Multi-energy network system modeling method based on energy concentrator

Abstract

The invention provides a multi-energy network system modeling method based on an energy concentrator, and relates to the technical field of integrated energy system modeling. The method comprises the following steps: S1, constructing an energy concentrator model; s2, performing optimization processing on the existing power network model, natural gas network model and thermal network model, and constructing a power network optimization model, a natural gas network optimization model and a thermal network optimization model; s3, constructing a coupling equipment model; and S4, based on the models constructed in the steps S1 to S3, integrating a plurality of energy internet, and constructing a multi-energy network system model. According to the multi-energy network system modeling method based on the energy concentrator, the defects of multi-energy network system modeling in the prior art are overcome, especially the defects in the aspect of processing energy interaction and coupling relations among multiple energy internets are overcome, and therefore the overall energy utilization efficiency and operation flexibility of the system are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of integrated energy system modeling, and particularly relates to a multi-energy grid system modeling method based on an energy concentrator. BACKGROUND

[0002] At present, a multi-energy grid system is usually composed of multiple regional energy internets. Each energy internet usually contains multiple energy subsystems such as power networks, natural gas networks and heat networks, and realizes the conversion and complementation between different forms of energy through coupling devices such as combined cooling heating and power (CCHP), ground source heat pump and electric-to-gas, so as to improve the energy utilization efficiency and energy supply flexibility in the region. Multiple energy internets are further interconnected to form a multi-energy grid system in a larger range, which can significantly enhance the overall energy coordination capability and operation flexibility of the system.

[0003] However, the existing energy internet system modeling methods mostly focus on the multi-energy coupling and complementary mechanism within a single energy internet, and fail to fully reflect the complex cross-regional multi-energy coupling and complementary relationship between multiple energy internets, such as cross-network power assistance, gas / heat transmission, energy carrier conversion and sharing. The existing technology has obvious deficiencies in constructing a global and multi-level coupled model of the multi-energy grid system, which makes it difficult for the existing model to comprehensively describe the global operation characteristics of the multi-energy grid system.

[0004] With the continuous expansion of the energy internet and its rising status in the energy system, it has become increasingly urgent to construct a system model that can accurately represent the multi-energy coupling and complementary relationship within and between networks. Therefore, it is urgent to develop a new modeling method that can comprehensively consider the multi-level and cross-regional energy flow and conversion mechanism to support the further improvement of the multi-energy grid system in terms of efficient operation and flexible energy supply. SUMMARY

[0005] The purpose of the present application is to provide a multi-energy grid system modeling method based on an energy concentrator, which overcomes the deficiencies of the prior art in modeling the multi-energy grid system, especially in handling the energy interaction and coupling relationship between multiple energy internets, so as to improve the overall energy utilization efficiency and operation flexibility of the system.

[0006] To achieve the above purpose, the present application provides a multi-energy grid system modeling method based on an energy concentrator, comprising the following steps: Step S1, constructing an energy concentrator model; Step S2, optimizing the existing power network model, natural gas network model and heat network model to construct a power network optimization model, a natural gas network optimization model and a heat network optimization model; Step S3, constructing a coupling device model; Step S4, based on the model constructed in steps S1-S3, integrating multiple energy internet, constructing a multi-energy grid system model.

[0007] Preferably, step S1 comprises: Step S101, constructing an energy conversion element input-output model; Step S102, constructing an energy storage element input-output model; Step S103, constructing a distributed renewable energy element input-output model.

[0008] Preferably, in step S101, the specific expression of the energy conversion element input-output model is: ; Wherein, , , , respectively represent the output power of the first energy conversion element at time electricity, natural gas, heat, and cold energy; , , , respectively represent the input power of the first energy conversion element at time electricity, natural gas, heat, and cold energy; represents the efficiency of the first energy conversion element from electricity to electricity; represents the efficiency of the first energy conversion element from electricity to natural gas; represents the efficiency of the first energy conversion element from electricity to heat; represents the efficiency of the first energy conversion element from electricity to cold; represents the efficiency of the first energy conversion element from natural gas to electricity; represents the efficiency of the first energy conversion element from natural gas to natural gas; represents the efficiency of the first energy conversion element from natural gas to heat; represents the efficiency of the first energy conversion element from natural gas to cold; represents the efficiency of the first energy conversion element from heat to electricity; represents the efficiency of the first Efficiency of the energy conversion element from thermal energy to natural gas; Efficiency of the energy conversion element from thermal energy to thermal energy; Efficiency of the energy conversion element from thermal energy to cold energy; Efficiency of the energy conversion element from cold energy to electric energy; Efficiency of the energy conversion element from cold energy to natural gas; Efficiency of the energy conversion element from cold energy to thermal energy; Efficiency of the energy conversion element from cold energy to cold energy; Efficiency of the energy conversion element from cold energy to natural gas; Efficiency of the energy conversion element from cold energy to thermal energy; Efficiency of the energy conversion element from cold energy to cold energy; When the energy hub contains an energy multiple-input multiple-output link, one energy can be provided through multiple ways; to describe this energy distribution engineering, a distribution coefficient is introduced ; the specific expression is: ; ; ; ; wherein, Pm,n represents the power of the energy distributed to the nth coupled link; ;

[0009] Preferably, in step S102, the specific expression of the energy storage element input-output model is: ; ; ; ; ; ; ; ; ; ; ; ; ; ;​​​​​ ; ; wherein, denotes the state of charge of the energy storage element at time t; , , denote the state of charge of the electrical storage element, the gaseous storage element, the thermal storage element at time t, respectively; denotes the matrix transpose; denotes the state of charge of the energy storage element at time t; , , denote the state of charge of the electrical storage element, the gaseous storage element, the thermal storage element at time t, respectively; denotes the charging efficiency of the energy storage element; , , denote the charging efficiency of the electrical storage element, the gaseous storage element, the thermal storage element, respectively; denotes the discharging efficiency of the energy storage element; , , denote the discharging efficiency of the electrical storage element, the gaseous storage element, the thermal storage element, respectively; denotes the rated capacity of the energy storage element; , , denote the rated capacity of the electrical storage element, the gaseous storage element, the thermal storage element, respectively; denotes the charging power of the energy storage element at time t; , , denote the charging power of the electrical storage element, the gaseous storage element, the thermal storage element at time t, respectively; denotes the discharging power of the energy storage element at time t; , , denote the discharging power of the electrical storage element, the gaseous storage element, the thermal storage element at time t, respectively; denotes the upper limit of the charging power of the energy storage element; , , denote the upper limit of the charging power of the electrical storage element, the gaseous storage element, the thermal storage element, respectively; denotes the upper limit of the discharging power of the energy storage element; , , respectively represent the upper limit of discharging power of the electricity storage element, the gas storage element, and the heat storage element; represent the upper limit of state of charge of the energy storage element; , , respectively represent the upper limit of state of charge of the electricity storage element, the gas storage element, and the heat storage element; represent a time period; represent the state of charge of the energy storage element at a time instant; represent the state of charge of the energy storage element at a time instant.

[0010] Preferably, step S2 comprises: Step S201, constructing a power network optimization model, including a wind power output model and a distributed photovoltaic power output model; Step S202, constructing a natural gas network optimization model, including a natural gas pipeline model and a gas turbine driven compressor model; Step S203, constructing a heat network optimization model, including a heat network hydraulic model, a heat network thermal model, and a heat storage tank model.

[0011] Preferably, in step S201, the wind power output model is constructed based on a Weibull distribution function, and the specific expression is as follows: ; ; ; ; ; ; wherein, represents the wind speed; represents the Weibull distribution function of the wind speed ; represents a shape parameter; represents a scale parameter; represents the annual average wind speed of the selected region; represents a natural constant; represents a standard deviation; represents a Gamma function; represents the cut-in wind speed; represents the rated wind speed; represents the cut-out wind speed; represents the rated output power of the wind turbine generator set; represents the slope of the wind turbine generator set power-wind speed curve; represents the intercept of the linear segment of the wind turbine power-wind speed curve; represents the output electric power of the wind turbine.

[0012] Preferably, in step S201, a distributed photovoltaic power generation output model is constructed based on a Beta distribution function, and the specific expression is as follows: ; ; ; ; wherein, represents the distributed photovoltaic power generation output; represents the light intensity; represents the photovoltaic component area; represents the photoelectric conversion rate; , represents the shape parameter of the Beta distribution function; represents the normalized light intensity; represents the mean value of the light intensity; represents the variance of the light intensity; represents the Beta distribution function of the light intensity.

[0013] Preferably, in step S202, the specific expression of the natural gas pipeline model is as follows: ; ; wherein, represents the pipeline natural gas flow; represents the natural gas flow direction in the pipeline; , respectively represent the node pressure and the node pressure in the natural gas network.

[0014] Preferably, in step S202, the specific expression of the gas turbine driven compressor model is as follows: ; ; ; wherein, represents the electric power when the gas turbine driven compressor is working; represents the natural gas flow when the gas turbine driven compressor is working; represents the gas turbine driven compressor temperature; represents the gas turbine-driven compressor efficiency; represents the gas adiabatic index; represents the gas turbine-driven compressor flow consumption; 、 、 represents the energy efficiency conversion coefficient; represents the comprehensive performance index; represents the thermodynamic index.

[0015] Preferably, the step S3 comprises: Step S301, constructing a gas turbine model; Step S302, constructing a combined heat and power unit model; Step S303, constructing an electric-gas conversion device model; Step S304, constructing a combined cooling, heating and power model, including an internal combustion engine system model and a ground source heat pump model; Step S305, constructing a gas boiler model and a compression refrigeration unit model.

[0016] Therefore, the present application adopts the above-mentioned multi-energy network system modeling method based on an energy concentrator, and has the following beneficial technical effects: The present application innovatively introduces an energy concentrator model, systematically describes the cross-regional energy coupling and complementary relationship between multiple energy internets, breaks through the limitation of traditional modeling methods which are only limited to the multi-energy coupling and complementarity within a single energy internet, and realizes the overall characterization of the multi-energy network system. By linearizing the existing power network model and establishing an optimization model of the natural gas network and the heat network, the solving complexity of the multi-energy network system model is significantly reduced, and the calculation efficiency and practicability are improved.

[0017] In addition, the present application uses probability distribution functions (such as Weibull distribution function and Beta distribution function) to describe the uncertainty and volatility of renewable energy power generation such as wind power and photovoltaic power, enhances the adaptability and accuracy of the model to the renewable energy access environment. By establishing various coupling device models including gas turbines, combined heat and power, electric-gas conversion and combined cooling, heating and power, the relationship between energy conversion and flow within the multi-energy network system is clearly revealed, laying a solid model foundation for system collaborative operation and multi-energy complementary optimization. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is a flow chart of the multi-energy network system modeling method based on an energy concentrator of the present application; Figure 2 is a structure diagram of the multi-energy network system model. DETAILED DESCRIPTION

[0019] The technical solution of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0020] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0021] Example 1 like Figure 1 As shown, a multi-energy network system modeling method based on energy hubs includes the following steps: Step S1: Based on the concept of energy hub, construct an energy hub model to reflect the multi-energy coupling and complementarity process between multi-energy grid systems.

[0022] Step S101: Construct the input and output model of the energy conversion element.

[0023] An energy hub is defined as a controllable unit capable of converting, distributing, and storing multiple energy sources; it can be viewed as an interface between energy input and energy demand. Inside the energy hub, input energy undergoes energy conversion and storage to form output energy.

[0024] The specific expression for the input-output model of the energy conversion element is as follows: ; in, , , , They represent Time of the first The output power of each energy conversion element for electrical energy, natural gas, heat energy, and cold energy; , , , They represent Time of the first The input power of each energy conversion element, including electrical energy, natural gas, thermal energy, and cold energy; Indicates the first The efficiency of an energy conversion element in converting electrical energy into electrical energy; Indicates the first The efficiency of an energy conversion element in converting electrical energy into natural gas; Indicates the first The efficiency of an energy conversion element in converting electrical energy into heat energy; Indicates the first The efficiency of an energy conversion element in converting electrical energy into cold energy; Indicates the first The efficiency of an energy conversion element in converting natural gas into electricity; Indicates the first The efficiency of an energy conversion element in converting natural gas to natural gas; Indicates the first The efficiency of an energy conversion element in converting natural gas into heat energy; Indicates the first The efficiency of an energy conversion element in converting natural gas into cold energy; Indicates the first The efficiency of an energy conversion element in converting heat energy into electrical energy; Indicates the first The efficiency of an energy conversion element in converting heat energy into natural gas; Indicates the first The efficiency of an energy conversion element in converting heat energy to heat energy; Indicates the first The efficiency of an energy conversion element in converting heat energy into cold energy; Indicates the first The efficiency of an energy conversion element in converting cold energy into electrical energy; Indicates the first The efficiency of an energy conversion element in converting cold energy into natural gas; Indicates the first The efficiency of an energy conversion element in converting cold energy into heat energy; Indicates the first The efficiency of an energy conversion element in converting cold energy to cold energy.

[0025] When an energy hub includes multiple-input multiple-output (MIMO) components, a single energy source can be provided through multiple pathways. To describe this energy distribution process, a distribution factor is introduced. The specific expression is: ; ; in, Indicates allocation to the first Energy of each coupling link The power; Indicates energy Total input power.

[0026] Step S102: Construct the input-output model of the energy storage element.

[0027] Energy hubs can store electrical energy, natural gas, and thermal energy. The energy storage elements in an energy hub include electrical storage elements, gas storage elements, and thermal storage elements. The specific expressions for the input-output model of the energy storage elements are as follows: ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; in, express The state of charge of the energy storage element at any given time; , , They represent The state of charge of the energy storage element, gas storage element, and heat storage element at all times; Indicates matrix transpose; express The state of charge of the energy storage element at any given time; , , They represent The state of charge of the energy storage element, gas storage element, and heat storage element at all times; Indicates the charging efficiency of energy storage components; , , These represent the charging efficiencies of the energy storage element, gas storage element, and heat storage element, respectively. This indicates the energy release efficiency of the energy storage element; , , These represent the energy release efficiencies of the energy storage element, gas storage element, and heat storage element, respectively. Indicates the rated capacity of the energy storage element; , , These represent the rated capacities of the energy storage element, gas storage element, and heat storage element, respectively. express The charging power of the energy storage element at any given time; , , They represent charging power of the energy storage element at the moment; denotes discharging power of the energy storage element at the moment; , , denote discharging power of the energy storage element, the gas storage element and the heat storage element at the moment, respectively; denotes the upper limit of the charging power of the energy storage element; , , denote the upper limit of the charging power of the energy storage element, the gas storage element and the heat storage element, respectively; denotes the upper limit of the discharging power of the energy storage element; , , denote the upper limit of the discharging power of the energy storage element, the gas storage element and the heat storage element, respectively; denotes the upper limit of the state of charge of the energy storage element; , , denote the upper limit of the state of charge of the energy storage element, the gas storage element and the heat storage element, respectively; denotes a time period; denotes the state of charge of the energy storage element at the moment; denotes the state of charge of the energy storage element at the moment.

[0028] Step S103, constructing a distributed renewable energy element input-output model.

[0029] With the increasing application of renewable energy integration in the energy internet, the modeling of energy concentrators also faces new requirements. Unlike traditional energy inputs, the intermittency and uncertainty of renewable energy make it impossible to match the energy demand of users in real time. When the output of renewable energy is excessive, the energy concentrator can adopt two processing methods: one is to store the remaining energy locally, and the other is to return the remaining energy to the upper energy subsystem.

[0030] To describe the integration form of distributed renewable energy, the matrix is introduced in the present application. denotes the power corresponding to the return of various energies (such as electric energy and heat energy) by the energy concentrator to the upper energy subsystem. Based on , a distributed renewable energy element input-output model is established, and the specific expression is as follows: ; wherein, denotes the energy output power; a coupling matrix; a storage energy source vector; a renewable energy input vector; a traditional energy input vector; a storage energy correlation matrix.

[0031] Step S2, the existing power network model, natural gas network model, heat network model is optimized, and the power network optimization model, natural gas network optimization model, heat network optimization model is constructed.

[0032] Step S201, constructing a power network optimization model, including a wind power generation output model and a distributed photovoltaic power generation output model.

[0033] To solve the problem of existing power network model solving complex, low calculation efficiency, the existing power network model can be optimized by linearization processing. The DC power flow model does not consider the reactive power and voltage amplitude constraint of the power network, and because the resistance in the power network is much smaller than the reactance, the line resistance and the branch resistance to ground can be ignored, which leads to the voltage change between nodes in the power network is very small, and the voltage phase angle difference between nodes is also very small. Therefore, the DC power flow modeling is adopted, and the specific expression of the generated power network optimization model is: ; wherein, represents the active power between node and node ; represents the phase angle difference between node and node ; represents the impedance of the line between node and node .

[0034] The power generation output of the wind turbine is related to the wind speed. Because the wind speed changes constantly, the actual available wind speed for power generation will fluctuate with time, which leads to the power generation output of the wind turbine has volatility and intermittency. Currently, the Weibull distribution function is commonly used to describe the change of wind speed, and the specific expression is as follows: ; ; ; wherein, represents the wind speed; represents the Weibull distribution function of the wind speed ; represents the shape parameter; represents the scale parameter; represents the average annual wind speed of the selected region; represents a natural constant; represents a standard deviation; represents the Gamma function.

[0035] According to the distribution of wind speed, the functional relationship between the wind turbine and the wind speed, i.e., the wind power generation output model, can be obtained, and the specific expression is as follows: ; ; ; wherein, represents the cut-in wind speed; represents the rated wind speed; represents the cut-out wind speed; represents the rated output power of the wind turbine; represents the slope of the wind turbine power-wind speed curve; represents the intercept of the wind turbine power-wind speed curve in the linear section; represents the output electric power of the wind turbine.

[0036] The distributed photovoltaic power generation output is directly related to the light intensity. The specific expression of the distributed photovoltaic power generation output model is as follows: ; wherein, represents the distributed photovoltaic power generation output; represents the light intensity; represents the photovoltaic component area; represents the photoelectric conversion rate.

[0037] However, in actual operation, the uncertainty of the distributed photovoltaic power generation output is mainly related to the light intensity of the location where it is located. Therefore, the Beta distribution function can be used to describe the probability distribution of the light intensity, and the specific expression is as follows: ; ; ; wherein, , represents the shape parameter of the Beta distribution function; represents the normalized light intensity; represents the average value of the light intensity; represents the variance of the light intensity; represents the Beta distribution function of the light intensity.

[0038] Step S202, constructing a natural gas network optimization model, including a natural gas pipeline model and a gas turbine driven compressor model.

[0039] The natural gas network includes a gas source, a pipeline, a compressor and a natural gas load. Since the natural gas network is similar to the power network and also contains two major parts of nodes and branches, the modeling method of the power network is analogously applied to the natural gas network for modeling.

[0040] The pipeline in the natural gas network is the only medium for supplying natural gas from the gas source to the user end. In the modeling process of the natural gas pipeline model, the operating condition thereof can be represented by a gas flow equation. In constructing the natural gas pipeline model, the influence of factors such as kinetic energy change and gas compressibility is usually ignored, and a pipeline resistance coefficient is introduced to comprehensively reflect the loss caused by the pipeline itself and the external environment. The node gas pressure in the natural gas network is a key state variable, and the solving logic thereof in the natural gas pipeline model is similar to the node voltage in the power network. Under the steady-state operating condition, the specific expression of the natural gas pipeline model is as follows: ; ; wherein, represents the pipeline natural gas flow rate; represents the pipeline natural gas flow direction; , respectively represent the node gas pressure and the node gas pressure in the natural gas network.

[0041] The compressor is usually divided into a motor driven type and a gas turbine driven type. When the compressor is driven by the gas turbine, the energy consumption thereof is mainly related to the flow rate of the gas flowing through and the pressure difference between the first end and the last end of the pipeline. The specific expression of the gas turbine driven compressor model is as follows: ; ; ; wherein, represents the electric power consumed by the gas turbine driven compressor when working; represents the natural gas flow rate through the gas turbine driven compressor when working; represents the temperature of the gas turbine driven compressor; represents the efficiency of the gas turbine driven compressor; represents the gas adiabatic index, which is generally taken as 1.3; represents the flow rate consumed by the gas turbine driven compressor; , , represents the energy efficiency conversion coefficient; represents the comprehensive performance coefficient; represents the thermodynamic index.

[0042] In the process of building the gas turbine driven compressor model, the node flow balance rule needs to be followed, and the specific expression of the node flow balance equation is: ; wherein, represents the gas supply flow rate of the gas source connected to the node at the moment; represents the gas supply flow rate of the gas source connected to the node at the moment; represents the gas supply flow rate of the gas source connected to the node at the moment; represents the gas supply flow rate of the gas source connected to the node at the moment; represents the gas supply flow rate of the gas source connected to the node at the moment; represents all the nodes connected to the node at the moment; represents all the nodes connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment; represents the natural gas injection flow rate of the pipeline connected to the node at the moment;

[0043] Step S203, building a heat network optimization model, including a heat network hydraulic model, a heat network thermodynamic model and a heat storage tank model.

[0044] The flow of hot water in the heat network needs to satisfy the network basic law: first, the flow rate of each pipeline at any node should satisfy the flow continuity equation, that is, the total flow rate injected into the node is equal to the total flow rate flowing out of the node; second, in any closed loop formed by pipelines, the algebraic sum of the pressure head losses caused by the flow of hot water in each section is zero.

[0045] Therefore, the construction of the heat network hydraulic model needs to satisfy the above constraint conditions, and the specific expression is as follows: ;​ ; ; wherein, represents the node-branch incidence matrix of the heat network; represents the flow of each pipe; represents the flow out of each node; represents the loop-branch incidence matrix of the heat network; represents the algebraic sum and matrix of pressure drop of each loop of the heat network; represents the flow of each pipe section; represents the resistance coefficient of each pipe section; represents the potential difference column vector of two nodes in the heat network; represents the actual head increase column vector of the water pump in the pipe section, and for the branch without water pump, = 0.

[0046] In the hydraulic model of the heat network, the flow distribution and pressure distribution of each pipe section need to strictly follow the above constraint conditions, which are specifically as follows: The flow continuity at the node is described by the node-branch incidence matrix of the heat network, the pressure head balance in the loop is described by the loop-branch incidence matrix of the heat network, and the pressure loss of the pipe section is calculated based on the pipe resistance characteristics, and the specific expression is as follows: ; ; ; wherein, represents the pressure loss of the pipe section; represents the resistance loss along the way; represents the unit pipe length loss along the way; represents the length of the pipe section; represents the equivalent length of the pipe section; represents the absolute roughness of the pipe wall, and for the outdoor hot water heating system pipe section, it is usually taken as ; represents the diameter of the pipe section; represents the local resistance loss of the pipe section; represents the density of hot water.

[0047] On the basis of establishing the hydraulic model of the heat network, in order to further characterize the temperature dynamic characteristics of heat energy in the process of transportation and distribution, the heat network thermodynamic model also needs to be built, and the specific expression is as follows: ; ; ; wherein, represents the thermal power of a thermal load node of the heat network; represents the specific heat capacity of hot water; represents the temperature of the end of the pipe; represents the temperature of the initial end of the pipe; represents the ambient temperature; represents the heat conduction coefficient of the pipe; represents the length of the pipe; represents the temperature of hot water before being injected into the thermal load node; represents the temperature of hot water when flowing out of the thermal load node; represents the temperature of hot water flowing out of the thermal load node after mixing with hot water of other pipes at the pipe node; represents the flow rate of hot water flowing out of the thermal load node; , respectively represent the flow rate of hot water in the outflowing and inflowing pipes; , respectively represent the temperature of hot water in the outflowing and inflowing pipes.

[0048] The heat storage tank stores heat by changing the temperature of water, and realizes the stratification of hot water and cold water in the tank according to the density. The specific expression of the heat storage tank model is as follows: ; ; wherein, represents the energy storage efficiency of the heat storage tank, ; represents the energy release efficiency of the heat storage tank, ; represents the heat stored in the heat storage tank at the moment; represents the state of charge of the heat storage tank; represents the rated heat capacity of the heat storage tank; , respectively represent the input and output heat power of the heat storage tank.

[0049] Step S3, constructing a coupling device model to reflect the multi-energy coupling complementary process inside the energy internet.

[0050] Step S301, constructing a gas turbine model.

[0051] The gas turbine as a commonly used coupling device, its working process is: input natural gas from the gas turbine inlet hole, the regenerator preheats high pressure air, the gas temperature is improved in advance, the natural gas and high pressure air are mixed and combusted in the combustion chamber, the pressure is generated to drive the turbine to work to rotate the shaft to cut and generate electricity. The electric energy generated by the gas turbine during the entire operation process can be preferentially supplied to the regional power users; the surplus electric energy can be uploaded to the power network to obtain income through electricity sales, thereby reducing the operation cost. In addition, the heat energy generated by the gas turbine can also be used to meet the regional heat load demand.

[0052] The specific expression of the gas turbine model is as follows: ; ; Among them, represents the power generation power of the gas turbine; represents the gas consumption; represents the conversion coefficient of the gas turbine; , respectively represent the lower limit and the upper limit of the power generation output of the gas turbine; represents the power generation power of the gas turbine at the moment.

[0053] Step S302, construct a combined heat and power unit model.

[0054] The combined heat and power (CHP) unit mainly consists of a gas turbine and a waste heat boiler and the like. Natural gas is combusted in the high-temperature combustion chamber of the combined heat and power unit to generate heat energy, which drives the gas turbine to generate electricity, and the waste heat generated during the electricity generation process is recovered by the waste heat boiler to meet the heat load demand. In order to further improve the model accuracy, the influence of external environment and operating conditions on the power generation efficiency and heat transfer efficiency of the combined heat and power unit also needs to be considered, so the expression of the combined heat and power unit model is: ; ; ; ; ; Among them, represents the total power generated after the combined heat and power unit combusts natural gas; represents the intake amount of the combined heat and power unit; , respectively represent the heat power and the electric power output by the combined heat and power unit; , respectively represent the thermal efficiency and the electric efficiency of the combined heat and power unit; , These represent the upper and lower limits of the output electrical power of the combined heat and power unit, respectively. , These represent the upper and lower limits of the ramp rate for the output power of a combined heat and power (CHP) unit, respectively. This indicates the gas consumption rate of a combined heat and power (CHP) unit.

[0055] Step S303: Construct a model of an electro-gas conversion device.

[0056] The power-to-gas (P2G) equipment can convert surplus electrical energy into gas energy. Its operation process is usually divided into two stages: the first stage is water electrolysis. Phase 2 is and Reforming .

[0057] The expression for the electro-gas conversion equipment model is as follows: ; ; ; ; in, This indicates the amount consumed by the electro-gas conversion equipment; This indicates the volume of natural gas generated by the power-to-gas conversion equipment; This indicates the lower heating value of natural gas. Indicates the efficiency of the electro-gas conversion equipment; Indicates the amount of natural gas required to produce one unit of power. The amount; This indicates the power consumption of the electro-gas conversion equipment; , These represent the minimum and maximum power consumption of the electro-gas conversion equipment, respectively. , These represent the lower and upper limits of the ramp rate for the power consumption of the electro-gas conversion equipment, respectively. This indicates the energy conversion efficiency of the electro-gas conversion equipment.

[0058] Step S304: Construct a combined cooling, heating and power (CCHP) model, including an internal combustion engine system model and a ground source heat pump model.

[0059] A combined cooling, heating and power (CCHP) unit mainly consists of a gas-fired internal combustion engine, a ground source heat pump, a gas-fired hot water boiler, an absorption chiller, and a thermal storage tank.

[0060] The internal combustion engine system mainly includes a gas internal combustion engine and an absorption chiller unit. The gas internal combustion engine works by burning natural gas, which drives a generator to generate electricity on one hand, and on the other hand, the residual heat of the cylinder liner cooling water formed by the cylinder liner cooling device of the gas internal combustion engine can be directly used for heating in winter. In addition, the residual heat of the gas after work in the gas internal combustion engine enters the absorption chiller unit, which can drive the absorption chiller unit to realize summer cooling and winter heating. According to the law of conservation of energy, the expression of the established internal combustion engine system model is as follows: ; ; ; ; ; wherein, represents the natural gas intake; represents the proportion of gas heat; represents the proportion of cylinder liner cooling water heat; represents the cylinder liner cooling water heat; represents the gas heat; when the absorption chiller unit is used for cooling, represents the cooling energy efficiency ratio of the absorption chiller unit; when the absorption chiller unit is used for heating, represents the heating energy efficiency ratio of the absorption chiller unit; when the combined cooling, heating and power unit is used for cooling, represents the cooling power of the combined cooling, heating and power unit; when the combined cooling, heating and power unit is used for heating, represents the heating power of the combined cooling, heating and power unit; represents the power generation of the gas internal combustion engine; represents the power generation efficiency of the gas internal combustion engine; represents the total heat output of the gas internal combustion engine.

[0061] The ground source heat pump is a device that utilizes stable underground geothermal resources to realize bidirectional energy supply, i.e., it can be used for heating and cooling. The ground source heat pump can realize energy transfer from a low-temperature heat source to a high-temperature heat source by inputting a small amount of high-grade energy. The expression of the established ground source heat pump model is as follows: ; ; ; ; ; wherein, represents the power of the ground source heat pump; when the ground source heat pump is used for cooling, This indicates the cooling energy efficiency ratio of a ground source heat pump. When a ground source heat pump is used for heating, This indicates the heating efficiency ratio of a ground source heat pump; when a ground source heat pump is used for cooling, This indicates the cooling capacity of the ground source heat pump. When the ground source heat pump is used for heating, This indicates the heating capacity of the ground source heat pump; This indicates the absorption of geothermal heat; , These represent the inlet water temperature and outlet water temperature on the load side, respectively. , These represent the inlet and outlet water temperatures on the ground source side, respectively. Indicates the mass flow rate of water from the ground source side; Indicates the mass flow rate of water on the load side; Indicates the specific heat of the fluid medium on the ground source side; Indicates the specific heat of the fluid medium on the load side; This indicates the minimum power of a ground source heat pump; This indicates the maximum power of the ground source heat pump.

[0062] Step S305: Construct a gas-fired boiler model and a compression refrigeration unit model.

[0063] The specific expression for the gas-fired boiler (GB) model is as follows: ; ; ; in, This indicates the thermal power generated by the gas-fired boiler; Indicates the efficiency of a gas-fired boiler; Indicates the air intake volume of the gas-fired boiler; This indicates the upper limit of the output of the gas-fired boiler; This indicates the lower limit of the output of the gas-fired boiler; This indicates the upper limit of the ramp rate for the output thermal power of a gas-fired boiler. This indicates the lower limit of the ramp-up rate for the output thermal power of a gas-fired boiler. In refrigeration equipment, the specific expression for the model of a compression refrigeration unit is as follows: ; ; in, express Cooling power of a compression chiller unit model at any given time; express Power consumption of the compression refrigeration unit model at any time; This indicates the refrigeration efficiency ratio of the compression refrigeration unit model; Indicate the minimum refrigeration power of the compression refrigeration unit model; Indicate the maximum refrigeration power of the compression refrigeration unit model.

[0064] Step S4, based on the model constructed in steps S1-S3, integrate multiple energy internet, construct a multi-energy grid system model, as shown in Figure 2

[0065] In the multi-energy grid system model, the energy transmission and conversion between each energy internet is realized through the energy hub model, realizing the energy coupling and complementation between multiple energy internets; and each energy internet internally contains a power network, a heat network, a cold network, a natural gas network and various energy conversion devices and energy storage devices, so in the modeling process, the corresponding power network optimization model, natural gas network optimization model, heat network optimization model and coupling device model are constructed for system analysis and optimization.

[0066] Therefore, the multi-energy grid system modeling method based on the energy hub adopted by the present application overcomes the deficiencies in the prior art in modeling the multi-energy grid system, especially in handling the energy interaction and coupling relationship between multiple energy internets, thereby improving the overall energy utilization efficiency and operation flexibility of the system.

[0067] Finally, it should be noted that: the above examples are only used to illustrate the technical solutions of the present application and not to limit them, although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that: it can still modify or equivalently replace the technical solutions of the present application, and these modifications or equivalent replacements cannot make the modified technical solutions deviate from the spirit and scope of the technical solutions of the present application.​

Claims

1. A multi-energy network system modeling method based on energy hubs, characterized in that, The method comprises the following steps: Step S1, constructing an energy hub model; Step S2, optimizing existing power network models, natural gas network models, and heat network models to construct power network optimization models, natural gas network optimization models, and heat network optimization models; Step S3, constructing a coupling device model; Step S4, based on the models constructed in steps S1-S3, integrating multiple energy internet, and constructing a multi-energy grid system model. 2.The energy hub based multi-energy network system modeling method of claim 1, wherein, Step S1 comprises: Step S101, constructing an energy conversion element input-output model; Step S102, constructing an energy storage element input-output model; Step S103, constructing a distributed renewable energy element input-output model. 3.The energy hub based multi-energy network system modeling method of claim 2, wherein, In step S101, the specific expression of the energy conversion element input-output model is: ； wherein, 、 、 、 respectively represent the output power of the electric energy, the natural gas, the heat energy, and the cold energy of the nth energy conversion element at the time t; respectively represent the input power of the electric energy, the natural gas, the heat energy, and the cold energy of the nth energy conversion element at the time t; 、 、 、 respectively represent the input power of the electric energy, the natural gas, the heat energy, and the cold energy of the nth energy conversion element at the time t; respectively represent the input power of the electric energy, the natural gas, the heat energy, and the cold energy of the nth energy conversion element at the time t; represents the efficiency of the nth energy conversion element from the electric energy to the electric energy; represents the efficiency of the nth energy conversion element from the electric energy to the natural gas; represents the efficiency of the nth energy conversion element from the electric energy to the heat energy; represents the efficiency of the nth energy conversion element from the electric energy to the cold energy; represents the efficiency of the nth energy conversion element from the natural gas to the electric energy; represents the efficiency of the nth energy conversion element from the natural gas to the natural gas; represents the efficiency of the nth energy conversion element from the natural gas to the heat energy; represents the efficiency of the nth energy conversion element from the natural gas to the cold energy; represents the efficiency of the nth energy conversion element from the heat energy to the electric energy; represents the efficiency of the nth energy conversion element from the heat energy to the natural gas; represents the efficiency of the nth energy conversion element from the heat energy to the heat energy; represents the efficiency of the nth energy conversion element from the heat energy to the cold energy; represents the efficiency of the nth energy conversion element from the cold energy to the electric energy; represents the efficiency of the nth energy conversion element from the cold energy to the natural gas; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; represents the efficiency of the nth energy conversion element from the cold energy to the heat energy; ​​the efficiency of the energy conversion element from cold energy to cold energy; When the energy concentrator contains an energy multiple-input multiple-output link, one kind of energy can be provided through multiple ways; to describe this energy distribution engineering, a distribution coefficient is introduced ; the specific expression is: ； ； wherein, Pn represents the power of the energy allocated to the nth coupling link; Ptot represents the total input power of the energy. ​​​ 4. The method of claim 3, wherein, In step S102, the specific expression of the energy storage element input-output model is: ； ； ； ； ； ； ； ； ； ； ； ； ； ； ； ； wherein denotes the state of charge of the energy storage element at the time instant , , denote the state of charge of the electrical storage element, the gaseous storage element, the thermal storage element at the time instant denotes matrix transposition denotes the state of charge of the energy storage element at the time instant , , denote the state of charge of the electrical storage element, the gaseous storage element, the thermal storage element at the time instant denotes the charging efficiency of the energy storage element , , denote the charging efficiency of the electrical storage element, the gaseous storage element, the thermal storage element denotes the discharging efficiency of the energy storage element , , denote the discharging efficiency of the electrical storage element, the gaseous storage element, the thermal storage element denotes the rated capacity of the energy storage element , , denote the rated capacity of the electrical storage element, the gaseous storage element, the thermal storage element denotes the charging power of the energy storage element at the time instant , , denote the charging power of the electrical storage element, the gaseous storage element, the thermal storage element at the time instant denotes the discharging power of the energy storage element at the time instant , , denote the discharging power of the electrical storage element, the gaseous storage element, the thermal storage element at the time instant denotes the upper limit of the charging power of the energy storage element , , denote the upper limit of the charging power of the electrical storage element, the gaseous storage element, the thermal storage element denotes the upper limit of the discharging power of the energy storage element , , denote the upper limit of the discharging power of the electrical storage element, the gaseous storage element, the thermal storage element denotes an upper limit of the state of charge of the energy storage element; , , denotes an upper limit of the state of charge of the energy storage element, respectively; denotes a time period; denotes the state of charge of the energy storage element at the time instant; denotes the state of charge of the energy storage element at the time instant.

5. The energy hub based multi-energy network system modeling method of claim 1, wherein, Step S2 comprises: Step S201, constructing a power network optimization model, including a wind power generation output model and a distributed photovoltaic power generation output model; Step S202, constructing a natural gas network optimization model, including a natural gas pipeline model and a gas turbine-driven compressor model; Step S203, constructing a heat network optimization model, including a heat network hydraulic model, a heat network thermal model, and a heat storage tank model.

6. The energy hub based multi-energy network system modeling method of claim 5, wherein, In step S201, based on the Weibull distribution function, the wind power generation output model is constructed, and the specific expression is as follows: ； ； ； ； ； ； wherein, denotes the wind speed; denotes the wind speed a Weibull distribution function; denotes the shape parameter; denotes the scale parameter; denotes the annual average wind speed of the selected region; denotes the natural constant; denotes the standard deviation; denotes the Gamma function; denotes the cut-in wind speed; denotes the rated wind speed; denotes the cut-out wind speed; denotes the rated output power of the wind turbine generator; denotes the slope of the wind turbine generator power-wind speed curve; denotes the intercept of the wind turbine generator power-wind speed curve at the linear section; denotes the output electric power of the wind turbine generator.

7. The energy hub based multi-energy network system modeling method of claim 6, wherein, In step S201, based on the Beta distribution function, the distributed photovoltaic power generation output model is constructed, and the specific expression is as follows: ； ； ； ； wherein, represents the distributed photovoltaic power generation output; represents the light intensity; represents the photovoltaic module area; represents the photoelectric conversion rate; , represents the shape parameter of the Beta distribution function; represents the normalized light intensity; represents the mean value of the light intensity; represents the variance of the light intensity; represents the Beta distribution function of the light intensity. 8.The energy hub based multi-energy network system modeling method of claim 7, wherein, In step S202, the specific expression of the natural gas pipeline model is: ； ； wherein, represents the pipeline natural gas flow rate; represents the direction of natural gas flow within the pipeline; , respectively represent the node gas pressure and the node gas pressure in the natural gas network. 9.The energy hub based multi-energy network system modeling method of claim 8, wherein, In step S202, the specific expression of the gas turbine-driven compressor model is: ； ； ； wherein, represents the electric power when the gas turbine drives the compressor in operation; represents the natural gas flow rate when the gas turbine drives the compressor in operation; represents the gas turbine driving compressor temperature; represents the gas turbine driving compressor efficiency; represents the gas adiabatic index; represents the flow rate consumed by the gas turbine driving compressor; , , represents the energy efficiency conversion coefficient; represents the comprehensive performance index; represents the thermodynamic index.

10. The energy hub based multi-energy network system modeling method of claim 1, wherein, Step S3 comprises: Step S301, constructing a gas turbine model; Step S302, constructing a combined heat and power unit model; Step S303, constructing an electric-to-gas device model; Step S304, constructing a combined cooling, heating, and power model, including an internal combustion engine system model and a ground source heat pump model; Step S305, constructing a gas boiler model and a compression type refrigeration unit model.

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