New energy-containing power grid low-carbon scheduling method involving flexible operation carbon capture

Abstract

A new energy-containing power grid low-carbon scheduling method related to flexible operation carbon capture comprises the following steps: step 1, based on a post-combustion carbon capture technology, a liquid storage tank is additionally arranged in a carbon capture system to form a comprehensive flexible operation carbon capture equipment model; 2, proposing a carbon transaction mechanism based on a datum line method; 3, a pumped storage unit model and a wind turbine generator unit model are introduced, unit output conditions serve as decision variables, power generation side economic benefit optimization serves as a target, unit operation constraints and system safety constraints are considered, and a low-carbon dispatching model of wind power-pumped storage-carbon capture combined operation considering carbon transaction is constructed; the method is used for solving the problems that when a carbon capture unit runs, spinning reserve is insufficient in the load peak period, the running efficiency of the unit is reduced due to frequent climbing, and a system cannot concentrate on carbon capture work. And after the carbon capture equipment is introduced, the problem of how to consider the economical efficiency and the environmental protection property of a power system under the working condition of keeping relatively high carbon capture energy consumption needs to be solved urgently.

Description

Technical Field

[0001] The present invention relates to a low-carbon dispatching method for a new energy-containing power grid involving flexible operation of carbon capture. Background Art

[0002] Pumped storage power stations can effectively participate in system peak regulation due to their large capacity, mature technology, and rapid start and stop. Introducing pumped storage units on the power supply side to assist carbon capture units in participating in peak regulation can control the coal consumption cost of carbon capture units on the basis of improving the level of wind power consumption, thereby reducing CO2 emissions from the source.

[0003] Research based on carbon capture technology, such as "Multi-time scale dispatch strategy for wind power abandonment considering energy transfer characteristics of carbon capture power plants", studied the inhibitory effect of split-flow carbon capture units on wind power uncertainty at different time scales, but split-flow carbon capture power plants cannot time-shift carbon capture energy consumption, and the units still face great peak-shaving pressure during peak load periods. "Low-carbon economic dispatch considering comprehensive flexible operation of carbon capture power plants". Peaking is achieved by using comprehensive and flexible carbon capture units, which achieves time-shifting of energy consumption. However, during peak load periods, carbon capture needs to increase net output to meet load demand. During this period, the carbon capture operation power is limited and more CO2 cannot be captured, which is not friendly to the system environment. Summary of the invention

[0004] The purpose of the present invention is to provide a low-carbon scheduling method for a new energy power grid involving flexible carbon capture operation, which is used to solve the problems of insufficient rotating reserve during peak load periods when the carbon capture unit is running, frequent ramping that reduces the operating efficiency of the unit, and the system being unable to focus on carbon capture work. In addition, the problem of how to balance the economy and environmental protection of the power system while maintaining a high carbon capture energy consumption after the introduction of carbon capture equipment needs to be solved.

[0005] In order to solve the above problems, the technical solution of the present invention is:

[0006] A low-carbon dispatching method for a new energy grid involving flexible operation of carbon capture comprises the following steps:

[0007] Step 1: Based on post-combustion carbon capture technology, a liquid storage tank is added to the carbon capture system to form a comprehensive and flexible operation carbon capture equipment model;

[0008] Step 2: Propose a carbon trading mechanism based on the baseline method;

[0009] Step 3: Introduce pumped storage units and wind turbine models, take unit output as the decision variable, optimize the economic benefits of the power generation side as the goal, consider unit operation constraints and system safety constraints, and build a low-carbon dispatch model for wind power-pumped storage-carbon capture combined operation that considers carbon trading;

[0010] Step 4: Replace wind power output and load with trapezoidal fuzzy parameters, and multiply the predicted values ​​of wind power and load by the proportional coefficient to express their respective fuzzy parameters;

[0011] Step 5: Convert the original power balance constraints and reserve capacity constraints into fuzzy chance constraints, set the confidence level, convert the fuzzy chance constraints into clear equivalence classes, and convert the model into mixed integer programming for easy solution;

[0012] Step 6: Use the CPLEX solver to solve the optimal output plan for this low-carbon dispatch.

[0013] The beneficial effects of the present invention are:

[0014] 1) The present invention constructs a comprehensive and flexible operation carbon capture working mechanism. Compared with traditional post-combustion carbon capture technology, the comprehensive and flexible operation carbon capture technology can achieve partial decoupling of carbon capture and power generation, realize the time shift of wind power energy consumption, and the time shift feature of energy consumption can greatly alleviate the peak load reduction and standby pressure of the unit, and has better low-carbon benefits.

[0015] 2) The method article of the present invention constructs a low-carbon power dispatch model of wind power-pumped storage-carbon capture units taking into account carbon trading, explores the joint operation mechanism of carbon capture units and pumped storage units, and fuzzy processes wind power output and load. This method is compared with the traditional thermal power-wind power dispatch strategy and the carbon capture-wind power dispatch strategy, and it is concluded that the wind power-carbon capture-pumped storage jointly operated power generation system obtains better economic and environmental benefits than the other two scenarios with the support of the carbon trading mechanism. Compared with the carbon capture-wind power dispatch strategy, the carbon capture unit of this method can focus more on carbon capture. In one dispatch cycle, the net income is increased by 7.62% and the carbon emissions are reduced by 7.01%.

[0016] 3) The present invention uses fuzzy parameters to handle the uncertainty of wind power and load, and uses clear equivalence classes to transform the model, which can cope with the situation where a high proportion of new energy power plants are connected. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention will be further described below in conjunction with the accompanying drawings:

[0018] Figure 1 It is a flow chart of the low-carbon dispatch strategy method for a new energy power grid taking into account the flexible operation of carbon capture according to the present invention.

[0019] Figure 2 It is a schematic diagram of the structure of the carbon capture system of the present invention.

[0020] Figure 3 This is the IEEE-30 system node diagram of the present invention. DETAILED DESCRIPTION

[0021] 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.

[0022] like Figures 1 to 3 As shown, a low-carbon dispatching method for a new energy grid involving flexible operation of carbon capture is characterized by comprising the following steps:

[0023] Step 1: Based on post-combustion carbon capture technology, a liquid storage tank is added to the carbon capture system to form a comprehensive and flexible operation carbon capture equipment model;

[0024] Step 2: Propose a carbon trading mechanism based on the baseline method;

[0025] Step 3: Introduce pumped storage units and wind turbine models, take unit output as the decision variable, optimize the economic benefits of the power generation side as the goal, consider unit operation constraints and system safety constraints, and build a low-carbon dispatch model for wind power-pumped storage-carbon capture combined operation that considers carbon trading;

[0026] Step 4: Replace wind power output and load with trapezoidal fuzzy parameters, and multiply the predicted values ​​of wind power and load by the proportional coefficient to express their respective fuzzy parameters;

[0027] Step 5: Convert the original power balance constraints and reserve capacity constraints into fuzzy chance constraints, set the confidence level, convert the fuzzy chance constraints into clear equivalence classes, and convert the model into mixed integer programming for easy solution;

[0028] Step 6: Use the CPLEX solver to solve the optimal output plan for this low-carbon dispatch.

[0029] The carbon capture system of the present invention uses post-combustion carbon capture technology. The post-combustion carbon capture unit is composed of a conventional thermal power unit and a carbon capture device. Its working process includes three links: absorption, regeneration, and compression. The main energy consumption of the carbon capture system is used in the regeneration and compression links. The comprehensive flexible operation carbon capture technology is to add a liquid storage tank on the basis of the post-combustion carbon capture technology to enable it to flexibly adjust the carbon capture power.

[0030] The carbon capture system includes an absorption tower, the lower end of which is connected to a rich liquid storage tank, a heat exchanger tube side and a regeneration tower feed port in sequence through a pipeline, the upper end of which is connected to a lean liquid storage tank, a heat exchanger shell side, a reboiler and the lower end of the regeneration tower in sequence, the top of the absorption tower is connected to an exhaust pipe, the lower end of the absorption tower is connected to a flue gas inlet pipe, and the top of the absorption tower is connected to a compressor through a carbon exhaust pipe.

[0031] The working process of the carbon capture system is as follows: the flue gas containing CO2 enters the absorption tower from the bottom of the tower, the lean liquid absorbs CO2 and converts it into rich liquid and stores it in the rich liquid storage tank. At this time, the storage tank is equivalent to an energy storage device. The system adjusts the inflow and outflow of the rich liquid storage tank according to the load conditions to control the amount of CO2 being processed by the regeneration tower and the compressor, thereby changing the net output power of the carbon capture unit. The rich liquid containing a large amount of CO2 enters the regeneration tower through the heat exchanger and is heated. After heating, the solution is separated from the CO2. Finally, the separated CO2 is compressed by the compressor for transportation and storage, and the lean liquid after the CO2 is separated returns to the absorption tower for the next stage of capture.

[0032] In step 2, the method for establishing a carbon trading mechanism includes the following steps:

[0033] Step 2.1: Establish the power relationship expression of the carbon capture unit:

[0034] P GN,i,t =P G,i,t -P GC,i,t (1);

[0035] P GC,i,t =P B,i +P op,i,t (2);

[0036] Where: P G,i,t , P GN,i,t is the total power generation output and net power generation output of carbon capture unit i during period t; P GC,i,t is the capture power of the carbon capture unit, which is determined by the unit's operating power P op,i,t and fixed power P B,i constitute.

[0037] Step 2.2: Adding a liquid storage tank based on post-combustion carbon capture technology:

[0038] P op,i,t =m c E deal,i,t (3);

[0039] E deal,i,t =E GC,i,t +βδE G,i,t (4);

[0040] E G,i,t =e i P G,i,t (5);

[0041] Where: m cis the operating energy consumption for processing unit mass of CO2; β is the flue gas diversion ratio of the unit, which indicates the proportion of flue gas generated by the thermal power unit flowing into the carbon capture equipment; E G,i,t E is the CO2 production of the unit; GC,i,t is the amount of CO2 supplied from the liquid storage tank to the regeneration tower; δ is the CO2 capture rate; e i is the carbon emission intensity per unit electricity of thermal power unit i.

[0042] From the above formula, the net output power of the carbon capture unit can be deduced as:

[0043] P GN,i,t =(1-m c βδe i ) G,i,t -P B,i -m c E GC,i,t (6);

[0044] From formula (6), we can know that after adding the liquid storage tank, the net output power of the carbon capture unit is related to the amount of CO2 provided by the liquid storage tank to the regeneration tower. Changing the amount of CO2 provided by the liquid storage tank can optimize the operating energy consumption and net output of the carbon capture unit. Since the regeneration tower of the carbon capture system has a maximum operating state constraint, there is an upper limit to the amount of CO2 processed in the tower. The constraint on the amount of CO2 that can be provided by the rich liquid storage tank can be further deduced:

[0045] -βδe i P G,i,t ≤E GC,i,t ≤ηδe i P G,i,max -βδe i P G,i,t (7);

[0046] Where: η is the maximum working state coefficient of the regeneration tower, P G,i,max The maximum power of the unit

[0047] Step 2.3: Construct a carbon trading mechanism model:

[0048] First, the net CO2 emissions of the carbon capture unit are derived from step 2.2:

[0049]

[0050] Where: N G is the number of thermal power units; T is the total number of time periods in a day.

[0051] After the thermal power plant introduces carbon capture equipment, CO2 emissions will be reduced. After taking the carbon trading mechanism into consideration for low-carbon power dispatch, the power plant can sell its remaining carbon emission quota to increase its own revenue. The CO2 emissions of the present invention all come from thermal power units. The principle of allocating carbon emission quotas for traditional thermal power units is mainly free allocation and supplemented by paid allocation. There are two methods for calculating the carbon emission quotas allocated free of charge for thermal power units: the historical method and the baseline method. The present invention adopts the baseline method. The carbon emission quota and carbon trading income of the system are:

[0052]

[0053] F trade =σ(E D -E dis ) (10);

[0054] Where: E D is the carbon emission quota allocated to the carbon capture unit; λ is the carbon emission quota per unit power of the carbon capture unit; F trade is the carbon trading income; σ is the carbon trading price.

[0055] This formula means that within the specified period, if the carbon emissions of the carbon capture power plant are less than the carbon quota, the remaining carbon quota can be traded to obtain income; if the carbon emissions of the carbon capture power plant are greater than the carbon quota, additional carbon emission quotas must be purchased.

[0056] Due to the anti-peaking characteristics of wind power, a certain amount of wind curtailment will be generated during the low-load period to ensure the safe operation of the system. However, during the peak load period, the wind power output is insufficient. In order to make up for the power shortage, the carbon capture unit needs to increase the net output to meet the power balance; the carbon capture unit faces a large upward rotation standby pressure. During this period, the unit's carbon capture energy consumption is limited and it cannot completely capture the large amount of CO2 it produces, and the system is less environmentally friendly. Because the pumped storage unit has the characteristics of large capacity and rapid start and stop, the introduction of the pumped storage unit can weaken the anti-peaking characteristics of wind power. During the low-load period, the pumped storage is in the pumping condition to absorb the wind curtailment. During the peak load period, the pumped storage generates electricity to share the peaking pressure of the carbon capture unit. The carbon capture unit can have more energy consumption margin for carbon capture work and reduce its own CO2 emissions; the introduction of pumped storage can also shift the output of wind turbines in time, increase the proportion of clean energy on the grid, and take into account both environmental and economic benefits.

[0057] The present invention establishes a low-carbon dispatch model for wind power-carbon capture-pumped storage combined operation considering the carbon trading mechanism, taking the maximum net system benefit as the objective function, and comprehensively considering the fuel cost, start-stop cost, wind power operation cost, grid-connected income of each unit, pumped storage income and carbon trading income of the carbon capture unit. The constraints include system constraints (standby constraints, power balance constraints), unit constraints (operating characteristics, output upper and lower limits, flue gas diversion ratio constraints, liquid storage tank capacity constraints), pumped storage capacity constraints and network transmission constraints.

[0058] In step 3, the unit output is used as the decision variable, the optimal economic benefit of the power generation side is the goal, and the maximum net profit of the system is used as the objective function. The objective function is:

[0059]

[0060] Where: F is the net income of the system; F S,t is the income from carbon capture units and wind turbines during period t; F H,t F is the benefit of calling the pumped storage unit during period t; C,t is the unit operating cost during period t (including the fuel cost, start-up and shutdown cost of the carbon capture unit and the wind power operation and maintenance cost); F trade It is the carbon trading income of the system after the introduction of the carbon trading mechanism.

[0061] 1) Wind power-carbon capture unit grid connection income

[0062]

[0063] Where: K t is the grid-connected electricity price of the unit; P w,t is the wind power in period t; ΔT is the scheduling time interval.

[0064] 2) Benefits of using pumped storage units

[0065] The benefit of using pumped storage is the difference between the power benefit of pumped storage and the start-stop loss cost:

[0066] F H,t =G h,t -S h,t (13);

[0067] G h,t =K hg P hg,t ΔT-K hp P hp ΔT (14);

[0068] S h,t =[y g,t (1-y g,t-1 )+y p,t (1-yp,t-1 )]C h +[y g,t-1 (1-y g,t )+y p,t-1 (1-y p,t )]C h (15);

[0069] Where: G h,t is the power efficiency of the pumped storage unit; S h,t is the start-stop loss cost of the pumped storage unit; P hg,t is the power generation capacity of the pumped storage unit; P hp is the pumping power of the pumped storage unit; K hg is the on-grid electricity price of the pumped storage unit; K hp is the pumped electricity price of the pumped storage unit; g,t ,y p,t Boolean variables representing whether the unit is in power generation or pumping operation; C h It is the cost of starting and stopping the pumped storage unit once.

[0070] 3) Unit operating costs

[0071] The unit operating cost is composed of the carbon capture unit operating cost S G,t and wind power operation cost S w,t composition:

[0072] F C,t =S G,t +S w,t (16);

[0073]

[0074] f(P G,i,t )=(a i (P G,i,t ) 2 +b i P G,i,t +c i )ΔT (18);

[0075] S w,t =C w P w,t ΔT (19);

[0076] Where: I i,t is a Boolean variable representing the operating status of unit i during period t; S i is the start-up and shutdown cost of unit i; f(P G,i,t ) is the power generation cost function of unit i in period t; a i , b i 、c i is the coal consumption cost coefficient of unit i.w is the wind power cost coefficient.

[0077] In step 3, the constraints of the low-carbon dispatch model for the joint operation of wind power-pumped storage-carbon capture considering carbon trading include: upper and lower limit constraints on the output of carbon capture units, unit climbing constraints, carbon capture flue gas diversion ratio constraints, liquid storage tank constraints, wind power output constraints, pumped storage unit power constraints, pumped storage reservoir water volume constraints, and network transmission constraints; 1) Carbon capture unit constraints.

[0078] Unit output upper and lower limit constraints:

[0079] P G,i,min I i,t ≤P G,i,t ≤P G,i,max I i,t (20);

[0080] Where: P G,i,min , P G,i,max are the minimum and maximum power of the carbon capture unit respectively.

[0081] Unit climbing constraints:

[0082] P G,i,t -P G,i,t-1 |≤ΔP G,i (twenty one);

[0083] Where: ΔP G,i is the ramp constraint value of the carbon capture unit.

[0084] Carbon capture flue gas split ratio constraints:

[0085]

[0086] The volume of solution in the storage tank can be expressed by the mass of CO2:

[0087]

[0088] Where: V CA,i,t M is the volume of CO2 required to be released from the liquid storage tank of unit i during period t; MEA is the molar mass of MEA; M CO2 is the molar mass of CO2; θ is the amount of analysis by the analysis tower; μ R is the solution concentration; σ R is the density of the solution.

[0089] Reservoir Constraints:

[0090]

[0091] Where: V CF,i,tis the solution content of the rich liquid storage tank of unit i at time t; V CP,i,t The solution content of the lean liquid storage tank of unit i during period t; V CR Configure the capacity for the liquid storage tank; V CF,i,0 V is the solution content in the rich liquid storage tank at the initial moment; CF,i,24 V is the solution content in the rich liquid storage tank at the end of the day; CP,i,0 V is the solution content in the lean liquid storage tank at the initial moment; CP,i,24 It is the solution content in the lean liquid storage tank at the end moment.

[0092] 2) Wind power output constraints.

[0093] 0≤P w,t ≤P wpre,t (25); where: P wpre,t is the wind power prediction value

[0094] 3) Pumped storage constraints.

[0095] Unit power constraints:

[0096]

[0097] Where: P hg,min , P hg,max are the upper and lower limits of pumped storage power generation output respectively; P hp,min , P hp,max are the upper and lower limits of pumped storage power respectively; g,t With y p,t The sum is less than or equal to 1, indicating that the pumped storage unit can only be in a single operating condition.

[0098] Water volume constraints of pumped storage reservoirs:

[0099]

[0100] Where: V h,t V is the reservoir capacity of the power station during period t; h,min 、V h,max are the upper and lower limits of reservoir capacity respectively; η p The water-to-electricity conversion coefficient during the unit's pumping period; η g The water-to-electricity conversion coefficient during the unit's power generation period; They are the reservoir capacity of the power station in the initial and final periods of the dispatching cycle respectively. The pumped storage and release water volume is kept balanced within a cycle.

[0101] 4) Network transmission constraints

[0102] -P ij,max ≤B ij (θ i,t -θ j,t )≤Pij,max (28);

[0103] Where: P ij,max is the maximum capacity of the transmission line between nodes i and j; B ij is the susceptance between nodes i and j; θ i,t and θ j,t are the voltage phase angles between nodes i and j respectively.

[0104] Affected by factors such as climate and geographical environment, wind power output has strong uncertainty. There is still a large error between the unit output forecast and the actual output, which will cause a certain amount of wind abandonment. and load fuzzy parameters The impact of the errors in the forecast of wind power output and load on the system is dealt with. First, the wind power and load in the system power constraint and reserve constraint are replaced by fuzzy parameters, and then relaxed into opportunity constraints under a specific confidence level. The confidence level is used to balance economy and safety. For the convenience of solving, the fuzzy opportunity constraints are converted into clear equivalent classes.

[0105] In step 4, the method of converting the fuzzy chance constraints into clear equivalence classes includes the following steps:

[0106] Step 4.1: Construction of fuzzy chance constraints:

[0107] For a single-objective optimization problem with fuzzy parameters in the constraints, it can be expressed as

[0108]

[0109] Where: f(x) is the objective function; P{·} represents the possibility of an event; g(x,ξ) is the constraint function; x and ξ are the n-dimensional decision vector and fuzzy parameter vector respectively; α is the confidence level.

[0110] The system power balance credibility opportunity constraint can be expressed as

[0111]

[0112] The system spinning reserve credibility opportunity constraint can be expressed as

[0113]

[0114] The trapezoidal blur parameters can be represented by a quaternion:

[0115]

[0116] Where: P Fi is the membership parameter, whose value is determined by the predicted value P pre OK; wk is the proportionality coefficient, and its value range is determined according to the historical data of wind power and load.

[0117] Since wind power and load are represented by fuzzy parameters, the fuzzy chance constraint has taken into account the handling of the uncertainty of the day-ahead forecast value, so there is no need to assume the reserve power separately.

[0118] Step 4.2: Conversion of fuzzy parameter clear equivalence classes;

[0119] When the constraint function has the following form:

[0120] g(x,ξ)=h1(x)ξ1+h2(x)ξ2...+h t (x)ξ t +h0(x) (33);

[0121] Where: k is the fuzzy membership parameter (r k1 ,r k2 ,r k3 ,r k4 ), k = 1, 2, ..., t, t∈R, r k1 -r k4 is the membership parameter.

[0122] Then we can define the following two functions:

[0123]

[0124] Where: k = 1, 2, ..., t; if h(x) = 1, then h + (x)=1,h - (x) = 0; if h(x) = -1, then h + (x) = 0, h - (x)=1.

[0125] In step S5, the confidence level needs to be α ≥ 0.5, and the clear equivalence class of the chance constraint is defined as

[0126]

[0127] The uncertain constraints of equations (30) and (31) are transformed into deterministic constraints according to the above clear equivalence class method, which is convenient for computer solution;

[0128] A clear equivalence class of system power balance constraints:

[0129]

[0130] A clear equivalence class of system spinning reserve constraints:

[0131]

[0132] Where: P w,t1 , P w,t2 is the wind power membership parameter; P l,t3 , P l,t4 is the load membership parameter.

[0133] Step 6: Use the IEEE-30 node to perform case analysis, input the parameters of each unit and the carbon trading parameters, set the confidence level to 0.95, and use the CPLEX solver to solve the optimal output plan for this low-carbon dispatch.

[0134] Table 1 Carbon capture unit parameters

[0135] Table 1Parameters of carbon capture plants

[0136]

[0137] Table 2 Pumped storage unit parameters

[0138] Table 2Parameters of pumped storage station

[0139]

[0140] Table 3 Time of use price

[0141]

[0142]

[0143] Table 4 Parameters of carbon capture equipment and carbon trading

[0144]

[0145] Table 5 Parameters of fuzzy membership

[0146]

[0147] Set up three comparison scenarios as follows:

[0148] 1) Thermal power and wind power operation and dispatch: basic scenario for day-ahead dispatch.

[0149] 2) Carbon capture-wind power operation and dispatch: Introduce flexible carbon capture units.

[0150] 3) Carbon capture-wind power-pumped storage joint operation and dispatch: Based on scenario 2, pumped storage units are introduced to cooperate with carbon capture units to participate in peak regulation.

[0151] The results of the day-ahead optimization scheduling of the units under the three scenarios are shown in the following table.

[0152] Table 6 Comparison of system benefits and costs in different scenarios

[0153] Table 6Comparisons of system benefits and costs in different scenarios

[0154]

[0155] A comprehensive comparison of the dispatch results of the three scenarios shows that the system after adding carbon capture equipment in scenario 2 has reduced carbon emissions by 1918.9 tons compared with the day-ahead dispatch of the traditional system containing new energy, but the carbon capture energy consumption needs to be supplied, resulting in an increase of 186,900 yuan in system fuel costs. Due to the reduction in carbon emissions, the carbon capture power plant can sell excess carbon quotas to obtain additional income, so the net income is only slightly reduced. After the pumped storage power station participates in the system peak regulation, it can absorb the abandoned wind and call the pumped storage unit to obtain a certain amount of electricity income. The output of the carbon capture unit is reduced, and after the introduction of pumped storage peak regulation, the carbon capture unit can be more focused on carbon capture, and the fuel cost and carbon emissions are also reduced accordingly. Compared with scenario 2, carbon emissions are reduced by 140.8 tons, a decrease of 7.01%; the net income of the system is increased by 63,900 yuan compared with scenario 2, an increase of 7.62%. The economic and environmental benefits of the system have improved after the introduction of the pumped storage unit.

[0156] The contents described in the embodiments of this specification are merely an enumeration of the implementation forms of the inventive concept. The protection scope of the present invention should not be regarded as limited to the specific forms described in the embodiments. The protection scope of the present invention also extends to equivalent technical means that can be conceived by those skilled in the art based on the inventive concept.

Claims

1. A low-carbon dispatching method for a new energy grid involving flexible operation of carbon capture, characterized in that: The steps include: Step 1: Add a liquid storage tank to the carbon capture system to form a comprehensive flexible operation carbon capture equipment model; Step 2: Propose a carbon trading mechanism based on the baseline method; Step 3: Introduce pumped storage units and wind turbine models, take unit output as the decision variable, optimize the economic benefits of the power generation side as the goal, consider unit operation constraints and system safety constraints, and build a low-carbon dispatch model for wind power-pumped storage-carbon capture combined operation that considers carbon trading; Step 4: Replace wind power output and load with trapezoidal fuzzy parameters, and multiply the predicted values ​​of wind power and load by the proportional coefficient to express their respective fuzzy parameters; Step 5: Convert the original power balance constraints and reserve capacity constraints into fuzzy chance constraints, set the confidence level, convert the fuzzy chance constraints into crisp equivalence classes, and convert the model into mixed integer programming; Step 6: Use the CPLEX solver to solve the optimal output plan for this low-carbon dispatch.

2. A low-carbon dispatching method for a new energy grid involving flexible operation of carbon capture according to claim 1, characterized in that: The carbon capture system includes an absorption tower, the lower end of which is connected to a rich liquid storage tank, a heat exchanger tube side and a regeneration tower feed port in sequence through a pipeline, the upper end of which is connected to a lean liquid storage tank, a heat exchanger shell side, a reboiler and the lower end of the regeneration tower in sequence, the top of the absorption tower is connected to an exhaust pipe, the lower end of the absorption tower is connected to a flue gas inlet pipe, and the top of the absorption tower is connected to a compressor through a carbon exhaust pipe.

3. A low-carbon dispatching method for a new energy grid involving flexible operation of carbon capture according to claim 2, characterized in that: In step 2, the method for establishing a carbon trading mechanism includes the following steps: Step 2.1: Establish the power relationship expression of the carbon capture unit: P GN,i,t =P G,i,t -P GC,i,t (1); P GC,i,t =P B,i +P op,i,t (2); Where: P G,i,t , P GN,i,t is the total power generation output and net power generation output of carbon capture unit i during period t; P GC,i,t The capture power of the carbon capture unit; Step 2.2: Adding a liquid storage tank based on post-combustion carbon capture technology: P op,i,t =m c E deal,i,t (3); THAT deal,i,t =E GC,i,t +βδE G,i,t (4) AND G,i,t =and i P G,i,t (5); Where: m c is the operating energy consumption for processing unit mass of CO2; β is the flue gas diversion ratio of the unit, which indicates the proportion of flue gas generated by the thermal power unit flowing into the carbon capture equipment; E G,i,t E is the CO2 production of the unit; GC,i,t is the amount of CO2 supplied from the liquid storage tank to the regeneration tower; δ is the CO2 capture rate; e i is the carbon emission intensity per unit of electricity of thermal power unit i; The net output power of the carbon capture unit is derived from the above formula: P GN,i,t =(1-m c βδe i )P G,i,t -P B,i -m c E GC,i,t (6); The amount of CO2 that can be provided by the rich liquid storage tank is constrained as follows: -βδe i P G,i,t ≤E GC,i,t ≤ηδe i P G,i,max -βδe i P G,i,t (7); Where: η is the maximum working state coefficient of the regeneration tower, P G,i,max is the maximum power of the unit; Step 2.3: Construct a carbon trading mechanism model: First, the net CO2 emissions of the carbon capture unit are derived from step 2.2: Where: N G is the number of thermal power units; T is the total number of time periods in a day; The baseline method is used to calculate the system's carbon emission quota and carbon trading income, and the relationship expression is: F trade =σ(E D -AND dis ) (10); Where: E D is the carbon emission quota allocated to the carbon capture unit; λ is the carbon emission quota per unit power of the carbon capture unit; F trade is the carbon trading income; σ is the carbon trading price; within the specified period, if the carbon emissions of the carbon capture power plant are less than the carbon quota, the remaining carbon quota can be traded to obtain income; if the carbon emissions of the carbon capture power plant are greater than the carbon quota, the excess carbon emission quota must be purchased additionally.

4. A low-carbon dispatching method for a new energy grid involving flexible operation of carbon capture according to any one of claims 1 to 3, characterized in that: In step 3, the unit output is used as the decision variable, the optimal economic benefit of the power generation side is the goal, and the maximum net profit of the system is used as the objective function. The objective function is: Where: F is the net income of the system; F S,t is the income from carbon capture units and wind turbines during period t; F H,t F is the benefit of calling the pumped storage unit during period t; C,t is the unit operating cost during period t; F trade The carbon trading income of the system after the introduction of the carbon trading mechanism; 1) Wind power-carbon capture unit grid connection income Where: K t is the grid-connected electricity price of the unit; P w,t is the wind power in period t; ΔT is the scheduling time interval; 2) Benefits of using pumped storage units The benefit of using pumped storage is the difference between the power benefit of pumped storage and the start-stop loss cost: F H,t =G h,t -S h,t (13); G h,t =K hg P hg,t ΔT-K hp P hp ΔT (14); S h,t =[and g,t (1-and g,t-1 )+y p,t (1-and p,t-1 )]C h +[and g,t-1 (1-and g,t )+y p,t-1 (1-and p,t )]C h (15); Where: G h,t is the power efficiency of the pumped storage unit; S h,t is the start-stop loss cost of the pumped storage unit; P hg,t is the power generation capacity of the pumped storage unit; P hp is the pumping power of the pumped storage unit; K hg is the on-grid electricity price of the pumped storage unit; K hp is the pumped electricity price of the pumped storage unit; g,t ,y p,t Boolean variables representing whether the unit is in power generation or pumping operation; C h It is the cost of starting and stopping the pumped storage unit once; 3) Unit operating costs The unit operating cost is composed of the carbon capture unit operating cost S G,t and wind power operation cost S w,t composition: F C,t =S G,t +S w,t (16); f(P G,i,t )=(a i (P G,i,t ) 2 +b i P G,i,t +c i )ΔT (18); S w,t =C w P w,t ΔT (19); Where: I i,t is a Boolean variable representing the operating status of unit i during period t; S i is the start-up and shutdown cost of unit i; f(P G,i,t ) is the power generation cost function of unit i in period t; a i 、b i 、c i is the coal consumption cost coefficient of unit i; C w is the wind power cost coefficient.

5. A low-carbon dispatching method for a new energy grid involving flexible operation of carbon capture according to any one of claims 1 to 3, characterized in that: In step 3, the constraints of the low-carbon dispatch model of wind power-pumped storage-carbon capture combined operation considering carbon trading include: upper and lower limits of carbon capture unit output, unit ramp constraints, carbon capture flue gas diversion ratio constraints, liquid storage tank constraints, wind power output constraints, pumped storage unit power constraints, pumped storage reservoir water volume constraints, and network transmission constraints; 1) Carbon capture unit constraints; Unit output upper and lower limit constraints: P G,i,min I i,t ≤P G,i,t ≤P G,i,max I i,t (20); Where: P G,i,min , P G,i,max are the minimum and maximum power of the carbon capture unit, respectively; Unit climbing constraints: |P G,i,t -P G,i,t-1 |≤ΔP G,i (21); Where: ΔP G,i is the ramp constraint value of the carbon capture unit; Carbon capture flue gas split ratio constraints: The volume of solution in the storage tank can be expressed by the mass of CO2: Where: V CA,i,t M is the volume of CO2 required to be released from the liquid storage tank of unit i during period t; MEA is the molar mass of MEA; is the molar mass of CO2; θ is the amount of analysis by the analysis tower; μ R is the solution concentration; σ R is the solution density; Tank constraints: Where: V CF,i,t is the solution content of the rich liquid storage tank of unit i at time t; V CP,i,t The solution content of the lean liquid storage tank of unit i during period t; V CR Configure the capacity for the liquid storage tank; V CF,i,0 V is the solution content in the rich liquid storage tank at the initial moment; CF,i,24 V is the solution content in the rich liquid storage tank at the end of the day; CP,i,0 V is the solution content in the lean liquid storage tank at the initial moment; CP,i,24 is the solution content at the end of the lean liquid storage tank; 2) Wind power output constraints; 0≤P w,t ≤P wpre,t (25); Where: P wpre,t is the predicted value of wind power; 3) Pumped storage constraints; Unit power constraints: Where: P hg,min , P hg,max are the upper and lower limits of pumped storage power generation output respectively; P hp,min , P hp,max are the upper and lower limits of pumped storage power respectively; g,t With y p,t The sum is less than or equal to 1, indicating that the pumped storage unit can only be in a single operating condition; Water volume constraints of pumped storage reservoirs: Where: V h,t V is the reservoir capacity of the power station during period t; h,min 、V h,max are the upper and lower limits of reservoir capacity respectively; η p The water-to-electricity conversion coefficient during the unit's pumping period; η g The water-to-electricity conversion coefficient during the unit's power generation period; They are the storage capacity of the power station reservoir at the initial and final periods of the dispatching cycle, and the pumped water volume is balanced within a cycle; 4) Network transmission constraints; -P ij,max ≤B ij (i i,t -θ j,t )≤P ij,max (28); Where: P ij,max is the maximum capacity of the transmission line between nodes i and j; B ij is the susceptance between nodes i and j; θ i,t and θ j,t are the voltage phase angles between nodes i and j respectively.

6. A low-carbon dispatching method for a new energy grid involving flexible operation of carbon capture according to any one of claims 1 to 3, characterized in that: In step 4, the method of converting the fuzzy chance constraints into clear equivalence classes includes the following steps: Step 4.1: Construction of fuzzy chance constraints: The single-objective optimization problem with fuzzy parameters in the constraints can be expressed as: Where: f(x) is the objective function; P{·} represents the probability of an event; g(x,ξ) is the constraint function; x and ξ are the n-dimensional decision vector and fuzzy parameter vector respectively; α is the confidence level; The system power balance credibility opportunity constraint can be expressed as: The system spinning reserve credibility opportunity constraint can be expressed as: The trapezoidal blur parameters can be represented by a quaternion: Where: P Fi is the membership parameter, whose value is determined by the predicted value P pre OK; w k is the proportionality coefficient; Step 4.2: Conversion of fuzzy parameter clear equivalence classes; When the constraint function has the following form: g(x,ξ)=h1(x)ξ1+h2(x)ξ2...+h t (x)ξ t +h0(x) (33); Where: k is the fuzzy membership parameter (r k1 ,r k2 ,r k3 ,r k4 ), k = 1, 2, ..., t, t∈R, r k1 -r k4 is the membership parameter; Then we can define the following two functions: Where: k = 1, 2, ..., t; if h(x) = 1, then h + (x)=1,h - (x) = 0; if h(x) = -1, then h + (x) = 0, h - (x)=1.

7. A low-carbon dispatching method for a new energy grid involving flexible operation of carbon capture according to any one of claims 1 to 3, characterized in that: In step S5, the confidence level needs to be α≥0.5, and the clear equivalence class of the chance constraint is defined as: The uncertain constraints of equations (30) and (31) are transformed into deterministic constraints according to the above clear equivalence class method, which is convenient for computer solution; A clear equivalence class of system power balance constraints: A clear equivalence class of system spinning reserve constraints: Where: P w,t1 , P w,t2 is the wind power membership parameter; P l,t3 , P l,t4 is the load membership parameter.

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