CN113806952A - Source-load-storage-considered cooling, heating and power comprehensive energy system and optimized operation method thereof - Google Patents

Source-load-storage-considered cooling, heating and power comprehensive energy system and optimized operation method thereof Download PDF

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CN113806952A
CN113806952A CN202111117745.2A CN202111117745A CN113806952A CN 113806952 A CN113806952 A CN 113806952A CN 202111117745 A CN202111117745 A CN 202111117745A CN 113806952 A CN113806952 A CN 113806952A
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赵琰
王亚茹
赵涛
周航
李兆滢
姜河
林盛
韩吉
于源
叶瀚文
白金禹
辛长庆
胡宸嘉
安琦
何雨桐
姜铭坤
魏莫杋
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Abstract

The invention discloses a source-load-storage considered cooling, heating and power comprehensive energy system and an optimized operation method thereof, wherein the method comprises the following steps: step 1: the electricity, gas and heat in the energy hub are coupled and converted into electricity, cold and heat for users to use. Step 2: units in an energy hub are modeled. And step 3: establishing an objective function and a constraint condition for optimizing the operation of the source-load-storage integrated cooling, heating and power energy system; and 4, step 4: firstly, converting inequality constraints into equality constraints, and then solving by using an improved branch-and-bound method to obtain an optimal solution of the objective function. The invention can improve the consumption of wind power and photoelectricity, realizes the mutual matching of source-load-storage, reduces the carbon emission of the system, reduces the operation cost of the system, enables the operation of the system to be more flexible, and realizes the economic operation and the environment-friendly operation of the system.

Description

Source-load-storage-considered cooling, heating and power comprehensive energy system and optimized operation method thereof
Technical Field
The invention relates to the field of comprehensive energy of power systems, in particular to a source-charge-storage considered cooling, heating and power comprehensive energy system and an optimized operation method thereof.
Background
With the rapid development of social economy, the demand of various industries on energy sources is increasing, so that the increasing exhaustion of the energy sources also becomes a significant problem which cannot be ignored nowadays, and the environmental pollution and the climate change follow the problem. Therefore, finding an environment-friendly and efficient energy source capable of replacing the traditional energy source is a serious task, and the utilization of clean energy sources is also carried out, wherein solar energy and wind energy are mainly used.
At present, most energy systems are operated independently, so that the system has low energy utilization rate and high operation cost, and therefore, a comprehensive energy system capable of coupling multiple energy sources and realizing advantage complementation among different energy sources is provided. The comprehensive energy system develops, converts, stores and uses different energy sources to meet the requirements of a user side. The concept of 'internet +' proposed in China clearly indicates that the core task of constructing the energy internet is to realize the coupling between different energy sources, an energy hub is an important component in a comprehensive energy system, the cascade utilization of the energy sources can be realized, the energy utilization rate is improved, clean energy is fully consumed, and stable energy supply is provided for users.
Disclosure of Invention
The invention aims to provide a source-load-storage considered cooling, heating and power comprehensive energy system and an optimized operation method thereof.
In order to solve the problems in the prior art, the invention adopts the following technical scheme:
a source-charge-storage considered cooling, heating and power comprehensive energy system comprises an input energy source, an energy hub and an output energy source, wherein the output energy source comprises electric energy, cold energy and heat energy; the input energy comprises a power grid, wind energy, solar energy and natural gas; the energy hub comprises WT, PV, a gas turbine, CHP, an auxiliary boiler, a waste heat boiler, an electric refrigerator, AC, an electricity storage device, a cold accumulation device and a heat accumulation device; the method is characterized in that: the energy hub further comprises P2G and P2H; the P2G is connected with a power transmission main road through an electric wire, and is connected with a natural gas pipeline after natural gas is generated; and the P2H is connected with the power transmission main pipeline through a power transmission line, and then transmits heat energy to the heat transmission main pipeline through the heat pipe to be supplied to users for use.
An optimized operation method of a source-charge-storage considered cooling, heating and power integrated energy system comprises the following steps:
the method comprises the following steps: the electricity, gas and heat in the energy hub are coupled and converted into electricity, cold and heat for users to use, and the linear mathematical expression of the energy hub is as follows:
Lm＝CmnPn
assuming that there are n input energy sources and m output energy sources in the energy hub, the matrix form can be expressed as:
Figure BDA0003276014290000021
wherein: l ismRepresenting the m-th energy source output; pnThe nth energy source is input; cmnIs a coupling matrix, wherein the elements represent the coupling factors for converting the nth input energy source into the mth output energy source;
step two: modeling devices in an energy hub;
step three: establishing an objective function and a constraint condition for optimizing the operation of the source-load-storage integrated cooling, heating and power energy system;
step IV: and solving the objective function, namely firstly converting inequality constraints into equality constraints, and then solving by using an improved branch-and-bound method to obtain the optimal solution of the objective function.
Further, the step (II) comprises the following steps:
(1) establishing a mathematical model for the wind turbine generator:
Figure BDA0003276014290000031
wherein: pfs、PfeRespectively representing the output power and rated power of the fan, wherein the unit of the output power and the rated power is KW; vts、Vfe、Vqi、VqoRespectively representing the actual wind speed, the rated wind speed, the cut-in wind speed and the cut-out wind speed at the time t, wherein the units of the actual wind speed, the rated wind speed, the cut-in wind speed and the cut-out wind speed are m/s;
(2) establishing a mathematical model for the photovoltaic generator set:
Figure BDA0003276014290000032
in the formula: pPhotovoltaic systemThe output of the photovoltaic generator set is expressed in KW; pmaxThe maximum output of the photovoltaic generator set is represented; sR、SmaxRepresenting the actual solar radiation intensity and the maximum solar radiation intensity, respectively; lPhotovoltaic systemThe power factor of the photovoltaic generator set is shown; t isstThe actual temperature of the surface of the photovoltaic generator set is represented; t isaThe ambient temperature around the photovoltaic generator set is expressed in units of ℃;
(3) establishing a mathematical model for the gas unit:
let the total volume of the natural gas fed be V and the volume of the natural gas distributed to the gas turbine be V1Volume of natural gas distributed to the CHP unit is V2Volume of natural gas distributed to auxiliary boiler is V3(ii) a Namely:
V＝V1+V2+V3
1) the mathematical model of gas turbine power generation and heat is as follows:
Pmt,g＝KVV1Δt
Figure BDA0003276014290000033
the mathematical model of the heat production of the waste heat boiler is as follows: prb,h＝(1-α4)Pmt,h；
In the formula: KV represents the heating value of natural gas, where 10KWh/m is taken3；V1Natural gas consumed by the gas turbine at a time Δ t; pmt,gRepresenting the natural gas power consumed by the gas turbine; pmt,e、Pmt,hThe electric power and the thermal power output by the gas turbine are shown;
Figure BDA0003276014290000043
representing the efficiency of the gas turbine converting electricity and heat; prb,hRepresenting the input thermal power of the waste heat boiler; alpha is alpha4The heat loss factor of the heat from the gas turbine to the waste heat boiler is shown;
2) the mathematical model of electricity and heat generation of the CHP unit by burning natural gas is as follows:
Pchp,g＝KVV2Δt
Figure BDA0003276014290000041
in the formula: pchp,e、Pchp,h、Pchp,gRespectively representing the electric power output by the CHP, the thermal power and the consumed natural gas power;
Figure BDA0003276014290000044
representing the efficiency of CHP conversion to electricity and heat; v2Represents the volume of natural gas consumed by the CHP over time Δ t;
3) mathematical model of P2H: pp2h,h＝(1-α8)Pp2h,e
Mathematical model of electric refrigerator: pec,c＝(1-α9)Pec,e
Mathematical model of absorption chiller: pac,c＝(1-α10)Pac,h
In the formula: pp2h,h、Pp2h,eRepresenting the output thermal power and the input electrical power of P2H; pec,c、Pec,eThe output cold power and the input electric power of the electric refrigerator are shown; pac,c、Pac,hIs shown asThe output cold power and the input heat power of the absorption refrigerator; alpha is alpha8、α9、α10Respectively representing the electrical loss factor input to P2H, the electrical loss factor input to the electrical chiller, and the thermal loss factor input to the absorption chiller;
(4) the mathematical model of the energy storage device is as follows:
Figure BDA0003276014290000042
in the formula: ek(t+1)、Ek(t) the energy of the energy storage equipment at the t +1 moment and the t moment is expressed in KW.h; lkIs the loss factor of the energy storage device; gamma rayk, charge、γk, placingRepresenting the efficiency of charging and discharging the energy storage device; ek, charge、Ek, placingThe unit of charging energy and discharging energy of the energy storage equipment is KW; k represents electricity, cold and heat.
Further, the objective function established in the third step is as follows:
the total cost Cmin is taken as an objective function and mainly comprises an operation cost COperation ofEquipment cost CDeviceCarbon emission cost C due to natural gas consumptionCarbon (C)Maintenance cost of the apparatus CMaintenanceCost of electricity and gas purchase of the system CShopping device(ii) a The mathematical expression is as follows:
C＝Coperation of+CDevice+CCarbon (C)+CMaintenance+CShopping device
Figure BDA0003276014290000051
Figure BDA0003276014290000052
Figure BDA0003276014290000053
Figure BDA0003276014290000054
Figure BDA0003276014290000056
In the formula: g represents the g-th device; g represents the total number of devices in the system; n represents the number of the g-th device; l isgRepresents the unit load of the g-th device; cgRepresenting the running cost of each g-th device under unit load; cgbRepresenting a purchase price of the g-th device; a represents the annual investment rate of the equipment; b represents the service life of the equipment; mcsAnd McaRepresents actual carbon emissions and average carbon emissions; p represents carbon remediation cost per unit volume; k is a radical ofg[Pg(t)]Representing a maintenance factor for the g-th device; pg(t) represents the output power of the g-th device; Δ t represents a time span;
Figure BDA0003276014290000057
and
Figure BDA0003276014290000058
representing the power purchasing and the unit price of power purchasing;
Figure BDA0003276014290000059
and
Figure BDA00032760142900000510
indicating the gas purchase volume and the gas purchase unit price.
Furthermore, the constraint conditions established in the third step comprise power balance constraint, equipment output constraint and energy storage equipment capacity constraint;
the power balance constraint model is as follows:
Figure BDA0003276014290000055
Figure BDA0003276014290000061
Figure BDA0003276014290000062
in the formula: el、Hl、ClRepresenting the electrical, thermal and cold loads supplied by the integrated energy system to the customer; eg、Hg、CgRepresents electricity, heat and cold provided by the g-th equipment in the integrated energy system; eElectric networkRepresenting the electrical energy delivered by the grid to the integrated energy system.
The equipment output constraint model is as follows:
Pg,min≤Pg≤Pg,max
in the formula: pgRepresenting the output condition of the g type equipment; pg,min、Pg,maxThe minimum output force and the maximum output force of the g-th device are shown.
The energy storage equipment capacity constraint model is as follows:
Sk，min≤Sk≤Sk，max
in the formula: skRepresenting charging and discharging of the kth energy source; sk,min、Sk,maxThe minimum capacity and the maximum capacity of the charge and discharge performance are shown.
Further, the step (iv) of solving by using an improved branch-and-bound method includes the following steps:
s1: inputting an objective function and equipment parameters;
s2: introducing a plurality of fitting factors, and converting inequality constraints into equality constraints; the mathematical model is represented as follows:
Figure BDA0003276014290000063
wherein: biIs a fitting factor;
s3: decomposing the target function into a plurality of sub-functions, and eliminating the sub-functions without the optimal solution by utilizing depth-first search;
s4: solving feasible solutions of the residual sub-functions, if the feasible solutions are not the solutions of the objective function, the objective function has no optimal solution, and the function is rejected; otherwise, executing the fifth step;
s5: continuously solving the optimal solution of the function, if the optimal solution is the solution of the objective function, the solution is the optimal solution of the objective function, and the solving process is finished; otherwise, returning to the step (sixthly);
s6: taking a subfunction of the optimal solution as a new upper bound of the objective function, taking a minimum feasible solution subfunction of feasible solutions as a new lower bound of the objective function, if the lower bound of the optimal solution of the remaining subfunctions is larger than the upper bound, the objective function has no solution, and rejecting the subfunction; otherwise, selecting the minimum objective function of the optimal solution to continue executing from the step (c).
The invention has the advantages that:
the source-charge-storage considered cooling, heating and power comprehensive energy system uses the P2G and P2H devices, realizes electricity-to-gas and electricity-to-heat, can improve the consumption of wind power and photoelectricity, can reduce the emission of carbon, improves the operation efficiency of the system, reduces the operation cost and realizes environment-friendly operation. The solving method of the objective function of the invention is to convert inequality constraint into equality constraint and then solve by using an improved branch-and-bound method to obtain the optimal solution of the objective function. The algorithm can reduce the iteration times and improve the calculation efficiency. The comprehensive energy system can improve the consumption of wind power and photoelectricity, realizes the mutual matching of source, load and storage, reduces the carbon emission of the system, reduces the operation cost of the system, enables the operation of the system to be more flexible, and realizes the economic operation and the environment-friendly operation of the system.
Drawings
FIG. 1 is a structural diagram of a source-charge-storage considered cooling, heating and power integrated energy system of the present invention;
FIG. 2 is a schematic diagram of P2G;
FIG. 3 is a flow chart of an improved branch-and-bound solution;
FIG. 4 is a comparison graph of wind power and photovoltaic power consumption of an integrated energy system not including P2G and including P2G;
FIG. 5 shows the output of the CHP and gas turbine without P2G and with P2G.
Detailed Description
The present invention is further described in detail with reference to the following specific examples, but the scope of the present invention is not limited by the specific examples, which are defined by the claims. In addition, any modification or change that can be easily made by a person having ordinary skill in the art without departing from the technical solution of the present invention will fall within the scope of the claims of the present invention.
As shown in fig. 1, the source-charge-storage considered cooling, heating and power integrated energy system of the present invention includes an input energy source, an energy hub and an output energy source, where the input energy source includes: electric power of a power grid, wind energy, solar energy and natural gas. The energy hub comprises: the system comprises a wind turbine WT, a photovoltaic generator set PV, an electricity-to-gas P2G, a gas turbine, a combined heat and power generation set CHP, an auxiliary boiler, a waste heat boiler, an electric heating P2H, an electric refrigerator, an absorption refrigerator AC, an electricity storage device, a cold storage device and a heat storage device. The output energy source comprises: electric energy, cold energy and heat energy. Wherein: the electric energy from the power grid is transmitted to users through the transformer by the transmission line. Wind energy drives the blades of the wind turbine, and the generated electric energy is transmitted to the main power transmission road through the power transmission line. The solar energy irradiates the solar cell panel to generate electric energy which is transmitted to the main power transmission road through the power transmission line. The P2G is connected with a power transmission main road through a wire, and is connected with a natural gas pipeline after natural gas is generated. The natural gas is conveyed to a gas boiler, a CHP (smoke and gas) and an auxiliary boiler through natural gas pipelines, electric energy generated by the gas boiler and the CHP is connected with a power transmission main pipeline through a power transmission line, a gas turbine is connected with a waste heat boiler through a high-temperature flue gas pipeline, and the waste heat boiler transmits heat energy to a heat transmission main pipeline through a heat pipe; the CHP and the auxiliary boiler transmit heat energy to a heat transmission main pipeline through a heat pipe; P2H is connected with the main power transmission line through the power transmission line, and then transmits the heat energy to the main heat transmission line through the heat pipe to be supplied to users. The electric refrigerator is connected with the power transmission main pipeline through the power transmission line, and then transmits cold energy to the cold transmission main pipeline through the cold pipe. The AC is connected with the hot transmission main pipeline, and then the cold energy is transmitted to the cold transmission main pipeline through the cold pipe to be supplied to users for use. The power storage equipment is provided with two power transmission lines which are connected with a power transmission main road, wherein one power transmission line is a charging line, and the other power transmission line is a discharging line. The cold accumulation device is provided with two pipelines which are connected with a cold conveying main pipeline, one is a cold accumulation pipeline, and the other is a cold conveying pipeline. The heat storage device is connected with the heat transmission main pipeline through two pipelines, one is a heat storage pipeline, and the other is a heat release pipeline.
As shown in fig. 2, the P2G plant converts electrical energy into natural gas for use by gas-fired plants. The P2H device converts electrical energy into thermal energy. The main purpose of using P2G and P2H is to improve wind power and photovoltaic consumption, and also to reduce economic cost and carbon emissions. P2G mainly comprises two steps of water electrolysis and methanation, and the chemical reaction is as follows:
water electrolysis process:
Figure BDA0003276014290000091
and (3) methanation process: 4H2+CO2→CH4↑+2H2O
The input energy sources in the source-load-storage considered cooling, heating and power integrated energy system comprise wind energy, solar energy, electric energy of a power grid and natural gas, and the electric load, the cooling load and the heating load of a user are met through coupling of various energy sources. The energy hub comprises the following devices: energy conversion equipment: the system comprises a wind turbine generator set, a photovoltaic generator set, a gas turbine, a CHP (steam turbine), an auxiliary boiler, P2G, P2H, a waste heat boiler, an electric refrigerator and an absorption refrigerator; the energy storage device comprises an electricity storage device, a cold storage device and a heat storage device.
The energy elements contained in the energy hub are shown in tables 1 and 2:
table 1. energy conversion device:
Figure BDA0003276014290000092
table 2. energy storage device:
Figure BDA0003276014290000093
Figure BDA0003276014290000101
the invention introduces a matrix F describing the characteristics of the energy transforming device, representing the characteristics of the energy transforming device, the number of rows of the matrix being equal to the total number of types of forms of energy present in the device, and the number of columns being equal to the total number of input and output ports. The characteristic matrix of the energy conversion device is shown in table 3:
TABLE 3. characteristic matrix table of energy conversion equipment
Figure BDA0003276014290000102
An optimized operation method of a source-charge-storage considered cooling, heating and power integrated energy system comprises the following steps:
the method comprises the following steps: the electricity, gas and heat in the energy hub are coupled and converted into electricity, cold and heat for users to use, and the linear mathematical expression of the energy hub is as follows:
Lm＝CmnPn
assuming that there are n input energy sources and m output energy sources in the energy hub, the matrix form can be expressed as:
Figure BDA0003276014290000111
wherein: l ismRepresenting the m-th energy source output; pnThe nth energy source is input; cmnThe coupling matrix is formed by elements which represent the coupling factors for converting the nth input energy source into the mth output energy source.
Step two: modeling each device in the energy hub; the system comprises a wind turbine generator set, a photovoltaic generator set, a gas turbine generator set and an energy storage system;
step three: establishing an objective function and a constraint condition for optimizing the operation of the source-load-storage integrated cooling, heating and power energy system;
step IV: and solving the objective function. And step three, the proposed target function is a mixed nonlinear programming function, firstly, the inequality constraint is converted into the equality constraint, and then, the improved branch-and-bound method is utilized to solve so as to obtain the optimal solution of the target function.
The step II comprises the following steps:
(1) establishing a mathematical model for the wind turbine generator:
the output power of the wind turbine is closely related to the cut-in wind speed and the cut-out wind speed, and the relationship between the output power and the cut-in wind speed can be represented by the following formula:
Figure BDA0003276014290000112
wherein: pfs、PfeRespectively representing the output power and rated power of the fan, wherein the unit of the output power and the rated power is KW; vts、Vfe、Vqi、VqoRespectively representing the actual wind speed, the rated wind speed, the cut-in wind speed and the cut-out wind speed at the time t, wherein the units of the actual wind speed, the rated wind speed, the cut-in wind speed and the cut-out wind speed are m/s;
(2) establishing a mathematical model for the photovoltaic generator set:
the photovoltaic generator set is related to the intensity of solar radiation, and the model can be expressed as:
Figure BDA0003276014290000121
in the formula: pPhotovoltaic systemThe output of the photovoltaic generator set is expressed in KW; pmaxThe maximum output of the photovoltaic generator set is represented; sR、SmaxRepresenting the actual solar radiation intensity and the maximum solar radiation intensity, respectively; lPhotovoltaic systemThe power factor of the photovoltaic generator set is shownA peptide; t isstThe actual temperature of the surface of the photovoltaic generator set is represented; t isaThe ambient temperature around the photovoltaic generator set is expressed in degrees c.
(3) Establishing a mathematical model for the gas unit:
let the total volume of the natural gas fed be V and the volume of the natural gas distributed to the gas turbine be V1Volume of natural gas distributed to the CHP unit is V2Volume of natural gas distributed to auxiliary boiler is V3. Namely:
V＝V1+V2+V3
1) establishing a mathematical model for the gas turbine:
the gas turbine can obtain electric energy by burning natural gas, and high-temperature flue gas generated by the gas turbine can obtain hot water and steam through the waste heat boiler to supply heat load for users. The mathematical model of gas turbine power generation and heat is as follows:
Pmt,g＝KVV1Δt
Figure BDA0003276014290000122
the mathematical model of the heat production of the waste heat boiler is as follows: prb,h＝(1-α4)Pmt,h；
In the formula: KV represents the heating value of natural gas, where 10KWh/m is taken3；V1Natural gas consumed by the gas turbine at a time Δ t; pmt,gRepresenting the natural gas power consumed by the gas turbine; pmt,e、Pmt,hThe electric power and the thermal power output by the gas turbine are shown;
Figure BDA0003276014290000123
representing the efficiency of the gas turbine converting electricity and heat; prb,hRepresenting the input thermal power of the waste heat boiler; alpha is alpha4The heat loss factor of the heat from the gas turbine to the waste heat boiler is shown.
2) Establishing a mathematical model for the CHP unit:
the CHP unit generates electricity and heat by burning natural gas, and the mathematical model is as follows:
Pchp,g＝KVV2Δt
Figure BDA0003276014290000131
in the formula: pchp,e、Pchp,h、Pchp,gRespectively representing the electric power output by the CHP, the thermal power and the consumed natural gas power;
Figure BDA0003276014290000133
representing the efficiency of CHP conversion to electricity and heat; v2Represents the volume of natural gas consumed by the CHP over time Δ t;
3) establishing a mathematical model for the refrigerating/heating equipment:
mathematical model of P2H: pp2h,h＝(1-α8)Pp2h,e
Mathematical model of electric refrigerator: pec,c＝(1-α9)Pec,e
Mathematical model of absorption chiller: pac,c＝(1-α10)Pac,h
In the formula: pp2h,h、Pp2h,eRepresenting the output thermal power and the input electrical power of P2H; pec,c、Pec,eThe output cold power and the input electric power of the electric refrigerator are shown; pac,c、Pac,hThe output cold power and the input heat power alpha of the absorption refrigerator are shown8、α9、α10Respectively representing the electrical loss factor input to P2H, the electrical loss factor input to the electrical chiller, and the thermal loss factor input to the absorption chiller;
(4) establishing a mathematical model for the energy storage equipment:
the energy storage equipment comprises electricity storage equipment, cold accumulation equipment and heat accumulation equipment, and the mathematical model of the energy storage equipment is as follows:
Figure BDA0003276014290000132
in the formula: ek(t+1)、Ek(t) the energy of the energy storage equipment at the t +1 moment and the t moment is expressed in KW.h; lkIs the loss factor of the energy storage device; gamma rayk, charge、γk, placingRepresenting the efficiency of charging and discharging the energy storage device; ek, charge、Ek, placingRepresenting the charging energy and the discharging energy of the energy storage device, and the unit of the charging energy and the discharging energy is KW; k may represent electricity, cold and heat.
The target function established in the third step is as follows:
the total cost Cmin is taken as an objective function and mainly comprises an operation cost COperation ofEquipment cost CDeviceCarbon emission cost C due to natural gas consumptionCarbon (C)Maintenance cost of the apparatus CMaintenanceCost of electricity and gas purchase of the system CShopping device. The mathematical expression is as follows:
C＝Coperation of+CDevice+CCarbon (C)+CMaintenance+CShopping device
Figure BDA0003276014290000141
Figure BDA0003276014290000142
Figure BDA0003276014290000143
Figure BDA0003276014290000144
Figure BDA0003276014290000146
In the formula: g represents the g-th device; g represents the equipment in the systemPreparing the total amount; n represents the number of the g-th device; l isgRepresents the unit load of the g-th device; cgRepresenting the running cost of each g-th device under unit load; cgbRepresenting a purchase price of the g-th device; a represents the annual investment rate of the equipment; b represents the service life of the equipment; mcsAnd McaRepresents actual carbon emissions and average carbon emissions; p represents carbon remediation cost per unit volume; k is a radical ofg[Pg(t)]Representing a maintenance factor for the g-th device; pg(t) represents the output power of the g-th device; Δ t represents a time span;
Figure BDA0003276014290000147
and
Figure BDA0003276014290000148
representing the power purchasing and the unit price of power purchasing;
Figure BDA0003276014290000149
and
Figure BDA00032760142900001410
indicating the gas purchase volume and the gas purchase unit price.
The constraint conditions established in the step three comprise power balance constraint, equipment output constraint and energy storage equipment capacity constraint;
the power balance constraint model is as follows:
Figure BDA0003276014290000145
Figure BDA0003276014290000151
Figure BDA0003276014290000152
in the formula: el、Hl、ClRepresents the comprehensive energyThe source system supplies the electrical, thermal and cold loads of the user; eg、Hg、CgRepresents electricity, heat and cold provided by the g-th equipment in the integrated energy system; eElectric networkRepresenting the electrical energy delivered by the grid to the integrated energy system.
The equipment output constraint model is as follows:
Pg,min≤Pg≤Pg,max
in the formula: pgRepresenting the output condition of the g type equipment; pg,min、Pg,maxThe minimum output force and the maximum output force of the g-th device are shown.
The energy storage equipment capacity constraint model is as follows:
Sk，min≤Sk≤Sk，max
in the formula: skRepresenting charging and discharging of the kth energy source; sk,min、Sk,maxThe minimum capacity and the maximum capacity of the charge and discharge performance are shown.
The step IV of solving by using an improved branch-and-bound method comprises the following steps:
s1: inputting an objective function and equipment parameters;
s2: introducing a plurality of fitting factors, and converting inequality constraints into equality constraints; the mathematical model is represented as follows:
Figure BDA0003276014290000153
wherein: biIs a fitting factor;
s3: decomposing the target function into a plurality of sub-functions, and eliminating the sub-functions without the optimal solution by utilizing depth-first search;
s4: solving feasible solutions of the residual sub-functions, if the feasible solutions are not the solutions of the objective function, the objective function has no optimal solution, and the function is rejected; otherwise, executing the fifth step;
s5: continuously solving the optimal solution of the function, if the optimal solution is the solution of the objective function, the solution is the optimal solution of the objective function, and the solving process is finished; otherwise, returning to the step (sixthly);
s6: taking a subfunction of the optimal solution as a new upper bound of the objective function, taking a minimum feasible solution subfunction of feasible solutions as a new lower bound of the objective function, if the lower bound of the optimal solution of the remaining subfunctions is larger than the upper bound, the objective function has no solution, and rejecting the subfunction; otherwise, selecting the minimum objective function of the optimal solution to continue executing from the step (c).
The invention relates to an optimized operation method of a source-load-storage considered cooling, heating and power comprehensive energy system, which comprises the following steps: the gas turbine and the CHP convert natural gas into electric energy by burning the natural gas, and when the electric load of a user cannot be met, the user needs to purchase electricity from a power grid to meet the requirement of the user. The heat energy generated by the CHP can be directly supplied to the heat load of the user, the heat energy generated by the gas turbine can be converted by the waste heat boiler to provide hot water for the user, when the heat energy is not sufficiently provided for the user, the auxiliary boiler can compensate the heat supply deficiency by burning natural gas, or the P2H converts the electric energy into heat energy to provide the user. In summer, the absorption refrigerator converts part of heat energy into cold energy to supply to users, and when the cold supply is insufficient, the electric refrigerator converts the electric energy into the cold energy to supply to the cold loads of the users. Because wind energy and solar energy power generation are greatly influenced by weather, the grid connection of wind power and photoelectric power is considered preferentially, and the P2G can convert electric energy into natural gas to be used by a gas turbine set. The invention can improve the consumption of wind power and photoelectricity, realizes the mutual matching of source-load-storage, reduces the carbon emission of the system, reduces the operation cost of the system, enables the operation of the system to be more flexible, and realizes the economic operation and the environment-friendly operation of the system.
On the basis of two scenes of operation proposed in the operation of a certain comprehensive energy system, the operation process of the comprehensive energy system is optimized by the method.
Scene 1: an integrated energy system that does not include P2G;
scene 2: an integrated energy system comprising P2G.
The curves of WT1 and PV1 in FIG. 4 represent the wind power and photovoltaic consumption in the integrated energy system without P2G, and the curves of WT2 and PV2 represent the wind power and photovoltaic consumption in the integrated energy system with P2G. In fig. 5, CHP1 and GT1 curves show the output of CHP and gas turbine in the integrated energy system without P2G, and CHP2 and GT2 curves show the output of CHP and gas turbine in the integrated energy system with P2G.
As is evident from the graph in fig. 4, the wind power and photovoltaic absorption capacity of the integrated energy system comprising P2G is higher than that of the integrated energy system not comprising P2G. As is evident from the graph in fig. 5, the CHP and gas turbine of the integrated power system including P2G have higher energy utilization, higher output and more stable operation than the integrated power system not including P2G.
While the preferred embodiments of the present invention have been illustrated and described, it will be appreciated by those skilled in the art that various modifications and additions may be made to the specific embodiments described and illustrated, and such modifications and additions are intended to be covered by the scope of the present invention.

Claims (6)

1. A source-charge-storage considered cooling, heating and power comprehensive energy system is characterized in that: the energy source system comprises an input energy source, an energy source hub and an output energy source, wherein the output energy source comprises electric energy, cold energy and heat energy; the input energy comprises a power grid, wind energy, solar energy and natural gas; the energy hub comprises WT, PV, a gas turbine, CHP, an auxiliary boiler, a waste heat boiler, an electric refrigerator, AC, an electricity storage device, a cold accumulation device and a heat accumulation device; the method is characterized in that: the energy hub further comprises P2G and P2H; the P2G is connected with a power transmission main road through an electric wire, and is connected with a natural gas pipeline after natural gas is generated; and the P2H is connected with the power transmission main pipeline through a power transmission line, and then transmits heat energy to the heat transmission main pipeline through the heat pipe to be supplied to users for use.
2. The method for optimizing the operation of an energy system according to claim 1, characterized by comprising the steps of:
the method comprises the following steps: the electricity, gas and heat in the energy hub are coupled and converted into electricity, cold and heat for users to use, and the linear mathematical expression of the energy hub is as follows:
Lm＝CmnPn
assuming that there are n input energy sources and m output energy sources in the energy hub, the matrix form can be expressed as:
Figure FDA0003276014280000011
wherein: l ismRepresenting the m-th energy source output; pnThe nth energy source is input; cmnIs a coupling matrix, wherein the elements represent the coupling factors for converting the nth input energy source into the mth output energy source;
step two: modeling devices in an energy hub;
step three: establishing an objective function and a constraint condition for optimizing the operation of the source-load-storage integrated cooling, heating and power energy system;
step IV: and solving the objective function, namely firstly converting inequality constraints into equality constraints, and then solving by using an improved branch-and-bound method to obtain the optimal solution of the objective function.
3. The method for optimizing an operation of an energy system according to claim 2, wherein the step (ii) comprises the steps of:
(1) establishing a mathematical model for the wind turbine generator:
Figure FDA0003276014280000021
wherein: pfs、PfeRespectively representing the output power and rated power of the fan, wherein the unit of the output power and the rated power is KW; vts、Vfe、Vqi、VqoRespectively representing the actual wind speed, the rated wind speed, the cut-in wind speed and the cut-out wind speed at the time t, wherein the units of the actual wind speed, the rated wind speed, the cut-in wind speed and the cut-out wind speed are m/s;
(2) establishing a mathematical model for the photovoltaic generator set:
Figure FDA0003276014280000022
in the formula: pPhotovoltaic systemThe output of the photovoltaic generator set is expressed in KW; pmaxThe maximum output of the photovoltaic generator set is represented; sR、SmaxRepresenting the actual solar radiation intensity and the maximum solar radiation intensity, respectively; lPhotovoltaic systemThe power factor of the photovoltaic generator set is shown; t isstThe actual temperature of the surface of the photovoltaic generator set is represented; t isaThe ambient temperature around the photovoltaic generator set is expressed in units of ℃;
(3) establishing a mathematical model for the gas unit:
let the total volume of the natural gas fed be V and the volume of the natural gas distributed to the gas turbine be V1Volume of natural gas distributed to the CHP unit is V2Volume of natural gas distributed to auxiliary boiler is V3(ii) a Namely:
V＝V1+V2+V3
1) the mathematical model of gas turbine power generation and heat is as follows:
Pmt,g＝KVV1Δt
Figure FDA0003276014280000031
the mathematical model of the heat production of the waste heat boiler is as follows: prb,h＝(1-α4)Pmt,h；
In the formula: KV represents the heating value of natural gas, where 10KWh/m is taken3；V1Natural gas consumed by the gas turbine at a time Δ t; pmt,gRepresenting the natural gas power consumed by the gas turbine; pmt,e、Pmt,hThe electric power and the thermal power output by the gas turbine are shown;
Figure FDA0003276014280000032
representing the efficiency of the gas turbine converting electricity and heat; prb,hRepresenting the input thermal power of the waste heat boiler; alpha is alpha4The heat loss factor of the heat from the gas turbine to the waste heat boiler is shown;
2) the mathematical model of electricity and heat generation of the CHP unit by burning natural gas is as follows:
Pchp,g＝KVV2Δt
Figure FDA0003276014280000033
in the formula: pchp,e、Pchp,h、Pchp,gRespectively representing the electric power output by the CHP, the thermal power and the consumed natural gas power;
Figure FDA0003276014280000034
representing the efficiency of CHP conversion to electricity and heat; v2Represents the volume of natural gas consumed by the CHP over time Δ t;
3) mathematical model of P2H: pp2h,h＝(1-α8)Pp2h,e
Mathematical model of electric refrigerator: pec,c＝(1-α9)Pec,e
Mathematical model of absorption chiller: pac,c＝(1-α10)Pac,h
In the formula: pp2h,h、Pp2h,eRepresenting the output thermal power and the input electrical power of P2H; pec,c、Pec,eThe output cold power and the input electric power of the electric refrigerator are shown; pac,c、Pac,hThe output cold power and the input heat power of the absorption refrigerator are shown; alpha is alpha8、α9、α10Respectively representing the electrical loss factor input to P2H, the electrical loss factor input to the electrical chiller, and the thermal loss factor input to the absorption chiller;
(4) the mathematical model of the energy storage device is as follows:
Figure FDA0003276014280000035
in the formula: ek(t+1)、Ek(t) the energy of the energy storage equipment at the t +1 moment and the t moment is expressed in KW.h; lkIs the loss factor of the energy storage device; gamma rayk, charge、γk, placingRepresenting the efficiency of charging and discharging the energy storage device; ek, charge、Ek, placingThe unit of charging energy and discharging energy of the energy storage equipment is KW; k represents electricity, cold and heat.
4. The method according to claim 2, wherein the objective function established in step (c) is as follows:
the total cost Cmin is taken as an objective function and mainly comprises an operation cost COperation ofEquipment cost CDeviceCarbon emission cost C due to natural gas consumptionCarbon (C)Maintenance cost of the apparatus CMaintenanceCost of electricity and gas purchase of the system CShopping device(ii) a The mathematical expression is as follows:
C＝Coperation of+CDevice+CCarbon (C)+CMaintenance+CShopping device
Figure FDA0003276014280000041
Figure FDA0003276014280000042
Figure FDA0003276014280000043
Figure FDA0003276014280000044
Figure FDA0003276014280000045
In the formula: g represents the g-th device; g represents the total number of devices in the system; n represents the number of the g-th device; l isgRepresents the unit load of the g-th device; cgRepresenting the running cost of each g-th device under unit load; cgbRepresenting a purchase price of the g-th device; a represents the annual investment rate of the equipment; b represents the service life of the equipment; mcsAnd McaRepresents actual carbon emissions and average carbon emissions; p represents carbon remediation cost per unit volume; k is a radical ofg[Pg(t)]Representing a maintenance factor for the g-th device; pg(t) represents the output power of the g-th device; Δ t represents a time span;
Figure FDA0003276014280000046
and
Figure FDA0003276014280000047
representing the power purchasing and the unit price of power purchasing;
Figure FDA0003276014280000048
and
Figure FDA0003276014280000049
indicating the gas purchase volume and the gas purchase unit price.
5. The method according to claim 2, wherein the constraints established in step (iii) include power balance constraints, equipment output constraints, and energy storage equipment capacity constraints;
the power balance constraint model is as follows:
Figure FDA0003276014280000051
Figure FDA0003276014280000052
Figure FDA0003276014280000053
in the formula: el、Hl、ClRepresenting the electrical, thermal and cold loads supplied by the integrated energy system to the customer; eg、Hg、CgRepresents electricity, heat and cold provided by the g-th equipment in the integrated energy system; eElectric networkRepresenting the electric energy transmitted by the power grid to the comprehensive energy system;
the equipment output constraint model is as follows:
Pg,min≤Pg≤Pg,max
in the formula: pgRepresenting the output condition of the g type equipment; pg,min、Pg,maxRepresenting the minimum output force and the maximum output force of the g type equipment;
the energy storage equipment capacity constraint model is as follows:
Sk，min≤Sk≤Sk，max
in the formula: skRepresenting charging and discharging of the kth energy source; sk,min、Sk,maxThe minimum capacity and the maximum capacity of the charge and discharge performance are shown.
6. The method for optimizing the operation of the energy system according to claim 2, wherein the step (iv) of solving using the improved branch-and-bound method comprises the steps of:
s1: inputting an objective function and equipment parameters;
s2: introducing a plurality of fitting factors, and converting inequality constraints into equality constraints; the mathematical model is represented as follows:
Figure FDA0003276014280000061
wherein: biIs a fitting factor;
s3: decomposing the target function into a plurality of sub-functions, and eliminating the sub-functions without the optimal solution by utilizing depth-first search;
s4: solving feasible solutions of the residual sub-functions, if the feasible solutions are not the solutions of the objective function, the objective function has no optimal solution, and the function is rejected; otherwise, executing the fifth step;
s5: continuously solving the optimal solution of the function, if the optimal solution is the solution of the objective function, the solution is the optimal solution of the objective function, and the solving process is finished; otherwise, returning to the step (sixthly);
s6: taking a subfunction of the optimal solution as a new upper bound of the objective function, taking a minimum feasible solution subfunction of feasible solutions as a new lower bound of the objective function, if the lower bound of the optimal solution of the remaining subfunctions is larger than the upper bound, the objective function has no solution, and rejecting the subfunction; otherwise, selecting the minimum objective function of the optimal solution to continue executing from the step (c).
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114844124A (en) * 2022-06-20 2022-08-02 中国电力工程顾问集团中南电力设计院有限公司 Operation control method of comprehensive energy system based on target optimization
CN116771450A (en) * 2023-07-14 2023-09-19 华北电力大学 Multi-energy control system and control method based on supercritical CO2 generator set

Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106169108A (en) * 2016-07-14 2016-11-30 河海大学 Active distribution network short-term active optimization method containing battery energy storage system
CN108494015A (en) * 2018-02-09 2018-09-04 中国科学院电工研究所 The integrated energy system design method of one introduces a collection-lotus-storage coordination and interaction
CN108563882A (en) * 2018-04-20 2018-09-21 浙江大学 A kind of on piece clock domain control sequence design method of noise perception
CN109390979A (en) * 2018-10-24 2019-02-26 云南电网有限责任公司电力科学研究院 A kind of optimal control method of integrated energy system
CN110322051A (en) * 2019-06-06 2019-10-11 国网浙江省电力有限公司经济技术研究院 Consider the integrated energy system Optimal Configuration Method of N-1 security constraint
US20190372391A1 (en) * 2018-06-01 2019-12-05 Siemens Industry, Inc. Methods and apparatus incorporating topology error estimation for management of an electric power system
CN110555595A (en) * 2019-08-09 2019-12-10 四川大学 biogas-wind-light all-renewable energy system based on energy hub and method thereof
CN110991764A (en) * 2019-12-16 2020-04-10 贵州电网有限责任公司 Day-ahead rolling optimization method for comprehensive energy system
CN111047097A (en) * 2019-12-16 2020-04-21 贵州电网有限责任公司 Day-to-day rolling optimization method for comprehensive energy system
CN111523213A (en) * 2020-04-15 2020-08-11 南京清然能源科技有限公司 Artificial intelligence-based optimized energy supply method for electricity core type comprehensive energy system
CN112966869A (en) * 2021-03-15 2021-06-15 中国电力科学研究院有限公司 Optimal scheduling method and system for park comprehensive energy system
CN113378409A (en) * 2021-07-06 2021-09-10 国网江苏省电力有限公司营销服务中心 Comprehensive energy system multi-energy complementary optimization scheduling method and system

Patent Citations (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106169108A (en) * 2016-07-14 2016-11-30 河海大学 Active distribution network short-term active optimization method containing battery energy storage system
CN108494015A (en) * 2018-02-09 2018-09-04 中国科学院电工研究所 The integrated energy system design method of one introduces a collection-lotus-storage coordination and interaction
CN108563882A (en) * 2018-04-20 2018-09-21 浙江大学 A kind of on piece clock domain control sequence design method of noise perception
US20190372391A1 (en) * 2018-06-01 2019-12-05 Siemens Industry, Inc. Methods and apparatus incorporating topology error estimation for management of an electric power system
CN109390979A (en) * 2018-10-24 2019-02-26 云南电网有限责任公司电力科学研究院 A kind of optimal control method of integrated energy system
CN110322051A (en) * 2019-06-06 2019-10-11 国网浙江省电力有限公司经济技术研究院 Consider the integrated energy system Optimal Configuration Method of N-1 security constraint
CN110555595A (en) * 2019-08-09 2019-12-10 四川大学 biogas-wind-light all-renewable energy system based on energy hub and method thereof
CN110991764A (en) * 2019-12-16 2020-04-10 贵州电网有限责任公司 Day-ahead rolling optimization method for comprehensive energy system
CN111047097A (en) * 2019-12-16 2020-04-21 贵州电网有限责任公司 Day-to-day rolling optimization method for comprehensive energy system
CN111523213A (en) * 2020-04-15 2020-08-11 南京清然能源科技有限公司 Artificial intelligence-based optimized energy supply method for electricity core type comprehensive energy system
CN112966869A (en) * 2021-03-15 2021-06-15 中国电力科学研究院有限公司 Optimal scheduling method and system for park comprehensive energy system
CN113378409A (en) * 2021-07-06 2021-09-10 国网江苏省电力有限公司营销服务中心 Comprehensive energy system multi-energy complementary optimization scheduling method and system

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
LI Z, ZHAO Y, XU J AND SHAO Q: "Research on Optimal Energy Flow Calculation of an Electro-Thermal Coupled System via an Interior-Point Approach", FRONT. ENERGY RES, pages 1 - 12 *
王江江;王壮;杨颖;武静;: "分布式冷热电联供系统集成设计与优化研究进展", 分布式能源, pages 1 - 10 *
赵哲林: "基于双层规划和多目标差分算法的经济环保调度研究", 中国优秀硕士学位论文全文数据库 工程科技Ⅰ辑, pages 027 - 335 *
魏文;王杰;: "支界法与内点法相结合的微网优化规划方法研究", 机电信息, pages 92 - 93 *

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114844124A (en) * 2022-06-20 2022-08-02 中国电力工程顾问集团中南电力设计院有限公司 Operation control method of comprehensive energy system based on target optimization
CN114844124B (en) * 2022-06-20 2024-04-19 中国电力工程顾问集团中南电力设计院有限公司 Operation control method of comprehensive energy system based on target optimization
CN116771450A (en) * 2023-07-14 2023-09-19 华北电力大学 Multi-energy control system and control method based on supercritical CO2 generator set
CN116771450B (en) * 2023-07-14 2024-01-23 华北电力大学 Multi-energy control system based on supercritical CO2 generator set

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Application publication date: 20211217

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Denomination of invention: A comprehensive energy system for cooling, heating, and power considering source load storage and its optimized operation method

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