CN115330105A - Day-ahead-day low-carbon economic dispatching method considering polymorphic high energy-carrying load - Google Patents
Day-ahead-day low-carbon economic dispatching method considering polymorphic high energy-carrying load Download PDFInfo
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Abstract
The invention discloses a day-ahead-day low-carbon economic dispatching method considering polymorphic high-energy-carrying loads, which comprises the steps of firstly, analyzing the operating characteristics of the adjustable high-energy-carrying loads in a system, and establishing a polymorphic high-energy-carrying load refined mathematical model; then, comprehensively considering the complementary low-carbon characteristics of the two sides of the source load and the difference of the polymorphic high-energy-carrying load response speed of the demand side, and establishing a two-stage low-carbon economic optimization scheduling model in the day-ahead and day-in by combining with an energy storage system; the scheduling method of the invention carries out simulation analysis on the improved IEEE39 node system through a CPLEX solver. The results show that: the method provided by the invention can simultaneously ensure the low carbon property and the economical efficiency of the system on the basis of improving the wind power consumption level of the system, and provides a reference basis for power grid dispatching.
Description
Technical Field
The invention belongs to the technical field of improving low carbon and economy of a wind power system, and particularly relates to a day-ahead-day low carbon economic dispatching method considering multi-form high energy load.
Background
The realization of the double-carbon target can lead the wind power with low marginal cost of power generation and no carbon emission to be developed rapidly. According to data of ' 2020 Power statistics basic data List ' issued by the China Union of electric Power enterprises ' society, the installed capacity of wind power reaches 28165 ten thousand kilowatts in 2020, and the installed capacity of wind power is increased by 34.66% on a same scale. The wind power output has daytime difference, uncertainty and anti-peak-shaving characteristics, and the large-scale grid connection of the wind power output can cause a large gap to exist in a power system adjusting power supply. At present, the high energy-carrying load is mainly researched on the aspect of monomorphic high energy-carrying load, and the analysis on the polymorphous high energy-carrying load is relatively rare. Therefore, in order to more accurately mine the adjustment potential and flexibility of the resources on the demand side of the system, the method has profound significance in using the polymorphic high-energy-carrying load as an adjustment means for scheduling the wind power-containing system.
Disclosure of Invention
The invention aims to provide a day-ahead-day low-carbon economic dispatching method considering polymorphic high-energy-carrying load, which can improve the wind power consumption level of a system and ensure the low-carbon property and economy of the system.
The technical scheme adopted by the invention is that a polymorphic high-energy-load day-ahead low-carbon economic dispatching method is considered, and the method is implemented according to the following steps:
step 3, constructing a two-stage low-carbon economic dispatching model in the day-ahead and day-in based on the difference of polymorphic high-energy-carrying load response speeds;
and 4, obtaining a day-ahead low-carbon economic dispatching plan according to the day-ahead two-stage low-carbon economic dispatching model.
The invention is also characterized in that:
the operation characteristics of the polymorphic adjustable high-load in the step 1 comprise the operation characteristics of a continuous adjustable high-load, the operation characteristics of a discrete adjustable high-load and the operation characteristics of a time-shifting adjustable high-load.
The step 1 of classifying according to the difference of the response speed of various types of adjustable high energy-carrying loads, and carrying out fine modeling on the polymorphic high energy-carrying loads specifically comprises the following conditions:
1) Modeling the continuous adjustable high-energy-load by considering the operating characteristics and cost constraint of the load:
and (3) power constraint:
P lsh (t)＝P ls-base (t)+P ls-up (t)-P ls-down (t) (1)
and (4) limiting the upper limit and the lower limit of the regulating quantity:
and (3) state constraint:
S 1 (t)+S 2 (t)≤1 (3)
and (4) regulating times constraint:
adjusting the duration constraint:
and (4) planning yield constraint:
adjusting the cost:
in the formula, P lsh (t) Power, P, of discrete adjustable high energy-carrying load at time t ls-base (t) is the base load at time t, P ls-up (t) is the amount of up-regulation at time t, P ls-down (t) is the down-regulation amount at time t; s 1 (t) the discrete adjustable high energy-carrying load is in an up-regulation state, S 2 (t) the load is in a down-regulated state, P ls-up-min To adjust up the minimum value, P ls-up-max To up-regulate the maximum, P ls-down-min To adjust the minimum value of the quantity, P ls-down-max The maximum value of the down regulation quantity is, and M is the maximum regulation frequency; t is 1 For maximum duration of upregulation, T 2 Maximum duration of down-regulation; lambda [ alpha ] i For adjusted operating efficiency, E ls-plan Planning production for a day; c ls For the total cost of load regulation, C (t) is the time-of-use electricity price of the industrial load at time t, K ls (T) response subsidy cost at time T, and T is scheduling period;
2) The operation characteristics and cost constraints of the discrete adjustable high-energy-carrying load are considered to be modeled as follows:
and (3) power constraint:
P lxh (t)＝P lx-base (t)+P lx-up (t)-P lx-down (t) (8)
and (4) constraint of upper and lower output limits:
P lx-min ≤P lxh (t)≤P lx-max (9)
adjusting rate constraints:
P lxh-down ≤P lxh (t)-P lxh (t-1)≤P lxh-up (10)
and (3) restricting the upper limit and the lower limit of the regulating quantity:
and (3) state constraint:
S 1 (t)+S 2 (t)≤1 (12)
and (3) yield constraint:
adjusting the cost:
in the formula, P lxh (t) continuous regulation of the power at time t after the regulation of the high-energy-carrying load, P lx-base (t) base load at time t of continuously adjusting high energy load, P lx-up (t) is the amount of up-regulation at time t, P lx-down (t) is the down-regulation quantity at t time; p lx-min To minimum value of force, P lx-max Is the maximum value of the output; p lxh-down To adjust the downhill speed, P lxh-up To adjust the rate of uphill; s 3 (t) is a load up decision variable, S 4 (t) is a load down-regulation decision variable; p lx-up-max Is the maximum value of the load up-regulation quantity, P lx-up-min Is the minimum value of the load up-regulation quantity, P lx-down-max Is the maximum value of the load turndown, P lxh-down-min Is the minimum value of the load down-regulation quantity; lambda [ alpha ] k For adjusted operating efficiency, E lx-plan A continuous high-energy-load daily production plan is formed; c lx For adjusting the total cost of the load, C (t) is the time-of-use electricity price of the industrial load at the moment t, K lx (t) response subsidy cost at time t;
3) The operation characteristics and cost constraints of the time-shifting type adjustable high-energy-carrying load are considered to be modeled as follows:
and (3) power constraint:
P syh (t)＝S 5 (t)P syq (t) (15)
time shift time constraint:
and (4) planning yield constraint:
adjusting the cost:
in the formula, P syq (t) is the load value at time t before adjustment, P syq (t) is the load size at the time t after adjustment; lambda [ alpha ] j For adjusted working efficiency, S 5 (t) is a time shift decision variable, wherein 1 represents that the time shift occurs at the moment, and 0 represents that the time shift does not occur at the moment; t is min Is a minimum transfer duration constraint; e sy-plan A time-shifting type daily production plan with high energy-carrying load is provided; c sy To adjust the total cost of the load, K sy And (t) the response subsidy cost at the time t.
CO in step 2 2 The processing cost calculation process comprises the following steps:
step 2.1, carbon capture unit CO 2 The emission cost calculation process is as follows:
carbon capture unit j at time t CO 2 The total capture volume of (a) is:
E cb,j (t)＝K cd P cb,j (t) (19)
carbon capture unit CO at t moment 2 The total capture volume of (a) is:
CO in scheduling period 2 The emission cost is as follows:
in the formula, E cb,j (t) CO production by the carbon capture unit j at time t 2 Total amount of (A), K cd To carbon emission intensity of carbon capture unit, P cb,j (t) is the total output of the carbon trapping unit j at the moment t; e j,total-co2 (t) CO Capture for carbon Capture Unit j 2 Beta is the carbon capture equipment capture efficiency; n is a radical of cb The number of carbon capture units, K c Is the unit carbon emission cost;
step 2.2, carbon capture unit CO 2 The trapping cost is as follows:
CO 2 the trapping cost comprises energy consumption cost, depreciation cost and sealing cost, and the specific expression is as follows:
the carbon trapping unit has the following trapping energy consumption cost:
the carbon capture unit capture depreciation cost:
the carbon capture unit sealing cost:
in the formula, C ne For carbon capture of power plant energy costs, P Dj (t) fixed energy consumption of carbon capture unit, P Bj (t) energy consumption for operation of the carbon capture unit, N cb The number of carbon trapping units; c (t) is the time-of-use electricity price of the industrial load; c zj For depreciation of cost, N zj For depreciation years, alpha is the item impression rate of the carbon capture unit, C tb Total cost of capture equipment for a carbon capture power plant; c ry Cost per unit volume of solution reservoir, V ry Is the volume of the solution reservoir, N ry Age of solution storage; k is se Is in the unit of CO 2 Cost of sealing, C se The total cost for the carbon capture unit sealing;
step 2.3, according to the CO of the carbon capture unit 2 Emission cost, carbon capture unit CO 2 CO capture cost calculation 2 Total cost of treatment C cbc Comprises the following steps:
C cbc ＝C ne +C se +C de +C cd (25)
the specific process of the step 3 is as follows:
step 3.1, establishing a day-ahead low-carbon economic model objective function and day-ahead low-carbon economic model constraint conditions:
the day-ahead low-carbon economic model objective function is as follows:
F 1 ＝min(C cg +C cb +C aw +C ls +C sy +C cbc +C cgc ) (26)
in the formula, F 1 Optimizing and scheduling the total running cost for the low-carbon economy of the system day ahead; c cg For the running cost of a conventional thermal power unit, C cbc Is CO 2 Total cost of treatment, U i (t) Start-stop state of conventional thermal power generating unit i at time t, a i 、b i 、c i Is the coal consumption cost coefficient, P, of the conventional thermal power generating unit i cg,i (t) is a constantThe power output of the conventional power generating unit i at the moment t; c cb For the operating cost of the carbon capture unit, U j (t) is the start-stop state of the carbon capture unit j at the moment t, a j 、b j 、c j Is the coal consumption cost coefficient, P, of the carbon capture unit j cb,j (t) is the output of the carbon capture unit j at the time t; c aw To abandon the cost of wind, K aw Cost per unit of wind abandoned, P wfore (t) predicted wind power output at time t, P w (t) is a planned value of the wind power day-ahead output at the moment t; c cgc The total cost of carbon emission of the conventional thermal power generating unit, K c Is the unit carbon emission cost;
step 3.2, establishing an intra-day low-carbon economic model objective function and intra-day low-carbon economic model constraint conditions:
the low-carbon economic model objective function in the day is expressed as:
F 2 ＝min(C cn +C lx -C Δaw ) (36)
in the formula, F 2 Is the total operating cost of the system in the intra-day phase, C lx Adjusting the cost for a continuous type adjustable high energy load, C cn For operating the energy storage system, C Δaw To reduce the cost of air waste, K cn Is the unit energy storage cost.
The day-ahead low-carbon economic model constraint conditions comprise system power balance constraint, wind power output constraint, conventional unit output upper and lower limit constraint, conventional unit climbing constraint, system rotation standby, carbon capture unit operation constraint and carbon capture unit solution storage device operation constraint, and are specifically represented as follows:
1) System power balance constraint:
2) Wind power output restraint:
0≤P w (t)≤P wfore (t) (29)
3) The upper limit and the lower limit of the output of the conventional unit are restricted:
U i (t)P cgmin,i ≤P cg,i (t)≤U i (t)P cgmax,i (30)
4) Conventional unit climbing restraint:
5) System spinning reserve
The system rotation standby is jointly borne by a conventional thermal power generating unit and a carbon capturing unit:
6) Carbon capture unit operational constraints
According to the energy consumption characteristics of the carbon capture unit, considering flue gas split ratio constraint, carbon capture amount constraint and carbon capture equipment energy consumption related constraint, wherein the carbon capture equipment energy consumption mainly comprises two parts of fixed energy consumption and running energy consumption, and the mathematical model of the carbon capture unit is as follows:
in the formula, P cg (t) is the normal load at time t, R i up For the rate of ascent of unit i, R i down The climbing rate of the unit i; r is down For negative rotation of the system, R up The system rotates forwards for standby; e cb,j (t) CO is generated by the carbon capture unit j at the moment t 2 Total amount of (A), K cd To carbon emission intensity of carbon capture unit, P cb,j (t) is the total output of the carbon capture unit j at the moment t; coefficient of state, P cj,j,max The maximum output of the carbon capture unit j; p Bj (t) is the operating energy of the carbon capture unit j at the time tLambda is trapped CO 2 Specific energy consumption of (2); p is cj,j (t) is the net output of the carbon capture unit j at time t, P Dj The fixed energy consumption of the carbon capture unit j;
7) Solution reservoir operational constraints
The solution in the solution storage of the carbon capture unit is ethanolamine solution, and the volume of the solution is used for calculating CO 2 The relational expression of (c) is as follows:
in the formula, V CAi (t) the carbon capture unit i captures CO at the moment t 2 Volume of solution of (2), Q Gi (t) the carbon capture unit i captures CO at the moment t 2 Mass of (A), M EA Molar mass of ethanolamine solution, M CO2 Is CO 2 Molar mass, M R Is ethanolamine solution concentration, ρ R Density of ethanolamine solution;
the operation constraint of the solution storage device of the carbon capture unit is as follows:
in the formula, V Fi (t) is the solution volume of the rich solution storage of the carbon capture unit i at the time t, V Pi (t) solution volume of lean solution storage of carbon capture unit i at t moment, V CAi (t) the carbon capture unit i captures CO at the moment t 2 Volume of solution of (D), V CAi The maximum volume of the solution storage of the carbon capture unit i.
The constraint conditions of the intra-day low-carbon economic model comprise intra-day power regulation balance and energy storage system operation constraint, and specifically comprise the following steps:
1) Intraday power regulation balance constraint
ΔP w (t)＝P lx-up (t)-P lx-down (t)+P cha (t)-P dis (t) (38)
2) Energy storage system operation constraints
Considering the charge state constraint and the charge-discharge power constraint of the energy storage system, the mathematical model is as follows:
the state of charge of the energy storage system and an expression thereof:
and (3) charge and discharge restraint of the energy storage system:
in the formula,. DELTA.P W (t) is the difference between the predicted wind output value in the day and the wind output value planned in the day before, B soc To the state of charge of the energy storage system, E b Is the current moment electric quantity of the energy storage system, C b The total capacity of the energy storage system; b is soc,min 、B soc,max Respectively minimum and maximum values of the 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 is soc (t + 1) is the state of charge of the energy storage system at the moment t + 1; p cha (t) is charging power of the energy storage system at time t, eta cha For charging efficiency, for scheduling period; p dis (t) is the discharge power of the energy storage system at time t, eta dis To the discharge efficiency; p cha,min 、P cha,max Respectively charging the upper limit and the lower limit of the energy storage system; p dis,min 、P dis,max Respectively the upper and lower limits of the discharge electric power of the energy storage system.
The specific process of the step 4 is as follows: in the day-ahead stage, inputting the discrete type and time-shifted type high-energy-carrying load plan values and the wind power intra-day predicted values into a day-ahead low-carbon economic model to obtain a day-ahead scheduling plan; and in the in-day stage, inputting the conventional load prediction, the time-shifting type and time-shifting type high-energy-load planning values and the predicted value of the wind power day ahead into an in-day low-carbon economic model to obtain an in-day scheduling plan.
The invention has the beneficial effects that:
the invention considers a day-ahead-day low-carbon economic dispatching method of polymorphic high-energy-carrying loads, considers the energy time shift and low-carbon characteristics of a carbon capture unit and the wind power zero-carbon and low-cost characteristics in a source-side comprehensive operation mode, and jointly brings the polymorphic high-energy-carrying loads and an energy storage system on a charge side into a low-carbon economic dispatching plan to realize the low-carbon characteristic excavation on two sides of the source load. Meanwhile, in order to reduce adverse effects brought by planned output before the day of wind power and predicted value errors in the day, the scheduling plans participating in two different periods before the day and in the day are reasonably arranged through the difference of the response characteristics of the polymorphic high-energy-carrying load, and then a two-stage day-before-day low-carbon economic scheduling method of the wind power system considering the polymorphic high-energy-carrying load is provided.
Drawings
FIG. 1 is a flow chart of a day-ahead-day low carbon economic dispatch method considering polymorphic high energy loads;
FIG. 2 is a graph of load prediction in an embodiment of the present invention;
FIG. 3 is a graph of time-of-charge electricity rates in an embodiment of the present invention;
FIG. 4 is a diagram of wind power prediction before the system day and wind power prediction within the system day in the embodiment of the invention;
FIG. 5 shows an embodiment of the present invention, in which the discrete adjustable high energy-carrying load adjustment condition and the time-of-use electricity price condition are set;
FIG. 6 is a diagram illustrating an embodiment of a time-shifting adjustable high energy load adjustment;
FIG. 7 shows the output of each unit of the system according to the embodiment of the present invention;
FIG. 8 shows the carbon dioxide capture amount and the time-of-use electricity price of the carbon capture unit in the embodiment of the present invention;
FIG. 9 illustrates a continuous adjustable high energy load adjustment condition according to an embodiment of the present invention;
FIG. 10 illustrates an embodiment of the present invention;
FIG. 11 is a diagram illustrating system error adjustment in an embodiment of the present invention;
fig. 12 is a comparison chart of the participation of the system load in scheduling in the embodiment of the present invention.
Detailed Description
The invention is described in detail below with reference to the drawings and the detailed description.
And taking the energy time shifting and low-carbon characteristics of the carbon capture unit and the zero-carbon and low-cost characteristics of wind power into consideration in the source side comprehensive operation mode, and jointly incorporating the polymorphic high-energy-carrying load on the load side and the energy storage system into a low-carbon economic dispatching plan to realize the low-carbon characteristic excavation on both sides of the source load. Meanwhile, in order to reduce adverse effects caused by errors of planned output of the wind power day ahead and predicted values in the day, the polymorphic high-energy-load response characteristics are differentiated to reasonably arrange to participate in scheduling plans of two different time periods in the day ahead and in the day, and therefore the polymorphic high-energy-load-bearing two-stage day-day low-carbon economic scheduling method for the wind power system is provided in consideration of the polymorphic high-energy-load.
The invention relates to a day-ahead-day low-carbon economic dispatching method considering polymorphic high energy-carrying load, which is specifically implemented according to the following steps as shown in figure 1:
1) Modeling the continuous adjustable high-energy-load by considering the operating characteristics and cost constraint of the load:
and (3) power constraint:
P lsh (t)＝P ls-base (t)+P ls-up (t)-P ls-down (t) (1)
and (3) restricting the upper limit and the lower limit of the regulating quantity:
and (3) state constraint:
S 1 (t)+S 2 (t)≤1 (3)
and (4) regulating times constraint:
adjusting the duration constraint:
and (4) planning yield constraint:
adjusting the cost:
in the formula, P lsh (t) discrete adjustable high energy load power at time t, P ls-base (t) is the base load at time t, P ls-up (t) is the amount of up-regulation at time t, P ls-down (t) is the down-regulation amount at time t; s 1 (t) the discrete adjustable high energy-carrying load is in an up-regulation state, S 2 (t) the load is in a down-regulated state, P ls-up-min To adjust up the minimum value, P ls-up-max To adjust the maximum value, P ls-down-min To adjust the minimum value of the quantity, P ls-down-max The maximum value of the down regulation quantity is obtained, and M is the maximum regulation frequency; t is 1 For maximum duration of upregulation, T 2 Maximum duration of down-regulation; lambda [ alpha ] i For adjusted operating efficiency, E ls-plan Planning production for a day; c ls For the total cost of load regulation, C (t) is the time-of-use electricity price of the industrial load at time t, K ls (T) response subsidy cost at time T, and T is a scheduling period;
2) The operation characteristics and cost constraints of the discrete adjustable high-energy-carrying load are considered to be modeled as follows:
and (3) power constraint:
P lxh (t)＝P lx-base (t)+P lx-up (t)-P lx-down (t) (8)
and (3) restraining an upper limit and a lower limit of output:
P lx-min ≤P lxh (t)≤P lx-max (9)
adjusting the rate constraint:
P lxh-down ≤P lxh (t)-P lxh (t-1)≤P lxh-up (10)
and (3) restricting the upper limit and the lower limit of the regulating quantity:
and (3) state constraint:
S 1 (t)+S 2 (t)≤1 (12)
and (3) yield constraint:
adjusting the cost:
in the formula, P lxh (t) continuously adjusting the power at time t after the high energy-carrying load adjustment, P lx-base (t) base load at time t of continuously adjusting high energy load, P lx-up (t) is the amount of up-regulation at time t, P lx-down (t) is the down-regulation quantity at t time; p lx-min To minimum value of force, P lx-max Is the maximum value of the output; p is lxh-down To adjust the downhill speed, P lxh-up To adjust the rate of uphill; s 3 (t) load Up adjustmentPolicy variable, S 4 (t) is a load down-regulation decision variable; p lx-up-max Is the maximum value of the load up-regulation quantity, P lx-up-min Is the minimum value of the load up-regulation quantity, P lx-down-max Is the maximum value of the load turndown, P lxh-down-min Is the minimum value of the load down-regulation quantity; lambda [ alpha ] k For adjusted operating efficiency, E lx-plan A continuous high-energy-load daily production plan is formed; c lx C (t) is the time-of-use electricity price of the industrial load at the moment t, K, in order to adjust the total cost of the load lx (t) response subsidy cost at time t;
3) The operation characteristics and cost constraints of the time-shifting type adjustable high-energy-carrying load are considered to be modeled as follows:
and (3) power constraint:
P syh (t)＝S 5 (t)P syq (t) (15)
time shift time constraint:
and (4) planning yield constraint:
adjusting the cost:
in the formula, P syq (t) is the load value at time t before adjustment, P syq (t) is the load size at the time t after adjustment; lambda [ alpha ] j For adjusted working efficiency, S 5 (t) is a time shift decision variable, wherein 1 represents that the time shift occurs at the moment, and 0 represents that the time shift does not occur at the moment; t is min A minimum transfer duration constraint; e sy-plan A time-shifting type daily production plan with high energy-carrying load is provided; c sy To adjust the total cost of the load, K sy (t) cost of subsidy for response at time t。
in the invention, the cost of the carbon capture unit is mainly considered by the coal consumption cost and CO 2 The cost of the treatment. The coal consumption cost is the same as that of the conventional unit, and the description is omitted here; CO 2 2 Cost of treatment divided into CO 2 Emission cost and CO 2 And (4) trapping cost. Wherein, CO 2 Emission cost is derived from CO emitted directly into the atmosphere through flue gas 2 CO discharged into the atmosphere after being discharged into the absorption tower 2 The discharge cost is composed of two parts.
CO 2 The processing cost calculation process comprises the following steps:
step 2.1, carbon capture unit CO 2 The emission cost calculation process is as follows:
carbon capture unit j CO at time t 2 The total capture volume of (a) is:
E cb,j (t)＝K cd P cb,j (t) (19)
carbon capture unit CO at t moment 2 The total capture volume of (a) is:
CO in scheduling period 2 The discharge cost is as follows:
in the formula, E cb,j (t) CO production by the carbon capture unit j at time t 2 Total amount of (1), K cd To carbon emission intensity of carbon capture unit, P cb,j (t) is the total output of the carbon trapping unit j at the moment t; e j,total-co2 (t) CO Capture for carbon Capture Unit j 2 Beta is the carbon capture equipment capture efficiency; n is a radical of cb Number of carbon capturing units, K c Is the unit carbon emission cost;
step 2.2, carbon capture unit CO 2 The trapping cost is as follows:
CO 2 the trapping cost comprises energy consumption cost, depreciation cost and sealing cost, and the specific expression is as follows:
the carbon trapping unit is used for trapping energy consumption cost:
the carbon capture unit capture depreciation cost:
the carbon capture unit sealing cost:
in the formula, C ne For carbon capture of power plant energy costs, P Dj (t) fixed energy consumption of carbon capture unit, P Bj (t) energy consumption for operation of the carbon capture unit, N cb The number of carbon trapping units; c (t) is the time-of-use electricity price of the industrial load; c zj For depreciation costs, N zj For depreciation years, alpha is the item discount rate of the carbon capture unit, C tb The total cost of the carbon capture plant capture equipment; c ry Cost per unit volume of solution reservoir, V ry Is the volume of the solution reservoir, N ry Age of solution storage; k se Is in the unit of CO 2 Cost of sequestration, C se The total cost for the carbon capture unit sealing;
step 2.3, according to the CO of the carbon capture unit 2 Emission cost, carbon capture unit CO 2 CO capture cost calculation 2 Total cost of treatment C cbc Comprises the following steps:
C cbc ＝C ne +C se +C de +C cd (25)。
step 3, constructing a two-stage low-carbon economic dispatching model in the day-ahead and day-in based on the difference of polymorphic high-energy-carrying load response speeds;
the specific process is as follows:
step 3.1, establishing a day-ahead low-carbon economic model objective function and day-ahead low-carbon economic model constraint conditions:
the day-ahead low-carbon economic model objective function is as follows:
F 1 ＝min(C cg +C cb +C aw +C ls +C sy +C cbc +C cgc ) (26)
in the formula, F 1 The total running cost is optimized and scheduled for the day-ahead low-carbon economy of the system; c cg For the operating costs of conventional thermal power units, C cbc Is CO 2 Total cost of treatment, U i (t) Start-stop state of conventional thermal power generating unit i at time t, a i 、b i 、c i Is the coal consumption cost coefficient, P, of the conventional thermal power generating unit i cg,i (t) the output of a conventional thermal power generating unit i at the moment t; c cb For the operating cost of the carbon capture unit, U j (t) is the start-stop state of the carbon capture unit j at the moment t, a j 、b j 、c j Is the coal consumption cost coefficient, P, of the carbon capture unit j cb,j (t) is the output of the carbon capture unit j at the time t; c aw To discard the wind cost, K aw Cost per unit of wind abandoned, P wfore (t) predicted wind power output at time t, P w (t) is a planned value of the wind power day-ahead output at the moment t; c cgc The total cost of carbon emission of the conventional thermal power generating unit, K c Is the unit carbon emission cost;
the day-ahead low-carbon economic model constraint conditions comprise system power balance constraint, wind power output constraint, conventional unit output upper and lower limit constraint, conventional unit climbing constraint, system rotation standby, carbon capture unit operation constraint and carbon capture unit solution storage device operation constraint, and are specifically represented as follows:
1) System power balance constraint:
2) Wind power output constraint:
0≤P w (t)≤P wfore (t) (29)
3) The upper limit and the lower limit of the output of the conventional unit are restricted:
U i (t)P cgmin,i ≤P cg,i (t)≤U i (t)P cgmax,i (30)
4) Conventional unit climbing restraint:
5) System spinning reserve
The system rotation standby is jointly borne by a conventional thermal power generating unit and a carbon capturing unit:
6) Carbon capture unit operational constraints
According to the energy consumption characteristics of the carbon capture unit, considering flue gas split ratio constraint, carbon capture amount constraint and carbon capture equipment energy consumption related constraint, wherein the carbon capture equipment energy consumption mainly comprises fixed energy consumption and running energy consumption, and the mathematical model of the carbon capture unit is as follows:
in the formula, P cg (t) is the normal load at time t, R i up For the rate of ascent of unit i, R i down The climbing rate of the unit i; r down For negative rotation of the system, R up Is a system isRotating for standby; e cb,j (t) CO is generated by the carbon capture unit j at the moment t 2 Total amount of (A), K cd To carbon emission intensity of carbon capture unit, P cb,j (t) is the total output of the carbon capture unit j at the moment t; coefficient of state, P cj,j,max The maximum output of the carbon capture unit j; p Bj (t) is the running energy consumption of the carbon capture unit j at the moment t, and lambda is the captured CO 2 Specific energy consumption of (2); p cj,j (t) is the net output of the carbon capture unit j at time t, P Dj The fixed energy consumption of the carbon capture unit j;
7) Solution reservoir operational constraints
The solution in the solution storage of the carbon capture unit is ethanolamine solution, and the volume of the solution is used for calculating CO 2 The relational expression of (c) is as follows:
in the formula, V CAi (t) the carbon capture unit i captures CO at the moment t 2 Volume of solution of (2), Q Gi (t) capturing CO for the carbon capture unit i at the moment t 2 Mass of (A), M EA Molar mass of ethanolamine solution, M CO2 Is CO 2 Molar mass, M R As ethanolamine solution concentration, p R Density of ethanolamine solution;
the operation constraint of the solution storage device of the carbon capture unit is as follows:
in the formula, V Fi (t) is the solution volume of the rich liquor storage of the carbon capture unit i at the time t, V Pi (t) is the solution volume of the lean solution storage of the carbon capture unit i at the time t, V CAi (t) the carbon capture unit i captures CO at the moment t 2 Volume of solution of (D), V CAi The maximum volume of the solution storage of the carbon capture unit i.
Step 3.2, establishing an intra-day low-carbon economic model objective function and intra-day low-carbon economic model constraint conditions:
the objective function of the intraday low-carbon economic model is expressed as follows:
F 2 ＝min(C cn +C lx -C Δaw ) (36)
in the formula, F 2 Is the total operating cost of the system in the intra-day phase, C lx Adjusting the cost for a continuous type adjustable high energy load, C cn For operating the energy storage system, C Δaw To reduce the cost of air waste, K cn Is the unit energy storage cost.
The constraint conditions of the intra-day low-carbon economic model comprise intra-day power regulation balance and energy storage system operation constraint, and specifically comprise the following steps:
1) Intraday power regulation balance constraint
ΔP w (t)＝P lx-up (t)-P lx-down (t)+P cha (t)-P dis (t) (38)
2) Energy storage system operation constraints
Considering the charge state constraint and the charge-discharge power constraint of the energy storage system, the mathematical model is as follows:
the state of charge of the energy storage system and an expression thereof:
and (3) charge and discharge restraint of the energy storage system:
in the formula,. DELTA.P W (t) is in the dayDifference between predicted wind output and planned wind output in the day-ahead, B soc To the state of charge of the energy storage system, E b Is the current moment electric quantity of the energy storage system, C b The total capacity of the energy storage system; b soc,min 、B soc,max Respectively minimum and maximum values of the 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 the moment t + 1; p cha (t) is charging power of the energy storage system at time t, eta cha For charging efficiency, for scheduling period; p dis (t) is the discharge power of the energy storage system at time t, eta dis To discharge efficiency; p cha,min 、P cha,max Respectively charging the upper limit and the lower limit of the energy storage system; p dis,min 、P dis,max Respectively the upper and lower limits of the discharge electric power of the energy storage system.
Examples
In order to verify the effectiveness of the method, 4 different operation scenes are set for verification analysis:
and 3, considering source-load coordination scheduling of the low-carbon characteristic of the carbon capture unit: the source side participates in system adjustment, a thermal power generating unit is transformed into a carbon capture unit, time-shifting type adjustable high energy-carrying load and discrete type adjustable high energy-carrying load participate in system adjustment, and day-ahead low-carbon economic dispatching is carried out;
Carrying out example analysis on an improved IEEE-39 node system, wherein the system comprises a 900MW wind power plant and 4 thermal power generating units, G1 is a carbon capture power plant, the rest are conventional thermal power generating units, the parameters of the thermal power generating units are detailed in a table 1, and the parameters of carbon capture equipment are detailed in a table 2; various adjustable high energy-carrying load adjusting parameters are detailed in a table 3; the system is provided with a 200MWh energy storage system, and the specific parameters are shown in a table 4; the load prediction diagram is detailed in fig. 2, the charge time-of-use electricity price diagram is detailed in fig. 3, and the wind power prediction before the system day and the wind power prediction in the day are detailed in fig. 4. The problem researched by the invention belongs to the mixed integer linear programming problem, and the model is solved by using a CPLEX solver.
TABLE 1
TABLE 2
TABLE 3
TABLE 4
The specific operation process comprises the following steps: a day-ahead stage: known amounts are: the system comprises a conventional load predicted value, a day-ahead wind power predicted value, a discrete type adjustable high-energy-load plan value, a time-shifting type discrete type adjustable high-energy-load plan value, equipment parameters, time-of-use electricity price and the like. Solving quantity: actual operation output values of a conventional unit and a carbon capture unit, a day-ahead wind power output value, a discrete adjustable high-load-capacity load actual load value and a time-shifting adjustable high-load-capacity load actual load value. In the in-day period: known amounts are: the wind power predicted value in the day and the continuous adjustable high energy load planning value. Solving quantity: the wind power output value in the day; the continuous type can adjust the actual operation value and the energy storage operation condition of the high-energy-carrying load. Both of the above processes are to input the known quantity into the scheduling model, and fig. 5-12 are just the scheduling result.
According to the fig. 5-12, the method for scheduling the low-carbon economic load in the day before and in the day with consideration of the polymorphic high energy-carrying load can simultaneously ensure the low-carbon property and the economical efficiency of the system and provide a reference basis for the scheduling of the power grid on the basis of improving the wind power consumption level of the system.
The invention considers the energy time shifting and low carbon characteristics of the carbon capture unit in a source side comprehensive operation mode and the zero carbon and low cost characteristics of wind power, combines a multi-form high energy-carrying load and an energy storage system on a load side into a low carbon economic dispatching plan, and realizes the low carbon characteristic mining on both sides of the source load. Meanwhile, in order to reduce adverse effects caused by planned output before the day of wind power and predicted value errors in the day, the scheduling plans participating in two different time periods before the day and in the day are reasonably arranged through the difference of polymorphic high-energy-carrying load response characteristics.
By the mode, the method for scheduling the high-energy-carrying load in the day-ahead and day-in low-carbon economy considering the polymorphic high-energy-carrying load comprises the steps of firstly analyzing the operating characteristics of the adjustable high-energy-carrying load in the system and establishing a polymorphic high-energy-carrying load refined mathematical model; then, comprehensively considering the complementary low-carbon characteristics of the two sides of the source load and the difference of the polymorphic high-energy-carrying load response speed of the demand side, and establishing a two-stage low-carbon economic optimization scheduling model in the day-ahead and day-in by combining with an energy storage system; and finally, carrying out simulation analysis on the improved IEEE39 node system by using a CPLEX solver. The results show that: the method provided by the invention can simultaneously ensure the low carbon property and the economical efficiency of the system on the basis of improving the wind power consumption level of the system, and provides a reference basis for power grid dispatching.
Claims (9)
1. The day-ahead-day low-carbon economic dispatching method considering the polymorphic high energy-carrying load is characterized by comprising the following steps:
step 1, analyzing the operation characteristics of polymorphic adjustable high-energy-carrying loads, classifying according to the difference of response speeds of various adjustable high-energy-carrying loads, and carrying out fine modeling on the polymorphic high-energy-carrying loads;
step 2, transforming the conventional unit into a carbon trapping unit with low carbon characteristics, deeply excavating the operation characteristics and the low carbon characteristics of the conventional unit, and establishing a low carbon operation cost model;
3, constructing a two-stage low-carbon economic dispatching model in the day-ahead and day-in based on the difference of polymorphic high-energy-carrying load response speeds;
and 4, obtaining a day-ahead low-carbon economic dispatching plan according to the day-ahead two-stage low-carbon economic dispatching model.
2. The method for day-ahead-day low-carbon economic dispatch considering polymorphic high energy loads according to claim 1, wherein the operation characteristics of the polymorphic adjustable high energy loads in the step 1 comprise the operation characteristics of a continuous adjustable high energy load, the operation characteristics of a discrete adjustable high energy load and the operation characteristics of a time-shifting adjustable high energy load.
3. The method for day-ahead-day low-carbon economic dispatching considering polymorphic high energy-carrying loads according to claim 2, wherein the step 1 of classifying according to the differences of the response speeds of various types of adjustable high energy-carrying loads and the step of carrying out fine modeling on the polymorphic high energy-carrying loads specifically comprises the following conditions:
1) Modeling the continuous adjustable high energy load by considering the operating characteristics and cost constraint of the load:
and (3) power constraint:
P lsh (t)＝P ls-base (t)+P ls-up (t)-P ls-down (t) (1)
and (3) restricting the upper limit and the lower limit of the regulating quantity:
and (3) state constraint:
S 1 (t)+S 2 (t)≤1 (3)
and (4) regulating times constraint:
adjusting the duration constraint:
and (4) planning yield constraint:
adjusting the cost:
in the formula, P lsh (t) discrete adjustable high energy load power at time t, P ls-base (t) is the base load at time t, P ls-up (t) is the amount of up-regulation at time t, P ls-down (t) is the down-regulation amount at time t; s 1 (t) the discrete adjustable high energy-carrying load is in an up-regulation state, S 2 (t) the load is in a down-regulated state, P ls-up-min To adjust up the minimum value, P ls-up-max To adjust the maximum value, P ls-down-min For down regulation minimum, P ls-down-max In order to adjust the maximum value of the amount downward,m is the maximum adjusting frequency; t is 1 For maximum duration of upregulation, T 2 Is the maximum downregulation duration; lambda [ alpha ] i For adjusted operating efficiency, E ls-plan Planning production for a day; c ls For the total cost of load regulation, C (t) is the time-of-use electricity price of the industrial load at time t, K ls (T) response subsidy cost at time T, and T is scheduling period;
2) The operation characteristics and the cost constraint of the discrete adjustable high-energy-carrying load are considered to be modeled as follows:
and (3) power constraint:
P lxh (t)＝P lx-base (t)+P lx-up (t)-P lx-down (t) (8)
and (3) restraining an upper limit and a lower limit of output:
P lx-min ≤P lxh (t)≤P lx-max (9)
adjusting the rate constraint:
P lxh-down ≤P lxh (t)-P lxh (t-1)≤P lxh-up (10)
and (3) restricting the upper limit and the lower limit of the regulating quantity:
and (3) state constraint:
S 1 (t)+S 2 (t)≤1 (12)
and (3) yield constraint:
adjusting the cost:
in the formula, P lxh (t) continuously adjusting the high energy load at the time tPower of P lx-base (t) base load at time t of continuously adjusting high energy load, P lx-up (t) is the amount of up-regulation at time t, P lx-down (t) is the down-regulation quantity at t time; p lx-min To minimum value of force, P lx-max Is the maximum value of the output; p is lxh-down To adjust the downhill speed, P lxh-up To adjust the rate of ascent; s 3 (t) is a load up decision variable, S 4 (t) is a load down-regulation decision variable; p is lx-up-max Is the maximum value of the load up-regulation quantity, P lx-up-min Is the minimum value of the load up-regulation quantity, P lx-down-max Is the maximum value of the load turndown, P lxh-down-min Is the minimum value of the load down-regulation quantity; lambda [ alpha ] k For adjusted operating efficiency, E lx-plan A continuous high-energy-load daily production plan is formed; c lx For adjusting the total load cost, C (t) is the time-of-use electricity price of the industrial load at the moment t, K lx (t) response subsidy cost at time t;
3) The operation characteristics and cost constraints of the time-shifting type adjustable high-energy-carrying load are considered to be modeled as follows:
and (3) power constraint:
P syh (t)＝S 5 (t)P syq (t) (15)
time shift time constraint:
and (4) planning yield constraint:
adjusting the cost:
in the formula, P syq (t) load at time t before adjustmentValue, P syq (t) is the load size at the time t after adjustment; lambda [ alpha ] j For adjusted working efficiency, S 5 (t) is a time shift decision variable, wherein 1 represents that the time shift occurs at the moment, and 0 represents that the time shift does not occur at the moment; t is min Is a minimum transfer duration constraint; e sy-plan A time-shifting type daily production plan with high energy-carrying load is adopted; c sy To adjust the total cost of the load, K sy And (t) the response subsidy cost at the time t.
4. The method for day-ahead and day-inside low-carbon economic dispatch in consideration of polymorphic high energy loads according to claim 1, wherein the cost of the carbon capture unit with low-carbon characteristic in the step 2 is coal consumption cost and CO cost 2 The treatment cost is the same as that of a conventional unit, and the CO is 2 Cost of treatment divided into CO 2 Emission cost and CO 2 And (4) trapping cost.
5. The method for day-ahead and day-inside low-carbon economic dispatch in consideration of polymorphic high energy loads according to claim 4, wherein the CO is used in the step 2 2 The processing cost calculation process comprises the following steps:
step 2.1, carbon capture unit CO 2 The emission cost calculation process is as follows:
carbon capture unit j at time t CO 2 The total capture volume of (a) is:
E cb,j (t)＝K cd P cb,j (t) (19)
carbon capture unit CO at t moment 2 The total capture volume of (a) is:
CO in scheduling period 2 The discharge cost is as follows:
in the formula, E cb,j (t) CO production by carbon capture unit j at time t 2 Total amount of (A), K cd Carbon emission intensity, P, of carbon capture unit cb,j (t) is the total output of the carbon trapping unit j at the moment t; e j,total-co2 (t) CO Capture for carbon Capture Unit j 2 Beta is the carbon capture equipment capture efficiency; n is a radical of cb Number of carbon capturing units, K c Is the unit carbon emission cost;
step 2.2, carbon capture unit CO 2 Trapping cost:
CO 2 the trapping cost comprises energy consumption cost, depreciation cost and sealing cost, and the specific expression is as follows:
the carbon trapping unit has the following trapping energy consumption cost:
the carbon capture unit capture depreciation cost:
the carbon capture unit sealing cost:
in the formula, C ne For carbon capture of power plant energy costs, P Dj (t) fixed energy consumption of carbon capture unit, P Bj (t) operating energy consumption of the carbon capture unit, N cb The number of the carbon capture units is; c (t) is the time-of-use electricity price of the industrial load; c zj For depreciation costs, N zj For depreciation years, alpha is the item discount rate of the carbon capture unit, C tb The total cost of the carbon capture plant capture equipment; c ry Cost per unit volume of solution storage, V ry As volume of solution reservoir, N ry Age of solution storage; k is se Is in the unit of CO 2 Cost of sequestration, C se The total cost for the carbon capture unit sealing;
step 2.3, capturing CO of the unit according to carbon 2 Emission cost, carbon capture unit CO 2 CO capture cost calculation 2 Total cost of treatment C cbc Comprises the following steps:
C cbc ＝C ne +C se +C de +C cd (25)
6. the method for day-ahead-day low-carbon economic dispatching considering polymorphic high energy-carrying load according to claim 1, wherein the specific process of the step 3 is as follows:
step 3.1, constructing a day-ahead low-carbon economic model objective function and a day-ahead low-carbon economic model constraint condition:
the day-ahead low-carbon economic model objective function is as follows:
F 1 ＝min(C cg +C cb +C aw +C ls +C sy +C cbc +C cgc ) (26)
in the formula, F 1 Optimizing and scheduling the total running cost for the low-carbon economy of the system day ahead; c cg For the running cost of conventional thermal power generating units, C cbc Is CO 2 Total cost of treatment, U i (t) Start-stop state of conventional thermal power generating unit i at time t, a i 、b i 、c i Is the coal consumption cost coefficient, P, of the conventional thermal power generating unit i cg,i (t) the output of a conventional thermal power generating unit i at the moment t; c cb For the operating cost of the carbon capture unit, U j (t) is the start-stop state of the carbon capture unit j at the moment t, a j 、b j 、c j Is the coal consumption cost coefficient, P, of the carbon capture unit j cb,j (t) the output of the carbon capture unit j at the moment t; c aw To discard the wind cost, K aw Cost per unit of wind abandoned, P wfore (t) predicted wind power output at time t, P w (t) is a planned value of the wind power day-ahead output at the moment t; c cgc The total cost of carbon emission of the conventional thermal power generating unit, K c Is the unit carbon emission cost;
3.2, constructing an intra-day low-carbon economic model objective function and intra-day low-carbon economic model constraint conditions:
the in-day low-carbon economic model objective function is expressed as:
F 2 ＝min(C cn +C lx -C Δaw ) (36)
in the formula, F 2 Total operating cost of the system in the intra-day period, C lx Cost adjustment for continuous adjustable high energy load, C cn For operating the energy storage system, C Δaw To reduce the cost of air waste, K cn Is the unit energy storage cost.
7. The method for day-ahead-day-inside low-carbon economic dispatching considering polymorphic high energy-carrying loads according to claim 6, wherein the day-ahead low-carbon economic model constraint conditions include a system power balance constraint, a wind power output constraint, a conventional unit output upper and lower limit constraint, a conventional unit climbing constraint, a system rotation standby, a carbon capture unit operation constraint, and a carbon capture unit solution storage device operation constraint, which are specifically expressed as:
1) System power balance constraint:
2) Wind power output restraint:
0≤P w (t)≤P wfore (t) (29)
3) The upper limit and the lower limit of the output of the conventional unit are restricted:
U i (t)P cgmin,i ≤P cg,i (t)≤U i (t)P cgmax,i (30)
4) And (3) climbing restraint of a conventional unit:
5) System spinning reserve
The system rotation standby is jointly borne by a conventional thermal power generating unit and a carbon capturing unit:
6) Carbon capture unit operational constraints
According to the energy consumption characteristics of the carbon capture unit, considering flue gas split ratio constraint, carbon capture amount constraint and carbon capture equipment energy consumption related constraint, wherein the carbon capture equipment energy consumption mainly comprises two parts of fixed energy consumption and operation energy consumption, and the mathematical model of the carbon capture unit is as follows:
in the formula, P cg (t) is the normal load at time t, R i up For the rate of ascent of unit i, R i down The climbing rate of the unit i; r down For negative rotation of the system, R up The system rotates forwards for standby; e cb,j (t) CO production by the carbon capture unit j at time t 2 Total amount of (1), K cd To carbon emission intensity of carbon capture unit, P cb,j (t) is the total output of the carbon trapping unit j at the moment t; coefficient of state, P cj,j,max The maximum output of the carbon capture unit j; p Bj (t) is the running energy consumption of the carbon capture unit j at the moment t, and lambda is the captured CO 2 The unit energy consumption of (2); p is cj,j (t) is the net output of the carbon capture unit j at time t, P Dj The fixed energy consumption of the carbon capture unit j;
7) Solution reservoir operational constraints
The solution in the solution storage of the carbon capture unit is ethanolamine solution, and the volume of the solution is used for calculating CO 2 The relational expression of (c) is as follows:
in the formula, V CAi (t) capturing CO for the carbon capture unit i at the moment t 2 Volume of solution of (2), Q Gi (t) capturing CO for the carbon capture unit i at the moment t 2 Mass of (A), M EA Molar mass of ethanolamine solution, M CO2 Is CO 2 Molar mass, M R As ethanolamine solution concentration, p R Density of ethanolamine solution;
the operation constraint of the solution storage device of the carbon capture unit is as follows:
in the formula, V Fi (t) is the solution volume of the rich solution storage of the carbon capture unit i at the time t, V Pi (t) is the solution volume of the lean solution storage of the carbon capture unit i at the time t, V CAi (t) the carbon capture unit i captures CO at the moment t 2 Volume of solution of (D), V CAi The maximum volume of the solution storage of the carbon capture unit i.
8. The method for scheduling low-carbon economy in day before-day in consideration of polymorphic high energy-carrying loads according to claim 6, wherein the constraint conditions of the low-carbon economy model in day comprise day-time power regulation balance and energy storage system operation constraint, and specifically comprise:
1) Intraday power regulation balance constraint
ΔP w (t)＝P lx-up (t)-P lx-down (t)+P cha (t)-P dis (t) (38)
2) Energy storage system operating constraints
Considering the charge state constraint and the charge-discharge power constraint of the energy storage system, the mathematical model is as follows:
the state of charge of the energy storage system and the expression thereof:
and (3) charge and discharge restraint of the energy storage system:
in the formula,. DELTA.P W (t) is the difference between the predicted wind output value in the day and the wind output value planned in the day before, B soc To the state of charge of the energy storage system, E b Is the current moment electric quantity of the energy storage system, C b The total capacity of the energy storage system; b is soc,min 、B soc,max Respectively the minimum and maximum of the 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 is soc (t + 1) is the state of charge of the energy storage system at the moment t + 1; p cha (t) is the charging power of the energy storage system at time t, eta cha For charging efficiency, for scheduling period; p is dis (t) is the discharge power of the energy storage system at time t, eta dis To discharge efficiency; p cha,min 、P cha,max Respectively charging the upper limit and the lower limit of the energy storage system; p dis,min 、P dis,max Respectively the upper and lower limits of the discharge electric power of the energy storage system.
9. The method for day-ahead-day low-carbon economic dispatching considering polymorphic high energy-carrying load according to claim 1, wherein the specific process of the step 4 is as follows: in the day-ahead stage, inputting the discrete type and time-shifted type high-energy-carrying load plan values and the wind power intra-day predicted values into a day-ahead low-carbon economic model to obtain a day-ahead scheduling plan; and in the in-day stage, inputting the conventional load prediction, the time-shifting type and time-shifting type high-energy-carrying load plan values and the predicted values before the wind power day into an in-day low-carbon economic model to obtain an in-day scheduling plan.
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