A low-carbon economic dispatch method considering multi-form high energy loads during the day and within the day

Abstract

This invention discloses a day-ahead and intraday low-carbon economic dispatch method that considers multi-modal high-energy loads. First, the operating characteristics of adjustable high-energy loads within the system are analyzed, and a refined mathematical model for these multi-modal high-energy loads is established. Then, by comprehensively considering the complementary low-carbon characteristics of the source and load sides and the differences in the response speed of multi-modal high-energy loads on the demand side, and incorporating energy storage systems, a two-stage day-ahead and intraday low-carbon economic optimization dispatch model is established. The proposed dispatch method was simulated and analyzed using the CPLEX solver on a modified IEEE 39-node system. Results demonstrate that the proposed method improves the system's wind power absorption capacity while simultaneously ensuring low-carbon and economic efficiency, providing a reference for grid dispatch.

Description

Technical Field

[0001] The present invention belongs to the technical field of improving the low-carbon and economic performance of wind power systems, and specifically relates to a day-ahead and intraday low-carbon economic dispatching method considering multi-form high-energy loads. Background Art

[0002] The achievement of the "dual carbon" goals will inevitably lead to the rapid development of wind power, which offers low marginal costs and zero carbon emissions. According to the "2020 Basic Data Summary of Electricity Statistics" released by the China Electricity Council, installed wind power capacity reached 281.65 million kilowatts in 2020, a year-on-year increase of 34.66%. However, wind power output exhibits diurnal variability, uncertainty, and peak-shaving characteristics. Its large-scale grid integration will create a significant gap in the power system's regulating power supply. Current research on high-energy loads primarily focuses on single-mode high-energy loads, while analysis of multi-mode high-energy loads is relatively rare. Therefore, to more accurately tap the regulatory potential and flexibility of demand-side resources, utilizing multi-mode high-energy loads as a regulatory tool for wind power-inclusive system scheduling holds profound significance. Summary of the Invention

[0003] The purpose of the present invention is to provide a day-ahead and intraday low-carbon economic dispatching method that takes into account multi-form high-energy loads, which can improve the system's wind power absorption level while ensuring the system's low-carbon and economic performance.

[0004] The technical solution adopted by the present invention is a day-ahead and intraday low-carbon economic dispatch method considering multi-form high-energy loads, which is specifically implemented according to the following steps:

[0005] Step 1: Analyze the operating characteristics of multi-mode adjustable high-energy loads, classify them according to the differences in their response speeds, and perform refined modeling of the multi-mode high-energy loads;

[0006] Step 2: Convert conventional units into carbon capture units with low-carbon characteristics, deeply explore their operating characteristics and low-carbon features, and establish a low-carbon operating cost model;

[0007] Step 3: Based on the differences in the response speed of multi-form high-energy loads, a two-stage low-carbon economic dispatch model (day-ahead and intraday) is constructed;

[0008] Step 4: Obtain the day-ahead-intraday low-carbon economic dispatch plan based on the day-ahead-intraday two-stage low-carbon economic dispatch model.

[0009] The present invention is also characterized in that:

[0010] Step 1: The multi-form adjustable high energy load operation characteristics include the operation characteristics of the continuous adjustable high energy load, the operation characteristics of the discrete adjustable high energy load, and the operation characteristics of the time-shifted adjustable high energy load.

[0011] Step 1: Classify various adjustable high-energy loads according to their response speed differences and conduct refined modeling of multi-form high-energy loads. Specifically, the following situations are included:

[0012] 1) Modeling of a continuously adjustable high-energy load considering its operating characteristics and cost constraints:

[0013] Power Constraints:

[0014] P lsh (t) = P ls-base (t)+P ls-up (t)-P ls-down (t) (1)

[0015] Upper and lower limit constraints of adjustment amount:

[0016]

[0017] State constraints:

[0018] S1(t)+S2(t)≤1 (3)

[0019] Adjustment times constraint:

[0020]

[0021] Adjust duration constraints:

[0022]

[0023] Planned output constraints:

[0024]

[0025] Adjustment costs:

[0026]

[0027] Where, P lsh (t) The power of the discrete adjustable high-energy load at time t, P ls-base (t) is the base load at time t, P ls-up (t) is the upward adjustment at time t, P ls-down (t) is the downward adjustment amount at time t; S1(t) is the state where the discrete adjustable high-energy load is in the upward adjustment state, S2(t) is the state where the load is in the downward adjustment state, P ls-up-min To increase the minimum value, P ls-up-maxTo increase the maximum value, P ls-down-min is the minimum value of the downward adjustment, P ls-down-max is the maximum value of the downward adjustment, M is the maximum number of adjustments; T1 is the maximum upward adjustment duration, T2 is the maximum downward adjustment duration; λ i is the adjusted working efficiency, E ls-plan is the planned daily output; C ls is the total cost of load regulation, C(t) is the time-of-use electricity price of industrial load at time t, K ls (t) is the response subsidy cost at time t, and T is the scheduling period;

[0028] 2) Considering the operating characteristics and cost constraints of discrete adjustable high-energy loads, the following model is established:

[0029] Power Constraints:

[0030] P lxh (t) = P lx-base (t)+P lx-up (t)-P lx-down (t) (8)

[0031] Output upper and lower limit constraints:

[0032] P lx-min ≤P lxh (t)≤P lx-max (9)

[0033] Adjust rate constraints:

[0034] P lxh-down ≤P lxh (t)-P lxh (t-1)≤P lxh-up (10)

[0035] Upper and lower limit constraints of adjustment amount:

[0036]

[0037] State constraints:

[0038] S1(t)+S2(t)≤1 (12)

[0039] Output constraints:

[0040]

[0041] Adjustment costs:

[0042]

[0043] Where, P lxh (t) is the power at time t after continuous high-energy load regulation, Plx-base (t) is the base load of the continuous high energy load at time t, P lx-up (t) is the upward adjustment amount at time t, P lx-down (t) is the downward adjustment amount at time t; P lx-min is the minimum output, P lx-max is the maximum output; P lxh-down To adjust the downhill rate, P lxh-up is to adjust the ramp rate; S3(t) is the load adjustment decision variable, S4(t) is the load adjustment decision variable; P lx-up-max is the maximum value of load increase, P lx-up-min is the minimum value of load increase, P lx-down-max is the maximum value of load reduction, P lxh-down-min is the minimum value of load reduction; k is the adjusted working efficiency, E lx-plan It is a continuous high-energy load daily production plan; C lx To regulate the total cost of load, C(t) is the time-of-use electricity price of industrial load at time t, K lx (t) is the response subsidy cost at time t;

[0044] 3) Considering the operating characteristics and cost constraints of the time-shifted adjustable high-energy load, the following model is established:

[0045] Power Constraints:

[0046] P syh (t) = S5(t)P syq (t) (15)

[0047] Time-shifting time constraints:

[0048]

[0049] Planned output constraints:

[0050]

[0051] Adjustment costs:

[0052]

[0053] Where, P syq (t) is the load value at time t before adjustment, P syq (t) is the load size at time t after adjustment; λ j is the adjusted work efficiency, S5(t) is the time shift decision variable, 1 means time shift occurs at this moment, 0 means no time shift occurs at this moment; T min is the minimum transfer duration constraint; E sy-planIt is a time-shifted high-energy load daily production plan; C sy K is the total cost of load regulation. sy (t) is the response subsidy cost at time t.

[0054] Step 2: The cost of the carbon capture unit with low carbon characteristics is the coal consumption cost and the CO2 treatment cost. The coal consumption cost is the same as that of the conventional unit, and the CO2 treatment cost is divided into the CO2 emission cost and the CO2 capture cost.

[0055] The CO2 treatment cost calculation process in step 2 is:

[0056] Step 2.1: The calculation process of CO2 emission cost of carbon capture unit is as follows:

[0057] The total CO2 capture capacity of carbon capture unit j at time t is:

[0058] E cb,j (t) = K cd P cb,j (t) (19)

[0059] The total amount of CO2 captured by the carbon capture unit at time t is:

[0060]

[0061] The CO2 emission cost during the scheduling period is:

[0062]

[0063] Where, E cb,j (t) is the total amount of CO2 produced by carbon capture unit j at time t, K cd is the carbon emission intensity of the carbon capture unit, P cb,j (t) is the total output of carbon capture unit j at time t; E j,total-co2 (t) is the total amount of CO2 captured by carbon capture unit j, β is the capture efficiency of carbon capture equipment; N cb is the number of carbon capture units, K c is the unit carbon emission cost;

[0064] Step 2.2, CO2 capture cost of carbon capture unit:

[0065] The CO2 capture cost includes energy consumption cost, depreciation cost and storage cost, and its specific expression is as follows:

[0066] Energy consumption cost of carbon capture unit:

[0067]

[0068] Depreciation cost of carbon capture unit:

[0069]

[0070] Storage costs of carbon capture units:

[0071]

[0072] Where C ne is the energy consumption cost of the carbon capture power plant, P Dj (t) is the fixed energy consumption of the carbon capture unit, P Bj (t) is the operating energy consumption of the carbon capture unit, N cb is the number of carbon capture units; C(t) is the time-of-use electricity price for industrial load; C zj is the depreciation cost, N zj is the depreciation period, α is the discount rate of the carbon capture unit project, C tb is the total cost of capture equipment in carbon capture power plants; C ry is the unit volume solution storage cost, V ry is the volume of the solution storage, N ry Solution storage depreciation period; K se is the unit CO2 storage cost, C se is the total storage cost of the carbon capture unit;

[0073] Step 2.3: Calculate the total CO2 treatment cost C based on the CO2 emission cost and CO2 capture cost of the carbon capture unit. cbc for:

[0074] C cbc =C ne +C se +C de +C cd (25)

[0075] The specific process of step 3 is as follows:

[0076] Step 3.1: Construct the objective function and constraints of the day-ahead low-carbon economic model:

[0077] The objective function of the low-carbon economy model today is:

[0078] F1=min(C cg +C cb +C aw +C ls +C sy +C cbc +C cgc ) (26)

[0079]

[0080] Where, F1 is the total cost of the system’s low-carbon economy optimization dispatch operation on the day before; C cg is the operating cost of conventional thermal power units, C cbc is the total cost of CO2 treatment, U i (t) The start and stop status of conventional thermal power unit i at time t, a i 、b i 、c i is the coal consumption cost coefficient of conventional thermal power unit i, P cg,i (t) is the output of conventional thermal power unit i at time t; C cb is the operating cost of the carbon capture unit, U j (t) is the start and stop status of the carbon capture unit j at time t, a j 、b j 、c j is the coal consumption cost coefficient of carbon capture unit j, P cb,j (t) is the output of carbon capture unit j at time t; C aw is the cost of wind curtailment, K aw is the unit wind curtailment cost, P wfore (t) is the predicted wind power output at time t, P w (t) is the planned wind power output value at time t; C cgc is the total carbon emission cost of conventional thermal power units, K c is the unit carbon emission cost;

[0081] Step 3.2: Construct the objective function and constraints of the intraday low-carbon economic model:

[0082] The objective function of the intraday low-carbon economy model is expressed as:

[0083] F2=min(C cn +C lx -C Δaw ) (36)

[0084]

[0085] Where, F2 is the total operating cost of the system during the day, C lx The continuous adjustable high energy load regulation cost, C cn is the operating cost of the energy storage system, C Δaw To reduce the cost of wind curtailment, K cn is the unit energy storage cost.

[0086] The constraints of the day-ahead low-carbon economy model include system power balance constraints, wind power output constraints, conventional unit output upper and lower limits constraints, conventional unit ramping constraints, system spinning reserve, carbon capture unit operation constraints, and carbon capture unit solution storage operation constraints. They are specifically expressed as follows:

[0087] 1) System power balance constraints:

[0088]

[0089] 2) Wind power output constraints:

[0090] 0≤P w (t)≤P wfore (t) (29)

[0091] 3) Upper and lower limits of conventional unit output:

[0092] U i (t)P cgmin,i ≤P cg,i (t)≤U i (t)P cgmax,i (30)

[0093] 4) Conventional unit climbing constraints:

[0094]

[0095] 5) System spinning reserve

[0096] The system's spinning reserve is shared by conventional thermal power units and carbon capture units:

[0097]

[0098] 6) Operational constraints of carbon capture units

[0099] According to the energy consumption characteristics of the carbon capture unit, the flue gas split ratio constraint, the carbon capture amount constraint, and the carbon capture equipment energy consumption constraints are considered. The energy consumption of the carbon capture equipment is mainly composed of two parts: fixed energy consumption and operating energy consumption. The mathematical model of the carbon capture unit is as follows:

[0100]

[0101] Where, P cg (t) is the normal load at time t, R i up is the ramp rate of unit i, R i down Ramp rate of unit i; R down is the system negative spinning reserve, R up The system is spinning reserve; E cb,j (t) is the total amount of CO2 produced by carbon capture unit j at time t, K cd is the carbon emission intensity of the carbon capture unit, P cb,j (t) is the total output of carbon capture unit j at time t; state coefficient, Pcj,j,max is the maximum output of carbon capture unit j; P Bj (t) is the operating energy consumption of carbon capture unit j at time t, λ is the unit energy consumption of capturing CO2; P cj,j (t) is the net output of carbon capture unit j at time t, P Dj is the fixed energy consumption of carbon capture unit j;

[0102] 7) Solution storage operation constraints

[0103] The solution in the solution storage of the carbon capture unit is ethanolamine solution. The mass of CO2 is calculated using the volume of the solution. The relationship expression is as follows:

[0104]

[0105] Where V CAi (t) is the volume of solution capturing CO2 by carbon capture unit i at time t, Q Gi (t) is the mass of CO2 captured by carbon capture unit i at time t, M EA is the molar mass of ethanolamine solution, M CO2 is the molar mass of CO2, M R is the concentration of ethanolamine solution, ρ R Density of ethanolamine solution;

[0106] The operating constraints of the solution storage of the carbon capture unit are:

[0107]

[0108] Where V Fi (t) is the volume of the solution in the rich liquid storage of carbon capture unit i at time t, V Pi (t) is the volume of the lean solution storage of carbon capture unit i at time t, V CAi (t) is the volume of solution capturing CO2 by carbon capture unit i at time t, V CAi is the maximum volume of the solution storage of carbon capture unit i.

[0109] The constraints of the daily low-carbon economic model include the daily power regulation balance and energy storage system operation constraints, specifically:

[0110] 1) Intraday power regulation balance constraints

[0111] ΔP w (t) = P lx-up (t)-P lx-down (t)+P cha (t)-P dis (t) (38)

[0112] 2) Energy storage system operation constraints

[0113] Considering the state of charge constraints and charge and discharge power constraints of the energy storage system, its mathematical model is as follows:

[0114] Energy storage system state of charge and its expression:

[0115]

[0116]

[0117] Energy storage system charging and discharging constraints:

[0118]

[0119] Where ΔP W (t) is the difference between the wind power output value predicted within the day and the wind power output value planned on the day before, B soc is the state of charge of the energy storage system, E b is the current power of the energy storage system, C b is the total capacity of the energy storage system; B soc,min 、B soc,max are the minimum and maximum state of charge of the energy storage system, B soc (t) is the state of charge of the energy storage system at time t; B soc (t+1) is the state of charge of the energy storage system at time t+1; P cha (t) is the charging power of the energy storage system at time t, η cha is the charging efficiency, is the scheduling period; P dis (t) is the discharge power of the energy storage system at time t, η dis is the discharge efficiency; P cha,min 、P cha,max are the upper and lower limits of the energy storage system charging power respectively; P dis,min 、P dis,max are the upper and lower limits of the energy storage system discharge power respectively.

[0120] The specific process of step 4 is as follows: in the day-ahead stage, the discrete and time-shifted high-energy load plan values and the wind power intraday forecast value are input into the day-ahead low-carbon economic model to obtain the day-ahead dispatch plan; in the intraday stage, the conventional load forecast, the time-shifted and time-shifted high-energy load plan values, and the wind power day-ahead forecast value are input into the intraday low-carbon economic model to obtain the intraday dispatch plan.

[0121] The beneficial effects of the present invention are:

[0122] This invention proposes a low-carbon, day-ahead, and intraday dispatching method for multi-modal high-energy loads. This method considers the energy time-shifting and low-carbon characteristics of carbon capture units under comprehensive source-side operation, as well as the zero-carbon and low-cost characteristics of wind power. It integrates multi-modal high-energy loads on the load side with energy storage systems into a low-carbon, economic dispatching plan, leveraging the low-carbon characteristics of both the source and the load. Furthermore, to mitigate the adverse effects of discrepancies between wind power's day-ahead planned output and its intraday forecast, the method leverages the differences in the response characteristics of multi-modal high-energy loads to rationally schedule their participation in dispatching plans for both the day-ahead and intraday periods. This method proposes a two-stage, day-ahead, and intraday dispatching method for wind power systems that considers multi-modal high-energy loads. This method improves the system's wind power absorption capacity while simultaneously ensuring both low carbon and economic efficiency, and provides a reference for grid dispatching. BRIEF DESCRIPTION OF THE DRAWINGS

[0123] Figure 1 This is a flow chart of the day-ahead and intraday low-carbon economic dispatch method considering multi-form high-energy loads;

[0124] Figure 2 is a load forecast diagram in an embodiment of the present invention;

[0125] Figure 3 This is a time-of-use electricity price diagram in an embodiment of the present invention;

[0126] Figure 4 The system day-ahead wind power forecast and intraday wind power forecast diagrams in the embodiment of the present invention are as follows;

[0127] Figure 5 The discrete adjustable high-energy load regulation and time-of-use electricity price in the embodiment of the present invention;

[0128] Figure 6 This is the time-shifted adjustable high-energy load regulation situation in the embodiment of the present invention;

[0129] Figure 7 The output of each unit in the system in the embodiment of the present invention;

[0130] Figure 8 The carbon dioxide capture capacity and time-of-use electricity price of the carbon capture unit in the embodiment of the present invention;

[0131] Figure 9 This is the continuous adjustable high energy load regulation situation in the embodiment of the present invention;

[0132] Figure 10 This is the operation status of the energy storage system in the embodiment of the present invention;

[0133] Figure 11 This is a diagram of system error adjustment in an embodiment of the present invention;

[0134] Figure 12This is a comparison diagram of the system load before and after participating in scheduling in an embodiment of the present invention. DETAILED DESCRIPTION

[0135] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0136] Considering the energy time-shifting and low-carbon characteristics of carbon capture units under the integrated source-side operation mode, as well as the zero-carbon and low-cost characteristics of wind power, the multi-modal high-energy load on the load side is integrated with the energy storage system into the low-carbon economic dispatch plan, realizing the low-carbon characteristics of both the source and the load. At the same time, to reduce the adverse impact of the error between the day-ahead planned output and the intraday forecast value of wind power, the differences in the response characteristics of multi-modal high-energy load are utilized to rationally arrange its participation in the dispatch plan during the day-ahead and intraday periods. A two-stage low-carbon economic dispatch method for the day-ahead and intraday period of wind power systems that considers multi-modal high-energy load is proposed.

[0137] The present invention considers a low-carbon economic dispatch method for day-ahead and intraday with multi-form high energy loads, such as Figure 1 As shown, please follow the steps below:

[0138] Step 1: Analyze the operating characteristics of continuous, discrete, and time-shifted adjustable high-energy loads, classify them according to their response speed differences, and perform refined modeling of multi-form high-energy loads; specifically:

[0139] 1) Modeling of a continuously adjustable high-energy load considering its operating characteristics and cost constraints:

[0140] Power Constraints:

[0141] P lsh (t) = P ls-base (t)+P ls-up (t)-P ls-down (t) (1)

[0142] Upper and lower limit constraints of adjustment amount:

[0143]

[0144] State constraints:

[0145] S1(t)+S2(t)≤1 (3)

[0146] Adjustment times constraint:

[0147]

[0148] Adjust duration constraints:

[0149]

[0150] Planned output constraints:

[0151]

[0152] Adjustment costs:

[0153]

[0154] Where, P lsh (t) The power of the discrete adjustable high-energy load at time t, P ls-base (t) is the base load at time t, P ls-up (t) is the upward adjustment at time t, P ls-down (t) is the downward adjustment amount at time t; S1(t) is the state where the discrete adjustable high-energy load is in the upward adjustment state, S2(t) is the state where the load is in the downward adjustment state, P ls-up-min To increase the minimum value, P ls-up-max To increase the maximum value, P ls-down-min is the minimum value of the downward adjustment, P ls-down-max is the maximum value of the downward adjustment, M is the maximum number of adjustments; T1 is the maximum upward adjustment duration, T2 is the maximum downward adjustment duration; λ i is the adjusted working efficiency, E ls-plan is the planned daily output; C ls is the total cost of load regulation, C(t) is the time-of-use electricity price of industrial load at time t, K ls (t) is the response subsidy cost at time t, and T is the scheduling period;

[0155] 2) Considering the operating characteristics and cost constraints of discrete adjustable high-energy loads, the following model is established:

[0156] Power Constraints:

[0157] P lxh (t) = P lx-base (t)+P lx-up (t)-P lx-down (t) (8)

[0158] Output upper and lower limit constraints:

[0159] P lx-min ≤P lxh (t)≤P lx-max (9)

[0160] Adjust rate constraints:

[0161] P lxh-down ≤P lxh (t)-P lxh (t-1)≤Plxh-up (10)

[0162] Upper and lower limit constraints of adjustment amount:

[0163]

[0164] State constraints:

[0165] S1(t)+S2(t)≤1 (12)

[0166] Output constraints:

[0167]

[0168] Adjustment costs:

[0169]

[0170] Where, P lxh (t) is the power at time t after continuous high-energy load regulation, P lx-base (t) is the base load of the continuous high energy load at time t, P lx-up (t) is the upward adjustment amount at time t, P lx-down (t) is the downward adjustment amount at time t; P lx-min is the minimum output, P lx-max is the maximum output; P lxh-down To adjust the downhill rate, P lxh-up is to adjust the ramp rate; S3(t) is the load adjustment decision variable, S4(t) is the load adjustment decision variable; P lx-up-max is the maximum value of load increase, P lx-up-min is the minimum value of load increase, P lx-down-max is the maximum value of load reduction, P lxh-down-min is the minimum value of load reduction; k is the adjusted working efficiency, E lx-plan It is a continuous high-energy load daily production plan; C lx To regulate the total cost of load, C(t) is the time-of-use electricity price of industrial load at time t, K lx (t) is the response subsidy cost at time t;

[0171] 3) Considering the operating characteristics and cost constraints of the time-shifted adjustable high-energy load, the following model is established:

[0172] Power Constraints:

[0173] P syh (t) = S5(t)P syq (t) (15)

[0174] Time-shifting time constraints:

[0175]

[0176] Planned output constraints:

[0177]

[0178] Adjustment costs:

[0179]

[0180] Where, P syq (t) is the load value at time t before adjustment, P syq (t) is the load size at time t after adjustment; λ j is the adjusted work efficiency, S5(t) is the time shift decision variable, 1 means time shift occurs at this moment, 0 means no time shift occurs at this moment; T min is the minimum transfer duration constraint; E sy-plan It is a time-shifted high-energy load daily production plan; C sy K is the total cost of load regulation. sy (t) is the response subsidy cost at time t.

[0181] Step 2: Convert conventional units into carbon capture units with low-carbon characteristics, deeply explore their operating characteristics and low-carbon features, and establish a low-carbon operating cost model;

[0182] In this invention, the cost of a carbon capture unit primarily considers its coal consumption and CO2 treatment costs. Coal consumption is the same as for conventional units and will not be further elaborated here. CO2 treatment costs are divided into CO2 emission costs and CO2 capture costs. The CO2 emission cost consists of the cost of CO2 emitted directly into the atmosphere through flue gas and the cost of CO2 emitted into the atmosphere after passing through the absorption tower.

[0183] The CO2 treatment cost calculation process is as follows:

[0184] Step 2.1: The calculation process of CO2 emission cost of carbon capture unit is as follows:

[0185] The total CO2 capture capacity of carbon capture unit j at time t is:

[0186] E cb,j (t) = K cd P cb,j (t) (19)

[0187] The total amount of CO2 captured by the carbon capture unit at time t is:

[0188]

[0189] The CO2 emission cost during the scheduling period is:

[0190]

[0191] Where, E cb,j (t) is the total amount of CO2 produced by carbon capture unit j at time t, K cd is the carbon emission intensity of the carbon capture unit, P cb,j (t) is the total output of carbon capture unit j at time t; E j,total-co2 (t) is the total amount of CO2 captured by carbon capture unit j, β is the capture efficiency of carbon capture equipment; N cb is the number of carbon capture units, K c is the unit carbon emission cost;

[0192] Step 2.2, CO2 capture cost of carbon capture unit:

[0193] The CO2 capture cost includes energy consumption cost, depreciation cost and storage cost, and its specific expression is as follows:

[0194] Energy consumption cost of carbon capture unit:

[0195]

[0196] Depreciation cost of carbon capture unit:

[0197]

[0198] Storage costs of carbon capture units:

[0199]

[0200] Where C ne is the energy consumption cost of the carbon capture power plant, P Dj (t) is the fixed energy consumption of the carbon capture unit, P Bj (t) is the operating energy consumption of the carbon capture unit, N cb is the number of carbon capture units; C(t) is the time-of-use electricity price for industrial load; C zj is the depreciation cost, N zj is the depreciation period, α is the discount rate of the carbon capture unit project, C tb is the total cost of capture equipment in carbon capture power plants; C ry is the unit volume solution storage cost, V ry is the volume of the solution storage, N ry Solution storage depreciation period; K se is the unit CO2 storage cost, C se is the total storage cost of the carbon capture unit;

[0201] Step 2.3: Calculate the total CO2 treatment cost C based on the CO2 emission cost and CO2 capture cost of the carbon capture unit. cbc for:

[0202] C cbc =C ne +C se +C de +C cd (25).

[0203] Step 3: Based on the differences in the response speed of multi-form high-energy loads, a two-stage low-carbon economic dispatch model (day-ahead and intraday) is constructed;

[0204] The specific process is:

[0205] Step 3.1: Construct the objective function and constraints of the day-ahead low-carbon economic model:

[0206] The objective function of the low-carbon economy model today is:

[0207] F1=min(C cg +C cb +C aw +C ls +C sy +C cbc +C cgc ) (26)

[0208]

[0209] Where, F1 is the total cost of the system’s low-carbon economy optimization dispatch operation on the day before; C cg is the operating cost of conventional thermal power units, C cbc is the total cost of CO2 treatment, U i (t) The start and stop status of conventional thermal power unit i at time t, a i 、b i 、c i is the coal consumption cost coefficient of conventional thermal power unit i, P cg,i (t) is the output of conventional thermal power unit i at time t; C cb is the operating cost of the carbon capture unit, U j (t) is the start and stop status of the carbon capture unit j at time t, a j 、b j 、c j is the coal consumption cost coefficient of carbon capture unit j, P cb,j (t) is the output of carbon capture unit j at time t; C aw is the cost of wind curtailment, K aw is the unit wind curtailment cost, P wfore(t) is the predicted wind power output at time t, P w (t) is the planned wind power output value at time t; C cgc is the total carbon emission cost of conventional thermal power units, K c is the unit carbon emission cost;

[0210] The constraints of the day-ahead low-carbon economy model include system power balance constraints, wind power output constraints, conventional unit output upper and lower limits constraints, conventional unit ramping constraints, system spinning reserve, carbon capture unit operation constraints, and carbon capture unit solution storage operation constraints. They are specifically expressed as follows:

[0211] 1) System power balance constraints:

[0212]

[0213] 2) Wind power output constraints:

[0214] 0≤P w (t)≤P wfore (t) (29)

[0215] 3) Upper and lower limits of conventional unit output:

[0216] U i (t)P cgmin,i ≤P cg,i (t)≤U i (t)P cgmax,i (30)

[0217] 4) Conventional unit climbing constraints:

[0218]

[0219] 5) System spinning reserve

[0220] The system's spinning reserve is shared by conventional thermal power units and carbon capture units:

[0221]

[0222] 6) Operational constraints of carbon capture units

[0223] According to the energy consumption characteristics of the carbon capture unit, the flue gas split ratio constraint, the carbon capture amount constraint, and the carbon capture equipment energy consumption constraints are considered. The energy consumption of the carbon capture equipment is mainly composed of two parts: fixed energy consumption and operating energy consumption. The mathematical model of the carbon capture unit is as follows:

[0224]

[0225] Where, P cg (t) is the normal load at time t, Ri up is the ramp rate of unit i, R i down Ramp rate of unit i; R down is the system negative spinning reserve, R up The system is spinning reserve; E cb,j (t) is the total amount of CO2 produced by carbon capture unit j at time t, K cd is the carbon emission intensity of the carbon capture unit, P cb,j (t) is the total output of carbon capture unit j at time t; state coefficient, P cj,j,max is the maximum output of carbon capture unit j; P Bj (t) is the operating energy consumption of carbon capture unit j at time t, λ is the unit energy consumption of capturing CO2; P cj,j (t) is the net output of carbon capture unit j at time t, P Dj is the fixed energy consumption of carbon capture unit j;

[0226] 7) Solution storage operation constraints

[0227] The solution in the solution storage of the carbon capture unit is ethanolamine solution. The mass of CO2 is calculated using the volume of the solution. The relationship expression is as follows:

[0228]

[0229] Where V CAi (t) is the volume of solution capturing CO2 by carbon capture unit i at time t, Q Gi (t) is the mass of CO2 captured by carbon capture unit i at time t, M EA is the molar mass of ethanolamine solution, M CO2 is the molar mass of CO2, M R is the concentration of ethanolamine solution, ρ R Density of ethanolamine solution;

[0230] The operating constraints of the solution storage of the carbon capture unit are:

[0231]

[0232] Where V Fi (t) is the volume of the solution in the rich liquid storage of carbon capture unit i at time t, V Pi (t) is the volume of the lean solution storage of carbon capture unit i at time t, V CAi (t) is the volume of solution capturing CO2 by carbon capture unit i at time t, V CAi is the maximum volume of the solution storage of carbon capture unit i.

[0233] Step 3.2: Construct the objective function and constraints of the intraday low-carbon economic model:

[0234] The objective function of the intraday low-carbon economy model is expressed as:

[0235] F2=min(C cn +C lx -C Δaw ) (36)

[0236]

[0237] Where, F2 is the total operating cost of the system during the day, C lx The continuous adjustable high energy load regulation cost, C cn is the operating cost of the energy storage system, C Δaw To reduce the cost of wind curtailment, K cn is the unit energy storage cost.

[0238] The constraints of the daily low-carbon economic model include the daily power regulation balance and energy storage system operation constraints, specifically:

[0239] 1) Intraday power regulation balance constraints

[0240] ΔP w (t) = P lx-up (t)-P lx-down (t)+P cha (t)-P dis (t) (38)

[0241] 2) Energy storage system operation constraints

[0242] Considering the state of charge constraints and charge and discharge power constraints of the energy storage system, its mathematical model is as follows:

[0243] Energy storage system state of charge and its expression:

[0244]

[0245]

[0246] Energy storage system charging and discharging constraints:

[0247]

[0248] Where ΔP W (t) is the difference between the wind power output value predicted within the day and the wind power output value planned on the day before, B soc is the state of charge of the energy storage system, E b is the current power of the energy storage system, C b is the total capacity of the energy storage system; Bsoc,min 、B soc,max are the minimum and maximum state of charge of the energy storage system, B soc (t) is the state of charge of the energy storage system at time t; B soc (t+1) is the state of charge of the energy storage system at time t+1; P cha (t) is the charging power of the energy storage system at time t, η cha is the charging efficiency, is the scheduling period; P dis (t) is the discharge power of the energy storage system at time t, η dis is the discharge efficiency; P cha,min 、P cha,max are the upper and lower limits of the energy storage system charging power respectively; P dis,min 、P dis,max are the upper and lower limits of the energy storage system discharge power respectively.

[0249] Step 4: In the day-ahead stage, the discrete and time-shifted high-energy load plan values and the wind power intraday forecast value are input into the day-ahead low-carbon economic model to obtain the day-ahead dispatch plan; in the intraday stage, the conventional load forecast, the time-shifted and time-shifted high-energy load plan values and the wind power day-ahead forecast value are input into the intraday low-carbon economic model to obtain the intraday dispatch plan.

[0250] Example

[0251] To verify the effectiveness of the method of the present invention, four different operating scenarios are set up for verification analysis:

[0252] Scenario 1. Traditional scheduling: The source side participates in system regulation, while the load side does not.

[0253] Scenario 2. Coordinated source-load dispatch: All thermal power units in the system are conventional units, and time-shifted and discrete adjustable high-energy loads participate in system regulation, implementing day-ahead low-carbon economic dispatch.

[0254] Scenario 3. Source-load coordinated scheduling considering the low-carbon characteristics of carbon capture units: The source side participates in system regulation, and one thermal power unit is converted to a carbon capture unit. Time-shifted and discrete adjustable high-energy loads participate in system regulation, implementing day-ahead low-carbon economic scheduling.

[0255] Scenario 4. Two-stage low-carbon economic dispatch: Based on Scenario 3, the system's continuous adjustable high-energy load and energy storage system participate in system regulation to carry out day-ahead and day-ahead low-carbon economic dispatch.

[0256] The improved IEEE-39 node system is analyzed by example. The system contains a 900MW wind farm and 4 thermal power units, of which G1 is a carbon capture power plant and the rest are conventional thermal power units. The thermal power unit parameters are detailed in Table 1, and the carbon capture equipment parameters are detailed in Table 2; the various adjustable high-energy load adjustment parameters are detailed in Table 3; the system is equipped with a 200MWh energy storage system, and its specific parameters are shown in Table 4; the load forecast diagram is detailed in Figure 2 , see the time-of-use electricity price chart for details. Figure 3 , the system's day-ahead wind power forecast and intraday wind power forecast are detailed in Figure 4 The problem studied in the invention belongs to a mixed integer linear programming problem, and the model is solved using the CPLEX solver.

[0257] Table 1

[0258]

[0259] Table 2

[0260]

[0261] Table 3

[0262]

[0263] Table 4

[0264]

[0265]

[0266] Specific operation process: Day-ahead stage: known quantities: conventional load forecast value, day-ahead wind power forecast value, discrete adjustable high energy load plan value, time-shifted discrete adjustable high energy load plan value, equipment parameters, time-of-use electricity price, etc. Quantity to be solved: actual operating output value of conventional units and carbon capture units, day-ahead wind power output value, discrete adjustable high energy load actual load value, time-shifted adjustable high energy load actual load value. Intraday stage: known quantities: intraday wind power forecast value, continuous adjustable high energy load plan value. Quantity to be solved: intraday wind power output value; continuous adjustable high energy load actual operating value, energy storage operation status. Both of the above processes input known quantities into the dispatching model, Figure 5-Figure 12 This is the scheduling result.

[0267] according to Figure 5-Figure 12 It can be seen that the day-ahead and intraday low-carbon economic dispatching method of the present invention, which takes into account multi-form high-energy loads, can simultaneously ensure the low-carbon and economic efficiency of the system on the basis of improving the wind power absorption level of the system, and provide a reference basis for power grid dispatching.

[0268] This invention considers the energy time-shifting and low-carbon characteristics of carbon capture units under integrated source-side operation, as well as the zero-carbon and low-cost nature of wind power. It integrates multi-modal high-energy loads on the load side with energy storage systems into a low-carbon economic dispatch plan, leveraging the low-carbon characteristics of both the source and the load. Furthermore, to mitigate the adverse effects of discrepancies between wind power's day-ahead output and intraday forecasts, the differences in the response characteristics of multi-modal high-energy loads are leveraged to rationally schedule their participation in the day-ahead and intraday dispatch plans.

[0269] Through the above approach, the present invention proposes a low-carbon, day-ahead, and intraday dispatching method for multi-modal high-energy loads. First, the operating characteristics of adjustable high-energy loads within the system are analyzed, and a refined mathematical model for these multi-modal high-energy loads is established. Next, by comprehensively considering the complementary low-carbon characteristics of the source and load sides and the varying response speeds of multi-modal high-energy loads on the demand side, and incorporating energy storage systems, a two-stage, day-ahead, and intraday low-carbon, economic dispatching model is established. Finally, a CPLEX solver is used to simulate and analyze the improved IEEE 39-node system. Results demonstrate that the proposed method improves the system's wind power absorption capacity while simultaneously ensuring low-carbon and economic efficiency, providing a reference for grid dispatch.

Claims

1. A low-carbon economic dispatch method for day-ahead and intraday considering multi-form high-energy loads, characterized by: Please follow the steps below to implement it: Step 1: Analyze the operating characteristics of multi-mode adjustable high-energy loads, classify them according to the differences in their response speeds, and perform refined modeling of the multi-mode high-energy loads; Step 2: Convert conventional units into carbon capture units with low-carbon characteristics, deeply explore their operating characteristics and low-carbon features, and establish a low-carbon operating cost model; Step 3: Based on the differences in the response speed of multi-form high-energy loads, a two-stage low-carbon economic dispatch model (day-ahead and intraday) is constructed; Step 4: Obtain a day-ahead and day-intraday low-carbon economic dispatch plan based on the day-ahead and day-intraday two-stage low-carbon economic dispatch model; The specific process of step 3 is as follows: Step 3.1: Construct the objective function and constraints of the day-ahead low-carbon economic model: The objective function of the day-ahead low-carbon economy model is: （26） （27） Where, F 1 is the total cost of the system's low-carbon economy optimization dispatch operation on the day before; C cg is the operating cost of conventional thermal power units, C cbc is the total cost of CO2 treatment, U i ( t ) Conventional thermal power units i exist t The start and stop status at all times, a i 、 b i 、 c i For conventional thermal power units i The coal consumption cost coefficient, P cg,i ( t ) is a conventional thermal power unit i exist t The effort of every moment; C cb is the operating cost of the carbon capture unit, U j ( t ) is a carbon capture unit j exist t The start and stop status at all times, a j 、 b j 、 c j Carbon capture unit j The coal consumption cost coefficient, P cb,j ( t ) is a carbon capture unit j exist t The effort of every moment; C aw is the cost of wind curtailment, K aw is the unit wind curtailment cost, P wfore ( t )for t Wind power forecast output at all times, P w ( t )for t The planned wind power output value at the moment; C cgc is the total carbon emission cost of conventional thermal power units, K c is the unit carbon emission cost; Step 3.2: Construct the objective function and constraints of the intraday low-carbon economic model: The objective function of the intraday low-carbon economic model is expressed as: （36） （37） Where, F 2 is the total operating cost of the system during the day, C lx It is a continuous adjustable high energy load regulation cost. C cn is the operating cost of the energy storage system, C Δaw To reduce the cost of wind curtailment, K cn is the unit energy storage cost.

2. The method for day-ahead and intraday low-carbon economic dispatch considering multi-form high-energy loads according to claim 1 is characterized in that: The multi-form adjustable high energy load operating characteristics described in step 1 include the operating characteristics of a continuous adjustable high energy load, the operating characteristics of a discrete adjustable high energy load, and the operating characteristics of a time-shifted adjustable high energy load.

3. The method for day-ahead and intraday low-carbon economic dispatch considering multi-form high-energy loads according to claim 2 is characterized in that: Step 1 classifies various adjustable high-energy loads according to their response speed differences, and conducts refined modeling of multi-form high-energy loads. Specifically, the following situations are included: 1) Modeling of a continuously adjustable high-energy load considering its operating characteristics and cost constraints: Power Constraints: （1） Upper and lower limit constraints of adjustment amount: （2） State constraints: （3） Adjustment times constraint: （4） Adjust duration constraints: （5） Planned output constraints: （6） Adjustment costs: （7） Where, P lsh ( t ) Discrete adjustable high energy load t The power of the moment, P ls-base ( t )for t The base load at the time, P ls-up ( t )for t The amount of increase in time, P ls-down ( t )for t The downward adjustment amount at the moment; S1( t ) is the discrete adjustable high energy load is in the upward state, S2( t ) means the load is in a downward adjustment state, P ls-up-min To increase the minimum value, P ls-up-max To increase the maximum value, P ls-down-min is the minimum value of the downward adjustment. P ls-down-max is the maximum value of the downward adjustment, M is the maximum number of adjustments; T 1 is the maximum duration of the increase, T 2 is the maximum down-regulation duration; λ i For the adjusted working efficiency, E ls-plan The planned daily output; C ls is the total load regulation cost, C ( t )for t Time-of-use electricity price for industrial load at all times, K ls ( t )for t Always respond to subsidy costs, T is the scheduling period; 2) Considering the operating characteristics and cost constraints of discrete adjustable high-energy loads, the following model is established: Power Constraints: （8） Output upper and lower limit constraints: （9） Adjust rate constraints: （10） Upper and lower limit constraints of adjustment amount: （11） State constraints: （12） Output constraints: （13） Adjustment costs: （14） Where, P lxh ( t ) is a continuous regulation high load energy load regulation t The power of the moment, P lx-base ( t ) is a continuous regulation of high energy load t The base load at the time, P lx-up ( t )for t Always increase the amount, P lx-down ( t )for t Always adjust the amount downward; P lx-min is the minimum output, P lx-max is the maximum output; P lxh-down To adjust the downhill speed, P lxh-up To adjust the uphill speed; S 3( t ) is the load increase decision variable, S 4( t ) is the load reduction decision variable; P lx-up-max is the maximum value of the load increase, P lx-up-min is the minimum value of the load increase, P lx-down-max is the maximum value of load reduction, P lxh-down-min is the minimum value of load reduction; λ k For the adjusted working efficiency, E lx-plan It is a continuous high-energy-load daily production plan; C lx To adjust the total cost of load, C ( t )for t Time-of-use electricity price for industrial load at all times, K lx ( t )for t Always respond to subsidy costs; 3) Considering the operating characteristics and cost constraints of the time-shifted adjustable high-energy load, the following model is established: Power Constraints: （15） Time-shifting time constraints: （16） Planned output constraints: （17） Adjustment costs: （18） Where, P syq ( t ) before adjustment t The load value at the moment, P syq ( t ) is after adjustment t The load size at the moment; λ j For the adjusted working efficiency, S 5( t ) is the time shift decision variable, 1 indicates that time shift occurs at this moment, and 0 indicates that time shift does not occur at this moment; T min is the minimum transfer duration constraint; E sy-plan It is a time-shifted high-energy load daily production plan; C sy To adjust the total cost of load, K sy ( t )for t Always respond to subsidy costs.

4. The method for day-ahead and intraday low-carbon economic dispatch considering multi-form high-energy loads according to claim 1 is characterized in that: The cost of the carbon capture unit with low carbon characteristics in step 2 is the coal consumption cost and the CO2 treatment cost. The coal consumption cost is the same as that of the conventional unit, and the CO2 treatment cost is divided into the CO2 emission cost and the CO2 capture cost.

5. The method for day-ahead and intraday low-carbon economic dispatch considering multi-form high-energy loads according to claim 4 is characterized in that: The CO2 treatment cost calculation process described in step 2 is: Step 2.1: The calculation process of CO2 emission cost of carbon capture unit is as follows: Carbon capture unit j exist t The total amount of CO2 captured at the moment is: （19） Carbon capture unit t The total amount of CO2 captured at the moment is: （20） The CO2 emission cost during the scheduling period is: （21） Where, E cb,j ( t ) is a carbon capture unit j exist t The total amount of CO2 produced at any given moment, K cd is the carbon emission intensity of the carbon capture unit, P cb,j ( t ) is a carbon capture unit j exist t Always make an effort; E j,total-co2 ( t ) is a carbon capture unit j The total amount of captured CO2, β The capture efficiency of carbon capture equipment; N cb is the number of carbon capture units, K c is the unit carbon emission cost; Step 2.2, CO2 capture cost of carbon capture unit: The CO2 capture cost includes energy consumption cost, depreciation cost and storage cost, and its specific expression is as follows: Energy consumption cost of carbon capture unit: （22） Depreciation cost of carbon capture unit: （23） Storage costs of carbon capture units: （24） Where, C ne is the energy consumption cost of the carbon capture power plant, P Dj ( t ) is the fixed energy consumption of the carbon capture unit, P Bj ( t ) is the operating energy consumption of the carbon capture unit, N cb is the number of carbon capture units; C ( t ) is the time-of-use electricity price for industrial loads; C zj is the depreciation cost, N zj is the depreciation period, α is the discount rate for carbon capture unit projects, C tb Total cost of capture equipment for carbon capture power plants; C ry is the unit volume solution storage cost, V ry is the volume of the solution reservoir, N ry Depreciation period of solution storage; K se is the unit CO2 storage cost, C se is the total storage cost of the carbon capture unit; Step 2.3: Calculate the total cost of CO2 treatment based on the CO2 emission cost and CO2 capture cost of the carbon capture unit. C cbc for: （25）。 6. The method for day-ahead and intraday low-carbon economic dispatch considering multi-form high-energy loads according to claim 5 is characterized in that: The constraints of the day-ahead low-carbon economic model include system power balance constraints, wind power output constraints, conventional unit output upper and lower limit constraints, conventional unit ramping constraints, system spinning reserve, carbon capture unit operation constraints, and carbon capture unit solution storage operation constraints, which are specifically expressed as follows: 1) System power balance constraints: （28） 2) Wind power output constraints: （29） 3) Upper and lower limits of conventional unit output: （30） 4) Conventional unit climbing constraints: （31） 5) System spinning reserve The system's spinning reserve is shared by conventional thermal power units and carbon capture units: （32） 6) Operational constraints of carbon capture units According to the energy consumption characteristics of the carbon capture unit, the flue gas split ratio constraint, the carbon capture amount constraint, and the carbon capture equipment energy consumption constraints are considered. The energy consumption of the carbon capture equipment is mainly composed of two parts: fixed energy consumption and operating energy consumption. The mathematical model of the carbon capture unit is as follows: （33） Where, P cg ( t )for t Normal load at all times, R i up For the crew i Climbing rate, R i down unit i Downhill climbing rate; R down Negative spinning reserve for the system, R up It is the system's positive spinning reserve; E cb,j ( t ) is a carbon capture unit j exist t The total amount of CO2 produced at any given moment, K cd is the carbon emission intensity of the carbon capture unit, P cb,j (t ) is a carbon capture unit j exist t Total output at any moment; state coefficient, P cj,j,max Carbon capture unit j Maximum output; P Bj ( t ) is a carbon capture unit j exist t The operating energy consumption at each moment, λ is the unit energy consumption for capturing CO2; P cj,j ( t ) is a carbon capture unit j exist t Net output at any moment, P Dj Carbon capture unit j Fixed energy consumption; 7) Solution storage operation constraints The solution in the solution storage of the carbon capture unit is ethanolamine solution. The mass of CO2 is calculated using the volume of the solution. The relationship expression is as follows: （34） Where, V CAi ( t ) is a carbon capture unit i exist t The volume of solution capturing CO2 at any given moment, Q Gi ( t ) is a carbon capture unit i exist t The quality of CO2 captured at any given moment, M EA is the molar mass of ethanolamine solution, M CO2 is the molar mass of CO2, M R is the concentration of ethanolamine solution, ρ R Density of ethanolamine solution; The operating constraints of the solution storage of the carbon capture unit are: （35） Where, V Fi ( t ) is a carbon capture unit i Rich liquid storage t The volume of the solution at time V Pi ( t ) is a carbon capture unit i Lean solution storage t The volume of the solution at time V CAi ( t ) is a carbon capture unit i exist t The volume of solution capturing CO2 at any given moment, V CAi Carbon capture unit i The maximum volume of the solution reservoir.

7. The method for day-ahead and intraday low-carbon economic dispatch considering multi-form high-energy loads according to claim 6 is characterized in that: The constraints of the intraday low-carbon economic model include intraday power regulation balance and energy storage system operation constraints, specifically: 1) Intraday power regulation balance constraints （38） 2) Energy storage system operation constraints Considering the state of charge constraints and charge and discharge power constraints of the energy storage system, its mathematical model is as follows: Energy storage system state of charge and its expression: （39） （40） Energy storage system charging and discharging constraints: （41） Where, Δ P W ( t ) is the difference between the wind power output value predicted within the day and the wind power output value planned on the previous day, B soc is the state of charge of the energy storage system, E b is the current power of the energy storage system, C b is the total capacity of the energy storage system; B soc,min 、 B soc,max are the minimum and maximum state of charge of the energy storage system, B soc ( t ) is the energy storage system t State of charge at the moment; B soc ( t +1) for energy storage system t +1 moment state of charge; P cha ( t ) is the energy storage system t Charging power at all times, η cha is the charging efficiency, is the scheduling period; P dis ( t ) is the energy storage system t Discharge power at all times, η dis is the discharge efficiency; P cha,min 、 P cha,max are the upper and lower limits of the energy storage system charging power respectively; P dis,min 、 P dis,max are the upper and lower limits of the energy storage system discharge power respectively.

8. The method for day-ahead and intraday low-carbon economic dispatch considering multi-form high-energy loads according to claim 1 is characterized in that: The specific process of step 4 is as follows: in the day-ahead stage, the discrete and time-shifted high-energy load plan values and the wind power intraday forecast value are input into the day-ahead low-carbon economic model to obtain the day-ahead dispatch plan; in the intraday stage, the conventional load forecast, time-shifted and time-shifted high-energy load plan values, and the wind power day-ahead forecast value are input into the intraday low-carbon economic model to obtain the intraday dispatch plan.

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