Method for determining dynamic energy flow of electric heating integrated energy system based on flux limiter

Abstract

The invention discloses a flux limiter-based dynamic energy flow determination method for an electric heating comprehensive energy system. The method specifically comprises the following steps of: establishing a dynamic energy flow model of the electric heating comprehensive energy system; the thermal dynamic partial differential equation is differentiated by using a flux limiter format with the property that total variation is not increased; establishing a self-adaptive variable step size strategy; and constructing a dynamic energy flow calculation process of the electric heating comprehensive energy system, determining the dynamic energy flow of the electric heating comprehensive energy system, and alternately solving thermal, hydraulic and electric power equations so as to obtain a time sequence change track of thermal, hydraulic and electric power variables. According to the method, the partial differential equation is differentiated by using a flux limiter format with a total variation non-increasing property, so that dispersion and dissipation errors are effectively reduced, and the calculation accuracy is improved; and a self-adaptive step size control technology is used, so that the convergence of calculation is ensured, and the efficiency of dynamic energy flow calculation of the electric heating comprehensive energy system is improved.

Description

Technical Field

[0001] The invention relates to the field of calculation and analysis of integrated energy systems, and in particular to a method for determining dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter. Background Art

[0002] Since the Industrial Revolution, the amount of heat-absorbing greenhouse gases such as carbon dioxide emitted into the atmosphere by humans has increased year by year, and the greenhouse effect of the atmosphere has also increased accordingly. Therefore, it has become urgent to improve energy efficiency, reduce carbon dioxide emissions, and get out of the global climate crisis.

[0003] The integrated energy system uses advanced physical information technology and innovative management models to integrate multiple energy sources such as coal, oil, natural gas, electricity, and thermal energy in the region, and realizes coordinated planning and optimized operation among multiple heterogeneous energy subsystems. While meeting the diversified energy needs within the system, it effectively improves energy utilization efficiency and reduces overall carbon emissions. The coupling and conversion of multiple heterogeneous energy sources make the operating characteristics of the integrated energy system quite complex, so it is necessary to accurately predict the operating status of the integrated energy system in order to achieve coordinated planning and optimized operation among multiple heterogeneous energy subsystems.

[0004] Dynamic energy flow calculation is an important tool for the operation analysis of integrated energy systems. By solving a set of nonlinear partial differential algebraic equations, the time-varying trajectories of electric, hydraulic, and thermal variables are obtained, providing data support for the prediction of energy operation status. However, the existing dynamic energy flow calculation methods are affected by dispersion and dissipation errors, with large errors, and due to the problem of alternating iterations between equations, the calculation efficiency is very low. Therefore, it is urgent to develop an accurate and efficient method for determining the dynamic energy flow of electric and thermal integrated energy systems to meet the needs of integrated energy system operation analysis. Summary of the invention

[0005] The object of the present invention is to provide a method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter, which has a simple algorithm, high calculation efficiency and high accuracy.

[0006] The technical solution to achieve the purpose of the present invention is: a method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter, comprising the following steps:

[0007] Step 1: Establish a dynamic energy flow model of the electric and thermal integrated energy system;

[0008] Step 2: Differentiate the thermodynamic partial differential equation using the flux limiter format with the total variation non-increasing property;

[0009] Step 3: Establish an adaptive variable step size strategy;

[0010] Step 4: Construct the dynamic energy flow calculation process of the electric-thermal integrated energy system to determine the dynamic energy flow of the electric-thermal integrated energy system.

[0011] A computer terminal comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter is implemented.

[0012] Compared with the prior art, the present invention has the following significant advantages: (1) The partial differential equations are differentiated using a flux limiter format with a total variation non-increasing property, which effectively reduces dispersion and dissipation errors and improves calculation accuracy; (2) The adaptive step size control technology is used to improve the efficiency of dynamic energy flow calculation of the electric and thermal integrated energy system and ensure the convergence of the calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a flow chart of the method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter of the present invention.

[0014] Figure 2 It is a schematic diagram of the dynamic energy flow calculation process of the electric and thermal integrated energy system constructed in an embodiment of the present invention.

[0015] Figure 3 It is a schematic diagram of the structure of the electric and thermal integrated energy system used in the embodiment of the present invention.

[0016] Figure 4 It is a comparison curve diagram of the water supply temperature simulation results using the method in the embodiment of the present invention and the traditional method. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is described in detail below in conjunction with the accompanying drawings and implementation examples. It should be understood that the specific implementation examples described herein are only used to explain the present invention and are not used to limit the invention.

[0018] The present invention provides a method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter, such as Figure 1 As shown, the following steps are included:

[0019] Step 1: Establish a dynamic energy flow model of the electric and thermal integrated energy system;

[0020] Step 2: Differentiate the thermodynamic partial differential equation using the flux limiter format with the total variation non-increasing property;

[0021] Step 3: Establish an adaptive variable step size strategy;

[0022] Step 4: Construct the dynamic energy flow calculation process of the electric-thermal integrated energy system to determine the dynamic energy flow of the electric-thermal integrated energy system.

[0023] As a specific example, the establishment of a dynamic energy flow model of the electric-thermal integrated energy system described in step 1 is as follows:

[0024] The dynamic energy flow model of the electric-thermal integrated energy system is the nonlinear partial differential-algebraic equation group of the dynamic energy flow of the electric-thermal integrated energy system when it works in the quantity regulation operation mode, including:

[0025] 1) One-dimensional hyperbolic convection partial differential equation describing the pipeline transport process of the heating system:

[0026]

[0027] Among them, τ is the distribution of temperature in time and space, in °C; is the mass flow rate of the heating pipeline, in kg / s; γ is the cross-sectional area of ​​the heating pipeline, in m 2 ; ρ is the heat medium density, unit is kg m -3 ; λ is the total thermal conductivity, unit is Wk -1 m -1 ; C p is the specific heat capacity of the heat medium, in J kg -1 K -1 ; t and x are time and position variables respectively; τ amb is the external temperature of the heating pipe, in °C;

[0028] The initial value conditions of the equation are:

[0029]

[0030] The boundary conditions are:

[0031] τ(0,t)=ψ(t), t≥0 (3)

[0032] Among them, τ(x, 0) is the spatial distribution of temperature in the initial state of t = 0, is the distribution function of temperature with respect to space; τ(0, t) is the distribution of temperature with respect to time at x=0, and ψ(t) is the distribution function of temperature with respect to time;

[0033] 2) Mass flow continuity equation:

[0034]

[0035] Among them, V is the node association matrix of the heating system, and its elements are:

[0036]

[0037] in, The mass flow vector representing the node injection of the heating system; represents the pipeline mass flow vector of the heating system; the subscripts R, S, L, and 1 represent the rows or elements of the vector or matrix corresponding to the balanced heat source, unbalanced heat source, load, and intermediate node, respectively; V R represents the row of the node association matrix corresponding to the balanced heat source; V S represents the row of the node association matrix corresponding to the non-equilibrium heat source; V L represents the row of the node correlation matrix corresponding to the load; V I represents the row of the node association matrix corresponding to the intermediate node; represents the mass flow rate of the equilibrium heat source; represents the mass flow rate of the non-equilibrium heat source; Indicates the mass flow rate of the load;

[0038] 3) Loop pressure drop equation:

[0039]

[0040] Where L is the loop incidence matrix, and its elements are:

[0041]

[0042] Where K is the drag coefficient vector; the diag(·) operator represents the generation of the vector into a diagonal matrix, where the diagonal elements are the corresponding elements of the original vector;

[0043] 4) Node temperature equation:

[0044]

[0045] Among them, τ s , τ r are the node supply water temperature vector and return water temperature vector respectively; τ out，s , τ out，r They are the outlet temperature vector of the water supply pipe and the outlet temperature vector of the return pipe respectively; It represents the part of the node water supply temperature vector corresponding to the load and the intermediate node; Represents the part of the node water supply temperature vector corresponding to the balanced heat source, the unbalanced heat source and the intermediate node; Where V LI V represents the row of the node association matrix corresponding to the load and the intermediate node; RSI Represents the rows of the node association matrix corresponding to the non-equilibrium heat source, the equilibrium heat source and the intermediate node;

[0046] 5) Node power equation:

[0047]

[0048] Where, φ is the node power vector; φ R，S，L Represents the node power of balanced heat source, unbalanced heat source and load; C P represents the specific heat capacity at constant pressure; Represents the injected mass flow rate of balanced heat sources, unbalanced heat sources and loads; Indicates the supply water temperature for balanced heat sources, unbalanced heat sources and loads; Indicates the return water temperature of balanced heat source, unbalanced heat source and load;

[0049] 6) Power system flow equation:

[0050] p=diag(e)(Ge-Bf)+diag(f)(Be+Gf) (11)

[0051] q=diag(f)(Ge-Bf)-diag(e)(Be+Gf) (12)

[0052]

[0053] e R =e SP , f R =f sP (14)

[0054] Among them, p and q are active and reactive power vectors respectively; e and f are real and imaginary vectors of node voltage respectively; G and B are node conductance and susceptance matrices respectively; is the PV node voltage amplitude; e SP 、f SP are the real and imaginary parts of the equilibrium node voltage respectively; e PV is the real part of the PV node voltage, f PV is the imaginary part of the PV node voltage, e R is the real part of the equilibrium node voltage, f R is the imaginary part of the equilibrium node voltage;

[0055] 7) Coupling element equation:

[0056] Air extraction condensing unit:

[0057] p CHP =-φ CHP / Z+η e F in (15)

[0058] gas turbine:

[0059] φ GT =c m2 PGT (16)

[0060] Where Z is the electrothermal conversion coefficient, c m2 is the thermoelectric conversion coefficient; η e is the electrical efficiency; F in is the fuel input of the steam turbine; p CHP With φ CHP Respectively represent the electrical and thermal power of the exhaust condensing unit; p GT With φ GT Represent the electrical and thermal power of the gas turbine respectively.

[0061] As a specific example, the thermodynamic partial differential equation is differentiated using the flux limiter format with the total variation non-increasing property as described in step 2, as follows:

[0062] Step 2.1, using a flux limiter format with total variation non-increasing property and precision 2, transform the one-dimensional hyperbolic convection partial differential equation of the pipeline transport process of the heating system into an algebraic equation;

[0063] Step 2.2, using another low-precision format with the non-increasing total variation property, transform the one-dimensional hyperbolic convection partial differential equation of the pipeline transport process of the heating system into an algebraic equation;

[0064] Step 2.3: Estimate the local truncation error by comparing the difference between the calculation results of the flux limiter format and the low-precision format.

[0065] As a specific example, the one-dimensional hyperbolic convection partial differential equation of the pipeline transport process of the heating system is converted into an algebraic equation using a flux limiter format with a total variation non-increasing property and an accuracy of 2 as described in step 2.1. The format is:

[0066]

[0067] Where R = Δt / Δx, Δt and Δx represent the time and space steps respectively; Indicates the temperature value at discrete point k of the pipeline at the nth moment; Indicates the temperature value at the discrete point k+1 of the pipeline at the n+1th moment; b=1 / AρcR, A represents the cross-sectional area, ρ represents the density, and c represents the specific heat capacity; 2≤k≤M represents the spatial difference index; n represents the time difference index; M represents the total number of spatial difference pipe sections; and is the numerical flux function, represents the flux value at the spatial position k+1 / 2 at the nth time, represents the flux value at the spatial position k-1 / 2 at the nth time, and The calculation formulas are:

[0068]

[0069] in, Represents the temperature value at position k-1 at the nth moment; function and is the flux limiter, represents the flux limitation function at position k at the nth time, represents the flux limiting function at position k-1 at the nth time, in is a smooth indicator, and the calculation formula is:

[0070]

[0071] In the formula, When k = 2 or M, let φ = 0;

[0072] The expression of the flux limiter φ(θ) is:

[0073]

[0074] Here, θ represents the smoothness indicator.

[0075] As a specific example, step 2.2 uses another low-precision format with the property of non-increasing total variation to transform the one-dimensional hyperbolic convection partial differential equation of the pipeline transport process of the heating system into an algebraic equation in the following format:

[0076]

[0077] As a specific example, the local truncation error is estimated by comparing the difference between the calculation results of the flux limiter format and the low-precision format as described in step 2.3, as follows:

[0078] Using X I The calculation result of the first-order accuracy format of expression (20) is expressed as X II The calculation result of the second-order accuracy flux limiter format of formula (17) is expressed as follows:

[0079]

[0080] Define the error limit of the i-th variable as:

[0081] ε i =Atol+min(|X i (0)|,|X i (Δt)|)·Rtol

[0082] Among them, Atol and Rtol represent the absolute error limit and relative error limit respectively; |X i (0)|、|X i (Δt)|represents the value of the i-th variable at time 0 and time Δt respectively;

[0083] The total simulation error is:

[0084]

[0085] in, represents the local truncation error of the jth variable, and m represents the total number of variables;

[0086] Finally, the simulation step size is adaptively controlled according to the total simulation error.

[0087] As a specific example, the establishment of the adaptive variable step size strategy described in step 3 is as follows:

[0088] According to the estimated value of the local truncation error, the step size is adaptively controlled, and the control rule is as follows:

[0089] If X err ≤1, accept the current time step and continue with the next step 4.6; otherwise, repeat the current time step calculation and return to step 4.4;

[0090] In each case, the calculation step size is updated using the following formula:

[0091]

[0092] Among them, Δt max is the maximum allowed step size to prevent divergence; Δt min is the minimum allowed step size to ensure computational efficiency, Δt new is the new step size, and Δt is the step size before updating.

[0093] As a specific example, the dynamic energy flow calculation process of constructing the electric-thermal integrated energy system described in step 4 calculates the dynamic energy flow of the electric-thermal integrated energy system, such as Figure 2 As shown, the details are as follows:

[0094] Step 4.1, perform steady-state energy flow calculation;

[0095] Step 4.2: Set the spatiotemporal distribution of pipeline temperature T(x, t) and pipeline mass flow vector Node water supply temperature T s , Node return water temperature T r, the initial values ​​of the node power vector φ, the active power vector P, the reactive power vector Q, the real part vector e of the node voltage, the imaginary part vector f of the node voltage, the initialization time step Δt, and the total simulation time T;

[0096] Step 4.3, let t←t+Δt;

[0097] Step 4.4, Set up X err =2, use equations (17) and (20) to calculate the temperature distribution of each pipe, and update X err and Δt;

[0098] Step 4.5: Determine X err Is it greater than 1? If so, go to step 4.6; otherwise, return to step 4.4 and use the updated X err and Δt to recalculate the temperature distribution of each pipe and update X again err and Δt; repeat the operation until X err Greater than 1;

[0099] Step 4.6, solve the mass flow continuity equation, i.e., equation (4), equation (5), equation (6) and the loop pressure drop equation, i.e., equation (7);

[0100] Step 4.7, calculate the node temperature equation, that is, equation (8) and equation (9);

[0101] Step 4.8, solve the node power equation, i.e., equation (10);

[0102] Step 4.9, solve the coupling element equations, i.e., equation (15) and equation (16);

[0103] Step 4.10, solve the power system power flow equations, i.e., equations (11), (12), (13), and (14);

[0104] Step 4.11: Determine whether t is greater than T. If so, the calculation is completed and the calculation result is output; otherwise, return to step 4.3.

[0105] As a specific example, through the dynamic energy flow calculation process of the electric-thermal integrated energy system, the thermal, hydraulic and electric equations are solved alternately to obtain the time series change trajectory of the thermal, hydraulic and electric variables.

[0106] The present invention also provides a computer terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter is implemented.

[0107] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0108] Example

[0109] This embodiment adopts an electric and thermal integrated energy system to verify the method of the present invention. Figure 3 This is the structural diagram of the electric-thermal integrated energy system used in this embodiment. The system includes 35 thermal nodes and 9 electric nodes. An exhaust-condensing unit connects the heat source node 1 of the heating system and the PV bus ix of the power system. A gas turbine connects the heat source node 34 of the heating system and the balance bus i of the power system. The proposed dynamic energy flow calculation method is verified in the matrix laboratory MATLAB and compared with the iterative method based on the implicit upwind format and the second-order explicit difference format. M1 represents the iterative method based on the implicit upwind format, M2 represents the iterative method based on the second-order explicit difference, and M3 represents the method proposed in the present invention. All methods use the same spatial difference step size of 20m, and use the results of the 4th-5th order Runge-Kutta format as the reference value.

[0110] Given a 24-hour load change trajectory for all load nodes, with a load change step of 15 minutes, the calculation accuracy and efficiency of the method of the present invention are verified. The calculation results are compared as follows: Figure 4 As shown in Table 1 and Table 2, Table 1 is a comparison of the calculation accuracy of the method of the present invention in an embodiment of the present invention and the traditional method, and Table 2 is a comparison of the calculation efficiency of the method of the present invention in an embodiment of the present invention and the traditional method.

[0111] Table 1 Mean square error comparison

[0112]

[0113] Table 2 Total calculation time

[0114]

[0115] Depend on Figure 4 As can be seen from Table 1, the method proposed in the present invention can effectively reduce false numerical oscillation and attenuation, namely dispersion and dissipation errors, thereby significantly improving the calculation accuracy. As can be seen from Table 2, the calculation efficiency of the method proposed in the present invention is significantly improved compared with the traditional method.

[0116] It can be seen from this embodiment that the method proposed in the present invention can realize accurate and efficient calculation of the dynamic energy flow of the electric and thermal integrated energy system.

[0117] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter, characterized in that: The following steps are involved: Step 1: Establish a dynamic energy flow model of the electric and thermal integrated energy system; Step 2: Differentiate the thermodynamic partial differential equation using the flux limiter format with the total variation non-increasing property; Step 3: Establish an adaptive variable step size strategy; Step 4: Construct the dynamic energy flow calculation process of the electric-thermal integrated energy system to determine the dynamic energy flow of the electric-thermal integrated energy system.

2. The method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter according to claim 1, characterized in that: The dynamic energy flow model of the electric-thermal integrated energy system is established as described in step 1, as follows: The dynamic energy flow model of the electric-thermal integrated energy system is the nonlinear partial differential-algebraic equation group of the dynamic energy flow of the electric-thermal integrated energy system when it works in the quantity regulation operation mode, including: 1) One-dimensional hyperbolic convection partial differential equation describing the pipeline transport process of the heating system: Among them, τ is the distribution of temperature in time and space, in °C; is the mass flow rate of the heating pipeline, in kg / s; γ is the cross-sectional area of ​​the heating pipeline, in m 2 ; ρ is the heat medium density, unit is kgm -3 ; λ is the total thermal conductivity, unit is Wk -1 m -1 ; C p is the specific heat capacity of the heat medium, in Jkg -1 K -1 ; t and x are time and position variables respectively; τ amb is the external temperature of the heating pipe, in °C; The initial value conditions of the equation are: The boundary conditions are: τ(0,t)=ψ(t),t≥0 (3) Among them, τ(x,0) is the spatial distribution of temperature in the initial state of t=0, is the temperature distribution function with respect to space; τ(0,t) is the temperature distribution with respect to time at x=0, ψ(t) is the temperature distribution function with respect to time; 2) Mass flow continuity equation: Among them, V is the node association matrix of the heating system, and its elements are: in, The mass flow vector representing the node injection of the heating system; represents the pipeline mass flow vector of the heating system; the subscripts R, S, L, and I represent the rows or elements of the vector or matrix corresponding to the balanced heat source, unbalanced heat source, load, and intermediate node, respectively; V R represents the row of the node association matrix corresponding to the balanced heat source; V S represents the row of the node association matrix corresponding to the non-equilibrium heat source; V L represents the row of the node correlation matrix corresponding to the load; V I represents the row of the node association matrix corresponding to the intermediate node; represents the mass flow rate of the equilibrium heat source; represents the mass flow rate of the non-equilibrium heat source; Indicates the mass flow rate of the load; 3) Loop pressure drop equation: Where L is the loop incidence matrix, and its elements are: Where K is the drag coefficient vector; the diag(·) operator represents the generation of the vector into a diagonal matrix, where the diagonal elements are the corresponding elements of the original vector; 4) Node temperature equation: Among them, τ s , τ r are the node supply water temperature vector and return water temperature vector respectively; τ out,s , τ out,r They are the outlet temperature vector of the water supply pipe and the outlet temperature vector of the return pipe respectively; It represents the part of the node water supply temperature vector corresponding to the load and the intermediate node; Represents the part of the node water supply temperature vector corresponding to the balanced heat source, the unbalanced heat source and the intermediate node; Where V LI V represents the row of the node association matrix corresponding to the load and the intermediate node; RSI Represents the rows of the node association matrix corresponding to the non-equilibrium heat source, the equilibrium heat source and the intermediate node; 5) Node power equation: Where, φ is the node power vector; φ R,S,L Represents the node power of balanced heat source, unbalanced heat source and load; C P represents the specific heat capacity at constant pressure; Represents the injected mass flow rate of balanced heat sources, unbalanced heat sources and loads; Indicates the supply water temperature for balanced heat sources, unbalanced heat sources and loads; Indicates the return water temperature of balanced heat source, unbalanced heat source and load; 6) Power system flow equation: p=diag(e)(Ge-Bf)+diag(f)(Be+Gf) (11) q=diag(f)(Ge-Bf)-diag(e)(Be+Gf) (12) e R =e SP ,f R =f SP (14) Among them, p and q are active and reactive power vectors respectively; e and f are real and imaginary vectors of node voltage respectively; G and B are node conductance and susceptance matrices respectively; is the PV node voltage amplitude; e sP 、f SP are the real and imaginary parts of the equilibrium node voltage respectively; e PV is the real part of the PV node voltage, f PV is the imaginary part of the PV node voltage, e R is the real part of the equilibrium node voltage, f R is the imaginary part of the equilibrium node voltage; 7) Coupling element equation: Air extraction condensing unit: p CHP =-φ CHP / Z+η e F in (15) gas turbine: φ GT =c m2 p GT (16) Where Z is the electrothermal conversion coefficient, c m2 is the thermoelectric conversion coefficient; η e is the electrical efficiency; F in is the fuel input of the steam turbine; p CHP With φ CHP Respectively represent the electrical and thermal power of the exhaust condensing unit; p GT With φ GT Represent the electrical and thermal power of the gas turbine respectively.

3. The method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter according to claim 2, characterized in that: The thermodynamic partial differential equation is differentiated using the flux limiter format with the total variation non-increasing property as described in step 2, as follows: Step 2.1, using a flux limiter format with total variation non-increasing property and precision 2, transform the one-dimensional hyperbolic convection partial differential equation of the pipeline transport process of the heating system into an algebraic equation; Step 2.2, using another low-precision format with the non-increasing total variation property, transform the one-dimensional hyperbolic convection partial differential equation of the pipeline transport process of the heating system into an algebraic equation; Step 2.3: Estimate the local truncation error by comparing the difference between the calculation results of the flux limiter format and the low-precision format.

4. The method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter according to claim 3 is characterized in that: Step 2.1 uses a flux limiter format with a total variation non-increasing property and an accuracy of 2 to transform the one-dimensional hyperbolic convection partial differential equation of the heating system pipeline transport process into an algebraic equation in the format of: Where R = Δt / Δx, Δt and Δx represent the time and space steps respectively; Indicates the temperature value at discrete point k of the pipeline at the nth moment; Indicates the temperature value at the discrete point k+1 of the pipeline at the n+1th moment; b=1 / AρcR, A represents the cross-sectional area, ρ represents the density, and c represents the specific heat capacity; 2≤k≤M represents the spatial difference index; n represents the time difference index; M represents the total number of spatial difference pipe sections; and is the numerical flux function, represents the flux value at the spatial position k+1 / 2 at the nth time, represents the flux value at the spatial position k-1 / 2 at the nth time, and The calculation formulas are: in, Represents the temperature value at position k-1 at the nth moment; function and is the flux limiter, represents the flux limitation function at position k at the nth time, represents the flux limiting function at position k-1 at the nth time, in is a smooth indicator, and the calculation formula is: In the formula, When k = 2 or M, let φ = 0; The expression of the flux limiter φ(θ) is: Here, θ represents the smoothness indicator.

5. The method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter according to claim 4 is characterized in that: Step 2.2 uses another low-precision format with the property of non-increasing total variation to transform the one-dimensional hyperbolic convection partial differential equation of the pipeline transport process of the heating system into an algebraic equation in the following format:

6. The method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter according to claim 5 is characterized in that: The local truncation error is estimated by comparing the difference between the calculation results of the flux limiter format and the low-precision format as described in step 2.3, as follows: Using X I The calculation result of the first-order accuracy format of expression (20) is expressed as X II The calculation result of the second-order accuracy flux limiter format of formula (17) is expressed as follows: Define the error limit of the i-th variable as: ε i =Atoll+min(|X i (0)|,|X i (Δt)|)·Rtol Among them, δAtol and Rtol represent the absolute error limit and relative error limit respectively; |X i (0)|、|X i (Δt)|represents the value of the i-th variable at time 0 and time Δt respectively; The total simulation error is: in, represents the local truncation error of the jth variable, and m represents the total number of variables; Finally, the simulation step size is adaptively controlled according to the total simulation error.

7. The method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter according to claim 6, characterized in that: The establishment of the adaptive variable step size strategy described in step 3 is as follows: According to the estimated value of the local truncation error, the step size is adaptively controlled, and the control rule is as follows: If X err ≤1, accept the current time step and continue the next step calculation; otherwise, repeat the current time step calculation; In each case, the calculation step size is updated using the following formula: Among them, Δt max is the maximum allowed step size to prevent divergence; Δt min is the minimum allowed step size to ensure computational efficiency, Δt new is the new step size, and Δt is the step size before updating.

8. The method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter according to claim 7, characterized in that: The dynamic energy flow calculation process for constructing the electric-thermal integrated energy system described in step 4 calculates the dynamic energy flow of the electric-thermal integrated energy system as follows: Step 4.1, perform steady-state energy flow calculation; Step 4.2: Set the spatiotemporal distribution of pipeline temperature T(x,t) and pipeline mass flow vector Node water supply temperature T s , Node return water temperature T r , the initial values ​​of the node power vector φ, the active power vector P, the reactive power vector Q, the real part vector e of the node voltage, the imaginary part vector f of the node voltage, the initialization time step Δt, and the total simulation time T; Step 4.3, let t←t+Δt; Step 4.4, Set up X err =2, use equations (17) and (20) to calculate the temperature distribution of each pipe, and update X err and Δt; Step 4.5: Determine X err Is it greater than 1? If so, go to step 4.6; otherwise, return to step 4.4 and use the updated X err and Δt to recalculate the temperature distribution of each pipe and update X again err and Δt; repeat the operation until X err Greater than 1; Step 4.6, solve the mass flow continuity equation, i.e., equation (4), equation (5), equation (6) and the loop pressure drop equation, i.e., equation (7); Step 4.7, calculate the node temperature equation, that is, equation (8) and equation (9); Step 4.8, solve the node power equation, i.e., equation (10); Step 4.9, solve the coupling element equations, i.e., equation (15) and equation (16); Step 4.10, solve the power system power flow equations, i.e., equations (11), (12), (13), and (14); Step 4.11: Determine whether t is greater than T. If so, the calculation is completed and the calculation result is output; otherwise, return to step 4.

3.

9. The method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter according to claim 8, characterized in that: Through the dynamic energy flow calculation process of the electric-thermal integrated energy system, the thermal, hydraulic and electric equations are solved alternately to obtain the time series change trajectory of the thermal, hydraulic and electric variables.

10. A computer terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, it implements the method for determining the dynamic energy flow of an electric-thermal integrated energy system based on a flux limiter as described in any one of claims 1 to 9.

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