CN114021911A - Low-carbon optimization scheduling method for comprehensive energy system of carbon-containing capture device - Google Patents

Low-carbon optimization scheduling method for comprehensive energy system of carbon-containing capture device Download PDF

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CN114021911A
CN114021911A CN202111229089.5A CN202111229089A CN114021911A CN 114021911 A CN114021911 A CN 114021911A CN 202111229089 A CN202111229089 A CN 202111229089A CN 114021911 A CN114021911 A CN 114021911A
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carbon
period
chp
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gas
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郝捷
席楚妍
刘新元
郑惠萍
程雪婷
曲莹
张一帆
王玮茹
高宏
段伟文
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State Grid Electric Power Research Institute Of Sepc
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
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    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
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    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
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Abstract

The invention belongs to the technical field of comprehensive energy, and particularly relates to a low-carbon optimal scheduling method of a comprehensive energy system with a carbon capture device, which comprises the following steps: establishing a comprehensive energy system containing a carbon capture device, and acquiring the predicted values of daily electricity, gas and heat loads of the comprehensive energy system and the predicted values of the output of wind electricity and photovoltaic power generation; step two, constructing an equipment mathematical model of the comprehensive energy system in the step one; constructing a low-carbon optimized dispatching model of the comprehensive energy system, and establishing a target function and a constraint condition corresponding to the low-carbon optimized dispatching model; and step four, substituting the predicted value in the step one, solving the objective function in the step three to obtain an optimal solution, further obtaining an optimal operation scheme, and solving the problems of unreasonable operation and high cost of the conventional comprehensive energy system.

Description

Low-carbon optimization scheduling method for comprehensive energy system of carbon-containing capture device
Technical Field
The invention belongs to the technical field of comprehensive energy, and particularly relates to a low-carbon optimal scheduling method for a comprehensive energy system with a carbon capture device.
Background
With the increase of global energy crisis, the promotion of the construction of green and clean renewable energy systems is the choice of China and even most countries in the world, under the background of carbon neutralization, low carbon emission reduction and the absorption of new energy resources such as wind energy are increasingly emphasized, the application of the currently developed electricity-to-gas technology is gradually popularized, the electricity-to-gas technology is a technology for converting electricity into gas fuel, the method is to decompose water into oxygen and hydrogen by electrolyzing electricity, the hydrogen can further synthesize methane and introduce natural gas pipelines, the electricity-to-gas technology is used as a connecting unit of an electric power network and a natural gas network, and has two functions of electric power load and natural gas source, the production raw material in the second step of reaction of electricity-to-gas is carbon dioxide, and the carbon dioxide has wide source, the carbon dioxide can be sourced from air at present, and can be sourced from the capture of carbon dioxide emitted by a thermal power generating unit.
On the basis of the technology, the electricity-heat-gas comprehensive energy system is greatly developed, the multi-energy coordination complementary operation mode of the comprehensive energy system becomes the direction of future energy utilization, the existing comprehensive energy system model is not completely constructed, influence factors cannot be comprehensively considered, and the comprehensive energy system is unreasonable in operation and high in operation cost.
Disclosure of Invention
The invention overcomes the defects in the prior art and provides a low-carbon optimal scheduling method for a comprehensive energy system of a carbon-containing capture device.
In order to solve the technical problems, the invention adopts the technical scheme that:
the low-carbon optimization scheduling method of the comprehensive energy system of the carbon-containing capture device comprises the following steps:
establishing a comprehensive energy system containing a carbon capture device, and acquiring the predicted values of daily electricity, gas and heat loads of the comprehensive energy system and the predicted values of the output of wind electricity and photovoltaic power generation;
step two, constructing an equipment mathematical model of the integrated energy system in the step one, wherein the integrated energy system comprises: the system comprises a gas turbine, an electric boiler, a cogeneration unit and energy storage equipment;
thirdly, constructing a low-carbon optimized dispatching model of the comprehensive energy system according to the equipment mathematical model in the second step, and establishing a target function and a constraint condition corresponding to the low-carbon optimized dispatching model;
and step four, substituting the predicted value in the step one, solving the objective function in the step three to obtain an optimal solution, and further obtaining an optimal operation scheme.
Further, in the second step, the mathematical model of the gas turbine is as follows:
Gt＝ηG,tGgHL
Figure BDA0003315320380000021
wherein eta isG,tFor the efficiency of the gas turbine power generation, HLIs methane low heating value, HLCan take 9.7 kW.h/m3，GgGas turbine power consumption xi for time t1As a result of the thermoelectric ratio,
Figure BDA0003315320380000022
for the heat-generating power of the gas turbine during the period t, GtThe total output of the gas turbine in the period of t;
the constraint conditions of the mathematical model of the gas turbine equipment are as follows:
Figure BDA0003315320380000023
Figure BDA0003315320380000024
wherein the content of the first and second substances,
Figure BDA0003315320380000025
and
Figure BDA0003315320380000026
respectively is the lower limit and the upper limit of the climbing rate of the gas turbine,
Figure BDA0003315320380000027
in order to minimize the power of the gas turbine,
Figure BDA0003315320380000028
the power of the gas turbine is rated,
Figure BDA0003315320380000029
output power of gas turbine, P, for period tGTIs the output power of the gas turbine. Further, the mathematical model of the electric boiler in the second step is as follows:
PEB,h＝ηEBPEB,e
wherein, PEB,hFor the heat production power of electric boilers, PEB,eFor the power consumed by the electric boiler, ηEBThe heat production efficiency of the electric boiler is improved; the constraint conditions of the mathematical model of the electric boiler equipment are as follows:
Figure BDA00033153203800000210
Figure BDA00033153203800000211
wherein the content of the first and second substances,
Figure BDA00033153203800000212
and
Figure BDA00033153203800000213
respectively is the lower limit and the upper limit of the climbing rate of the electric boiler,
Figure BDA00033153203800000214
and
Figure BDA00033153203800000215
respectively the lower limit and the upper limit of the output of the electric boiler.
Further, the mathematical model of the cogeneration unit (CHP) in the second step is as follows:
HCHP＝ηpCophPCHP(1-ηw-ηs)/ηw
Figure BDA0003315320380000031
wherein HCHPIs the output thermal power of the CHP unit in the period of t, PCHPIs the actual output, eta, of the CHP unit in the t periodwThe generating efficiency, eta, of the micro-combustion engine in the time period of tsIs the heat dissipation loss rate, η, of the period tpFor flue gas recovery rate, i.e. waste heat recovery of bromine refrigerator, CophIs the heating coefficient of the bromine refrigerator, GCHPThe gas consumption of the CHP unit in the period t;
the constraint conditions of the mathematical model of the combined heat and power generation unit (CHP) equipment are as follows:
Figure BDA0003315320380000032
Figure BDA0003315320380000033
Figure BDA0003315320380000034
wherein the content of the first and second substances,
Figure BDA0003315320380000035
for the power supply of the CHP unit in the period t,
Figure BDA0003315320380000036
and
Figure BDA0003315320380000037
respectively the minimum and maximum electric output of the CHP unit,
Figure BDA0003315320380000038
and
Figure BDA0003315320380000039
respectively the minimum and maximum heat output of the CHP unit,
Figure BDA00033153203800000310
and
Figure BDA00033153203800000311
the upper limit and the lower limit of the climbing power of the CHP unit are respectively.
Further, the energy storage device model is:
Et+1＝(1-θ)Et+ηe,cPe,c-Pe,u/ηe,u
wherein E istIs the capacity of the energy storage device in the time period t, theta is the self-loss rate of the energy storage device, etae,cAnd ηe,uRespectively charging and discharging efficiency, P, of the energy storage devicee,cAnd Pe,uRespectively charging and discharging energy of the energy storage equipment;
the constraint conditions of the energy storage equipment model are as follows:
Emin≤Et≤Emax
Figure BDA00033153203800000312
Figure BDA00033153203800000313
E1＝ET
wherein E ismaxAnd EminRespectively the upper and lower limits of the capacity of the energy storage device,
Figure BDA00033153203800000314
and
Figure BDA00033153203800000315
respectively charging energy storage equipment with energy power upper and lower limits,
Figure BDA0003315320380000041
and
Figure BDA0003315320380000042
respectively an upper and a lower limit of the discharge power of the energy storage equipment, E1For the capacity of the energy storage device at the initial moment, ETThe capacity of the energy storage device at the end time.
Further, the objective function in step three is:
minF＝(F1+F2)
wherein, F1Is a function of the system running cost, F2Is a carbon emission cost function;
the system operating cost function is:
Figure BDA0003315320380000043
wherein, ce、ch、cgThe unit energy prices of electricity, heat and gas, Pbuy,t、Hbuy,t、Gbuy,tRespectively the power, heat and gas purchasing power of t time period cfFor the fuel cost of the system, coThe operation and maintenance cost of the system;
Figure BDA0003315320380000044
Figure BDA0003315320380000045
Figure BDA00033153203800000410
volume of methane produced for electrogas conversion during time t, GtTotal output, η, of the gas turbine during the period tG,tFor the efficiency of the gas turbine power generation, HLIs methane low calorific value, gammaP2GFor the efficiency of electric gas-converting apparatus, XPEnergy consumption of the electric gas (P2G) plant for a period t;
Figure BDA0003315320380000046
Figure BDA0003315320380000047
Figure BDA0003315320380000048
ηG,tin order to achieve the power generation efficiency of the gas turbine,
Figure BDA0003315320380000049
cP2Grespectively carbon capture unit and electric gas conversion operating cost coefficient, PCEnergy consumption of carbon-capturing devices, XPFor the energy consumption of the electric gas-converting apparatus during the period t, a1、b1、c1Respectively a second term coefficient, a first term coefficient and a constant term of electric power in the fuel consumption characteristic of the CHP unit2、b2、c2Respectively a quadratic term coefficient, a first term coefficient and a constant term of the heat power in the fuel consumption characteristic of the CHP unit, KiFor each purpose providePreparing corresponding unit output operation and maintenance cost coefficient, PiAs a result of the forces exerted by the respective devices,
Figure BDA0003315320380000051
CO being processed for a period of t2Emission intensity of xP-GThe operating energy required to treat a unit of carbon dioxide,
Figure BDA0003315320380000052
carbon Capture Rate for period t, GtThe total output of the gas turbine in the period of t;
the carbon emission cost function is:
Figure BDA0003315320380000053
Figure BDA0003315320380000054
Figure BDA0003315320380000055
Figure BDA0003315320380000056
mc＝αNGt
eCHP＝ctaxPCHP(αCHP-mCHP)
wherein, ctaxIs the carbon number of the t period, GNNet carbon emission, G, of gas turbine for period tpAmount of carbon trapped in the carbon trap device for t period, GqFor the CO consumed in the process of synthesizing methane by converting electricity into gas in the period of t2Amount of (a), mcCarbon emission quota for gas turbine period t, eCHPIs the carbon emission of the CHP unit,
Figure BDA0003315320380000057
CO being processed for a period of t2The intensity of the discharge of (a) is,
Figure BDA0003315320380000058
carbon Capture Rate for period t, GtTotal gas turbine output, ρ, for a period of tNIs CO2The density of (a) of (b),
Figure BDA0003315320380000059
volume of methane produced for electrogas conversion during period t, alphaNIs a carbon emission reference limit per unit electric quantity, eCHPCarbon emission of CHP units, mCHP、αCHPRespectively unit carbon emission quota and unit carbon emission intensity, P, of the CHP unit in the t periodCHPThe actual output of the CHP unit in the period t.
Further, the constraints in step three include: the power balance constraint conditions comprise the following power balance constraint conditions:
Pbuy,t+PWP+PPV+Gt+PCHP＝PEB,e+PP-G+Pload
wherein, PWP、PPVActual output of wind power and photovoltaic power, P, respectively, at time tCHPIs the actual output of the CHP unit in the t period, PP-GTotal power consumed for the t-period electrotransport gas operation and carbon capture operation, PloadElectric load for a period of t, PEB,eThe power consumption of the electric boiler is;
the constraint conditions of thermodynamic power balance are as follows:
Hbuy,t+HCHP+PEB,h＝Hload
wherein HCHPIs the output thermal power of the CHP unit in the period of t, HloadIs the thermal load of period t, PEB,hGenerating heat power for the electric boiler;
natural gas power balance constraint conditions:
Figure BDA0003315320380000061
wherein the content of the first and second substances,
Figure BDA0003315320380000067
volume of methane produced for electrogas conversion during time t, GgGas turbine power consumption for period t, GCHPGas consumption of the CHP unit in t period, GloadIs the gas load for the period t.
Further, the constraint conditions in step three further include:
electric-to-gas energy climbing restraint:
Figure BDA0003315320380000062
wherein the content of the first and second substances,
Figure BDA0003315320380000063
and
Figure BDA0003315320380000064
respectively the minimum and maximum climbing speed values of the electric gas conversion equipment;
energy consumption operation constraint of the electric gas conversion equipment:
Figure BDA0003315320380000065
wherein the content of the first and second substances,
Figure BDA0003315320380000066
the maximum power for the operation of the electric gas conversion equipment.
Compared with the prior art, the invention has the following beneficial effects.
According to the method, the comprehensive energy system coupling the electricity-to-gas and the carbon capture device is established, two factors of operation cost and carbon emission cost are taken as targets, the time-of-use electricity price of an external power grid is considered, a low-carbon optimization scheduling model is established, all influence factors in the comprehensive energy system are comprehensively considered, the optimal operation scheme of the comprehensive energy system is obtained by optimally solving the low-carbon optimization scheduling model, and the problems that the existing comprehensive energy system is unreasonable in operation and high in cost are solved.
Detailed Description
The present invention is further illustrated by the following specific examples.
The low-carbon optimization scheduling method of the comprehensive energy system of the carbon-containing capture device comprises the following steps:
establishing a comprehensive energy system containing a carbon capture device, and acquiring the predicted values of daily electricity, gas and heat loads of the comprehensive energy system and the predicted values of the output of wind electricity and photovoltaic power generation;
step two, constructing an equipment mathematical model of the integrated energy system in the step one, wherein the integrated energy system comprises: the system comprises a gas turbine, an electric boiler, a cogeneration unit and energy storage equipment;
the mathematical model of the gas turbine is as follows:
Gt＝ηG,tGgHL
Figure BDA0003315320380000071
wherein eta isG,tFor the efficiency of the gas turbine power generation, HLIs methane low heating value, GgGas turbine power consumption xi for time t1As a result of the thermoelectric ratio,
Figure BDA0003315320380000072
for the heat-generating power of the gas turbine during the period t, GtThe total output of the gas turbine in the period of t;
the constraint conditions of the mathematical model of the gas turbine equipment are as follows:
Figure BDA0003315320380000073
Figure BDA0003315320380000074
wherein the content of the first and second substances,
Figure BDA0003315320380000075
and
Figure BDA0003315320380000076
respectively is the lower limit and the upper limit of the climbing rate of the gas turbine,
Figure BDA0003315320380000077
in order to minimize the power of the gas turbine,
Figure BDA0003315320380000078
the power of the gas turbine is rated,
Figure BDA0003315320380000079
output power of gas turbine, P, for period tGTIs the output power of the gas turbine.
The mathematical model of the electric boiler is as follows:
PEB,h＝ηEBPEB,e
wherein, PEB,hFor the heat production power of electric boilers, PEB,eFor the power consumed by the electric boiler, ηEBThe heat production efficiency of the electric boiler is improved;
the constraint conditions of the mathematical model of the electric boiler equipment are as follows:
Figure BDA00033153203800000710
Figure BDA00033153203800000711
wherein the content of the first and second substances,
Figure BDA00033153203800000712
and
Figure BDA00033153203800000713
respectively is the lower limit and the upper limit of the climbing rate of the electric boiler,
Figure BDA00033153203800000714
and
Figure BDA00033153203800000715
respectively the lower limit and the upper limit of the output of the electric boiler.
The mathematical model of the equipment of the combined heat and power generation unit (CHP) is as follows:
HCHP＝ηpCophPCHP(1-ηw-ηs)/ηw
Figure BDA0003315320380000081
wherein HCHPIs the output thermal power of the CHP unit in the period of t, PCHPIs the actual output, eta, of the CHP unit in the t periodwThe generating efficiency, eta, of the micro-combustion engine in the time period of tsIs the heat dissipation loss rate, η, of the period tpFor flue gas recovery rate, CophIs the heating coefficient of the bromine refrigerator, GCHPThe gas consumption of the CHP unit in the period t;
the constraint conditions of the mathematical model of the combined heat and power generation unit (CHP) equipment are as follows:
Figure BDA0003315320380000082
Figure BDA0003315320380000083
Figure BDA0003315320380000084
wherein the content of the first and second substances,
Figure BDA0003315320380000085
for the power supply of the CHP unit in the period t,
Figure BDA0003315320380000086
and
Figure BDA0003315320380000087
respectively the minimum and maximum electric output of the CHP unit,
Figure BDA0003315320380000088
and
Figure BDA0003315320380000089
respectively the minimum and maximum heat output of the CHP unit,
Figure BDA00033153203800000810
and
Figure BDA00033153203800000811
the upper limit and the lower limit of the climbing power of the CHP unit are respectively.
The energy storage equipment model is as follows:
Et+1＝(1-θ)Et+ηe,cPe,c-Pe,u/ηe,u
wherein E istIs the capacity of the energy storage device in the time period t, theta is the self-loss rate of the energy storage device, etae,cAnd ηe,uRespectively charging and discharging efficiency, P, of the energy storage devicee,cAnd Pe,uRespectively charging and discharging energy of the energy storage equipment;
the constraint conditions of the energy storage equipment model are as follows:
Emin≤Et≤Emax
Figure BDA00033153203800000812
Figure BDA00033153203800000813
E1＝ET
wherein E ismaxAnd EminRespectively the upper and lower limits of the capacity of the energy storage device,
Figure BDA0003315320380000091
and
Figure BDA0003315320380000092
respectively charging energy storage equipment with energy power upper and lower limits,
Figure BDA0003315320380000093
and
Figure BDA0003315320380000094
respectively an upper and a lower limit of the discharge power of the energy storage equipment, E1For the capacity of the energy storage device at the initial moment, ETThe capacity of the energy storage device at the end time.
Thirdly, constructing a low-carbon optimized dispatching model of the comprehensive energy system according to the equipment mathematical model in the second step, and establishing a target function and a constraint condition corresponding to the low-carbon optimized dispatching model;
the objective function corresponding to the low-carbon optimized dispatching mode is as follows:
minF＝(F1+F2)
wherein, F1Is a function of the system running cost, F2Is a carbon emission cost function;
the system operating cost function is:
Figure BDA0003315320380000095
wherein, ce、ch、cgThe unit energy prices of electricity, heat and gas, Pbuy,t、Hbuy,t、Gbuy,tRespectively the power, heat and gas purchasing power of t time period cfFor the fuel cost of the system, coThe operation and maintenance cost of the system;
Figure BDA0003315320380000096
Figure BDA0003315320380000097
Figure BDA0003315320380000098
volume of methane produced for electrogas conversion during time t, GtTotal output, η, of the gas turbine during the period tG,tFor the efficiency of the gas turbine power generation, HLIs methane low calorific value, gammaP2GFor the efficiency of electric gas-converting apparatus, XPEnergy consumption of the electric gas (P2G) plant for a period t;
Figure BDA0003315320380000099
Figure BDA0003315320380000101
Figure BDA0003315320380000102
ηG,tin order to achieve the power generation efficiency of the gas turbine,
Figure BDA0003315320380000103
cP2Grespectively carbon capture unit and electric gas conversion operating cost coefficient, PCEnergy consumption of carbon-capturing devices, XPFor the energy consumption of the electric gas-converting apparatus during the period t, a1、b1、c1Respectively a second term coefficient, a first term coefficient and a constant term of electric power in the fuel consumption characteristic of the CHP unit2、b2、c2Respectively a quadratic term coefficient, a first term coefficient and a constant term of the heat power in the fuel consumption characteristic of the CHP unit, KiFor the unit output operation and maintenance cost coefficient, P, corresponding to each equipmentiAs a result of the forces exerted by the respective devices,
Figure BDA0003315320380000104
CO being processed for a period of t2Emission intensity of xP-GThe operating energy required to treat a unit of carbon dioxide,
Figure BDA0003315320380000105
carbon Capture Rate for period t, GtThe total output of the gas turbine in the period of t;
the carbon emission cost function is:
Figure BDA0003315320380000106
Figure BDA0003315320380000107
Figure BDA0003315320380000108
Figure BDA0003315320380000109
mc＝αNGt
eCHP＝ctaxPCHP(αCHP-mCHP)
wherein, ctaxIs the carbon number of the t period, GNNet carbon emission, G, of gas turbine for period tpAmount of carbon trapped in the carbon trap device for t period, GqFor the CO consumed in the process of synthesizing methane by converting electricity into gas in the period of t2Amount of (a), mcCarbon emission quota for gas turbine period t, eCHPIs the carbon emission of the CHP unit,
Figure BDA00033153203800001010
CO being processed for a period of t2The intensity of the discharge of (a) is,
Figure BDA00033153203800001011
carbon Capture Rate for period t, GtTotal gas turbine output, ρ, for a period of tNIs CO2The density of (a) of (b),
Figure BDA00033153203800001012
volume of methane produced for electrogas conversion during period t, alphaNIs a carbon emission reference limit per unit electric quantity, eCHPCarbon emission of CHP units, mCHP、αCHPRespectively unit carbon emission quota and unit carbon emission intensity, P, of the CHP unit in the t periodCHPThe actual output of the CHP unit in the period t.
The constraints in the third step include: the power balance constraint conditions comprise the following power balance constraint conditions:
Pbuy,t+PWP+PPV+Gt+PCHP＝PEB,e+PP-G+Pload
wherein, PWP、PPVActual output of wind power and photovoltaic power, P, respectively, at time tCHPIs the actual output of the CHP unit in the t period, PP-GTotal power consumed for the t-period electrotransport gas operation and carbon capture operation, PloadElectric load for a period of t, PEB,eThe power consumption of the electric boiler is;
the constraint conditions of thermodynamic power balance are as follows:
Hbuy,t+HCHP+PEB,h＝Hload
wherein HCHPIs the output thermal power of the CHP unit in the period of t, HloadIs the thermal load of period t, PEB,hGenerating heat power for the electric boiler;
natural gas power balance constraint conditions:
Figure BDA0003315320380000116
wherein the content of the first and second substances,
Figure BDA0003315320380000117
volume of methane produced for electrogas conversion during time t, GgGas turbine power consumption for period t, GCHPGas consumption of the CHP unit in t period, GloadIs the gas load for the period t.
The constraints in step three further include: electric-to-gas energy climbing restraint:
Figure BDA0003315320380000111
wherein the content of the first and second substances,
Figure BDA0003315320380000112
and
Figure BDA0003315320380000113
respectively the minimum and maximum climbing speed values of the electric gas conversion equipment;
energy consumption operation constraint of the electric gas conversion equipment:
Figure BDA0003315320380000114
wherein the content of the first and second substances,
Figure BDA0003315320380000115
the maximum power for the operation of the electric gas conversion equipment.
And step four, bringing the predicted value in the step one into a low-carbon optimization scheduling model objective function in the step three, and solving the objective function in the step three by using a Yalmip and Cplex solver to obtain an optimal solution, so as to obtain an optimal operation scheme.
The above embodiments are merely illustrative of the principles of the present invention and its effects, and do not limit the present invention. It will be apparent to those skilled in the art that modifications and improvements can be made to the above-described embodiments without departing from the spirit and scope of the invention. Accordingly, it is intended that all equivalent modifications or changes be made by those skilled in the art without departing from the spirit and technical spirit of the present invention, and be covered by the claims of the present invention.

Claims (8)

1. The low-carbon optimization scheduling method of the comprehensive energy system of the carbon-containing capture device is characterized by comprising the following steps of:
establishing a comprehensive energy system containing a carbon capture device, and acquiring the predicted values of daily electricity, gas and heat loads of the comprehensive energy system and the predicted values of the output of wind electricity and photovoltaic power generation;
step two, constructing an equipment mathematical model of the integrated energy system in the step one, wherein the integrated energy system comprises: the system comprises a gas turbine, an electric boiler, a cogeneration unit and energy storage equipment;
thirdly, constructing a low-carbon optimized dispatching model of the comprehensive energy system according to the equipment mathematical model in the second step, and establishing a target function and a constraint condition corresponding to the low-carbon optimized dispatching model;
and step four, substituting the predicted value in the step one, solving the objective function in the step three to obtain an optimal solution, and further obtaining an optimal operation scheme.
2. The method for low-carbon optimized dispatching of integrated energy systems of carbon-containing capture devices as claimed in claim 1,
the equipment mathematical model of the gas turbine in the second step is as follows:
Gt＝ηG,tGgHL
Figure FDA0003315320370000011
wherein eta isG,tFor the efficiency of the gas turbine power generation, HLIs methane low heating value, GgGas turbine power consumption xi for time t1As a result of the thermoelectric ratio,
Figure FDA0003315320370000012
for the heat-generating power of the gas turbine during the period t, GtThe total output of the gas turbine in the period of t;
the constraint conditions of the mathematical model of the gas turbine equipment are as follows:
Figure FDA0003315320370000013
Figure FDA0003315320370000014
wherein the content of the first and second substances,
Figure FDA0003315320370000015
and
Figure FDA0003315320370000016
respectively is the lower limit and the upper limit of the climbing rate of the gas turbine,
Figure FDA0003315320370000017
in order to minimize the power of the gas turbine,
Figure FDA0003315320370000018
the power of the gas turbine is rated,
Figure FDA0003315320370000019
output power of gas turbine, P, for period tGTIs the output power of the gas turbine.
3. The method for low-carbon optimized dispatching of integrated energy system of carbon-containing capture device as claimed in claim 2,
the equipment mathematical model of the electric boiler in the second step is as follows:
PEB,h＝ηEBPEB,e
wherein, PEB,hFor the heat production power of electric boilers, PEB,eFor the power consumed by the electric boiler, ηEBThe heat production efficiency of the electric boiler is improved;
the constraint conditions of the mathematical model of the electric boiler equipment are as follows:
Figure FDA0003315320370000021
Figure FDA0003315320370000022
wherein the content of the first and second substances,
Figure FDA0003315320370000023
and
Figure FDA0003315320370000024
respectively is the lower limit and the upper limit of the climbing rate of the electric boiler,
Figure FDA0003315320370000025
and
Figure FDA0003315320370000026
respectively the lower limit and the upper limit of the output of the electric boiler.
4. The method for low-carbon optimized dispatching of integrated energy system of carbon-containing capture device as claimed in claim 3,
in the second step, the mathematical model of the cogeneration unit (CHP) is as follows:
HCHP＝ηpCophPCHP(1-ηw-ηs)/ηw
Figure FDA0003315320370000027
wherein HCHPIs the output thermal power of the CHP unit in the period of t, PCHPIs the actual output, eta, of the CHP unit in the t periodwThe generating efficiency, eta, of the micro-combustion engine in the time period of tsIs the heat dissipation loss rate, η, of the period tpFor flue gas recovery rate, CophIs the heating coefficient of the bromine refrigerator, GCHPThe gas consumption of the CHP unit in the period t;
the constraint conditions of the mathematical model of the combined heat and power generation unit (CHP) equipment are as follows:
Figure FDA0003315320370000028
Figure FDA0003315320370000029
Figure FDA00033153203700000210
wherein the content of the first and second substances,
Figure FDA00033153203700000211
for the power supply of the CHP unit in the period t,
Figure FDA00033153203700000212
and
Figure FDA00033153203700000213
respectively the minimum and maximum electric output of the CHP unit,
Figure FDA00033153203700000214
and
Figure FDA00033153203700000215
respectively the minimum and maximum heat output of the CHP unit,
Figure FDA00033153203700000216
and
Figure FDA00033153203700000217
the upper limit and the lower limit of the climbing power of the CHP unit are respectively.
5. The low-carbon optimal scheduling method for the integrated energy system with the carbon capturing device according to claim 1, wherein the energy storage equipment model is as follows:
Et+1＝(1-θ)Et+ηe,cPe,c-Pe,u/ηe,u
wherein E istIs the capacity of the energy storage device in the time period t, theta is the self-loss rate of the energy storage device, etae,cAnd ηe,uRespectively charging and discharging efficiency, P, of the energy storage devicee,cAnd Pe,uRespectively charging and discharging energy of the energy storage equipment;
the constraint conditions of the energy storage equipment model are as follows:
Emin≤Et≤Emax
Figure FDA0003315320370000031
Figure FDA0003315320370000032
E1＝ET
wherein E ismaxAnd EminRespectively the upper and lower limits of the capacity of the energy storage device,
Figure FDA0003315320370000033
and
Figure FDA0003315320370000034
respectively charging energy storage equipment with energy power upper and lower limits,
Figure FDA0003315320370000035
and
Figure FDA0003315320370000036
respectively an upper and a lower limit of the discharge power of the energy storage equipment, E1For the capacity of the energy storage device at the initial moment, ETThe capacity of the energy storage device at the end time.
6. The method for low-carbon optimized dispatching of integrated energy systems of carbon-containing capture devices as claimed in claim 1,
the objective function in the third step is:
min F＝(F1+F2)
wherein, F1Is a function of the system running cost, F2Is a carbon emission cost function;
the system operating cost function is:
Figure FDA0003315320370000037
wherein, ce、ch、cgThe unit energy prices of electricity, heat and gas, Pbuy,t、Hbuy,t、Gbuy,tRespectively the power, heat and gas purchasing power of t time period cfFor the fuel cost of the system, coThe operation and maintenance cost of the system;
Figure FDA0003315320370000041
Figure FDA0003315320370000042
Figure FDA00033153203700000413
volume of methane produced for electrogas conversion during time t, GtTotal output, η, of the gas turbine during the period tG,tFor the efficiency of the gas turbine power generation, HLIs methane low calorific value, gammaP2GFor the efficiency of electric gas-converting apparatus, XPEnergy consumption of the electric gas (P2G) plant for a period t;
Figure FDA0003315320370000043
Figure FDA0003315320370000044
Figure FDA0003315320370000045
ηG,tin order to achieve the power generation efficiency of the gas turbine,
Figure FDA0003315320370000046
cP2Grespectively carbon capture unit and electric gas conversion operating cost coefficient, PCEnergy consumption of carbon-capturing devices, XPFor the energy consumption of the electric gas-converting apparatus during the period t, a1、b1、c1Respectively a second term coefficient, a first term coefficient and a constant term of electric power in the fuel consumption characteristic of the CHP unit2、b2、c2Respectively a quadratic term coefficient, a first term coefficient and a constant term of the heat power in the fuel consumption characteristic of the CHP unit, KiFor the unit output operation and maintenance cost coefficient, P, corresponding to each equipmentiAs a result of the forces exerted by the respective devices,
Figure FDA0003315320370000047
CO being processed for a period of t2Emission intensity of xP-GThe operating energy required to treat a unit of carbon dioxide,
Figure FDA0003315320370000048
carbon Capture Rate for period t, GtThe total output of the gas turbine in the period of t;
the carbon emission cost function is:
Figure FDA0003315320370000049
Figure FDA00033153203700000410
Figure FDA00033153203700000411
Figure FDA00033153203700000412
mc＝αNGt
eCHP＝ctaxPCHP(αCHP-mCHP)
wherein, ctaxIs the carbon number of the t period, GNNet carbon emission, G, of gas turbine for period tpAmount of carbon trapped in the carbon trap device for t period, GqFor the CO consumed in the process of synthesizing methane by converting electricity into gas in the period of t2Amount of (a), mcCarbon emission quota for gas turbine period t, eCHPIs the carbon emission of the CHP unit,
Figure FDA0003315320370000051
CO being processed for a period of t2The intensity of the discharge of (a) is,
Figure FDA0003315320370000055
carbon Capture Rate for period t, GtTotal gas turbine output, ρ, for a period of tNIs CO2The density of (a) of (b),
Figure FDA0003315320370000052
volume of methane produced for electrogas conversion during period t, alphaNIs a carbon emission reference limit per unit electric quantity, eCHPCarbon emission of CHP units, mCHP、αCHPRespectively unit carbon emission quota and unit carbon emission intensity, P, of the CHP unit in the t periodCHPThe actual output of the CHP unit in the period t.
7. The integrated energy system low-carbon optimized dispatching method for carbon-containing capture devices as claimed in claim 6, wherein the constraints in the third step comprise: the power balance constraint conditions comprise the following power balance constraint conditions:
Pbuy,t+PWP+PPV+Gt+PCHP＝PEB,e+PP-G+Pload
wherein, PWP、PPVActual output of wind power and photovoltaic power, P, respectively, at time tCHPIs the actual output of the CHP unit in the t period, PP-GTotal power consumed for the t-period electrotransport gas operation and carbon capture operation, PloadElectric load for a period of t, PEB,eThe power consumption of the electric boiler is;
the constraint conditions of thermodynamic power balance are as follows:
Hbuy,t+HCHP+PEB,h＝Hload
wherein HCHPIs the output thermal power of the CHP unit in the period of t, HloadIs the thermal load of period t, PEB,hGenerating heat power for the electric boiler;
natural gas power balance constraint conditions:
Figure FDA0003315320370000053
wherein the content of the first and second substances,
Figure FDA0003315320370000054
volume of methane produced for electrogas conversion during time t, GgGas turbine power consumption for period t, GCHPGas consumption of the CHP unit in t period, GloadIs the gas load for the period t.
8. The integrated energy system low-carbon optimized dispatching method for carbon-containing capture devices as claimed in claim 7, wherein the constraints in the third step comprise:
electric-to-gas energy climbing restraint:
Figure FDA0003315320370000061
wherein the content of the first and second substances,
Figure FDA0003315320370000062
and
Figure FDA0003315320370000063
respectively the minimum and maximum climbing speed values of the electric gas conversion equipment;
energy consumption operation constraint of the electric gas conversion equipment:
Figure FDA0003315320370000064
wherein the content of the first and second substances,
Figure FDA0003315320370000065
the maximum power for the operation of the electric gas conversion equipment.
CN202111229089.5A 2021-10-21 2021-10-21 Low-carbon optimization scheduling method for comprehensive energy system of carbon-containing capture device Pending CN114021911A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114676979A (en) * 2022-03-04 2022-06-28 南方科技大学 Energy scheduling method and device, computer equipment and storage medium
CN115062869A (en) * 2022-08-04 2022-09-16 国网山东省电力公司东营供电公司 Comprehensive energy scheduling method and system considering carbon emission
CN115563816A (en) * 2022-11-30 2023-01-03 国网天津市电力公司城西供电分公司 Low-carbon-oriented photovoltaic and wind power generation grid connection and energy storage optimization method and device

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114676979A (en) * 2022-03-04 2022-06-28 南方科技大学 Energy scheduling method and device, computer equipment and storage medium
CN115062869A (en) * 2022-08-04 2022-09-16 国网山东省电力公司东营供电公司 Comprehensive energy scheduling method and system considering carbon emission
CN115563816A (en) * 2022-11-30 2023-01-03 国网天津市电力公司城西供电分公司 Low-carbon-oriented photovoltaic and wind power generation grid connection and energy storage optimization method and device

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