CN114818269A - Industrial park comprehensive energy system and factory production plan collaborative optimization method - Google Patents

Industrial park comprehensive energy system and factory production plan collaborative optimization method Download PDF

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CN114818269A
CN114818269A CN202210294463.8A CN202210294463A CN114818269A CN 114818269 A CN114818269 A CN 114818269A CN 202210294463 A CN202210294463 A CN 202210294463A CN 114818269 A CN114818269 A CN 114818269A
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马锴
乔东东
杨婕
郭士亮
刘阳
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Abstract

The invention discloses a method for collaborative optimization of an industrial park comprehensive energy system and a factory production plan, which aims at the structures of the industrial park comprehensive energy system and industrial users, and establishes a comprehensive energy system hydrogen preparation model, a carbon dioxide recycling and storage model and a production raw material storage area model on the basis of the original energy supply, conversion and storage equipment model; constructing a multi-energy coupling model and a factory production constraint model of different workshop energy consumption of an industrial user; the method comprises the steps of constructing a collaborative optimization model of the operation of the comprehensive energy system and industrial users in the park by taking the operation efficiency of all devices of the comprehensive energy system in the park, a multi-energy coupling model of different workshops of the industrial users and a factory production flow as constraint conditions and taking the total energy consumption cost of one day of the industrial park as an objective function; and solving the collaborative optimization model to obtain the output plan of each device of the park integrated energy system and the production scheduling arrangement of the factory, thereby reducing the total daily operation energy consumption cost of the park integrated energy system and industrial users.

Description

Industrial park comprehensive energy system and factory production plan collaborative optimization method
Technical Field
The invention relates to the technical field of energy configuration optimization, in particular to a collaborative optimization method for an industrial park comprehensive energy system and a factory production plan.
Background
With the increasing demand for various energy sources such as electricity, natural gas, heat supply, refrigeration and the like, modern power systems are developing towards comprehensive energy systems. Integrated energy systems are considered an effective model to reduce fossil fuel usage, reduce energy costs, and improve the efficiency and flexibility of traditional energy systems. The energy input comprises natural gas and electric power, and the output type can simultaneously comprise various energy sources such as electric power, heat supply, refrigeration, natural gas and the like. Industrial loads require a large amount of electrical, thermal and cold energy, and thus play an important role in end users; however, the traditional factory operation mode lacks of management and optimization of multiple energy sources, and the economic benefit and the energy efficiency of an enterprise are seriously influenced; therefore, there is a need to develop energy consumption optimization strategies for industrial park integrated energy systems and industrial users.
With increasing concern for environmental issues, much research effort has taken carbon emissions into account in integrated energy systems and various frameworks have been proposed to optimize the operation of integrated energy systems in parks to reduce energy costs; in addition, in demand response, management and optimization of industrial loads are widely used to improve economic efficiency and energy efficiency. However, the research on the energy conversion of the park integrated energy system and the production plan of the factory user for collaborative optimization scheduling is few; and the recycling of the carbon dioxide of the park comprehensive energy system and the coupling relation among different energy sources consumed by factory production are not considered, and the daily production task of an industrial user is not considered to carry out demand response, so that the user participation is seriously influenced.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a method for the collaborative optimization of the industrial park comprehensive energy system and the factory production plan, so that the total daily operation energy consumption cost of the industrial user and the comprehensive energy system in the park is reduced, the comprehensive energy utilization rate is improved, and the carbon emission is reduced.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows: a method for collaborative optimization of an industrial park comprehensive energy system and a factory production plan comprises the following steps:
step S1, aiming at the structures of the comprehensive energy system and the industrial users in the industrial park, on the basis of the original energy supply, conversion and storage equipment model, a hydrogen preparation model, a carbon dioxide recycling and storage model and a production raw material storage area model of the comprehensive energy system are established;
step S2, the park integrated energy management center receives the production tasks, the workshop energy consumption types and the production constraints of the industrial users, and a multi-energy coupling model and a factory production constraint model of different workshop energy consumptions of the industrial users are constructed;
step S3, the park integrated energy management center integrates the received industrial user information, the equipment information of the integrated energy system, the price and the power information of the external air network and the power grid, and under the premise of finishing the daily production task of the factory, the operation efficiency of all the equipment of the integrated energy system in the park, the multi-energy coupling model of different workshops of the industrial user and the factory production flow are taken as constraint conditions, the total daily energy consumption cost of the industrial park is taken as a target function, and a collaborative optimization model of the operation of the integrated energy system and the industrial user is constructed;
step S4, the park integrated energy management center solves the collaborative optimization model of the integrated energy system and the industrial user operation to obtain the output plan of each device and the factory production scheduling arrangement of the park integrated energy system;
and step S5, the park integrated energy management center controls the operation of the integrated energy system according to the solving result, and sends the obtained result to the factory user to enable the factory user to engage in the production activities according to the corresponding arrangement.
The technical scheme of the invention is further improved as follows: the energy supply equipment model in the step S1 comprises a natural gas network, a power grid, a photovoltaic generator set and a solar water heater; the energy conversion equipment model comprises a gas boiler, a gas turbine, a P2G unit, an absorption refrigerator and an electric refrigerator; the storage device model of energy includes an electrical energy storage device; the comprehensive energy system hydrogen production model comprises an electrolytic water unit; the carbon dioxide recycling and storing model comprises carbon dioxide capturing equipment; the production raw material storage area model comprises an initial raw material warehouse, a workshop 1 intermediate product storage warehouse, a workshop 2 intermediate product storage warehouse and a workshop z intermediate product storage warehouse.
The technical scheme of the invention is further improved as follows: the model of the P2G unit and the electrolyzed water unit is as follows:
Figure BDA0003561376830000031
in the above formula:
Figure BDA0003561376830000032
representing the rate at which the electric gas conversion unit produces natural gas; δ represents a proportionality coefficient between the rate of hydrogen consumption and the rate of natural gas production;
Figure BDA0003561376830000033
representing the rate at which hydrogen is produced by the electrolysis cell of water;
Figure BDA0003561376830000034
in the above formula:
Figure BDA0003561376830000035
representing the rate at which carbon dioxide is consumed by the electrical conversion unit; λ represents the proportionality coefficient between the rate of hydrogen consumption and the rate of carbon dioxide consumption for natural gas production;
Figure BDA0003561376830000036
in the above formula:
Figure BDA0003561376830000037
power representing electrical energy consumed by the electrical conversion unit;
Figure BDA0003561376830000038
representing a conversion factor between a rate of hydrogen consumption and power consumption;
Figure BDA0003561376830000039
in the above formula:
Figure BDA00035613768300000310
represents the maximum power of the electric energy consumed by the electric gas conversion unit;
Figure BDA00035613768300000311
in the above formula:
Figure BDA00035613768300000312
representing the rate of oxygen production from the electrolytic cell; τ represents a proportionality coefficient between the rate of hydrogen production and the rate of oxygen production;
Figure BDA00035613768300000313
in the above formula:
Figure BDA00035613768300000314
representing the rate at which the electric gas conversion unit produces natural gas; θ represents a coefficient for converting the production rate of natural gas into natural gas power.
The technical scheme of the invention is further improved as follows: the carbon dioxide recycling and storing model of the integrated energy system in the step S1 is as follows:
Figure BDA0003561376830000041
in the above formula:
Figure BDA0003561376830000042
representing the rate of capture of carbon dioxide produced by the cogeneration unit and the gas boiler;
Figure BDA0003561376830000043
indicating the rate of carbon dioxide being discharged into the air due to capture technology limitations; ρ represents a conversion coefficient;
Figure BDA0003561376830000044
representing the heat production power of the gas boiler;
Figure BDA0003561376830000045
representing the heat production efficiency of the gas boiler;
Figure BDA0003561376830000046
respectively representing the power generation and heat production of the cogeneration unit;
Figure BDA0003561376830000047
respectively representing the electricity generation efficiency and the heat generation efficiency of the cogeneration unit;
Figure BDA0003561376830000048
in the above formula:
Figure BDA0003561376830000049
represents the rate at which the recovered carbon dioxide is used for consumption by the P2G unit;
Figure BDA00035613768300000410
indicating the rate of storage to the carbon dioxide tank.
The technical scheme of the invention is further improved as follows: the carbon dioxide storage model of the integrated energy system in the step S1 is as follows:
Figure BDA00035613768300000411
in the above formula: CO 2 2s,t Represents the carbon dioxide storage amount;
Figure BDA00035613768300000412
representing an initial storage amount of carbon dioxide;
Figure BDA00035613768300000413
represents the carbon dioxide sales rate;
Figure BDA00035613768300000414
the above formula shows that the carbon dioxide storage amount is kept unchanged at the beginning and end of carbon dioxide;
0≤CO 2s,t ≤CO 2s,max ，
in the above formula: CO 2 2s,max Represents a maximum storage capacity of carbon dioxide;
Figure BDA00035613768300000415
in the above formula:
Figure BDA00035613768300000416
indicating the maximum storage rate of carbon dioxide.
The technical scheme of the invention is further improved as follows: the types of the energy consumption of the workshop in the step S2 comprise a pure electric energy workshop, a pure cold energy workshop, a pure heat energy workshop, an electric-heat coupling workshop, an electric-cold coupling workshop and a hot-cold coupling workshop.
The technical scheme of the invention is further improved as follows: in step S2, the multi-energy coupling model of the energy consumption of different workshops of the industrial user is:
Figure BDA0003561376830000051
in the above formula: p E,t Represents the total power consumed by the plant; z represents a shop mark; e' represents a set of pure electric energy consumption workshops; x is a binary system and represents the running state of the workshop, and the workshop works when 1 is taken out, otherwise the workshop does not work; p E,z Represents the electric power consumed by the z plant; EH' represents a hot spot coupled plant set;
Figure BDA0003561376830000052
represents the electric power consumed by the electro-thermal coupling plant z; EC' represents an electric cold coupling workshop set;
Figure BDA0003561376830000053
represents the electric power consumed by the electric cold coupling workshop z;
Figure BDA0003561376830000054
in the above formula: p H,t Representing the total power of the plant consuming thermal energy; h' represents a set of pure thermal energy consumption plants; p H,z Represents the thermal power consumed by the z plant;
Figure BDA0003561376830000055
represents the total thermal power consumed by the electro-thermal coupling workshop; HC' represents a set of hot and cold coupled plants;
Figure BDA0003561376830000056
represents the thermal power consumed by the hot-cold coupling workshop z;
Figure BDA0003561376830000057
in the above formula: p C,t Represents the total power of the plant consuming cooling energy; c' represents a pure cold energy consumption workshop set;
Figure BDA0003561376830000058
representing the total cold power consumed by the electric cold coupling workshop;
Figure BDA0003561376830000059
representing the total cold power consumed by the hot-cold coupling workshop;
wherein:
Figure BDA00035613768300000510
Figure BDA00035613768300000511
Figure BDA0003561376830000061
in the above formula:
Figure BDA0003561376830000062
representing the z workshop electrical thermal coupling coefficient;
Figure BDA0003561376830000063
representing the z workshop electric cold coupling coefficient;
Figure BDA0003561376830000064
represents the z workshop heat-cold coupling coefficient.
The technical scheme of the invention is further improved as follows: the production constraints in the step S2 include the production sequence, the production speed, the operation state of different workshops, and the initial number and the remaining capacity of the storage warehouses;
P (EHC),z representing various coupling energy consumption powers of a workshop z; υ ═ υ 1 …υ Z Indicates the production rates of the different plants;
Figure BDA0003561376830000065
an initial storage amount of intermediate products representing the plant z;
Figure BDA0003561376830000066
representing a plant z intermediate product storage capacity;
specifically, the intermediate product storage warehouse model:
Figure BDA0003561376830000067
in the above formula:
Figure BDA0003561376830000068
representing the number of intermediate product stores in shop z;
Figure BDA0003561376830000069
representing the initial storage amount of the intermediate products in the workshop z; upsilon is z,t Representing the processing rate of the workshop z at different moments;
Figure BDA00035613768300000610
the above expression shows that the storage capacity of the intermediate product is kept unchanged at the beginning and the end;
Figure BDA00035613768300000611
in the above formula:
Figure BDA00035613768300000612
representing the maximum storage capacity of the intermediate product in the workshop z;
υ z,t ＝x z,t ·υ z ，
in the above formula: upsilon is z Representing the plant z processing rate.
The technical scheme of the invention is further improved as follows: the specific process of step S3 is as follows:
on the premise of finishing daily production tasks of a factory, taking total energy consumption cost of one day in an industrial park as a target function, specifically comprising electricity purchasing cost to a power grid, gas purchasing cost to a natural gas station, carbon dioxide emission cost, income of carbon dioxide sale capture and income of oxygen sale as a byproduct of hydrogen production by electrolyzing water;
specifically, the objective function expression of the total energy consumption cost of the industrial park in one day is as follows:
Figure BDA00035613768300000720
in the above formula: c total Represents the total energy consumption cost of one day of the industrial park; c t Represents the total cost of energy consumption at a certain time in one day of the industrial park;
wherein:
Figure BDA0003561376830000071
in the above formula:
Figure BDA0003561376830000072
representing the power purchased by the power grid; p is a radical of E,t Representing the electricity purchase price of the power grid;
Figure BDA0003561376830000073
representing the gas purchasing power of the natural gas station; p is a radical of g,t Representing the gas purchase price of the natural gas station;
Figure BDA0003561376830000074
represents the carbon dioxide emission rate;
Figure BDA0003561376830000075
represents a carbon dioxide emission price;
Figure BDA0003561376830000076
represents a carbon dioxide purchase rate;
Figure BDA0003561376830000077
represents a carbon dioxide purchase price;
Figure BDA0003561376830000078
representing the rate of oxygen production from the electrolysis of water to produce hydrogen;
Figure BDA0003561376830000079
represents the price for oxygen sale;
Figure BDA00035613768300000710
represents the rate at which carbon dioxide is sold;
Figure BDA00035613768300000711
represents the price for selling carbon dioxide;
the constraint conditions include: the method comprises the following steps of electric heating and cooling power balance constraint, power grid and gas grid interaction power constraint, operation constraint of each energy device, energy storage constraint and factory production constraint;
the relation expression among electricity, heat and cold produced by the comprehensive energy system is as follows:
Figure BDA00035613768300000712
in the above formula:
Figure BDA00035613768300000713
representing the power of electricity, heat and cold provided by the park comprehensive energy system;
Figure BDA00035613768300000714
Figure BDA00035613768300000715
represents the charge and discharge power of the storage battery;
Figure BDA00035613768300000716
representing the photovoltaic power generation;
Figure BDA00035613768300000717
representing the electricity converted into the electricity consumption power;
Figure BDA00035613768300000718
indicating electricityGas conversion and gas production power;
Figure BDA00035613768300000719
the heat production power of the solar water heater is represented;
wherein:
Figure BDA0003561376830000081
in the above formula: ω represents a percentage;
Figure BDA0003561376830000082
representing the heat production efficiency and the electricity production efficiency of the cogeneration unit;
Figure BDA0003561376830000083
representing gas boiler efficiency; COP EC Representing the conversion coefficient of the electric refrigerator; COP AC Representing the conversion coefficient of the absorption refrigerator;
specifically, the balance constraints of the comprehensive energy system and the electricity, heat and cold powers of the industrial users in the park are as follows:
Figure BDA0003561376830000084
Figure BDA0003561376830000085
Figure BDA0003561376830000086
specifically, the power grid and gas grid interaction power constraint is as follows:
Figure BDA0003561376830000087
Figure BDA0003561376830000088
in the above formula:
Figure BDA0003561376830000089
the maximum power of the power grid and the gas grid is represented.
Due to the adoption of the technical scheme, the invention has the technical progress that:
the invention provides a method for collaborative optimization of an industrial park comprehensive energy system and a factory production plan, which aims at the structures of the industrial park comprehensive energy system and industrial users, and establishes a comprehensive energy system hydrogen preparation model, a carbon dioxide recycling and storage model and a production raw material storage area model on the basis of the original energy supply, conversion and storage equipment model; constructing a multi-energy coupling model and a factory production constraint model of different workshop energy consumption of an industrial user; on the premise of finishing daily production tasks of a factory, constructing a collaborative optimization model of the operation of the comprehensive energy system and industrial users in the park by taking the operation efficiency of all devices of the comprehensive energy system in the park, a multi-energy coupling model of different workshops of the industrial users and the production flow of the factory as constraint conditions and taking the total energy consumption cost of one day of the industrial park as an objective function; and solving the established collaborative optimization model to obtain the output plan of each device of the park integrated energy system and the production scheduling arrangement of the factory, so that the total daily operation energy consumption cost of the park integrated energy system and industrial users can be reduced, the energy integrated utilization rate is improved, and the carbon emission is reduced.
Drawings
FIG. 1 is a block diagram of the collaborative optimization steps for operation of an integrated energy system and industrial users on a campus in accordance with the present invention;
FIG. 2 is a system block diagram of a collaborative optimization model of the operation of the integrated energy system and the industrial users on the campus in accordance with the present invention;
figure 3 is a schematic diagram of the production of the various plants of the plant of the present invention on a campus.
Detailed Description
The present invention will be described in further detail with reference to the following examples:
as shown in fig. 1, a method for collaborative optimization of an industrial park integrated energy system and a factory production plan includes the following steps:
and step S1, aiming at the structures of the comprehensive energy system and the industrial users in the industrial park, establishing a hydrogen preparation model, a carbon dioxide recycling and storing model and a production raw material storage area model of the comprehensive energy system on the basis of the original energy supply, conversion and storage equipment models. As shown in fig. 2, the relation between the supply and demand of the electric energy, the heat energy and the cold energy produced by the park integrated energy system and the consumption of the electric energy, the heat energy and the cold energy in different workshops of the factory is described, and the optimization of the park integrated energy system and the production scheduling arrangement of the factory are realized through the cooperative optimization between the supply and demand, so that the total daily production energy consumption cost of the park integrated energy system and the factory is reduced; the supply equipment model of the energy of the comprehensive energy system comprises a natural gas network, a power grid, a photovoltaic generator set and a solar water heater; the energy conversion equipment model comprises a gas boiler, a gas turbine, a P2G unit, an absorption refrigerator and an electric refrigerator; the storage device model of energy includes an electrical energy storage device; the comprehensive energy system hydrogen production model comprises an electrolytic water unit; the carbon dioxide recycling and storing model comprises carbon dioxide capturing equipment; the factory is provided with N production workshops, and the production raw material storage area model comprises an initial raw material warehouse, a workshop 1 intermediate product storage warehouse, a workshop 2 intermediate product storage warehouse and a workshop z intermediate product storage warehouse.
The model of the P2G cell and the electrolyzed water cell is as follows:
Figure BDA0003561376830000101
in the above formula:
Figure BDA0003561376830000102
representing the rate at which the electric gas conversion unit produces natural gas; δ represents a proportionality coefficient between the rate of hydrogen consumption and the rate of natural gas production;
Figure BDA0003561376830000103
representing the rate at which hydrogen is produced by the electrolysis cell of water;
Figure BDA0003561376830000104
in the above formula:
Figure BDA0003561376830000105
representing the rate at which carbon dioxide is consumed by the electrical conversion unit; λ represents the proportionality coefficient between the rate of hydrogen consumption and the rate of carbon dioxide consumption for natural gas production;
Figure BDA0003561376830000106
in the above formula:
Figure BDA0003561376830000107
power representing electrical energy consumed by the electrical conversion unit;
Figure BDA0003561376830000108
representing a conversion factor between a rate of hydrogen consumption and power consumption;
Figure BDA0003561376830000109
in the above formula:
Figure BDA00035613768300001010
represents the maximum power of the electric energy consumed by the electric gas conversion unit;
Figure BDA00035613768300001011
in the above formula:
Figure BDA00035613768300001012
representing the rate of oxygen production from the electrolytic cell; τ represents the rate of hydrogen production and oxygen productionA proportionality coefficient between rates of;
Figure BDA00035613768300001013
in the above formula:
Figure BDA00035613768300001014
representing the rate at which the electric gas conversion unit produces natural gas; θ represents a coefficient for converting the production rate of natural gas into natural gas power.
The comprehensive energy system carbon dioxide recycling model comprises the following steps:
Figure BDA00035613768300001015
in the above formula:
Figure BDA00035613768300001016
representing the rate of capture of carbon dioxide produced by the cogeneration unit and the gas boiler;
Figure BDA0003561376830000111
indicating the rate of carbon dioxide being discharged into the air due to capture technology limitations; ρ represents a conversion coefficient;
Figure BDA0003561376830000112
representing the heat production power of the gas boiler;
Figure BDA0003561376830000113
representing the heat production efficiency of the gas boiler;
Figure BDA0003561376830000114
respectively representing the power generation and heat production of the cogeneration unit;
Figure BDA0003561376830000115
respectively representing the electricity generation efficiency and the heat generation efficiency of the cogeneration unit;
Figure BDA0003561376830000116
in the above formula:
Figure BDA0003561376830000117
represents the rate at which the recovered carbon dioxide is used for consumption by the P2G unit;
Figure BDA0003561376830000118
indicating the rate of storage to the carbon dioxide tank.
The carbon dioxide storage model of the comprehensive energy system is as follows:
Figure BDA0003561376830000119
in the above formula: CO 2 2s,t Represents the carbon dioxide storage amount;
Figure BDA00035613768300001110
representing an initial storage amount of carbon dioxide;
Figure BDA00035613768300001111
represents the carbon dioxide sales rate;
Figure BDA00035613768300001112
the above formula shows that the carbon dioxide storage amount is kept unchanged at the beginning and end of carbon dioxide;
0≤CO 2s,t ≤CO 2s,max ，
in the above formula: CO 2 2s,max Represents a maximum storage capacity of carbon dioxide;
Figure BDA00035613768300001113
in the above formula:
Figure BDA00035613768300001114
indicating the maximum storage rate of carbon dioxide.
And S2, the park comprehensive energy management center receives the production tasks, the workshop energy consumption types and the production constraints of the industrial users, and a multi-energy coupling model and a factory production constraint model of different workshop energy consumptions of the industrial users are constructed, wherein the workshop energy consumption types comprise a pure electric energy workshop, a pure cold energy workshop, a pure heat energy workshop, an electric-heat coupling workshop, an electric-cold coupling workshop and a hot-cold coupling workshop. The multi-energy coupling model of the energy consumption of different workshops of the industrial user is as follows:
Figure BDA0003561376830000121
in the above formula: p E,t Represents the total power consumed by the plant; z represents a shop mark; e' represents a set of pure electric energy consumption plants; x is a binary system and represents the running state of a workshop, and the workshop works when 1 is taken out, otherwise the workshop does not work; p E,z Represents the electric power consumed by the z plant; EH' represents a hot spot coupled plant set;
Figure BDA0003561376830000122
represents the electric power consumed by the electro-thermal coupling plant z; EC' represents an electric cold coupling workshop set;
Figure BDA0003561376830000123
represents the electric power consumed by the electric cold coupling workshop z;
Figure BDA0003561376830000124
in the above formula: p H,t Representing the total power of the plant consuming thermal energy; h' represents a set of pure thermal energy consumption plants; p H,z Represents the thermal power consumed by the z plant;
Figure BDA0003561376830000125
represents the total thermal power consumed by the electro-thermal coupling workshop; HC' represents a set of hot and cold coupled plants;
Figure BDA0003561376830000126
represents the thermal power consumed by the hot-cold coupling workshop z;
Figure BDA0003561376830000127
in the above formula: p C,t Represents the total power of the plant consuming cooling energy; c' represents a pure cold energy consumption workshop set;
Figure BDA0003561376830000128
representing the total cold power consumed by the electric cold coupling workshop;
Figure BDA0003561376830000129
representing the total cold power consumed by the hot-cold coupling workshop;
wherein:
Figure BDA00035613768300001210
Figure BDA00035613768300001211
Figure BDA00035613768300001212
in the above formula:
Figure BDA00035613768300001213
representing the z workshop electrical thermal coupling coefficient;
Figure BDA00035613768300001214
representing the z workshop electric cold coupling coefficient;
Figure BDA00035613768300001215
represents the z workshop heat-cold coupling coefficient.
The production constraints comprise the production sequence, the production speed and the running state of different workshops, and the initial number and the residual capacity of the storage warehouses;
as shown in FIG. 3, P (EHC),z Representing various coupling energy consumption powers of a workshop z; υ ═ υ 1 …υ Z Indicates the production rates of the different plants;
Figure BDA0003561376830000131
an initial storage amount of intermediate products representing the plant z;
Figure BDA0003561376830000138
representing a plant z intermediate product storage capacity;
specifically, the intermediate product storage warehouse model:
Figure BDA0003561376830000132
in the above formula:
Figure BDA0003561376830000133
representing the number of intermediate product stores in shop z;
Figure BDA0003561376830000134
representing the initial storage amount of the intermediate products in the workshop z; upsilon is z,t Representing the processing rate of the workshop z at different moments;
Figure BDA0003561376830000135
the above expression shows that the storage capacity of the intermediate product is kept unchanged at the beginning and the end;
Figure BDA0003561376830000136
in the above formula:
Figure BDA0003561376830000137
representing the maximum storage capacity of the intermediate product in the workshop z;
υ z,t ＝x z,t ·υ z ，
in the above formula: upsilon is z Representing the plant z processing rate.
Step S3, the park integrated energy management center integrates the received industrial user information, the equipment information of the integrated energy system, the price and the power information of the external air network and the power grid, and under the premise of finishing the daily production task of the factory, the operation efficiency of all the equipment of the integrated energy system in the park, the multi-energy coupling model of different workshops of the industrial user and the factory production flow are taken as constraint conditions, the total daily energy consumption cost of the industrial park is taken as a target function, and a collaborative optimization model of the operation of the integrated energy system and the industrial user is constructed; the specific process is as follows:
on the premise of finishing daily production tasks of a factory, taking total energy consumption cost of one day in an industrial park as a target function, specifically comprising electricity purchasing cost to a power grid, gas purchasing cost to a natural gas station, carbon dioxide emission cost, income of carbon dioxide sale capture and income of oxygen sale as a byproduct of hydrogen production by electrolyzing water;
specifically, the objective function expression of the total energy consumption cost of the industrial park in one day is as follows:
Figure BDA0003561376830000141
in the above formula: c total Represents the total energy consumption cost of one day of the industrial park; c t The total energy consumption cost at a certain time in one day of the industrial park is represented;
wherein:
Figure BDA0003561376830000142
in the above formula:
Figure BDA0003561376830000143
representing the power purchased by the power grid; p is a radical of E,t Representing the electricity purchase price of the power grid;
Figure BDA0003561376830000144
representing the gas purchasing power of the natural gas station; p is a radical of g,t Representing the gas purchase price of the natural gas station;
Figure BDA0003561376830000145
represents the carbon dioxide emission rate;
Figure BDA0003561376830000146
represents a carbon dioxide emission price;
Figure BDA0003561376830000147
representing a carbon dioxide purchase rate;
Figure BDA0003561376830000148
represents a carbon dioxide purchase price;
Figure BDA0003561376830000149
representing the rate of oxygen production from the electrolysis of water to produce hydrogen;
Figure BDA00035613768300001410
represents the price for oxygen sale;
Figure BDA00035613768300001411
represents the rate at which carbon dioxide is sold;
Figure BDA00035613768300001412
represents the price for selling carbon dioxide;
the constraint conditions include: the method comprises the following steps of electric heating and cooling power balance constraint, power grid and gas grid interaction power constraint, operation constraint of each energy device, energy storage constraint and factory production constraint;
the relation expression among the electricity, heat and cold produced by the comprehensive energy system is as follows:
Figure BDA00035613768300001413
in the above formula:
Figure BDA00035613768300001414
representing the power of electricity, heat and cold provided by the park comprehensive energy system;
Figure BDA00035613768300001415
Figure BDA00035613768300001416
represents the charge and discharge power of the storage battery;
Figure BDA00035613768300001417
representing the photovoltaic power generation;
Figure BDA00035613768300001418
representing electricity to gas consumption power;
Figure BDA0003561376830000151
the power of the electricity-to-gas production is shown;
Figure BDA0003561376830000152
the heat production power of the solar water heater is represented;
wherein:
Figure BDA0003561376830000153
in the above formula: ω represents a percentage;
Figure BDA0003561376830000154
representing the heat production efficiency and the electricity production efficiency of the cogeneration unit;
Figure BDA0003561376830000155
representing gas boiler efficiency; COP EC Representing the conversion coefficient of the electric refrigerator; COP AC Representing the conversion coefficient of the absorption refrigerator;
specifically, the balance constraints of the comprehensive energy system and the electricity, heat and cold powers of the industrial users in the park are as follows:
Figure BDA0003561376830000156
Figure BDA0003561376830000157
Figure BDA0003561376830000158
specifically, the power grid and gas grid interaction power constraint is as follows:
Figure BDA0003561376830000159
Figure BDA00035613768300001510
in the above formula:
Figure BDA00035613768300001511
the maximum power of the power grid and the gas grid is represented.
Step S4, the park integrated energy management center solves the collaborative optimization model of the integrated energy system and the industrial user operation to obtain the output plan of each device and the factory production scheduling arrangement of the park integrated energy system;
and step S5, the park integrated energy management center controls the operation of the integrated energy system according to the solving result, and sends the obtained result to the factory user to enable the factory user to engage in the production activities according to the corresponding arrangement.
The invention provides a method for collaborative optimization of an industrial park comprehensive energy system and a factory production plan, which aims at the structures of the industrial park comprehensive energy system and industrial users, and establishes a comprehensive energy system hydrogen preparation model, a carbon dioxide recycling and storage model and a production raw material storage area model on the basis of the original energy supply, conversion and storage equipment model; constructing a multi-energy coupling model and a factory production constraint model of different workshop energy consumption of an industrial user; on the premise of finishing daily production tasks of a factory, constructing a collaborative optimization model of the operation of the comprehensive energy system and industrial users in the park by taking the operation efficiency of all devices of the comprehensive energy system in the park, a multi-energy coupling model of different workshops of the industrial users and the production flow of the factory as constraint conditions and taking the total energy consumption cost of one day of the industrial park as an objective function; and solving the established collaborative optimization model to obtain the output plan of each device of the park integrated energy system and the production scheduling arrangement of the factory, so that the total daily operation energy consumption cost of the park integrated energy system and industrial users can be reduced, the energy integrated utilization rate is improved, and the carbon emission is reduced.

Claims (9)

1. A method for collaborative optimization of an industrial park comprehensive energy system and a factory production plan is characterized by comprising the following steps: the method comprises the following steps:
step S1, aiming at the structures of the comprehensive energy system and the industrial users in the industrial park, on the basis of the original energy supply, conversion and storage equipment model, a hydrogen preparation model, a carbon dioxide recycling and storage model and a production raw material storage area model of the comprehensive energy system are established;
step S2, the park integrated energy management center receives the production tasks, the workshop energy consumption types and the production constraints of the industrial users, and a multi-energy coupling model and a factory production constraint model of different workshop energy consumptions of the industrial users are constructed;
step S3, the park integrated energy management center integrates the received industrial user information, the equipment information of the integrated energy system, the price and the power information of the external air network and the power grid, and under the premise of finishing the daily production task of the factory, the operation efficiency of all the equipment of the integrated energy system in the park, the multi-energy coupling model of different workshops of the industrial user and the factory production flow are taken as constraint conditions, the total daily energy consumption cost of the industrial park is taken as a target function, and a collaborative optimization model of the operation of the integrated energy system and the industrial user is constructed;
step S4, the park integrated energy management center solves the collaborative optimization model of the integrated energy system and the industrial user operation to obtain the output plan of each device and the factory production scheduling arrangement of the park integrated energy system;
and step S5, the park integrated energy management center controls the operation of the integrated energy system according to the solving result, and sends the obtained result to the factory user to enable the factory user to engage in the production activities according to the corresponding arrangement.
2. The method of claim 1 for collaborative optimization of an industrial park integrated energy system and a factory production plan, wherein the method comprises the following steps: the energy supply equipment model in the step S1 comprises a natural gas network, a power grid, a photovoltaic generator set and a solar water heater; the energy conversion equipment model comprises a gas boiler, a gas turbine, a P2G unit, an absorption refrigerator and an electric refrigerator; the storage device model of energy includes an electrical energy storage device; the comprehensive energy system hydrogen production model comprises an electrolytic water unit; the carbon dioxide recycling and storing model comprises carbon dioxide capturing equipment; the production raw material storage area model comprises an initial raw material warehouse, a workshop 1 intermediate product storage warehouse, a workshop 2 intermediate product storage warehouse and a workshop z intermediate product storage warehouse.
3. The method of claim 2, wherein the method comprises the steps of: the model of the P2G unit and the electrolyzed water unit is as follows:
Figure FDA0003561376820000021
in the above formula:
Figure FDA0003561376820000022
representing the rate at which the electric gas conversion unit produces natural gas; δ represents a proportionality coefficient between the rate of hydrogen consumption and the rate of natural gas production;
Figure FDA0003561376820000023
indicating waterThe rate at which hydrogen is produced by the electrolyzer of (a);
Figure FDA0003561376820000024
in the above formula:
Figure FDA0003561376820000025
representing the rate at which carbon dioxide is consumed by the electrical conversion unit; λ represents the proportionality coefficient between the rate of hydrogen consumption and the rate of carbon dioxide consumption for natural gas production;
Figure FDA0003561376820000026
in the above formula:
Figure FDA0003561376820000027
power representing the electric energy consumed by the electric gas conversion unit;
Figure FDA0003561376820000028
representing a conversion factor between a rate of hydrogen consumption and power consumption;
Figure FDA0003561376820000029
in the above formula:
Figure FDA00035613768200000210
represents the maximum power of the electric energy consumed by the electric gas conversion unit;
Figure FDA00035613768200000211
in the above formula:
Figure FDA00035613768200000212
representing the rate of oxygen production from the electrolytic cell; τ represents a proportionality coefficient between the rate of hydrogen production and the rate of oxygen production;
Figure FDA00035613768200000213
in the above formula:
Figure FDA00035613768200000214
representing the rate at which the electric gas conversion unit produces natural gas; θ represents a coefficient for converting the production rate of natural gas into natural gas power.
4. The method of claim 3, wherein the method comprises: the carbon dioxide recycling model of the integrated energy system in the step S1 is as follows:
Figure FDA0003561376820000031
in the above formula:
Figure FDA0003561376820000032
representing the rate of capture of carbon dioxide produced by the cogeneration unit and the gas boiler;
Figure FDA0003561376820000033
indicating the rate of carbon dioxide being discharged into the air due to capture technology limitations; ρ represents a conversion coefficient;
Figure FDA0003561376820000034
representing the heat production power of the gas boiler;
Figure FDA0003561376820000035
representing the heat production efficiency of the gas boiler;
Figure FDA0003561376820000036
respectively representing the power generation and heat production of the cogeneration unit;
Figure FDA0003561376820000037
respectively representing the electricity generation efficiency and the heat generation efficiency of the cogeneration unit;
Figure FDA0003561376820000038
in the above formula:
Figure FDA0003561376820000039
represents the rate at which the recovered carbon dioxide is consumed for the P2G unit;
Figure FDA00035613768200000310
indicating the rate of storage to the carbon dioxide tank.
5. The method of claim 4 for collaborative optimization of an industrial park energy system and a factory production plan, wherein the method comprises the following steps: the carbon dioxide storage model of the integrated energy system in the step S1 is as follows:
Figure FDA00035613768200000311
in the above formula: CO 2 2s,t Represents the carbon dioxide storage amount;
Figure FDA00035613768200000312
representing an initial storage amount of carbon dioxide;
Figure FDA00035613768200000313
represents the carbon dioxide sales rate;
Figure FDA00035613768200000314
the above formula shows that the carbon dioxide storage amount is kept unchanged at the beginning and end of carbon dioxide;
0≤CO 2s,t ≤CO 2s,max ，
in the above formula: CO 2 2s,max Represents a maximum storage capacity of carbon dioxide;
Figure FDA00035613768200000315
in the above formula:
Figure FDA00035613768200000316
indicating the maximum storage rate of carbon dioxide.
6. The method of claim 5 for collaborative optimization of an industrial park energy system and a factory production plan, wherein the method comprises the following steps: the types of the energy consumption of the workshop in the step S2 comprise a pure electric energy workshop, a pure cold energy workshop, a pure heat energy workshop, an electric-heat coupling workshop, an electric-cold coupling workshop and a hot-cold coupling workshop.
7. The method of claim 6, wherein the method comprises: in step S2, the multi-energy coupling model of the energy consumption of different workshops of the industrial user is:
Figure FDA0003561376820000041
in the above formula: p E,t Represents the total power consumed by the plant; z represents a shop mark; e' represents a set of pure electric energy consumption workshops; x is a binary system and represents the running state of the workshop, and the workshop works when 1 is taken out, otherwise the workshop does not work; p E,z Represents the electric power consumed by the z plant; EH' represents a hot spot coupled plant set;
Figure FDA0003561376820000042
represents the electric power consumed by the electro-thermal coupling plant z; EC' represents an electric cold coupling workshop set;
Figure FDA0003561376820000043
represents the electric power consumed by the electric cold coupling workshop z;
Figure FDA0003561376820000044
in the above formula: p is H,t Representing the total power of the plant consuming thermal energy; h' represents a set of pure thermal energy consumption plants; p H,z Represents the thermal power consumed by the z plant;
Figure FDA0003561376820000045
represents the total thermal power consumed by the electro-thermal coupling plant; HC' represents a set of hot and cold coupled plants;
Figure FDA0003561376820000046
represents the thermal power consumed by the hot-cold coupling workshop z;
Figure FDA0003561376820000047
in the above formula: p C,t Represents the total power of the plant consuming cooling energy; c' represents a pure cold energy consumption workshop set;
Figure FDA0003561376820000048
representing the total cold power consumed by the electric cold coupling workshop;
Figure FDA0003561376820000049
representing the total cold power consumed by the hot-cold coupling workshop;
wherein:
Figure FDA00035613768200000410
Figure FDA0003561376820000051
Figure FDA0003561376820000052
in the above formula:
Figure FDA0003561376820000053
representing the z workshop electrical thermal coupling coefficient;
Figure FDA0003561376820000054
representing the z workshop electric cold coupling coefficient;
Figure FDA0003561376820000055
represents the z workshop heat-cold coupling coefficient.
8. The method of claim 7, wherein the method comprises: the production constraints in the step S2 include the production sequence, the production speed, the operation state of different workshops, and the initial number and the remaining capacity of the storage warehouses;
P (EHC),z representing various coupling energy consumption powers of a workshop z; υ ═ υ 1 …υ Z Indicates the production rates of the different plants;
Figure FDA0003561376820000056
an initial storage amount of intermediate products representing the plant z;
Figure FDA0003561376820000057
representing a plant z intermediate product storage capacity;
specifically, the intermediate product storage warehouse model:
Figure FDA0003561376820000058
in the above formula:
Figure FDA0003561376820000059
representing the number of intermediate product stores in shop z;
Figure FDA00035613768200000510
representing the initial storage amount of the intermediate products in the workshop z; v is a cell z,t Representing the processing rate of the workshop z at different moments;
Figure FDA00035613768200000511
the above expression shows that the storage capacity of the intermediate product is kept unchanged at the beginning and the end;
Figure FDA00035613768200000512
in the above formula:
Figure FDA00035613768200000513
representing the maximum storage capacity of the intermediate product in the workshop z;
υ z,t ＝x z,t ·υ z ，
in the above formula: v is a cell z Representing the plant z processing rate.
9. The method of claim 8, wherein the method comprises: the specific process of step S3 is as follows:
on the premise of finishing daily production tasks of a factory, taking total energy consumption cost of one day in an industrial park as a target function, specifically comprising electricity purchasing cost to a power grid, gas purchasing cost to a natural gas station, carbon dioxide emission cost, income of carbon dioxide sale capture and income of oxygen sale as a byproduct of hydrogen production by electrolyzing water;
specifically, the objective function expression of the total energy consumption cost of the industrial park in one day is as follows:
Figure FDA0003561376820000061
in the above formula: c total Represents the total energy consumption cost of one day of the industrial park; c t Represents the total cost of energy consumption at a certain time in one day of the industrial park;
wherein:
Figure FDA0003561376820000062
in the above formula:
Figure FDA0003561376820000063
representing the power purchased by the power grid; p is a radical of E,t Representing the electricity purchase price of the power grid;
Figure FDA0003561376820000064
representing the gas purchasing power of the natural gas station; p is a radical of g,t Representing the gas purchase price of the natural gas station;
Figure FDA0003561376820000065
represents the carbon dioxide emission rate;
Figure FDA0003561376820000066
represents a carbon dioxide emission price;
Figure FDA0003561376820000067
represents a carbon dioxide purchase rate;
Figure FDA0003561376820000068
represents a carbon dioxide purchase price;
Figure FDA0003561376820000069
representing the rate of oxygen production from the electrolysis of water to produce hydrogen;
Figure FDA00035613768200000610
represents the price at which oxygen is sold;
Figure FDA00035613768200000611
represents the rate at which carbon dioxide is sold;
Figure FDA00035613768200000612
represents the price for selling carbon dioxide;
the constraint conditions include: the method comprises the following steps of electric heating and cooling power balance constraint, power grid and gas grid interaction power constraint, operation constraint of each energy device, energy storage constraint and factory production constraint;
the relation expression among the electricity, heat and cold produced by the comprehensive energy system is as follows:
Figure FDA00035613768200000613
in the above formula:
Figure FDA00035613768200000614
representing the power of electricity, heat and cold provided by the park comprehensive energy system;
Figure FDA00035613768200000615
Figure FDA0003561376820000071
represents the charge and discharge power of the storage battery;
Figure FDA0003561376820000072
representing photovoltaic productsElectrical power;
Figure FDA0003561376820000073
representing the electricity converted into the electricity consumption power;
Figure FDA0003561376820000074
representing the power of electricity-to-gas production;
Figure FDA0003561376820000075
the heat production power of the solar water heater is represented;
wherein:
Figure FDA0003561376820000076
in the above formula: ω represents a percentage;
Figure FDA0003561376820000077
representing the heat production efficiency and the electricity production efficiency of the cogeneration unit;
Figure FDA0003561376820000078
representing gas boiler efficiency; COP EC Representing the conversion coefficient of the electric refrigerator; COP (coefficient of Performance) AC Representing the conversion coefficient of the absorption refrigerator;
specifically, the balance constraints of the comprehensive energy system and the electricity, heat and cold powers of the industrial users in the park are as follows:
Figure FDA0003561376820000079
Figure FDA00035613768200000710
Figure FDA00035613768200000711
specifically, the power grid and gas grid interaction power constraint is as follows:
Figure FDA00035613768200000712
Figure FDA00035613768200000713
in the above formula:
Figure FDA00035613768200000714
the maximum power of the power grid and the gas grid is represented.
CN202210294463.8A 2022-03-23 2022-03-23 Industrial park comprehensive energy system and factory production plan collaborative optimization method Pending CN114818269A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117911055A (en) * 2024-03-19 2024-04-19 国网辽宁省电力有限公司技能培训中心 Carbon emission optimizing system based on regional comprehensive energy coupling characteristics

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117911055A (en) * 2024-03-19 2024-04-19 国网辽宁省电力有限公司技能培训中心 Carbon emission optimizing system based on regional comprehensive energy coupling characteristics

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