Optimal Scheduling Method for Hydrogen-Integrated Energy System Considering Ladder Green Certificate Trading Mechanism and Dual Response of Source and Load

Abstract

The present invention discloses an optimized scheduling method for a hydrogen-integrated energy system considering a stepped green certificate trading mechanism and dual responses of power generation and load, including establishing a carbon capture coupled power-to-gas model; wherein, the carbon capture coupled power-to-gas model includes a CCS model and a P2G model; establishing a stepped green certificate trading model; wherein, the stepped green certificate trading model includes a stepped carbon trading mechanism and a stepped green certificate trading mechanism; establishing a dual response model of power generation and load; wherein, the dual response model of power generation and load includes a flexible response model on the power generation side and a flexible response model on the load side; establishing and solving an HIES optimized scheduling model considering CCS-P2G and dual responses of power generation and load under stepped green certificates. The method proposed by the present invention improves the operation flexibility of the hydrogen-integrated energy system while improving the economy and carbon emission level of the hydrogen-integrated energy system.

Description

Technical Field

[0001] The present invention relates to an optimal scheduling method for a hydrogen-integrated energy system considering a stepped green certificate trading mechanism and dual response of power generation and load, belonging to the field of optimal scheduling of integrated energy systems. Background Technique

[0002] Key technologies such as renewable energy power generation, combined heat and power, power-to-gas, and energy storage. Constructing a hydrogen-integrated energy system that realizes multi-energy complementarity through energy conversion devices will become the key to carbon reduction and efficiency improvement in the energy field, and strongly promote the sustainable development of the green and low-carbon economy. At the same time, to further reduce carbon emissions and establish a carbon emission trading system, the hydrogen-integrated energy system (HIES) can carry out carbon emission rights trading through the carbon trading mechanism (CTM). Corresponding to the CTM is the green certificate trading market (GCT). HIES obtains green certificates by producing and using green electricity. After meeting the specified indicators, it can sell the surplus green certificates to obtain additional economic returns. However, most of the existing studies only consider the GCT with a traditional fixed green certificate price, and there is still room for research on the further trading income of green certificates.

[0003] In view of this, the present invention is specifically proposed. Summary of the Invention

[0004] The present invention provides an optimal scheduling method for a hydrogen-integrated energy system considering a stepped green certificate trading mechanism and dual response of power generation and load, which is used to establish an HIES optimal scheduling model considering CCS-P2G and dual response of power generation and load under stepped green certificates, and solve it to obtain an optimal operation plan for the hydrogen-integrated energy system considering the stepped green certificate trading mechanism and dual response of power generation and load.

[0005] The technical solution of the present invention is as follows:

[0006] According to the first aspect of the present invention, there is provided an optimal scheduling method for a hydrogen-integrated energy system considering a stepped green certificate trading mechanism and dual response of power generation and load, including: establishing a carbon capture coupled power-to-gas model; wherein, the carbon capture coupled power-to-gas model includes a CCS model and a P2G model; establishing a stepped green certificate trading model; wherein, the stepped green certificate trading model includes a stepped carbon trading mechanism and a stepped green certificate trading mechanism; establishing a dual response model of power generation and load; wherein, the dual response model of power generation and load includes a flexible response model on the power generation side and a flexible response model on the load side; establishing and solving an HIES optimal scheduling model considering CCS-P2G and dual response of power generation and load under stepped green certificates.

[0007] The HIES optimization scheduling model considering CCS-P2G and dual response of power generation and load under the stepped green certificate includes the objective function and constraint conditions of the optimization scheduling method for the hydrogen-integrated energy system considering the stepped green certificate trading mechanism and dual response of power generation and load.

[0008] The stepped green certificate trading mechanism is modeled as follows:

[0009]

[0010] where: f GCT is the revenue from stepped green certificate trading; c GCT is the basic trading unit price of green certificates; l is the length of the stepped green certificate trading interval; λ GCT and α GCT are the penalty factor and compensation factor when exceeding or falling short of the quota index; N GCT is the number of green certificates participating in the green certificate market trading.

[0011] The number of green certificates N participating in the green certificate market trading GCT , the expression is: N GCT = N ob - N ne ; where, N ob is the number of green certificates obtained by the enterprise; N ne is the number of green certificates required to meet the index.

[0012] The flexible response model on the power generation side includes: the combined operation model of HFC, WHB, and ORC; the combined operation model of GT, WHB, and ORC; and the combined heat and power generation model of HFC and GT, WHB, and ORC.

[0013] The flexible response model on the load side includes: establishing a horizontal DR model and a vertical DR model for the multi-load including electricity, heat, and gas loads.

[0014] The vertical DR model:

[0015]

[0016] where: is the post-vertical DR load of the i-th load at time t; is the replaceable load of the i-th load at time t; is the amount of the i-th load participating in the vertical DR at time t; is a 0-1 variable; are the power replaced out and replaced in of the i-th load at time t, respectively; respectively represent the maximum load ratio of the i-th load participating in the vertical DR at time t; is the initial value of the i-th load; T represents the scheduling period.

[0017] The objective function aims to minimize the sum of the energy purchase cost, carbon trading cost, green certificate trading cost, demand response cost, and wind curtailment cost of the hydrogen-integrated energy system.

[0018] The constraint conditions include energy storage system constraints, GB operation constraints, electric power balance constraints, thermal power balance constraints, natural gas balance constraints, and hydrogen balance constraints.

[0019] According to the second aspect of the present invention, there is provided an optimized scheduling system for a hydrogen-integrated energy system considering a stepped green certificate trading mechanism and dual-source and load responses, including: a first establishment module for establishing a carbon capture-coupled power-to-gas model; wherein, the carbon capture-coupled power-to-gas model includes a CCS model and a P2G model; a second establishment module for establishing a stepped green certificate trading model; wherein, the stepped green certificate trading model includes a stepped carbon trading mechanism and a stepped green certificate trading mechanism; a third establishment module for establishing a dual-source and load response model; wherein, the dual-source and load response model includes a source-side flexible response model and a load-side flexible response model; an establishment and solution module for establishing and solving an HIES optimized scheduling model considering CCS-P2G and dual-source and load responses under stepped green certificates.

[0020] The beneficial effects of the present invention are as follows:

[0021] 1) The traditional green certificate trading mechanism has limited promotion of the utilization of green electricity. The stepped green certificate trading strategy proposed in the present invention can take into account both energy conservation and emission reduction effects while achieving good economic performance, and promote the development of green certificate trading. In the future scenario analysis of stepped green certificates, the optimal green certificate step length is obtained, further improving the economic performance of HIES and the green certificate trading revenue.

[0022] 2) Through the coupled operation of CCS and P2G, the internal carbon cycle of the HIES system is realized. Through the synergistic effect of the green certificate trading market, carbon trading market, and CCS-P2G, the low-carbon and economic performance of HIES operation is further improved.

[0023] 3) After implementing the flexibility response strategies on both the source and load sides, HIES can flexibly adjust the thermal and electric power outputs according to real-time demands on the supply side. Especially under the coordinated operation of HFC, the low-carbon economic benefits of HIES are further enhanced. On the load side, through the flexible management of multiple loads, the carbon emissions are reduced while the total system operation cost is lowered, promoting the low-carbon economic optimized operation of HIES. Description of the Drawings

[0024] Figure 1 is the flowchart of the present invention;

[0025] Figure 2 is the framework diagram of the hydrogen-integrated energy system;

[0026] Figure 3 is the initial load and the predicted output of wind power;

[0027] Figure 4 is the electric power balance according to Scenario 4 of the embodiment of the present invention;

[0028] Figure 5 is the thermal power balance according to Scenario 4 of the embodiment of the present invention;

[0029] Figure 6 is the flexible demand response of electric load according to Scenario 4 of the embodiment of the present invention;

[0030] Figure 7 is the flexible demand response of thermal load according to Scenario 4 of the embodiment of the present invention;

[0031] Figure 8 is the flexible demand response of gas load according to Scenario 4 of the embodiment of the present invention;

[0032] Figure 9 is the relationship between the length of the segmented interval of green certificates, the total cost and the revenue from green certificate trading according to Scenario 4 of the embodiment of the present invention. Detailed implementation manners

[0033] To make the objectives, 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. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without making creative efforts fall within the protection scope of the present invention. It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other arbitrarily.

[0034] Embodiment 1: As Figures 1-9 shown, according to the first aspect of the embodiment of the present invention, an optimized scheduling method for a hydrogen-integrated energy system considering a stepped green certificate trading mechanism and dual response of source and load is provided, including: Step 1, establish a carbon capture coupled power-to-gas model; among them, the carbon capture coupled power-to-gas model includes a CCS model and a P2G model; Step 2, construct a stepped green certificate trading model; among them, the stepped green certificate trading model includes a stepped carbon trading mechanism and a stepped green certificate trading mechanism; Step 3, establish a dual response model of source and load; among them, the dual response model of source and load includes a flexible response model on the source side and a flexible response model on the load side; Step 4, establish and solve an HIES optimized scheduling model considering carbon capture (Carbon Capture System, CCS) coupled power-to-gas (Power to Gas, P2G) and dual response of source and load under stepped green certificates, and the model is as Figure 2 shown.

[0035] Furthermore, the establishment of the carbon capture coupled with power-to-gas model includes:

[0036] S1.1: Establish a CCS model. CCS involves two steps of carbon capture and storage. The captured CO2 is diverted and utilized: a part is introduced into the P2G system through a pipeline for recycling, and the remaining part is permanently stored by means of CO2 compression technology. The specific model is as follows:

[0037]

[0038] In the formula: P CCS (t) is the total power consumption of CCS at time t; and are the operating energy consumption and fixed energy consumption of CCS at time t respectively; λ GE is the electric power consumed per unit of CO2 captured; is the amount of CO2 captured at time t; λ C is the CO2 capture efficiency of CCS; a G is the unit carbon emission factor of the traditional energy unit; P G (t) is the generated electric power of the traditional energy unit at time t; are the upper and lower limits of the total power consumption of CCS respectively.

[0039] S1.2: Establish a P2G model. P2G can absorb excess wind energy and convert it into natural gas for storage, and supply natural gas-consuming equipment in the system. Its working principle can be divided into two stages: electrolytic water hydrogen production and subsequent methane synthesis. In the methane synthesis stage, the consumed CO2 volume and the produced natural gas volume have a one-to-one correspondence relationship. The detailed expression is as follows:

[0040]

[0041] In the formula: is the gas production power of P2G at time t; λ P2G is the natural gas production efficiency of P2G; is the electric power consumed by P2G at time t; V C (t), V g (t) are the CO2 absorbed and the natural gas produced by P2G at time t respectively; H CH4 is the lower heating value of natural gas; is the amount of CO2 consumed by P2G at time t; ρ C is the CO2 density; are the upper and lower limits of the electric power consumption of P2G respectively.

[0042] Furthermore, the said Step2 includes:

[0043] S2.1: Establish a stepped carbon trading mechanism. The carbon trading mechanism refers to a mechanism in which carbon emission sources obtain legitimate carbon emission rights through relevant departments and can trade them as commodities in the carbon market. The regulatory agency first allocates a certain amount of carbon emission quotas to carbon emission entities. Enterprises optimize production and emissions based on these quotas. If there are surplus quotas, enterprises can choose to sell them on the market; if carbon emissions exceed the quotas, they need to purchase additional emission permits.

[0044]

[0045] In the formula: E IES is the carbon emission right participating in the transaction; E e is the actual carbon emission; E a is the free carbon quota of the system; is the amount of CO2 consumed by P2G at time t; is the amount of CO2 captured at time t; f CTM is the stepped carbon trading cost; λ is the benchmark trading price of the carbon market; L is the length of the trading interval; α is the price increase rate after the quota exceeds the target; T represents the scheduling period.

[0046] S2.2: Establish a stepped green certificate trading mechanism. The green certificates issued by the regulatory department to the enterprise itself and those bought and sold in the green certificate market are added to the green certificate trading, and a compensation factor and a penalty factor are introduced, thus dividing the green certificate trading mechanism into several sub-intervals. This mechanism follows an incentive principle similar to that of stepped carbon trading: the more green certificates an enterprise sells, the higher the unit price when selling; conversely, the greater the demand for purchasing green certificates, the higher the unit price will be. The model is constructed as follows:

[0047]

[0048] N GCT = N ob - N ne

[0049] In the formula: f GCT is the stepped green certificate trading income; c GCT is the basic trading unit price of the green certificate; l is the length of the stepped green certificate trading interval; λ GCT and α GCT are the penalty factor and compensation factor when exceeding or falling short of the quota target; N GCT is the number of green certificates participating in the green certificate market trading; N ob is the number of green certificates obtained by the enterprise; N ne is the number of green certificates required to meet the target.

[0050] Furthermore, the said Step3 includes:

[0051] S3.1: Establish a flexible response model on the source side (i.e., the supply-side flexible response model). When a gas turbine (GT) and a hydrogen fuel cell (HFC) generate electricity by burning fuel, a large amount of waste heat is produced. A waste heat boiler (WHB) can collect the waste heat to generate heat. Therefore, the combination of GT, HFC, and WHB can achieve combined heat and power generation and improve energy utilization efficiency. However, the current "electricity-determined heat" operation mode restricts the adjustment ability of GT and HFC in thermoelectric output. By introducing an organic Rankine cycle (ORC) to recover and utilize the waste heat energy for power generation, the flexibility of thermoelectric output on the energy supply side can be enhanced. Combining ORC with GT, HFC, and WHB to establish a combined heat and power generation model can maximize the waste heat utilization rate and achieve the optimal proportion configuration of heat and power supply, thereby promoting the efficient dynamic adjustment of thermoelectric output at the supply end.

[0052] The operation model of HFC combined with WHB and ORC is as follows:

[0053]

[0054] In the formula: are the power generation power of HFC and the heat power of HFC delivered to ORC and WHB at time t, respectively; is the hydrogen consumption power of HFC at time t; are the power generation and heat generation efficiencies of HFC, respectively; are the upper and lower limits of the power input to HFC, respectively; are the upper and lower limits of the ramp power of HFC, respectively.

[0055] The operation model of GT combined with WHB and ORC is as follows:

[0056]

[0057] In the formula: are the power generation power of GT and the heat power of GT delivered to ORC and WHB at time t, respectively; is the natural gas power input to GT at time t; are the power generation and heat generation efficiencies of GT, respectively; are the upper and lower limits of the power input to GT, respectively; are the upper and lower limits of the GT ramp constraint, respectively.

[0058] The combined heat and power generation model of HFC and GT combined with WHB and ORC is as follows:

[0059]

[0060] In the formula: are the input heat powers of WHB and ORC at time t, respectively; are the power generation electric power of HFC and the heat powers of HFC delivered to ORC and WHB at time t, respectively; are the power generation electric power of GT and the heat powers of GT delivered to ORC and WHB at time t, respectively; are the output heat power of WHB and the output electric power of ORC at time t; ρ WHB and ρ ORC are the operation conversion efficiencies of WHB and ORC, respectively; are the upper and lower limits of the thermal energy input from GT and HFC to WHB, respectively; are the upper and lower limits of the thermal energy input from GT and HFC to ORC, respectively; are the upper and lower limits of the ramping power of WHB, respectively; are the upper and lower limits of the ramping power of ORC, respectively; are the electric and heat powers output by combined heat and power (CHP), respectively.

[0061] S3.2: Establish a flexible response model on the load side. The multi-load including electric, heat, and gas loads can move horizontally between peak and valley hours, which is called the horizontal DR ability; in addition, the multi-load can also be replaced with each other at any time, having the vertical DR ability. Based on this, the load is classified into fixed load, transferable load, and replaceable load, and the horizontal and vertical DR models of the multi-load are as follows.

[0062] Horizontal DR model:

[0063]

[0064] In the formula: are the load amounts after the horizontal DR of the i-th load and the load amounts participating in the horizontal DR at time t, respectively; is the initial load amount of the i-th load that can be horizontally DR at time t; is a 0-1 variable (when is 1, it means transfer in, and when is 1, it means transfer out); are the horizontal DR out and in load amounts of the i-th load at time t, respectively; respectively represent the maximum load ratio of the i-th load participating in the horizontal DR at time t; is the initial value of the i-th load; T represents the scheduling period.

[0065] Vertical DR model:

[0066]

[0067] Wherein: is the longitudinal DR backload of the i-th load at time t; is the alternative load of the i-th load at time t; is the amount of the i-th load participating in longitudinal DR at time t; is a 0-1 variable (when is 1, it means transfer in, and when is 1, it means transfer out); are the replacement-out and replacement-in powers of the i-th load at time t, respectively; respectively represent the maximum load proportion of the i-th load participating in longitudinal DR at time t; is the initial value of the i-th load; T represents the scheduling period.

[0068] Thus, the flexible response model on the load side is determined, that is, the expression of the multi-load horizontal and longitudinal DR model:

[0069]

[0070] Wherein: P i,load (t) represents the value of the i-th load after DR at time t (for the multi-load including electric, thermal, and gas loads, specifically P e,load (t), P h,load (t), P g,load (t)); is the fixed load amount of the i-th load; is the horizontal DR backload of the i-th load at time t; is the longitudinal DR backload of the i-th load at time t.

[0071] Furthermore, the HIES optimal scheduling model considering CCS-P2G and dual response of source and load under stepped green certificates includes the objective function and constraint conditions of the optimal scheduling method of the hydrogen-integrated energy system considering the stepped green certificate trading mechanism and dual response of source and load.

[0072] Specifically, it includes:

[0073] S4.1: Establish the objective function of the optimal scheduling method of the hydrogen-integrated energy system considering the stepped green certificate trading mechanism and dual response of source and load. Taking the minimum sum of the energy purchase cost, carbon trading cost, green certificate trading cost, demand response cost, and wind curtailment cost of HIES as the optimization objective:

[0074] F = min(f buy + f CTM + f GCT + f W,cut + f DR )

[0075] In the formula: F is the system objective function; f buy is the power purchase cost of HIES; f CTM is the carbon trading cost; f GCT is the green certificate trading cost; f DR is the demand response compensation cost; f W,cut is the curtailment cost of wind power.

[0076] (1) Power purchase cost

[0077]

[0078] In the formula: f buy is the power purchase cost of HIES; c e is the power purchase price per unit from the power grid; c g is the gas purchase price per unit from the gas grid; c H2 is the unit hydrogen purchase price; is the power purchase power of the system at time t; is the gas purchase power of the system at time t; is the hydrogen purchase power of the system at time t; T represents the dispatching period.

[0079] (2) Carbon trading cost

[0080]

[0081] In the formula: E IES is the carbon emission rights participating in the transaction; f CTM is the ladder carbon trading cost; λ is the benchmark trading price of the carbon market; L is the length of the trading interval; α is the price increase rate after the quota exceeds the target.

[0082] (3) Green certificate trading cost

[0083]

[0084] In the formula: f GCT is the ladder green certificate trading income; c GCT is the basic trading unit price of the green certificate; l is the length of the ladder green certificate trading interval; λ GCT and α GCT are the penalty factor and compensation factor when the quota exceeds or is less than the target; N GCT is the number of green certificates participating in the green certificate market transaction.

[0085] (4) Demand response compensation cost

[0086]

[0087] In the formula: f DR is the demand response compensation cost; c s is the load transfer compensation cost factor; cr is the load substitution compensation cost factor; ) is the amount of electrical load participating in horizontal DR at time t; is the amount of thermal load participating in horizontal DR at time t; is the amount of gas load participating in horizontal DR at time t; is the amount of electrical load participating in vertical DR at time t; is the amount of thermal load participating in vertical DR at time t; is the amount of gas load participating in vertical DR at time t; T represents the scheduling period.

[0088] (5) Curtailment cost

[0089]

[0090] In the formula: f W,cut is the curtailment cost; c cut is the curtailment penalty factor; P W,cut (t) is the curtailment power at time t; T represents the scheduling period.

[0091] S4.2: Set the constraint conditions of the hydrogen-integrated energy system optimal scheduling method considering the stepped green certificate trading mechanism and source-load dual response. The constraint conditions include energy storage system constraints, GB operation constraints, electric power balance constraints, thermal power balance constraints, natural gas balance constraints, and hydrogen balance constraints.

[0092] (1) Energy storage system constraints

[0093]

[0094] In the formula: S s (t) is the energy storage state of the s-th type of energy storage at time t; are the charging and discharging efficiencies of the s-th type of energy storage respectively; are the charging and discharging powers of the s-th type of energy storage device at time t respectively; is a binary variable; are the upper limits of the charging and discharging powers of the s-th type of energy storage device respectively; S s (1), S s (T) are the initial and final energy storage states of the energy storage device; are the upper and lower limits of the energy storage state of the s-th type of energy storage respectively; s ∈ {E, H, G, H2}, where E, H, G, and H2 represent electricity, heat, gas, and hydrogen respectively; T represents the scheduling period.

[0095] (2) GB operation constraints

[0096]

[0097] In the formula: is the heat generation power of GB at time t; ρ GB is the heat generation efficiency of GB; is the natural gas consumption power of GB at time t; are the upper and lower limits of the natural gas power input to GB, respectively; are the upper and lower limits of the ramping power of GB, respectively.

[0098] (3) Electric power balance constraint

[0099]

[0100] In the formula: is the purchased electric power of the system at time t; is the electric power output by CHP; P W (t) is the wind power output at time t; P e,load (t) is the electric load after DR of the system; is the electric power consumed by P2G at time t; P CCS (t) is the total power consumption of CCS at time t; is the predicted wind power output; is the upper limit of the purchased electric power of the system; is the power storage of the energy storage device at time t; is the discharge power of the energy storage device at time t.

[0101] (4) Heat power balance constraint

[0102]

[0103] In the formula: is the heat generation power of GB at time t; is the heat power output by CHP; P h,load (t) is the heat load after DR of the system at time t; is the heat storage of the heat storage device at time t; is the heat release power of the heat storage device at time t.

[0104] (5) Natural gas balance constraint

[0105]

[0106] In the formula: is the purchased gas power of the system at time t; is the gas production power of P2G at time t; P g,load (t) is the gas load after DR at time t; is the gas consumption power of GT at time t; is the gas consumption power of GB at time t; is the gas storage of the gas storage device at time t; is the gas release power of the gas storage equipment at time t; is the upper limit of the natural gas power purchased by the system from the gas grid.

[0107] (6) Hydrogen balance constraint

[0108]

[0109] In the formula: is the hydrogen power purchased by the system from the hydrogen grid at time t; is the hydrogen consumption power of HFC at time t; is the hydrogen storage power of the hydrogen storage equipment at time t; is the hydrogen release power of the hydrogen storage equipment at time t; is the upper limit value of the hydrogen power purchased from the hydrogen grid.

[0110] According to the second aspect of the present invention, there is provided an optimized scheduling system for a hydrogen - containing integrated energy system considering a stepped green certificate trading mechanism and dual - response of power generation and load, including: a first establishment module for establishing a carbon capture coupled power - to - gas model; wherein, the carbon capture coupled power - to - gas model includes a CCS model and a P2G model; a second establishment module for establishing a stepped green certificate trading model; wherein, the stepped green certificate trading model includes a stepped carbon trading mechanism and a stepped green certificate trading mechanism; a third establishment module for establishing a dual - response model of power generation and load; wherein, the dual - response model of power generation and load includes a flexible response model on the power generation side and a flexible response model on the load side; an establishment and solution module for establishing and solving an HIES optimized scheduling model considering CCS - P2G and dual - response of power generation and load under stepped green certificates.

[0111] Furthermore, taking a certain region as an example, the present invention sets the scheduling period to 24h, and uses MATLAB + YALMIP to call the CPLEX commercial solver for solution to verify the effectiveness of the HIES low - carbon economy optimized scheduling model considering the stepped green certificate trading mechanism and dual - response of power generation and load. The initial load and predicted wind power output are as Figure 3 shown; the time - of - use electricity price is shown in Table 1; wherein the base carbon trading price λ is 0.35 yuan / t; the length L of the carbon emission interval is 2t; the carbon price increase rate α is 0.25; the basic trading price c GCT in the green certificate trading market is 50 yuan / book; the compensation factor α GCT and the penalty factor λ GCT are both 0.1; the capacities and related parameters of each device in the HIES system are shown in Table 2.

[0112] Table 1 Time - of - use electricity price information

[0113] Time period Time-of-use electricity price / (yuan / kW·h) 01:00—07:00、23:00—24:00 0.38 08:00—11:00、15:00—18:00 0.68 12:00—14:00、19:00—22:00 1.20

[0114] Table 2 Device capacities and related parameters

[0115]

[0116] Four scenarios are set in the present invention for comparative analysis to verify the effectiveness of the model proposed in the present invention:

[0117] Scenario 1: Under the traditional green certificate trading and carbon trading mechanisms, the optimization scheduling of the objective function does not consider the flexible response on the load side;

[0118] Scenario 2: Under the traditional green certificate trading and carbon trading mechanisms, the optimization scheduling of the objective function considers the flexible response on the load side on the basis of Scenario 1;

[0119] Scenario 3: Under the stepped green certificate trading and carbon trading mechanisms, without considering the flexible response model on the source side of the present invention, and at the same time, the optimization objective does not consider the cost of demand response on the load side for optimization scheduling;

[0120] Scenario 4: Under the stepped green certificate trading and carbon trading mechanisms, the optimization objective considers the optimization scheduling of the energy purchase cost, carbon trading cost, green certificate trading cost, demand response compensation cost, and wind curtailment cost.

[0121] (1) Comparative analysis of simulation results of different scenarios

[0122] The optimization scheduling results of each scenario are shown in Table 3. It can be seen from Table 3 that the cost of Scenario 1 is the highest and the cost of Scenario 4 is the lowest among the four scenarios. Comparing Scenario 1 and Scenario 2, the carbon trading cost, carbon emissions, and total cost of the former are all higher than those of the latter. The reason is that Scenario 1 does not consider the flexible demand response on the demand side and cannot reduce the comprehensive operation cost of the system through flexible load transfer and substitution, while Scenario 2 considers the flexible response of multiple loads brought by the multi-energy coupling of HIES and reduces the operation cost of the system.

[0123] Comparing Scenario 2 and Scenario 4, the cost of the former is 308.8 yuan higher than that of the latter, and the year-on-year growth rate of the total cost is 2.38%. This is because Scenario 4 considers the stepped green certificate trading mechanism compared with Scenario 2, which improves the income of green certificate trading. At the same time, the more green certificates are traded, the greater the income obtained, which promotes the development of green certificate trading; the carbon emissions of Scenario 2 are also 328.9 kg higher than those of Scenario 4. The reason is that Scenario 4 considers the synergistic effect of stepped carbon trading and CCS-P2G technology, which plays a better role in restricting the carbon emissions of the system.

[0124] Combined with Scenario 3 and Scenario 4, the former is higher than the latter in terms of carbon trading cost, carbon emissions, and total cost. The reason is that the optimization goal of Scenario 4 considers the flexible demand response on both the supply and demand sides: for the supply side, HFC and GT generate electricity for the power system load by burning natural gas and hydrogen respectively, and supply the waste heat generated to WHB and ORC to achieve flexible supply of power and heat on the source side. The HFC fuel is mainly provided by purchasing hydrogen. Although the cost of hydrogen has increased, burning hydrogen for power generation by HFC does not produce carbon emissions, reducing the carbon emissions, power purchase cost, and natural gas cost of the system; for the load side, after the diversified loads inside HIES flexibly respond through horizontal and vertical shifting, part of the electrical load during the daytime peak electricity consumption is transferred to the night, and at the same time, part of the electrical load at night vertically replaces the heat and gas loads, improving the ability of HIES to absorb wind power at night. In summary, the model proposed in the present invention can further reduce the carbon emissions and operating costs of the HIES system, while improving the utilization rate of new energy and realizing the low-carbon economic optimal operation of HIES.

[0125] Analysis of the optimization scheduling results of each scenario in Table 3

[0126]

[0127] (2) Analysis of the operating characteristics of Scenario 4

[0128] In Scenario 4, the balance between power supply and demand is as Figure 4 shown. It can be seen from the figure that the grid electricity price is relatively high from 12:00 to 14:00 and from 19:00 to 22:00. On the premise of ensuring the normal operation of the system, HIES implements the strategy of substituting and transferring electrical loads to reduce the energy cascade consumption of CCS-P2G. During the period from 00:00 to 07:00, the grid electricity price drops to the trough, and at the same time, the wind power generation is abundant. After implementing flexible response, the electrical load demand in this period increases. In addition, the electricity consumption of carbon capture and power-to-gas technology also increases accordingly, increasing the natural gas production. Make full use of the abundant wind energy in this stage to reduce the operating cost and improve the utilization rate of new energy. Through price-guided and substitution-based demand response means, the system not only improves the operating cost but also makes the load curve smoother, alleviating the pressure on the power grid caused by the large difference between peak and valley loads.

[0129] The heat supply-demand balance relationship under Scenario 4 is as Figure 5 shown. As can be seen from Figure 5It can be seen that the heat load is mainly supplied by GB and GT. During the periods of 12:00 - 13:00 and 19:00 - 22:00, the system's electrical load is relatively small. In the "electricity-determined heat" mode, the heat output of GT is also relatively small. At this time, the system balances the heat load demand through the strategies of heat release from energy storage and heat production by HFC operation. From 15:00 to 18:00, the electrical load is at a relatively large stage. GT generates a relatively large thermal power, but the heat load is relatively small. The energy storage device starts to store heat for standby.

[0130] (3) Analysis of the optimization results of flexible demand response for multiple loads

[0131] Taking Scenario 4 as an example, the flexible demand response on the load side is as Figures 6-8 shown. It can be seen from the figure that after the lateral demand response ability of the electrical load, by adjusting the electricity consumption distribution from the daytime peak load to the night, not only the cascaded energy efficiency loss from P2G electricity to natural gas is reduced, but also the system's ability to absorb wind energy is enhanced. At the same time, considering that the demand for natural gas heating is relatively large at night, which is traditionally accompanied by relatively high carbon emissions, but through the implementation of the lateral demand response of the heat load and the combination of carbon emission cost control, part of the night heating demand is transferred to the day. In addition, part of the original heat energy and gas energy demand using natural gas during the day is replaced by electricity, further optimizing the energy structure and improving the utilization rate of wind power resources.

[0132] (4) Analysis of the future scenarios of ladder green certificates

[0133] The present invention conducts a simulation analysis on the scenarios when the length of the segmented interval of green certificate trading changes, and verifies the adaptability of the ladder-type green certificate trading mechanism when the trading information in the green certificate market changes. The change relationship between the length of the green certificate segmented interval and the total cost and the green certificate trading revenue is as Figure 9 shown. It can be seen from the figure that when the green certificate segmented interval is less than or equal to 4, the effect of reducing the total cost is significant, and the green certificate revenue is also relatively high; when the green certificate ladder interval is greater than 6, the total cost gradually starts to increase, and the green certificate revenue gradually decreases. Therefore, selecting a suitable ladder interval for the system helps to improve the system economy and green certificate revenue.

[0134] Applying the above technical solutions, it can be known that the present invention designs a ladder-type green certificate trading mechanism by referring to the action mechanism of the ladder-type carbon trading mechanism, introducing a compensation factor and a penalty factor; on the basis of the traditional demand response (Demand Response, DR), a source-load dual response model is established to achieve flexible response on both the supply and demand sides. Then, an HIES optimization scheduling model considering CCS-P2G and source-load dual response under ladder green certificates is established with the minimum total cost as the optimization goal. Finally, through simulation, it is verified that the method proposed by the present invention improves the operation flexibility of the hydrogen-containing integrated energy system while improving the economy and carbon emission level of the hydrogen-containing integrated energy system.

[0135] The specific embodiments of the present invention have been described in detail with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present invention within the scope of knowledge possessed by those of ordinary skill in the art.

Claims

1. An optimal scheduling method for a hydrogen - integrated energy system considering a stepped green certificate trading mechanism and dual response of power generation and load, characterized in that, Including: Establish a carbon capture coupled power-to-gas model; among them, the carbon capture coupled power-to-gas model includes a CCS model and a P2G model; Establish a stepped green certificate trading model; among them, the stepped green certificate trading model includes a stepped carbon trading mechanism and a stepped green certificate trading mechanism; Establish a source-load dual response model; among them, the source-load dual response model includes a source-side flexible response model and a load-side flexible response model; Establish and solve an HIES optimal scheduling model considering the carbon capture coupled power-to-gas model and source-load dual response under stepped green certificates; For the stepped green certificate trading mechanism, its model construction is as follows: Where: f GCT is the revenue from the trading of stepped green certificates; c GCT is the basic trading unit price of green certificates; l is the length of the trading interval of stepped green certificates; λ GCT and α GCT are the penalty factor and compensation factor when exceeding or falling short of the quota; N GCT is the number of green certificates participating in the green certificate market trading; The source-side flexible response model includes: an HFC combined with WHB and ORC operation model, a GT combined with WHB and ORC operation model, and a combined heat and power generation model of HFC and GT combined with WHB and ORC; The HIES optimal scheduling model considering the carbon capture coupled power-to-gas model and source-load dual response under stepped green certificates includes the objective function and constraint conditions of an optimal scheduling method for a hydrogen-integrated energy system considering the stepped green certificate trading mechanism and source-load dual response; The objective function takes the minimum sum of the energy purchase cost, carbon trading cost, green certificate trading cost, demand response cost, and wind curtailment cost of the hydrogen-integrated energy system as the optimization goal, and the expression is as follows: F = min(f buy + f CTM + f GCT + f W,cut + f DR ) where: F is the objective function; f buy is the energy purchase cost of HIES; f CTM is the carbon trading cost; f GCT is the green certificate trading cost; f DR is the demand response compensation cost; f W,cut is the curtailment cost; Where: c e is the electricity purchase price from the power grid unit; c g is the gas purchase price from the gas grid unit; c H2 is the unit hydrogen purchase price; is the electricity purchase power of the system at time t; is the gas purchase power of the system at time t; is the hydrogen purchase power of the system at time t; T represents the scheduling period; Where: c s is the load transfer compensation cost factor; c r is the load substitution compensation cost factor; is the amount of electrical load participating in lateral DR at time t; is the amount of thermal load participating in lateral DR at time t; is the amount of gas load participating in lateral DR at time t; is the amount of electrical load participating in longitudinal DR at time t; is the amount of thermal load participating in longitudinal DR at time t; is the amount of gas load participating in longitudinal DR at time t.

2. The optimal scheduling method for a hydrogen-integrated energy system considering the stepped green certificate trading mechanism and dual response of source and load according to claim 1, wherein, The number of green certificates N participating in the green certificate market transaction GCT , the expression is: N GCT = N ob -N ne ; Among them, N ob is the number of green certificates obtained by the enterprise; N ne is the number of green certificates required to meet the indicators.

3. The optimal scheduling method for a hydrogen-integrated energy system considering the stepped green certificate trading mechanism and dual response of source and load according to claim 1, characterized in that, The load-side flexible response model includes: establishing a horizontal DR model and a vertical DR model for a multi-load including electric, thermal, and gas loads.

4. The optimal scheduling method for a hydrogen-integrated energy system considering the stepped green certificate trading mechanism and dual response of source and load according to claim 3, wherein, The vertical DR model: Wherein: is the longitudinal DR post-load of the i-th load at time t; is the alternative load of the i-th load at time t; is the amount of the i-th load participating in longitudinal DR at time t; is a 0-1 variable; are the replacement-out and replacement-in powers of the i-th load at time t, respectively; respectively represent the maximum load ratio of the i-th load participating in longitudinal DR at time t; is the initial value of the i-th load; T represents the scheduling period.

5. The optimal scheduling method for a hydrogen-integrated energy system considering the stepped green certificate trading mechanism and dual response of power generation and load according to claim 1, characterized in that The constraint conditions include energy storage system constraints, GB operation constraints, electric power balance constraints, thermal power balance constraints, natural gas balance constraints, and hydrogen balance constraints.

6. A system for implementing the optimization scheduling method of a hydrogen-integrated energy system considering the stepped green certificate trading mechanism and dual response of power generation and load as claimed in claim 1, characterized in that, Including: The first establishment module is used to establish a carbon capture coupled power-to-gas model; among them, the carbon capture coupled power-to-gas model includes a CCS model and a P2G model; The second establishment module is used to establish a stepped green certificate trading model; among them, the stepped green certificate trading model includes a stepped carbon trading mechanism and a stepped green certificate trading mechanism; The third establishment module is used to establish a source-load dual response model; among them, the source-load dual response model includes a source-side flexible response model and a load-side flexible response model; The establishment and solution module is used to establish and solve an HIES optimal scheduling model considering the carbon capture coupled power-to-gas model and source-load dual response under stepped green certificates.

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