Comprehensive energy system multi-energy flow distribution and loss evaluation method, electronic equipment and medium

Abstract

The invention discloses a comprehensive energy system multi-energy flow distribution and loss evaluation method, electronic equipment and a medium, and the method comprises the steps: constructing a comprehensive energy system, and enabling a power system, a thermodynamic system and a natural gas system to respectively comprise a power grid tidal current variable, a heat supply network tidal current variable and a gas network tidal current variable; a system power flow model is constructed based on a comprehensive energy system, the system power flow model comprises a power grid power flow model, a heat supply network power flow model, a gas network power flow model and a coupling link model, and the coupling link model comprises a gas turbine model, a combined heat and power generation unit model, an electric boiler model and a power-to-natural gas system model; calculating power flow parameters based on a system power flow model; constructing a system flow mechanism model based on the integrated energy system, wherein the system flow mechanism model comprises node potential and branch flow; and identifying links with loss exceeding a preset threshold value in the system based on the flow mechanism model and the power flow parameters. According to the invention, clear mastering of the multi-energy flow distribution of the integrated energy system and accurate evaluation of the loss are realized.

Description

Technical Field

[0001] This invention belongs to the field of integrated energy system technology, specifically relating to a method for assessing the multi-energy flow distribution and loss in integrated energy systems, electronic equipment, and media. Background Technology

[0002] As the cornerstone of the energy internet, the integrated energy system encompasses energy generation ("source"), energy transmission network ("network"), and energy consumption. Its energy utilization efficiency often requires the use of effective thermodynamic analysis methods.

[0003] In related technical fields, independent and refined models of each subsystem of electricity, heat, and gas are established, and energy efficiency assessment and optimized scheduling are carried out at the system level using black box or preliminary system models.

[0004] Mainstream energy analysis methods generally treat the system as a black box model, focusing only on the total amount of input and output. This makes it impossible to accurately locate the specific equipment or pipe section with the greatest energy loss, resulting in local diagnostic failures. As a result, existing optimization strategies appear blind and inefficient due to the lack of precise targets, making it difficult to achieve optimal system improvement in terms of input-output ratio. Summary of the Invention

[0005] The purpose of this invention is to provide a method, electronic device, and medium for assessing the multi-energy flow distribution and loss of an integrated energy system by constructing a networked energy flow mechanism model, which can clearly characterize the spatial distribution and flow of energy in the internal network of an integrated energy system.

[0006] On the one hand, to achieve the above objectives, this invention proposes a method for assessing the multi-energy flow distribution and losses in an integrated energy system, comprising: constructing an integrated energy system, which includes a power system, a heating system, a natural gas system, and coupling nodes, such that the power system, the heating system, and the natural gas system all include power grid flow variables, heating network flow variables, and gas network flow variables; constructing a system flow model based on the integrated energy system, which includes a power grid flow model, a heating network flow model, a gas network flow model, and a coupling node model, wherein the coupling node model includes a gas turbine model, a combined heat and power unit model, an electric boiler model, and a power-to-natural gas system model; calculating flow parameters based on the system flow model; constructing a system backflow mechanism model based on the integrated energy system, which includes node backflow and branch backflow; and identifying nodes in the system where backflow exceeds a preset threshold based on the backflow mechanism model and the flow parameters.

[0007] In one optional implementation, the expression for the integrated energy system is: ; ; In the formula, The power balance equations for the power grid; For power flow variables in the power grid; For the power flow equation of the heating network; For heat network current variables; For the air flow equation; For gas flow variables.

[0008] In one optional implementation, power flow parameters are calculated based on the system power flow model. These power flow parameters include thermal parameters, specifically including: initializing pipe water flow and node temperature to generate initial values; calculating the actual flow corresponding to the heat load node based on the initial values; calculating the pressure and temperature of the heat load node based on the actual flow corresponding to the heat load node and in combination with heat loss; determining whether the pressure and temperature of the heat load node converge. If they converge, the calculation results are output; if they do not converge, the initial values ​​are readjusted.

[0009] In one optional implementation, the expression for the heating network power flow model is: ; For nodes The return water temperature; For nodes The return water temperature; for , Inter-node pipe length; for , Water flow rate in the pipeline between nodes.

[0010] In one optional implementation, a system current flow mechanism model is constructed based on the integrated energy system. This model includes nodal current potentials and branch currents, specifically including: defining nodal current potentials. : In the formula, For node temperature; Ambient temperature; The specific heat capacity at constant pressure of the fluid is given; the branch inrush flow is calculated based on the nodal potential and the power flow parameters, wherein the branch inrush flow includes heat source-heat load inrush, component inrush, supply and return water pipe inrush and heat load inrush.

[0011] In one optional implementation, the expression for the heat source-heat load is: In the formula, For heat source, kW; Heat load (kW); The power of the water supply node is expressed in kW·s / kg. The potential for return water flow is expressed in kW·s / kg. This is to create an advantage for export nodes; The flow rate at the heat source node is kg / s; denoted as the flow rate at the load node, in kg / s.

[0012] In one optional implementation, the expression for the element flow is: In the formula, For water supply pipeline flow, kW; For the return water pipe flow, kW.

[0013] In one alternative implementation, the supply and return water pipe losses are represented by the product of the difference in node potential and the pipe flow rate.

[0014] On the other hand, the present invention also proposes an electronic device, comprising: at least one processor; a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform any of the integrated energy system multi-energy flow distribution and loss assessment methods described in the present invention.

[0015] On the other hand, the present invention also proposes a computer storage medium storing a computer program, which, when executed by a processor, implements a method for evaluating the multi-energy flow distribution and loss of an integrated energy system.

[0016] The beneficial effects of this invention are as follows: by constructing a comprehensive energy system and power flow model containing multiple systems and multiple coupling links, and combining it with a backflow mechanism model, it is possible to accurately calculate power flow parameters and effectively identify links where backflow exceeds the threshold, ultimately achieving a clear understanding of the multi-energy flow distribution of the comprehensive energy system and accurate assessment of losses. Attached Figure Description

[0017] Figure 1 A flowchart of a method for assessing the multi-energy flow distribution and losses in an integrated energy system, provided as an embodiment of the present invention;

[0018] Figure 2 This is a schematic diagram illustrating the connection of electricity, heat, and natural gas via coupling elements in a method for assessing the multi-energy flow distribution and loss of an integrated energy system according to an embodiment of the present invention.

[0019] Figure 3 This is a flowchart illustrating the calculation of power flow parameters for a method for assessing the multi-energy flow distribution and losses in an integrated energy system, as provided in an embodiment of the present invention. Detailed Implementation

[0020] In system modeling and power flow calculation, existing technologies have formed a basic framework for subsystem modeling and joint analysis. For power networks, research typically establishes AC models in polar coordinates or DC models in rectangular coordinates for power flow calculation to characterize their operating characteristics. For thermal networks, existing methods propose a steady-state modeling approach that separates energy flow from working fluid flow, using temperature analysis to process energy flow and fluid analysis to study working fluid flow, thereby more accurately revealing the operating mechanism of the thermal network; subsequent research has also proposed corresponding improvement methods to address the calculation errors of the working fluid flow method. For natural gas networks, research focuses on establishing equations describing the steady-state flow of compressible gases in pipeline networks. Based on this, scholars have further explored multi-energy flow coupling, proposed joint optimization concepts such as natural gas-electricity optimal power flow, and established coupling degree calculation models for analyzing the interrelationships between multiple energy loads such as electricity, heat, and gas.

[0021] In the field of system energy efficiency assessment and optimization, the efficiency analysis method based on the second law of thermodynamics has been introduced into the study of integrated energy systems. Existing technical solutions mainly follow two paths: First, the entire integrated energy system is treated as a "black box model," with the overall system efficiency as the core evaluation index, and a multi-objective optimization scheduling model incorporating efficiency analysis is established on this basis, or the maximization of system efficiency is directly used as the optimization objective function. Second, efforts are made to draw analogies between efficiency research methods and current and carbon flow, proposing the "efficiency potential" theory of integrated energy systems, attempting to construct a more systematic analytical framework, and proposing a new energy efficiency assessment method and energy quality coefficient conversion method based on efficiency and considering differences in energy grade.

[0022] Multi-energy flow calculations, which form the basis of analysis, especially thermal network models, suffer from idealization flaws. They generally ignore the actual heat loss of the return water network or do not match the actual multi-branch network structure. This leads to significant deviations between the flow calculation results provided and the actual engineering situation, causing all subsequent advanced analyses to be based on distorted data. Ultimately, the combination of these two shortcomings makes existing optimization strategies appear blind and inefficient due to a lack of precise targeting, making it difficult to achieve system improvements with the best return on investment.

[0023] Therefore, another objective of this invention is to provide an improved power flow model for heating networks that accurately accounts for return water heat loss and is applicable to complex pipe network structures, thereby solidifying the foundation for the accuracy of the entire multi-energy flow analysis. The fundamental objective of this invention is to achieve accurate and quantitative identification of weak points in the system's energy structure by solving the aforementioned problems, thereby providing direct and actionable decision-making basis for the system's planning, operation, and modification.

[0024] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0025] like Figure 1 and Figure 2 As shown in the embodiments of the present invention, in one aspect, a method for evaluating the multi-energy flow distribution and losses of an integrated energy system is provided, comprising the following steps:

[0026] Step S101: Construct an integrated energy system, which includes an electric system, a heating system, a natural gas system, and coupling nodes, such that the electric system, heating system, and natural gas system all contain power flow variables of the power grid, heating network, and gas network.

[0027] Step S103: Based on the integrated energy system, construct a system power flow model. The system power flow model includes a power grid power flow model, a heat network power flow model, a gas network power flow model, and a coupling link model. The coupling link model includes a gas turbine model, a combined heat and power unit model, an electric boiler model, and a power-to-natural gas system model.

[0028] Step S105: Calculate the power flow parameters based on the system power flow model.

[0029] Step S107: Construct a system current mechanism model based on the integrated energy system. The system current mechanism model includes nodal current and branch current.

[0030] Step S109: Identify the components in the system where the loss exceeds a preset threshold based on the backflow mechanism model and power flow parameters.

[0031] In this embodiment, as Figure 2 As shown, the topology of the power, heat, and gas networks is clearly defined, integrating the power system (generation / transmission / distribution / load nodes), the heat system (heat source / heat network / heat load nodes), and the natural gas system (gas station / gas pipeline / gas consumption node). Physical and data interconnection is achieved through coupling nodes; power flow variables are uniformly defined (power grid: node voltage / branch power; heat network: pipeline flow / node temperature and pressure; gas network: pipeline gas flow / node pressure) to ensure that the variables of the coupling nodes can interact.

[0032] The power grid uses the Newton-Raphson method to establish the power balance equation, the heating network uses the temperature-pressure iterative model based on heat transfer / fluid mechanics, and the gas network uses the Weymouth equation to describe the flow-pressure relationship.

[0033] Coupled Model: Construct energy conversion equations for gas turbine (gas → electricity / heat), combined heat and power (CHP) unit (gas → electricity + heat), electric boiler (electricity → heat), and P2G (electricity → gas) to achieve interoperability of variables among the three networks.

[0034] Input initial parameters (initial voltage of the power grid, initial temperature of the heating network, etc.), and output steady-state parameters (node ​​status of the power / heat / gas network, branch transmission volume and input / output values ​​of coupling equipment) through multi-system collaborative iteration (meeting convergence conditions such as voltage deviation ≤ 0.01 pu and temperature deviation ≤ 0.5℃).

[0035] Based on potential theory, nodal potentials are defined for electricity (voltage correlation), heat (temperature correlation), and gas (pressure / composition correlation); branch currents (e.g., heating network current = flow rate × potential difference) and losses (input current - output current) of each link are calculated in combination with power flow parameters.

[0036] Set a loss threshold (e.g., power branch ≥5%, heating network pipeline ≥8%), substitute it into the power flow parameters and the loss model, and screen out links that exceed the threshold (e.g., poorly insulated heating network pipelines, inefficient CHP units).

[0037] By integrating the three networks and their coupling relationships, and avoiding the bias of single-system analysis, it can fully describe the multi-energy flow transmission and conversion process. The subsystems and coupling models iterate collaboratively to ensure the steady-state accuracy of power flow parameters, providing reliable data for backflow analysis. Based on backflow mechanisms and power flow parameters, it can accurately locate high-loss links, which is superior to traditional experience-based judgments. It can also identify inefficient links, providing direction for equipment upgrades (such as replacing with high-efficiency CHP) and operation scheduling, thereby improving the system's energy utilization efficiency.

[0038] like Figure 2 As shown, the electricity, heat, and natural gas systems are closely connected through diverse coupling elements, thereby achieving a synergistic energy supply effect from multiple energy flows. The expression for the integrated energy system is:

[0039] (1)

[0040] (2)

[0041] (3)

[0042] In the formula, The power balance equations for the power grid; For power flow variables in the power grid; For the power flow equation of the heating network; For heat network current variables; For the air flow equation; For gas flow variables.

[0043] Compared to traditional power flow calculation models, integrated energy system power flow models involve different physical constraints on different systems, and the types and quantities of energy flows and variables also vary in each system. Therefore, integrated energy system power flow models contain more variables and are more nonlinear than traditional power flow models.

[0044] By constructing a comprehensive energy system model that integrates electricity, heat, natural gas systems and multiple coupled components, and characterizing the system relationships with power balance equations that relate to multiple systems, this model, compared to traditional single power flow models, not only achieves coordinated energy supply from multiple energy flows, but also accurately adapts to the physical constraints and differences in energy flow and variables of different systems. This enhances the comprehensiveness and adaptability of energy flow analysis in the comprehensive energy system and provides model support for the efficient operation of multi-energy coordination.

[0045] Based on the operational characteristics of power network power balance in an integrated energy system, a steady-state power flow model is established. The parameters in the model are expressed in per-unit values. The power flow model is as follows:

[0046] (4)

[0047] (5)

[0048] In the formula, For nodes Injection is effective; For nodes Injecting reactive power; , Two nodes respectively , The voltage amplitude; For nodes , The voltage phase angle difference; For nodes , Inter-line conductivity; For nodes , Inter-line susceptance.

[0049] The power steady-state power flow model uses per-unit parameters and constructs active and reactive power equations based on nodal voltage amplitude phasors and line admittances. This accurately matches the power balance characteristics of the power network, clearly quantifies the correlation between nodal power and line electrical parameters, and improves the accuracy of power flow calculations and stability analysis capabilities of the power subsystem. Through the hierarchical design of the overall system model and power subsystems, it achieves coordinated management of multiple energy flows and provides comprehensive and accurate model support for energy flow distribution analysis and operational optimization of integrated energy systems, contributing to the efficient and reliable operation of the system.

[0050] Furthermore, combined Figure 3 As shown, step S105 involves calculating the power flow parameters based on the system power flow model. The power flow parameters include thermal parameters, and specifically include the following steps:

[0051] Step S1051: Initialize the pipe water flow rate and node temperature to generate initial values.

[0052] Step S1053: Calculate the actual flow rate corresponding to the heat load node based on the initial value.

[0053] Step S1055: Calculate the pressure and temperature of the heat load node based on the actual flow rate corresponding to the heat load node and the heat loss.

[0054] Step S1057: Determine whether the pressure and temperature at the heat load node have converged. If they have converged, output the calculation results; if they have not converged, readjust the initial values.

[0055] Traditional power flow models for thermal systems largely draw upon modeling methods for power transmission networks. However, structural differences between transmission networks and thermal networks prevent analogous models from accurately describing the operational characteristics of thermal networks. Furthermore, electricity, a high-quality energy source, exhibits negligible line losses in actual power lines due to its trinomial symmetry. In contrast, heat transfer in pipelines requires a working medium, resulting in significant heat loss in practical applications. For these reasons, traditional thermal models often produce substantial errors in engineering practice. To account for heat loss in pipelines, a common practice is to artificially estimate a mixed return water temperature in the return water section of the thermal network and incorporate it into the model for heat loss calculations. While this corrects the results to some extent, it fails to achieve the required accuracy. To obtain accurate results consistent with engineering realities, this invention incorporates the calculation of return water heat loss. Using a baseline parameter temperature as the initial value, the accurate temperature of the working medium at the return water node is calculated iteratively through a mixed temperature equation and then incorporated into the thermal model to calculate the power flow distribution of the thermal network. The expression for the thermal network power flow model is:

[0056] (6)

[0057] For nodes The return water temperature; For nodes The return water temperature; for , Inter-node pipe length; for , Water flow rate in the pipeline between nodes.

[0058] By optimizing the formula, the existing power flow calculation methods are able to overcome the difficulty in reflecting the heat loss problem in the pipeline network, while improving the accuracy and computational efficiency of the power flow model when applied to systems containing multiple pipelines and complex energy conversion equipment.

[0059] Through an iterative process of "initial value initialization - actual flow calculation - parameter solution of heat loss coupling - convergence determination", the structural differences between heating networks and power grids are specifically adapted, overcoming the limitations of traditional analog power grid modeling and more accurately depicting the operating characteristics of heating networks.

[0060] Through an iterative convergence mechanism, the thermodynamic parameters such as flow rate, pressure, and temperature of heat load nodes are accurately calculated, while heat loss factors are also incorporated, providing reliable data support for the energy flow distribution and loss assessment of the heat network in the integrated energy system.

[0061] In the steady-state power flow calculation of the thermal network, the heat loss caused by heat conduction in the return water pipe is explicitly calculated by introducing the return water temperature friction decay equation. The equation is specifically stated as the return water temperature being a function of the pipe initial temperature, ambient temperature, heat transfer coefficient, pipe length, working fluid flow rate, and specific heat capacity.

[0062] The natural gas system flow model includes the natural gas flow steady-state equation, network node equations, and network loop equations. Due to the high pressure in natural gas transmission pipelines, the Panhandle'A' formula and the Weymouth formula are applicable.

[0063] Panhandle 'A' formula:

[0064] (7)

[0065] (8)

[0066] Weymouth formula:

[0067] (9)

[0068] In the formula, for , The flow between the two nodes, m 3 / h; For nodes The pressure is 0.1 MPa; For nodes The pressure, MPa; Pressure under standard conditions, MPa; For nodes , The diameter of the pipe between them, in mm; For nodes , The length of the pipe between them, in meters; The coefficient of friction is omnidirectional. Let K be the average temperature of the natural gas. The temperature under standard conditions is 288 K; This is the average compressibility factor, typically 0.95; This represents the specific gravity of natural gas, with a typical value of 0.589. It is the Reynolds number; This is the efficiency coefficient of the pipeline, with a typical value of 0.92.

[0069] The network node equations can be expressed in matrix form as follows:

[0070] (10)

[0071] In the formula, For non-electric gas demand; For electricity and gas demand; For the gas load in the natural gas network; The simplified node-branch association matrix; This represents the flow of nodes in the branch, with positive values ​​for inflow nodes and negative values ​​for outflow nodes.

[0072] The network loop equations can be expressed in matrix form as follows:

[0073] (11)

[0074] (12)

[0075] In the formula, The square of the nodal pressure; The branch-loop correlation equation is given.

[0076] The coupling components mainly include gas turbines, combined heat and power (CHP) units, electric boilers, and power-to-gas (P2G) systems. These components, through their specific energy conversion mechanisms, establish energy flow links between electricity, heat, and natural gas networks, enabling the entire integrated energy system to efficiently and flexibly achieve multi-energy complementarity and synergistic optimization.

[0077] Gas turbines can be combined with wind and solar power in integrated energy systems to achieve energy conversion and cascade utilization. The expression for a gas turbine model is:

[0078] (13)

[0079] (14)

[0080] In the formula, To dissipate heat, MW; Electric output, MW; , , The energy conversion efficiency coefficient; Gas consumption, m 3 ; The calorific value of natural gas is generally taken as 0.010833 MW / m3.

[0081] Combined heat and power (CHP) units are highly efficient energy utilization devices that not only improve energy efficiency but also reduce energy consumption and environmental pollution, making them an important component of modern energy systems. A CHP unit model is as follows:

[0082] (15)

[0083] In the formula, Thermoelectric ratio; For thermal output, MW; Electric output, MW.

[0084] An electric boiler, as an energy conversion device, has the ability to efficiently convert high-quality electrical energy into low-quality thermal energy. Its electrothermal conversion efficiency is usually expressed as the ratio of the actual heat energy generated to the electrical energy consumed during the conversion process; this ratio reflects the efficiency of the electric boiler in the energy conversion process. The electric boiler model is as follows:

[0085] (16)

[0086] In the formula, For electrothermal conversion efficiency; For the thermal output of the electric boiler, MW; Power consumption, in MW.

[0087] P2G systems can convert electrical energy into hydrogen or methane and integrate it into the natural gas network. This not only helps to distribute the peak load of gas turbines but also reduces the overall carbon dioxide emissions of the system, effectively improving the environmental protection capabilities of the energy system. The P2G system model is as follows:

[0088] (17)

[0089] In the formula, For P2G natural gas flow output, m 3 / h; Power consumption, in MW; For P2G conversion efficiency; L HV为 Low calorific value of natural gas, MJ / m 3 .

[0090] Currently, two main methods are used for power flow calculation in integrated energy systems. The first is the joint calculation method, which directly combines the equations of the three sub-networks and the characteristic equations of the coupling elements to form a complex non-homogeneous linear equation describing the overall integrated energy system. An iterative method is then used to calculate the power flow distribution. The second method is the discrete solution method, which arranges the calculation order of each sub-network based on the internal operating logic of the system and uses the Newton-Raphson method to calculate the power flow distribution sequentially. The power flow calculation results of the sub-networks are then transformed into the initial parameters of the next sub-network through the characteristic equations of the coupling elements. Because the discrete solution method is simple in structure, clear in principle, and requires less computation, this invention chooses this method to calculate the power flow of the integrated energy system.

[0091] The discrete solution method is an effective approach for calculating power flow in integrated energy systems. Its core idea lies in using the outputs of the coupled components at the slack nodes for iterative decomposition to gradually approximate the actual power flow distribution. During the iteration process, the method arranges the calculation order of each sub-network based on the system's internal operating logic, employing the Newton-Raphson method to calculate the power flow distribution sequentially. The power flow calculation results of each sub-network are transformed into the initial parameters of the next sub-network through the characteristic equations of the coupled components. Through iterative calculation, the power flow distribution of each system gradually approaches the true value. The iteration stops when the calculation results meet the convergence condition, and the final calculation result is output.

[0092] The sequential iterative solution strategy is adopted. The calculation sequence starts with the power network. The power flow calculation results of the power network are converted into the boundary conditions of the thermal network and the natural gas network through the coupled model of gas turbine, cogeneration unit, electric boiler and electric-to-gas equipment. Then, the power flow of the thermal network and the natural gas network are solved in sequence, and the power flow distribution of the whole network is converged through iterative calculation.

[0093] Alternatively, an integrated solution strategy can be adopted, combining the steady-state power flow control equations of the power system, thermal system, and natural gas system with the equality and inequality constraints of all coupled components (including but not limited to gas turbines, cogeneration units, electric boilers, and electric-to-gas conversion equipment) into a unified, large-scale nonlinear equation system. Subsequently, extended forms of the Newton-Raphson algorithm, interior-point methods, or homotopy extension methods based on modern computational algebra systems can be used to directly and synchronously solve this coupled system. Theoretically, this method can avoid the potential error propagation and convergence problems in sequential iterative solutions, but its computational complexity and requirements for algorithm robustness are significantly higher.

[0094] Of course, the multi-energy flow steady-state calculation problem can also be transformed into a nonlinear optimization problem. The core of this approach lies in defining an optimization model with the objective function of minimizing the sum of squared residuals of the power (electrical, thermal, and gaseous) balance equations at all system nodes. Subsequently, metaheuristic global search strategies such as genetic algorithms, particle swarm optimization, or simulated annealing are employed to optimize within the feasible region of the system's state variables, thereby obtaining a power flow solution that meets engineering accuracy requirements. This method does not rely on model derivative information and has lower requirements for the mathematical smoothness of the problem; however, its computational efficiency is usually limited by the problem size, and the global optimality of the solution is difficult to strictly guarantee.

[0095] Power flow calculation is a fundamental electrical calculation used to study the steady-state operation of a power system. Based on the calculated line voltages, network power flow distribution, and power flow losses, the operating state of the power system under steady-state conditions can be determined. Currently, the most commonly used method is the Newton-Raphson method, whose core idea is successive linearization, that is, successively approximating nonlinear equations to linear equations for solution.

[0096] The purpose of power flow calculation in a thermal system is to determine parameters such as the supply water temperature, return water temperature, and pipe flow rate of heat load nodes in the thermal network. The algorithms can be divided into the main loop method and the full assumption method, depending on the method used to determine the temperature of each node in the return water network (i.e., the return temperature of the heat load node). The core idea of ​​the main loop method is to find the longest branch in the thermal system network as the main branch. The supply and return water temperatures and flow rates of other branches in the network are then calculated from the main branch data. This method is suitable for long-distance, few-branch thermal network structures. However, the actual thermal networks in China are characterized by multi-branch radial structures, making the main loop method not entirely applicable. The full assumption method assumes that the return temperatures of all nodes are known and equal during calculation, and then uses an iterative method to calculate the network power flow. However, it ignores the heat loss of the return water network, resulting in excessive errors in practical applications.

[0097] The multi-branched, radial characteristics of heating networks render traditional power flow calculation methods unsuitable for practical applications. Therefore, this invention improves the power flow algorithm for heating networks by analogy to the forward-backward iteration method used in radial distribution networks. The optimized algorithm considers heat losses in the return water network, making it more applicable to the actual conditions in China. Through iteration, each node in the improved algorithm can adjust its return temperature in real time based on the return water flow rate, thereby improving the accuracy of the results.

[0098] The purpose of natural gas flow calculation is to determine the pressure and flow rate at various points in the network. Since the calculation involves fluid motion equations, the process is complex. To simplify the calculation, it is assumed that the temperature and gas properties of the natural gas remain constant during pipeline transportation, and that the friction coefficient of each pipe section is a constant value.

[0099] Based on the assumptions, let Za = 0.95, Ta = 288 K, and G = 0.589, equation (13) can be simplified to:

[0100] (18)

[0101] (19)

[0102] In the formula, This is the pipeline constant.

[0103] The simplified method uses the Newton mesh-node method for power flow calculation.

[0104] In this embodiment, a unified "power flow-energy flow" analysis method based on a discrete solution strategy is developed. To address the complexity of modeling and solving multi-energy flow coupled systems, this invention employs a discrete solution method based on the internal energy flow logic of the system. This method decomposes the coupled system into three relatively independent subsystems—electric, thermal, and gaseous—for iterative solutions by setting a reasonable calculation sequence, and exchanges data at the coupling interface through the characteristic equations of energy conversion elements. This strategy effectively reduces the solution difficulty while ensuring computational accuracy, and ultimately seamlessly imports the steady-state power flow calculation results into the energy flow model, forming a complete technical process from multi-energy flow calculation to energy flow distribution diagnosis.

[0105] An integrated energy system comprises multiple subsystems and multi-energy flow couplings. The power system transmits electrical energy, the natural gas system transmits natural gas, and the thermal system transmits heat via the flow of a working fluid. These three systems influence each other through coupling links. Backflow analysis involves establishing backflow mechanism models for each system and combining them with power flow calculation results to analyze the backflow distribution and losses of the entire integrated energy system.

[0106] In power system power flow calculations, active power flow is a key indicator, representing the actual flow of electrical energy within the system. Due to the high-quality characteristics of electrical energy, these active power flows can actually be considered as non-active flow, that is, the energy flowing in the system that can be converted into useful work. Meanwhile, active power loss refers to the energy loss caused by factors such as resistance and inductance during electrical energy transmission and conversion. This lost energy also exists in the form of non-active energy, hence it can be called non-active loss.

[0107] (20)

[0108] ;(twenty one)

[0109] In the formula, Current of power lines, kW; The active power of the power line is expressed in kW. Line loss, kW; The active power loss of the power line is expressed in kW.

[0110] The vortex distribution in a thermal system includes heat source vortex and heat load vortex, component vortex, supply and return water pipe losses, and heat load losses. A thermal system vortex model based on potential theory can effectively calculate the overall and local vortex distribution of the system.

[0111] Further, step S107 involves constructing a system current flow mechanism model based on the integrated energy system. The system current flow mechanism model includes nodal current potentials and branch currents, specifically including the following steps:

[0112] Step S1071: Define the node potential :

[0113] ;(twenty two)

[0114] In the formula, For node temperature; Ambient temperature; This is the specific heat capacity at constant pressure of the fluid.

[0115] The potential of a thermal system is defined by analogy with that of an electric field. The distribution of the thermal current in the system can be determined based on the potential and power flow data.

[0116] In this embodiment, a high-precision steady-state thermal flow model of the heating network considering return water heat loss was established. As the basis for backflow analysis, this invention addresses the shortcomings of existing thermal network models in describing the heat loss of the return water network by proposing an improved steady-state thermal flow model. This model explicitly quantifies the heat dissipation of the return water network by introducing a decay equation describing the change in return water temperature along the pipes, thereby significantly improving the calculation accuracy of thermal flow and temperature distribution in complex multi-branch radial topologies, and providing a reliable physical basis for subsequent backflow calculations.

[0117] Step S1073: Calculate the branch inrush flow based on the node potential and power flow parameters. The branch inrush flow includes heat source-heat load inrush, component inrush, supply and return water pipe inrush and heat load inrush.

[0118] By introducing a return water temperature decay equation to improve the steady-state thermal flow model, the heat dissipation of the return water network is explicitly quantified, making up for the shortcomings of the traditional model in describing the heat loss of the return water. This significantly improves the calculation accuracy of energy flow and temperature distribution in complex heat network topologies and lays a reliable physical foundation for thermal flow analysis.

[0119] By analogy with electric potential, the node potential of a thermal system is defined, and branch currents are calculated in combination with power flow parameters (covering the current loss of the entire process from heat source, components, pipe network, and load). This clearly depicts the current distribution and loss composition of the heating network, providing accurate quantitative basis for the efficiency assessment and optimization of integrated energy systems.

[0120] The water supply and return pipe losses are represented by the product of the difference in node potential and the pipe flow rate.

[0121] ;(twenty three)

[0122] In the formula, Damage to water supply pipelines, kW; Loss of return water pipe, kW; , For the nodes at both ends of the water supply pipeline; , The potential of the nodes at both ends of the return water pipe; The flow rate in the pipeline is expressed in kg / s.

[0123] By using the quantitative method of "node potential difference × pipeline flow rate", the quantitative calculation of supply and return water network losses is realized accurately and simply. This not only clearly links the physical logic of potential distribution and water flow parameters, but also improves the quantitative dimension of losses in the entire heating network, providing a direct and reliable calculation basis for the efficiency assessment and loss optimization of the heating network in the integrated energy system.

[0124] The energy gained by a working fluid at a high-temperature heat source and lost at a low-temperature load is called the heat source (×) and the heat lost (×) is called the load (×). The expression for heat source - heat load (×) is:

[0125] ;(twenty four)

[0126] In the formula, For heat source, kW; Heat load (kW); The power of the water supply node is expressed in kW·s / kg. The potential for return water flow is expressed in kW·s / kg. This is to create an advantage for export nodes; The flow rate at the heat source node is kg / s; denoted as the flow rate at the load node, in kg / s.

[0127] The unusable load loss caused by the mixing of working fluids at different temperatures at the return water node is called load loss, denoted as . The unit is kW.

[0128] (25)

[0129] Since the heat source is the heat provided by the high-temperature heat source and the load is the heat consumed by the load, they are not heat losses.

[0130] The flow rate of a component in a system can be expressed as the product of the nodal potential flowing into the component and the flow rate. Here, we take the flow rate of the supply and return water pipes as an example; the same applies to other components.

[0131] (26)

[0132] In the formula, For water supply pipeline flow, kW; For the return water pipe flow, kW.

[0133] The expression for the component flow is:

[0134] ;

[0135] In the formula, For water supply pipeline flow, kW; For the return water pipe flow, kW.

[0136] In multi-energy flow coupling analysis, natural gas, like water, is considered an energy carrier rather than a fuel. Therefore, in the construction of the natural gas system flow model, the flow characteristics in the pipeline of a thermal system are analogous to those of water flow, and a flow-load conversion relationship based on the calorific value of natural gas is established. At the same time, the losses caused by pressure changes are ignored, simplifying the calculation process.

[0137] (27)

[0138] (28)

[0139] (29)

[0140] In the formula, For natural gas system flow, kW; The energy quality coefficient of natural gas; Let K be the theoretical combustion temperature of natural gas. The total calorific value of natural gas is expressed in MJ / m³. 3 ; m is the natural gas flow rate. 3 / h.

[0141] This invention proposes a networked current-voltage mechanism model for integrated energy systems. It overcomes the limitations of treating integrated energy systems as black boxes for overall current-voltage calculations. By analogy with circuit theory, it introduces the concept of "current potential" into integrated energy systems and, based on this, constructs a distributed mathematical model capable of accurately describing current transmission, conversion, and loss in electricity, heat, and natural gas networks. This model deconstructs the abstract total system current-voltage into current and current-voltage losses for each branch and component in the specific network, thus achieving a transparent, "white-box" understanding of the evolution of energy quality within the system.

[0142] On the other hand, the present invention also proposes an electronic device for setting up a data processing module. The electronic device includes: at least one processor; a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform any of the integrated energy system multi-energy flow distribution and loss assessment methods.

[0143] On the other hand, the present invention also proposes a computer storage medium storing a computer program, which, when executed by a processor, implements a method for evaluating the multi-energy flow distribution and loss of an integrated energy system.

[0144] Those skilled in the art will understand that implementing all or part of the processes in the above embodiments can be accomplished by a computer program instructing related hardware, and can be stored in a non-volatile computer-readable storage medium. When executed, the program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Dual Data SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), Rambus Direct RAM (RDRAM), Direct Memory Bus Dynamic RAM (DRDRAM), and Memory Bus Dynamic RAM (RDRAM). The various embodiments described in this specification are presented in a progressive manner, and similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, for embodiments of apparatus, devices, and non-volatile computer storage media, since they are substantially similar to the method embodiments, the description is relatively simple, and relevant parts can be referred to the description of the method embodiments.

[0145] The above embodiments are merely illustrative examples and are not intended to limit the implementation. Those skilled in the art will recognize that other variations or modifications can be made based on the above description. It is neither necessary nor possible to exhaustively list all possible implementations. However, obvious variations or modifications derived therefrom are still within the scope of protection of this invention.

Claims

1. A method for assessing the multi-energy flow distribution and losses in an integrated energy system, characterized in that, include: Construct an integrated energy system, which includes an electric system, a heating system, a natural gas system, and coupling nodes, such that the electric system, the heating system, and the natural gas system all include power grid flow variables, heating network flow variables, and gas network flow variables; Based on the integrated energy system structure system power flow model, the system power flow model includes a power grid power flow model, a heating network power flow model, a gas network power flow model, and a coupling link model. The coupling link model includes a gas turbine model, a combined heat and power unit model, an electric boiler model, and a power-to-natural gas system model. The power flow parameters are calculated based on the system power flow model. Based on the aforementioned integrated energy system, a system flow mechanism model is constructed, which includes nodal flow potential and branch flow. Based on the aforementioned backflow mechanism model and the aforementioned power flow parameters, the link in the system where backflow exceeds a preset threshold is identified.

2. The method for assessing the multi-energy flow distribution and losses in a comprehensive energy system according to claim 1, characterized in that, The expression for the integrated energy system is: ； ； ； In the formula, The power balance equations for the power grid; For power flow variables in the power grid; For the power flow equation of the heating network; For heat network current variables; For the air flow equation; For gas flow variables.

3. The method for assessing the multi-energy flow distribution and losses in a comprehensive energy system according to claim 1, characterized in that, Based on the system power flow model, power flow parameters are calculated, including thermal parameters, specifically: Initialize the pipe water flow rate and node temperature to generate initial values; The actual flow rate corresponding to the heat load node is calculated based on the initial value; Based on the actual flow rate corresponding to the heat load node, the pressure and temperature of the heat load node are calculated in combination with the heat loss. Determine whether the pressure and temperature at the heat load node converge. If they converge, output the calculation results; otherwise, readjust the initial values.

4. The method for assessing the multi-energy flow distribution and losses in a comprehensive energy system according to claim 3, characterized in that, The expression for the heat network power flow model is: ； For nodes The return water temperature; For nodes The return water temperature; for , Inter-node pipe length; for , Water flow rate in the pipeline between nodes.

5. The method for assessing the multi-energy flow distribution and losses in an integrated energy system according to any one of claims 1 to 4, characterized in that, Based on the aforementioned integrated energy system, a system current flow mechanism model is constructed. This model includes nodal currents and branch currents, specifically comprising: Define node potential : ； In the formula, For node temperature; The ambient temperature; The specific heat capacity at constant pressure of the fluid; The branch inrush flow is calculated based on the node potential and the power flow parameters. The branch inrush flow includes heat source-heat load inrush, component inrush, supply and return water pipe inrush and heat load inrush.

6. The method for assessing the multi-energy flow distribution and losses in a comprehensive energy system according to claim 5, characterized in that, The expression for the heat source-heat load is: ； In the formula, For heat source, kW; Heat load (kW); The power of the water supply node is expressed in kW·s / kg. The potential for return water flow is expressed in kW·s / kg. This is to create an advantage for export nodes; The flow rate at the heat source node is kg / s; The flow rate at the load node is kg / s.

7. The method for assessing the multi-energy flow distribution and losses in a comprehensive energy system according to claim 5, characterized in that, The expression for the component flow is: ； In the formula, For water supply pipeline flow, kW; For the return water pipe flow, kW.

8. The method for assessing the multi-energy flow distribution and losses in an integrated energy system according to any one of claims 1 to 4, characterized in that, The loss in the supply and return water pipes is represented by the product of the difference in node potential and the water flow rate in the pipes.

9. An electronic device, characterized in that, include: At least one processor; A memory that is communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the integrated energy system multi-energy flow distribution and loss assessment method as described in any one of claims 1 to 8.

10. A computer storage medium, characterized in that, The system contains a computer program that, when executed by a processor, implements the method for assessing the multi-energy flow distribution and losses of an integrated energy system as described in any one of claims 1 to 8.

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