A method for matching and operation optimization of coal power-SOE coupling peak shaving system

Abstract

The present application relates to coal-fired power generation and hydrogen energy technical field, it discloses a kind of coal power-SOE coupling peak shaving system proportion and operation optimization method, it includes: S1: the proportioning benefit model of establishing coal-fired unit and solid oxide electrolysis coupling system, the proportioning benefit model includes system cost model and system benefit model: S2: collaborative peak shaving model is constructed, SOEC capacity proportioning and operation optimization are carried out using double-layer planning method;S3: the upper and lower model is solved using CPLEX solver;The optimal capacity configuration and coordinated operation optimization scheme of coal-fired unit and solid oxide electrolysis coupling system are generated;S4: real-time monitoring system operating state, verify power grid power balance constraint and hydrogen mass balance constraint, and according to operation result update lower layer dispatching or feedback to upper layer and carry out periodic correction.The present application coupling peak shaving system realizes electric heat hydrogen multi-energy coupling operation, to significantly improve the peak shaving depth and variable load rate of coal-fired power plant.

Description

Technical Field

[0001] This invention relates to the fields of coal-fired power generation and hydrogen energy technology, and in particular to a method for optimizing the proportioning and operation of a coal-fired power-SOE coupled peak-shaving system. Background Technology

[0002] With the rapid expansion of installed capacity of renewable energy (such as wind power and photovoltaics), the power grid faces the challenge of increased power output intermittency and load fluctuation, urgently requiring coal-fired power plants to improve peak-shaving flexibility to ensure stable grid operation. Existing peak-shaving technologies for coal-fired units have problems such as: limited deep peak-shaving capacity and safety hazards, poor economic efficiency and high environmental costs of peak-shaving, and insufficient synergy between energy storage and peak-shaving technologies.

[0003] When coal-fired power units operate at low loads, the minimum stable combustion load limit on the boiler side can easily lead to problems such as unstable combustion and water-cooled wall tube rupture, while the turbine side efficiency drops significantly, resulting in a sharp increase in coal consumption costs. Traditional deep peak shaving relies on oil injection for stable combustion or frequent start-ups and shutdowns of units, which not only increases oil consumption costs but also exacerbates the environmental burden due to carbon and pollutant emissions. In addition, existing technologies have limited capacity to absorb curtailed wind and solar power, resulting in insufficient utilization of renewable energy. Existing energy storage technologies (such as battery energy storage) have problems with small capacity and short lifespan. Hydrogen energy storage has great potential, but there are few methods for system-wide coordinated optimization operation coupled with coal-fired power units. System economics is a crucial factor directly related to the implementation of deep peak shaving for coal-fired power units, and the economics of peak shaving for thermal power units has become a widely studied topic by scholars both domestically and internationally. The implementation plan for the new generation of coal-fired power upgrading special action indicates that in areas with peak shaving deficits, a number of coal-fired power units with deep peak shaving capabilities and wide-load efficient regulation capabilities will be upgraded and newly built. The current generation of new-generation coal-fired power pilot demonstration units has achieved a breakthrough in load change rate (4% rated load / minute in the 50% and above load range, and 2% rated load / minute in the 30%-50% load range). Solid oxide electrolysis (SOEC) technology, with its high-temperature operating characteristics and multi-energy cogeneration capabilities (heat, electricity, and hydrogen), can be coupled with coal-fired units on a large scale through modular design, providing an innovative path to overcome the current economic dilemma of peak-shaving technology. This invention utilizes the coupling of coal-fired units with SOEC, and through upper-level capacity matching, avoids excessive or insufficient SOEC configuration, achieving a balance between capital investment and peak-shaving benefits, and significantly reducing overall operating costs. In real-time operation, SOEC can quickly absorb surplus electricity from coal-fired units for hydrogen production, achieving deep peak shaving for the units; simultaneously, SOEC has a second-level power response capability, which can adjust the system's load reduction rate and response speed during grid fluctuations.

[0004] A Chinese patent with publication number CN120119293A discloses an auxiliary machine-free solid oxide electrolysis (SOE) hydrogen production system and an auxiliary coal-fired power plant deep peak shaving method. The system includes an SOE hot box system, a hydrogen circulation subsystem, and a hydrogen storage subsystem. The SOE hydrogen production system can assist coal-fired power plants in deep peak shaving. By establishing a power-steam-air-condensate process coupling between the SOE hydrogen production system and the coal-fired power plant, and combining multi-stage steam extraction adjustment, it achieves efficient and flexible deep peak shaving. However, this patented technology lacks capacity configuration and coordinated operation optimization technology between coal-fired power plants and the SOE system.

[0005] A Chinese patent with publication number CN111668834A provides a method for optimizing the capacity configuration of a hydrogen production system in a thermal power plant based on auxiliary peak-shaving services. It establishes an economic model for the hydrogen production system of thermal power units oriented towards auxiliary peak-shaving for renewable energy consumption, including an auxiliary peak-shaving cost model and an auxiliary peak-shaving revenue model, and establishes a control strategy for the coordinated operation of the thermal power unit and the hydrogen production system. However, this technology does not consider the type of electrolyzer in the hydrogen production system and the impact of the hydrogen and oxygen produced on peak-shaving costs.

[0006] A Chinese patent with publication number CN116896074A provides an optimization method for electrolytic hydrogen production facilities to participate in peak shaving and frequency regulation. The method involves determining first-stage and second-stage decision variables; constructing an objective function based on these variables, along with the total costs incurred when the first and second electrolytic hydrogen production facilities participate as frequency regulation equipment in grid peak shaving and frequency regulation; setting constraints; solving for the first and second-stage decision variables based on the objective function and constraints to obtain the first and second decisions; and then using these decisions to perform stochastic optimization on the participation of the first and second electrolytic hydrogen production facilities in grid peak shaving and frequency regulation. While this method considers the uncertainty of the frequency regulation signal and addresses this uncertainty by setting random variables, it does not include equipment lifespan costs in the model, sets the ramp-up limit to a fixed value, and does not consider the differences in ramp-up capabilities of the equipment at different operating points.

[0007] A Chinese patent with publication number CN118249422A provides an optimized scheduling method for industrial virtual power plants that considers hydrogen production and energy storage. This method solves the technical problems of limited adjustable range and reduced unit flexibility caused by the thermoelectric coupling characteristics of current virtual power plants. In particular, it relates to an optimized scheduling method for industrial virtual power plants that considers hydrogen production and energy storage. This method can reduce the degree of multi-energy coupling in industrial virtual power plants and enhance the peak-shaving capacity of cogeneration units to a certain extent. However, it has an excessively strong predictive dependence and has not been verified for grid compatibility. Summary of the Invention

[0008] In order to overcome or alleviate one or more of the above technical problems, the purpose of this invention is to provide a method for optimizing the proportioning and operation of a coal-fired power-SOE coupled peak shaving system. The coupled peak shaving system realizes multi-energy coupled operation of electricity, heat and hydrogen to significantly improve the peak shaving depth and load change rate of coal-fired power plants.

[0009] This invention provides the following technical solution:

[0010] A method for optimizing the proportioning and operation of a coal-fired power plant-SOE coupled peak-shaving system includes the following steps:

[0011] S1: Based on the collected parameters, establish a ratio benefit model for the coal-fired power unit and the solid oxide electrolysis coupling system. The ratio benefit model includes a system cost model and a system revenue model: the system cost model includes a system coal consumption cost model and an SOEC system investment cost model; the system revenue model includes hydrogen production revenue, electricity sales revenue, and peak shaving subsidy revenue.

[0012] S2: Construct a collaborative peak-shaving model and use a two-level programming method for SOEC capacity allocation and operation optimization. The collaborative peak-shaving model includes an upper-level model and a lower-level model: the upper-level model is for capacity allocation decision-making, used to determine the SOEC installed capacity with long-term economic efficiency as the objective; the lower-level model is for operation optimization, used to calculate the output allocation ratio for minute-level response and hour-level economic scheduling within the given capacity boundary in the upper-level model, with the objective of maximizing the total system revenue and comprehensive energy efficiency.

[0013] During operation, the output of coal-fired units is reduced to the safe peak-shaving benchmark value according to the grid peak-shaving instructions. When further deep adjustment is required, the surplus electricity is absorbed and hydrogen is produced through the solid oxide electrolysis coupling system. When the peak-shaving demand exceeds the response capacity of the coal-fired units, that is, about 30% of their rated load, the SOEC fast power regulation function is activated first to balance grid fluctuations.

[0014] S3: Using mixed-integer linear programming on the AMPL platform, combining minute-level peak-shaving response and hour-level economic scheduling, the CPLEX solver is used to solve the upper and lower layer models. The upper and lower layers are coupled and verified through iterative or feedback mechanisms, and the upper layer capacity decision is corrected; generating a coupling between coal-fired units and solid oxide electrolysis. system The optimal capacity configuration and coordinated operation optimization scheme;

[0015] S4: Monitor the system's operating status in real time, verify the power balance constraints of the power grid and the hydrogen quality balance constraints, and update the lower-level scheduling or feed back to the upper level for periodic correction based on the operating results.

[0016] According to some possible implementation methods, the system coal consumption cost model is calculated using the following formula:

[0017] (1)

[0018] In the formula, For fuel costs; For coal prices; Coal consumption for load range i; The duration of operation for load interval i.

[0019] According to some possible implementation methods, in the system revenue model, the hydrogen production revenue is calculated using the following formula:

[0020] (2)

[0021] In the formula, For revenue from hydrogen sales; For the price of hydrogen; The hydrogen production rate in load range i; Duration of operation within load interval i;

[0022] The revenue from electricity sales is calculated using the following formula:

[0023] (3)

[0024] In the formula, Revenue from electricity sales; Electricity consumption within load range i; The on-grid electricity price is RMB / kWh, and the value is determined based on the local electricity price.

[0025] The peak-shaving subsidy revenue is calculated using the following formula:

[0026] (4)

[0027] In the formula, For peak shaving revenue; The peak-shaving subsidy price within load range i; Peak-shaving capacity within load range i.

[0028] According to some possible implementations, the constraints that the coal-fired power unit and the solid oxide electrolytic coupling system need to satisfy include:

[0029] The output constraints and variable load speeds of the coal-fired power units are as follows:

[0030] (5)

[0031] (6)

[0032] In the formula, Rated power of coal-fired power units, in MW; Let t be the output power of the coal-fired unit at time t, in MW; The output power of the coal-fired unit at time t-1 is expressed in MW. and These are the upper and lower constraints on the ramp rate during peak shaving for coal-fired power units;

[0033] Output constraints and variable load speeds of the solid oxide electrolytic coupling system:

[0034] (7)

[0035] (8)

[0036] In the formula, Minimum power of SOEC electrolysis system, MW; λ represents the rated power of the solid oxide electrolytic coupling system (MW); λ is the upper limit of the variable load rate. Let be the power (in MW) of the solid oxide electrolytic coupling system at time t. The power of the solid oxide electrolytic coupling system at time t-1 is expressed in MW.

[0037] The power balance constraints of the power grid:

[0038] (9)

[0039] In the formula, Power supplied to the grid, in MW;

[0040] The hydrogen mass balance constraint:

[0041] (10)

[0042] (11)

[0043] In the formula, The hydrogen production rate in load range i; Duration of operation within load interval i; Let t be the amount of hydrogen stored in the system at time t, in kg; The amount of hydrogen stored in the system at time t-1, in kg; Let t be the hydrogen production of the solid oxide electrolytic coupling system at time t, in kg; Let t be the amount of hydrogen used for stable combustion of the coal-fired unit, in kg; Let t be the amount of hydrogen sold by the system at time t, in kg.

[0044] According to some possible implementation methods, the overall revenue objective function of the coal-fired power-SOE ratio benefit model is:

[0045] (12)

[0046] In the formula, X represents the total revenue of the coal-fired power plant-SOEC coupled system, and C soec This indicates the initial investment cost of SOEC;

[0047] The efficiency objective function of the solid oxide electrolytic coupling system is:

[0048] (13)

[0049] (14)

[0050] In the formula, η is the efficiency of the coal-fired power plant-SOEC coupled system, and W ele For internet access power consumption, W hyd For the energy of hydrogen output by the system, m H2 To output the mass flow rate of hydrogen, LHV H2 This is the lower heating value of hydrogen.

[0051] According to some possible implementation methods, the parameters collected in step S1 include real-time grid peak-shaving demand, coal-fired power plant operation sequence data, upper and lower limits of coal-fired unit output, hydrogen market price, peak-shaving subsidy policy, and system component technical parameters.

[0052] According to some possible implementation methods, the solid oxide electrolytic coupling system is replaced with a reversible solid oxide unit, i.e., RSOC, while the operation optimization method remains unchanged. When the grid is under low load or the output of new energy is at its peak, the RSOC is controlled to operate in SOEC mode. When the grid load increases or the peak shaving command requires rapid load increase, the RSOC is controlled to switch from SOEC mode to SOFC mode to achieve rapid load increase assistance. Through the mode switching of the RSOC, bidirectional energy flow and time-shift regulation are realized, the peak shaving capacity is expanded, and the system load increase rate is improved.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] (1) The proposed method for optimizing the allocation and operation of a coal-fired power plant-SOE coupled peak-shaving system addresses the issue of coordinated operation between coal-fired power units and SOEC. It employs a two-level programming method to simultaneously obtain the SOEC capacity allocation and coordinated operation optimization strategy for the coupled system, achieving a unified approach between long-term investment decisions and real-time operation scheduling. By correcting capacity allocation through operational feedback, it avoids over-investment or insufficient response caused by traditional static allocation, ensuring the system maintains optimal economic efficiency and energy performance.

[0055] (2) The method for optimizing the ratio and operation of a coal-fired power-SOE coupled peak shaving system proposed in this invention addresses the problem of limited peak shaving depth of existing units. It utilizes the rapid adjustment capability of SOEC to absorb the surplus power of coal-fired units and combines it with the cascade utilization of waste heat to achieve multi-energy coupled operation of electricity, heat and hydrogen. This method effectively expands the adjustable output range of coal-fired units, significantly improves the peak shaving depth and load change rate of the system, improves the stability and energy efficiency of the units under deep peak shaving conditions, and achieves multi-dimensional synergistic gains.

[0056] (3) The proposed method for optimizing the allocation and operation of a coal-fired power-SOE coupled peak-shaving system takes the maximization of overall system energy efficiency and revenue as the optimization criterion, and comprehensively considers multi-dimensional economic factors such as electricity sales, hydrogen production, and peak-shaving subsidies to achieve the optimal economic allocation between SOEC capacity and coal-fired power output. By reducing costs and increasing efficiency, this method improves the overall economic return of the coupled system, enhances the peak-shaving and frequency regulation capabilities of coal-fired power units in a high-proportion renewable energy grid, and provides technical support for the transformation of coal-fired power. Attached Figure Description

[0057] Figure 1 This is a schematic diagram illustrating the ratio and operation optimization method of a coal-fired power-SOE coupled peak-shaving system provided in an embodiment of the present invention. Detailed Implementation

[0058] The present invention will now be described in detail with reference to embodiments and accompanying drawings. However, it should be understood that the embodiments and drawings are for illustrative purposes only and do not constitute any limitation on the scope of protection of the present invention. All reasonable modifications and combinations included within the inventive spirit of the present invention fall within the scope of protection of the present invention.

[0059] The present invention will be further described below with reference to the accompanying drawings.

[0060] Example 1

[0061] like Figure 1 As shown in Embodiment 1, a method for optimizing the proportioning and operation of a coal-fired power-SOE coupled peak-shaving system is disclosed, which includes the following steps:

[0062] (1) Establish a proportional benefit model for the coupling system of coal-fired power units and solid oxide electrolysis (SOEC), including a system cost model and a system revenue model: the system cost model includes the system coal consumption cost and the SOEC system investment cost model; the system revenue model covers hydrogen production revenue, electricity sales revenue and peak shaving subsidy revenue; multi-objective optimization model: with the dual objectives of maximizing the total system revenue and energy efficiency, the constraints include the output constraints and load change speed of coal-fired power units, the output constraints and load change speed of SOEC, and the power balance and hydrogen balance requirements of the power grid.

[0063] (2) Based on the collaborative peak shaving model, a graded collaborative operation control strategy of coal-fired unit-SOEC is designed to address the differentiated peak shaving demands of existing coal-fired units (minimum power output 25%-40% of rated load) and new generation demonstration units (minimum output <20% of rated load). A two-layer planning method is adopted for capacity allocation and operation optimization: the upper layer is for capacity allocation decision (i.e. SOEC capacity and control strategy decision), which is used to determine the SOEC installed capacity with long-term economic efficiency as the goal; the lower layer is for operation optimization, which calculates the output allocation ratio for minute-level response and hour-level economic dispatch within the given capacity boundary of the upper layer, with the goal of maximizing the total system revenue and comprehensive energy efficiency; after receiving the grid peak shaving command, the output of coal-fired units is reduced to the safe peak shaving benchmark value first; when further deep adjustment is required, the SOEC system is activated to absorb the surplus power of coal-fired units and push the unit load depth down to below the benchmark value; when the peak shaving demand exceeds the response capacity of coal-fired units (around 30% of rated load), the SOEC fast power regulation function is activated first to balance grid fluctuations;

[0064] (3) Using the AMPL platform for mixed integer linear programming, combined with minute-level peak shaving response and hour-level economic scheduling, the CPLEX solver is used to solve the upper and lower level models. The upper and lower levels are coupled and verified through iteration or feedback mechanisms, and the upper level capacity decision is corrected; the optimal capacity configuration and coordinated operation optimization scheme of coal-fired units and SOEC is generated.

[0065] (4) Monitor the system operation status in real time, verify constraints such as power balance and hydrogen mass balance, and update the lower-level scheduling or feed back to the upper level for periodic correction based on the operation results.

[0066] Furthermore, in the coal consumption cost model for coal-fired power units, the coal consumption cost is calculated using the following formula:

[0067] (1)

[0068] In the formula, - Fuel costs; - Coal prices; -Coal consumption in load range i; -Duration of load interval i;

[0069] In the system revenue model, the revenue from hydrogen production is calculated using the following formula:

[0070] (2)

[0071] In the formula, For revenue from hydrogen sales; For the price of hydrogen; The hydrogen production rate in load range i; Running time within load interval i.

[0072] Revenue from electricity sales is calculated using the following formula:

[0073] (3)

[0074] In the formula, Revenue from electricity sales; Electricity consumption within load range i; The on-grid electricity price (RMB / kWh) is determined based on the local electricity price.

[0075] Peak-shaving subsidy revenue is calculated using the following formula:

[0076] (4)

[0077] In the formula, For peak shaving revenue; The peak-shaving subsidy price within load range i; Peak-shaving capacity within load range i.

[0078] The constraints that coal-fired power units and SOEC electrolysis systems need to meet include:

[0079] Output constraints and load change speed of coal-fired power units:

[0080] (5)

[0081] (6)

[0082] In the formula, Rated power of coal-fired power units, in MW; Let t be the output power of the coal-fired unit at time t, in MW; The output power of the coal-fired unit at time t-1 is expressed in MW. and These are the upper and lower constraints on the ramp rate during peak shaving for coal-fired power units.

[0083] SOEC electrolysis system output constraints and variable load speed:

[0084] (7)

[0085] (8)

[0086] In the formula, Minimum power of SOEC electrolysis system, MW; λ represents the rated power of the SOE electrolysis system (MW); λ is the upper limit of the variable load rate. Let t be the power of the SOEC electrolysis system at time t, in MW; Let represent the power of the SOEC electrolysis system at time t-1, in MW.

[0087] Power balance constraints of the power grid:

[0088] (9)

[0089] In the formula, The power output of the grid is expressed in MW.

[0090] Hydrogen mass balance constraint:

[0091] (10)

[0092] (11)

[0093] In the formula, The hydrogen production rate in load range i; Duration of operation within load interval i; Let t be the amount of hydrogen stored in the system at time t, in kg; The amount of hydrogen stored in the system at time t-1, in kg; Let t be the hydrogen production of the SOEC electrolysis system at time t, in kg; Let t be the amount of hydrogen used for stable combustion of the coal-fired unit, in kg; Let t be the amount of hydrogen sold by the system at time t, in kg.

[0094] The objective function for the total revenue of the model is:

[0095] (12)

[0096] In the formula, X represents the total revenue of the coal-fired power plant-SOEC coupled system, and C soec This represents the initial investment cost of SOEC.

[0097] The efficiency objective function of the coupled system is:

[0098] (13)

[0099] (14)

[0100] In the formula, η is the efficiency of the coal-fired power plant-SOEC coupled system, and W ele For internet access power consumption, W hyd For the energy of hydrogen output by the system, m H2 To output the mass flow rate of hydrogen, LHV H2 This is the lower heating value of hydrogen.

[0101] Furthermore, the input parameters for optimizing the execution method include:

[0102] Real-time grid peak-shaving demand, coal-fired power plant operation sequence data, upper and lower limits of coal-fired unit output, hydrogen market price, peak-shaving subsidy policy and system technical parameters; furthermore, the peak-shaving interval is 15 minutes.

[0103] Example 2

[0104] This embodiment provides an improved scheme for the proportioning and operation method of a coal-fired power plant-SOE coupled peak-shaving system. The SOEC in Embodiment 1 is replaced with a reversible solid oxide cell (RSOC). The system employs a unified energy management controller to achieve coordinated power allocation between the coal-fired power plant and the RSOC based on grid dispatch instructions and load forecast signals. When the grid is under low load or during peak renewable energy output, the RSOC operates in SOEC mode, utilizing surplus electricity for hydrogen electrolysis and simultaneously using waste heat from the coal-fired unit for thermal integration to improve electrolysis efficiency. When the grid load increases or peak-shaving instructions require the unit to rapidly increase load, the RSOC switches from SOEC mode to SOFC mode, using stored hydrogen as fuel to generate electricity and output power to the grid, achieving rapid load increase assistance. The control system prioritizes stable combustion of the coal-fired power plant and rapid response of the SOFC through hierarchical control logic.

[0105] This embodiment significantly improves the system's load-up rate through SOFC discharge assistance, effectively mitigating the lag problem of traditional coal-fired units in rapid peak shaving. SOEC mode absorbs off-peak electricity from the grid to produce hydrogen, while SOFC mode discharges during peak hours, achieving bidirectional energy flow and time-shift regulation, thus expanding the unit's peak-shaving capacity and enhancing its bidirectional peak-shaving capability. The periodic switching between hydrogen energy storage and power generation improves system utilization and peak-shaving benefits, while reducing the cost of frequent start-ups and shutdowns. Furthermore, it reduces the demand for stable fuel combustion and short-term emission peaks during rapid load increases, improving the unit's environmental performance.

[0106] The technical solution in this embodiment can further improve the overall load increase rate and bidirectional peak shaving capability of the system.

[0107] The above embodiments are merely preferred embodiments of the present invention, and the scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for optimizing the proportioning and operation of a coal-fired power-SOE coupled peak-shaving system, characterized in that, Includes the following steps: S1: Based on the collected parameters, establish a ratio benefit model for the coal-fired power unit and the solid oxide electrolysis coupling system. The ratio benefit model includes a system cost model and a system revenue model: the system cost model includes a system coal consumption cost model and an SOEC system investment cost model; the system revenue model includes hydrogen production revenue, electricity sales revenue, and peak shaving subsidy revenue. S2: Construct a collaborative peak-shaving model and use a two-level programming method for SOEC capacity allocation and operation optimization. The collaborative peak-shaving model includes an upper-level model and a lower-level model: the upper-level model is for capacity allocation decision-making, used to determine the SOEC installed capacity with long-term economic efficiency as the objective; the lower-level model is for operation optimization, used to calculate the output allocation ratio for minute-level response and hour-level economic scheduling within the given capacity boundary in the upper-level model, with the objective of maximizing the total system revenue and comprehensive energy efficiency. During operation, the output of coal-fired units is reduced to the safe peak-shaving benchmark value according to the grid peak-shaving instructions. When further deep adjustment is required, the surplus electricity is absorbed and hydrogen is produced through the solid oxide electrolysis coupling system. When the peak-shaving demand exceeds the response capacity of the coal-fired units, that is, about 30% of their rated load, the SOEC fast power regulation function is activated first to balance grid fluctuations. S3: Using mixed integer linear programming on the AMPL platform, combining minute-level peak shaving response and hour-level economic scheduling, the CPLEX solver is used to solve the upper and lower layer models. The upper and lower layers are coupled and verified through iterative or feedback mechanisms, and the upper layer capacity decision is corrected. The optimal capacity configuration and coordinated operation optimization scheme of the coal-fired unit and the solid oxide electrolysis coupling system is generated. S4: Monitor the system's operating status in real time, verify the power balance constraints of the power grid and the hydrogen quality balance constraints, and update the lower-level scheduling or feed back to the upper level for periodic correction based on the operating results; The objective function of the coal-fired power plant-SOE ratio benefit model for maximizing the total system revenue and comprehensive energy efficiency described in step S2 is: （12） In the formula, X represents the total revenue of the coal-fired power plant-SOEC coupled system; For revenue from hydrogen sales; Revenue from electricity sales; For peak shaving revenue; For fuel costs; C soec This indicates the initial investment cost of SOEC; The efficiency objective function of the solid oxide electrolytic coupling system is: （13） （14） In the formula, η is the efficiency of the coal-fired power plant-SOEC coupled system, and W ele For internet access power consumption, W hyd For the energy of hydrogen output by the system, m H2 To output the mass flow rate of hydrogen, LHV H2 This is the lower heating value of hydrogen.

2. The method for optimizing the proportioning and operation according to claim 1, characterized in that, The system coal consumption cost model is calculated using the following formula: （1） In the formula, For fuel costs; For coal prices; Coal consumption for load range i; The duration of operation for load interval i.

3. The method for optimizing the proportioning and operation according to claim 1, characterized in that, In the system revenue model, the hydrogen production revenue is calculated using the following formula: （2） In the formula, For revenue from hydrogen sales; For the price of hydrogen; The hydrogen production rate in load range i; Duration of operation within load interval i; The revenue from electricity sales is calculated using the following formula: （3） In the formula, Revenue from electricity sales; Electricity consumption within load range i; The on-grid electricity price is in yuan / kWh and is determined based on the local electricity price. The peak-shaving subsidy revenue is calculated using the following formula: （4） In the formula, For peak shaving revenue; The peak-shaving subsidy price within load range i; Peak-shaving capacity within load range i.

4. The method for optimizing the proportioning and operation according to claim 1, characterized in that, The constraints that the coal-fired power unit and the solid oxide electrolytic coupling system need to meet include: Output constraints and load change speed of coal-fired power units: （5） （6） In the formula, Rated power of coal-fired power units, in MW; The output power of the coal-fired unit at time t is expressed in MW. The output power of the coal-fired unit at time t-1 is expressed in MW. and These are the upper and lower constraints on the ramp rate during peak shaving for coal-fired power units; Output constraints and variable load speed of solid oxide electrolytic coupling system: （7） （8） In the formula, This is the minimum power output of the SOEC electrolysis system, measured in MW. λ represents the rated power of the solid oxide electrolytic coupling system, in MW; λ is the upper limit of the variable load rate. The power of the solid oxide electrolytic coupling system at time t is expressed in MW. The power of the solid oxide electrolytic coupling system at time t-1 is expressed in MW. The power balance constraints of the power grid: （9） In the formula, Power supplied to the grid, in MW; The hydrogen mass balance constraint: （10） （11） In the formula, The hydrogen production rate in load range i; Duration of operation within load interval i; The system's hydrogen storage capacity at time t is expressed in kg. The system's hydrogen storage capacity at time t-1 is expressed in kg. The hydrogen production of the solid oxide electrolytic coupling system at time t is expressed in kg. The amount of hydrogen used for stable combustion of the coal-fired unit at time t is expressed in kg. The amount of hydrogen sold by the system at time t is expressed in kg.

5. The method for optimizing the proportioning and operation according to claim 1, characterized in that, The parameters collected in step S1 include real-time grid peak-shaving demand, operating sequence data of coal-fired power plants, upper and lower limits of coal-fired unit output, hydrogen market price, peak-shaving subsidy policy, and technical parameters of system components.

6. The method for optimizing the proportioning and operation according to any one of claims 1 to 5, characterized in that, The solid oxide electrolytic coupling system is replaced with a reversible solid oxide unit, i.e., RSOC, while the operation optimization method remains unchanged. When the grid is under low load or when the output of new energy sources is at its peak, the RSOC is controlled to operate in SOEC mode. When the grid load increases or the peak shaving command requires rapid load increase, the RSOC is controlled to switch from SOEC mode to SOFC mode to achieve rapid load increase assistance. Through the mode switching of the RSOC, bidirectional energy flow and time-shift regulation are realized, the peak shaving capacity is expanded, and the system load increase rate is improved.

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