CN115545478A - Environment economic dispatching method considering carbon emission quota influence and regional pollutant concentration constraint - Google Patents
Environment economic dispatching method considering carbon emission quota influence and regional pollutant concentration constraint Download PDFInfo
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Abstract
The invention relates to an environmental economy scheduling method considering carbon emission quota influence and regional pollutant concentration constraint, which adopts an A value method to calculate regional atmospheric environment capacity coefficients and determine the environmental pollutant concentration threshold of each region; determining initial carbon emission quota of each area based on a traditional benchmark method and by considering a pollutant concentration threshold value, thereby establishing a carbon trading cost model; establishing a pollutant concentration distribution model of the coal-fired unit from three dimensions of time, space and concentration by adopting a multi-source Gaussian plume diffusion model; and (4) establishing an environmental economic dispatching optimization model by considering pollutant concentration constraint and carbon transaction cost. Compared with the prior art, the method has the advantages that the initial carbon emission quota is distributed by considering regional environment differences, an optimization model is established from controlling the carbon emission and limiting the pollutant concentration space-time distribution, the output of a unit is reasonably adjusted, and the environmental pressure of a region with a lower pollutant concentration threshold value is relieved.
Description
Technical Field
The invention belongs to the technical field of low-carbon optimization of power systems, and particularly relates to an environmental economic dispatching method considering carbon emission quota influence and regional pollutant concentration constraint.
Background
Carbon emissions trading is being adopted by more and more countries and regions as a tool to limit greenhouse gas emissions by market means. The low-carbon transformation of the power system is a key for dealing with climate change and implementing deep emission reduction in the power industry, and not only needs support of various low-carbon technologies, but also needs to construct a proper market mechanism to provide carbon emission reduction incentive for market bodies.
The reasonable distribution of the carbon emission right is the foundation for building a carbon trading market. At present, the unified carbon emission quota and the total carbon emission control do not consider the influence of regional environment differences on carbon transaction cost and emission reduction strategies, and the control of the total carbon emission and pollutant distribution is difficult to consider.
Disclosure of Invention
Aiming at the problems of the existing regional power system low-carbon scheduling method, the invention aims to provide an environmental economy scheduling method to realize double constraints of the total carbon emission and the regional pollutant concentration distribution.
In order to achieve the purpose, the invention adopts the technical scheme that:
an environmental economic scheduling method considering carbon emission quota influence and regional pollutant concentration constraint comprises the following steps:
step 1: calculating the atmospheric environment capacity coefficient of each region by adopting an A value method, and determining the environmental pollutant concentration threshold of each region;
step 2: determining initial carbon emission quota of each region based on a reference value method and considering a pollutant concentration threshold, and establishing a step-type carbon transaction cost model;
and step 3: establishing a pollutant concentration distribution model of the coal-fired unit from three dimensions of time, space and concentration by adopting a multi-source Gaussian plume diffusion model;
and 4, step 4: the method comprises the steps of establishing an environmental economic dispatching model by considering regional environmental pollutant concentration constraint with the targets of carbon transaction cost, unit start-stop cost, wind and light abandoning cost and the like;
and 5: and performing refined operation simulation by taking the year as an operation period, and solving the model to obtain the optimal power output, the operation curve of each device and the power distribution of the coal-fired unit.
Further, in the step 1, the atmospheric environment capacity is solved according to an a-value method, and the pollutant concentration at the boundary of the area is expressed as:
wherein: a is the atmospheric environment capacity coefficient, km 2 A; h is the height of the mixed layer, m; v. of d 、v w The average dry sedimentation velocity and the wet sedimentation velocity are m/s respectively; u is the gas advection velocity, m/s; s is the area of the region, km 2 (ii) a c is the concentration of the contaminant, mg/m 3 C = c when a =0 0 (ii) a q is the discharge amount of the atmospheric pollutants when the concentration is c, t/a; t represents time.
The calculated pollutant concentration threshold of the area k is as follows:
wherein, tv k Is the threshold contaminant concentration for zone k, i.e., the maximum contaminant concentration tolerable for that zone, mg/m 3 ； q k Total pollutant emission amount of the region k, t; a. The k Is the area k atmospheric environment capacity coefficient, km 2 /a；v k Is the wind speed of region k, m/s; s k Is the area of region k, km 2 ；H k Is the mixed layer height, m, of region k.
Further, in step 2, the initial carbon emission quota of each area is determined in consideration of the pollutant concentration threshold, and first, the initial carbon emission quota determined by using the reference value method is as follows:
in the formula, cea k.0 Denotes the initial carbon emission quota, of the region k 0 Is the initial carbon emission allowance coefficient, P, per unit of generated energy t.k And T is a scheduling period and represents the power generation amount of the area k at the time T.
And secondly, on the basis of the initial carbon emission quota, adjusting the carbon emission quota according to the regional environmental pollutant threshold value. Dividing a planning area into K sub-areas according to environment difference, wherein the pollutant concentration threshold value of the sub-area K0 is tv k0 Assuming that the carbon quota coefficient of unit generated energy in the area is quota 0 If the regional environmental concentration threshold value satisfies tv k ≤tv k+1 The carbon quota coefficient for region k is then:
wherein K is the total number of divided regions, quota k The carbon quota coefficient for the atmospheric environment background is considered for region k. Omega represents a correlation coefficient between a pollutant concentration threshold value and a carbon emission quota, and the thermal power generating unit needs to convert the pollutant concentration threshold value and the carbon dioxide emission quota due to the difference of orders of magnitude between the pollutant concentration threshold value and the carbon dioxide emission quota.
Further, in the step 2, the ladder type carbon transaction cost model is:
in the formula (f) CO2 Representing a carbon transaction cost function, cem k Carbon emissions of zone k,. DELTA.cem k The carbon emission trade volume for region k, cc represents the coal fired unit carbon emission coefficient, cea k Denotes the k carbon emission quota, P, of the region C.t.k For the thermal power unit power, P, of the region k at time t t.k Representing the total power of the power supply at time t in region k, theta is the length of the carbon emission interval,
lambda is the carbon trade price interval growth rate, C 1 Is the carbon transaction base price.
Further, in step 3, the pollutant concentration distribution model of the coal-fired unit is derived by the following process:
the ground concentration of the overhead continuous point source is as follows:
wherein c is the concentration of the contaminant; x, y and z respectively represent coordinate values from any point to the origin; sigma y 、σ z Respectively a horizontal diffusion coefficient and a vertical diffusion coefficient; v is the average wind speed, m/s; effective height H of chimney c Is the actual height H of the chimney cs Height delta H of smoke plume c And Q is the amount of pollutants discharged by the coal-fired power plant in unit time.
Converting the wind direction coordinate system into a geographic coordinate system:
wherein x and y are coordinate variables used by the Gaussian plume diffusion model, and m; x is the number of pol 、y pol A geographical coordinate system coordinate variable m of the point source; x is the number of mon 、y mon Calculating the coordinate variable m of the geographic coordinate system of the point or the monitoring point;
is the wind direction angle (with the positive south direction as the positive direction), degree;
from this, the concentration value of the emission m of the coal-fired unit i at the coordinates (x, y, 0) can be obtained:
wherein the content of the first and second substances,
is the concentration value of the pollution m of the unit i,
indicating the discharge amount of the pollutant m of the unit i.
Therefore, the contribution value of the concentration of the pollutant m of the coal-fired unit in the area k at the time t can be expressed by the following formula:
wherein the content of the first and second substances,
representing the pollutant m concentration contribution of the coal-fired unit in the k region at time t,
the concentration of the pollutants m at the detection point j of the unit i at the time t is shown, Y is the number of the pollutant concentration detection points, and N is the number of the coal-fired units.
Further, in step 4, the environmental economic dispatch model objective function includes carbon transaction cost, operation and maintenance cost, wind and light abandoning cost, fuel cost and unit start-stop cost:
min F＝F cem +F om +F ab +F fuel +F sts (13)
in the formula, F cem 、F om 、F ab 、F fuel 、F sts Respectively carbon transaction cost, operation and maintenance cost, wind and light abandoning cost, fuel cost and unit start-stop cost, P g.t Representing the power of the power supply g at time t. Δ cem k.t The carbon emissions trading volume for region k at time t. P r.t 、
And the actual output values and the predicted values of the wind power and the photovoltaic are respectively. a is a i 、b i 、c i Are respectively the coal burning coefficient, PG, of the coal burning unit i i.t And (4) the power of the thermal power generating unit i at the time t. Epsilon f 、ε ab Respectively a fuel cost coefficient, a wind abandoning cost coefficient and a light abandoning cost coefficient, ud represents a start-stop cost coefficient, SS i.t The running state of the coal-fired unit i at the time t is 1, the running state is 1, and the shutdown state is 0.
Further, in the step 4, the constraint conditions of the eco-economic dispatch model include a Carbon Capture and Storage (CCS) unit, a Methanation Efficiency (ME) unit, and an electricity-hydrogen Hybrid Energy Storage (HES) characteristic constraint, that is:
wherein eta is CCS Represents the power consumption coefficient, V, of CCS CO2.CCS.t Denotes the time point CO 2 Amount of trapping, P CCS.t Represents CCS power consumption at time t; alpha is alpha CCS Is the trapping efficiency of CCS, V CO2.t The carbon emission of the thermal power generating unit; eta PC Carbon emission coefficient, P, of thermal power generating units C.t The power of the thermal power generating unit.
Wherein, V CH4.t 、P CH4.t 、η CH4 Are respectivelythe methane yield, the power consumption and the power consumption coefficient at the time t; v H2.CH4.t 、α H2.CH4 Hydrogen consumption and hydrogen consumption coefficient respectively; v CO2.CH4.t 、α CO2.CH4 Respectively carbon consumption amount and carbon consumption coefficient.
In the formula eta EC For the efficiency of the electrical hydrogen production, P EL.t 、V HS.EC.t The power and the hydrogen production quantity of the electric hydrogen production equipment at the time t are respectively; eta FC For fuel cell operating efficiency, P FC.t 、V HS.FC.t Respectively representing the power generation power and the hydrogen consumption of the fuel cell at the time t; p BA.c.t Charging power for the battery; p BA.d.t Is the discharge power of the storage battery; eta s Energy storage charging and discharging efficiency; SOC HS.t Energy storage state, SOC, for hydrogen storage at time t HS.0 For an initial energy storage state of hydrogen energy storage, CAP HS Storage of installed capacity for hydrogen, H HS.max For maximum storage time of hydrogen, delta s.0 Representing the initial storage capacity ratio; SOC (system on chip) BA.t State of energy storage, SOC, for electrical energy storage at time t BA.0 Initial energy storage state for electrical energy storage, CAP BA Charging capacity for electrical energy, H BA.max The longest storage time is for electrical energy storage.
Further, in step 4, the constraints of the environmental economic dispatch model include balance of electricity, hydrogen, and carbon energy flows, that is:
P C.t +P W.t +P PV.t +P H.t +P FC.t +P BA.d.t ＝P CCS.t +P EL.t +P CH4.t +P BA.c.t +L E.t (19)
V HS.EC.t ＝V HS.FC.t +V H2.CH4.t (20)
V CO2.t -V CO2.CH4.t ＝cem t (21)
wherein, P C.t 、P W.t 、P PV.t 、P H.t Respectively thermal power, wind power, photovoltaic and hydroelectric power output at the moment t, L E.t Is the electric load value at the time t. cem t Carbon emissions at time t.
The output of each thermal power unit needs to meet the total thermal power dispatching requirement, namely:
further, in the step 4, the constraint conditions of the environmental economic dispatch model include a regional environmental pollutant concentration constraint:
wherein the content of the first and second substances,
representing the background concentration of contaminant m at time t in the k region,
representing the threshold concentration of contaminant m in region k.
And finally, carrying out refined operation simulation by taking the year as an operation period, and solving the model to obtain the optimal power output, the operation curve of each device and the power distribution of the coal-fired unit.
Has the advantages that:
the coal-fired unit power distribution can be effectively improved by adopting a region-differentiated carbon emission quota distribution mode, the annual operation cost is reduced, and the carbon emission is reduced; meanwhile, the output of the coal-fired unit can be adjusted by considering the environmental concentration constraint of pollutants, and the environmental pressure of an area with a lower pollutant concentration threshold value is reduced.
Drawings
FIG. 1 is a power flow diagram of a high-ratio renewable energy power system in an exemplary embodiment of the invention;
FIG. 2 is a schematic illustration of the location of a coal fired unit in an exemplary embodiment of the invention;
FIG. 3 is a graph of electrical load in an exemplary embodiment of the invention;
FIG. 4 is a graph of power curves of various equipment units according to an embodiment of the present invention;
FIG. 5 shows carbon emissions of various zones determined in an example of the present invention;
FIG. 6 shows SO in each area obtained in an embodiment of the present invention 2 Concentration changes with time.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
In the following, embodiments of the present invention are described in further detail with reference to the accompanying drawings, and an environmental economic dispatch method considering the carbon emission quota effect and regional pollutant concentration constraint includes the following steps:
step 1: calculating the capacity coefficient of the atmospheric environment of the regions by adopting an A value method, and determining the concentration threshold of the environmental pollutants of each region;
step 2: determining initial carbon emission quota of each region based on a reference value method and considering a pollutant concentration threshold, and establishing a step-type carbon transaction cost model;
and step 3: establishing a pollutant concentration distribution model of the coal-fired unit from three dimensions of time, space and concentration by adopting a multi-source Gaussian plume diffusion model;
and 4, step 4: the method comprises the steps of establishing an environmental economic dispatching model by considering regional environmental pollutant concentration constraint with the targets of carbon transaction cost, unit start-stop cost, wind and light abandoning cost and the like;
and 5: and performing refined operation simulation by taking the year as an operation period, and solving the model to obtain the optimal power output, the operation curve of each device and the power distribution of the coal-fired unit.
And (3) solving the atmospheric environment capacity according to an A value method, wherein the pollutant concentration at the boundary of the area is expressed as:
wherein: a is the atmospheric environment capacity coefficient, km 2 A; h is the height of the mixed layer, m; v. of d 、v w Respectively, the average dry sedimentation velocity and the wet sedimentation velocity are m/s; u is the gas advection velocity, m/s; s is the area of the region, km 2 (ii) a c is the concentration of the contaminant, mg/m 3 C = c when a =0 0 (ii) a q is the discharge amount of the atmospheric pollutants when the concentration is c, t/a; t represents time.
The threshold contaminant concentration for region k can then be determined as:
wherein, tv k Is the threshold contaminant concentration for zone k, i.e., the maximum contaminant concentration tolerable for that zone, mg/m 3 ； q k Total pollutant emission amount of the region k, t; a. The k Respectively, the area k atmospheric environment capacity coefficient, km 2 /a；v k Is the wind speed of region k, m/s; s k Is the area of region k, km 2 ；H k Is the mixed layer height, m, of region k.
The initial carbon emission quota determined using the baseline method is:
in the formula, cea k.0 Indication areaDomains k gratuitous carbon emission quota, quota 0 Is the initial carbon emission allowance coefficient, P, per unit of generated energy t.k And T is a scheduling period and represents the power generation amount of the area k at the time T.
And adjusting the carbon emission quota according to the regional environmental pollutant threshold. Dividing a planning area into K sub-areas according to environment difference, wherein the pollutant concentration threshold of the sub-area K0 is tv k0 Assuming that the carbon quota coefficient of the unit generated energy in the area is quota 0 If the regional environmental concentration threshold value satisfies tv k ≤tv k+1 Then the carbon quota coefficient for region k is:
wherein K is the total number of divided regions, quota k The carbon quota coefficient for region k is taken into account for the background of the atmospheric environment. Omega represents a correlation coefficient between a pollutant concentration threshold value and a carbon emission quota, and the thermal power generating unit needs to convert the pollutant concentration threshold value and the carbon dioxide emission quota due to the difference of orders of magnitude between the pollutant concentration threshold value and the carbon dioxide emission quota.
The step-type carbon transaction cost model established based on the carbon quota is as follows:
in the formula (f) CO2 Representing a carbon transaction cost function, cem k Region k carbon emissions, Δ cem k The carbon emission trade volume for region k, cc represents the coal fired unit carbon emission coefficient, cea k Denotes the carbon emission quota of region k, P C.t.k Power P of thermal power generating unit at time t in region k t.k Representing the total power of the power supply at time t in region k, theta is the length of the carbon emission interval,
lambda is the carbon transaction price interval growth rate, C 1 Is the carbon transaction base price.
The ground concentration of the overhead continuous point source is as follows:
wherein c is the concentration of the contaminant; x, y and z respectively represent coordinate values from any point to the origin; sigma y 、σ z Respectively a horizontal diffusion coefficient and a vertical diffusion coefficient; v is the average wind speed, m/s; effective height H of chimney c Is the actual height H of the chimney cs And the smoke plume lifting height delta H c And Q is the pollutant mass discharged by the coal-fired power plant in unit time.
Converting the wind direction coordinate system into a geographic coordinate system:
wherein x and y are coordinate variables used by the Gaussian smoke plume diffusion model, and m is the coordinate variable used by the Gaussian smoke plume diffusion model; x is the number of pol 、y pol A geographical coordinate system coordinate variable m of the point source; x is the number of mon 、y mon A geographic coordinate system coordinate variable m of a calculation point or a monitoring point;
wind direction angle (with the south direction as the positive direction), degree;
from this, the concentration value of the emission m of the coal-fired unit i at coordinates (x, y, 0) can be obtained:
wherein, the first and the second end of the pipe are connected with each other,
is unit i sewageThe concentration value of the dye m is measured,
indicating the discharge amount of the pollutant m of the unit i.
Therefore, the contribution value of the concentration of the pollutant m of the coal-fired unit in the area k at the time t can be expressed by the following formula:
wherein, the first and the second end of the pipe are connected with each other,
representing the pollutant m concentration contribution of the coal-fired unit in the k region at time t,
the concentration of the pollutants m at the detection point j of the unit i at the time t is shown, Y is the number of the pollutant concentration detection points, and N is the number of the coal-fired units.
So far, an environmental economic dispatching model can be established, and an objective function comprises carbon transaction cost, operation and maintenance cost, wind and light abandoning cost, fuel cost and unit start-stop cost:
min F＝F cem +F om +F ab +F fuel +F sts (13)
in the formula, F cem 、F om 、F ab 、F fuel 、F sts The carbon transaction cost, the operation and maintenance cost, the wind and light abandoning cost, the fuel cost and the unit start-stop cost are respectively. T is a scheduling period. Δ cem k.t Trading carbon emissions for region k at time t. C inv.g 、ε g Is the unit investment cost and operation and maintenance cost coefficient, P, of the power supply g g.t Representing the power of the power source g at time t. P r.t 、
And the actual output values and the predicted values of the wind power and the photovoltaic are respectively. a is a i 、b i 、c i Is the coal burning coefficient, PG, of the coal burning unit i i.t And (4) the power of the thermal power generating unit i at the time t. Epsilon f 、ε ab Respectively a fuel cost coefficient, a wind abandoning cost coefficient and a light abandoning cost coefficient, ud represents a start-stop cost coefficient, SS i.t The running state of the coal-fired unit i at the time t is 1, the running is performed, and the shutdown is performed 0.
The constraint conditions comprise equipment characteristic constraint, energy flow balance constraint and pollutant concentration distribution constraint:
(1) Carbon capture unit (CCS):
wherein eta is CCS Represents the power consumption coefficient, V, of CCS CO2.CCS.t Denotes the time point CO 2 Amount of capture, P CCS.t Represents CCS power consumption at time t; alpha (alpha) ("alpha") CCS Is the trapping efficiency of CCS, V CO2.t Carbon emission of a thermal power generating unit; eta PC Carbon emission coefficient, P, of thermal power generating units C.t The power of the thermal power generating unit.
(2) Methanation assembly (ME):
wherein, V CH4.t 、P CH4.t 、η CH4 The yield of methane, the power consumption and the power consumption coefficient at the moment t are respectively; v H2.CH4.t 、α H2.CH4 Hydrogen consumption and hydrogen consumption coefficient respectively; v CO2.CH4.t 、α CO2.CH4 Respectively carbon consumption amount and carbon consumption coefficient.
(3) Electric-hydrogen Hybrid energy storage unit (HES):
in the formula eta EC For the efficiency of electrical hydrogen production, P EL.t 、V HS.EC.t The power and the hydrogen production quantity of the electric hydrogen production equipment at the time t are respectively; eta FC For fuel cell operating efficiency, P FC.t 、V HS.FC.t Respectively representing the power generation power and the hydrogen consumption of the fuel cell at the time t; p is BA.c.t Charging power for the battery; p BA.d.t Is the discharge power of the storage battery; eta s Energy storage charging and discharging efficiency; SOC (system on chip) HS.t Energy storage state, SOC, for hydrogen storage at time t HS.0 An initial energy storage state for storing hydrogen, CAP HS Storing installed capacity for hydrogen, H HS.max For maximum storage time of hydrogen, delta s.0 Representing the initial storage capacity ratio; SOC (system on chip) BA.t State of energy storage, SOC, for electrical energy storage at time t BA.0 Initial energy storage state for electrical energy storage, CAP BA Charging capacity for electrical energy, H BA.max The longest storage time is for electricity storage.
(4) Energy flow balance of electricity, hydrogen and carbon:
P C.t +P W.t +P PV.t +P H.t +P FC.t +P BA.d.t ＝P CCS.t +P EL.t +P CH4.t +P BA.c.t +L E.t (19)
V HS.EC.t ＝V HS.FC.t +V H2.CH4.t (20)
V CO2.t -V CO2.CH4.t ＝cem t (21)
wherein, P C.t 、P W.t 、P PV.t 、P H.t Respectively thermal power, wind power, photovoltaic and hydroelectric output at the moment t, L E.t Is the electric load value at the time t. cem t Carbon emissions at time t.
The output of each thermal power unit needs to meet the total thermal power dispatching requirement, namely:
(5) And (3) restricting the concentration distribution of the regional environmental pollutants:
wherein the content of the first and second substances,
representing the background concentration of contaminant m at time t in the k region,
representing the threshold concentration of contaminant m in region k.
The system structure is shown in figure 1, a power supply comprises four types of wind, light, water and fire, an electric energy storage system and a hydrogen energy storage system form a hybrid energy storage system, and methanation equipment utilizes CO captured by a carbon capture device 2 And H produced by electrolysis of water 2 Synthesis of CH 4 . The four energy material flows of electricity, hydrogen, carbon and methane are involved, and the arrows indicate the flowing direction.
The unit positions are shown in figure 2, the planning area is divided into a central area k1, an urban area k2 and a suburban area k3, the coal-fired units G1 are located at k1, G2-G3 are located at k2, and G4-G5 are located at k3.
The system parameters are as follows:
TABLE 1 System configuration
TABLE 2 coal-fired unit parameters
Force limit [0, 400] (MW), hill climb limit 50MW.
The present embodiment sets four scenarios as follows:
scene 1: performing optimized scheduling according to the uniform carbon emission quota;
scene 2: performing optimized scheduling by using a unified carbon emission quota and considering environmental constraints;
scene 3: performing optimized scheduling by adopting a regional differentiated carbon emission quota;
scene 4: and performing optimal scheduling by adopting the regional differentiated carbon emission quota and considering environmental constraints.
And (4) calling GUROBI by using a YALMIP toolbox in MATLAB to solve, wherein the electrical load curve of the embodiment is shown in figure 3, and the electrical load of the area in spring and summer is slightly lower than that of the area in autumn and winter.
Fig. 4 shows power curves of each equipment unit obtained in scene 1, where (a), (b), (c), and (d) are power curves of wind power, hydropower, photovoltaic, and thermal power, respectively, and wind-solar power generation is sufficient, and water resources are abundant in summer, so that thermal power mainly plays a role in autumn and winter, and thermal power hardly participates in power supply for a long period of time in spring and summer; (e) For the methanation plant power curve, CO can be reacted 2 And H 2 The amount of synthesized methane; (f) The curve of the charging and discharging power of the electricity energy storage and the hydrogen energy storage and the residual capacity of the hydrogen energy storage is shown in the step (g), and the electricity-hydrogen hybrid energy storage system plays an important supporting role; with the assistance of carbon capture, electric hydrogen production and methanation equipment, the electricity quantity is 0 by the abandoned wind.
As shown in fig. 5, the total carbon emission of the k1 and k2 regions under the scenes 3 and 4 is much smaller than that of the scenes 2 and 3, and the total carbon emission of the k1 and k2 regions under the scenes 3 and 4 is transferred to the k3 in the scenes 3 and 4, because the scenes 3 and 4 adopt the initial carbon emission quota with the region differentiation, the environmental coefficient and the initial carbon emission quota of the k1 and k2 regions are lower, and the carbon transaction cost caused by the same carbon emission is higher, the power distribution is more prone to preferentially utilize the unit in the k3 region for power supply. In the total annual emission, scenes 3 and 4 have 1.5X 10 carbon emissions less than scenes 1 and 2 4 t is more than t. The results indicate regional differencesThe differentiated initial carbon emission quota has obvious control effect on the total carbon emission.
Each region SO 2 The time-dependent concentration changes are shown in FIG. 6, where (a) - (d) are SO for scenes 1-4, respectively 2 The concentration distribution. SO exists in K1 and K2 regions under scene 1 2 The concentration exceeds the environmental concentration threshold value, and the maximum concentration exceeds the concentration threshold value by 1.6 percent; scene 2 consideration area SO 2 After the concentration distribution is restrained, SO is generated in each area 2 The concentration profile returns to within the region threshold; in scenario 3, although the total amount of carbon emission is controlled, the k2 region still has a part of the time SO 2 The concentration exceeds the environmental concentration threshold, and the highest position exceeds the threshold by 1.99 percent; scene 4 gives consideration to control of total carbon emission of regions and SO in each time period 2 The constraint of the ground concentration not only meets the requirement of a concentration threshold value, but also limits the carbon emission of each area according to the environmental difference.
The carbon quota considering the regional differentiation can effectively reduce the carbon transaction cost, although the start-stop cost of the unit is increased, the total scheduling cost is far lower than that of the scheme of unifying the carbon quotas, and the annual running cost is reduced by 2 multiplied by 10 7 Yuan above. The total scheduling cost slightly rises by considering the atmospheric environment constraint, but the annual operation cost does not exceed 0.008 per thousand and 0.002 per thousand, and SO is avoided 2 The concentration exceeds the regional environmental concentration threshold, and under the large background of environmental protection, the scheme of adopting the regional differentiated initial carbon emission quota and considering the atmospheric environmental constraint is more advantageous.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. An environmental economic dispatching method considering carbon emission quota influence and regional pollutant concentration constraint is characterized by comprising the following steps:
step 1: calculating the capacity coefficient of the atmospheric environment of the regions by adopting an A value method, and determining the concentration threshold of the environmental pollutants of each region;
step 2: determining initial carbon emission quota of each region based on a reference value method and considering a pollutant concentration threshold, and establishing a step-type carbon transaction cost model;
and 3, step 3: establishing a pollutant concentration distribution model of the coal-fired unit from three dimensions of time, space and concentration by adopting a multi-source Gaussian plume diffusion model;
and 4, step 4: the method comprises the steps of establishing an environmental economic dispatching model by considering regional environmental pollutant concentration constraint with the carbon transaction cost, the unit start-stop cost and the wind and light abandoning cost as targets;
and 5: and performing operation simulation by taking years as an operation period, and solving the model to obtain the optimal power output, the operation curve of each device and the power distribution of the coal-fired unit.
2. The method according to claim 1, wherein in the step 1, the atmospheric environment capacity is solved according to an A-value method, and the pollutant concentration at the boundary of the area is expressed as:
wherein: a is the atmospheric environment capacity coefficient, km 2 A; h is the height of the mixed layer, m; v. of d 、v w Respectively, the average dry sedimentation velocity and the wet sedimentation velocity are m/s; u is the gas advection velocity, m/s; s is the area of the region, km 2 (ii) a c is the concentration of the contaminant, mg/m 3 C = c when a =0 0 (ii) a q is the discharge amount of the atmospheric pollutants when the concentration is c, t/a; t represents time;
the calculated pollutant concentration threshold of the area k is as follows:
wherein, tv k Is the threshold contaminant concentration for zone k, i.e., the maximum contaminant concentration tolerable for that zone, mg/m 3 ；q k Total pollutant emission amount of the region k, t; a. The k Is the area k atmospheric environment capacity coefficient, km 2 /a；v k Is the wind speed of region k, m/s; s k Is the area of region k, km 2 ；H k Is the mixed layer height, m, of region k.
3. The method of claim 2, wherein in step 2, the initial carbon emission quota for each region is determined in consideration of the pollutant concentration threshold, and first, the initial carbon emission quota determined by using the reference value method is:
in the formula, cea k.0 Denotes the initial carbon emission quota, of region k 0 Is the initial carbon emission allowance coefficient, P, per unit of generated energy t.k Representing the power generation amount of the area k at the time T, wherein T is a scheduling period;
secondly, on the basis of the initial carbon emission quota, adjusting the carbon emission quota according to the threshold value of the regional environmental pollutants; dividing a planning area into K sub-areas according to environment difference, wherein the pollutant concentration threshold of the sub-area K0 is tv k0 Assuming that the carbon quota coefficient of the unit generated energy in the area is quota 0 If the regional environmental concentration threshold value satisfies tv k ≤tv k+1 Then the carbon quota coefficient for region k is:
wherein K is the total number of divided regions, quota k A carbon quota coefficient for region k that takes into account atmospheric environmental background; omega represents the ratio between the pollutant concentration threshold and the carbon emission quotaThe correlation coefficient of the thermal power generating unit is changed due to the difference of orders of magnitude between the pollutant and carbon dioxide emission of the thermal power generating unit.
4. The method of claim 3, wherein in step 2, the ladder type carbon trading cost model is:
in the formula (f) CO2 Representing a carbon transaction cost function, cem k Region k carbon emissions, Δ cem k The carbon emission trade volume for region k, cc represents the coal fired unit carbon emission coefficient, cea k Denotes the k carbon emission quota, P, of the region C.t.k For the thermal power unit power, P, of the region k at time t t.k Representing the total power of the power supply at time t in region k, theta is the length of the carbon emission interval,
λ is carbon trade price interval growth rate, C 1 Is the carbon transaction base price.
5. The method according to claim 4, wherein in the step 3, the pollutant concentration distribution model of the coal-fired unit is derived by the following process:
the ground concentration of the overhead continuous point source is as follows:
wherein c is the concentration of the contaminant; x, y and z respectively represent coordinate values from any point to the origin; sigma y 、σ z Are respectively asHorizontal diffusion coefficient, vertical diffusion coefficient; v is the average wind speed, m/s; effective height H of chimney c Is the actual height H of the chimney cs And the smoke plume lifting height delta H c Q is the quality of pollutants discharged by the coal-fired power plant in a detection period;
converting the wind direction coordinate system into a geographic coordinate system:
wherein x and y are coordinate variables used by the Gaussian smoke plume diffusion model, and m is the coordinate variable used by the Gaussian smoke plume diffusion model; x is the number of pol 、y pol A geographical coordinate system coordinate variable m of the point source; x is the number of mon 、y mon Calculating the coordinate variable m of the geographic coordinate system of the point or the monitoring point;
wind direction angle (with the south direction as the positive direction), degree;
from this, the concentration value of the emission m of the coal-fired unit i at the coordinates (x, y, 0) can be obtained:
wherein the content of the first and second substances,
is the concentration value of the pollution m of the unit i,
representing the discharge amount of pollutants m of the unit i;
therefore, the contribution value of the concentration of the pollutant m of the coal-fired unit in the area k at the time t can be expressed by the following formula:
wherein the content of the first and second substances,
representing the pollutant m concentration contribution of the coal-fired unit in the k region at time t,
the concentration of the pollutants m at the detection point j of the unit i at the time t is shown, Y is the number of the pollutant concentration detection points, and N is the number of the coal-fired units.
6. The method according to claim 5, wherein in the step 4, the environmental economic dispatch model objective function includes carbon transaction cost, operation and maintenance cost, wind and light abandonment cost, fuel cost and unit start-stop cost:
min F＝F cem +F om +F ab +F fuel +F sts (13)
in the formula, F cem 、F om 、F ab 、F fuel 、F sts Respectively carbon transaction cost, operation and maintenance cost, wind and light abandoning cost, fuel cost and unit start-stop cost; Δ cem k.t Is the carbon emission transaction amount of the region k at the time t; t is a scheduling period; c inv.g 、ε g The unit investment cost and the operation and maintenance cost coefficient, P, of the power supply g g.t Represents the power of the power source g at time t; p r.t 、
Actual output values and predicted values of wind power and photovoltaic are respectively; a is i 、b i 、c i Respectively the coal burning coefficient, PG, of the coal burning unit i i.t The power of the thermal power generating unit i at the moment t is obtained; epsilon f 、ε ab Respectively a fuel cost coefficient, a wind abandoning cost coefficient and a light abandoning cost coefficient, a ud tableStart stop cost factor, SS i.t The running state of the coal-fired unit i at the time t is 1, the running is performed, and the shutdown is performed 0.
7. The method of claim 6, wherein in the step 4, the constraint conditions of the environmental economic dispatch model include device characteristic constraints:
(1) Carbon capture unit (CCS)
Wherein eta is CCS Represents the power consumption coefficient, V, of CCS CO2.CCS.t Denotes the time point CO 2 Amount of capture, P CCS T represents CCS power consumption at time t; alpha (alpha) ("alpha") CCS Is the trapping efficiency of CCS, V CO2.t The carbon emission of the thermal power generating unit; eta PC Carbon emission coefficient, P, of thermal power generating units C.t The power of the thermal power generating unit.
(2) Methanation unit (ME)
Wherein, V CH4.t 、P CH4.t 、η CH4 The yield of methane, the power consumption and the power consumption coefficient at the moment t are respectively; v H2.CH4.t 、α H2.CH4 Hydrogen consumption and hydrogen consumption coefficient respectively; v CO2.CH4.t 、α CO2.CH4 Respectively the carbon consumption amount and the carbon consumption coefficient;
(3) Electric-hydrogen Hybrid energy storage unit (HES):
in the formula eta EC For the efficiency of the electrical hydrogen production, P EL.t 、V HS.EC.t The power and the hydrogen production quantity of the electric hydrogen production equipment at the time t are respectively; eta FC For fuel cell operating efficiency, P FC.t 、V HS.FC.t Respectively representing the power generation power and the hydrogen consumption of the fuel cell at the time t; p is BA.c.t Charging power for the battery; p is BA.d.t Is the discharge power of the storage battery; eta s Energy storage charging and discharging efficiency; SOC HS.t Energy storage state, SOC, for hydrogen storage at time t HS.0 An initial energy storage state for storing hydrogen, CAP HS Storing installed capacity for hydrogen, H HS.max For maximum storage time of hydrogen, delta s.0 Representing the initial storage capacity ratio; SOC (system on chip) BA.t State of energy storage, SOC, for electrical energy storage at time t BA.0 For an initial energy storage state of the electrical energy storage, CAP BA Charging capacity for electric energy, H BA.max The longest storage time is for electrical energy storage.
8. The method of claim 7, wherein in the step 4, the constraints of the environmental economic dispatch model include balance of electricity, hydrogen and carbon energy flows, that is:
P C.t +P W.t +P PV.t +P H.t +P FC.t +P BA.d.t ＝P CCS.t +P EL.t +P CH4.t +P BA.c.t +L E.t (19)
V HS.EC.t ＝V HS.FC.t +V H2.CH4.t (20)
V CO2.t -V CO2.CH4.t ＝cem t (21)
wherein, P C.t 、P W.t 、P PV.t 、P H.t Respectively thermal power, wind power, photovoltaic and hydroelectric power output at the moment t, L E.t Is the electric load value at the moment t; cem t Carbon emissions at time t.
The output of each thermal power unit needs to meet the total thermal power dispatching requirement, namely:
9. the method of claim 8, wherein in the step 4, the constraint conditions of the environmental economic dispatch model comprise regional environmental pollutant concentration constraints:
wherein, the first and the second end of the pipe are connected with each other,
representing the background concentration of contaminant m at time t in the k-region,
representing the threshold concentration of contaminant m in zone k.
10. The method according to claim 9, wherein in the step 5, a refined operation simulation is performed by taking years as an operation period, and the model is solved to obtain the optimal power output, the operation curve of each device and the power distribution condition of the coal-fired unit.
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| CN116718733A (en) * | 2023-06-28 | 2023-09-08 | 中国海洋大学 | Volatile organic compound concentration calculation method, system, electronic equipment and medium |
| CN117647963A (en) * | 2024-01-29 | 2024-03-05 | 四川速聚智联科技有限公司 | Intelligent liquid discharge control method and system for natural gas square well pool |
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| CN116718733A (en) * | 2023-06-28 | 2023-09-08 | 中国海洋大学 | Volatile organic compound concentration calculation method, system, electronic equipment and medium |
| CN116718733B (en) * | 2023-06-28 | 2024-05-31 | 中国海洋大学 | Volatile organic compound concentration calculation method, system, electronic equipment and medium |
| CN117647963A (en) * | 2024-01-29 | 2024-03-05 | 四川速聚智联科技有限公司 | Intelligent liquid discharge control method and system for natural gas square well pool |
| CN117647963B (en) * | 2024-01-29 | 2024-04-09 | 四川速聚智联科技有限公司 | Intelligent liquid discharge control method and system for natural gas square well pool |
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