 Figure 5 shows the heat energy scheduling results of the three schemes.

[0074] Table 4 Scheduling results under three schemes Dispatch result Scheme 1 Scheme 2 Scheme 3 Coal purchase cost / 10,000 yuan 129.61 120.97 114.53 Gas purchase cost / 10,000 yuan 217.35 192.03 183.57 Operation and maintenance cost / 10,000 yuan 67.09 48.23 32.68 Startup and shutdown cost / yuan 3.46 2.53 1.27 Wind and solar curtailment cost / 10,000 yuan 6.13 2.09 0.93 Environmental cost / 10,000 yuan 5.76 3.57 2.35 Carbon trading cost / 10,000 yuan 11.14 6.34 4.13 IDR cost / 10,000 yuan 0 0 7.37 Total cost / 10,000 yuan 440.54 375.76 346.83 Carbon emissions / ton 4707.43 3982.08 3527.62 Wind and solar curtailment rate 24.52% 8.34% 3.71%

[0075] As shown in Table 4, Scheme 1 does not include P2A equipment, and the system fails to fully utilize the wind and light resources, resulting in the highest costs for coal purchase, gas purchase, and renewable energy curtailment. Therefore, its carbon emissions and total costs are the highest. After introducing P2A in Scheme 2, P2A converts the surplus wind and light output into ammonia fuel for storage. Compared with Scheme 1, the curtailment rate of wind and light is reduced by 16.18%. In addition, in Scheme 2, the system directly uses ammonia fuel as part of the fuel for the coal-fired unit to increase its power output and utilizes the heat generated during the ammonia synthesis process in P2A, reducing the coal usage of the system and the natural gas required for the gas-fired unit for heating. As a result, the coal and natural gas procurement costs of the system are reduced by 6.67% and 11.65% respectively.

[0076] Generally speaking, compared with Scheme 1, the total cost of Scheme 2 is reduced by 14.7%, and the carbon emissions are reduced by 15.41%, proving that considering P2A and ammonia-coal co-firing technology can effectively improve the low-carbon economic operation ability of the system. Scheme 3 introduces integrated demand response on the demand side on the basis of Scheme 2. By adjusting the energy consumption plans of multiple energy consumers, that is, transferring part of the electricity and heat loads during high energy price periods to low energy periods and reducing the energy consumption of part of the loads, the supply-demand relationship is optimized, so as to realize the mutual substitution of electric energy and heat energy on the user side and smooth the demand for electric and heat loads. Compared with Scheme 2, the total cost, carbon trading cost, and curtailment cost of wind and light of the system are all reduced. Therefore, introducing integrated demand response effectively coordinates the environmental protection and economy of the system.

[0077] As Figure 4 neutralize Figure 5As shown in a) of , in Scenario 1, the electricity demand is low while the heat demand is high during the two time periods of 1:00 - 05:00 and 23:00 - 24:00, resulting in the CHP operating at a high level. During this period, the WHB recovers waste heat from the CHP to generate steam and meet the heat demand. However, the power output of the CHP compresses the system's ability to absorb wind and solar resources, leading to a significant increase in the curtailment of wind and solar power. Also, due to the high output of the GB and CHP, the carbon emissions of Scenario 1 reach the highest level.

[0078] As Figure 4 shown in Figure 5 b) of , in Scenario 2, the system in Scenario 2 uses P2A to convert surplus wind and solar power into ammonia and uses ammonia as part of the fuel supply for the coal-fired unit. This reduces the use of fossil fuels in the system, enables the coal-fired unit to obtain more zero-carbon fuels, improves the low-carbon economy and operational efficiency of the coal-fired unit, and increases the power generation of the coal-fired unit at all times. As the power generation of the coal-fired unit increases, the power generation of the gas turbine during this period will decrease. At the same time, it also reduces the thermal power output of the WHB during low heat demand periods, resulting in an increase in the heat output power of the GB. However, during the peak heat load period from 1:00 - 05:00, the thermal power generated by P2A alleviates the heating pressure of the system. Although the increase in the heat power output of the GB will lead to an increase in carbon emissions, the reduction in carbon emissions from the coal-fired unit and CHP offsets the increase in carbon emissions from the GB. Therefore, the application of P2A technology realizes the utilization of multiple energy pathways, reduces the operating costs of gas and coal-fired units in the system, and enhances the low-carbon operation ability of the system.

[0079] Scenario 3 adjusts the energy consumption pattern on the load side of the system through integrated demand response, enabling the system to optimize the supply-demand relationship, thereby alleviating the mismatch between the power load and the characteristics of wind power generation. The electricity dispatch results of Scenario 3 are as Figure 4 shown in Figure 5 c) of . Some power loads are affected by time-differentiated electricity prices, and the load is shifted from the peak electricity consumption periods of 10:00 - 13:00 and 18:00 - 21:00 to the off-peak electricity consumption periods of 01:00 - 07:00 and 14:00 - 16:00, thus increasing the consumption of renewable energy. The heat dispatch results of Scenario 3 are as shown in c) of . The heat load is affected by the natural gas price, and the heat load is shifted from the peak period to the off-peak period. Moreover, the thermal power generated by P2A and the WHB supply additional heat loads during the off-peak period, thereby reducing the consumption of natural gas and lowering the operating cost and carbon emission level of the system.

[0080] (3) Sensitivity analysis of carbon emission trading: The parameter setting of the stepped carbon emission trading will directly affect the energy dispatch of the integrated energy system. In this section, the operating costs and carbon emissions of different carbon emission costs are compared and analyzed, and the optimization results are as follows Figure 6 as shown

[0081] As the carbon trading price rises from 0 yuan / ton to 200 yuan / ton, the system carbon emissions decrease by 14.6%. This is because the cost of carbon trading gradually increases, restricting the system's carbon emissions, thus prompting the system to reduce emissions to lower the trading cost. When the carbon trading price rises, the carbon trading cost increases, and the total cost of the system also increases accordingly. Taking the carbon trading price of 100 yuan / ton set in this paper as an example, if carbon trading is not carried out, the system carbon emissions are 202.94 tons higher than those in Scheme 3, indicating that the stepped carbon trading can effectively reduce emissions and improve the environmental protection of the system.

[0082] Conclusion To improve the low-carbon economic operation ability of the integrated energy system, this paper proposes a low-carbon dispatching method for the integrated energy system considering power-to-ammonia and demand response. The following conclusions are obtained through the comparative analysis of different schemes.

[0083] 1) The coordination of P2A and ammonia-coal co-firing enhances the consumption capacity and low-carbon characteristics of the integrated energy system. Compared with the scheme without considering P2A, the proposed scheme in this paper reduces the carbon emissions by 15.4% and the wind and light curtailment rates by 16.18%. At the same time, in the process of using P2A heat, the system energy supply form of the heat load is changed, the demand for natural gas by CHP is reduced, and the low-carbon economic operation of the system is promoted.

[0084] 2) Considering IDR can effectively exert the regulation ability of the demand side and achieve "peak shaving and valley filling" of the load. Through the translation and reduction of the electric and heat loads, the dependence of the system on fossil fuels such as coal and gas is reduced, and the carbon emission cost and energy purchase cost are reduced by 34.9% and 4.8% respectively, improving the economy and flexibility of the system.

[0085] 3) Parameters such as the carbon trading base price will significantly affect the energy utilization strategy and total cost of the system. Through the sensitivity analysis of the system, it can be found that the total cost of the system increases with the increase of the carbon trading price, and the carbon emissions generally show a downward trend.

Claims

1. A low-carbon scheduling method for an integrated energy system considering electro-transamination and demand response, characterized in that Specifically, it includes the following steps: 1) Construct a refined power-to-ammonia model and an ammonia-coal co-firing model, and establish models for other energy conversion devices and energy storage devices; 2) Establish an integrated electricity-heat demand response model based on the transferable and interruptible characteristics of electricity load and heat load, and introduce a stepped carbon trading mechanism; 3) Establish a low-carbon optimal scheduling model for the integrated energy system considering power-to-ammonia and demand response; 4) Obtain the equipment and operation parameters of the integrated energy system, as well as the predicted values of wind, light, and load; 5) Solve the established low-carbon optimal scheduling model for the ammonia-containing integrated energy system to obtain the optimal scheduling plan.

2. The low-carbon scheduling method for an integrated energy system considering electro-ammonia conversion and demand response according to claim 1, characterized in that In step 1), the construction of the refined power-to-ammonia model includes three core links: hydrogen production by electrolyzer (EL), nitrogen production by air separation unit (ASU), and power-to-ammonia (P2A) to improve the utilization efficiency of renewable energy; establish an ammonia-coal co-firing model for coal-fired units; according to the characteristics of combined heat and power (CHP) units, gas boilers (GB), waste heat boilers (WHB), electric energy storage, thermal energy storage, and ammonia energy storage, construct relevant mathematical models.

3. The low-carbon scheduling method for an integrated energy system considering electro-ammonia conversion and demand response according to claim 1, wherein In step 2), the integrated demand response model classifies the load into fixed load, transferable load, and interruptible load according to the characteristics of the load on the demand side, and implements demand response based on the incentive price; the stepped carbon trading mechanism effectively supervises carbon emissions and reduces the overall carbon emissions of the integrated energy system by setting parameters such as carbon emission quotas, carbon trading base prices, carbon trading price growth rates, and carbon emission interval lengths.

4. The low-carbon scheduling method for an integrated energy system considering electro-transamination and demand response according to claim 1, wherein In step 3), the establishment of the low-carbon optimal scheduling model for the integrated energy system takes the minimum system operation cost as the objective function, and on this basis, converts the wind and light curtailment amounts and carbon trading volumes into penalty costs and includes them in the system operation cost, and constructs constraint conditions such as electricity-heat power constraints, equipment model constraints, wind and light output constraints, environmental emission constraints, and demand response constraints to improve the economy and environmental protection of the system.

5. The low-carbon scheduling method for an integrated energy system considering electro-transamination and demand response according to claim 1, characterized in that, In step 4), the acquisition of the equipment and operation parameters of the integrated energy system, as well as the predicted values of wind, light, and load, where the equipment and operation parameters of the integrated energy system include the parameters of EL, P2A, CHP, GB, WHB, electric energy storage, thermal energy storage, and ammonia energy storage; the predicted values of wind, light, and load include the predicted values of wind power output, photovoltaic power output, electricity load, and heat load.

6. The low-carbon scheduling method for an integrated energy system considering electro-ammonia conversion and demand response according to claim 1, wherein In step 5), the established low-carbon optimal scheduling model for the ammonia-containing integrated energy system is solved to obtain the optimal scheduling plan. The present invention sets three scenarios: only considering the stepped carbon trading, without considering the influence of P2A and IDR; considering the participation of P2A, taking into account the influence of P2A heating power and ammonia-coal co-firing; considering both P2A and IDR at the same time to verify their influence on the low-carbon operation of the integrated energy system. The economy and environmental protection of the method proposed by the present invention are verified through the three scenarios set.

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