CN114998052A - Low-carbon economic optimized operation method of comprehensive energy system considering demand response - Google Patents

Low-carbon economic optimized operation method of comprehensive energy system considering demand response Download PDF

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CN114998052A
CN114998052A CN202210622810.5A CN202210622810A CN114998052A CN 114998052 A CN114998052 A CN 114998052A CN 202210622810 A CN202210622810 A CN 202210622810A CN 114998052 A CN114998052 A CN 114998052A
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段建东
赵铭
程冉
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Xian University of Technology
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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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Abstract

The invention discloses a low-carbon economic optimal operation method of a comprehensive energy system considering demand response, which divides user load participating in demand response into longitudinal demand response and transverse demand response and fully considers demand response to IES low-carbon economic optimal operation. Aiming at the defects of the existing model for the consideration of the demand response, the multi-energy load is divided into longitudinal demand response which can be transferred and reduced in time by the same energy type and transverse demand response which can be replaced mutually among different energy types according to the energy utilization characteristics of the load, and modeling is carried out. The superiority of the demand response in the aspects of reducing the carbon emission of the system and promoting the economic operation of the system is verified through numerical simulation.

Description

Low-carbon economic optimized operation method of comprehensive energy system considering demand response
Technical Field
The invention belongs to the technical field of comprehensive energy optimization scheduling, and particularly relates to a low-carbon economic optimization operation method of a comprehensive energy system in consideration of demand response.
Background
In the aspect of realizing IES low-carbon economic optimized operation, the current carbon trading mechanism is recognizedIs one of the most effective means. In carbon trading, governments and related departments manage carbon emission, and each carbon emission main body is prompted to voluntarily reduce emission in the market so as to achieve the purpose of reducing CO 2 And controlling the total emission. On the other hand, with the advanced innovation of the energy market, in the integrated energy system, in addition to the economical efficiency of energy supply realized by the energy coupling device on the supply side, the response characteristic on the load side is not negligible.
With the continuous development of comprehensive energy systems and the gradual opening of energy markets, demand responses are more and more widely involved in the optimized operation of the IES, and demand responses based on price and excitation, electricity price demand responses and the like are all taken into consideration when an IES low-carbon economic optimized operation model is established. It can still be optimized from two aspects: 1) the demand response has a smooth load curve, the benefit of curve peak-valley difference is reduced, and the economy of system operation can be further optimized by introducing the demand response into the IES; 2) in addition to considering the electric demand response in the IES, the comprehensive demand response of various energy systems should be paid attention, and in the carbon trading market environment, the carbon reduction benefit of the comprehensive demand response in the operation of the comprehensive energy system needs to be further mined.
In summary, an IES low-carbon economic optimization operation model based on demand response is researched aiming at a comprehensive energy operation model, so that the peak-valley difference of a load curve is reduced, the optimization of the load curve is realized, and the reduction of CO generated in IES operation is realized 2 And the economical efficiency of the system operation is improved while the discharge amount is reduced.
Disclosure of Invention
The invention aims to provide a low-carbon economic optimization operation method of a comprehensive energy system considering demand response. And various energy demand responses on the load side are considered in the IES, the low-carbon benefit of the demand responses in the IES is further excavated, and the low-carbon economic optimization operation of the IES is promoted.
The technical scheme adopted by the invention is that the low-carbon economic optimization operation method of the comprehensive energy system considering the demand response mainly comprises the steps of establishing a longitudinal demand response model and a transverse demand response model by analyzing IES load characteristics and establishing an IES low-carbon economic optimization operation model considering the demand response. The method is implemented according to the following steps:
step 1, analyzing the load characteristics of an integrated energy system IES;
step 2, respectively establishing a longitudinal demand response model and a transverse demand response model;
step 3, constructing a low-carbon economic optimization operation model of the comprehensive energy system considering demand response;
and 4, solving the low-carbon economic optimization operation model of the comprehensive energy system by using a CPLEX solver.
The specific implementation process of the step 1 is as follows:
according to the energy utilization characteristics of the loads, the multi-energy loads are divided into longitudinal demand responses which can be transferred and reduced in time by the same energy type and transverse demand responses which can be replaced mutually among different energy types, and the specific classification is as follows:
1) longitudinal demand responses include transferable electric/gas demand responses and curtailable electric/gas demand responses. Such loads use only one energy source, and the shift of the energy period and the reduction of the amount of power used can be realized according to the electricity rate and the incentive scheme.
2) Lateral demand response refers to alternative electrical/pneumatic loads. Such loads may use a variety of energy sources, with the alternative effects of energy sources enabling flexible adjustment of the load.
The specific implementation process of the step 2 is as follows:
step 2.1, establishing a longitudinal demand response model;
in the IES, the electric power system and the natural gas system respectively guide the transferable load to carry out electric quantity transfer in a unit energy consumption time period in the forms of time-of-use electricity price and time-of-use gas price, and the total load quantity in the total time scale is kept unchanged, so that load peak clipping and valley filling are realized, and the operation reliability and the economical efficiency of the IES are improved. The transferable electricity/gas load modeling adopts an elastic matrix method, the elastic matrix is
Figure BDA0003677516760000031
In the formula (1), ε represents an elastic coefficient, a diagonal represents a self-elasticity, and the others represent mutual elasticities. The self-elasticity is negative, which represents that the corresponding load in the time interval is reduced; the mutual elasticity is positive, and the load response quantity to the price change in other time periods is represented.
Coefficient of elasticity ε
Figure BDA0003677516760000032
In the formula (2), p and q are the electric quantity and the time-sharing price of the transferable load; and delta p and delta q are the electric quantity variable quantity and the time-sharing price variable quantity of the transferable load.
The mathematical model capable of transferring electric and gas loads is
Figure BDA0003677516760000033
Figure BDA0003677516760000034
In the formula (3), P TRY 、P TR An initial load that is a transferable electrical load and a responsive electrical load; p TR1 …P TRt The electric load after the electric load response can be transferred in each time period of 1-t; delta P TR The amount of transfer for transferable electrical load; the diagonal line of the elastic matrix is the self-elasticity of the electric load, and the others are the mutual elasticity of the electric load; Δ q of E1 …Δq Et The time-sharing price variable quantity of the transferable electric load in each time period of 1-t; q. q.s E1 …q Et The time-sharing price of the transferable electric load can be achieved in each time period of 1-t. In the formula (4), E TRY 、E TR The initial load is transferable gas load and the gas load after response; e TR1 …E TRt The gas load after the gas load response can be transferred in each time period of 1-t; delta E TR The transfer quantity is the transferable gas load; the diagonal line of the elastic matrix is air load self-elasticity, and the others are air load mutual elasticity; Δ q of E1 …Δq Et The time-sharing price variable quantity of the transferable gas load in each time period of 1-t; q. q.s E1 …q Et Is transferable for each time interval of 1-tTime-of-use price of gas load;
the total load amount of the transferable electric/gas load is unchanged in one operation period, the power of the transferable load in unit time is limited by upper and lower limits, and the constraint is as follows:
Figure BDA0003677516760000041
Figure BDA0003677516760000042
in formulae (5) and (6), P TRY,t 、P TR,t Transferring the initial load of the electrical load and the responded electrical load for a period t; e TRY,t 、E TR,t The initial load of the gas load and the gas load after response can be transferred for the period t; delta P TR,max 、ΔP TR,min The upper limit and the lower limit of the transferable electric load transfer amount; delta E TR,max 、ΔE TR,min The upper and lower limits of the transferable gas load transfer amount.
The reducible power/gas load is a demand response load capable of performing power reduction within a certain range according to the contract content. In the comprehensive energy system, the load relieves the energy shortage in the operation process by reducing the power of the corresponding load according to the energy supply and demand conditions of the system. The mathematical model for the reducible electrical/gas load is:
Figure BDA0003677516760000043
in the formula (7), P CUY,t 、P CU,t The initial load and the responded load of the electric load can be reduced for the t period; e CUY,t 、E CU,t The initial load of the gas load and the load after response can be reduced for the time period t; delta P CU,t 、ΔE CU,t The reduction of the electrical load and the air load can be reduced for the t period; b CUE,t 、b CUG,t In a reduced state in which the electric/gas load can be reduced, a value of 1 indicates that the reduction adjustment is performed during the period t, and a value of 0 indicates that the reduction is not performedReducing and adjusting; theta E,t 、θ G,t In order to allow a reduction ratio of the electric/gas load to be reduced, a value of 1 indicates that the load is completely reduced during the t period, and a value of 0 indicates that no reduction adjustment has occurred.
The reducible power/gas load needs to satisfy a reduced power range constraint of
Figure BDA0003677516760000051
In the formula (8), Δ P CU,max 、ΔP CU,min The upper and lower limits of the electric load reduction can be reduced; delta E CU,max 、ΔE CU,min The upper and lower limits of the air load reduction amount can be reduced.
And 2.2, establishing a transverse demand response model.
The replaceable energy source can replace electricity/gas load under the guidance of different energy source prices and different electricity demands, and the replacement among different energy sources can be realized through the coupling among the energy sources. The expression of energy coupling is
Figure BDA0003677516760000052
In the formula (9), P SUY,t 、P SU,t An initial load and a responded load which can replace the electric load; e SUY,t 、E SU,t Initial load and responded load which can replace gas load; delta P SU 、ΔE SU Is a substitute quantity that can substitute for the electrical load and the gas load;
Figure BDA0003677516760000053
an alternative state in which the electrical load can be replaced;
Figure BDA0003677516760000054
is an alternative state that can replace the gas load;
Figure BDA0003677516760000055
replacing the electric energy replacing amount of the gas load with the electric energy replacing amount of the electric load;
Figure BDA0003677516760000056
the gas energy replacing amount of the gas load replacing the electric load and the gas energy replacing amount of the electric load replacing the gas load.
The alternative power range of the alternative electrical/gas load satisfies the constraint:
Figure BDA0003677516760000057
Figure BDA0003677516760000058
in the formulae (10) and (11),
Figure BDA0003677516760000059
the upper limit and the lower limit of the electric energy substitution amount for substituting the electric load for the gas load;
Figure BDA0003677516760000061
the upper limit and the lower limit of the electric energy substitution amount for substituting the electric load for the gas load;
Figure BDA0003677516760000062
the upper limit and the lower limit of the gas energy substitution amount for substituting the gas load for the electric load;
Figure BDA0003677516760000063
the upper limit and the lower limit of the gas energy substitution amount for substituting the gas load for the electric load.
The specific implementation process of the step 3 is as follows:
step 3.1, constructing a low-carbon operation objective function by considering the energy purchase cost, the demand response cost and the carbon transaction cost of a superior power grid and a gas well;
the objective function of the IES low-carbon economic optimization operation model considering the demand response is
min f＝f 1 +f 2 (12)
Figure BDA0003677516760000064
Figure BDA0003677516760000065
In equations (12), (13) and (14), f1 is the system operating cost; f2 is carbon transaction cost; p is E,t The generated power of the coal-fired unit is t time period; delta P CU 、ΔE CU The reduction of the electrical load and the air load can be reduced; p GT,t The active power generated by the gas turbine in the period t; gamma ray CUE 、γ CUG Reducing the cost coefficient for the unit capable of reducing the electric/gas load; ξ is the reward base price for carbon trading; delta E is the length of the carbon emission interval; kappa is the carbon transaction price growth rate in the penalty stage; λ is the carbon trading price growth rate in the reward phase; ρ is a unit of a gradient E,t The unit electricity price of the superior power grid in the period t; rho G,t The unit price of the natural gas in the t time period; e IES The total gratuitous carbon emission quota of the system is obtained; e IES,C Is the total carbon emissions for the actual operation of the system.
Step 3.2, considering power network constraint, node voltage constraint, natural gas network constraint and the like during system operation, wherein the constraint conditions are as follows:
power network constraints:
Figure BDA0003677516760000071
Figure BDA0003677516760000072
Figure BDA0003677516760000073
Figure BDA0003677516760000074
P EL,t ＝P TR,t +P CU,t +P SU,t (19)
in formulae (15), (16), (17), (18) and (19), P ij,t 、Q ij,t Active and reactive power for the ij branch; p jk,t 、Q jk,t Active power and reactive power are provided for the jk branch; p GT,t 、Q GT,t The active power and the reactive power of the gas turbine are generated in the period t; p WT,t 、Q WT,t Wind power active power and reactive power in a t time period; p is EC,t 、Q EC,t Inputting active electric power and reactive electric power for the electrolytic cell in a period t; p EL,t 、Q EL,t The active power and the reactive power of the electric load in a t period; delta P W,t 、ΔQ W,t The wind abandoning active amount and the wind abandoning inactive amount are in t time period; r is ij 、x ij Resistance and reactance for the ij branch; u shape i,t 、U j,t Voltages at nodes i and j; i is ij,t 、U ij,t The current flows through the ij branch and the voltage difference at the ij node.
Node voltage constraint:
U j,min ≤U j,t ≤U j,max (20)
in formula (20), U j,max 、U j,min The upper and lower limits allowed for the voltage at the j node.
Natural gas network constraints:
Figure BDA0003677516760000075
Figure BDA0003677516760000076
in the formulae (21) and (22), sgn (. pi.) ( i,t ,π j,t ) When the pressure of the node i is higher than that of the node j, the value is 1, otherwise, the value is-1; pi i,t 、π j,t The natural gas pressure of an i node and a j node in a t period; pi p,t 、π q,t The natural gas pressure of a p node and a q node in a t period; fp p,t The pipeline flow of the natural gas pipeline p in the period t; phi is a p Is the gas flow transmission parameter of the natural gas pipeline p.
Node airflow balance constraint:
Figure BDA0003677516760000081
P GL,t ＝E TR,t +E CU,t +E SU,t (24)
in the formulas (23) and (24), v (n), u (n) are gas pipeline sets with n nodes as end points and start nodes; x (n), Z (n) is a methane reactor and a gas turbine set at n node; psi H2G 、ψ GT Conversion factors for the methane reactor and the gas turbine; p H2G,t Methane reactor power for a period of t; p GL,t The gas load active power is in the period of t.
And (3) restricting the flow of the pipeline:
fq mn,min ≤fq mn,t ≤fq mn,max (25)
in formula (25), fq mn,t The flow rate of the pipeline mn is shown; fq of mn,max 、fq mn,min The upper and lower flow limits of the mn pipeline.
And (3) node air pressure constraint:
π m,min ≤π m,t ≤π m,max (26)
in the formula (26), n m,t Is the air pressure at node m; pi m,max 、π m,min Is the upper and lower limit of the air pressure allowance at the node m.
And (3) power exchange constraint with a superior power grid and a natural gas network:
Figure BDA0003677516760000082
in formula (27), P E,t The purchased electric quantity is t time period; p G,t The quantity of the purchased natural gas in the t period; p Emax 、P Emin Purchasing an upper limit and a lower limit of electric quantity for the system; p Gmax 、P Gmin Purchase gas amount for systemAnd (4) limiting.
Hydrogen energy balance constraint:
Figure BDA0003677516760000083
in the formula (28), y (n) is a set of hydrogen storage tanks at the n-node; p P2H,t Generating a volume of hydrogen gas for the electrolyzer; p H2H,t The volume of hydrogen consumed for the methane reactor;
Figure BDA0003677516760000084
the air inlet quantity and the air outlet quantity of the hydrogen storage tank.
And (3) output constraint of each unit:
Figure BDA0003677516760000091
in formula (29), P WTmax 、P WTmin The output power is the upper and lower limits of wind power; p EC,t Inputting active electric power for the electrolytic cell in a period t; e MRHmax 、E MRHmin The upper and lower limits for the hydrogen input to the methane reactor; e MRH,t Is hydrogen input by the methane reactor during the period t; p WTmax 、P WTmin The output power is the upper and lower limits of wind power; p WT,t Wind power active power is obtained for t time period; p GTmax 、P GTmin The upper and lower limits of the output of the gas turbine; p GT,t The active power generated by the gas turbine in the period t; delta P GTmax 、ΔP GTmin The upper and lower limits of the climbing power of the gas turbine.
The specific implementation process of the step 4 is as follows:
step 4.1, setting model input parameters: inputting original load data of an electric load and an air load, and inputting output data of the wind power and corresponding parameters of each unit in the system;
4.2, performing linearization treatment on the constructed IES low-carbon economic optimization operation model by adopting a second-order cone relaxation and incremental linearization method, performing simulation solution in an MATLAB by using a CPLEX solver, and obtaining the optimal cost under the operation scheme;
4.3, if the constraint condition of the step 3.2 is met, stopping calculation; if the condition is not met, adjusting the parameters to calculate again;
and 4.4, obtaining the operation condition of each unit in the comprehensive energy system, and determining the operation scheme of the system.
The invention has the beneficial effects that:
1) the integrated energy system IES low-carbon economic optimization operation model constructed by the invention divides the user load participating in demand response into longitudinal demand response and transverse demand response, and is effectively combined with a reward and punishment step-type carbon transaction mechanism;
2) the energy consumption habit and the energy consumption mode of a user can be changed in consideration of demand response, so that the peak-valley difference of the load curve is reduced, and the optimization of the load curve is realized;
3) under the reward and punishment stepped carbon transaction mechanism, the flexible coordination performance of the load side can be fully exerted by simultaneously considering the longitudinal demand response and the transverse demand response, and the reduction of CO generated in IES operation is realized 2 And the economical efficiency of the system operation is improved while the discharge amount is reduced.
Drawings
FIG. 1 is a diagram of a low-carbon economic optimization operation model of an integrated energy system in consideration of demand response;
FIG. 2 is a load classification diagram of the integrated energy system of the present invention;
FIG. 3 is a flow chart of the model solution algorithm of the present invention;
FIG. 4 is a schematic diagram of the integrated energy system of the present invention;
FIG. 5 is a graph of the operating results of the power subsystem during various time periods after the optimized operation of the present invention;
FIG. 6 is a graph of the results of the operation of the natural gas subsystem during various periods of time after the optimized operation of the present invention;
FIG. 7 is a graph of the results of the operation of the hydrogen energy subsystem during various periods of time after the optimized operation of the present invention;
FIG. 8 is a graph of scenario 2 electrical load changes in accordance with the present invention;
FIG. 9 is a graph of the air load change for scenario 2 of the present invention;
FIG. 10 is a graph of scenario 3 electrical and gas load changes in accordance with the present invention;
FIG. 11 is a graph of the electrical load change for scenarios 1 and 4 of the present invention;
FIG. 12 is a schematic view of scenarios 1-4 carbon emissions according to the present invention;
FIG. 13 is a schematic diagram of scenario 1 and scenario 4 electricity purchases of the present invention;
fig. 14 is a schematic view of the gas purchase amount of scenario 1 and scenario 4 of the present invention.
Detailed Description
The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.
The low-carbon economic optimization operation model of the comprehensive energy system considering demand response is shown in figure 1, and the specific implementation steps are as follows:
step 1, analyzing the load characteristics of the comprehensive energy system, and dividing the load into a rigid load which cannot be adjusted and a flexible load with adjustment potential;
according to the energy utilization characteristics of the loads, the multi-energy loads are divided into longitudinal demand responses which can be transferred and reduced in time by the same energy type and transverse demand responses which can be replaced mutually among different energy types, and the specific classification is as follows:
1) the longitudinal demand response includes a transferable electrical/pneumatic demand response and a cuttable electrical/pneumatic demand response. Such loads use only one energy source, and the shift of the energy period and the reduction of the amount of power used can be realized according to the electricity rate and the incentive scheme.
2) Lateral demand response refers to alternative electrical/gas loads. Such loads may use a variety of energy sources, with the alternative effects of energy sources enabling flexible adjustment of the load. The integrated energy system load classification is shown in fig. 2.
Step 2, respectively establishing a longitudinal demand response model and a transverse demand response model;
step 2.1, establishing a longitudinal demand response model;
in the IES, a power system and a natural gas system respectively guide a transferable load to transfer electric quantity in a unit energy consumption time period in the forms of time-of-use electricity price and time-of-use gas price, and the total load quantity in the total time scale is kept unchanged, so that load peak clipping and valley filling are realized, and the operation reliability and the economy of the IES are improved. The transferable electric/gas load modeling adopts an elastic matrix method, the elastic matrix is
Figure BDA0003677516760000111
In the formula (1), ε represents an elastic coefficient, a diagonal represents a self-elasticity, and the others represent mutual elasticities. The self-elasticity is negative, which represents that the corresponding load in the time interval is reduced; the mutual elasticity is positive, and the load response quantity to the price change in other time periods is represented.
Has a coefficient of elasticity ε of
Figure BDA0003677516760000121
In the formula (2), p and q are the electric quantity and time-sharing price of the transferable load; and delta p and delta q are the electric quantity variable quantity and the time-sharing price variable quantity of the transferable load.
The mathematical model capable of transferring electric and gas loads is
Figure BDA0003677516760000122
Figure BDA0003677516760000123
In formulae (3) and (4), P TRY 、P TR An initial load that is a transferable electrical load and a responsive electrical load;
ΔP TR the amount of transfer for transferable electrical load; e TRY 、E TR The initial load is transferable gas load and the gas load after response; delta E TR Is the amount of transfer of the transferable gas load.
The total load amount of the transferable electric/gas load is unchanged in one operation period, the power of the transferable load in unit time is limited by upper and lower limits, and the constraint is as follows:
Figure BDA0003677516760000124
Figure BDA0003677516760000125
in formulae (5) and (6), P TRY,t 、P TR,t Transferring the initial load of the electrical load and the responded electrical load for a period t; e TRY,t 、E TR,t The initial load of the gas load and the gas load after response can be transferred for the period t; delta P TR,max 、ΔP TR,min The upper limit and the lower limit of the transferable electric load transfer amount; delta E TR,max 、ΔE TR,min The upper and lower limits of the transferable gas load transfer amount.
The reducible power/gas load is a demand response load capable of performing power reduction within a certain range according to the contract content. In the comprehensive energy system, the load relieves the energy shortage in the operation process by reducing the power of the corresponding load according to the energy supply and demand conditions of the system. The mathematical model for reducing the electric/gas load is
Figure BDA0003677516760000131
In the formula (7), P CUY,t 、P CU,t The initial load and the responded load of the electric load can be reduced; e CUY,t 、E CU,t The initial load and the responded load of the air load can be reduced; delta P CU 、ΔE CU The reduction of the electrical load and the air load can be reduced; b CUE,t 、b CUG,t In a reduction state of reducible electric/gas load, a value of 1 indicates that reduction adjustment occurs in a period t, and a value of 0 indicates that reduction adjustment does not occur; theta E,t 、θ G,t In order to allow a reduction ratio of the electric/gas load to be reduced, a value of 1 indicates that the load is completely reduced during the t period, and a value of 0 indicates that no reduction adjustment has occurred.
The reducible power/gas load needs to satisfy the reduced power range constraint of
Figure BDA0003677516760000132
In the formula (8), Δ P CU,max 、ΔP CU,min The upper and lower limits of the electric load reduction can be reduced; delta E CU,max 、ΔE CU,min The upper and lower limits of the air load reduction amount can be reduced.
And 2.2, establishing a transverse demand response model.
The replaceable energy source can replace electricity/gas load under the guidance of different energy source prices and different electricity demands, and the replacement among different energy sources can be realized through the coupling among the energy sources. The expression of energy coupling is
Figure BDA0003677516760000133
In the formula (9), P SUY,t 、P SU,t The initial load and the responded load which can replace the electric load; e SUY,t 、E SU,t Initial load and responded load which can replace gas load; delta P SU 、ΔE SU Is a substitute quantity that can substitute for the electrical load and the gas load;
Figure BDA0003677516760000141
an alternative state in which the electrical load can be replaced;
Figure BDA0003677516760000142
is an alternative state that can replace the gas load;
Figure BDA0003677516760000143
replacing the electric energy replacing amount of the gas load with the electric energy replacing amount of the electric load;
Figure BDA0003677516760000144
the gas energy replacing amount of the gas load replacing the electric load and the gas energy replacing amount of the electric load replacing the gas load.
The alternative power range of the alternative electrical/gas load satisfies the constraint:
Figure BDA0003677516760000145
Figure BDA0003677516760000146
in the formulae (10) and (11),
Figure BDA0003677516760000147
the upper limit and the lower limit of the electric energy substitution amount for substituting the electric load for the gas load;
Figure BDA0003677516760000148
the upper limit and the lower limit of the electric energy substitution amount for substituting the electric load for the gas load;
Figure BDA0003677516760000149
the upper limit and the lower limit of the gas energy substitution amount for substituting the gas load for the electric load;
Figure BDA00036775167600001410
the upper limit and the lower limit of the gas energy substitution amount for substituting the gas load for the electric load.
Step 3, constructing a low-carbon economic optimization operation model of the comprehensive energy system considering demand response;
step 3.1, constructing a low-carbon operation objective function by considering the energy purchase cost, the demand response cost and the carbon transaction cost of a superior power grid and a gas well;
the objective function of the IES low-carbon economic optimization operation model considering the demand response is
min f＝f 1 +f 2 (12)
Figure BDA00036775167600001411
Figure BDA0003677516760000151
In formulae (12), (13) and (14), f 1 The system operating cost; f. of 2 Is the carbon transaction cost; p E,t The generated power of the coal-fired unit is t time period; delta P CU 、ΔE CU The reduction of the electrical load and the air load can be reduced; p is GT,t The generated power of the gas turbine is t time period; gamma ray CUE 、γ CUG Reducing the cost coefficient for the unit capable of reducing the electric/gas load; xi is the reward base price of the carbon transaction; delta E is the length of the carbon emission interval; kappa is the carbon transaction price growth rate in the penalty stage; λ is the carbon trading price growth rate in the reward phase; rho E,t The unit electricity price of the superior power grid in the period t; rho G,t The unit price of the natural gas in the t time period; e IES The total uncompensated carbon emission quota of the system; e IES,C Is the total carbon emission for the actual operation of the system;
step 3.2, considering power network constraint, node voltage constraint, natural gas network constraint and the like during system operation, wherein the constraint conditions are as follows:
power network constraints:
Figure BDA0003677516760000152
Figure BDA0003677516760000153
Figure BDA0003677516760000154
Figure BDA0003677516760000155
P EL,t ＝P TR,t +P CU,t +P SU,t (19)
in formulae (15), (16), (17), (18) and (19)V (j), u (j) are the branch set with j node as the first and last node; z (j), x (j), y (j) are the gas turbine, fan and electrolyzer set at node j; p is ij,t 、Q ij,t Active and reactive power for the ij branch; p jk,t 、Q jk,t Active power and reactive power are provided for the jk branch; p GT,t 、Q GT,t The active power and the reactive power of the gas turbine are generated in the period t; p is WT,t 、Q WT,t Wind power active power and reactive power in a time period t; p EC,t 、Q EC,t Inputting active electric power and reactive electric power for the electrolytic cell in a period t; p EL,t 、Q EL,t The active power and the reactive power of the electric load are t time periods; delta P W,t 、ΔQ W,t The wind abandoning active amount and the wind abandoning inactive amount are in t time period; r is ij 、x ij Resistance and reactance for the ij branch; u shape i,t 、U j,t Voltages at nodes i and j; I.C. A ij,t 、U ij,t A current flows through the ij branch and the voltage difference of the ij node is obtained;
node voltage constraint:
U j,min ≤U j,t ≤U j,max (20)
in formula (20), U j,max 、U j,min The upper and lower limits allowed for the voltage at the j node.
Natural gas network constraints:
Figure BDA0003677516760000161
Figure BDA0003677516760000162
in the formulae (21) and (22), sgn (. pi.) ( i,t ,π j,t ) The value is 1 when the pressure of the node i is higher than that of the node j, and is-1 otherwise; pi i,t 、π j,t The natural gas pressure of an i node and a j node in a t period; pi p,t 、π q,t The natural gas pressure of a p node and a q node in a t period; fp p,t Pipeline flow for a period t natural gas pipeline pAn amount; phi is a p Is the gas flow transmission parameter of the natural gas pipeline p;
node airflow balance constraint:
Figure BDA0003677516760000163
P GL,t ＝E TR,t +E CU,t +E SU,t (24)
in the formulas (23) and (24), v (n), u (n) are gas pipeline sets with n nodes as end points and start nodes; x (n), Z (n) is a methane reactor and a gas turbine set at n node; fq of mn,t 、fq nl,t The flow rates of the pipelines mn and nl in the period t; psi H2G 、ψ GT Conversion factors for the methane reactor and the gas turbine; p H2G,t Methane reactor power for a period of t; p GL,t The gas load active power is t time period;
and (3) restricting the flow of the pipeline:
fq mn,min ≤fq mn,t ≤fq mn,max (25)
in formula (25), fq mn,max 、fq mn,min The upper and lower flow limits of the mn pipeline.
And (3) node air pressure constraint:
π m,min ≤π m,t ≤π m,max (26)
in the formula (26), n m,max 、π m,min Is the upper and lower limit of the air pressure allowance at the node m.
And (3) power exchange constraint with a superior power grid and a natural gas network:
Figure BDA0003677516760000171
in the formula (27), P Emax 、P Emin Purchasing an upper limit and a lower limit of electric quantity for the system; p is Gmax 、P Gmin The upper and lower limits of the gas purchasing quantity of the system.
Hydrogen energy balance constraint:
Figure BDA0003677516760000172
in the formula (28), y (n) is a set of hydrogen storage tanks at the n-node; p P2H,t Generating a volume of hydrogen gas for the electrolyzer; p H2H,t The volume of hydrogen consumed for the methane reactor;
Figure BDA0003677516760000173
the air inlet quantity and the air outlet quantity of the hydrogen storage tank.
And (3) output constraint of each unit:
Figure BDA0003677516760000174
in formula (29), P WTmax 、P WTmin The output power is the upper and lower limits of wind power; p EC,t Input active electric power for the electrolyzer during the period t; e MRHmax 、E MRHmin The upper and lower limits for the hydrogen input to the methane reactor; e MRH,t Is hydrogen input by the methane reactor during the period t; p WTmax 、P WTmin The upper limit and the lower limit of the wind power output are set; p WT,t Wind power active power is obtained for t time period; p is GTmax 、P GTmin The upper and lower limits of the output of the gas turbine; p GT,t The active power generated by the gas turbine in the period t; delta P GTmax 、ΔP GTmin The upper and lower limits of the climbing power of the gas turbine;
and 4, solving the optimized scheduling model.
The IES low-carbon economic optimization operation model constructed by the invention is a non-convex nonlinear model, after second-order cone relaxation and linearization processing are carried out on nonlinear terms in the model, the IES low-carbon economic optimization operation model is a mixed integer linear programming model, and a CPLEX solver is adopted to obtain a result. The main flow of model solution is shown in fig. 3.
Step 1, setting model input parameters. Inputting original load data of an electric load and an air load, and inputting output data of the wind power and corresponding parameters of each unit in the system;
step 2, performing linearization treatment on the constructed IES low-carbon economic optimization operation model by adopting a second-order cone relaxation and incremental linearization means, performing simulation solution in an MATLAB by using a CPLEX solver, and obtaining the optimal cost under the operation scheme;
step 3, if the constraint condition is met, stopping calculation; if the condition is not met, adjusting the parameters to calculate again;
and 4, obtaining the operation condition of each unit in the comprehensive energy system, and determining the operation scheme of the system.
Examples
The comprehensive energy system is taken as an example for simulation analysis, and the structure of the comprehensive energy system is shown in figure 4. Table 1 is a price elasticity matrix for alternative electrical/pneumatic demand responses.
TABLE 1 elastic matrix coefficients
Figure BDA0003677516760000181
In order to verify the advantages of the demand response considered in this chapter, the following 4 scenes are set for comparative analysis. 1) IES low-carbon economic optimization operation without considering demand response; 2) the IES low-carbon economic optimization operation considering the longitudinal demand response; 3) considering IES low-carbon economic optimization operation of transverse demand response; 4) the IES low carbon economic optimization run considering longitudinal and lateral demand responses.
The IES optimization operation results are shown in FIGS. 5-7. Wherein, fig. 5 is the operation result of the electric energy subsystem, fig. 6 is the operation result of the natural gas subsystem, and fig. 7 is the operation result of the hydrogen energy subsystem.
Scenario 2 electrical load and air load changes are shown in fig. 8 and 9, respectively. As can be seen from fig. 8, 0: 00 to 6: and 00 is a low electricity price valley period, the demand of the electric load is low at the moment, and the user actively transfers the electric loads of other high electricity price periods to the period under the guidance of time-of-use electricity prices, and the transferable loads are positive. Meanwhile, the wind power output is in the peak period, and partial wind power in the system is difficult to be consumed, so that surplus wind power can be converted into hydrogen for storage by utilizing P2G. In the time period from 11:00 to 22:00, the user actively transfers the load in the time period to other time periods with lower electricity price, and the transferable load is negative. Meanwhile, at 11, where the load demand is high: 00. 15: 00 and 19: 00 to 20: in the 00 time period, the system transfers partial electric loads and properly reduces the peak-valley difference of the load curve by properly reducing the partial electric loads on the premise of ensuring the operation economy, thereby relieving the energy supply pressure of the IES when the electric loads are at the peak value. As can be seen from fig. 9, there is a similar longitudinal response characteristic for the gas load demand response and the electrical load demand response of the system. At a temperature of 0: 00 to 5: 00. 14: 00 to 16: in the low-gas-price period such as 00, the user transfers the loads of other periods to the period under the guidance of time-of-use gas price, and the transferable load is positive. In the following step 7: 00 to 12: 00. 18: 00 to 20: and 00 and other periods with higher gas prices, the load can be transferred to other periods with lower gas prices, and the transferable load is negative. Meanwhile, in a period when the gas load demand is high, besides the transferable load response, the system reduces the peak-valley difference of the load curve by reducing part of the gas load, and relieves the energy supply pressure of the comprehensive energy system when the natural gas load is at a high peak value.
The electrical load and the air load change of scenario 3 are shown in fig. 10. As can be seen, in the following 1:00 to 6: in the 00 time period, the electricity price and the gas price are both in the valley moment, but the wind power output is higher at the moment, so that the wind power can be absorbed to the maximum extent, part of the natural gas load can be converted into the electric load, and the electric load of the system is equivalently increased. In the following 10: 00 to 22: and in the period of 00 hours, both the electricity price and the gas price are higher, and after considering the factors of higher carbon emission for purchasing electricity from a superior power grid, the lowest total running cost of the system and the like, part of the electricity load is replaced by the natural gas load.
The electrical load variation of scenario 4 is shown in fig. 11. As can be seen, the electrical load curve has a significant peak-to-valley difference when the system does not account for demand response, at 12: 00 and 18: around 00, the electrical load demand is at peak hours, at 5: 00 and 24: the electrical load demand is around 00 in the valley period. The wind power output has obvious peak-off regulation characteristics, the output at night is high, the output at daytime is low, the matching degree of a load curve without considering demand response and the wind power output characteristics is poor, and the IES supplies energy to the load in daytime rather tensely. After the system considers the demand response, under the excitation of time-of-use electricity price and a response mechanism, the electric load smoothes a load curve by changing energy utilization habits and adjusting energy utilization modes. The flexible transferable load in the electricity utilization time period can transfer the energy utilization time of partial load of the system from the electricity price peak to the valley, can reduce the load and relieve the energy supply tension of the system when the electricity utilization peak is realized by reducing the power of the partial load, and can replace the load to realize the replacement among different energy sources. And the IES reduces the peak-valley difference of the load curve through the synergistic action of different demand responses, and realizes the optimization of the load curve.
The demand response benefit of the IES is analyzed by comparing the cost, the carbon emission and the outsourcing energy quantity of the running scheme of the comprehensive energy system in the 4 scenes. The costs of scenes 1 to 4 are shown in table 2, and the carbon emissions at the times of scenes 1 to 4 are shown in fig. 12.
TABLE 2 scene 1-4 cost comparisons
Figure BDA0003677516760000201
As can be seen from table 2, scenario 1 does not consider demand response, and the load cannot change its own energy usage policy according to the time-sharing price information and the response mechanism. When the load demand is in a peak period, the energy supply pressure of the system is higher, and at the moment, the system needs to purchase more electricity and natural gas to meet the load demand, so that the electricity and gas purchase costs are higher, namely 6431 yuan and 35794 yuan respectively. And because the quantity of outsourcing energy sources is high, the carbon emission and the total cost of the system are high, and are 24204kg and 47254 yuan respectively. The longitudinal demand response and the transverse demand response are considered in the scenes 2 and 3 respectively, the user can adjust the self energy using behavior by responding the time-of-use electricity price and the time-of-use gas price, the electricity purchasing cost and the gas purchasing cost of the system are both obviously reduced, and the total cost and the carbon emission of the system are also effectively reduced. Compared with scenario 1, the carbon emission of the system is reduced by 24.4% and 28.1%, respectively, and the total cost of the system is reduced by 7.5% and 8.6%, respectively. It follows that the optimal operation of the system can be improved by taking into account the demand response.
Fig. 13 and 14 are comparisons of the electricity and gas purchases for scenarios 1 and 4, respectively. As can be seen from fig. 13, fig. 14 and table 2, when two demand responses are considered at the same time in scenario 4, the peak-to-valley difference of the load curve after response is reduced and the curve is smoother due to the change of the load electricity utilization period, the load reduction, and the substitution of the load energy utilization manner. Through the guidance of the time-of-use electricity price and the time-of-use gas price, the system reduces the electricity purchasing quantity and the gas purchasing quantity from a superior power grid and a gas well in the electricity price and gas price peak period, and increases the electricity purchasing quantity and the gas purchasing quantity in the electricity price and gas price valley period, so that the electricity purchasing cost and the gas purchasing cost of the system are respectively reduced by 10.7% and 12.3% compared with the scene 1. Compared with scenario 1, although scenario 4 increases demand response cost of 1132 yuan, the total system cost is reduced by 12.6% and carbon emission is reduced by 38.8% compared with scenario 1. Meanwhile, compared with scenario 2 and scenario 3, in scenario 4, the total system cost is reduced by 4.4% and 5.6%, respectively, and the carbon emission is reduced by 19.0% and 14.9%, respectively.
In conclusion, the system can effectively reduce the total cost of the system and reduce the carbon emission of the system at the same time compared with the mode that only one of the longitudinal demand response and the transverse comprehensive demand response is considered by the system, so that the operation mode of the comprehensive energy system is optimized.

Claims (5)

1. The low-carbon economic optimization operation method of the comprehensive energy system considering the demand response is characterized in that a longitudinal demand response model and a transverse demand response model are established by analyzing IES load characteristics of the comprehensive energy system, and an IES low-carbon economic optimization operation model considering the demand response is established; the method is implemented according to the following steps:
step 1, analyzing the load characteristics of an integrated energy system IES;
step 2, respectively establishing a longitudinal demand response model and a transverse demand response model;
step 3, constructing a low-carbon economic optimization operation model of the comprehensive energy system considering demand response;
and 4, solving the low-carbon economic optimization operation model of the comprehensive energy system by using a CPLEX solver.
2. The low-carbon economic optimal operation method of the comprehensive energy system considering the demand response as claimed in claim 1, wherein the specific process of the step 1 is as follows:
according to the energy utilization characteristics of the load, the load of the integrated energy system IES is divided into longitudinal demand response which can be transferred and reduced in time by the same energy type and transverse demand response which can be replaced mutually by different energy types, and the specific classification is as follows:
1) the longitudinal demand response comprises transferable electricity/gas demand response and reducible electricity/gas demand response, the loads only use one energy source, and the transfer of the energy time interval and the reduction of the electricity consumption can be realized according to the electricity price and the incentive mechanism;
2) lateral demand response refers to alternative electrical/gas loads that can use a variety of energy sources, with the alternative action of the energy sources enabling flexible adjustment of the load.
3. The low-carbon economic optimization operation method of the comprehensive energy system considering the demand response as claimed in claim 2, wherein the specific process of the step 2 is as follows:
step 2.1, establishing a longitudinal demand response model;
in IES, an electric power system and a natural gas system respectively guide a transferable load to carry out electric quantity transfer in a unit energy utilization time period in the form of time-of-use electricity price and time-of-use gas price, and the transferable electricity/gas load modeling adopts an elastic matrix method, wherein the elastic matrix is
Figure FDA0003677516750000021
In the formula (1), epsilon is an elastic coefficient, a diagonal line is self-elasticity, the others are mutual elasticity, and the self-elasticity is negative, which represents that the corresponding load in the period is reduced; the mutual elasticity is positive, and the load response quantity to price changes in other periods is represented;
coefficient of elasticity ε
Figure FDA0003677516750000022
In the formula (2), p and q are the electric quantity and the time-sharing price of the transferable load; delta p and delta q are the variable quantity of the electric quantity of the transferable load and the variable quantity of the time-sharing price;
the mathematical model capable of transferring electric and gas loads is
Figure FDA0003677516750000023
Figure FDA0003677516750000024
In the formula (3), P TRY 、P TR The initial load and the responded electric load are transferable electric loads; p TR1 …P TRt The electric load after the electric load response can be transferred in each time period of 1-t; delta P TR The amount of transfer for transferable electrical load; the diagonal line of the elastic matrix is the self-elasticity of the electric load, and the others are the mutual elasticity of the electric load; Δ q of E1 …Δq Et The time-sharing price variable quantity of the transferable electric load in each time interval of 1-t; q. q.s E1 …q Et The time-sharing price of the transferable electric load can be achieved in each time period of 1-t. In the formula (4), E TRY 、E TR The initial load is transferable gas load and the gas load after response; e TR1 …E TRt The gas load after the gas load response can be transferred in each time period of 1-t; delta E TR The amount of transfer for transferable gas loads; the diagonal line of the elastic matrix is air load self-elasticity, and the others are air load mutual elasticity; Δ q of E1 …Δq Et The time-sharing price variable quantity of the transferable gas load in each time period of 1-t; q. q.s E1 …q Et The time-sharing price of transferable gas load in each time period of 1-t;
the total load amount of the transferable electric/gas load is unchanged in one operation period, the power of the transferable load in unit time is limited by upper and lower limits, and the constraint is as follows:
Figure FDA0003677516750000031
Figure FDA0003677516750000032
in formulae (5) and (6), P TRY,t 、P TR,t Transferring the initial load of the electrical load and the responded electrical load for a period t; e TRY,t 、E TR,t The initial load of the gas load and the gas load after response can be transferred for the period t; delta P TR,max 、ΔP TR,min The upper limit and the lower limit of the transferable electric load transfer amount; delta E TR,max 、ΔE TR,min The upper limit and the lower limit of the transferable gas load transfer amount;
in the comprehensive energy system, according to the energy supply and demand condition of the system, the energy use tension in the operation process is relieved by reducing the power of corresponding loads, and a mathematical model capable of reducing electricity/gas loads is as follows:
Figure FDA0003677516750000033
in the formula (7), P CUY,t 、P CU,t The initial load of the electrical load and the load after response can be reduced for the time period t; e CUY,t 、E CU,t The initial load of the gas load and the load after response can be reduced for the t period; delta P CU,t 、ΔE CU,t The reduction of the electrical load and the air load can be reduced for the t period; b CUE,t 、b CUG,t In a reduction state of reducible electric/gas load, a value of 1 indicates that reduction adjustment occurs in a period t, and a value of 0 indicates that reduction adjustment does not occur; theta E,t 、θ G,t The load is a reduction proportion of reducible electricity/gas load, the value of 1 represents that the load is completely reduced in the t period, and the value of 0 represents that the reduction adjustment does not occur;
the reducible power/gas load needs to satisfy the reduced power range constraint of
Figure FDA0003677516750000041
In the formula (8), Δ P CU,max 、ΔP CU,min The upper and lower limits of the electric load reduction can be reduced; delta E CU,max 、ΔE CU,min The upper and lower limits of the air load reduction amount can be reduced;
step 2.2, establishing a transverse demand response model
Under the guidance of different energy prices and different power consumption requirements, the replaceable energy sources can replace electricity/gas loads and realize the replacement among different energy sources through the coupling among the energy sources, and the energy source coupling expression is
Figure FDA0003677516750000042
In the formula (9), P SUY,t 、P SU,t An initial load and a responded load which can replace the electric load; e SUY,t 、E SU,t The initial load and the responded load which can replace the gas load; delta P SU 、ΔE SU Is a substitute quantity that can substitute for the electrical load and the gas load;
Figure FDA0003677516750000043
is an alternative state to an electrical load;
Figure FDA0003677516750000044
is an alternative state that can replace the gas load;
the alternative power range of the alternative electrical/gas load satisfies the constraint:
Figure FDA0003677516750000045
Figure FDA0003677516750000046
formula (1)0) And in the formula (11),
Figure FDA0003677516750000047
the upper limit and the lower limit of the electric energy substitution amount for substituting the electric load for the gas load;
Figure FDA0003677516750000048
the upper limit and the lower limit of the electric energy substitution amount for substituting the electric load for the gas load;
Figure FDA0003677516750000049
the upper limit and the lower limit of the gas energy substitution amount for substituting the gas load for the electric load;
Figure FDA00036775167500000410
the upper limit and the lower limit of the gas energy substitution amount for substituting the gas load for the electric load.
4. The low-carbon economic optimization operation method of the comprehensive energy system considering the demand response as claimed in claim 1, wherein the specific process of the step 3 is as follows:
step 3.1, constructing a low-carbon operation objective function by considering the energy purchase cost, the demand response cost and the carbon transaction cost of a superior power grid and a gas well;
the objective function of the IES low-carbon economic optimization operation model considering the demand response is
minf＝f 1 +f 2 (12)
Figure FDA0003677516750000051
Figure FDA0003677516750000052
In formulae (12), (13) and (14), f 1 The cost of system operation; f. of 2 Is the carbon transaction cost; p E,t The generated power of the coal-fired unit is t time period; delta P CU 、ΔE CU To cut downReduction of electrical and gas loads; p GT,t The generated power of the gas turbine is t time period; gamma ray CUE 、γ CUG Reducing the cost coefficient for the unit capable of reducing the electric/gas load; ξ is the reward base price for carbon trading; delta E is the length of the carbon emission interval; kappa is the carbon transaction price growth rate in the penalty stage; λ is the carbon trading price growth rate in the reward phase; rho E,t The unit electricity price of the superior power grid in the period t; ρ is a unit of a gradient G,t The unit price of the natural gas in the t time period; e IES The total uncompensated carbon emission quota of the system; e IES,C Is the total carbon emission for the actual operation of the system;
step 3.2, considering the power network constraint, the node voltage constraint and the natural gas network constraint during system operation, wherein the constraint conditions are as follows:
power network constraints:
Figure FDA0003677516750000053
Figure FDA0003677516750000054
Figure FDA0003677516750000061
Figure FDA0003677516750000062
P EL,t ＝P TR,t +P CU,t +P SU,t (19)
in formulae (15), (16), (17), (18) and (19), P ij,t 、Q ij,t Active and reactive power for the ij branch; p is jk,t 、Q jk,t Active power and reactive power are provided for the jk branch; p GT,t 、Q GT,t The active power and the reactive power of the gas turbine are generated in the period t; p is WT,t 、Q WT,t Wind power active power and reactive power in a time period t; p EC,t 、Q EC,t Inputting active electric power and reactive electric power for the electrolytic cell in a period t; p EL,t 、Q EL,t The active power and the reactive power of the electric load are t time periods; delta P W,t 、ΔQ W,t The wind abandoning active amount and the wind abandoning inactive amount are in t time period; r is ij 、x ij Resistance and reactance for the ij branch; u shape i,t 、U j,t Voltages at nodes i and j; I.C. A ij,t 、U ij,t A current and the voltage difference of an ij node flow through the ij branch;
node voltage constraint:
U j,min ≤U j,t ≤U j,max (20)
in formula (20), U j,max 、U j,min The upper and lower limits allowed for the voltage at the j node;
natural gas network constraints:
Figure FDA0003677516750000063
Figure FDA0003677516750000064
in the formulae (21) and (22), sgn (. pi.) ( i,t ,π j,t ) When the pressure of the node i is higher than that of the node j, the value is 1, otherwise, the value is-1; pi i,t 、π j,t The natural gas pressure of an i node and a j node in a t period; pi p,t 、π q,t The natural gas pressure of a p node and a q node in a t period; fp p,t The pipeline flow of the natural gas pipeline p in the period t; phi is a p Is the gas flow transmission parameter of the natural gas pipeline p;
node airflow balance constraint:
Figure FDA0003677516750000071
P GL,t ＝E TR,t +E CU,t +E SU,t (24)
in the formulas (23) and (24), v (n), u (n) are gas pipeline sets with n nodes as end points and start nodes; x (n), Z (n) is a methane reactor and a gas turbine set at the n node; psi H2G 、ψ GT Conversion factors for the methane reactor and the gas turbine; p is H2G,t Methane reactor power for a period of t; p is GL,t The active power of the gas load in the period t;
and (3) restricting the flow of the pipeline:
fq mn,min ≤fq mn,t ≤fq mn,max (25)
in formula (25), fq mn,t The flow rate of the pipeline mn is shown; fq of mn,max 、fq mn,min The upper and lower flow limits of the mn pipeline are set;
and (3) node air pressure constraint:
π m,min ≤π m,t ≤π m,max (26)
in the formula (26), n m,t Is the air pressure at node m; pi m,max 、π m,min The upper and lower limits of the air pressure allowance at the node m;
and (3) power exchange constraint with a superior power grid and a natural gas network:
Figure FDA0003677516750000072
in the formula (27), P E,t The quantity of electricity purchased outside in the time period t; p G,t The amount of the purchased natural gas in the t period; p Emax 、P Emin Purchasing upper and lower limits of electric quantity for the system; p Gmax 、P Gmin Purchasing an upper limit and a lower limit of gas for the system;
hydrogen energy balance constraint:
Figure FDA0003677516750000073
in the formula (28), y (n) is a set of hydrogen storage tanks at the n node; p P2H,t Generating hydrogen volumes for electrolysis cells；P H2H,t The volume of hydrogen consumed for the methane reactor;
Figure FDA0003677516750000074
the air inlet quantity and the air outlet quantity of the hydrogen storage tank;
and (3) output constraint of each unit:
Figure FDA0003677516750000081
in formula (29), P WTmax 、P WTmin The output power is the upper and lower limits of wind power; p EC,t Inputting active electric power for the electrolytic cell in a period t; e MRHmax 、E MRHmin The upper and lower limits for the hydrogen input to the methane reactor; e MRH,t Is hydrogen input by the methane reactor during the period t; p WTmax 、P WTmin The output power is the upper and lower limits of wind power; p WT,t Wind power active power is obtained for t time period; p GTmax 、P GTmin The upper and lower limits of the output of the gas turbine; p is GT,t The active power generated by the gas turbine in the period t; delta P GTmax 、ΔP GTmin The upper and lower limits of the climbing power of the gas turbine.
5. The low-carbon economic optimization operation method of the comprehensive energy system considering the demand response according to claim 4, characterized in that the specific process of the step 4 is as follows:
step 4.1, setting input parameters of a low-carbon economic optimization operation model of the comprehensive energy system, inputting original load data of an electric load and an air load, inputting output data of wind power and corresponding parameters of all units in the system;
step 4.2, performing linearization treatment on the constructed IES low-carbon economic optimization operation model by adopting a second-order cone relaxation and incremental linearization means, performing simulation solution in MATLAB by using a CPLEX solver, and obtaining the optimal cost under the operation scheme;
4.3, if the constraint condition of the step 3.2 is met, stopping calculation; if the condition is not met, adjusting the parameters to calculate again;
and 4.4, obtaining the operation condition of each unit in the comprehensive energy system, and determining the operation scheme of the system.
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Cited By (3)

* Cited by examiner, † Cited by third party
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CN115241931A (en) * 2022-09-23 2022-10-25 国网浙江省电力有限公司宁波供电公司 Garden comprehensive energy system scheduling method based on time-varying electrical carbon factor curve
CN116128262A (en) * 2023-04-19 2023-05-16 山东科技大学 Low-carbon scheduling method and system for comprehensive energy system
CN116247725A (en) * 2023-02-14 2023-06-09 国网宁夏电力有限公司中卫供电公司 Scheduling method for comprehensive energy system containing electricity and gas and considering classified load demand response

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115241931A (en) * 2022-09-23 2022-10-25 国网浙江省电力有限公司宁波供电公司 Garden comprehensive energy system scheduling method based on time-varying electrical carbon factor curve
CN116247725A (en) * 2023-02-14 2023-06-09 国网宁夏电力有限公司中卫供电公司 Scheduling method for comprehensive energy system containing electricity and gas and considering classified load demand response
CN116128262A (en) * 2023-04-19 2023-05-16 山东科技大学 Low-carbon scheduling method and system for comprehensive energy system
CN116128262B (en) * 2023-04-19 2023-07-25 山东科技大学 Low-carbon scheduling method and system for comprehensive energy system

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