CN115186902A - Regulating and controlling method, device, terminal and storage medium of greenhouse comprehensive energy system - Google Patents

Regulating and controlling method, device, terminal and storage medium of greenhouse comprehensive energy system Download PDF

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CN115186902A
CN115186902A CN202210817689.1A CN202210817689A CN115186902A CN 115186902 A CN115186902 A CN 115186902A CN 202210817689 A CN202210817689 A CN 202210817689A CN 115186902 A CN115186902 A CN 115186902A
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energy system
greenhouse
model
cost
equipment
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杜旭浩
李秉宇
庞先海
曾四鸣
郭小凡
蔡子文
刘杰
赵俊蕾
李博
胡长斌
边子轩
张洪杰
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State Grid Corp of China SGCC
Electric Power Research Institute of State Grid Hebei Electric Power Co Ltd
State Grid Hebei Energy Technology Service Co Ltd
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State Grid Corp of China SGCC
Electric Power Research Institute of State Grid Hebei Electric Power Co Ltd
State Grid Hebei Energy Technology Service Co Ltd
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    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
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Abstract

The invention provides a regulation and control method, a regulation and control device, a terminal and a storage medium of a greenhouse comprehensive energy system. The method comprises the following steps: establishing an energy coupling model and an equipment constraint model of the greenhouse comprehensive energy system based on equipment parameters of various energy conversion equipment and various energy storage equipment; establishing a carbon transaction cost calculation model of the greenhouse integrated energy system based on the carbon emission quota of the greenhouse integrated energy system and the carbon emission parameters of the multiple energy conversion devices; establishing a target function based on demand side parameters of the greenhouse comprehensive energy system and an energy coupling model calculation model; and optimizing the operation parameters of the greenhouse comprehensive energy system based on the equipment constraint model and the objective function by taking the minimum operation cost and the minimum carbon transaction cost as optimization targets. The operation parameters of the greenhouse comprehensive energy system are optimized through the multi-objective mathematical model, and the optimized operation parameters can realize layered regulation and control of the greenhouse comprehensive energy system.

Description

Regulation and control method, device, terminal and storage medium of greenhouse comprehensive energy system
Technical Field
The invention relates to the technical field of energy system regulation, in particular to a regulation and control method, a regulation and control device, a terminal and a storage medium of a greenhouse comprehensive energy system.
Background
The energy supply of the current agricultural greenhouse in rural areas of China is mainly coal, the energy consumption structure is unreasonable, the energy utilization rate is low, and the carbon pollutant emission is high. Therefore, the construction of a green and efficient energy supply system has great significance, which is beneficial to the cooperative optimization among various energy sources, improves the limitation of the single energy supply form of the original energy system, and enhances the stability, high efficiency, energy conservation and environmental protection of the system.
However, most of the current researches on the regulation and control of energy systems are carried out from the aspects of industrial parks and rural industries, few researches on the operation of greenhouse-based multi-energy coupling systems are carried out, and no technology for carrying out layered regulation and control on greenhouse comprehensive energy systems is provided.
Disclosure of Invention
The embodiment of the invention provides an optimization method, device, terminal and storage medium of a greenhouse comprehensive energy system, and aims to solve the problem of hierarchical regulation and control of the greenhouse comprehensive energy system.
In a first aspect, an embodiment of the present invention provides a method for optimizing a greenhouse integrated energy system, where the greenhouse integrated energy system includes multiple energy conversion devices and multiple energy storage devices, and the method includes:
establishing an energy coupling model and an equipment constraint model of the greenhouse comprehensive energy system based on equipment parameters of various energy conversion equipment and various energy storage equipment;
establishing a carbon trading cost calculation model of the greenhouse comprehensive energy system based on the carbon emission quota of the greenhouse comprehensive energy system and the carbon emission parameters of various energy conversion devices;
establishing a target function based on demand side parameters of the greenhouse comprehensive energy system and an energy coupling model calculation model;
and optimizing the operation parameters of the greenhouse comprehensive energy system based on the equipment constraint model and the objective function by taking the minimum operation cost and the minimum carbon transaction cost as optimization targets, and regulating and controlling the greenhouse comprehensive energy system based on the operation parameters.
In one possible implementation mode, the greenhouse comprehensive energy system acquires electric energy through electricity purchase, gas-heat energy conversion is carried out through a gas boiler, and energy coupling is carried out through CCHP equipment;
establishing a carbon trading cost calculation model of the greenhouse integrated energy system based on the carbon emission quota of the greenhouse integrated energy system and the carbon emission parameters of various energy conversion devices, wherein the carbon trading cost calculation model comprises the following steps:
determining the emission quota of the free carbon of the greenhouse comprehensive energy system;
establishing a power purchase carbon emission calculation model based on the unit electric quantity carbon emission;
establishing a gas boiler carbon emission calculation model based on unit heat carbon emission;
establishing a CCHP carbon emission calculation model based on the unit heat carbon emission and the power generation-heat supply conversion coefficient of the CCHP equipment;
determining a carbon transaction cost calculation model of the greenhouse comprehensive energy system based on the uncompensated carbon emission quota, the electricity purchasing carbon emission calculation model, the gas boiler carbon emission calculation model and the CCHP carbon emission model;
in one possible implementation manner, the electricity purchasing carbon emission calculation model is as follows:
E h ＝δ p P buy
wherein E is h Represents the amount of carbon emission, delta, of electricity purchase p Represents the carbon emission per unit of electricity, P buy Indicating the electricity purchasing quantity;
the model for calculating the carbon emission of the gas boiler comprises the following steps:
E gb ＝δ h H gb (t)
wherein, E gb Represents the carbon emission of the gas boiler, delta h Represents the carbon emission per unit heat, H gb (t) heat production of the gas boiler;
the CCHP carbon emission calculation model is as follows:
Figure BDA0003741518110000021
wherein E is cchp Represents the carbon emission of the CCHP plant, delta h Represents the carbon emission per unit heat, Q eb (t) represents the heat supply of the electric boiler, Q hb (t) represents the heat supply amount of the exhaust-heat boiler, Q er (t) represents refrigerating capacity, Q, of the refrigerating machine of the electric refrigerator ac (t) represents the refrigerating capacity of the absorption refrigerating machine, P gt (t) represents the amount of power supplied to the gas turbine,
Figure BDA0003741518110000022
representing a power generation-heat supply conversion coefficient;
the carbon transaction cost calculation model is:
Figure BDA0003741518110000031
in the formula, C co2 Cost of carbon trading for greenhouse integrated energy systems, E ci The actual carbon emission of each device in the greenhouse comprehensive energy system, and c is the carbon trading price; λ represents the increase of the price per stepped carbon transaction, E pi Representing the total carbon emission of the electricity, gas boiler and CCHP equipment, h representing the length of the carbon emission interval, E ci And the carbon emission of a thermal power generating unit, a CCHP unit and a gas boiler is shown.
In one possible implementation, the establishing of the objective function based on the demand-side parameters of the greenhouse integrated energy system and the energy coupling model calculation model comprises:
constructing an electricity purchasing cost model based on the electricity purchasing price;
constructing a gas turbine power generation cost model based on the gas price;
constructing a fuel cost model of the gas boiler based on the efficiency coefficient of the gas boiler;
constructing an equipment operation and maintenance cost model based on the unit operation and maintenance cost of each equipment;
constructing an operation cost calculation model of the greenhouse comprehensive energy system based on the electricity purchasing cost model, the gas turbine power generation cost model, the gas boiler fuel cost model and the equipment operation maintenance cost model;
and respectively substituting the energy conversion relation in the demand side parameter and the energy coupling model into the operation cost calculation model and the carbon transaction cost calculation model to obtain the objective function.
In one possible implementation, the electricity purchase cost model is:
Figure BDA0003741518110000032
wherein, F 1 Indicating the cost of electricity purchase, P grid (t) represents the power purchased during time t, C system (t) represents the purchase price of electricity for a period of time t;
the gas turbine power generation cost model is as follows:
Figure BDA0003741518110000033
wherein, F 2 Representing the cost of power generation of the gas turbine, C gas (t) represents the gas price, η, over a period of time t Gr Representing the efficiency coefficient, P, of the gas turbine gt (t) represents the output electric power of the gas turbine, LHV, over a period of time t gas Indicating a low heating value of natural gas;
the fuel cost model of the gas boiler is as follows:
Figure BDA0003741518110000041
wherein, F 3 Representing the fuel cost of the gas boiler. C gas (t) gas price in time period t, H gb (t) represents the output thermal power of the gas boiler, η, over a time period t gb Representing an efficiency coefficient of the gas boiler;
the equipment operation and maintenance cost model is as follows:
Figure BDA0003741518110000042
wherein, F 4 Represents the cost of operating and maintaining the equipment, k i To representUnit operating maintenance cost, P, of the equipment i i (t) represents the input power at which device i operates during time period t;
the objective function is:
Figure BDA0003741518110000043
wherein F represents the operation economic cost of the greenhouse integrated energy system, and E represents the total emission of carbon-containing pollutant gases of the greenhouse integrated energy system.
In one possible implementation manner, the establishing an energy coupling model and an equipment constraint model of a greenhouse integrated energy system based on equipment parameters of a plurality of energy conversion equipment and a plurality of energy storage equipment includes:
establishing an energy coupling model of the greenhouse comprehensive energy system based on the conversion efficiency parameters of various energy conversion devices and the device parameters of various energy storage devices;
and establishing an equipment constraint model of the greenhouse comprehensive energy system based on the safe operation parameters of various energy conversion equipment and various energy storage equipment.
In one possible implementation, optimizing operating parameters of the greenhouse integrated energy system based on the plant constraint model and the objective function with the minimum operating cost and the minimum carbon trading cost as optimization objectives includes:
linearizing the target function to obtain a linear target function; the linear objective function is:
Figure BDA0003741518110000044
wherein Z represents a system multi-objective optimization expectation; f represents the optimal value of the operating economic cost of the greenhouse integrated energy system, omega 1 Weighting factor, ω, representing economic objective optimization 2 Weighting factor, omega, representing an optimization of an environmental objective 1 +ω 2 ＝ 1，(0≤ω 1 ≤1，0≤ω 2 ≤1)；
And optimizing the operation parameters of the greenhouse comprehensive energy system based on the equipment constraint model and the objective function by taking the minimum operation cost and the minimum carbon transaction cost as optimization targets to obtain the optimized operation parameters of the greenhouse comprehensive energy system.
In a second aspect, an embodiment of the present invention provides a control device for a greenhouse integrated energy system, including:
the model establishing module is used for establishing an energy coupling model and an equipment constraint model of the greenhouse comprehensive energy system based on equipment parameters of various energy conversion equipment and various energy storage equipment;
the cost calculation module is used for establishing a carbon transaction cost calculation model of the greenhouse integrated energy system based on the carbon emission quota of the greenhouse integrated energy system and the carbon emission parameters of the multiple energy conversion devices;
the function establishing module is used for establishing a target function based on demand side parameters of the greenhouse comprehensive energy system and an energy coupling model calculation model;
and the parameter optimization module is used for optimizing the operation parameters of the greenhouse comprehensive energy system based on the equipment constraint model and the objective function by taking the minimum operation cost and the minimum carbon transaction cost as optimization targets, and regulating and controlling the greenhouse comprehensive energy system based on the operation parameters.
In a third aspect, an embodiment of the present invention provides a terminal, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method according to the first aspect or any possible implementation manner of the first aspect when executing the computer program.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where a computer program is stored, and the computer program, when executed by a processor, implements the steps of the method according to the first aspect or any one of the possible implementation manners of the first aspect.
The embodiment of the invention provides a regulation and control method of a greenhouse comprehensive energy system, wherein the greenhouse comprehensive energy system comprises a plurality of energy conversion devices and a plurality of energy storage devices, and the method comprises the following steps: establishing an energy coupling model and an equipment constraint model of the greenhouse comprehensive energy system based on equipment parameters of various energy conversion equipment and various energy storage equipment; establishing a carbon transaction cost calculation model of the greenhouse integrated energy system based on the carbon emission quota of the greenhouse integrated energy system and the carbon emission parameters of the multiple energy conversion devices; establishing a target function based on demand side parameters of the greenhouse comprehensive energy system and an energy coupling model calculation model; and optimizing the operation parameters of the greenhouse comprehensive energy system based on the equipment constraint model and the objective function by taking the minimum operation cost and the minimum carbon transaction cost as optimization targets, and regulating and controlling the greenhouse comprehensive energy system based on the operation parameters. The method takes the minimum carbon transaction cost as a target, optimizes the operation parameters of the greenhouse comprehensive energy system through the multi-target mathematical model on the premise of meeting the parameters on the demand side, and can realize the layered regulation and control of the greenhouse comprehensive energy system through the optimized operation parameters.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required to be used in the embodiments or the prior art description will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings may be obtained according to these drawings without inventive labor.
FIG. 1 is an application scenario diagram of a regulating and controlling method of a greenhouse comprehensive energy system provided by an embodiment of the invention;
FIG. 2 is a flow chart of an implementation of a regulation and control method of the greenhouse integrated energy system provided by the embodiment of the invention;
FIG. 3 is a schematic diagram of PID thermostatic control of a greenhouse integrated energy system provided by an embodiment of the invention;
fig. 4 is a simulation result diagram of cold load output scheduling of the regulating method of the greenhouse integrated energy system according to the embodiment of the present invention;
FIG. 5 is a simulation result diagram of thermal load output scheduling of the method for regulating and controlling the greenhouse integrated energy system according to the embodiment of the present invention;
FIG. 6 is a simulation result diagram of electric load output scheduling of the method for regulating and controlling the comprehensive energy system of the greenhouse according to the embodiment of the present invention;
FIG. 7 is a simulation result diagram of the unit outlet water temperature and flow rate of the regulation and control method of the greenhouse integrated energy system provided by the embodiment of the invention;
FIG. 8 is a schematic structural diagram of a regulating device of the comprehensive energy system for greenhouses according to an embodiment of the invention;
fig. 9 is a schematic diagram of a terminal according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the following description is made by way of specific embodiments with reference to the accompanying drawings.
Fig. 1 is an application scenario diagram of a regulation and control method of a greenhouse integrated energy system provided by an embodiment of the invention. As shown in fig. 1, the method for regulating and controlling the greenhouse integrated energy system according to the embodiment of the present invention can be applied to the greenhouse integrated energy system shown in fig. 1. The greenhouse integrated energy system obtains electric energy from an external power distribution network, obtains fuel gas from an external fuel gas network, and then outputs electric load, cold load and heat load to a demand side. The greenhouse comprehensive energy system comprises multiple energy conversion devices and multiple energy storage devices, wherein the energy conversion devices comprise gas turbines, waste heat boilers, gas boilers, electric boilers, absorption refrigerators and electric refrigerators, and the energy storage devices comprise energy storage battery devices, heat storage water tanks and cold storage water tanks. The gas turbine is used for converting gas energy into electric energy and generating waste heat, the waste heat boiler is used for transmitting the waste heat absorbed by the gas turbine to the absorption refrigerator and the heat storage water tank, the absorption refrigerator is used for converting the waste heat of the gas turbine into cold energy, the electric refrigerator is used for converting the electric energy into the cold energy, the electric boiler is used for converting the electric energy into heat energy, the cold storage water tank is used for storing the cold energy in the form of cold water and providing the cold energy for a demand side, and the heat storage water tank is used for storing the heat energy in the form of hot water and providing the heat energy for the demand side.
Referring to fig. 2, it shows an implementation flowchart of the regulation and control method of the greenhouse integrated energy system provided by the embodiment of the present invention, which is detailed as follows:
step 201, establishing an energy coupling model and an equipment constraint model of the greenhouse comprehensive energy system based on equipment parameters of various energy conversion equipment and various energy storage equipment.
In this embodiment, the energy coupling model is used to describe a conversion relationship between various types of energy in the greenhouse integrated energy system, so that the power before and after energy conversion can be calculated, the input energy power can be calculated based on the output energy power, or the output energy power can be calculated based on the input energy power. The equipment constraint model is used for determining the operation parameter range of each equipment in the greenhouse comprehensive energy system in a safe and efficient operation and energy conservation state.
Step 202, establishing a carbon trading cost calculation model of the greenhouse integrated energy system based on the carbon emission quota of the greenhouse integrated energy system and the carbon emission parameters of the multiple energy conversion devices.
In this embodiment, the carbon trading policy is in a fully developed stage in china, the distribution mode of the initial carbon allotment mainly includes three modes of free distribution, auction distribution, and mixed distribution of free distribution and auction, and when the carbon emission of an enterprise is higher than the uncompensated carbon emission quota, additional purchase is required. When the carbon emission of the greenhouse comprehensive energy system is low, extra carbon trading gain can be obtained, the overall operation cost of the greenhouse comprehensive energy system is reduced, the output of an excitation equipment unit is increased, the electric quantity purchased by a large power grid is reduced, the carbon emission of the large power grid is reduced, the carbon trading cost is used as an optimization item of operation parameters, and the economic benefit and the environmental benefit of the greenhouse comprehensive energy system can be effectively improved.
And step 203, establishing an objective function based on the demand side parameters of the greenhouse comprehensive energy system and the energy coupling model calculation model.
In this embodiment, the optimization objective is that the operation cost is minimum and the carbon trading cost is minimum, and the output power of the greenhouse integrated energy system needs to meet the demand-side parameter, so that the objective function needs to reflect the influence relationship of the operation parameter on the operation cost, the carbon trading cost and the demand-side parameter, wherein the energy coupling model includes the relationship between the operation parameter and the output power, and the objective function can be obtained by adding a calculation model of the operation cost on the basis of the energy coupling model and the demand-side parameter.
And 204, optimizing the operation parameters of the greenhouse comprehensive energy system based on the equipment constraint model and the objective function by taking the minimum operation cost and the minimum carbon transaction cost as optimization targets, and regulating and controlling the greenhouse comprehensive energy system based on the operation parameters.
In this embodiment, in the state of satisfying the electric cooling and heating load of the greenhouse integrated energy system, the operation process of the greenhouse integrated energy system includes purchasing and selling electricity through the large power grid, operating the gas turbine, charging and discharging the energy storage battery, operating the boiler, and calculating the mutually coordinated stable operation cost and the equipment operation and maintenance cost of the devices, so as to ensure that the economic cost of the greenhouse integrated energy system is minimized during operation.
The embodiment of the invention provides a regulation and control method of a greenhouse comprehensive energy system, wherein the greenhouse comprehensive energy system comprises a plurality of energy conversion devices and a plurality of energy storage devices, and the method comprises the following steps: establishing an energy coupling model and an equipment constraint model of the greenhouse comprehensive energy system based on equipment parameters of various energy conversion equipment and various energy storage equipment; establishing a carbon trading cost calculation model of the greenhouse comprehensive energy system based on the carbon emission quota of the greenhouse comprehensive energy system and the carbon emission parameters of various energy conversion devices; establishing a target function based on demand side parameters of the greenhouse comprehensive energy system and an energy coupling model calculation model; and optimizing the operation parameters of the greenhouse comprehensive energy system based on the equipment constraint model and the objective function by taking the minimum operation cost and the minimum carbon transaction cost as optimization targets, and regulating and controlling the greenhouse comprehensive energy system based on the operation parameters. The method takes the minimum carbon transaction cost as a target, optimizes the operation parameters of the greenhouse comprehensive energy system through the multi-target mathematical model on the premise of meeting the parameters on the demand side, and can realize the layered regulation and control of the greenhouse comprehensive energy system through the optimized operation parameters.
In one possible implementation mode, the greenhouse comprehensive energy system acquires electric energy through electricity purchase, performs gas-heat energy conversion through a gas boiler, and performs energy coupling through CCHP equipment;
establishing a carbon transaction cost calculation model of the greenhouse integrated energy system based on the carbon emission quota of the greenhouse integrated energy system and the carbon emission parameters of the multiple energy conversion devices, wherein the carbon transaction cost calculation model comprises the following steps:
determining the emission quota of the free carbon of the greenhouse comprehensive energy system;
establishing a power purchase carbon emission calculation model based on the unit electric quantity carbon emission;
establishing a gas boiler carbon emission calculation model based on unit heat carbon emission;
establishing a CCHP carbon emission calculation model based on the unit heat carbon emission and the power generation-heat supply conversion coefficient of the CCHP equipment;
determining a carbon transaction cost calculation model of the greenhouse comprehensive energy system based on the uncompensated carbon emission quota, the electricity purchasing carbon emission calculation model, the gas boiler carbon emission calculation model and the CCHP carbon emission model;
in this embodiment, a reference line method is adopted to determine the emission quota of the uncompensated carbon of the greenhouse integrated energy system, and it is considered that the sources of the carbon emission in the greenhouse integrated energy system mainly include three parts, namely, an external power grid power purchase, a gas boiler and a CCHP unit, then the carbon emission of each part is calculated respectively, the carbon emission of each part is added to the total carbon emission of the greenhouse integrated energy system, and the carbon trading cost can be calculated by the difference between the total carbon emission and the uncompensated carbon emission quota.
In one possible implementation manner, the electricity purchasing carbon emission calculation model is as follows:
E h ＝δ p P buy
wherein E is h Represents the amount of carbon emission, delta, of electricity purchase p Represents the carbon emission per unit of electricity, P buy Indicating the electricity purchasing quantity;
the model for calculating the carbon emission of the gas boiler is as follows:
E gb ＝δ h H gb (t)
wherein E is gb Represents the carbon emission of the gas boiler, delta h Represents the carbon emission per unit heat, H gb (t) heat generation capacity of the gas boiler;
the CCHP carbon emission calculation model is as follows:
Figure BDA0003741518110000091
wherein E is cchp Represents the carbon emission, δ, of a CCHP plant h Represents the carbon emission per unit heat, Q eb (t) represents the heat supply of the electric boiler, Q hb (t) represents the heat supply amount of the exhaust-heat boiler, Q er (t) represents refrigerating capacity, Q of the refrigerating machine of the electric refrigerator ac (t) represents the refrigerating capacity of the absorption refrigerating machine, P gt (t) represents the amount of power supplied to the gas turbine,
Figure BDA0003741518110000093
representing a power generation-heat supply conversion coefficient;
the carbon transaction cost calculation model is as follows:
Figure BDA0003741518110000092
in the formula, C co2 Cost of carbon trading for greenhouse integrated energy systems, E ci The actual carbon emission of each device in the greenhouse comprehensive energy system, and c is the carbon trading price; λ represents the increase of the price per stepped carbon transaction, E pi Representing the total carbon emission of the electricity, gas boiler and CCHP equipment, h representing the length of the carbon emission interval, E ci Indicating carbon emissions of thermal power generating units, CCHP units and gas boilers。
In this embodiment, the actual carbon emission is subjected to piecewise linearization, and the carbon emission in different piecewise ranges corresponds to different step-type carbon trading prices, so that the total carbon emission can be controlled.
In one possible implementation, the establishing of the objective function based on the demand-side parameters of the greenhouse integrated energy system and the energy coupling model calculation model comprises:
constructing an electricity purchasing cost model based on the electricity purchasing price;
constructing a gas turbine power generation cost model based on the gas price;
constructing a fuel cost model of the gas boiler based on the efficiency coefficient of the gas boiler;
constructing an equipment operation and maintenance cost model based on the unit operation and maintenance cost of each equipment;
constructing an operation cost calculation model of the greenhouse comprehensive energy system based on the electricity purchase cost model, the gas turbine power generation cost model, the gas boiler fuel cost model and the equipment operation maintenance cost model;
and respectively substituting the energy conversion relation in the demand side parameter and the energy coupling model into the operation cost calculation model and the carbon transaction cost calculation model to obtain the target function.
In this embodiment, in the state of satisfying the electric cooling and heating load of the greenhouse integrated energy system, the operation process of the greenhouse integrated energy system includes purchasing and selling electricity through the large power grid, operating the gas turbine, charging and discharging the energy storage battery, operating the boiler, and calculating the mutually coordinated stable operation cost and the equipment operation and maintenance cost of the devices, so as to ensure that the economic cost of the greenhouse integrated energy system is minimized during operation.
In the embodiment, in order to accurately control the water temperature at the outlet of the heat pump to meet the domestic water at the demand side of the comprehensive energy system of the greenhouse, the PID controller is used for controlling the outlet flow of the variable-frequency flow water pump and the outlet temperature of the heat pump. Control Block diagram As shown in FIG. 3, the system gives the desired outlet water temperature T out0 And omega T For the actual outlet water temperature T of the heat pump out Error Δ e of sampled value of T Is input to PID controller, PID controller control signal regulating frequency conversion flow water pump G 1 (s) outlet water flow, regulating heat pump G under external disturbance of water flow M 2 (s) actual outlet water temperature. When the PID controller regulates the water flow at the outlet of the variable-frequency flow water pump, the variable-frequency flow water pump is equivalent to a first-order inertia link G 1 (s)。
Figure BDA0003741518110000101
Transfer function G of heat pump 2 (s) is
Figure BDA0003741518110000102
In one possible implementation, the electricity purchase cost model is:
Figure BDA0003741518110000103
wherein, F 1 Indicating the cost of electricity purchase, P grid (t) represents the power purchased during time t, C system (t) represents a purchase price for a time period t;
the gas turbine power generation cost model is as follows:
Figure BDA0003741518110000104
wherein, F 2 Representing the cost of power generation of the gas turbine, C gas (t) represents the gas price, η, over a period of time t GT Representing the efficiency coefficient, P, of the gas turbine gt (t) represents the output electric power of the gas turbine, LHV, over a period of time t gas Indicating a low heating value of natural gas;
the fuel cost model of the gas boiler is as follows:
Figure BDA0003741518110000105
wherein, F 3 Representing the fuel cost of the gas boiler. C gas (t) represents the gas price over a period of time t, H gb (t) represents the output thermal power, η, of the gas boiler over a time period t gb Representing an efficiency coefficient of the gas boiler;
the equipment operation and maintenance cost model is as follows:
Figure BDA0003741518110000106
wherein, F 4 Represents the cost of operating and maintaining the equipment, k i Indicating the unit operating maintenance cost, P, of the equipment i i (t) represents the input power at which device i operates during time period t;
the objective function is:
Figure BDA0003741518110000111
wherein F represents the operation economic cost of the greenhouse integrated energy system, and E represents the total emission of carbon-containing pollutant gases of the greenhouse integrated energy system.
In this embodiment, the operation cost part of the objective function aims at minimizing the operation economic cost of the greenhouse integrated energy system, the environment part aims at minimizing the total emission of carbon-containing pollutant gas of the greenhouse integrated energy system, when the total emission of the carbon-containing pollutant gas is low, the greenhouse integrated energy system can obtain additional carbon trading gain and reduce the overall operation cost, and when the total emission of the carbon-containing pollutant gas is too low, the greenhouse integrated energy system needs to increase additional carbon trading cost and improve the overall operation cost, so that the two parts of the objective function have an influence relationship with each other, and both parts need to be taken as optimization targets.
In a possible implementation manner, an energy coupling model and an equipment constraint model of the greenhouse integrated energy system are established based on equipment parameters of a plurality of energy conversion equipment and a plurality of energy storage equipment, and the method comprises the following steps:
establishing an energy coupling model of the greenhouse comprehensive energy system based on the conversion efficiency parameters of various energy conversion devices and the device parameters of various energy storage devices;
and establishing an equipment constraint model of the greenhouse comprehensive energy system based on the safe operation parameters of various energy conversion equipment and various energy storage equipment.
In this embodiment, the establishing an energy coupling model of the greenhouse integrated energy system based on the conversion efficiency parameters of the multiple energy conversion devices and the device parameters of the multiple energy storage devices may include:
establishing an electric cold coupling model based on the refrigeration coefficient of the electric refrigerator; the electric cooling coupling model is as follows:
Q er (t)＝COP er *P er (t)
wherein the COP er To the refrigeration coefficient, P er (t) is the power consumed by the electric refrigerator at time t, Q er (t) is the refrigerating capacity of the electric refrigerator at the moment t; wherein the electric-cold coupling link is composed of an electric refrigerator and converts the electric energy into a cold load [13 ]]The transient process is complex, so only the steady state process is considered, and the refrigerating capacity of the electric refrigerator at the time t is determined by the refrigerating coefficient and the power consumption;
establishing an electrical coupling model based on the energy consumption coefficient of the gas turbine, the heat efficiency of the gas boiler and the conversion efficiency of the electric gas conversion equipment; the electrical coupling model is:
Figure BDA0003741518110000121
wherein, G gt (t) power consumption of gas turbine natural gas, E gt (t) Start-stop State of the gas turbine, P gt (t) is the output electric power of the gas turbine at time t, a, b, c are the energy consumption coefficients, H gb (t) is the output thermal power of the gas boiler, eta gb Is the thermal efficiency of a gas boiler, V gb (t) is the gas input power of the gas boiler at time t, PP2G (t) is the power consumption of the electric gas conversion equipment at time t, V P2G (t) is an electric gas-converting apparatusthe amount of gas generated at time t,
Figure BDA0003741518110000122
for the conversion efficiency of the electric gas-converting apparatus, f LHV Is the low heating value of natural gas; the electric heating coupling ring joint comprises a gas turbine mathematical model, a gas boiler mathematical model and a P2G (electric gas conversion equipment) mathematical model; the gas boiler coupling mode and the P2G coupling mode mainly provide heat energy for the system, and the micro gas turbine coupling mode can provide electric energy and heat energy simultaneously. The power generation system formed by the gas turbine converts energy between natural gas and electric power, the gas turbine obtains kinetic energy by burning natural gas provided by a natural gas pipe network so as to drive the permanent magnet synchronous generator to generate power, waste heat generated by burning can provide heat energy for heat load in the comprehensive energy system in the form of hot water and the like, and the relation between natural gas consumption power and t output electric power of the gas turbine at t moment is as follows; the gas boiler mainly solves the problem that the heat generated by the waste heat boiler is insufficient by acquiring natural gas and converting the gas into heat, and the heating capacity of the gas boiler at the time t is determined by the heat efficiency of the gas boiler and the consumption of the gas at the time t; the P2G equipment can convert electric energy into combustible gas such as hydrogen energy and natural gas to supplement the combustible gas in a gas network, the natural gas is taken as a research object, and the amount of the natural gas generated at the time t is determined by the ratio of the power consumption of the P2G at the time t to the conversion efficiency to the low calorific value; in this embodiment, the fuel gas may further include other combustible gases, such as hydrogen, and corresponding parameters of the corresponding natural gas may also be replaced by parameters of hydrogen or other combustible gases;
establishing an electric-thermal coupling model based on the heat recovery efficiency of the waste heat boiler and the efficiency coefficient of the electric boiler; the electric-thermal coupling model is as follows:
Figure BDA0003741518110000123
wherein, P gt (t) output electric power at time t of the gas turbine, P hb (t) is the residual heat power of the residual heat boiler at t moment, H eb (t) Is the output power at time t of the electric boiler, eta eb Is the efficiency coefficient of the electric boiler, P eb (t) is the power consumption of the electric boiler at time t, lambda gt Is the output electric power ratio, eta, of the gas turbine gt The heat recovery efficiency of the waste heat boiler; the electric heating coupling ring joint comprises a waste heat boiler and an electric boiler mathematical model, wherein the waste heat boiler mainly collects high-temperature flue gas generated by a gas turbine and secondarily collects heat for utilization, the utilization rate of energy is improved, and the effects of energy conservation and emission reduction are fully embodied. An electric boiler is a device for converting electric energy into heat energy, generally transfers heat through steam, high-temperature water or other heat energy carriers, is often used for participating in the peak-valley coordination work of heat/electricity load of an electric heating combined system, and the thermal power of the electric boiler at the moment t is closely related to the power consumption of the electric boiler at the moment t.
Establishing a heat-cold coupling model based on the refrigeration coefficient of the absorption refrigerator; the hot-cold coupling model is:
Q ar (t)＝COP ar *P ar (t)
wherein the COP ar Is the refrigeration coefficient of absorption refrigerator, P ar (t) is the thermal power of the heating source of the absorption refrigerator at time t, Q ar (t) is the refrigerating capacity of the absorption refrigerator at the moment t; the heat and cold coupling link is an absorption refrigerating unit and mainly aims to convert heat generated by a power system and a natural gas network into cold in the actual process. The absorption refrigerator is a device which takes water as a refrigerant and lithium bromide as an absorbent and performs refrigeration by consuming low-grade heat energy by utilizing the absorption refrigeration principle, and a large amount of water vapor generated in the production process is absorbed by the lithium bromide refrigerator;
establishing an energy storage charging and discharging model based on the charging efficiency and the discharging efficiency of the energy storage battery and the energy loss efficiency, the heat storage efficiency and the heat release efficiency of the heat storage water tank; the energy storage charging and discharging model comprises:
Figure BDA0003741518110000131
wherein, Δ SOC bt Is the difference value of the current state of charge and the previous time state of charge of the energy storage battery, and the unit is kWh, P bt.c (t) is the charging power of the energy storage battery at time t, P bt.d (t) is the discharge power of the energy storage battery at the moment t, and the unit of the discharge power are kW and eta bt.c For the charging efficiency of energy-storage cells, eta bt.d For the discharge efficiency of energy storage cells, W hwt The heat storage amount of the heat storage water tank at the current moment, kWh, Δ W hwt Is the difference value between the heat storage quantity of the heat storage water tank at the current moment and the heat storage quantity at the previous moment, H hwt.c (t) is the heat charging power of the heat storage water tank, H hwt.d (t) is the heat release power of the heat storage water tank, kW and gamma h For the energy loss efficiency of the heat storage water tank, eta hwt.c For the heat storage efficiency of the heat storage water tank, eta hwt.d The heat release efficiency of the heat storage water tank is obtained; in order to avoid the adverse effect of charging and discharging under low power and low charge state on the service life, the storage battery is required to meet the charging and discharging constraint and the charge state constraint during operation; the system operation flexibility and the economy are improved.
Establishing an electric cooling and heating load model based on the relationship between the transferable load and the fixed load in the electric load and the cold/heat load and the load required by the greenhouse comprehensive energy system; the electric heating and cooling load model comprises:
Figure BDA0003741518110000132
wherein, P Cel (t) electric load required by greenhouse comprehensive energy system, P fel (t) is a fixed electrical load, P tel (t) is a transferable electrical load, Q Chl (t) Cold/Heat load required by greenhouse Integrated energy System, Q fhl (t) is the cold/hot fixed load, Q thl (t) is transferable cold/heat load; wherein, the coupling of multiple energy sources in the greenhouse integrated energy system enables the loads to participate in demand response in a mutual substitution and multi-energy complementary mode. Therefore, in the greenhouse comprehensive energy system, the electric load, the cold load and the heat load can not only participate in demand response in respective forms, but also realize the coupling complementation and mutual complementation of the three loads through the energy conversion equipment and the energy storage deviceAnd (4) replacing. The greenhouse comprehensive energy system in the embodiment is mainly capable of transferring loads, firstly, a demand response model of electricity, cold and heat loads is constructed based on adjustability of the electricity, cold and heat loads, and secondly, energy conversion equipment and energy storage equipment in the greenhouse comprehensive energy system are utilized to enable the electricity, cold and heat loads to be coupled and complemented; the load types mainly comprise rigid load and flexible load, wherein the flexible load is mainly used for regulating and controlling the overall load curve of the system on the premise of meeting the basic rigid load of the system, and the overall energy consumption level of the system is improved. According to the regulation and control mode of the flexible load, the flexible load can be divided into a reducible load and a transferable load, the transferable load refers to a load of which the power utilization time of the load can be changed according to the greenhouse requirement, the electric load of the greenhouse comprehensive energy system comprises a fixed electric load and a transferable electric load, the flexible heat/cold load in the embodiment is also the transferable load, and the heat/cold load of the greenhouse comprehensive energy system comprises the fixed heat/cold load and the transferable heat/cold load; the traditional greenhouse demand response only adjusts the electric load curve, and the adjusting mode is usually to stimulate a user to actively change the electricity utilization habit by adopting price signals. In a greenhouse comprehensive energy system, the load is in various forms of electricity, cold, heat and the like, natural gas and electric energy have the same market commodity attribute, and heat energy and cold energy have system inertia and temperature change time lag, so that the cold load and the heat load can also participate in demand response to carry out optimization and adjustment;
establishing an energy coupling model of the greenhouse comprehensive energy system based on the electric-cold coupling model, the electric-thermal coupling model, the heat-cold coupling model, the electric energy charging and discharging model and the heat energy charging and discharging model; the energy coupling model is:
Figure BDA0003741518110000141
wherein, P c Is total electric energy H c Total heat energy, Q c Total cold energy, H gh The total heat energy generated by the gas turbine and the gas boiler is calculated by the following formula:
Figure BDA0003741518110000142
the coupling link is composed of a CCHP unit, and works by utilizing the trend obtained by the operation of a power system, a natural gas network, a heating system and a cooling system to obtain the electric energy, the heat energy and the cold energy required by the load of the greenhouse comprehensive energy system. Wherein the equipment for generating electric energy is a gas turbine; the equipment for generating heat energy is a gas turbine, a gas boiler and an electric boiler; the equipment for generating cold energy is a compression type refrigerator and an absorption type refrigerator; the P2G equipment is used for supplementing the gas input of a natural gas network; the waste heat boiler is used as a heat energy storage device, and the transformer and the heat exchanger are used as conversion links in the transmission process of electric energy and heat energy.
In another embodiment, the device constraint model of the greenhouse integrated energy system is established based on safe operation parameters of the plurality of energy conversion devices and the plurality of energy storage devices, and comprises the following steps:
power constraint of absorption refrigerator is not less than 0 and not more than P ar (t)≤P ar.max ；
Wherein, P ar.max The upper limit of the thermal power of the heating source of the absorption refrigerator;
power constraint of electric refrigerator is more than or equal to 0 and less than or equal to P er (t)≤P er.max ；
Wherein, P er.max The upper limit of the electric energy power consumed by the electric refrigerator;
operating power constraint P of gas turbine gt.min ≤P gt (t)≤P gt.max Power constraint on climbing P gt.down ≤ΔP gt ≤ P gt.up ；
Wherein, P gt.max Is the upper limit of the output electric power of the gas turbine; p gt.min Is the output electric power lower limit value of the gas turbine; p gt.up Is the gas turbine climbing power upper limit; p is gt.down A lower ramp power limit for the gas turbine; delta P gt A difference between the output electric power at the previous time and the output electric power at the next time;
h is not less than 0 and constrained by output thermal power of the gas boiler gb (t)≤H gb.max ；
Wherein H gb.max The upper limit value of the output thermal power of the gas-fired boiler;
the power consumption constraint of the electric boiler is not less than 0 and not more than P eb (t)≤P eb.max ；
Wherein, P eb.max The maximum power limit of the power consumption of the electric boiler;
energy storage battery charging constraint U bt.c (t)P bt.c.min ≤P bt.c (t)≤U bt.c (t)P bt.c.max
Energy storage battery discharge restraint U bt.d (t)P bt.d.min ≤P bt.d (t)≤U bt.d (t)P bt.d.max
Energy storage battery state of charge constraint SOC bt.min ≤SOC bt (t)≤SOC bt.max
Wherein, U bt.c (t) is the state of charge of the battery; u shape bt.d (t) is the discharge state of the battery; SOC bt (t) is the state of charge of the battery, kWh;
energy storage battery mutual exclusion constraint U bt.d (t)+U bt.c (t)≤1
Energy storage battery charge-discharge frequency constraint
Figure BDA0003741518110000151
Energy storage battery charging climbing power constraint P bt.c.min ≤ΔP bt.c ≤P bt.c.max
Energy storage battery discharging and climbing power constraint P bt.d.down ≤ΔP bt.d (t)≤P bt.d.up
Wherein, P bt.c.min Is the minimum power, kW, of the battery in the charged state; p is bt.c.max The maximum power in the charging state of the storage battery is kW; p bt.d.down Is the minimum power in the discharging state of the storage battery, kW; p is bt.d.up kW is the maximum power of the storage battery in a discharging state;
capacity constraint W of heat storage water tank hwt.min ≤W hwt (t)≤W hwt.max
Heat storage water tank heat filling restraint U hwt.c (t)H hwt.c.min ≤H hwt.c ≤H hwt.c.max U hwt.c (t)
Heat release constraint U of heat storage water tank hwt.d (t)H hwt.d.min ≤H hwt.d (t)≤H hwt.d.max U hwt.d (t)
Wherein, U hwt.c (t) is the heat-charging state of the heat storage water tank, U hwt.d (t) is the heat release state of the heat storage water tank;
mutually exclusive constraint U of heat storage water tank hwt.d +U hwt.c ≤1
Heat-storage water tank heat-filling climbing power constraint H hwt.c.min ≤ΔH hwt.c ≤H hwt.c.max
Heat release climbing power constraint H of heat storage water tank hwt.d.min ≤ΔH hwt.d ≤H hwt.d.max
Wherein H hwt.c.min Is the minimum power in the heat charging state of the heat storage water tank, kW; h hwt.c.max Is the maximum power of the heat storage water tank in the heat charging state, kW and H hwt.d.min Is the minimum heat release power, kW, H, of the heat storage water tank in the heat release state hwt.d.max kW is the maximum heat release power of the heat storage water tank in a heat release state;
P2G equipment rated power constraint is not less than 0 and not more than P P2a (t)≤P P2a.max
Wherein, P P2Gmax The maximum rated power, kW, of the P2G plant.
Grid constraint E b.grid (t)+E s.grid (t)≤1、0≤P b.grid (t)≤P b . grid.max 、0≤P s . grid (t)≤ P s，grid.max
Wherein E is b.grid (t) represents the purchase status of the greenhouse integrated energy system in the time period t; e s.grid (t) representing the power selling state of the greenhouse integrated energy system at t time period; p b.grid (t) purchasing electric power for the greenhouse comprehensive energy system; p s.grid (t) selling power of the greenhouse comprehensive energy system; p is bgrid.max The upper limit of the electricity purchasing power of the greenhouse comprehensive energy system; p is s.grid.max Is warmThe lower limit of the electricity selling power of the indoor comprehensive energy system; the greenhouse integrated energy system can maintain the balance of electric load in the system by purchasing and selling electric power to an external large power grid, and in order to ensure the safe operation of a power distribution network, the integrated energy system cannot purchase and sell the electric power to the power grid at the same time, and the upper limit of the interactive power with the power distribution network is regulated within a certain range;
electrical load constraint of 0 ≤ P tel (t)≤P tel，max 、
Figure BDA0003741518110000161
Wherein, P tel.max Represents the upper limit of transferable electrical load, kW; w tel Representing the total amount of transferable electrical load over T periods; the greenhouse comprehensive energy system can automatically adjust the power consumption and time, such as charging load and the like, according to the electricity price information;
transferable load constraint 0 ≦ Q thl (t)≤Q thl，max 、
Figure BDA0003741518110000162
In the formula Q thl.max Represents an upper limit of transferable load; w thl Representing the total amount of transferable load over T periods;
large power grid electric power constraint P grid.min ≤ΔP grid (t)≤P grid.max 、P grid.down ≤ΔP grid ≤P grid.up
Wherein, P grid.max The maximum purchasing power of the power grid is kW; p grid.min The minimum purchasing power of the power grid, kW; p grid.up kW is the upper limit of the climbing rate of the power grid; p is grid.down For the climbing rate lower limit of electric wire netting, kW:
electric power balance constraint
P wt (t)+P gt (t)+P gb (t)+P bt.dis (t)+P PV (t)
-P P2G (t)-P ac (t)-P eh (t)＝P fel (t)+P sel (t)+P bt.chr (t)
Wherein t represents the t moment of the comprehensive energy system; p wt Representing the power generation output of the fan; p gt Representing the power generated by the gas turbine; p gb Indicating the output of the gas boiler; p is btdis Represents the battery discharge power; p PV Representing the power generated by the photovoltaic panel; p e2G2G Representing the energy consumption situation of the P2G equipment; p ac Represents the power consumed by the absorption chiller; p eh Consuming energy and power for the electric boiler; p bt.chr Charging power for the battery; p fel Is a fixed electrical load; p is sel Is a translatable electrical load;
thermal power balance constraint
H cchp (t)+H gb (t)-H ac (t) +H hwt.dis (t)＝H fhl (t)+H shl (t)+H hwt.ch (t)
Wherein Hcchp is the heat supply of a CCHP unit; h gb Heat supply for gas boiler; h ac Absorbing heat of the absorption refrigerating unit; h tst.dis The heat supply quantity of the energy storage water tank is provided; h tst.ch The heat release of the energy storage water tank; h fhl To fix the thermal load; h shl Is translatable of thermal load;
cold power balance constraint Q ar (t)+Q ac (t)＝Q fcl (t)+Q scl (t)
Wherein Q is ar Supplying cold for the electric refrigerator; q ac The cooling capacity of the absorption refrigerator; q fcl To fix the cooling load; q scl To translate the cooling load.
In one possible implementation, optimizing operating parameters of the greenhouse integrated energy system based on the plant constraint model and the objective function with the minimum operating cost and the minimum carbon trading cost as optimization objectives includes:
linearizing the target function to obtain a linear target function; the linear objective function is:
Figure BDA0003741518110000171
wherein Z represents a system of more(ii) a target optimization expectation; f represents the optimal value of the operating economic cost of the greenhouse integrated energy system, omega 1 Weighting factor, ω, representing economic objective optimization 2 Weighting factor, omega, representing an optimization of an environmental objective 1 +ω 2 ＝ 1，(0≤ω 1 ≤1，0≤ω 2 ≤1)；
And optimizing the operation parameters of the greenhouse comprehensive energy system based on the equipment constraint model and the objective function by taking the minimum operation cost and the minimum carbon transaction cost as optimization targets to obtain the optimized operation parameters of the greenhouse comprehensive energy system.
In this embodiment, a multi-objective optimization problem is converted into a single-objective optimization method through a linear weighted sum method, so as to obtain a convex objective function with an optimal system comprehensive scheduling expectation. In this embodiment, a mixed integer linear programming method is used to optimize the operation parameters, and the specific mathematical model is as follows:
Figure BDA0003741518110000172
wherein z = f (x) is an objective function; g i (x) The inequality constraint is more than or equal to 0; h is j (x) =0 is an identity constraint; the variable x is an integer.
The above formula is a nonlinear greenhouse integrated energy system optimization scheduling model, which needs to be converted into a mixed integer linear programming problem for solving, and the nonlinear coupling relational expression therein can be processed by using a related linearization method.
U (t) is a 0,1 variable, and N (t) is a positive variable. To linearize U (t) N (t), assume that N (t) is set to a larger upper limit value, N max . Two temporary variables M (t), R (t) are added.
The linearization steps are as follows:
adding an equality constraint:
M(t)＝N(t)-R(t)
adding inequality constraints:
M(t)≤N(t) max
R(t)≤N(1-U(t)) max
thus M (t) is fully equivalent to U (t) N (t), but with two variables and three constraints added.
In a specific embodiment, in order to consider the practical effect of the method provided by the present invention, the present embodiment sets 3 scenes for comparison and description:
scene 1: greenhouse integrated energy system considering only economic targets in case of carbon trading
Scene 2: greenhouse integrated energy system considers both economic and environmental goals in consideration of carbon trading
Scene 3: in the case of considering carbon trading, both economic and environmental objectives are considered, but the demand side load is not considered.
The economic environmental cost pair for three scenario runs is shown in table 1.
TABLE 1
Scheme(s) Cost/dollar for carbon transaction Economic cost/dollar Comprehensive cost/yuan
Scene 1 -125.8 1784.1 748.9
Scene 2 -140.8 1947.9 631.4
Scene 3 -108.3 1834.2 710.6
In a general view, the carbon transaction mechanism is considered in all three scenes, the carbon transaction cost of the scene 2 is the largest, and the scene 3 is the smallest, so that the carbon emission of the scene 2 in the three scenes is the lowest, extra carbon transaction benefits can be obtained, the output of the excitation equipment unit is increased, the electricity purchasing quantity of a large power grid is reduced, and the carbon emission of the large power grid is reduced. Considering the scenario 2 the most from one side of economic cost, but still the comprehensive cost of the scenario 2 is the lowest from the point of view of the overall comprehensive cost, which is 15.7% lower than the comprehensive cost of the scenario 1 and 11.1% lower than the comprehensive cost of the scenario 3. Therefore, the optimization method of the greenhouse comprehensive energy system provided by the invention can effectively improve the economic benefit and the environmental benefit of the greenhouse comprehensive energy system. The following analyses the effects of the present invention in the case of priority scheduling of various types of energy loads, respectively:
1. cold load contribution scheduling
Because a large number of coupled capacity devices exist at the energy supply side, a system operator can optimize and set the electricity price in the system and the production schemes of various capacity devices according to the data of the external energy price, the output of renewable energy and the like of the system, and the coordinated optimization of both supply and demand sides of the system is realized. Fig. 4 is a production scheme of the absorption chiller, the electric chiller, and the cooling load relationship in each time period in scenario 2, in which the cooling load power generated by the absorption chiller and the electric chiller at each moment is displayed as a positive value.
The output condition of the demand side cold load response cold load equipment under the condition of considering both system economy and environmental targets is shown in the figure, under the cold supply working condition, the greenhouse cold load requirement is integrally low in the time periods from 1 point to 7 points and from 19 points to 23 points, the cold load requirement can be met only by starting the electric refrigerator, the full-power starting of the electric refrigerator can not meet the cold load requirement when the electric refrigerator is in an electricity utilization peak time period in the time period from 7 points to 19 points, and the cold load requirement can be conveniently met by starting the absorption refrigerator. The result of the priority scheduling of the operation of the cooling load device is shown in fig. 4.
2. Thermal load contribution scheduling
The lower diagram shows a production scheme of a gas boiler, a waste heat boiler, a heat storage water tank, an electric boiler, an absorption refrigerator and a heat load relation in each time period in the scene 2, wherein the heat generation power of the gas boiler, the waste heat boiler and the heat storage water tank and the heat load power generated by the electric boiler at each moment are all used as positive values, and the heat generation power of the heat storage water tank and the heat power absorbed by the absorption refrigerator are all used as negative values.
The demand side cold load response thermal load plant capacity is shown with both system economics and environmental objectives in mind, with the thermal load of the greenhouse coming primarily from the basic demand of production in the heating regime. And in the time period from 0 point to 3 points, the electricity price is at the valley, the gas turbine, the gas boiler, the electric boiler and the heat storage water tank are started to meet the heat load demand of the user side, redundant heat is released into the absorption refrigerating unit, and redundant heat generated by normal operation of the gas turbine, the waste heat boiler and the gas boiler enters the heat storage water tank and the absorption refrigerating unit in the time period from 3 points to 24 points. The thermal load cold-hot priority scheduling results are shown in fig. 5.
3. Electrical load contribution scheduling
Fig. 6 shows a power exchange of the active power distribution network, a discharge of the energy storage battery, a discharge of the gas turbine, wind power, photovoltaic, electricity selling power, a charge of the energy storage battery, an electric refrigerator, an energy consumption of the electric-to-heat equipment, and a P2G device and an electric load relation production scheme in each time period in the scene 2, wherein the power exchange of the active power distribution network, the discharge of the energy storage battery, the discharge of the gas turbine, the wind power and the photovoltaic all generate electric load power as positive values, and the electricity selling power, the charge of the energy storage battery, the electric refrigerator, the energy consumption of the electric-to-heat equipment, and the electric power of the P2G device all display as negative values.
Under the condition of considering both system economy and environmental targets, the output condition of demand side electric load response equipment is shown in the figure, under the working condition of power supply, at the time of valley electricity price, the system purchases electricity from the active power distribution network side, so that the system has excellent economic benefit, the system meets daily load requirements, a gas turbine in the system is always kept in an operating state, wind power and photovoltaic generate partial force, redundant electricity in individual time intervals can be used for charging other equipment of the system and an energy storage battery to perform difference compensation on the load in partial peak time intervals, the system does not purchase electricity to the power distribution network side in the peak time intervals, and the electric load electric energy priority scheduling result is shown in the figure 6.
The situation of the cold, heat and power loads in the three scenes can be obtained by comparing, the economical efficiency is considered as the target, the influence of time-of-use gas price and time-of-use electricity price strategies is taken into consideration, the power of electricity purchasing from the power distribution network can be weakened by optimizing operation at the moment of peak electricity price, and further the economic burden caused by wind electricity and natural gas reduction of the electricity price at the moment of wind is enhanced; when the economic target and the environmental target are considered to be optimal, the system is optimized to operate, the electric power purchasing at the valley time is increased, the electric power purchasing at the peak time is reduced, and in the summer cooling season, the electric power purchasing beyond the optimized operation meets the load requirement; in the winter heating season, optimizing operation to increase natural gas and reduce electricity purchase to meet the heat load demand; meanwhile, when the economic target, the environmental target and the demand side response are considered, the optimization operation can be balanced between economy and environment, so that the comprehensive energy system can operate with better economic environmental protection performance, and the utilization efficiency of energy is improved.
4. Lower layer constant temperature control
The expected water outlet temperature is set to be 50 ℃ according to system simulation, at the simulation operation time, the PID control system is overshot in the whole operation process, the water temperature at the outlet of the system tends to be stable within 1500s, the water temperature at the outlet can be stabilized at 50 ℃, the frequency-conversion flow water pump system of the system changes according to the water temperature condition at the outlet of the system, and when the water temperature tends to be stable, the flow of the water pump also tends to be stable, and finally is stabilized to be near 8kg/min according to the frequency-conversion flow water pump system of the system. The living requirements of users in the greenhouse can be better met, and the water outlet temperature and flow of the unit are shown in figure 7.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
The following are embodiments of the apparatus of the invention, reference being made to the corresponding method embodiments described above for details which are not described in detail therein.
Fig. 8 is a schematic structural diagram of a regulating device of a greenhouse integrated energy system according to an embodiment of the present invention, and for convenience of description, only the parts related to the embodiment of the present invention are shown, and the details are as follows:
as shown in fig. 8, the control device 8 of the greenhouse integrated energy system includes:
the model establishing module 81 is used for establishing an energy coupling model and an equipment constraint model of the greenhouse comprehensive energy system based on equipment parameters of various energy conversion equipment and various energy storage equipment;
the cost calculation module 82 is used for establishing a carbon transaction cost calculation model of the greenhouse integrated energy system based on the carbon emission quota of the greenhouse integrated energy system and the carbon emission parameters of the various energy conversion devices;
the function establishing module 83 is used for establishing a target function based on the demand side parameters of the greenhouse comprehensive energy system and the energy coupling model calculation model;
and the parameter optimization module 84 is used for optimizing the operation parameters of the greenhouse comprehensive energy system based on the equipment constraint model and the objective function by taking the minimum operation cost and the minimum carbon transaction cost as optimization targets, and regulating and controlling the greenhouse comprehensive energy system based on the operation parameters.
In one possible implementation mode, the greenhouse comprehensive energy system acquires electric energy through electricity purchase, gas-heat energy conversion is carried out through a gas boiler, and energy coupling is carried out through CCHP equipment;
the cost calculation module 82 is specifically configured to:
determining the uncompensated carbon emission quota of the greenhouse integrated energy system;
establishing a power purchase carbon emission calculation model based on the unit electric quantity carbon emission;
establishing a gas boiler carbon emission calculation model based on unit heat carbon emission;
establishing a CCHP carbon emission calculation model based on the carbon emission of unit heat and the conversion coefficient of the power generation and heat supply of the CCHP equipment;
determining a carbon transaction cost calculation model of the greenhouse comprehensive energy system based on the uncompensated carbon emission quota, the electricity purchasing carbon emission calculation model, the gas boiler carbon emission calculation model and the CCHP carbon emission model;
in one possible implementation manner, the electricity purchasing carbon emission calculation model is as follows:
E h ＝δ p P buy
wherein E is h Represents the amount of carbon emission, delta, of electricity purchase p Represents the carbon emission per unit of electricity, P buy Indicating the electricity purchasing quantity;
the model for calculating the carbon emission of the gas boiler comprises the following steps:
E gb ＝δ h H gb (t)
wherein, E gb Represents the carbon emission of the gas boiler, delta h Represents the carbon emission per unit heat, H gb (t) heat production of the gas boiler;
the CCHP carbon emission calculation model is as follows:
Figure BDA0003741518110000211
wherein, E cchp Represents the carbon emission of the CCHP plant, delta h Denotes carbon emission per unit heat, Q eb (t) represents the heat supply of the electric boiler, Q hb (t) represents the heat supply amount of the exhaust-heat boiler, Q er (t) represents refrigerating capacity, Q, of the refrigerating machine of the electric refrigerator ac (t) represents the refrigerating capacity of the absorption refrigerating machine, P gt (t) represents the amount of power supplied to the gas turbine,
Figure BDA0003741518110000213
representing a power generation-heat supply conversion coefficient;
the carbon transaction cost calculation model is:
Figure BDA0003741518110000212
in the formula, C co2 Cost of carbon trading for greenhouse integrated energy systems, E ci The actual carbon emission of each device in the greenhouse comprehensive energy system, and c is the carbon trading price; λ represents the increase of the price per stepped carbon transaction, E pi Denotes the total carbon emission of the electricity, gas boiler and CCHP equipment, h denotes the length of the carbon emission interval, E ci And the carbon emission of a thermal power generating unit, a CCHP unit and a gas boiler is shown.
In a possible implementation manner, the function establishing module 83 is specifically configured to:
constructing an electricity purchasing cost model based on the electricity purchasing price;
constructing a gas turbine power generation cost model based on the gas price;
constructing a fuel cost model of the gas boiler based on the efficiency coefficient of the gas boiler;
constructing an equipment operation and maintenance cost model based on the unit operation and maintenance cost of each equipment;
constructing an operation cost calculation model of the greenhouse comprehensive energy system based on the electricity purchase cost model, the gas turbine power generation cost model, the gas boiler fuel cost model and the equipment operation maintenance cost model;
and respectively substituting the energy conversion relation in the demand side parameter and the energy coupling model into the operation cost calculation model and the carbon transaction cost calculation model to obtain the target function.
In one possible implementation, the electricity purchase cost model is:
Figure BDA0003741518110000221
wherein, F 1 Indicating the cost of electricity purchase, P grid (t) represents the power purchase during time period t, C system (t) represents a purchase price for a time period t;
the gas turbine power generation cost model is as follows:
Figure BDA0003741518110000222
wherein, F 2 Represents the cost of power generation of the gas turbine, C gas (t) represents the gas price, η, over a period of time t Gr Representing the efficiency coefficient, P, of the gas turbine gt (t) represents the output electric power of the gas turbine, LHV, over a period of time t gas Indicating a low heating value of natural gas;
the fuel cost model of the gas boiler is as follows:
Figure BDA0003741518110000223
wherein, F 3 Representing the fuel cost of the gas boiler. C gas (t) represents the gas price over a period of time t, H gb (t) represents the output thermal power, η, of the gas boiler over a time period t gb Representing an efficiency coefficient of the gas boiler;
the equipment operation and maintenance cost model is as follows:
Figure BDA0003741518110000224
wherein, F 4 Represents the cost of operating and maintaining the equipment, k i Represents the unit operating maintenance cost, P, of the equipment i i (t) represents the input power at which device i operates during time period t;
the objective function is:
Figure BDA0003741518110000231
wherein F represents the operation economic cost of the greenhouse integrated energy system, and E represents the total emission of carbon-containing pollutant gases of the greenhouse integrated energy system.
In a possible implementation manner, the model building module 81 is specifically configured to:
establishing an energy coupling model of the greenhouse comprehensive energy system based on the conversion efficiency parameters of various energy conversion devices and the device parameters of various energy storage devices;
and establishing an equipment constraint model of the greenhouse comprehensive energy system based on the safe operation parameters of various energy conversion equipment and various energy storage equipment.
In one possible implementation, the parameter optimization module 84 is specifically configured to:
linearizing the target function to obtain a linear target function; the linear objective function is:
Figure BDA0003741518110000232
wherein Z represents a system multi-objective optimization expectation; f represents the optimal value of the operating economic cost of the greenhouse integrated energy system, omega 1 Weighting factor, ω, representing economic objective optimization 2 Weighting factor, omega, representing an optimization of an environmental objective 1 +ω 2 ＝ 1，(0≤ω 1 ≤1，0≤ω 2 ≤1)；
And optimizing the operation parameters of the greenhouse comprehensive energy system based on the equipment constraint model and the objective function by taking the minimum operation cost and the minimum carbon transaction cost as optimization targets to obtain the optimized operation parameters of the greenhouse comprehensive energy system.
The embodiment of the invention takes the minimum carbon transaction cost as the target, optimizes the operation parameters of the greenhouse comprehensive energy system through the multi-objective mathematical model on the premise of meeting the parameters on the demand side, and the optimized operation parameters can realize the layered regulation and control of the greenhouse comprehensive energy system.
Fig. 9 is a schematic diagram of a terminal according to an embodiment of the present invention. As shown in fig. 9, the terminal 9 of this embodiment includes: a processor 90, a memory 91 and a computer program 92 stored in said memory 91 and executable on said processor 90. The processor 90, when executing the computer program 92, implements the steps of the embodiments of the method for regulating and controlling the greenhouse integrated energy system described above. Alternatively, the processor 90 implements the functions of the modules/units in the above device embodiments when executing the computer program 92.
Illustratively, the computer program 92 may be partitioned into one or more modules/units that are stored in the memory 91 and executed by the processor 90 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 92 in the terminal 9. For example, the computer program 52 may be divided into modules/units 81 to 84 shown in fig. 8.
The terminal 9 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal 9 may include, but is not limited to, a processor 90, a memory 91. It will be appreciated by those skilled in the art that fig. 9 is merely an example of a terminal 9 and does not constitute a limitation of the terminal 9, and may include more or fewer components than shown, or some components may be combined, or different components, e.g., the terminal may also include input-output devices, network access devices, buses, etc.
The Processor 90 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 91 may be an internal storage unit of the terminal 9, such as a hard disk or a memory of the terminal 9. The memory 91 may also be an external storage device of the terminal 9, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) and the like provided on the terminal 9. Further, the memory 91 may also include both an internal storage unit and an external storage device of the terminal 9. The memory 91 is used for storing the computer program and other programs and data required by the terminal. The memory 91 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the technical solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal and method may be implemented in other ways. For example, the above-described apparatus/terminal embodiments are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the method according to the above embodiments of the present invention can also be implemented by a computer program, which can be stored in a computer readable storage medium, and when the computer program is executed by a processor, the steps of the embodiments of the regulation and control method for a greenhouse integrated energy system can be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U.S. disk, removable hard disk, magnetic diskette, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signal, telecommunications signal, and software distribution medium, etc. It should be noted that the computer readable medium may contain other components which may be suitably increased or decreased as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media which may not include electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.

Claims (10)

1. A regulation and control method for a greenhouse integrated energy system is characterized in that the greenhouse integrated energy system comprises a plurality of energy conversion devices and a plurality of energy storage devices, and the method comprises the following steps:
establishing an energy coupling model and an equipment constraint model of the greenhouse comprehensive energy system based on the equipment parameters of the multiple energy conversion equipment and the multiple energy storage equipment;
establishing a carbon trading cost calculation model of the greenhouse integrated energy system based on the carbon emission quota of the greenhouse integrated energy system and the carbon emission parameters of the multiple kinds of energy conversion equipment;
establishing a target function based on the demand side parameters of the greenhouse comprehensive energy system and the energy coupling model calculation model;
and optimizing the operation parameters of the greenhouse comprehensive energy system based on the equipment constraint model and the objective function by taking the minimum operation cost and the minimum carbon transaction cost as optimization targets, and regulating and controlling the greenhouse comprehensive energy system based on the operation parameters.
2. The method for regulating and controlling the greenhouse integrated energy system as claimed in claim 1, wherein the greenhouse integrated energy system obtains electric energy by purchasing electricity, performs gas-heat energy conversion by a gas boiler, and performs energy coupling by a CCHP (combined cycle power plant);
the method comprises the following steps of establishing a carbon trading cost calculation model of the greenhouse integrated energy system based on the carbon emission quota of the greenhouse integrated energy system and the carbon emission parameters of the multiple energy conversion devices, wherein the carbon trading cost calculation model comprises the following steps:
determining the uncompensated carbon emission quota of the greenhouse integrated energy system;
establishing a power purchase carbon emission calculation model based on the unit electric quantity carbon emission;
establishing a carbon emission calculation model of the gas boiler based on the carbon emission of unit heat;
establishing a CCHP carbon emission calculation model based on the carbon emission of unit heat and the conversion coefficient of the power generation and heat supply of the CCHP equipment;
and determining a carbon transaction cost calculation model of the greenhouse integrated energy system based on the gratuitous carbon emission quota, the electricity purchasing carbon emission calculation model, the gas boiler carbon emission calculation model and the CCHP carbon emission model.
3. The method for regulating and controlling the greenhouse integrated energy system according to claim 2, wherein the model for calculating the amount of purchased electrical carbon emission is:
E h ＝δ p P buy
wherein, E h Represents the amount of carbon emission, delta, of electricity purchase p Represents the carbon emission per unit of electricity, P buy Indicating the electricity purchasing quantity;
the model for calculating the carbon emission of the gas boiler comprises the following steps:
E gb ＝δ h H gb (t)
wherein, E gb Represents the carbon emission amount, delta, of the gas boiler h Represents the carbon emission per unit heat, H gb (t) the heat production of the gas boiler;
the CCHP carbon emission calculation model comprises the following steps:
Figure FDA0003741518100000021
wherein E is cchp Represents the carbon emission, δ, of the CCHP plant h Represents the carbon emission per unit heat, Q eb (t) represents the heat supply of the electric boiler, Q hb (t) represents the heat supply amount of the exhaust-heat boiler, Q er (t) represents refrigerating capacity, Q of the refrigerating machine of the electric refrigerator ac (t) represents the refrigerating capacity of the absorption refrigerating machine, P gt (t) represents the amount of power supplied to the gas turbine,
Figure FDA0003741518100000022
representing the power generation-heat supply amount conversion coefficient;
the carbon transaction cost calculation model is as follows:
Figure FDA0003741518100000023
in the formula, C co2 Cost of carbon trading for said greenhouse integrated energy system, E ci C is the actual carbon emission of each device in the greenhouse comprehensive energy system, and c is the carbon trading price; λ represents the increase of the price per stepped carbon transaction, E pi Represents the total carbon emission of the electricity purchase, the gas boiler and the CCHP equipment, h represents the length of the carbon emission interval, E ci And the carbon emission of a thermal power generating unit, a CCHP unit and a gas boiler is shown.
4. The method for regulating and controlling the greenhouse integrated energy system according to claim 1, wherein the establishing of the objective function based on the demand-side parameters of the greenhouse integrated energy system and the energy coupling model calculation model comprises:
constructing an electricity purchasing cost model based on the electricity purchasing price;
constructing a gas turbine power generation cost model based on the gas price;
constructing a fuel cost model of the gas boiler based on the efficiency coefficient of the gas boiler;
constructing an equipment operation and maintenance cost model based on the unit operation and maintenance cost of each equipment;
constructing an operation cost calculation model of the greenhouse comprehensive energy system based on the electricity purchasing cost model, the gas turbine power generation cost model, the gas boiler fuel cost model and the equipment operation and maintenance cost model;
and respectively substituting the energy conversion relation in the demand side parameter and the energy coupling model into the operation cost calculation model and the carbon transaction cost calculation model to obtain a target function.
5. The method for regulating and controlling the greenhouse integrated energy system according to claim 4, wherein the electricity purchasing cost model is:
Figure FDA0003741518100000031
wherein, F 1 Indicating the cost of electricity purchase, P grid (t) represents the power purchased during time t, C system (t) represents a purchase price for a time period t;
the gas turbine power generation cost model is as follows:
Figure FDA0003741518100000032
wherein, F 2 Represents the cost of electricity generation of the gas turbine, C gas (t) represents the gas price, eta, over a period of time t GT Representing the coefficient of efficiency, P, of the gas turbine gt (t) denotes a period tOutput electric power of internal gas turbine, LHV gas Indicating a low heating value of natural gas;
the fuel cost model of the gas boiler is as follows:
Figure FDA0003741518100000033
wherein, F 3 Representing the fuel cost of the gas boiler. C gas (t) represents the gas price over a period of time t, H gb (t) represents the output thermal power of the gas boiler, η, over a time period t gb Representing an efficiency coefficient of the gas boiler;
the equipment operation and maintenance cost model is as follows:
Figure FDA0003741518100000034
wherein, F 4 Represents the cost of operating and maintaining the equipment, k i Indicating the unit operating maintenance cost, P, of the equipment i i (t) represents the input power at which device i operates during time period t;
the objective function is:
Figure FDA0003741518100000035
wherein F represents the operation economic cost of the greenhouse integrated energy system, and E represents the total emission of carbon-containing pollutant gases of the greenhouse integrated energy system.
6. The method for regulating and controlling the greenhouse integrated energy system according to any one of claims 1 to 5, wherein the establishing an energy coupling model and an equipment constraint model of the greenhouse integrated energy system based on the equipment parameters of the plurality of energy conversion equipment and the plurality of energy storage equipment comprises:
establishing an energy coupling model of the greenhouse comprehensive energy system based on the conversion efficiency parameters of the multiple kinds of energy conversion equipment and the equipment parameters of the multiple kinds of energy storage equipment;
and establishing an equipment constraint model of the greenhouse comprehensive energy system based on the safe operation parameters of the multiple energy conversion equipment and the multiple energy storage equipment.
7. The method for controlling the greenhouse integrated energy system according to any one of claims 1 to 5, wherein the optimizing the operating parameters of the greenhouse integrated energy system based on the equipment constraint model and the objective function with the minimum operating cost and the minimum carbon trading cost as optimization objectives comprises:
linearizing the target function to obtain a linear target function; the linear objective function is:
Figure FDA0003741518100000041
wherein Z represents a system multi-objective optimization expectation; f represents the optimal value of the operating economic cost of the greenhouse integrated energy system, omega 1 Weighting factor, ω, representing economic objective optimization 2 Weighting factor, omega, representing an optimization of an environmental objective 1 +ω 2 ＝1，(0≤ω 1 ≤1,0≤ω 2 ≤1)；
And optimizing the operation parameters of the greenhouse comprehensive energy system based on the equipment constraint model and the objective function by taking the minimum operation cost and the minimum carbon transaction cost as optimization targets to obtain the optimized operation parameters of the greenhouse comprehensive energy system.
8. A regulation and control device of a greenhouse comprehensive energy system is characterized by comprising:
the model establishing module is used for establishing an energy coupling model and an equipment constraint model of the greenhouse comprehensive energy system based on the equipment parameters of the multiple kinds of energy conversion equipment and the multiple kinds of energy storage equipment;
the cost calculation module is used for establishing a carbon transaction cost calculation model of the greenhouse integrated energy system based on the carbon emission quota of the greenhouse integrated energy system and the carbon emission parameters of the multiple energy conversion devices;
the function establishing module is used for establishing a target function based on the demand side parameters of the greenhouse comprehensive energy system and the energy coupling model calculation model;
and the parameter optimization module is used for optimizing the operation parameters of the greenhouse comprehensive energy system based on the equipment constraint model and the objective function by taking the minimum operation cost and the minimum carbon transaction cost as optimization targets, and regulating and controlling the greenhouse comprehensive energy system based on the operation parameters.
9. A terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor when executing the computer program performs the steps of the method for regulating and controlling the greenhouse integrated energy system as claimed in any one of the preceding claims 1 to 7.
10. A computer-readable storage medium, in which a computer program is stored, wherein the computer program, when being executed by a processor, implements the steps of the method for regulating and controlling an integrated energy system for greenhouses according to any one of claims 1 to 7.
CN202210817689.1A 2022-07-12 2022-07-12 Regulating and controlling method, device, terminal and storage medium of greenhouse comprehensive energy system Pending CN115186902A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115660258A (en) * 2022-12-09 2023-01-31 南方电网数字电网研究院有限公司 Carbon reduction assessment method and device for comprehensive energy system and computer equipment
CN116131249A (en) * 2022-11-30 2023-05-16 淮阴工学院 Temperature control power supply system and temperature control power supply method for small building
CN116976528A (en) * 2023-09-22 2023-10-31 国网江苏省电力有限公司常州供电分公司 Optimal configuration method and device for low-carbon port hybrid energy supply system

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116131249A (en) * 2022-11-30 2023-05-16 淮阴工学院 Temperature control power supply system and temperature control power supply method for small building
CN115660258A (en) * 2022-12-09 2023-01-31 南方电网数字电网研究院有限公司 Carbon reduction assessment method and device for comprehensive energy system and computer equipment
CN115660258B (en) * 2022-12-09 2023-08-11 南方电网数字电网研究院有限公司 Comprehensive energy carbon reduction evaluation method and device considering optimal carbon emission planning
CN116976528A (en) * 2023-09-22 2023-10-31 国网江苏省电力有限公司常州供电分公司 Optimal configuration method and device for low-carbon port hybrid energy supply system
CN116976528B (en) * 2023-09-22 2023-12-12 国网江苏省电力有限公司常州供电分公司 Optimal configuration method and device for low-carbon port hybrid energy supply system

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