Proportioning and operation optimization method of coal electricity-SOE coupling peak shaving system

Abstract

The invention relates to the technical field of coal-fired power generation and hydrogen energy, and discloses a matching and operation optimization method of a coal power-SOE coupling peak shaving system, which comprises the following steps: S1, establishing a matching benefit model of a coal-fired unit and a solid oxide electrolysis coupling system, the matching benefit model comprises a system cost model and a system income model; S2, constructing a collaborative peak regulation model, and performing SOEC capacity matching and operation optimization by adopting a bilevel planning method; s3, solving the upper layer model and the lower layer model by using a CPLEX solver; generating an optimal capacity configuration and coordinated operation optimization scheme of the coal-fired unit and the solid oxide electrolysis coupling system; and S4, monitoring the operation state of the system in real time, verifying the power balance constraint of the power grid and the hydrogen mass balance constraint, and updating lower-layer scheduling or feeding back to an upper layer for periodic correction according to an operation result. According to the coupling peak regulation system, electricity, heat and hydrogen multi-energy coupling operation is achieved, so that the peak regulation depth and the variable load rate of a coal-fired power plant are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of coal-fired power generation and hydrogen energy technology, and in particular to a coal power-SOE coupling peak shaving system matching and operation optimization method. BACKGROUND

[0002] With the rapid expansion of renewable energy (such as wind power and photovoltaic) installed capacity, the power grid is facing the challenge of increasing intermittency of output and volatility of load, and it is urgent to improve the flexibility of coal-fired power plants to ensure stable operation of the power grid. The existing coal-fired unit peak shaving technology has the following problems: limited deep peak shaving capacity and safety hazards, poor peak shaving economy and high environmental cost, and insufficient energy storage and peak shaving coordination technology.

[0003] When the coal-fired unit is running at low load, the boiler side is prone to cause unstable combustion, water wall pipe explosion and other problems due to the minimum stable combustion load limit, while the efficiency of the steam turbine side decreases significantly, resulting in a sharp increase in coal consumption cost; traditional deep peak shaving relies on oil injection to stabilize combustion or frequent start-stop of the unit, which not only increases oil consumption cost, but also increases environmental burden due to carbon emissions and pollutant emissions. In addition, the existing technology has limited capacity to absorb abandoned wind and light power, resulting in insufficient utilization of renewable energy; the existing energy storage technology (such as battery energy storage) has small capacity and short service life, and hydrogen energy storage has great potential, but there are few methods for coupled system optimization operation with coal-fired units. System economy is an important factor directly related to the implementation of deep peak shaving of coal-fired units, and the economy of thermal power unit peak shaving has become a hot research topic for scholars at home and abroad. The implementation plan of the new generation of coal power upgrading special action shows that in the areas where there is a shortage of peak shaving, a number of coal-fired units with deep peak shaving capacity and wide load high-efficiency regulation capacity are to be transformed and newly built. The current new generation of coal power pilot demonstration unit has achieved a breakthrough in load change rate (4% rated load per minute in the 50% and above load range, and 2% rated load per minute in the 30%-50% load range). The solid oxide electrolysis (SOEC) technology, with its high-temperature operation characteristics and heat-electricity-hydrogen multi-energy co-production capacity, can be coupled with coal-fired units on a large scale through modular design, providing an innovative path to solve the current economic dilemma of peak shaving technology. The present application utilizes the coupling of coal-fired units and SOEC, through upper layer capacity matching, to avoid SOEC over-provisioning or under-provisioning, achieve a balance between capital investment and peak shaving revenue, and significantly reduce overall operating costs. In real-time operation, SOEC can quickly absorb excess power from coal-fired units for hydrogen production, achieving deep peak shaving of the unit; at the same time, SOEC has a second-level power response capability, which can adjust the load reduction rate and response speed of the system when the power grid fluctuates.

[0004] The existing Chinese patent with publication number CN120119293A provides a solid oxide electrolysis system without auxiliary machine for hydrogen production and an auxiliary coal power deep adjustment method. The SOE hydrogen production system can assist the coal-fired power plant in deep adjustment. By establishing a power-steam-air-condensed water process coupling between the SOE hydrogen production system and the coal-fired power plant, combined with steam extraction multi-stage adjustment, efficient and flexible deep peak regulation is achieved. The patent lacks the capacity configuration and collaborative operation optimization technology of coal power and SOEC.

[0005] The existing Chinese patent with publication number CN111668834A provides a capacity optimization configuration method for hydrogen production system of thermal power plant based on auxiliary peak regulation service. An economic model of hydrogen production system of thermal power unit facing new energy consumption auxiliary peak regulation is established, including auxiliary peak regulation cost model and auxiliary peak regulation income model, and a control strategy for collaborative operation of thermal power unit and hydrogen production system is established. This technology does not consider the type of electrolytic cell of hydrogen production system and the influence of hydrogen and oxygen generated by the electrolytic cell on peak regulation cost.

[0006] The existing Chinese patent with publication number CN116896074A provides an optimization method for electrolytic hydrogen production facility participating in peak regulation and frequency regulation. The one-stage decision variable and the two-stage decision variable are determined. The objective function is constructed based on the one-stage decision variable, the two-stage decision variable, and the total cost generated when the first electrolytic hydrogen production facility and the second electrolytic hydrogen production facility participate in grid peak regulation and frequency regulation as frequency regulation devices, and the constraint condition is set. The one-stage decision variable and the two-stage decision variable are solved based on the objective function and the constraint condition to obtain the first decision and the second decision. The first decision and the second decision are used to randomly optimize the process of the first electrolytic hydrogen production facility and the second electrolytic hydrogen production facility participating in grid peak regulation and frequency regulation. This scheme considers the uncertainty of frequency regulation signal and solves the uncertainty factor by setting random variables, but the equipment life cost is not considered in the model, the climbing upper limit is set as a fixed value, and the climbing ability difference of the equipment at different operating points is not considered.

[0007] The existing Chinese patent with publication number CN118249422A provides an industrial virtual power plant optimization scheduling method considering hydrogen production and energy storage, which solves the technical problems of small adjustable range and reduced unit flexibility of virtual power plant due to thermal power coupling characteristics, especially relates to an industrial virtual power plant optimization scheduling method considering hydrogen production and energy storage. This method can reduce the degree of multi-energy coupling of industrial virtual power plant and enhance the peak regulation capacity of combined heat and power unit to a certain extent, but the prediction dependence is too strong and the grid compatibility verification is not performed. SUMMARY

[0008] In order to overcome or alleviate one or more of the above technical problems, the present application aims to provide a coal-SOE coupling peak shaving system matching and operation optimization method, which realizes the multi-energy coupling operation of electric heating hydrogen, so as to significantly improve the peak shaving depth and variable load rate of the coal-fired power plant.

[0009] The present application provides the following technical solutions:

[0010] A coal-SOE coupling peak shaving system matching and operation optimization method, comprising the following steps:

[0011] S1: According to the collected parameters, a matching benefit model of the coal-fired unit and the solid oxide electrolysis coupling system is established, the matching benefit model includes a system cost model and a system benefit model: the system cost model includes a system coal consumption cost model and an SOEC system investment cost model; the system benefit model includes hydrogen production benefit, electricity sales benefit and peak shaving subsidy benefit;

[0012] S2: A collaborative peak shaving model is constructed, and a double-layer planning method is used for SOEC capacity matching and operation optimization, the collaborative peak shaving model includes an upper model and a lower model: the upper model is a capacity matching decision, which is used to determine the SOEC installed capacity and take the long-term economy as the target; the lower model is operation optimization, which is used to calculate the output matching of the minute-level response and the hour-level economic dispatch within the capacity boundary given in the upper model, so as to maximize the system total benefit and comprehensive energy efficiency;

[0013] During operation, according to the power grid peak shaving instruction, the coal-fired unit output is preferentially reduced to the safe peak shaving reference value, when further deep adjustment is needed, the solid oxide electrolysis coupling system is used to consume the excess power to produce hydrogen; when the peak shaving demand exceeds the response capacity of the coal-fired unit, i.e. about 30% of its rated load, the SOEC rapid power regulation function is preferentially started to balance the power grid fluctuation;

[0014] S3: The AMPL platform mixed integer linear programming is used, combined with the minute-level peak shaving response and the hour-level economic dispatch, the CPLEX solver is used to solve the upper and lower models, the upper and lower layers are coupled and verified through the iteration or feedback mechanism, and the upper 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 are generated; System

[0015] S4: The system operation state is monitored in real time, the power balance constraint and the hydrogen quality balance constraint are verified, and the lower dispatch is updated or fed back to the upper layer for periodic correction according to the operation result.

[0016] According to some possible embodiments, the system coal consumption cost model is calculated by the following formula:

[0017] ​ (1)

[0018] wherein, is the fuel cost; is the coal price; is the coal consumption in load interval i; is the running time in load interval i.

[0019] According to some possible embodiments, in the system benefit model, the hydrogen production benefit is calculated by the following formula:

[0020] (2)

[0021] wherein, is the hydrogen sales benefit; is the hydrogen price; is the hydrogen production in load interval i; is the running time in load interval i;

[0022] The electricity sales benefit is calculated by the following formula:

[0023] (3)

[0024] wherein, is the electricity sales benefit; is the grid-connected electricity in load interval i; is the grid-connected electricity price, yuan / kWh, which is valued according to the electricity price in the region;

[0025] The peak shaving subsidy benefit is calculated by the following formula:

[0026] (4)

[0027] wherein, is the peak shaving benefit; is the peak shaving subsidy price in load interval i; is the peak shaving capacity in load interval i.

[0028] According to some possible embodiments, the constraints that the coal-fired unit and the solid oxide electrolysis coupling system need to meet include:

[0029] The coal-fired unit output constraint and variable load speed:

[0030] (5)

[0031] (6)

[0032] wherein, is the rated power of the coal-fired unit, MW; P t is the output power of the coal-fired unit at time t, MW; P t-1 is the output power of the coal-fired unit at time t-1, MW; and are respectively the upper and lower constraints of the ramping rate when the coal-fired unit is peaking;

[0033] The output constraint and variable load speed of the solid oxide electrolysis coupling system:

[0034] (7)

[0035] (8)

[0036] In the formula, P min is the minimum power of the SOEC electrolysis system, MW; P rated is the rated power of the solid oxide electrolysis coupling system, MW; and λ is the upper limit of the variable load rate; P t is the power of the solid oxide electrolysis coupling system at time t, MW; P t-1 is the power of the solid oxide electrolysis coupling system at time t-1, MW;

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

[0038] (9)

[0039] In the formula, P grid is the on-grid power of the power grid, MW;

[0040] The hydrogen mass balance constraint:

[0041] (10)

[0042] (11)

[0043] In the formula, H i is the hydrogen production amount of the load interval i; T i is the running time in the load interval i; H t is the system hydrogen storage amount at time t, kg; H t-1 is the system hydrogen storage amount at time t-1, kg; H t, SOEC is the hydrogen production amount of the solid oxide electrolysis coupling system at time t, kg; H t, CFU is the hydrogen amount for stable combustion of the coal-fired unit at time t, kg; H t, sell is the system hydrogen sales amount at time t, kg.

[0044] According to some possible embodiments, the total revenue objective function of the coal-SOE ratio benefit model is:

[0045] (12)

[0046] In the formula, X is the total income of the coal-fired power plant-SOEC coupling system, C soec represents the initial investment cost of SOEC;

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

[0048] (13)

[0049] (14)

[0050] In the formula, η is the efficiency of the coal-fired power plant-SOEC coupling system, W ele is the on-grid power, W hyd is the energy of the system output hydrogen, m H2 is the mass flow of the output hydrogen, LHV H2 is the low heat value of hydrogen.

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

[0052] According to some possible embodiments, the solid oxide electrolysis coupling system is replaced by a reversible solid oxide cell, i.e., RSOC, and the operation optimization method remains unchanged. When the power grid is in low load or new energy output peak, the RSOC is controlled to operate in SOEC mode. When the power grid load rises or the peak shaving instruction requires rapid loading, the RSOC is controlled to switch from SOEC mode to SOFC mode to realize rapid loading assistance. Through the mode switching of the RSOC, bidirectional flow of energy and time-shifting adjustment are realized, the peak shaving capacity is widened, and the system loading rate is improved.

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

[0054] (1) The ratio and operation optimization method of the coal power-SOE coupling peak shaving system proposed in the present application, aiming at the problem of coordinated operation of coal-fired units and SOEC, adopts a double-layer planning method to simultaneously obtain the coupling system SOEC capacity ratio and coordinated operation optimization strategy, realizing the coordinated unity of long-term investment decision and real-time operation scheduling. The capacity configuration is corrected through operation feedback, avoiding excessive investment or insufficient response caused by traditional static configuration, so that the system maintains optimal economic efficiency and energy efficiency level.

[0055] (2) The coal-SOE coupling peak shaving system ratio and operation optimization method provided by the application can effectively expand the adjustable output interval of the coal-fired unit, significantly improve the peak shaving depth and variable load rate of the system, improve the stability and energy efficiency of the unit under the condition of deep peak shaving, and realize multi-dimensional collaborative gain.

[0056] (3) The coal-SOE coupling peak shaving system ratio and operation optimization method provided by the application takes the maximization of system comprehensive energy efficiency and benefit as the optimization criterion, comprehensively considers multi-dimensional economic factors such as power sales, hydrogen production, peak shaving subsidies, etc., realizes the economic optimization of SOEC capacity configuration and coal power output ratio, and improves the overall economic return of the coupling system through cost reduction and benefit increase, enhances the peak shaving and frequency modulation capability of the coal-fired unit in the high-proportion renewable energy power grid, and provides technical support for coal-fired unit transformation. BRIEF DESCRIPTION OF DRAWINGS

[0057] Figure 1 A coal-SOE coupling peak shaving system ratio and operation optimization method provided by the embodiment of the application is shown in the figure. DETAILED DESCRIPTION

[0058] The application will be described in detail below in combination with embodiments and drawings, but it should be understood that the embodiments and drawings are only used to exemplarily describe the application and cannot constitute any limitation on the protection scope of the application. All reasonable transformations and combinations within the scope of the inventive concept of the application fall within the protection scope of the application.

[0059] The application will be further described below in combination with the drawings.

[0060] Embodiment 1

[0061] As shown in the figure, the embodiment 1 discloses a coal-SOE coupling peak shaving system ratio and operation optimization method, which comprises the following steps: Figure 1 (1) A solid oxide electrolysis (SOEC) coupling system ratio benefit model of a coal-fired unit is established, including a system cost model and a system benefit model: the system cost model includes a system coal consumption cost and a SOEC system investment cost model; the system benefit model covers hydrogen production benefit, power sales benefit and peak shaving subsidy benefit; a multi-objective optimization model: taking the maximization of system total benefit and energy efficiency as double objectives, the constraint conditions include coal-fired unit output constraint and variable load speed, SOEC output constraint and variable load speed, power grid power balance and hydrogen balance requirement.

[0062]

[0063] ​(2) Based on the coordinated peak shaving model, a coal-fired unit-SOEC hierarchical coordinated operation control strategy is designed for the differentiated peak shaving requirements of active coal-fired units (minimum power output 25%-40% of rated load) and new generation demonstration units (minimum output <20% of rated load). A bi-level planning method is used for capacity allocation and operation optimization: the upper layer is capacity allocation decision (i.e., SOEC capacity and control strategy decision), which is used to determine the SOEC installed capacity and aims at long-term economy; the lower layer is operation optimization, which calculates the output allocation within the capacity boundary given by the upper layer for minute-level response and hour-level economic dispatch, aiming at maximizing the total system revenue and comprehensive energy efficiency; after receiving the grid peak shaving instruction, the coal-fired unit output is preferentially reduced to the safe peak shaving reference value; when further deep adjustment is required, the SOEC system is started to consume the excess power of the coal-fired unit, and the unit load is deeply explored below the reference value; when the peak shaving demand exceeds the response capacity of the coal-fired unit (about 30% of rated load), the SOEC fast power regulation function is preferentially enabled to balance the grid fluctuation;

[0064] (3) AMPL platform mixed integer linear programming is used to combine minute-level peak shaving response and hour-level economic dispatch, and CPLEX solver is used to solve the upper and lower layer models. The upper and lower layers are coupled and verified through iteration or feedback mechanism to correct the upper layer capacity decision; the optimal capacity configuration and coordinated operation optimization scheme of the coal-fired unit and SOEC are generated;

[0065] (4) Real-time monitoring of system operation state, verification of power balance and hydrogen quality balance constraints, and updating of lower layer dispatch or feedback to upper layer for periodic correction according to operation results.

[0066] Further, in the coal consumption cost model of the coal-fired unit, the coal consumption cost is calculated by the following formula:

[0067] (1)

[0068] In the formula, - fuel cost; - coal price; - coal consumption in load interval i; - running time in load interval i;

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

[0070] (2)

[0071] In the formula, is the hydrogen sales revenue; is the hydrogen price; is the hydrogen production in load interval i; is the running time in load interval i.

[0072] The electricity sales revenue is calculated by the following formula:

[0073] (3)

[0074] wherein, the electricity sales revenue; the online electricity quantity in the load interval i; the online electricity price (yuan / kWh), which is valued according to the electricity price in the region.

[0075] The peak shaving subsidy revenue is calculated by the following formula:

[0076] (4)

[0077] wherein, the peak shaving revenue; the peak shaving subsidy price in the load interval i; the peak shaving capacity in the load interval i.

[0078] The constraint conditions that the coal-fired unit and the SOEC electrolysis system need to meet include:

[0079] The coal-fired unit output constraint and variable load speed:

[0080] (5)

[0081] (6)

[0082] wherein, the rated power of the coal-fired unit, MW; the output power of the coal-fired unit at t time, MW; the output power of the coal-fired unit at t-1 time, MW; and the upper and lower constraints of the climbing rate of the coal-fired unit when peak shaving.

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

[0084] (7)

[0085] (8)

[0086] wherein, the minimum power of the SOEC electrolysis system, MW; the rated power of the SOEC electrolysis system, MW; λ is the upper limit of the variable load rate; the power of the SOEC electrolysis system at t time, MW; the power of the SOEC electrolysis system at t-1 time, MW.

[0087] Grid power balance constraint:

[0088] (9)

[0089] where, is the grid on-grid power, MW.

[0090] Hydrogen mass balance constraint:

[0091] (10)

[0092] (11)

[0093] where, is the hydrogen production of load interval i; is the running time in load interval i; is the system hydrogen storage at t, kg; is the system hydrogen storage at t-1, kg; is the hydrogen production of SOEC electrolysis system at t, kg; is the hydrogen consumption for coal-fired unit stable combustion at t, kg; is the system hydrogen sales at t, kg.

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

[0095] (12)

[0096] where, X is the total revenue of coal-fired power plant-SOEC coupling system, C soec represents the initial investment cost of SOEC.

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

[0098] (13)

[0099] (14)

[0100] where, η is the efficiency of coal-fired power plant-SOEC coupling system, W ele is the on-grid power, W hyd is the energy of system output hydrogen, m H2 is the mass flow rate of output hydrogen, LHV H2 is the low heat value of hydrogen.

[0101] Further, the input parameters of the optimization operation method include:

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

[0103] Embodiment 2

[0104] The embodiment provides an improved scheme of a ratio and operation method of a coal-SOE coupled peak shaving system, replaces the SOEC in the embodiment 1 with a reversible solid oxide cell (RSOC), and the system adopts a unified energy management controller to realize collaborative power distribution of the coal-fired unit and the RSOC according to a grid dispatching instruction and a load prediction signal. When the grid is in a low load or a new energy output peak, the RSOC operates in a SOEC mode, hydrogen is prepared by electrolysis by using surplus power, and heat integration is performed by using waste heat of the coal-fired unit, so that the electrolysis efficiency is improved. When the grid load rises or a peak shaving instruction requires the unit to be quickly loaded, the RSOC is switched from the SOEC mode to a SOFC mode, hydrogen is stored as fuel to generate power and output power to the grid side, the rapid loading assistance is realized, and the control system realizes stable combustion priority of the coal-fired unit and rapid response priority of the SOFC through hierarchical control logic.

[0105] The embodiment significantly improves the loading rate of the system through SOFC discharge assistance, effectively improves the hysteresis problem of the traditional coal-fired unit in rapid peak shaving, absorbs hydrogen by electrolysis by using valley power of the grid in the SOEC mode, discharges in the SOFC mode at a peak, realizes bidirectional flow and time shift regulation of energy, widens the peak shaving capacity of the unit, and enhances the bidirectional peak shaving. Through periodic conversion of hydrogen energy storage and power generation, the system utilization rate and peak shaving income are improved, and the frequent start-stop cost is reduced. The fuel stable combustion demand and short-term emission peak are reduced during rapid loading, and the environmental protection performance of the unit operation is improved.

[0106] The technical scheme of the embodiment can further improve the overall loading rate and bidirectional peak shaving capacity of the system.

[0107] The above embodiments are only preferred embodiments of the present application, and the protection scope of the present application is not limited to the above embodiments. Any technical scheme falling within the concept of the present application belongs to the protection scope of the present application. It should be pointed out that, for ordinary skilled persons in the technical field, improvements and refinements without departing from the principles of the present application are also regarded as the protection scope of the present application.

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; generating a coupling between coal-fired units and solid oxide electrolysis. system The optimal capacity configuration and coordinated operation optimization scheme; 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.

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 RMB / kWh, which 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: The output constraints and variable load speeds of the coal-fired power units are as follows: （5） （6） 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; Output constraints and variable load speeds of the solid oxide electrolytic coupling system: （7） （8） In the formula, Minimum power of SOEC electrolysis system, 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. 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. 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; 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.

5. The method for optimizing the proportioning and operation according to claim 1, characterized in that, The overall revenue objective function of the coal-power-SOE ratio benefit model is: （12） 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; 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.

6. 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.

7. The method for optimizing the proportioning and operation of a coal-fired power-SOE coupled peak-shaving system according to claims 1-6, 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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