Power plant low-carbon optimization scheduling method, terminal equipment and storage medium

Abstract

The invention discloses a power plant low-carbon optimal scheduling method, terminal equipment and a storage medium, and the method is suitable for a coal-fired unit, a carbon capture subsystem, a methane reactor, an electrolytic cell, carbon storage equipment, hydrogen storage equipment, a hydrogen fuel cell and a comprehensive energy system capable of reducing load. Constructing a low-carbon economic dispatching model of the comprehensive energy system by taking the power balance constraint of the comprehensive energy system, the operation and climbing constraint of a coal-fired unit, the flue gas split ratio constraint of the carbon capture subsystem, the operation energy consumption constraint of the carbon capture subsystem and the constraint of hydrogen storage equipment as constraint conditions; solving the comprehensive energy system low-carbon economic dispatching model to obtain a target decision variable dispatching value; and scheduling the integrated energy system according to the target decision variable scheduling value. According to the invention, the emission of carbon dioxide is reduced, and energy conservation and emission reduction are realized; and hydrogen energy is introduced, so that low-carbon operation can be realized.

Description

Technical Field

[0001] The present invention relates to the technical field of integrated energy system optimization and scheduling, and in particular to a power plant low-carbon optimization and scheduling method, terminal equipment and storage medium. Background Art

[0002] With the worsening of greenhouse effect and energy depletion, energy conservation and emission reduction have become a consensus among all sectors of society. Among the carbon dioxide emissions generated by the global energy industry, the total carbon emissions generated by the power industry account for more than 40%. Therefore, low-carbon operation of the power industry is the key to reducing greenhouse gas emissions. How to achieve low-carbon operation of the power industry is an urgent problem to be solved. Summary of the invention

[0003] The present invention provides a low-carbon optimization scheduling method for a power plant, a terminal device and a storage medium to achieve low-carbon operation of the power industry and achieve the purpose of energy conservation and emission reduction.

[0004] In order to solve the above technical problems, the embodiment of the present invention provides a low-carbon optimization scheduling method for a power plant, which is applicable to an integrated energy system;

[0005] The integrated energy system includes: a coal-fired unit, a carbon capture subsystem, a methane reactor, an electrolyzer, a carbon storage device, a hydrogen storage device, a hydrogen fuel cell and a curtailable load;

[0006] The coal-fired unit is connected to the carbon capture subsystem; the carbon capture subsystem is respectively connected to the methane reactor and the carbon storage device; the electrolyzer is respectively connected to the methane reactor and the hydrogen storage device; the hydrogen storage device is connected to the hydrogen fuel cell; the hydrogen fuel cell is connected to the reducible load;

[0007] The carbon capture subsystem includes: a flue gas diversion device, an absorption tower and a regeneration tower;

[0008] The power plant low-carbon optimization scheduling method comprises:

[0009] Taking the minimum total system operation cost as the objective function, and taking the power balance constraint of the integrated energy system, the operation and ramping constraint of the coal-fired unit, the flue gas diversion ratio constraint of the carbon capture subsystem, the operation energy consumption constraint of the carbon capture subsystem and the hydrogen storage equipment constraint as the constraint conditions, a low-carbon economic dispatch model of the integrated energy system is constructed; wherein the total system operation cost is the sum of the coal cost, the gas purchase cost, the carbon dioxide capture and storage cost, the load demand response cost and the system equipment operation cost;

[0010] Selecting a target decision variable from a preset decision variable set, taking the target decision variable as a decision variable of the low-carbon economic dispatch model of the integrated energy system, solving the low-carbon economic dispatch model of the integrated energy system, and obtaining a dispatch value of the target decision variable; wherein the decision variable set includes: flue gas split ratio, carbon dioxide absorption efficiency of the absorption tower, carbon dioxide regeneration efficiency of the regeneration tower, methane reactor efficiency, and unit compensation cost of load that can be reduced;

[0011] The integrated energy system is scheduled according to the target decision variable scheduling value.

[0012] As a preferred solution, the operation mathematical model of the carbon capture subsystem is:

[0013] P G (t) = P CCPP (t)+P cap (t);

[0014] P cap (t) = P base +P ope (t);

[0015] P ope (t) = δQ re (t);

[0016] Q G (t) = εP G (t);

[0017] Q abo (t) = λ(t)ξ abo Q G (t);

[0018] Q cap (t) = ξ re Q re (t);

[0019] Where P G (t) represents the total power generation of coal-fired units during period t; P CCPP (t) represents the net output power of the carbon capture power plant during period t; P cap (t) represents the carbon capture energy consumption during period t; P base represents the fixed energy consumption of carbon capture; P ope (t) represents the energy consumption of carbon capture operation; Q re (t) represents the amount of carbon dioxide regeneration that needs to be processed by the regeneration tower during period t; δ represents the energy consumption coefficient of carbon capture operation; Q G (t) represents the total carbon dioxide generated by the coal-fired unit during period t; ε represents the carbon emission coefficient of the coal-fired unit; Q abo(t) represents the carbon dioxide absorption of the absorption tower during period t; λ(t) represents the flue gas diversion ratio during period t; ξ abo represents the carbon dioxide absorption efficiency of the absorption tower; ξ re Indicates the carbon dioxide regeneration efficiency of the regeneration tower; Q cap (t) represents the actual amount of carbon dioxide captured during period t;

[0020] The operation mathematical model of the electrolyzer is:

[0021] P out,e (t) = η ET P in,e (t);

[0022] Where P out,e (t) represents the output power of the electrolytic cell during period t; P in,e (t) represents the input power of the electrolytic cell during period t; η ET It represents the energy conversion efficiency of the electrolyzer;

[0023] The operation mathematical model of the methane reactor is:

[0024] P out,CH (t) = η CH P in,CH (t);

[0025] Where P out,CH (t) represents the output power of the methane reactor during period t; P in,CH (t) represents the input power of the methane reactor during period t; η CH represents the energy conversion efficiency of the methane reactor;

[0026] The operation mathematical model of the hydrogen fuel cell is:

[0027]

[0028] Where P out,H2 (t) represents the output power of the hydrogen fuel cell during period t; represents the input power of the hydrogen fuel cell during period t; Indicates the power generation efficiency of hydrogen fuel cells;

[0029] The operating mathematical model of the load reduction is:

[0030]

[0031] T j =[t j,start ,t j,end ];

[0032]

[0033] Where P t,j It indicates the jth type of load power that can be reduced during period t; represents the upper limit of load power that can be reduced in the jth time period t; μ t,j represents a binary state variable, a value of 1 indicates participation in demand response, and a value of 0 indicates non-participation in demand response; n t,j It represents the number of times the j-th type of curtailable load participates in demand response during period t; Indicates the upper limit of the number of participations; T j represents the jth type of load scheduling cycle that can be reduced; t j,start represents the start time of the jth type of load reduction scheduling cycle; t j,end represents the end time of the jth type of load reduction scheduling cycle; t j represents the single dispatching time of the jth type of load that can be reduced; Indicates the lower limit of a single scheduling duration; Indicates the upper limit of a single scheduling duration.

[0034] As a preferred solution, the expression of the objective function is:

[0035]

[0036] C dev =k G P G (t)+k Hys P Hys (t)+k P2G P out,e (t)+k ccs Q cap (t);

[0037] In the formula, C represents the total cost of system operation; C coal represents the cost of coal; C gas represents the gas purchase cost; represents the cost of carbon dioxide capture and storage; C DR represents the load demand response cost; C dev Indicates the operating cost of system equipment; k coal represents the unit power generation cost of coal-fired units; P G (t) represents the total power generation of the coal-fired unit in period t; T represents the total number of periods in a cycle; k gas P represents the unit gas purchase cost; buy,g (t) represents the gas volume required in period t; k cap represents the unit carbon capture cost; Q cap (t) represents the actual carbon dioxide capture in period t; k cs represents the unit carbon sequestration cost; QP2G (t) represents the amount of carbon dioxide required in the power-to-gas stage during period t; Indicates the density of carbon dioxide; P out,CH (t) represents the output power of the methane reactor during period t; k DR P represents the unit compensation cost of load reduction; t,j represents the jth type of load power that can be reduced in period t; J represents the total number of types of loads that can be reduced.

[0038] As a preferred solution, the expression of the power balance constraint of the integrated energy system is:

[0039]

[0040] P out,CH (t)+P buy,g (t) = P g,load (t);

[0041]

[0042] Where P G (t) represents the total power generation of coal-fired units during period t; represents the output power of the hydrogen fuel cell during period t; P in,e (t) represents the input power of the electrolytic cell during period t; P e,load (t) represents the actual power demand of the system during period t; P t,j represents the jth type of load power that can be reduced in time period t; J represents the total number of types of loads that can be reduced; P out,CH (t) represents the output power of the methane reactor during period t; P buy,g (t) represents the gas purchase volume required in period t; P g,load (t) represents the actual gas demand of the system; P out,e (t) represents the output power of the electrolyzer during period t; Indicates the hydrogen storage power of the hydrogen storage tank during period t; P represents the hydrogen release power of the hydrogen storage tank during period t; in,CH (t) represents the input power of the methane reactor during period t; Represents the input power of the hydrogen fuel cell during period t.

[0043] As a preferred solution, the expression of the operation and ramp constraints of the coal-fired unit is:

[0044]

[0045] Where P G (t) represents the total power generation of coal-fired units during period t; Indicates the lower limit of the total output of coal-fired units; Indicates the upper limit of the total output of coal-fired units; Indicates the lower limit of the ramp power of the coal-fired unit; Indicates the upper limit of the ramp power of the coal-fired unit

[0046] As a preferred solution, the expression for the flue gas split ratio constraint of the carbon capture subsystem is:

[0047] λ min ≤λ(t)≤λ max ;

[0048] Where, λ(t) represents the flue gas split ratio; λ min Indicates the lower limit of the smoke diversion ratio of the smoke diversion device; λ max Indicates the upper limit of the flue gas diversion ratio of the flue gas diversion device.

[0049] As a preferred solution, the expression of the energy consumption constraint of the carbon capture subsystem operation is:

[0050]

[0051] Where P cap (t) represents the carbon capture energy consumption during period t; represents the total output upper limit of the coal-fired unit; τ represents the maximum operating condition coefficient of the regeneration tower; δ represents the carbon capture operation energy consumption coefficient; ε represents the carbon emission coefficient of the coal-fired unit; ξ abo Indicates the carbon dioxide absorption efficiency of the absorption tower.

[0052] As a preferred solution, the expression of the hydrogen storage device constraint is:

[0053]

[0054] S H (0) = S H (T);

[0055] In the formula, S H (t) represents the storage capacity of the hydrogen storage equipment during time period t; represents the hydrogen storage power during period t; represents the hydrogen release power during period t; represents the hydrogen storage efficiency coefficient; represents the hydrogen release efficiency coefficient; represents a binary variable of charge state; represents a binary variable of release state; T represents the total number of time periods in a cycle.

[0056] Based on the above embodiments, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, the low-carbon optimization scheduling method for power plants described in the above invention embodiments is implemented.

[0057] Based on the above embodiments, another embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the low-carbon optimization scheduling method for power plants described in the above invention embodiments.

[0058] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0059] The present invention is applicable to an integrated energy system including a coal-fired unit, a carbon capture subsystem, a methane reactor, an electrolyzer, a carbon storage device, a hydrogen storage device, a hydrogen fuel cell and a load-reducible integrated energy system. The objective function is to minimize the total cost of system operation, and the power balance constraint of the integrated energy system, the operation and ramp constraint of the coal-fired unit, the flue gas diversion ratio constraint of the carbon capture subsystem, the energy consumption constraint of the carbon capture subsystem operation and the hydrogen storage device constraint are used as constraint conditions to construct a low-carbon economic dispatch model for the integrated energy system. The total cost of system operation is the coal cost, the gas purchase cost, the carbon dioxide capture and storage cost, the load The sum of the demand response cost and the system equipment operating cost; select the target decision variable from the preset decision variable set, use the target decision variable as the decision variable of the low-carbon economic dispatch model of the integrated energy system, solve the low-carbon economic dispatch model of the integrated energy system, and obtain the target decision variable dispatch value; wherein, the decision variable set includes: flue gas diversion ratio, carbon dioxide absorption efficiency of the absorption tower, carbon dioxide regeneration efficiency of the regeneration tower, methane reactor efficiency and unit compensation cost of the load that can be reduced; according to the target decision variable dispatch value, the integrated energy system is dispatched. The present invention is equipped with a carbon capture subsystem, which realizes the recycling of carbon dioxide, reduces the emission of carbon dioxide, and achieves energy conservation and emission reduction. In addition, the present invention introduces the use of hydrogen energy, reduces dependence on fossil fuels, improves the energy structure of the system, and helps to achieve low-carbon operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 It is a flow chart of a method for low-carbon optimization scheduling of a power plant provided by an embodiment of the present invention;

[0061] Figure 2 It is a schematic diagram of the framework of an integrated energy system;

[0062] Figure 3 It is a carbon capture subsystem operation structure diagram. DETAILED DESCRIPTION

[0063] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] Embodiment 1

[0065] Please refer to Figure 1 , is a flow chart of a low-carbon optimization scheduling method for a power plant provided by an embodiment of the present invention, comprising:

[0066] S1. Taking the minimum total system operation cost as the objective function, and taking the power balance constraint of the integrated energy system, the operation and ramping constraint of the coal-fired units, the flue gas diversion ratio constraint of the carbon capture subsystem, the operation energy consumption constraint of the carbon capture subsystem and the hydrogen storage equipment constraint as the constraint conditions, a low-carbon economic dispatch model of the integrated energy system is constructed; wherein the total system operation cost is the sum of the coal burning cost, the gas purchase cost, the carbon dioxide capture and storage cost, the load demand response cost and the system equipment operation cost.

[0067] S2. Select a target decision variable from a preset decision variable set, use the target decision variable as the decision variable of the low-carbon economic dispatch model of the integrated energy system, solve the low-carbon economic dispatch model of the integrated energy system, and obtain the dispatch value of the target decision variable; wherein the decision variable set includes: flue gas diversion ratio, carbon dioxide absorption efficiency of the absorption tower, carbon dioxide regeneration efficiency of the regeneration tower, methane reactor efficiency and unit compensation cost of reducible load.

[0068] S3. Scheduling the integrated energy system according to the target decision variable scheduling value.

[0069] The low-carbon optimization scheduling method for a power plant is applicable to an integrated energy system, which includes: a coal-fired unit, a carbon capture subsystem, a methane reactor, an electrolyzer, a carbon storage device, a hydrogen storage device, a hydrogen fuel cell, and a curtailable load;

[0070] The coal-fired unit is connected to the carbon capture subsystem; the carbon capture subsystem is respectively connected to the methane reactor and the carbon storage device; the electrolyzer is respectively connected to the methane reactor and the hydrogen storage device; the hydrogen storage device is connected to the hydrogen fuel cell; the hydrogen fuel cell is connected to the reducible load;

[0071] The carbon capture subsystem includes: a flue gas diversion device, an absorption tower and a regeneration tower.

[0072] It should be noted that if Figure 2 The figure shows a schematic diagram of the framework of an integrated energy system, including: a coal-fired unit, a carbon capture subsystem, a methane reactor, an electrolyzer, a hydrogen storage device and a hydrogen fuel cell.

[0073] In order to further achieve energy conservation and emission reduction, the present invention intends to introduce the use of hydrogen energy, including replacing traditional lithium-ion batteries with hydrogen fuel cells, and adding hydrogen storage tanks as the actual energy storage of the system. It provides additional clean energy for the system, reduces dependence on fossil fuels, improves the energy structure of the system, and helps to achieve low-carbon operation.

[0074] like Figure 3 The figure shows a structural diagram of the operation of a carbon capture subsystem. The flue gas is first passed into the absorption tower, where the carbon dioxide is absorbed by the solution, and the solution containing a large amount of carbon dioxide flows into the regeneration tower. The solution is heated in the regeneration tower to separate the carbon dioxide and the absorbent by heat. The separated carbon dioxide can be transported and sealed after compression, and the solution after the carbon dioxide is separated returns to the absorption tower for the next round of capture process. The flue gas diversion system is installed at the entrance of the absorption tower to control the ratio of the flue gas entering the absorption tower and the direct exhaust flue gas, thereby decoupling the power generation cycle of the carbon capture unit from the absorption link of the capture system.

[0075] The present invention adds a carbon capture unit after the generator set to transform it into a carbon capture power plant, and adds a flue gas diversion link to optimize the overall capture process.

[0076] In step S2, one or more decision variables are selected from the decision variable set as target decision variables. The flue gas split ratio is used to control the flue gas split device; the carbon dioxide absorption efficiency is used to control the absorption tower; the carbon dioxide regeneration efficiency is used to control the regeneration tower; the methane reactor efficiency refers to the energy conversion efficiency of the methane reactor, which is used to control the methane reactor; the unit compensation cost of the reducible load is used to use the price signal as an incentive signal to control the reducible load.

[0077] In step S3, common scheduling strategies are:

[0078] 1. If the operating cost of the carbon capture system is too high or the capture rate is too low, you can consider optimizing the flue gas split ratio or improving the efficiency of the absorption tower and regeneration tower;

[0079] 2. If the cost of purchasing gas or carbon sequestration is high, the demand for external gas can be reduced by improving the efficiency of power-to-gas or methane reactors;

[0080] 3. Adjust the price signal strength according to the power reduction of the load that can be reduced, further stimulate users to participate in demand response and smooth the system load.

[0081] In a preferred embodiment, the operation mathematical model of the carbon capture subsystem is:

[0082] P G (t) = P CCPP (t)+P cap (t);

[0083] P cap (t) = P base +P ope (t);

[0084] P ope (t) = δQ re (t);

[0085] Q G (t) = εP G (t);

[0086] Q abo (t) = λ(t)ξ abo Q G (t);

[0087] Q cap (t) = ξ re Q re (t);

[0088] Where P G (t) represents the total power generation of coal-fired units during period t; P CCPP (t) represents the net output power of the carbon capture power plant during period t; P cap (t) represents the carbon capture energy consumption during period t; P base represents the fixed energy consumption of carbon capture; P ope (t) represents the energy consumption of carbon capture operation; Q re (t) represents the amount of carbon dioxide regeneration that needs to be processed by the regeneration tower during period t; δ represents the energy consumption coefficient of carbon capture operation; Q G (t) represents the total carbon dioxide generated by the coal-fired unit during period t; ε represents the carbon emission coefficient of the coal-fired unit; Q abo (t) represents the carbon dioxide absorption of the absorption tower during period t; λ(t) represents the flue gas diversion ratio during period t; ξ abo represents the carbon dioxide absorption efficiency of the absorption tower; ξ re Indicates the carbon dioxide regeneration efficiency of the regeneration tower; Q cap (t) represents the actual amount of carbon dioxide captured during period t;

[0089] The operation mathematical model of the electrolyzer is:

[0090] P out,e (t) = η ET P in,e (t);

[0091] Where P out,e(t) represents the output power of the electrolytic cell during period t; P in,e (t) represents the input power of the electrolytic cell during period t; η ET It represents the energy conversion efficiency of the electrolyzer;

[0092] The operation mathematical model of the methane reactor is:

[0093] P out,CH (t) = η CH P in,CH (t);

[0094] Where P out,CH (t) represents the output power of the methane reactor during period t; P in,CH (t) represents the input power of the methane reactor during period t; η CH represents the energy conversion efficiency of the methane reactor;

[0095] The operation mathematical model of the hydrogen fuel cell is:

[0096]

[0097] In the formula, represents the output power of the hydrogen fuel cell during period t; represents the input power of the hydrogen fuel cell during period t; Indicates the power generation efficiency of hydrogen fuel cells;

[0098] The operating mathematical model of the load reduction is:

[0099]

[0100] T j =[t j,start ,t j,end ];

[0101]

[0102] Where P t,j It indicates the jth type of load power that can be reduced during period t; represents the upper limit of load power that can be reduced in the jth time period t; μ t,j represents a binary state variable, a value of 1 indicates participation in demand response, and a value of 0 indicates non-participation in demand response; n t,j It represents the number of times the j-th type of curtailable load participates in demand response during period t; Indicates the upper limit of the number of participations; T j represents the jth type of load scheduling cycle that can be reduced; t j,start represents the start time of the jth type of load reduction scheduling cycle; t j,end represents the end time of the jth type of load reduction scheduling cycle; tj represents the single dispatching time of the jth type of load that can be reduced; Indicates the lower limit of a single scheduling duration; Indicates the upper limit of a single scheduling duration.

[0103] It should be noted that the carbon dioxide captured by the carbon capture equipment can be used as the raw material for the methane reactor part of the power-to-gas scheme.

[0104] Power-to-gas is divided into two stages: electrolyzer and methane reactor. The electrolyzer produces hydrogen, part of which enters the hydrogen storage tank for storage, and part of which enters the methane reactor for gas production.

[0105] Hydrogen fuel cells can burn hydrogen as fuel to generate electricity, which can reduce peak power consumption and fill valleys during peak electricity consumption periods, alleviating the pressure on power supply in the power grid.

[0106] On the load side, the main consideration is to use curtailable loads with huge regulation capacity and demand response potential as virtual energy storage to participate in system operation.

[0107] In a preferred embodiment, the objective function is expressed as:

[0108]

[0109] C dev =k G P G (t)+k Hys P Hys (t)+k P2G P out,e (t)+k ccs Q cap (t);

[0110] In the formula, C represents the total cost of system operation; C coal represents the cost of coal; C gas represents the gas purchase cost; represents the cost of carbon dioxide capture and storage; C DR represents the load demand response cost; C dev Indicates the operating cost of system equipment; k coal represents the unit power generation cost of coal-fired units; P G (t) represents the total power generation of the coal-fired unit in period t; T represents the total number of periods in a cycle; k gas P represents the unit gas purchase cost; buy,g (t) represents the gas volume required in period t; k cap represents the unit carbon capture cost; Q cap (t) represents the actual carbon dioxide capture in period t; k cs represents the unit carbon sequestration cost; Q P2G(t) represents the amount of carbon dioxide required in the power-to-gas stage during period t; Indicates the density of carbon dioxide; P out,CH (t) represents the output power of the methane reactor during period t; k DR P represents the unit compensation cost of load reduction; t,j represents the jth type of load power that can be reduced in period t; J represents the total number of types of loads that can be reduced.

[0111] It should be noted that the system's gas demand is first provided by power-to-gas conversion, and when the system supply is insufficient, it is purchased from the outside.

[0112] After the system completes the entire carbon capture process, it also needs to be stored. Part of the carbon dioxide produced by the system is used to generate methane, and the rest is stored, which can reduce the system's gas purchase cost and carbon storage cost. According to the chemical formula of the methane reactor, ideally, the volume of carbon dioxide consumed is equal to the volume of methane generated.

[0113] The system equipment operating costs are composed of the operating costs of coal-fired units, power-to-gas (P2G) equipment, carbon capture and storage equipment, hydrogen storage tanks and other equipment.

[0114] In a preferred embodiment, the expression of the power balance constraint of the integrated energy system is:

[0115]

[0116] P out,CH (t)+P buy,g (t) = P g,load (t);

[0117]

[0118] Where P G (t) represents the total power generation of coal-fired units during period t; represents the output power of the hydrogen fuel cell during period t; P in,e (t) represents the input power of the electrolytic cell during period t; P e,load (t) represents the actual power demand of the system during period t; P t,j represents the jth type of load power that can be reduced in time period t; J represents the total number of types of loads that can be reduced; P out,CH (t) represents the output power of the methane reactor during period t; P buy,g (t) represents the gas purchase volume required in period t; P g,load (t) represents the actual gas demand of the system; P out,e (t) represents the output power of the electrolyzer during period t; Indicates the hydrogen storage power of the hydrogen storage tank during period t; P represents the hydrogen release power of the hydrogen storage tank during period t; in,CH (t) represents the input power of the methane reactor during period t; Represents the input power of the hydrogen fuel cell during period t.

[0119] In a preferred embodiment, the expression of the operation and ramp constraints of the coal-fired unit is:

[0120]

[0121] Where P G (t) represents the total power generation of coal-fired units during period t; Indicates the lower limit of the total output of coal-fired units; Indicates the upper limit of the total output of coal-fired units; Indicates the lower limit of the ramp power of the coal-fired unit; Indicates the upper limit of the ramp power of the coal-fired unit.

[0122] In a preferred embodiment, the expression for the flue gas split ratio constraint of the carbon capture subsystem is:

[0123] λ min ≤λ(t)≤λ max ;

[0124] Where, λ(t) represents the flue gas split ratio; λ min Indicates the lower limit of the smoke diversion ratio of the smoke diversion device; λ max Indicates the upper limit of the flue gas diversion ratio of the flue gas diversion device.

[0125] In a preferred embodiment, the expression of the energy consumption constraint of the carbon capture subsystem operation is:

[0126]

[0127] Where P cap (t) represents the carbon capture energy consumption during period t; represents the total output upper limit of the coal-fired unit; τ represents the maximum operating condition coefficient of the regeneration tower; δ represents the carbon capture operation energy consumption coefficient; ε represents the carbon emission coefficient of the coal-fired unit; ξ abo Indicates the carbon dioxide absorption efficiency of the absorption tower.

[0128] It should be noted that the operating conditions of the carbon capture subsystem are subject to the maximum operating conditions of the regeneration tower and the compressor, so the maximum operating energy consumption does not exceed the operating energy consumption when the power plant is at full output.

[0129] In a preferred embodiment, the expression of the hydrogen storage device constraint is:

[0130]

[0131] S H (0) = S H (T);

[0132] In the formula, S H (t) represents the storage capacity of the hydrogen storage equipment during time period t; represents the hydrogen storage power during period t; represents the hydrogen release power during period t; represents the hydrogen storage efficiency coefficient; represents the hydrogen release efficiency coefficient; represents a binary variable of charge state; represents a binary variable of release state; T represents the total number of time periods in a cycle.

[0133] It should be noted that the model of the hydrogen storage tank needs to consider storage capacity constraints, single hydrogen storage / release constraints, storage and release state complementarity constraints, and periodic reserve conservation constraints.

[0134] S H (0) = S H (T) means that the storage capacity of the hydrogen storage tank at the beginning and end of a cycle is the same, that is, the cycle reserve is conserved.

[0135] The present invention fully considers the combination of hydrogen energy, a clean secondary energy source, and traditional power generation. The introduction of hydrogen energy provides additional clean energy for the system, reduces dependence on fossil fuels, improves the energy structure of the system, and helps to achieve low-carbon operation; the storage and release functions of hydrogen energy can optimize energy supply during peak load periods, reduce the cost of purchasing electricity and gas, and reduce system operating costs. The present invention also fully considers the load-side demand-side response, and uses price signals as incentive signals to encourage users to adjust the load as much as possible to achieve decarbonization. This dynamic adjustment not only helps to optimize the energy mix of the supplier, so that more renewable energy can be effectively utilized, but also balances the supply and demand relationship of the power system. Ultimately, this will lead to a significant reduction in carbon emissions and promote the development of energy systems in a more sustainable and environmentally friendly direction.

[0136] Embodiment 2

[0137] Accordingly, an embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, the low-carbon optimization scheduling method for power plants described in the above-mentioned embodiment of the invention is implemented.

[0138] Embodiment 3

[0139] Accordingly, an embodiment of the present invention provides a storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the power plant low-carbon optimization scheduling method described in the above-mentioned embodiment of the invention.

[0140] It should be noted that the terminal device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0141] The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the device, and various interfaces and lines are used to connect various parts of the entire device.

[0142] The memory can be used to store the computer program, and the processor realizes various functions of the device by running or executing the computer program stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0143] The storage medium is a storage medium, and the computer program is stored in the storage medium. When the computer program is executed by the processor, the steps of each method embodiment described above can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer readable media do not include electric carrier signals and telecommunication signals.

[0144] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A low-carbon optimization scheduling method for a power plant, characterized in that: Applicable to integrated energy systems; The integrated energy system includes: a coal-fired unit, a carbon capture subsystem, a methane reactor, an electrolyzer, a carbon storage device, a hydrogen storage device, a hydrogen fuel cell and a curtailable load; The coal-fired unit is connected to the carbon capture subsystem; the carbon capture subsystem is respectively connected to the methane reactor and the carbon storage device; the electrolyzer is respectively connected to the methane reactor and the hydrogen storage device; the hydrogen storage device is connected to the hydrogen fuel cell; the hydrogen fuel cell is connected to the reducible load; The carbon capture subsystem includes: a flue gas diversion device, an absorption tower and a regeneration tower; The power plant low-carbon optimization scheduling method comprises: Taking the minimum total system operation cost as the objective function, and taking the power balance constraint of the integrated energy system, the operation and ramping constraint of the coal-fired unit, the flue gas diversion ratio constraint of the carbon capture subsystem, the operation energy consumption constraint of the carbon capture subsystem and the hydrogen storage equipment constraint as the constraint conditions, a low-carbon economic dispatch model of the integrated energy system is constructed; wherein the total system operation cost is the sum of the coal cost, the gas purchase cost, the carbon dioxide capture and storage cost, the load demand response cost and the system equipment operation cost; Selecting a target decision variable from a preset decision variable set, taking the target decision variable as a decision variable of the low-carbon economic dispatch model of the integrated energy system, solving the low-carbon economic dispatch model of the integrated energy system, and obtaining a dispatch value of the target decision variable; wherein the decision variable set includes: flue gas split ratio, carbon dioxide absorption efficiency of the absorption tower, carbon dioxide regeneration efficiency of the regeneration tower, methane reactor efficiency, and unit compensation cost of load that can be reduced; The integrated energy system is scheduled according to the target decision variable scheduling value.

2. The low-carbon optimization scheduling method for a power plant according to claim 1, characterized in that: The operation mathematical model of the carbon capture subsystem is: P G (t)=P CCPP (t)+P cap (t); P cap (t)=P base +P ope (t); P ope (t)=δQ re (t); Q G (t)=εP G (t); Q abo (t)=λ(t)ξ abo Q G (t); Q cap (t)=ξ re Q re (t); Where P G (t) represents the total power generation of coal-fired units during period t; P CCPP (t) represents the net output power of the carbon capture power plant during period t; P cap (t) represents the carbon capture energy consumption during period t; P base represents the fixed energy consumption of carbon capture; P ope (t) represents the energy consumption of carbon capture operation; Q re (t) represents the amount of carbon dioxide regeneration that needs to be processed by the regeneration tower during period t; δ represents the energy consumption coefficient of carbon capture operation; Q G (t) represents the total carbon dioxide generated by the coal-fired unit during period t; v represents the carbon emission coefficient of the coal-fired unit; Q abo (t) represents the carbon dioxide absorption of the absorption tower during period t; λ(t) represents the flue gas diversion ratio during period t; ξ abo represents the carbon dioxide absorption efficiency of the absorption tower; ξ re Indicates the carbon dioxide regeneration efficiency of the regeneration tower; Q cap (t) represents the actual amount of carbon dioxide captured during period t; The operation mathematical model of the electrolyzer is: P out,e (t)=η ET P in,e (t); Where P out,e (t) represents the output power of the electrolytic cell during period t; P in,e (t) represents the input power of the electrolytic cell during period t; η ET It represents the energy conversion efficiency of the electrolyzer; The operation mathematical model of the methane reactor is: P out,CH (t)=η CH P in,CH (t); Where P out,CH (t) represents the output power of the methane reactor during period t; P in,CH (t) represents the input power of the methane reactor during period t; η CH represents the energy conversion efficiency of the methane reactor; The operation mathematical model of the hydrogen fuel cell is: In the formula, represents the output power of the hydrogen fuel cell during period t; represents the input power of the hydrogen fuel cell during period t; Indicates the power generation efficiency of hydrogen fuel cells; The operating mathematical model of the load reduction is: T j =[t j,start ,t j,end ]; Where P t,j It indicates the jth type of load power that can be reduced during period t; represents the upper limit of load power that can be reduced in the jth time period t; μ t,j represents a binary state variable, a value of 1 indicates participation in demand response, and a value of 0 indicates non-participation in demand response; n t,j It represents the number of times the j-th type of curtailable load participates in demand response during period t; Indicates the upper limit of the number of participations; T j represents the jth type of load scheduling cycle that can be reduced; t j,start represents the start time of the jth type of load reduction scheduling cycle; t j,end represents the end time of the jth type of load reduction scheduling cycle; t j represents the single dispatching time of the jth type of load that can be reduced; Indicates the lower limit of a single scheduling duration; Indicates the upper limit of a single scheduling duration.

3. The low-carbon optimization scheduling method for a power plant according to claim 1, characterized in that: The expression of the objective function is: C dev =k G P G (t)+k Hys P Hys (t)+k P2G P out,e (t)+k ccs Q cap (t); In the formula, C represents the total cost of system operation; C coal represents the cost of coal; C gas represents the gas purchase cost; represents the cost of carbon dioxide capture and storage; C DR represents the load demand response cost; C dev Indicates the operating cost of system equipment; k coal represents the unit power generation cost of coal-fired units; P G (t) represents the total power generation of the coal-fired unit in period t; T represents the total number of periods in a cycle; k gas Indicates the unit gas purchase cost; P buy,g (t) represents the gas volume required in period t; k cap represents the unit carbon capture cost; Q cap (t) represents the actual carbon dioxide capture in period t; k cs represents the unit carbon sequestration cost; Q P2G (t) represents the amount of carbon dioxide required for the power-to-gas conversion stage during period t; ρ CO2 Indicates the density of carbon dioxide; P out,CH (t) represents the output power of the methane reactor during period t; k DR P represents the unit compensation cost of load reduction; t,j represents the jth type of load power that can be reduced in period t; J represents the total number of types of loads that can be reduced.

4. The low-carbon optimization scheduling method for a power plant according to claim 1, characterized in that: The expression of the power balance constraint of the integrated energy system is: P out,CH (t)+P buy,g (t)=P g,load (t); Where P G (t) represents the total power generation of coal-fired units during period t; represents the output power of the hydrogen fuel cell during period t; P in,e (t) represents the input power of the electrolytic cell during period t; P e,load (t) represents the actual power demand of the system during period t; P t,j represents the jth type of load power that can be reduced in time period t; J represents the total number of types of loads that can be reduced; P out,CH (t) represents the output power of the methane reactor during period t; P buy,g (t) represents the gas purchase volume required in period t; P g,load (t) represents the actual gas demand of the system; P out,e (t) represents the output power of the electrolyzer during period t; Indicates the hydrogen storage power of the hydrogen storage tank during period t; P represents the hydrogen release power of the hydrogen storage tank during period t; in,CH (t) represents the input power of the methane reactor during period t; Represents the input power of the hydrogen fuel cell during period t.

5. The low-carbon optimization scheduling method for a power plant according to claim 1, characterized in that: The expression of the operation and ramp constraints of the coal-fired unit is: Where P G (t) represents the total power generation of coal-fired units during period t; Indicates the lower limit of the total output of coal-fired units; Indicates the upper limit of the total output of coal-fired units; Indicates the lower limit of the ramp power of the coal-fired unit; Indicates the upper limit of the ramp power of the coal-fired unit.

6. The low-carbon optimization scheduling method for a power plant according to claim 1, characterized in that: The expression of the flue gas split ratio constraint of the carbon capture subsystem is: l min ≤λ(t)≤λ max ; In the formula, λ(t) represents the flue gas split ratio; λ min Indicates the lower limit of the flue gas diversion ratio of the flue gas diversion device; λ max Indicates the upper limit of the flue gas diversion ratio of the flue gas diversion device.

7. The low-carbon optimization scheduling method for a power plant according to claim 1, characterized in that: The expression of the energy consumption constraint of the carbon capture subsystem operation is: Where P cap (t) represents the carbon capture energy consumption during period t; represents the total output upper limit of the coal-fired unit; τ represents the maximum operating condition coefficient of the regeneration tower; δ represents the carbon capture operation energy consumption coefficient; ε represents the carbon emission coefficient of the coal-fired unit; ξ abo Indicates the carbon dioxide absorption efficiency of the absorption tower.

8. The low-carbon optimization scheduling method for a power plant according to claim 1, characterized in that: The expression of the hydrogen storage device constraint is: S H (0)=S H (T); In the formula, S H (t) represents the storage capacity of the hydrogen storage equipment during time period t; represents the hydrogen storage power during period t; represents the hydrogen release power during period t; represents the hydrogen storage efficiency coefficient; represents the hydrogen release efficiency coefficient; represents a binary variable of charge state; represents a binary variable of release state; T represents the total number of time periods in a cycle.

9. A terminal device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the method for low-carbon optimization scheduling of a power plant as described in any one of claims 1 to 8 is implemented.

10. A storage medium, characterized in that: The storage medium includes a stored computer program, wherein when the computer program is running, the device where the storage medium is located is controlled to execute the power plant low-carbon optimization scheduling method according to any one of claims 1 to 8.

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