CN114066204A - Integrated optimization planning and operation method and device of comprehensive energy system - Google Patents

Integrated optimization planning and operation method and device of comprehensive energy system Download PDF

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CN114066204A
CN114066204A CN202111331629.0A CN202111331629A CN114066204A CN 114066204 A CN114066204 A CN 114066204A CN 202111331629 A CN202111331629 A CN 202111331629A CN 114066204 A CN114066204 A CN 114066204A
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杨培宏
江晖
亢岚
魏毅立
张自雷
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Inner Mongolia University of Science and Technology
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Abstract

The invention provides an integrated optimization planning and operation method and device of an integrated energy system, and the method comprises the steps of constructing a multi-energy flow coupling model according to basic parameters of the integrated energy system; based on the constraint conditions and the multi-energy flow coupling model, adjusting the output power of all energy supply equipment and energy conversion equipment in the comprehensive energy system under the zeroth configuration scheme to obtain a first configuration scheme; based on the constraint conditions and the multi-energy flow coupling model, adjusting the output of various energy sources in the comprehensive energy system under the first configuration scheme to obtain a second configuration scheme; determining a scheme with lower operation cost in the first configuration scheme and the second configuration scheme as an optimal scheme of the iteration; and continuously iterating until the total cost of the optimal scheme of the iteration is less than the total cost threshold value, and obtaining the optimal configuration scheme. The invention can improve the overall optimization level of the comprehensive energy system by adjusting the output power of the energy supply equipment and the energy conversion equipment and the output power of various energy sources.

Description

Integrated optimization planning and operation method and device of comprehensive energy system
Technical Field
The invention relates to the technical field of comprehensive energy, in particular to an integrated optimization planning and operation method and device of a comprehensive energy system.
Background
Energy is a basic condition for human society to live, and is also a power source spring and a foundation stone for the development and progress of the human society. With the progress of society and the improvement of living standard of people, the demand of human beings on energy sources increases year by year, while the traditional primary energy sources are exhausted day by day and seriously polluted, and the defects are obvious day by day, so that the energy source revolution is imperative. In recent years, new energy technologies represented by renewable energy and distributed power generation have been developed rapidly, and in particular, micro grids aimed at local consumption of renewable energy have been widely used. However, the micro-grid is limited to power energy supply, and cannot be operated in coordination with various energy sources such as natural gas, heat energy, cold energy and the like, so that the energy utilization efficiency of the system is not high. However, an energy network in which an integrated energy system collects multiple types of energy such as electricity, heat, gas, and cold has characteristics of high energy efficiency, low loss, low pollution, flexible operation, and good system economy, and has attracted worldwide attention in recent years. The longitudinal and multi-energy supply complementary transverse cooperative regulation and control optimization operation of the source, the network, the load and the storage in the comprehensive energy system network effectively promotes the coordinated efficient utilization of various energy sources, improves the energy utilization efficiency to the greatest extent, and reduces the energy utilization cost and the environmental pollution.
The comprehensive energy system is closely around the comprehensive utilization and low-carbon operation of renewable clean new energy, so that the future application prospect is very huge, and the comprehensive energy system has good prospect and value for the integrated optimization planning and operation work of the comprehensive energy system. Through the rational planning of the comprehensive energy system, the construction cost can be reduced, the operation reliability is improved, and through operation optimization, a reasonable operation scheme can be formulated, so that the economy of the whole comprehensive energy system is improved. If the integrated planning and operation research of the comprehensive energy system is carried out, the energy utilization requirements of users are met, the reasonable configuration of energy equipment in the comprehensive energy system can be realized, a reasonable operation optimization scheme can be provided, and finally the comprehensive energy system can operate economically and reliably.
At present, planning and operation of the comprehensive energy system are divided into two optimization sub-problems to be solved, and an optimization configuration scheme is obtained by coordinating after optimization calculation, so that the calculation result does not comprehensively consider the organic combination of the planning problem and the operation optimization, and the operation of the comprehensive energy system in an optimal scheme cannot be ensured. In a word, the optimization problem of the comprehensive energy system is to simultaneously pursue the minimization of equipment construction investment and operation cost, and the two are closely coupled and inseparable. Therefore, further research is still needed for the integrated optimization planning and operation method of the comprehensive energy system to improve the overall optimization level and effect.
Disclosure of Invention
The invention aims to provide an integrated optimization planning and operation method and device of an integrated energy system, which can improve the overall optimization level of the integrated energy system.
In order to achieve the purpose, the invention provides the following scheme:
an integrated optimization planning and operation method of an integrated energy system obtains basic parameters of the integrated energy system;
constructing a multi-energy flow coupling model of the comprehensive energy system according to the basic parameters;
constructing an operation cost objective function, a total cost objective function and the constraint condition; the total cost objective function comprises an operation cost and an infrastructure cost;
taking an initial configuration scheme of energy supply equipment and energy conversion equipment in the comprehensive energy system as a zeroth configuration scheme;
based on the constraint conditions and the multi-energy flow coupling model, adjusting the output power of all energy supply equipment and energy conversion equipment in the comprehensive energy system under the zeroth configuration scheme to obtain a first configuration scheme of the energy supply equipment and the energy conversion equipment;
based on the constraint conditions and the multi-energy flow coupling model, adjusting the output of various energy sources in the comprehensive energy system under the first configuration scheme to obtain a second configuration scheme of energy supply equipment and energy conversion equipment;
respectively calculating the operation cost objective functions of the first configuration scheme and the second configuration scheme, and determining a scheme with a smaller operation cost objective function as an optimal scheme of the current iteration;
calculating a total cost objective function of the optimal scheme of the iteration;
when the total cost target function of the optimal scheme of the iteration is larger than or equal to the total cost threshold value, taking the optimal scheme of the iteration as a zeroth configuration scheme, and returning to the step of adjusting the output power of all energy supply equipment and energy conversion equipment in the comprehensive energy system under the zeroth configuration scheme based on the constraint condition and the multi-energy flow coupling model to obtain a first configuration scheme of the energy supply equipment and the energy conversion equipment;
and when the total cost target function of the optimal scheme of the iteration is smaller than the total cost threshold value, determining the optimal scheme of the iteration as the optimal configuration scheme of the comprehensive energy system.
Optionally, the multi-energy flow coupling model is: l ═ JP;
wherein, L represents an output power matrix,
Figure BDA0003349091150000031
Le、Lh、Lgand LcRespectively representing the output power of electricity, heat, natural gas and cold in the comprehensive energy system Z; j represents a coupled sparse matrix and J represents,
Figure BDA0003349091150000032
fWTweir distribution probability density function, f, representing wind speed vPVA probability density function representing the Beta distribution of the illumination intensity within a preset time period;
Figure BDA0003349091150000033
and
Figure BDA0003349091150000034
respectively representing the proportion coefficients of the electric energy consumed by a power grid, an electric boiler, an electric gas-converting machine and an electric refrigerator in the comprehensive energy system to the total electric energy;
Figure BDA0003349091150000035
Figure BDA0003349091150000036
and
Figure BDA0003349091150000037
respectively representing the efficiency of the output power of a gas turbine, a gas boiler, a waste heat boiler, an electric gas conversion device, an electric refrigerator and an absorption refrigerator in the comprehensive energy system;
Figure BDA0003349091150000038
Figure BDA0003349091150000039
and
Figure BDA00033490911500000310
respectively representing the proportional coefficients of natural gas energy consumed by a natural gas network, a gas boiler and a gas turbine in the comprehensive energy system in the total natural gas energy; p represents the input power matrix and P represents the input power matrix,
Figure BDA00033490911500000311
EWTand EPVRespectively representing the input energy of a fan and a photovoltaic in the comprehensive energy system; peAnd PgRespectively representing electric energy and gas energy which can be directly used in the integrated energy system.
Optionally, the operation cost objective function is:
C＝Cp+Cma+Ce+Cg；
wherein C represents the planning cost, CPRepresents the cost of the construction of the equipment,
Figure BDA00033490911500000312
Cl,nthe equipment construction cost is represented by the position node L and the capacity number N, L represents the total number of the position nodes, N represents the total number of the capacity numbers, Il,n(0, 1) decision variables representing devices with location nodes of l capacity number n; cmaFor the operating and maintenance costs of each piece of equipment,
Figure BDA0003349091150000041
t represents a period; rGT、RWHB、RP2G、RWT、RPV、RGB、REC、RAC、REB、Rbe、RhcRespectively representing the operation and maintenance cost coefficients of a gas turbine, a waste heat boiler, an electric gas conversion device, a wind turbine generator, a photovoltaic generator, a gas boiler, an electric refrigerating device, an absorption refrigerating device, an electric boiler, an electric energy storage device and a heat energy storage device in the comprehensive energy system; pGT,t、HWHB,t、PP2G,t、PWT,t、PPV,t、HGB,t、CEC,t、CAC,t、HEB,t、Pbc,t、Pbd,t、Hhc,t、Hhd,tRespectively representing the output electric power of a gas turbine, the output thermal power of a waste heat boiler, the input electric power of electricity-to-gas, the output electric power of a wind turbine generator, the output electric power of photovoltaic power, the output thermal power of a gas boiler, the output cold power of electric refrigeration, the output cold power of absorption refrigeration, the output thermal power of an electric boiler, the storage electric power of an electric storage device, the output electric power of the electric storage device, the storage thermal power of a thermal storage device and the output thermal power of the thermal storage device in a delta t time period; ceRepresenting the cost of purchasing electricity from the grid,
Figure BDA0003349091150000042
ce,trepresenting grid electricity price, P, over a period of Δ tg,tRepresenting electric power input into the integrated energy system by the power grid during the delta t period; cgIndicating a purchase of gas from the gas network,
Figure BDA0003349091150000043
cg,tgas network gas price, Q, for a period of Δ tg,tAnd inputting the gas quantity of the comprehensive energy system for the natural gas pipe network in the delta t period.
Optionally, the total cost objective function is:
Itotal＝IP+IMA+IE+IG
wherein, ItotalRepresents the total cost, IPThe construction cost of the full life cycle is represented,
Figure BDA0003349091150000044
x is the total number of devices, SlCapacity of the l-th equipment, ClThe construction cost per unit capacity of the first equipment, R is the fixed capital residual rate, R is the discount rate, mlThe life cycle of the device l; i isMARepresenting the maintenance costs of the respective equipment for one year,
Figure BDA0003349091150000045
Klfor the maintenance cost factor, P, of the apparatus ll,tThe output power of the device during the delta t period; i isERepresents the electricity purchase cost of one year,
Figure BDA0003349091150000046
IGrepresents the gas purchase cost of one year,
Figure BDA0003349091150000047
optionally, the constraint condition includes: power balance constraint, tie line constraint, energy supply equipment constraint, energy conversion equipment output constraint, energy storage device constraint and unit climbing constraint; wherein the power balance constraint specifically includes: an electric power balance constraint, a thermal power balance constraint, a cold power balance constraint, and a natural gas power balance constraint.
Alternatively to this, the first and second parts may,
the electric power balance constraint is:
Figure BDA0003349091150000051
wherein E isbuy,e,tThe power purchasing power is used for purchasing power from the power grid at the moment t; ePV,e,tRepresenting the output electric power of the wind turbine; eWT,e,tRepresenting the output electric power of the photovoltaic unit; eGT,e,tElectrical power representing gas turbine output at time t; eEES,tRepresenting the electrical stored energy power at time t; eEC,c,tRepresents the cold power output by the electric refrigerator at time t,
Figure BDA0003349091150000052
representing the efficiency of the electric refrigerator; eEB,h,tRepresents the thermal power output by the electric boiler at the moment t,
Figure BDA0003349091150000053
representing the efficiency of the thermal power output by the electric boiler; eP2G,g,tThe natural gas power of the electric conversion gas output at the moment t is shown,
Figure BDA0003349091150000054
indicating the efficiency of electric gas conversion; euser,e,tRepresenting the electric load before the user carries out demand response at the time t; Δ q oftRepresenting the amount of load that the user changes after engaging in the demand response;
the thermal power balance constraint is as follows:
Figure BDA0003349091150000055
wherein E isGB,h,tThe thermal power output by the gas boiler at the time t is represented; eWHB,h,tThe thermal power output by the waste heat boiler at the moment t is represented; eAC,c,tThe cold power output by the absorption refrigerator at the time t is represented;
Figure BDA0003349091150000056
showing the refrigeration efficiency of the absorption refrigerator; eTES,tThe heat storage and energy heating power at the time t is shown; euser,th,tRepresenting the actual heat load of the user at the time t;
the cold power balance constraint is:
EEC,c,t+EAC,c,t＝Euser,c,t
wherein E isuser,c,tIndicating the actual cooling load for the user at time t.
The natural gas power balance constraint is as follows:
Figure BDA0003349091150000057
wherein,
Figure BDA0003349091150000058
representing the efficiency of the gas turbine;
Figure BDA0003349091150000059
efficiency of heat output of gas boiler, Euser,g,tRepresenting the actual natural gas load of the user at the time t;
the tie line constraint is:
Pgrid,min≤Ebuy,e,t≤Pgrid,max
wherein, Pgrid,min、Pgrid,maxRespectively representing the minimum value and the maximum value of the interaction power of the power distribution network;
the energy supply device is constrained as follows:
Figure BDA0003349091150000061
wherein, PWT(t)、PPV(t) respectively representing the generated energy of the wind power and the photovoltaic unit in the period of t, PWT,max、PPV，maxRespectively representing the upper limits of the output of the wind power generator set and the photovoltaic generator set;
the output constraint of the energy conversion equipment is as follows:
Figure BDA0003349091150000062
wherein E isGT,e,t、EWHB,h,t、EGB,h,t、EEC,c,t、EEB,h,t、EP2G,g,t、EAC,c,tRespectively representing the capacities of a gas turbine, a waste heat boiler, a gas boiler, an electric refrigerator, an electric boiler, an electric gas-converting machine and an absorption refrigerator; eGT,e,max、EWHB,h,max、EGB,h,max、EEC,c,max、EEB,h,max、EP2G,g,max、EAC,c,maxRespectively representing the maximum capacities of the gas turbine, the waste heat boiler, the gas boiler, the electric refrigerator, the electric boiler, the electric gas-transferring and absorption refrigerator;
the energy storage device constraints are:
Figure BDA0003349091150000063
wherein E isEES,ch,t、EEES,dis,tRespectively the charging power and the discharging power at the time t; eEES,tThe storage capacity at the time t; eTES,ch,t、ETES,dis,tRespectively the charging power and the heat release power at the moment t; eTES,tThe heat storage capacity at time t; eEES,min、EEES,maxRespectively the minimum and maximum capacities of the electricity storage device; eTES,min、ETES,maxThe minimum and maximum capacities of the heat storage device are respectively set; gamma rayEES,ch、γEES,disThe charging state and the discharging state are respectively, and are variable 0-1; gamma rayTES,ch、γTES,disRespectively in a heat charging state and a heat discharging state, and the variables are 0-1; eEES,0A storage capacity at 0; eEES,24A storage capacity of 24 hours; eTES,0A heat storage capacity at 0; eTES,24A heat storage capacity of 24 hours;
the unit climbing restraint is as follows:
|Em,t+1-Em,t|≤ΔPm,max
wherein E ism,t+1And Em,tRespectively representing the output of the fan at t +1 and tEnergy; delta Pm,maxIs the upper limit of the climbing of the device m.
An integrated optimization planning and operation device of an integrated energy system comprises:
the basic parameter acquisition module is used for acquiring basic parameters of the comprehensive energy system;
the multi-energy flow coupling model building module is used for building a multi-energy flow coupling model of the comprehensive energy system according to the basic parameters;
the target function construction module is used for constructing an operation cost target function, a total cost target function and the constraint condition; the total cost objective function comprises an operation cost and an infrastructure cost;
the zero configuration scheme determining module is used for taking the initial configuration scheme of the energy supply equipment and the energy conversion equipment in the comprehensive energy system as a zero configuration scheme;
the first configuration scheme determining module is used for adjusting the output power of all energy supply equipment and energy conversion equipment in the comprehensive energy system under the zeroth configuration scheme based on the constraint condition and the multi-energy flow coupling model to obtain a first configuration scheme of the energy supply equipment and the energy conversion equipment;
the second configuration scheme determining module is used for adjusting the output of various energy sources in the comprehensive energy system under the first configuration scheme based on the constraint conditions and the multi-energy flow coupling model to obtain a second configuration scheme of the energy supply equipment and the energy conversion equipment;
the optimal scheme determining module of the iteration is used for respectively calculating the operation cost objective functions of the first configuration scheme and the second configuration scheme and determining a scheme with a smaller operation cost objective function as the optimal scheme of the iteration;
the total cost calculation module is used for calculating a total cost target function of the optimal scheme of the iteration;
the loop iteration module is used for taking the optimal scheme of the current iteration as a zeroth configuration scheme and calling the first configuration scheme determining module when the total cost target function of the optimal scheme of the current iteration is greater than or equal to a total cost threshold;
and the optimal configuration scheme determining module is used for determining the optimal scheme of the iteration as the optimal configuration scheme of the comprehensive energy system when the total cost target function of the optimal scheme of the iteration is smaller than the total cost threshold.
Optionally, the multi-energy flow coupling model is: l ═ JP;
wherein, L represents an output power matrix,
Figure BDA0003349091150000081
Le、Lh、Lgand LcRespectively representing the output power of electricity, heat, natural gas and cold in the comprehensive energy system Z; j represents a coupled sparse matrix and J represents,
Figure BDA0003349091150000082
fWTweir distribution probability density function, f, representing wind speed vPVA probability density function representing the Beta distribution of the illumination intensity within a preset time period;
Figure BDA0003349091150000083
and
Figure BDA0003349091150000084
respectively representing the proportion coefficients of the electric energy consumed by a power grid, an electric boiler, an electric gas-converting machine and an electric refrigerator in the comprehensive energy system to the total electric energy;
Figure BDA0003349091150000085
Figure BDA0003349091150000086
and
Figure BDA0003349091150000087
respectively representing the efficiency of the output power of a gas turbine, a gas boiler, a waste heat boiler, an electric gas conversion device, an electric refrigerator and an absorption refrigerator in the comprehensive energy system;
Figure BDA0003349091150000088
Figure BDA0003349091150000089
and
Figure BDA00033490911500000810
respectively representing the proportional coefficients of natural gas energy consumed by a natural gas network, a gas boiler and a gas turbine in the comprehensive energy system in the total natural gas energy; p represents the input power matrix and P represents the input power matrix,
Figure BDA00033490911500000811
EWTand EPVRespectively representing the input energy of a fan and a photovoltaic in the comprehensive energy system; peAnd PgRespectively representing electric energy and gas energy which can be directly used in the integrated energy system.
Optionally, the operation cost objective function is:
C＝Cp+Cma+Ce+Cg；
wherein C represents the planning cost, CPRepresents the cost of the construction of the equipment,
Figure BDA00033490911500000812
Cl,nthe equipment construction cost is represented by the position node L and the capacity number N, L represents the total number of the position nodes, N represents the total number of the capacity numbers, Il,n(0, 1) decision variables representing devices with location nodes of l capacity number n; cmaFor the operating and maintenance costs of each piece of equipment,
Figure BDA0003349091150000091
t represents a period; rGT、RWHB、RP2G、RWT、RPV、RGB、REC、RAC、REB、Rbe、RhcRespectively representing a gas turbine, a waste heat boiler, an electric gas conversion device, a wind turbine generator, a photovoltaic generator, a gas boiler, an electric refrigerating device, an absorption refrigerating device, an electric boiler, an electric energy storage device and a heat energy storage device in the comprehensive energy systemThe operation and maintenance cost coefficient; pGT,t、HWHB,t、PP2G,t、PWT,t、PPV,t、HGB,t、CEC,t、CAC,t、HEB,t、Pbc,t、Pbd,t、Hhc,t、Hhd,tRespectively representing the output electric power of a gas turbine, the output thermal power of a waste heat boiler, the input electric power of electricity-to-gas, the output electric power of a wind turbine generator, the output electric power of photovoltaic power, the output thermal power of a gas boiler, the output cold power of electric refrigeration, the output cold power of absorption refrigeration, the output thermal power of an electric boiler, the storage electric power of an electric storage device, the output electric power of the electric storage device, the storage thermal power of a thermal storage device and the output thermal power of the thermal storage device in a delta t time period; ceRepresenting the cost of purchasing electricity from the grid,
Figure BDA0003349091150000092
ce,trepresenting grid electricity price, P, over a period of Δ tg,tRepresenting electric power input into the integrated energy system by the power grid during the delta t period; cgIndicating a purchase of gas from the gas network,
Figure BDA0003349091150000093
cg,tgas network gas price, Q, for a period of Δ tg,tAnd inputting the gas quantity of the comprehensive energy system for the natural gas pipe network in the delta t period.
Optionally, the total cost objective function is:
Itotal＝IP+IMA+IE+IG
wherein, ItotalRepresents the total cost, IPThe construction cost of the full life cycle is represented,
Figure BDA0003349091150000094
x is the total number of devices, SlCapacity of the l-th equipment, ClThe construction cost per unit capacity of the first equipment, R is the fixed capital residual rate, R is the discount rate, mlThe life cycle of the device l; i isMARepresenting the maintenance costs of the respective equipment for one year,
Figure BDA0003349091150000095
Klfor the maintenance cost factor, P, of the apparatus ll,tThe output power of the device during the delta t period; i isERepresents the electricity purchase cost of one year,
Figure BDA0003349091150000096
IGrepresents the gas purchase cost of one year,
Figure BDA0003349091150000097
according to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides an integrated optimization planning and operation method and device of an integrated energy system, wherein the method comprises the steps of obtaining basic parameters of the integrated energy system; constructing a multi-energy flow coupling model of the comprehensive energy system according to the basic parameters; constructing an operation cost objective function, a total cost objective function and a constraint condition; the total cost objective function comprises operation cost and infrastructure cost; taking an initial configuration scheme of energy supply equipment and energy conversion equipment in the comprehensive energy system as a zeroth configuration scheme; based on the constraint conditions and the multi-energy flow coupling model, adjusting the output power of all energy supply equipment and energy conversion equipment in the comprehensive energy system under the zeroth configuration scheme to obtain a first configuration scheme of the energy supply equipment and the energy conversion equipment; based on the constraint conditions and the multi-energy flow coupling model, adjusting the output of various energy sources in the comprehensive energy system under the first configuration scheme to obtain a second configuration scheme of the energy supply equipment and the energy conversion equipment; respectively calculating the operation cost objective functions of the first configuration scheme and the second configuration scheme, and determining a scheme with a smaller operation cost objective function as an optimal scheme of the current iteration; calculating a total cost objective function of the optimal scheme of the iteration; when the total cost target function of the optimal scheme of the iteration is larger than or equal to the total cost threshold value, taking the optimal scheme of the iteration as a zeroth configuration scheme, and returning to the step of regulating the output power of all energy supply equipment and energy conversion equipment in the comprehensive energy system under the zeroth configuration scheme based on the constraint condition and the multi-energy flow coupling model to obtain a first configuration scheme of the energy supply equipment and the energy conversion equipment; and when the total cost target function of the optimal scheme of the iteration is smaller than the total cost threshold value, determining the optimal scheme of the iteration as the optimal configuration scheme of the comprehensive energy system. The invention can improve the overall optimization level of the comprehensive energy system by constructing an operation cost objective function, a total cost objective function and constraint conditions, adjusting the output power of the energy supply equipment and the energy conversion equipment and the output power of various energy sources.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
FIG. 1 is a flow chart of an integrated optimization planning and operation method of an integrated energy system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an integrated energy system according to an embodiment of the present invention;
FIG. 3 is an iterative schematic diagram of an optimal configuration scheme in an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an integrated optimization planning and operation device of the integrated energy system according to the embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide an integrated optimization planning and operation method and device of an integrated energy system, which can improve the overall optimization level of the integrated energy system.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Fig. 1 is a flowchart of an integrated optimal planning and operation method of an integrated energy system according to an embodiment of the present invention, and as shown in fig. 1, the present invention provides an integrated optimal planning and operation method of an integrated energy system, including:
step 101: acquiring basic parameters of the comprehensive energy system;
step 102: constructing a multi-energy flow coupling model of the comprehensive energy system according to the basic parameters;
step 103: constructing an operation cost objective function, a total cost objective function and a constraint condition; the total cost objective function comprises operation cost and infrastructure cost;
step 104: taking an initial configuration scheme of energy supply equipment and energy conversion equipment in the comprehensive energy system as a zeroth configuration scheme;
step 105: based on the constraint conditions and the multi-energy flow coupling model, adjusting the output power of all energy supply equipment and energy conversion equipment in the comprehensive energy system under the zeroth configuration scheme to obtain a first configuration scheme of the energy supply equipment and the energy conversion equipment;
step 106: based on the constraint conditions and the multi-energy flow coupling model, adjusting the output of various energy sources in the comprehensive energy system under the first configuration scheme to obtain a second configuration scheme of the energy supply equipment and the energy conversion equipment;
step 107: respectively calculating the operation cost objective functions of the first configuration scheme and the second configuration scheme, and determining a scheme with a smaller operation cost objective function as an optimal scheme of the current iteration;
step 108: calculating a total cost objective function of the optimal scheme of the iteration;
step 109: when the total cost target function of the optimal scheme of the iteration is larger than or equal to the total cost threshold value, taking the optimal scheme of the iteration as a zeroth configuration scheme, and returning to the step of regulating the output power of all energy supply equipment and energy conversion equipment in the comprehensive energy system under the zeroth configuration scheme based on the constraint condition and the multi-energy flow coupling model to obtain a first configuration scheme of the energy supply equipment and the energy conversion equipment;
step 110: and when the total cost target function of the optimal scheme of the iteration is smaller than the total cost threshold value, determining the optimal scheme of the iteration as the optimal configuration scheme of the comprehensive energy system.
Specifically, the multi-energy flow coupling model is as follows: l ═ JP;
wherein, L represents an output power matrix,
Figure BDA0003349091150000121
Le、Lh、Lgand LcRespectively representing the output power of electricity, heat, natural gas and cold in the comprehensive energy system Z; j represents a coupled sparse matrix and J represents,
Figure BDA0003349091150000122
fWTweir distribution probability density function, f, representing wind speed vPVA probability density function representing the Beta distribution of the illumination intensity within a preset time period;
Figure BDA0003349091150000123
and
Figure BDA0003349091150000124
respectively representing the proportion coefficients of the electric energy consumed by a power grid, an electric boiler, an electric gas-converting machine and an electric refrigerator in the comprehensive energy system to the total electric energy;
Figure BDA0003349091150000125
Figure BDA0003349091150000126
and
Figure BDA0003349091150000127
respectively representing a gas turbine, a gas boiler, a waste heat boiler, an electric boiler and an electric converter in the comprehensive energy systemEfficiency of output power of gas equipment, electric refrigerators and absorption refrigerators;
Figure BDA0003349091150000128
Figure BDA0003349091150000129
and
Figure BDA00033490911500001210
respectively representing the proportional coefficients of natural gas energy consumed by a natural gas network, a gas boiler and a gas turbine in the comprehensive energy system in the total natural gas energy; p represents the input power matrix and P represents the input power matrix,
Figure BDA00033490911500001211
EWTand EPVRespectively representing the input energy of a fan and a photovoltaic in the comprehensive energy system; peAnd PgRespectively representing electric energy and gas energy which can be directly used in the integrated energy system.
Specifically, the operation cost objective function is:
C＝Cp+Cma+Ce+Cg；
wherein C represents the planning cost, CPRepresents the cost of the construction of the equipment,
Figure BDA0003349091150000131
Cl,nthe equipment construction cost is represented by the position node L and the capacity number N, L represents the total number of the position nodes, N represents the total number of the capacity numbers, Il,n(0, 1) decision variables representing devices with location nodes of l capacity number n; cmaFor the operating and maintenance costs of each piece of equipment,
Figure BDA0003349091150000132
t represents a period; rGT、RWHB、RP2G、RWT、RPV、RGB、REC、RAC、REB、Rbe、RhcRespectively representing a gas turbine, a waste heat boiler and a heat pump in the comprehensive energy system,The operation and maintenance cost coefficients of the electric gas conversion device, the wind turbine generator, the photovoltaic generator, the gas boiler, the electric refrigerating device, the absorption refrigerating device, the electric boiler, the electric energy storage device and the heat energy storage device; pGT,t、HWHB,t、PP2G,t、PWT,t、PPV,t、HGB,t、CEC,t、CAC,t、HEB,t、Pbc,t、Pbd,t、Hhc,t、Hhd,tRespectively representing the output electric power of a gas turbine, the output thermal power of a waste heat boiler, the input electric power of electricity-to-gas, the output electric power of a wind turbine generator, the output electric power of photovoltaic power, the output thermal power of a gas boiler, the output cold power of electric refrigeration, the output cold power of absorption refrigeration, the output thermal power of an electric boiler, the storage electric power of an electric storage device, the output electric power of the electric storage device, the storage thermal power of a thermal storage device and the output thermal power of the thermal storage device in a delta t time period; ceRepresenting the cost of purchasing electricity from the grid,
Figure BDA0003349091150000133
ce,trepresenting grid electricity price, P, over a period of Δ tg,tRepresenting electric power input into the integrated energy system by the power grid during the delta t period; cgIndicating a purchase of gas from the gas network,
Figure BDA0003349091150000134
cg,tgas network gas price, Q, for a period of Δ tg,tAnd inputting the gas quantity of the comprehensive energy system for the natural gas pipe network in the delta t period.
Specifically, the total cost objective function is:
Itotal＝IP+IMA+IE+IG
wherein, ItotalRepresents the total cost, IPThe construction cost of the full life cycle is represented,
Figure BDA0003349091150000135
x is the total number of devices, SlCapacity of the l-th equipment, ClThe construction cost per unit capacity of the first equipment, R is the fixed capital residual rate, R is the discount rate, mlThe life cycle of the device l; i isMARepresenting the maintenance costs of the respective equipment for one year,
Figure BDA0003349091150000136
Klfor the maintenance cost factor, P, of the apparatus ll,tThe output power of the device during the delta t period; i isERepresents the electricity purchase cost of one year,
Figure BDA0003349091150000141
IGrepresents the gas purchase cost of one year,
Figure BDA0003349091150000142
wherein the constraint condition comprises: power balance constraint, tie line constraint, energy supply equipment constraint, energy conversion equipment output constraint, energy storage device constraint and unit climbing constraint; wherein the power balance constraint specifically includes: an electric power balance constraint, a thermal power balance constraint, a cold power balance constraint, and a natural gas power balance constraint.
The electric power balance constraint is:
Figure BDA0003349091150000143
wherein E isbuy,e,tThe power purchasing power is used for purchasing power from the power grid at the moment t; ePV,e,tRepresenting the output electric power of the wind turbine; eWT,e,tRepresenting the output electric power of the photovoltaic unit; eGT,e,tElectrical power representing gas turbine output at time t; eEES,tRepresenting the electrical stored energy power at time t; eEC,c,tRepresents the cold power output by the electric refrigerator at time t,
Figure BDA0003349091150000149
representing the efficiency of the electric refrigerator; eEB,h,tRepresents the thermal power output by the electric boiler at the moment t,
Figure BDA00033490911500001410
indicating heat output by electric boilerEfficiency of power; eP2G,g,tThe natural gas power of the electric conversion gas output at the moment t is shown,
Figure BDA00033490911500001411
indicating the efficiency of electric gas conversion; euser,e,tRepresenting the electric load before the user carries out demand response at the time t; Δ q oftRepresenting the amount of load that the user changes after engaging in the demand response;
the thermal power balance constraint is:
Figure BDA0003349091150000144
wherein E isGB,h,tThe thermal power output by the gas boiler at the time t is represented; eWHB,h,tThe thermal power output by the waste heat boiler at the moment t is represented; eAC,c,tThe cold power output by the absorption refrigerator at the time t is represented;
Figure BDA0003349091150000145
showing the refrigeration efficiency of the absorption refrigerator; eTES,tThe heat storage and energy heating power at the time t is shown; euser,th,tRepresenting the actual heat load of the user at the time t;
the cold power balance constraints are:
EEC,c,t+EAC,c,t＝Euser,c,t
wherein E isuser,c,tIndicating the actual cooling load for the user at time t.
The natural gas power balance constraints are:
Figure BDA0003349091150000146
wherein,
Figure BDA0003349091150000147
representing the efficiency of the gas turbine;
Figure BDA0003349091150000148
efficiency of heat output of gas boiler, Euser,g,tRepresenting the actual natural gas load of the user at the time t;
the tie line constraint is:
Pgrid,min≤Ebuy,e,t≤Pgrid,max
wherein, Pgrid,min、Pgrid,maxRespectively representing the minimum value and the maximum value of the interaction power of the power distribution network;
the energy supply equipment is restricted as follows:
Figure BDA0003349091150000151
wherein, PWT(t)、PPV(t) respectively representing the generated energy of the wind power and the photovoltaic unit in the period of t, PWT,max、PPV，maxRespectively representing the upper limits of the output of the wind power generator set and the photovoltaic generator set;
the output constraint of the energy conversion equipment is as follows:
Figure BDA0003349091150000152
wherein E isGT,e,t、EWHB,h,t、EGB,h,t、EEC,c,t、EEB,h,t、EP2G,g,t、EAC,c,tRespectively representing the capacities of a gas turbine, a waste heat boiler, a gas boiler, an electric refrigerator, an electric boiler, an electric gas-converting machine and an absorption refrigerator; eGT,e,max、EWHB,h,max、EGB,h,max、EEC,c,max、EEB,h,max、EP2G,g,max、EAC,c,maxRespectively representing the maximum capacities of the gas turbine, the waste heat boiler, the gas boiler, the electric refrigerator, the electric boiler, the electric gas-transferring and absorption refrigerator;
the energy storage device is constrained as follows:
Figure BDA0003349091150000153
wherein E isEES,ch,t、EEES,dis,tRespectively the charging power and the discharging power at the time t; eEES,tThe storage capacity at the time t; eTES,ch,t、ETES,dis,tRespectively the charging power and the heat release power at the moment t; eTES,tThe heat storage capacity at time t; eEES,min、EEES,maxRespectively the minimum and maximum capacities of the electricity storage device; eTES,min、ETES,maxThe minimum and maximum capacities of the heat storage device are respectively set; gamma rayEES,ch、γEES,disThe charging state and the discharging state are respectively, and are variable 0-1; gamma rayTES,ch、γTES,disRespectively in a heat charging state and a heat discharging state, and the variables are 0-1; eEES,0A storage capacity at 0; eEES,24A storage capacity of 24 hours; eTES,0A heat storage capacity at 0; eTES,24A heat storage capacity of 24 hours;
the unit climbing restriction is:
|Em,t+1-Em,t|≤ΔPm,max
wherein E ism,t+1And Em,tRespectively representing the output energy of the fan at t +1 and t moments; delta Pm,maxIs the upper limit of the climbing of the device m.
Fig. 3 is an iteration principle of an optimal configuration scheme in an embodiment of the present invention, and as shown in fig. 3, the integrated optimization planning and operation method of an electric heating and gas integrated energy system provided by the present invention, (1) original sample data of the capacity of a multi-energy supply device in the electric heating and gas integrated energy system is given by using a latin hypercube sampling method; (2) optimizing a planning scheme of the electric heating and gas comprehensive energy system by using a mixed integer linear programming method to obtain an optimized combination scheme of multiple energy supply devices; (3) taking the optimized combination scheme obtained in the step (2) as an optimized boundary condition for the operation of the electric-heat-gas comprehensive energy system, and obtaining an optimal output plan scheme of the multi-energy supply equipment by adopting a particle swarm optimization algorithm and considering the optimized operation scheme of the comprehensive energy system with source-charge uncertainty; (4) taking the calculation result of the step (3) as the initial condition of the step (2), and continuing to optimize the combination scheme; (5) and (5) repeating the steps (2) to (3) until the finishing condition is met, and finishing the integrated planning and operation of the electric heating gas comprehensive energy system. The method specifically comprises the following steps:
1) constructing a multi-energy flow coupling model of the electric heating and gas comprehensive energy system;
2) the whole economy of the electric heating and gas comprehensive energy system is taken as a core, the minimum operation cost is constructed as a target function, and the planning and optimization of the electric heating and gas comprehensive energy system are completed;
3) taking the configuration scheme of the optimally planned energy supply equipment and energy conversion equipment as a boundary condition of optimal operation, taking the minimum annual operation cost of the electric-heat-gas integrated energy system as an objective function, giving an optimal operation output scheme of the energy supply equipment and the energy conversion equipment in the integrated energy system, and finishing the operation optimization of the electric-heat-gas integrated energy system;
4) taking the optimal operation output scheme of the energy supply equipment and the energy conversion equipment in the optimized operation as a planned output plan, continuously optimizing the planning scheme of the comprehensive energy system, and mutually transmitting cyclic calculation by using the solution results of the planning and the operation until the total cost of the comprehensive energy system is minimum, thereby finishing the integrated optimization of the planning and the operation of the comprehensive energy system;
5) and establishing a constraint equation of the energy supply equipment, the energy conversion equipment and the comprehensive energy network as a constraint condition of integrated planning and operation optimization.
The multi-energy flow coupling model of the electric heating and gas comprehensive energy system in the step 1) is as follows: l ═ JP
Wherein, L represents an output power matrix, P represents an input power matrix, and J represents a coupling sparse matrix.
The method comprises the following specific steps:
Figure BDA0003349091150000171
wherein E isWT、EPVRespectively inputting energy of a fan and a photovoltaic; f. ofWTWeir distribution probability density function, f, representing wind speed vPVRepresenting a probability density function of the illumination intensity obeying Beta distribution within a certain time period;
Figure BDA0003349091150000172
the electric energy consumed by the power grid, the electric boiler, the electric gas conversion machine and the electric refrigerator respectively accounts for the proportionality coefficients of the total electric energy;
Figure BDA0003349091150000173
the natural gas energy consumed by the natural gas network, the gas boiler and the gas turbine respectively accounts for the proportion coefficient of the total natural gas energy;
Figure BDA0003349091150000174
efficiency of electrical power output for the gas turbine;
Figure BDA0003349091150000175
efficiency of thermal power output for the gas boiler;
Figure BDA0003349091150000176
efficiency of outputting thermal power for the exhaust-heat boiler;
Figure BDA0003349091150000177
efficiency of outputting thermal power to the electric boiler;
Figure BDA0003349091150000178
efficiency of outputting natural gas power for an electric gas-to-gas plant;
Figure BDA0003349091150000179
efficiency of cold power output for the electric refrigerator;
Figure BDA00033490911500001710
efficiency of cold power output for an absorption chiller; pe、PgElectric energy and gas energy which can directly participate in use and energy conversion in the system are respectively; wherein in the letters superscript and subscript, e denotes electricity, e.g
Figure BDA00033490911500001711
The proportional coefficient of the electric energy absorbed from the power grid to the total consumed electric energy is represented; EB represents an electric boiler; P2G represents electrotransformation; EC representsElectrically refrigerating; g represents natural gas; GB represents a gas boiler; GT denotes a gas turbine; h represents heat energy; WHB denotes a waste heat boiler; AC denotes absorption refrigeration.
fWTThe Weir distribution probability density function representing the wind speed v specifically comprises the following steps:
Figure BDA0003349091150000181
wherein k represents a shape parameter; c represents a scale parameter.
EWTCan be expressed as:
Figure BDA0003349091150000182
wherein, PWTCan be expressed as:
Figure BDA0003349091150000183
wherein a, b, c and d are fitting coefficients; v is the actual wind speed, vin、voutRespectively cut-in and cut-out wind speed, vNRated wind speed; pN、PWTAnd (m) is the rated power and the output power of the fan respectively.
Figure BDA0003349091150000184
Rated value, invariant to changes in wind speed
fPVRepresenting that the illumination intensity obeys Beta distribution within a certain time period, specifically:
Figure BDA0003349091150000185
wherein Gamma is a Gamma function, PPVAnd PmaxRespectively photovoltaic output power and maximum output power; alpha and Beta are Beta distribution shape functions, respectively.
PPV＝rMAη
Wherein r is the intensity of solar radiation per unit area; m is the number of solar cell modules in the photovoltaic array; a is the area of each solar cell module; eta is the photoelectric conversion efficiency of the photovoltaic array.
EPV＝∫PPV(m)dt
The multi-energy coupling matrix of the integrated energy system is represented as follows:
Figure BDA0003349091150000186
wherein the relevant scheduling coefficients of various input energy sources satisfy the relationship of
Figure BDA0003349091150000191
Wherein E isWT、EPVRespectively inputting energy of a fan and a photovoltaic; lambda and beta are respectively scheduling factors of electric energy and natural gas; eta is the energy conversion efficiency of the conversion equipment; pe、PgElectric energy and gas energy which can directly participate in use and energy conversion in the system are respectively;
Figure BDA0003349091150000192
PEESrespectively energy storage and power grid interaction power and energy storage charging and discharging power.
The minimum objective function for the total cost of the optimization plan is:
minC＝Cp+Cma+Ce+Cg
wherein, CpFor the cost of construction, CmaFor operating and maintaining the respective apparatus, CeFor purchasing electricity from the grid, CgFor the purchase of gas from the gas network.
The construction cost expense is specifically as follows:
Figure BDA0003349091150000193
the operation and maintenance cost of each device is specifically as follows:
Figure BDA0003349091150000194
the electricity purchasing cost from the power grid is specifically as follows:
Figure BDA0003349091150000195
the gas purchasing cost from the natural gas pipe network is specifically as follows:
Figure BDA0003349091150000196
the main difference between the operation cost and the planning cost is that on the time scale, the maximum value of the planned time is 24 hours a day, and the optimization scheme of the operation considers that the construction cost is the full life cycle, the operation cost is 8760 hours a year, and the objective function is as follows:
Itotal＝IP+IMA+IE+IG
the construction cost of the whole life cycle is as follows:
Figure BDA0003349091150000201
the maintenance cost of each equipment in one year is as follows:
Figure BDA0003349091150000202
the electricity purchase cost of one year:
Figure BDA0003349091150000203
gas purchase cost for one year:
Figure BDA0003349091150000204
and 4) performing multiple optimization on planning and operation through mutual transmission of calculation results, namely the planning result provides initial conditions of energy supply equipment and energy conversion equipment for operation, the optimization operation result provides a power output scheme of the energy supply equipment and the energy conversion equipment for planning, and the optimization operation result is calculated repeatedly until the total cost and the cost of the comprehensive energy system are minimum, so that the integrated planning and operation optimization of the electric-heat-gas comprehensive energy system is completed.
The constraint in step 4) comprises:
(1) and (4) power balance constraint. The electric, heat, gas and cold power balance constraints need to be met in the dispatching operation of the multi-energy collaborative system, and the demand response quantity needs to be considered in the electric power balance constraints.
Electric power balance constraint:
Figure BDA0003349091150000205
wherein E isbuy,e,tThe power purchasing power is purchased from the power grid at the moment t; ePV,e,tThe output electric power of the wind turbine generator is obtained; eWT,e,tThe output electric power of the photovoltaic unit; euser,e,tThe power load before the demand response is carried out for the user at the time t; Δ q oftThe amount of load that the user changes after engaging in the demand response.
Wherein:
Figure BDA0003349091150000206
wherein: eGT,e,tThe electric power output by the gas turbine at the moment t;
Figure BDA0003349091150000211
efficiency of the gas turbine; q. q.sgasAs natural gasA calorific value; eGT,g,tThe power consumed by the natural gas of the gas turbine at the moment t;
Figure BDA0003349091150000212
wherein: eEC,c,tThe cold power output by the electric refrigerator at the moment t; eEC,e,tThe electric power consumed by the electric refrigerator at the moment t;
Figure BDA0003349091150000213
is the efficiency of the electric refrigerator;
Figure BDA0003349091150000214
wherein: eEB,h,tThe thermal power output by the electric boiler at the moment t; eEB,e,tThe electric power consumed by the electric boiler at the moment t;
Figure BDA0003349091150000215
efficiency of outputting thermal power to the electric boiler;
Figure BDA0003349091150000216
wherein: eP2G,g,tThe natural gas power output for electric gas conversion at the time t; eP2G,e,tThe electric power consumed for electric gas conversion at the time t;
Figure BDA0003349091150000217
the efficiency of converting electricity into gas;
secondly, thermal power balance constraint:
Figure BDA0003349091150000218
wherein: euser,th,tThe actual heat load for the user at time t.
Wherein:
Figure BDA0003349091150000219
wherein: eGB,h,tThe thermal power output by the gas boiler at the moment t;
Figure BDA00033490911500002110
efficiency of thermal power output for the gas boiler; eGB,g,tThe natural gas consumption power of the gas boiler at the moment t;
Figure BDA00033490911500002111
wherein: eWHB,h,tThe thermal power output by the waste heat boiler at the moment t;
Figure BDA00033490911500002112
efficiency of outputting thermal power for the exhaust-heat boiler;
Figure BDA00033490911500002113
wherein: eAC,c,tThe cold power output by the absorption refrigerator at the moment t;
Figure BDA00033490911500002114
the refrigeration efficiency of the absorption refrigerator; eAC,h,tIs the thermal power consumed at time t.
Cold power balance constraint:
EEC,c,t+EAC,c,t＝Euser,c,t
wherein: euser,c,tThe actual cooling load is used for the user at time t.
Fourthly, natural gas power balance constraint:
Figure BDA0003349091150000221
wherein: euser,g,tThe actual natural gas load is the user at time t.
Tie line constraint:
Pgrid,min≤Ebuy,e,t≤Pgrid,max
wherein: pgrid,min、Pgrid,maxThe minimum value and the maximum value of the interaction power of the power distribution network are respectively.
(3) Energy supply equipment restraint:
Figure BDA0003349091150000222
wherein: pWT(t)、PPV(t) is the generated energy of the wind power and photovoltaic unit in the period of t, PWT,max、PPV，maxThe output of the wind power and photovoltaic units is the upper limit.
(4) And (3) output constraint of energy conversion equipment:
Figure BDA0003349091150000223
wherein E isGT,e,t、EWHB,h,t、EGB,h,t、EEC,c,t、EEB,h,t、EP2G,g,t、EAC,c,tRespectively representing the capacities of a gas turbine, a waste heat boiler, a gas boiler, an electric refrigerator, an electric boiler, an electric gas-converting machine and an absorption refrigerator; eGT,e,max、EWHB,h,max、EGB,h,max、EEC,c,max、EEB,h,max、EP2G,g,max、EAC,c,maxRespectively showing the maximum capacity of a gas turbine, a waste heat boiler, a gas boiler, an electric refrigerator, an electric boiler, an electric gas-transferring and absorption refrigerator.
(5) And (4) energy storage device restraint:
Figure BDA0003349091150000231
wherein: eEES,min、EEES,maxRespectively the minimum and maximum capacities of the electricity storage device; eTES,min、ETES,maxRespectively the minimum and maximum capacity of the heat storage device.
Wherein:
Figure BDA0003349091150000232
wherein: eEES,tThe storage capacity at the time t; alpha is the self-loss rate of the power storage equipment; eEES,t-1The storage capacity at the time t-1; eEES,ch,t、EEES,dis,tRespectively the charging power and the discharging power at the time t; etaEES,ch、ηEES,disRespectively charge and discharge efficiency; gamma rayEES,ch、γEES,disThe charging state and the discharging state are respectively, and are variable 0-1; Δ t1For the charging and discharging time, take 1 h.
Figure BDA0003349091150000233
In the formula: eTES,tThe heat storage capacity at time t; beta is the self-loss rate of the heat storage equipment; eTES,t-1The heat storage capacity at the time t-1; eTES,ch,t、ETES,dis,tRespectively the charging power and the heat release power at the moment t; etaTES,ch、ηTES,disRespectively has heat charging and discharging efficiency; gamma rayTES,ch、γTES,disRespectively in a heat charging state and a heat discharging state, and the variables are 0-1; Δ t2The heating and cooling time is 1 h.
(6) Unit climbing restraint:
|Em,t+1-Em,t|≤ΔPm,max
wherein: delta Pm,maxIs the upper limit of the climbing of the device m.
FIG. 2 is a schematic diagram of an integrated energy system according to an embodiment of the present invention; as shown in fig. 2, the electric-thermal-gas integrated energy system of the invention is composed of an E _ grid-power grid, a T _ grid-heat grid, an NG _ grid-gas grid, energy for users (including E _ load-electric load, T _ load-heat load and C _ load-cold load) and energy supply equipment, so as to form an integrated energy network, wherein the energy supply equipment includes PV-photovoltaic power generation, WT-wind power generation, P2G-electric gas conversion device, GT-gas turbine set, WHB-waste heat boiler, GB-gas boiler, EES-electric energy storage, EC-electric refrigeration, EB-electric boiler, TES-thermal energy storage, and AC-absorption refrigeration. Wherein, the electric network, the heat supply network and the gas network are all interconnected and intercommunicated with the electric heating gas public network. The energy supply side of the comprehensive energy system comprises electric energy, heat energy and natural gas, and the energy utilization side comprises an electric load, a heat load and a cold load.
The electric energy connects the power generation equipment, the electric load, the electric energy storage device, the energy conversion equipment and the public power grid through the power grid. The power generation equipment comprises wind power generation, photovoltaic power generation and a gas turbine set; the electric energy storage device is a storage battery; the energy conversion equipment comprises an electric gas conversion device, an electric boiler and an electric refrigerating device.
The heat energy connects the heat supply device, the heat load, the heat energy storage device, the energy conversion equipment and the public heat supply network through the heat supply network. Wherein, the heat supply device comprises a waste heat boiler, an electric boiler and a gas boiler; the heat energy storage device is a heat storage tank; the energy conversion device comprises an absorption refrigeration unit.
The natural gas is provided by a common natural gas pipe network and an electric gas conversion device and is used for generating electricity and supplying heat for a gas turbine set and supplying heat for a gas boiler.
The cold energy transmits the cold energy output by the absorption refrigeration and the electric refrigeration to the cold load through the cold energy pipeline.
According to the structure of the electric heating and gas comprehensive energy system provided by the figure 2, a comprehensive energy system multi-energy flow coupling model is established, and the planning and optimization of the comprehensive energy system are completed by taking the minimum construction cost and the minimum daily operation cost as targets, wherein the comprehensive energy system comprises a configuration scheme of multi-energy supply and energy conversion equipment in the figure 2. According to the configuration scheme, the minimum annual operating cost of the comprehensive energy system is taken as a target, uncertainty of renewable energy and user energy load is considered, operation optimization of the comprehensive energy system is completed, an output plan scheme of the multi-energy supply equipment and the energy conversion equipment in the comprehensive energy system is obtained, the output plan after operation optimization is used as an initial condition of planning to further carry out planning optimization, and circular optimization calculation is carried out through mutual transmission of planning and operation results until the total operating cost of the whole comprehensive energy system is minimum, so that the optimization calculation is finished, and integrated planning and operation optimization of the comprehensive energy system are completed.
As shown in fig. 3, the electric-heating-gas integrated energy system according to the invention provides an optimal planning and operation scheme of the integrated energy system with the aim of minimizing the total operation cost of the integrated energy system and with the constraint conditions of the output of energy supply equipment and the operation safety of the system.
The electric heating and gas comprehensive energy system is integrated in planning and operation optimization, the essence of the electric heating and gas comprehensive energy system is that the planning and the operation of the comprehensive energy system are closely related inseparable whole, the optimization results of the planning and the operation are mutually influenced, and the two parties interactively transfer the calculation results. The optimization planning result of the comprehensive energy system provides boundary conditions for operation optimization, and the result after the operation optimization can provide basis such as an operation scheme, total cost and the like for the optimization planning, and the two are mutually related. And (4) finishing the calculation until the conditions are met after repeated loop iterative calculation through mutual transmission of planning and operation optimization results. The iterative convergence condition of the invention is that when the deviation between the two adjacent calculation results is less than the set threshold value, the calculation is stopped. And the result of the calculation is the optimal planning configuration scheme and the optimal operation output planning scheme of the electric heating and gas comprehensive energy system.
As can be seen from fig. 3, through mutual transmission and interaction between the calculation results of the integrated energy system planning model and the integrated energy system operation model, the obtained optimized planning scheme is verified in the actual optimized operation, and the feasibility and the rationality of the planning scheme are verified; meanwhile, uncertainty of renewable energy supply and user energy consumption is fully considered during optimized operation, optimization calculation is carried out by combining boundary conditions provided by planning, the output plan of the optimized and calculated equipment is returned to the optimized planning in the operation cost, the optimized planning calculation is further carried out by correcting a planning target, and the optimal planning scheme and the operation scheme are finally obtained by repeating iterative calculation in the way.
Fig. 4 is a schematic structural diagram of an integrated optimal planning and operation device of an integrated energy system according to an embodiment of the present invention, and as shown in fig. 4, the present invention further provides an integrated optimal planning and operation device of an integrated energy system, including:
a basic parameter obtaining module 401, configured to obtain basic parameters of the integrated energy system;
a multi-energy flow coupling model building module 402, configured to build a multi-energy flow coupling model of the integrated energy system according to the basic parameters;
an objective function constructing module 403, configured to construct an operation cost objective function, a total cost objective function, and constraint conditions; the total cost objective function comprises operation cost and infrastructure cost;
a zeroth configuration scheme determining module 404, configured to use an initial configuration scheme of the energy supply devices and the energy conversion devices in the integrated energy system as a zeroth configuration scheme;
a first configuration scheme determining module 405, configured to adjust output powers of all energy supply devices and energy conversion devices in the integrated energy system under the zeroth configuration scheme based on the constraint condition and the multi-energy-flow coupling model, so as to obtain a first configuration scheme of the energy supply devices and the energy conversion devices;
a second configuration scheme determining module 406, configured to adjust output of various energy sources in the integrated energy system under the first configuration scheme based on the constraint condition and the multi-energy-flow coupling model, to obtain a second configuration scheme of the energy supply device and the energy conversion device;
an optimal scheme determining module 407 for the current iteration, configured to calculate operation cost objective functions of the first configuration scheme and the second configuration scheme, respectively, and determine a scheme with a smaller operation cost objective function as an optimal scheme for the current iteration;
a total cost calculation module 408, configured to calculate a total cost objective function of the optimal solution of the current iteration;
a loop iteration module 409, configured to, when the total cost target function of the optimal scheme of the current iteration is greater than or equal to the total cost threshold, take the optimal scheme of the current iteration as a zeroth configuration scheme, and call the first configuration scheme determining module;
and an optimal configuration scheme determining module 410, configured to determine the optimal scheme of the current iteration as the optimal configuration scheme of the integrated energy system when the total cost objective function of the optimal scheme of the current iteration is smaller than the total cost threshold.
The multi-energy flow coupling model is as follows: l ═ JP;
wherein, L represents an output power matrix,
Figure BDA0003349091150000261
Le、Lh、Lgand LcRespectively representing the output power of electricity, heat, natural gas and cold in the comprehensive energy system Z; j represents a coupled sparse matrix and J represents,
Figure BDA0003349091150000271
fWTweir distribution probability density function, f, representing wind speed vPVA probability density function representing the Beta distribution of the illumination intensity within a preset time period;
Figure BDA0003349091150000272
and
Figure BDA0003349091150000273
respectively representing the proportion coefficients of the electric energy consumed by a power grid, an electric boiler, an electric gas-converting machine and an electric refrigerator in the comprehensive energy system to the total electric energy;
Figure BDA0003349091150000274
Figure BDA0003349091150000275
and
Figure BDA0003349091150000276
respectively representing the efficiency of the output power of a gas turbine, a gas boiler, a waste heat boiler, an electric gas conversion device, an electric refrigerator and an absorption refrigerator in the comprehensive energy system;
Figure BDA0003349091150000277
Figure BDA0003349091150000278
and
Figure BDA0003349091150000279
respectively representing the proportional coefficients of natural gas energy consumed by a natural gas network, a gas boiler and a gas turbine in the comprehensive energy system in the total natural gas energy; p represents the input power matrix and P represents the input power matrix,
Figure BDA00033490911500002710
EWTand EPVRespectively representing the input energy of a fan and a photovoltaic in the comprehensive energy system; peAnd PgRespectively representing electric energy and gas energy which can be directly used in the integrated energy system.
The operating cost objective function is:
C＝Cp+Cma+Ce+Cg；
wherein C represents the planning cost, CPRepresents the cost of the construction of the equipment,
Figure BDA00033490911500002711
Cl,nthe equipment construction cost is represented by the position node L and the capacity number N, L represents the total number of the position nodes, N represents the total number of the capacity numbers, Il,n(0, 1) decision variables representing devices with location nodes of l capacity number n; cmaFor the operating and maintenance costs of each piece of equipment,
Figure BDA00033490911500002712
t represents a period; rGT、RWHB、RP2G、RWT、RPV、RGB、REC、RAC、REB、Rbe、RhcRespectively representing the operation and maintenance cost coefficients of a gas turbine, a waste heat boiler, an electric gas conversion device, a wind turbine generator, a photovoltaic generator, a gas boiler, an electric refrigerating device, an absorption refrigerating device, an electric boiler, an electric energy storage device and a heat energy storage device in the comprehensive energy system; pGT,t、HWHB,t、PP2G,t、PWT,t、PPV,t、HGB,t、CEC,t、CAC,t、HEB,t、Pbc,t、Pbd,t、Hhc,t、Hhd,tRespectively representing the output electric power of a gas turbine, the output thermal power of a waste heat boiler, the input electric power of electricity-to-gas, the output electric power of a wind turbine generator, the output electric power of photovoltaic power, the output thermal power of a gas boiler, the output cold power of electric refrigeration, the output cold power of absorption refrigeration, the output thermal power of an electric boiler, the storage electric power of an electric storage device, the output electric power of the electric storage device, the storage thermal power of a thermal storage device and the output thermal power of the thermal storage device in a delta t time period; ceRepresenting the cost of purchasing electricity from the grid,
Figure BDA0003349091150000281
ce,trepresenting grid electricity price, P, over a period of Δ tg,tRepresenting electric power input into the integrated energy system by the power grid during the delta t period; cgIndicating a purchase of gas from the gas network,
Figure BDA0003349091150000282
cg,tgas network gas price, Q, for a period of Δ tg,tAnd inputting the gas quantity of the comprehensive energy system for the natural gas pipe network in the delta t period.
The total cost objective function is:
Itotal＝IP+IMA+IE+IG
wherein, ItotalRepresents the total cost, IPThe construction cost of the full life cycle is represented,
Figure BDA0003349091150000283
x is the total number of devices, SlCapacity of the l-th equipment, ClThe construction cost per unit capacity of the first equipment, R is the fixed capital residual rate, R is the discount rate, mlThe life cycle of the device l; i isMARepresenting the maintenance costs of the respective equipment for one year,
Figure BDA0003349091150000284
Klfor the maintenance cost factor, P, of the apparatus ll,tThe output power of the device during the delta t period; i isERepresents the electricity purchase cost of one year,
Figure BDA0003349091150000285
IGrepresents the gas purchase cost of one year,
Figure BDA0003349091150000286
the embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (10)

1. An integrated optimization planning and operation method of an integrated energy system, the method comprising:
acquiring basic parameters of the comprehensive energy system;
constructing a multi-energy flow coupling model of the comprehensive energy system according to the basic parameters;
constructing an operation cost objective function, a total cost objective function and the constraint condition; the total cost objective function comprises an operation cost and an infrastructure cost;
taking an initial configuration scheme of energy supply equipment and energy conversion equipment in the comprehensive energy system as a zeroth configuration scheme;
based on the constraint conditions and the multi-energy flow coupling model, adjusting the output power of all energy supply equipment and energy conversion equipment in the comprehensive energy system under the zeroth configuration scheme to obtain a first configuration scheme of the energy supply equipment and the energy conversion equipment;
based on the constraint conditions and the multi-energy flow coupling model, adjusting the output of various energy sources in the comprehensive energy system under the first configuration scheme to obtain a second configuration scheme of energy supply equipment and energy conversion equipment;
respectively calculating the operation cost objective functions of the first configuration scheme and the second configuration scheme, and determining a scheme with a smaller operation cost objective function as an optimal scheme of the current iteration;
calculating a total cost objective function of the optimal scheme of the iteration;
when the total cost target function of the optimal scheme of the iteration is larger than or equal to the total cost threshold value, taking the optimal scheme of the iteration as a zeroth configuration scheme, and returning to the step of adjusting the output power of all energy supply equipment and energy conversion equipment in the comprehensive energy system under the zeroth configuration scheme based on the constraint condition and the multi-energy flow coupling model to obtain a first configuration scheme of the energy supply equipment and the energy conversion equipment;
and when the total cost target function of the optimal scheme of the iteration is smaller than the total cost threshold value, determining the optimal scheme of the iteration as the optimal configuration scheme of the comprehensive energy system.
2. The integrated optimization planning and operation method of an integrated energy system according to claim 1, wherein the multi-power flow coupling model is: l ═ JP;
wherein, L represents an output power matrix,
Figure FDA0003349091140000021
Le、Lh、Lgand LcRespectively representing the output power of electricity, heat, natural gas and cold in the comprehensive energy system Z; j represents a coupled sparse matrix and J represents,
Figure FDA0003349091140000022
fWTweir distribution probability density function, f, representing wind speed vPVA probability density function representing the Beta distribution of the illumination intensity within a preset time period;
Figure FDA0003349091140000023
and
Figure FDA0003349091140000024
respectively representing the proportion coefficients of the electric energy consumed by a power grid, an electric boiler, an electric gas-converting machine and an electric refrigerator in the comprehensive energy system to the total electric energy;
Figure FDA0003349091140000025
Figure FDA0003349091140000026
and
Figure FDA0003349091140000027
respectively representing the efficiency of the output power of a gas turbine, a gas boiler, a waste heat boiler, an electric gas conversion device, an electric refrigerator and an absorption refrigerator in the comprehensive energy system;
Figure FDA0003349091140000028
Figure FDA0003349091140000029
and
Figure FDA00033490911400000210
respectively representing the proportional coefficients of natural gas energy consumed by a natural gas network, a gas boiler and a gas turbine in the comprehensive energy system in the total natural gas energy; p represents the input power matrix and P represents the input power matrix,
Figure FDA00033490911400000211
EWTand EPVRespectively representThe input energy of a fan and a photovoltaic in the comprehensive energy system; peAnd PgRespectively representing electric energy and gas energy which can be directly used in the integrated energy system.
3. The integrated optimization planning and operation method of an integrated energy system according to claim 1, wherein the operation cost objective function is:
C＝Cp+Cma+Ce+Cg；
wherein C represents the planning cost, CPRepresents the cost of the construction of the equipment,
Figure FDA00033490911400000212
Cl,nthe equipment construction cost is represented by the position node L and the capacity number N, L represents the total number of the position nodes, N represents the total number of the capacity numbers, Il,n(0, 1) decision variables representing devices with location nodes of l capacity number n; cmaFor the operating and maintenance costs of each piece of equipment,
Figure FDA00033490911400000213
t represents a period; rGT、RWHB、RP2G、RWT、RPV、RGB、REC、RAC、REB、Rbe、RhcRespectively representing the operation and maintenance cost coefficients of a gas turbine, a waste heat boiler, an electric gas conversion device, a wind turbine generator, a photovoltaic generator, a gas boiler, an electric refrigerating device, an absorption refrigerating device, an electric boiler, an electric energy storage device and a heat energy storage device in the comprehensive energy system; pGT,t、HWHB,t、PP2G,t、PWT,t、PPV,t、HGB,t、CEC,t、CAC,t、HEB,t、Pbc,t、Pbd,t、Hhc,t、Hhd,tRespectively representing the output electric power of a gas turbine, the output thermal power of a waste heat boiler, the input electric power of electricity-to-gas, the output electric power of a wind turbine generator, the output electric power of photovoltaic, the output thermal power of a gas boiler and the output cold power of electric refrigeration in a delta t time periodThe absorption refrigeration system comprises an absorption refrigeration system, an electric boiler, an electric storage device, a heat storage device and a heat storage device, wherein the absorption refrigeration system outputs cold power, the electric boiler outputs heat power, the electric storage device stores electric power, the electric storage device outputs electric power, the heat storage device stores heat power, and the heat storage device outputs heat power; ceRepresenting the cost of purchasing electricity from the grid,
Figure FDA0003349091140000031
ce,trepresenting grid electricity price, P, over a period of Δ tg,tRepresenting electric power input into the integrated energy system by the power grid during the delta t period; cgIndicating a purchase of gas from the gas network,
Figure FDA0003349091140000032
cg,tgas network gas price, Q, for a period of Δ tg,tAnd inputting the gas quantity of the comprehensive energy system for the natural gas pipe network in the delta t period.
4. The integrated optimization planning and operation method of an integrated energy system according to claim 3, wherein the total cost objective function is:
Itotal＝IP+IMA+IE+IG
wherein, ItotalRepresents the total cost, IPThe construction cost of the full life cycle is represented,
Figure FDA0003349091140000033
x is the total number of devices, SlCapacity of the l-th equipment, ClThe construction cost per unit capacity of the first equipment, R is the fixed capital residual rate, R is the discount rate, mlThe life cycle of the device l; i isMARepresenting the maintenance costs of the respective equipment for one year,
Figure FDA0003349091140000034
Klfor the maintenance cost factor, P, of the apparatus ll,tThe output power of the device during the delta t period; i isERepresents the electricity purchase cost of one year,
Figure FDA0003349091140000035
IGrepresents the gas purchase cost of one year,
Figure FDA0003349091140000036
5. the integrated optimization planning and operation method of integrated energy system according to claim 1, wherein the constraint condition includes: power balance constraint, tie line constraint, energy supply equipment constraint, energy conversion equipment output constraint, energy storage device constraint and unit climbing constraint; wherein the power balance constraint specifically includes: an electric power balance constraint, a thermal power balance constraint, a cold power balance constraint, and a natural gas power balance constraint.
6. The integrated optimization planning and operation method of integrated energy system according to claim 5,
the electric power balance constraint is:
Figure FDA0003349091140000041
wherein E isbuy,e,tThe power purchasing power is used for purchasing power from the power grid at the moment t; ePV,e,tRepresenting the output electric power of the wind turbine; eWT,e,tRepresenting the output electric power of the photovoltaic unit; eGT,e,tElectrical power representing gas turbine output at time t; eEES,tRepresenting the electrical stored energy power at time t; eEC,c,tRepresents the cold power output by the electric refrigerator at time t,
Figure FDA0003349091140000042
representing the efficiency of the electric refrigerator; eEB,h,tRepresents the thermal power output by the electric boiler at the moment t,
Figure FDA0003349091140000043
indicating output thermal power of electric boilerThe efficiency of (c); eP2G,g,tThe natural gas power of the electric conversion gas output at the moment t is shown,
Figure FDA0003349091140000044
indicating the efficiency of electric gas conversion; euser,e,tRepresenting the electric load before the user carries out demand response at the time t; Δ q oftRepresenting the amount of load that the user changes after engaging in the demand response;
the thermal power balance constraint is as follows:
Figure FDA0003349091140000045
wherein E isGB,h,tThe thermal power output by the gas boiler at the time t is represented; eWHB,h,tThe thermal power output by the waste heat boiler at the moment t is represented; eAC,c,tThe cold power output by the absorption refrigerator at the time t is represented;
Figure FDA0003349091140000046
showing the refrigeration efficiency of the absorption refrigerator; eTES,tThe heat storage and energy heating power at the time t is shown; euser,th,tRepresenting the actual heat load of the user at the time t;
the cold power balance constraint is:
EEC,c,t+EAC,c,t＝Euser,c,t
wherein E isuser,c,tIndicating the actual cooling load for the user at time t.
The natural gas power balance constraint is as follows:
Figure FDA0003349091140000047
wherein,
Figure FDA0003349091140000048
representing the efficiency of the gas turbine;
Figure FDA0003349091140000049
efficiency of heat output of gas boiler, Euser,g,tRepresenting the actual natural gas load of the user at the time t;
the tie line constraint is:
Pgrid,min≤Ebuy,e,t≤Pgrid,max
wherein, Pgrid,min、Pgrid,maxRespectively representing the minimum value and the maximum value of the interaction power of the power distribution network;
the energy supply device is constrained as follows:
Figure FDA0003349091140000051
wherein, PWT(t)、PPV(t) respectively representing the generated energy of the wind power and the photovoltaic unit in the period of t, PWT,max、PPV，maxRespectively representing the upper limits of the output of the wind power generator set and the photovoltaic generator set;
the output constraint of the energy conversion equipment is as follows:
Figure FDA0003349091140000052
wherein E isGT,e,t、EWHB,h,t、EGB,h,t、EEC,c,t、EEB,h,t、EP2G,g,t、EAC,c,tRespectively representing the capacities of a gas turbine, a waste heat boiler, a gas boiler, an electric refrigerator, an electric boiler, an electric gas-converting machine and an absorption refrigerator; eGT,e,max、EWHB,h,max、EGB,h,max、EEC,c,max、EEB,h,max、EP2G,g,max、EAC,c,maxRespectively representing the maximum capacities of the gas turbine, the waste heat boiler, the gas boiler, the electric refrigerator, the electric boiler, the electric gas-transferring and absorption refrigerator;
the energy storage device constraints are:
Figure FDA0003349091140000053
wherein E isEES,ch,t、EEES,dis,tRespectively the charging power and the discharging power at the time t; eEES,tThe storage capacity at the time t; eTES,ch,t、ETES,dis,tRespectively the charging power and the heat release power at the moment t; eTES,tThe heat storage capacity at time t; eEES,min、EEES,maxRespectively the minimum and maximum capacities of the electricity storage device; eTES,min、ETES,maxThe minimum and maximum capacities of the heat storage device are respectively set; gamma rayEES,ch、γEES,disThe charging state and the discharging state are respectively, and are variable 0-1; gamma rayTES,ch、γTES,disRespectively in a heat charging state and a heat discharging state, and the variables are 0-1; eEES,0A storage capacity at 0; eEES,24A storage capacity of 24 hours; eTES,0A heat storage capacity at 0; eTES,24A heat storage capacity of 24 hours;
the unit climbing restraint is as follows:
|Em,t+1-Em,t|≤ΔPm,max
wherein E ism,t+1And Em,tRespectively representing the output energy of the fan at t +1 and t moments; delta Pm,maxIs the upper limit of the climbing of the device m.
7. An integrated optimization planning and operation device for an integrated energy system, the device comprising:
the basic parameter acquisition module is used for acquiring basic parameters of the comprehensive energy system;
the multi-energy flow coupling model building module is used for building a multi-energy flow coupling model of the comprehensive energy system according to the basic parameters;
the target function construction module is used for constructing an operation cost target function, a total cost target function and the constraint condition; the total cost objective function comprises an operation cost and an infrastructure cost;
the zero configuration scheme determining module is used for taking the initial configuration scheme of the energy supply equipment and the energy conversion equipment in the comprehensive energy system as a zero configuration scheme;
the first configuration scheme determining module is used for adjusting the output power of all energy supply equipment and energy conversion equipment in the comprehensive energy system under the zeroth configuration scheme based on the constraint condition and the multi-energy flow coupling model to obtain a first configuration scheme of the energy supply equipment and the energy conversion equipment;
the second configuration scheme determining module is used for adjusting the output of various energy sources in the comprehensive energy system under the first configuration scheme based on the constraint conditions and the multi-energy flow coupling model to obtain a second configuration scheme of the energy supply equipment and the energy conversion equipment;
the optimal scheme determining module of the iteration is used for respectively calculating the operation cost objective functions of the first configuration scheme and the second configuration scheme and determining a scheme with a smaller operation cost objective function as the optimal scheme of the iteration;
the total cost calculation module is used for calculating a total cost target function of the optimal scheme of the iteration;
the loop iteration module is used for taking the optimal scheme of the current iteration as a zeroth configuration scheme and calling the first configuration scheme determining module when the total cost target function of the optimal scheme of the current iteration is greater than or equal to a total cost threshold;
and the optimal configuration scheme determining module is used for determining the optimal scheme of the iteration as the optimal configuration scheme of the comprehensive energy system when the total cost target function of the optimal scheme of the iteration is smaller than the total cost threshold.
8. The integrated optimization planning and operation device of integrated energy system according to claim 7, wherein the multi-power flow coupling model is: l ═ JP;
wherein, L represents an output power matrix,
Figure FDA0003349091140000071
Le、Lh、Lgand LcRespectively representing the output power of electricity, heat, natural gas and cold in the comprehensive energy system Z; j represents a coupled sparse matrix and J represents,
Figure FDA0003349091140000072
fWTweir distribution probability density function, f, representing wind speed vPVA probability density function representing the Beta distribution of the illumination intensity within a preset time period;
Figure FDA0003349091140000073
and
Figure FDA0003349091140000074
respectively representing the proportion coefficients of the electric energy consumed by a power grid, an electric boiler, an electric gas-converting machine and an electric refrigerator in the comprehensive energy system to the total electric energy;
Figure FDA0003349091140000075
Figure FDA0003349091140000076
and
Figure FDA0003349091140000077
respectively representing the efficiency of the output power of a gas turbine, a gas boiler, a waste heat boiler, an electric gas conversion device, an electric refrigerator and an absorption refrigerator in the comprehensive energy system;
Figure FDA0003349091140000078
Figure FDA0003349091140000079
and
Figure FDA00033490911400000710
respectively representing the proportional coefficients of natural gas energy consumed by a natural gas network, a gas boiler and a gas turbine in the comprehensive energy system in the total natural gas energy; p represents the input power momentThe number of the arrays is determined,
Figure FDA00033490911400000711
EWTand EPVRespectively representing the input energy of a fan and a photovoltaic in the comprehensive energy system; peAnd PgRespectively representing electric energy and gas energy which can be directly used in the integrated energy system.
9. The integrated optimization planning and operation device of integrated energy system according to claim 7, wherein the operation cost objective function is:
C＝Cp+Cma+Ce+Cg；
wherein C represents the planning cost, CPRepresents the cost of the construction of the equipment,
Figure FDA00033490911400000712
Cl,nthe equipment construction cost is represented by the position node L and the capacity number N, L represents the total number of the position nodes, N represents the total number of the capacity numbers, Il,n(0, 1) decision variables representing devices with location nodes of l capacity number n; cmaFor the operating and maintenance costs of each piece of equipment,
Figure FDA0003349091140000081
t represents a period; rGT、RWHB、RP2G、RWT、RPV、RGB、REC、RAC、REB、Rbe、RhcRespectively representing the operation and maintenance cost coefficients of a gas turbine, a waste heat boiler, an electric gas conversion device, a wind turbine generator, a photovoltaic generator, a gas boiler, an electric refrigerating device, an absorption refrigerating device, an electric boiler, an electric energy storage device and a heat energy storage device in the comprehensive energy system; pGT,t、HWHB,t、PP2G,t、PWT,t、PPV,t、HGB,t、CEC,t、CAC,t、HEB,t、Pbc,t、Pbd,t、Hhc,t、Hhd,tRespectively represent the time of deltatThe gas turbine in the section outputs electric power, the waste heat boiler outputs heat power, the electricity is converted into gas input electric power, the wind turbine generator outputs electric power, the photovoltaic output electric power, the gas boiler outputs heat power, the electric refrigeration output cold power, the absorption refrigeration output cold power, the electric boiler outputs heat power, the electric storage device stores electric power, the electric storage device outputs electric power, the heat storage device stores heat power, and the heat storage device outputs heat power; ceRepresenting the cost of purchasing electricity from the grid,
Figure FDA0003349091140000082
ce,trepresenting grid electricity price, P, over a period of Δ tg,tRepresenting electric power input into the integrated energy system by the power grid during the delta t period; cgIndicating a purchase of gas from the gas network,
Figure FDA0003349091140000083
cg,tgas network gas price, Q, for a period of Δ tg,tAnd inputting the gas quantity of the comprehensive energy system for the natural gas pipe network in the delta t period.
10. The integrated optimization planning and operation device of the integrated energy system according to claim 9, wherein the total cost objective function is:
Itotal＝IP+IMA+IE+IG
wherein, ItotalRepresents the total cost, IPThe construction cost of the full life cycle is represented,
Figure FDA0003349091140000084
x is the total number of devices, SlCapacity of the l-th equipment, ClThe construction cost per unit capacity of the first equipment, R is the fixed capital residual rate, R is the discount rate, mlThe life cycle of the device l; i isMARepresenting the maintenance costs of the respective equipment for one year,
Figure FDA0003349091140000085
Klis a devicel maintenance cost factor, Pl,tThe output power of the device during the delta t period; i isERepresents the electricity purchase cost of one year,
Figure FDA0003349091140000086
IGrepresents the gas purchase cost of one year,
Figure FDA0003349091140000087
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CN115049149A (en) * 2022-07-08 2022-09-13 天津泰达滨海清洁能源集团有限公司 Comprehensive energy system capacity optimal configuration and optimal scheduling method
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CN115049149A (en) * 2022-07-08 2022-09-13 天津泰达滨海清洁能源集团有限公司 Comprehensive energy system capacity optimal configuration and optimal scheduling method
CN115081259A (en) * 2022-08-23 2022-09-20 成都国星宇航科技股份有限公司 Watt-hour energy calculation method and device for optimizing satellite solar cell array
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Application publication date: 20220218