An Improved Method for Optimal Scheduling of Electricity-Gas Interconnected Integrated Energy Systems

Abstract

This invention relates to an improved method for optimal scheduling of an integrated power-electricity interconnected energy system, belonging to the field of electrical technology. The method includes the following steps: S1) analyzing the structure of the integrated power-electricity interconnected energy system; S2) building a mathematical model for optimal scheduling of the integrated power-electricity interconnected energy system; S3) solving and comparing the optimal scheduling methods of the integrated power-electricity interconnected energy system; and S4) performing simulation analysis of the optimal scheduling of the integrated power-electricity interconnected energy system. Based on decoupling analysis, this invention addresses the problems of existing distributed power flow calculation methods for integrated power-electricity interconnected energy systems by proposing an improvement based on the Schmitt orthogonal method. The improved method and the original optimal scheduling method are simulated separately, and the results are analyzed. The improved method reduces the condition number to 1 through preprocessing, reducing the number of iterations and shortening the calculation time, thereby improving computational efficiency.

Description

Technical Field

[0001] The improved method for optimizing the scheduling of an integrated energy system with electrical-gas interconnection, as described in this invention, belongs to the field of electrical technology. Background Technology

[0002] The input of the integrated electric-gas energy system consists of electricity, renewable energy, and natural gas. Through the interactive conversion of various coupling devices, the output delivers either electricity or natural gas. That is, energy is obtained from the natural gas system via a gas-fired system and a combined heat and power (CHP) system. It flows to the power system, and the conversion of electrical energy into natural gas energy flow is achieved through peer-to-peer (P2G) communication, thus realizing the interconnection between the two networks.

[0003] Numerous studies, both domestic and international, have been conducted on modeling energy networks with interconnected electric and gas systems. For steady-state system models, one paper proposed a unified modeling framework for interconnected electric and gas systems, and combined it with commonly used safety-constrained unit combination methods to study the impact of the natural gas system on the natural gas supply of gas-fired units, validating its applicability. The research project "Cooperative Planning of an Integrated Electric-Gas Hybrid Energy System with Electric-to-Gas Converter" in a new environment studies the cooperative planning of an integrated electric-gas hybrid energy system with electric and gas devices. It models the energy center, including the heat-electric interconnection (CHP) unit, and establishes an integrated energy system model with linear power flow distribution characteristics.

[0004] Meanwhile, scholars have also expanded and extended their research on modeling integrated energy systems with interconnected power and gas systems to some extent. The paper "Stochastic Optimal Power Flow in Integrated Energy Systems with Interconnected Power and Gas Systems Based on Chance-Constrained Programming" mainly discusses the distributed optimization problem of such systems considering cross-regional wind energy consumption. To characterize the uncertainty of wind energy output, the model introduces chance-objective constraint programming based on the transmission limit of cross-regional tie lines. However, the problem is that this solution still lacks specificity. Some foreign literature has also established electro-thermal interconnection models, but these use a centralized approach and do not consider the modeling of network coupling elements. It should be noted that the modeling of coupling elements is crucial in the modeling of integrated energy systems, involving the relationships between energy conversions; neglecting this will affect reliability. The general modeling method proposed in "A Review and Outlook on the Optimization Planning and Operation of Energy Hubs in the Energy Internet" is based on complex coupled systems and uses the energy tracking method to obtain an accurate energy allocation mechanism. However, for current IES coupling, this modeling method cannot accurately describe the network operating characteristics. "A Topology Model of the Energy Internet Based on Complex Hybrid Networks" proposes a modeling method based on complex hybrid networks, featuring unique energy and network location allocation mechanisms. However, the theory is relatively abstract, making it difficult to describe the specific characteristics of multi-energy-flow network variables. "An Overall Energy Transport Model in an Electric-Heat Integrated Energy System" introduces the concept of heat dissipation resistance and uses an energy flow method to homogenize the heating and power systems in an integrated energy system (IES). However, it neglects the local characteristics of the heat treatment fluid, potentially leading to significant errors in the final results. Based on the various studies described in the aforementioned documents, it is currently difficult to find a universal model for integrated energy systems; that is, it is difficult to solve problems with a unified model, even though such models are rarely established. Some models can accurately describe the complexity and variability of reality. We can flexibly handle system models according to research priorities. For some interconnected systems with lower reliability requirements, a universal model can be used. However, for some important systems, the integrated energy domain has high requirements for the economic scheduling and operation of the system, and each part of the system can be divided into separate models for analysis.

[0005] At this stage, a widely accepted and applied general modeling method for Energy Systems (IES) exists, which is currently a research hotspot. It is based on the EnergyHub (EH) integrated energy system model. In principle, an EH can be viewed as an energy integration node in an energy network, where energy flows are coupled and interact, thus it can be considered a multi-input, multi-output node model. An EH has three stages: energy production, conversion, and storage. It can accept various energy sources as external inputs, such as electricity, gas, heat, and cooling. To meet the needs of end users, the EH can use various internal devices to form different distribution schemes when external energy is input. Related research, represented by the EH model, has analyzed in detail the coupling relationships and synergistic optimization between the electricity, natural gas, and heat systems (electricity / gas / heat). The shortcoming of the traditional EH model is that, from the perspective of the power grid, it cannot reflect the reactive power changes between the transmission network and the integrated energy system. Furthermore, when connecting the electrical components of a regional integrated energy system to the distribution system, the electrical system (composed of microgrids and connected distribution systems) may experience three-phase imbalances, making it difficult to consider traditional models. Future EH research needs to focus more on dynamic modeling methods and establish linear dynamic process expressions based on the linear relationship between inputs and outputs. Furthermore, attention should be paid to models that couple to the device control level to make the calculation results more accurate.

[0006] Currently, power grids and natural gas networks are planned and designed separately. With the increasing coupling and interaction of energy networks within energy systems (IES) due to facilities such as P2G and CHP (combined heat and power), it is necessary to consider the mutual influence of these two networks at the planning and design levels. In long-distance and trans-regional IESs, the combined power-gas network is often the mainstay. Modeling IES planning problems is complex, requiring simplified models or the selection of appropriate modeling methods based on a certain level of computational accuracy. Furthermore, traditional intelligent algorithms are relatively complex to solve, necessitating in-depth research into simpler solution algorithms.

[0007] Currently, there are still many issues that require further research and analysis in areas such as the research of electric-gas interconnected integrated energy systems, model simulation, collaborative planning, the establishment of reliability models, the improvement of algorithm speed and accuracy, the optimization of scheduling operations, and economic analysis. Summary of the Invention

[0008] In order to solve the problems mentioned in the background art, the present invention proposes an improved method for the optimized scheduling of an integrated energy system with interconnected electricity and gas.

[0009] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: an improved method for optimized scheduling of an integrated energy system with interconnected electricity and gas, characterized by the following steps:

[0010] S1) Analyze the structure of the integrated energy system with electrical-electrical interconnection;

[0011] S2) Establish a mathematical model for the optimal scheduling of an integrated energy system with interconnected electrical and gas systems;

[0012] S3) Solve and compare the optimal scheduling of the integrated energy system with electrical-gas interconnection;

[0013] S4) Simulation analysis of optimized scheduling of integrated energy system with electrical-gas interconnection.

[0014] Compared with the prior art, the present invention has the following advantages:

[0015] 1. This invention takes the integrated energy system of electric-gas interconnection as the research object, sets the optimization scheduling objective and system operation constraints, and is committed to improving the optimization scheduling model and solution algorithm of the electric-gas interconnection energy system, so as to optimize the system model and obtain the optimal solution;

[0016] 2. Based on the collected data, the decoupling approach of the system was summarized. Decoupling distributed power flow calculation was performed on the integrated energy system of electric-gas interconnection. The conclusion is that compared with centralized hybrid power flow calculation, decoupling distributed is more efficient and easier to perform targeted analysis.

[0017] 3. Based on the decoupling analysis, an improvement approach based on the Schmidt orthogonal method is proposed to address the problems existing in the distributed power flow calculation method of the existing electric-gas interconnected integrated energy system.

[0018] 4. Simulations were performed on the improved and original optimization scheduling methods respectively, and the results were analyzed. The conclusion is that the improved method reduces the condition number to 1 through preprocessing, thereby reducing the number of iterations and shortening the computation time of iterations, thus improving the computational efficiency. Attached Figure Description

[0019] The present invention will now be described in further detail with reference to the accompanying drawings;

[0020] Figure 1 This is a current system structure diagram of the electrical-gas interconnected integrated energy system in this invention;

[0021] Figure 2 This is a diagram showing the energy and information transmission paths of the electro-pneumatic interconnected integrated energy system in this invention.

[0022] Figure 3 This is a diagram showing the energy flow transmission path of the power-to-gas conversion plant in this invention;

[0023] Figure 4 This is a flowchart of the hybrid power flow calculation for the electrical-gas interconnected integrated energy system in this invention;

[0024] Figure 5This is a computational network structure diagram of the integrated energy system with electrical-gas interconnection in this invention;

[0025] Figure 6 This is a flowchart of the power flow calculation for the improved electrical-electric interconnected integrated energy system in this invention;

[0026] Figure 7 This is a computational network structure diagram of the integrated energy system with interconnected electrical and gas systems in this invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are some embodiments of the present invention, but not all embodiments; based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] The improved method for optimal scheduling of an integrated energy system with interconnected electrical and gas systems, as described in this invention, is characterized by comprising the following steps:

[0029] S1) Analyze the structure of the integrated energy system with electrical-electrical interconnection;

[0030] S2) Establish a mathematical model for the optimal scheduling of an integrated energy system with interconnected electrical and gas systems;

[0031] S3) Solve and compare the optimal scheduling of the integrated energy system with electrical-gas interconnection;

[0032] S4) Simulation analysis of optimized scheduling of integrated energy system with electrical-gas interconnection.

[0033] The content of step S1) analyzing the structure of the electric-gas interconnected integrated energy system includes the composition architecture of the electric-gas interconnected integrated energy system, the main equipment and energy information flow path of the electric-gas interconnected integrated energy system, and the analysis of the coupling equipment of the electric-gas interconnected integrated energy system.

[0034] S11) Composition Architecture of Electric-Interconnected Integrated Energy System

[0035] The integrated power-gas (E-Gas) energy system uses gas turbine units and combined heat and power (CHP) units to transfer energy from the natural gas system to the power system, and achieves the conversion of electrical energy into natural gas energy flow through power-to-gas (P2G) units, thereby realizing the interconnection and coupling between the two networks. The current system structure is as follows: Figure 1The diagram illustrates the coupling relationship between the power grid and the gas grid. Generating units and renewable energy generation provide energy input to the grid. Energy conversion is achieved through coupling equipment such as gas turbines and P2G (Power-to-Gas) systems. Electrical energy is converted into natural gas and output to storage tanks, or natural gas is converted back into electricity and output to the power grid. During energy transfer, electrical energy is converted into gas energy via electro-gas conversion, and gas energy is converted into electrical energy via gas turbines. In the energy conversion stage, coupling equipment enables the mutual conversion and interaction of energy flows. In these two stages, the various energy flows are in a highly interactive and coupled state, realizing a multi-energy complementary mechanism and the technical characteristics of integrated energy flow.

[0036] S12) Main equipment and energy information flow path of the electrical-interconnected integrated energy system

[0037] The main equipment in an integrated energy system with interconnected electrical and gas systems includes: energy generation and storage equipment, energy transfer equipment, coupling equipment, and information exchange equipment.

[0038] To optimize the use of renewable energy, energy and information exchange and conversion occur frequently in interconnected power and gas systems. The energy and information flow paths between interconnected power and gas systems are as follows: Figure 2 As shown, the overall system includes a power system, a natural gas system, and an energy center; energy storage and gas storage equipment, gas turbine units, and power-to-gas conversion plants all belong to the energy center.

[0039] As the most important components of an integrated electricity-gas energy system, the power system is not significantly different from a conventional power system, while the natural gas system mainly consists of long-distance gas transmission networks and gas pipelines. As energy transmission systems, the power system and the natural gas system share many similarities:

[0040] In terms of transmission distance, both systems have large-scale and high-level energy transmission networks, and both electricity and natural gas can be transmitted over long distances with large capacity.

[0041] In terms of transmission speed, electricity is transmitted at the speed of light, which is very fast; while natural gas is usually transmitted in the form of liquid or gas, which is slower. At the same time, considering that the transmission of natural gas is also affected by the resistance of fluid flow and the differences in the shape and manufacturing process of natural gas pipelines, the transmission speed of natural gas systems is much slower than that of electricity systems.

[0042] In terms of transmission costs, the power transmission lines are currently quite mature, making it very convenient to carry out large-capacity transmission, so the transmission costs are low; while natural gas transportation requires the laying of pipelines or sea transport ships, and gas fields are generally far from urban load centers, which leads to higher transmission costs.

[0043] In terms of energy storage capacity, given that current electricity storage technology is not yet mature and electricity is instantaneous (i.e., it is generated and used immediately), it is still very difficult to achieve large-scale long-term storage of electricity. On the other hand, natural gas can be stored on a large scale for medium and long term using huge pipelines or storage facilities.

[0044] S13) Coupling equipment for an integrated energy system with electrical interconnection

[0045] Gas turbines and power-to-gas (P2G) plants, which connect the power grid and the natural gas grid, serve as coupling devices in an integrated power-gas interconnected energy system. The core of the P2G plant is power-to-gas (P2G) technology, which converts electrical energy into gaseous fuel, enabling the transfer of energy from the power system to the natural gas system.

[0046] Electro-to-gas technology refers to the process of using electrical energy to convert water (H2O) and carbon dioxide (CO2) into hydrogen (H2) or methane (CH4). It consists of two steps: the first step is the electrolysis of water to produce hydrogen, which separates water into hydrogen and oxygen; the second step is the hydrogen methanation process, which uses the hydrogen produced in the first electrolysis process to reduce carbon dioxide to produce artificial methane under high temperature, high pressure and catalyst conditions. The synthesis efficiency is generally 60-80%.

[0047] The first step, obtaining hydrogen and oxygen through water electrolysis, is an endothermic reaction, and the chemical reaction can be represented by the following equation:

[0048]

[0049] The second step, methanation, is an exothermic reaction. Because the chemical reaction proceeds more readily at low temperatures, a highly active catalyst is needed to achieve low-temperature CO2 methanation. Catalytic reactions applied in P2G technology mainly include chemical methanation and biomethanation. The chemical formula for the methanation reaction is as follows:

[0050] CO2 + 4H2 → CH4 + 2H2O

[0051] The energy flow transmission path of the power-to-gas conversion plant is as follows: Figure 3 .

[0052] The method for building a mathematical model for the optimal scheduling of an integrated energy system with interconnected electricity and gas in step S2) includes the following steps:

[0053] S21) Mathematical Model of Electric-Interconnected Integrated Energy System

[0054] The model of the integrated electric-gas energy system involves two energy networks: the power grid and the natural gas pipeline network. The modeling of the natural gas network involves the pipeline pressure drop formula, the nodal flow equation, and the ring energy equation, which can be analogized to Ohm's law, Kirchhoff's current law, and Kirchhoff's voltage law for the power grid, respectively. The gas network can be analogized to the power grid analysis.

[0055] S211) Power Grid Model

[0056] The power network modeling in an integrated energy system with interconnected electrical and gas systems is analogous to that of a conventional power system. Based on the nodal and loop equations of the power grid, branch and nodal admittance matrices are derived, and the active power P at each node is determined. i and reactive power Q i It can be represented as follows:

[0057]

[0058]

[0059] In the formula, V i and V j Let δ be the node voltages of i and j. ij G is the phase angle difference between the two nodes; while G ij and B ij These are the conductance and susceptance of the line between nodes i and j, respectively.

[0060] Since the calculation of such a power grid model containing active and reactive power requires solving a large number of nonlinear equations, it will undoubtedly increase the difficulty of solving the problem. If the power grid model is linearized, the difficulty of solving the problem can be greatly reduced. Introducing DC power flow equations allows voltage amplitude to be calculated in the transmission network planning model based on DC power flow, reducing the calculation difficulty. For the more complex IES architecture, selecting a suitable power grid model is even more important.

[0061] S212) Natural Gas Network Model

[0062] When solving for natural gas network flow, the main focus is on pipeline pressure and node flow. Because natural gas is compressible and a fluid, the different conditions in different parts of the network mean that the gas network cannot be as stable as a power grid. The parameters determining natural gas flow are: gas pressure, gas density, and gas velocity within the pipeline. All three are related to pipeline length and time. Generally, the steady-state and transient flows of natural gas are described using equations of motion, continuity equations, and state equations. The three equations are as follows:

[0063]

[0064]

[0065] p=ZρRT (5)

[0066] In the formula, ρ is the gas density; W is the flow velocity in the gas pipe; p is the gas pressure; τ is the unit time; x is the pipe length; g is the acceleration due to gravity; α is the angle between the pipe and the horizontal plane; μ is the pipe friction coefficient; d is the pipe inner diameter; Z is the compressibility factor; R is the molar gas constant; and T is the absolute temperature.

[0067] In equation (3), gρsinα describes the separation impulse of gas gravity along the pipe axis. Describes the frictional impulse of the pipeline;

[0068] However, the above three equations form a system of nonlinear partial differential equations, which are very difficult to solve. Moreover, these three equations are not convenient for solving for flow rates. Considering that most natural gas networks are ring networks, the model uses the pipeline pressure drop formula, the nodal flow equation, and the ring energy equation, as follows:

[0069]

[0070]

[0071]

[0072] In the formula, M ij d is the pipe resistance coefficient; ij Characterizes the direction of natural gas flow within the pipeline; f ij The flow rate in the same pipe; while π i Indicates the node air pressure at point i in the pipeline network; a ij For node branch association elements, representing whether pipeline branch j and node i are associated; F i External energy injected into node i; b ij For loop association elements, M represents whether branch j is in the i-th loop; j Let π be the resistance coefficient of pipe branch j. i π represents the nodal air pressure at point i in the pipeline network; j Indicates the nodal air pressure at point j in the pipeline network; f j This represents the flow rate in branch i of the pipeline network;

[0073] Equation (6) represents the flow equation of a pipeline node with n branches, and Equation (7) represents the ring energy equation of a network loop with n pipeline branches.

[0074] S213) Mathematical Model of Coupled Element Device

[0075] (1) Gas turbine modeling

[0076] As a crucial energy conversion device between electricity and natural gas networks, gas turbines offer numerous advantages, such as flexible start-stop and energy cascade utilization. Currently, the power generation conversion rate of a single-cycle gas turbine is 30-40%, while that of a combined-cycle gas turbine is 50-60%. The gas turbine is modeled within an integrated electricity-gas energy system as follows:

[0077]

[0078] In the formula, P t and f t These represent the output power of the gas turbine and the gas flow rate it consumes, respectively; α, β, and υ are the energy consumption coefficients of the gas turbine, respectively.

[0079] Equation (9) can characterize the coupling relationship between the power grid and the natural gas grid to a certain extent;

[0080] (2) Modeling of the electro-gas conversion device

[0081] The power-to-gas (P2G) unit is a device that uses electricity as input, produces hydrogen using water electrolysis technology, and then uses the hydrogen to produce methane through incomplete combustion with carbon. With the popularization of natural gas, P2G is gradually becoming more important in today's integrated power-gas energy system. Together with gas turbines, it realizes the energy conversion between electricity and natural gas, and further deepens the coupling between the power grid and the gas grid.

[0082] If we consider the power-to-gas converter as a load on the power grid, the mathematical model for the power-to-gas converter is as follows:

[0083] E P2G =P P2G tη PzG γ E (10)

[0084]

[0085] In the formula, P P2G η represents the electrical power consumed by the electro-gas conversion device, t represents the equipment operating time, and η represents the total electrical power consumed by the device. P2G For conversion efficiency, γ E E is the coefficient for the conversion of electrical energy to heat. P2G H represents the output energy value of the electro-gas conversion device. G f represents the calorific value of natural gas. P2G The output flow rate of natural gas from the electro-gas conversion unit;

[0086] Based on the analysis of various aspects of the mathematical model of the integrated energy system with interconnected electrical and gas systems, the mathematical model of the integrated energy system with interconnected electrical and gas systems with n nodes is summarized as follows:

[0087]

[0088]

[0089]

[0090]

[0091]

[0092] In the integrated energy system network of electric-gas interconnection, gas turbines burn natural gas to generate electricity, and electric-to-gas converters consume electricity to produce natural gas.

[0093] S22) Optimize the scheduling objective function

[0094] In the optimization operation solution of the electric-gas interconnected integrated energy system in this invention, the optimization objective function only considers the generator cost and gas source input cost, and does not consider the internal operating costs of the gas turbine and P2G (that is, the system network of this design is regarded as an internal network, and internal cost losses are not considered).

[0095] The interior-point method is used to solve this problem. It is assumed that the operation and scheduling of the integrated electricity-gas energy system network is handled by a single organization with unlimited information exchange. Based on the price curves of electricity purchased externally and gas purchased internally, the optimization objective is to minimize the system's 24-hour operating cost. The objective function is expressed as:

[0096] minC E +C G (17)

[0097] Where C E and C G These represent the total operating costs of the power grid and the natural gas grid over 24 hours, respectively. They can be expressed as:

[0098]

[0099]

[0100] In the formula, Let i represent the i-th coal-fired power unit and its price parameters. For the hourly output of the i-th coal-fired unit, Let i be the cost of the i-th gas source in the natural gas network. Let i be the hourly flow rate of the i-th gas source;

[0101] S23) Operational constraints of the integrated energy system with electrical interconnection

[0102] (1) Power grid constraints

[0103] There are two types of grid constraints: power balance constraints and generator output constraints. These two constraints are as follows:

[0104] ∑ d∈i P Gd，t +∑ d∈i PG Td，t +∑ d∈i P WTd，t =∑ d∈i P P2Gd，t +∑ d∈i P Ld，t (20)

[0105]

[0106] In the formula, P G For the hourly output of the coal-fired unit, P GT To provide power to the gas turbine unit, P wT P contributes power to the wind farm P2G For the power consumption of the electro-gas conversion device, P L For electrical load; P Gi P represents the hourly output of the coal-fired unit at node i; GTi This represents the hourly output of the gas turbine at node i; This represents the minimum output per hour of the coal-fired unit at node i; This represents the maximum hourly output of the coal-fired unit at node i; This represents the minimum output per hour of the gas turbine at node i; This represents the maximum output per hour of the gas turbine at node i;

[0107] (2) Natural gas network constraints

[0108] There are five types of constraints in a natural gas network: gas source constraints, gas load constraints, pipeline pressure constraints, pressure-flow relationship constraints at nodes in the gas transmission pipeline, and node flow balance equations.

[0109]

[0110]

[0111] n min ≤π≤π max (twenty four)

[0112]

[0113] E×f G =F×f L +A×f P (26)

[0114] In the formula, f G f is the gas source flow rate. LHere, E represents the natural gas load flow rate, F represents the node-gas source correlation matrix, F represents the node-load correlation matrix, and A represents the node-pipeline correlation matrix; π represents the gas pressure at the pipeline node; f ij f ij M represents the flow rate in the same pipe. ij d ij π i The meaning is the same as before; f p Indicates the pipeline natural gas flow rate;

[0115] (3) Constraints of coupling element device

[0116] The constraints of the gas turbine with coupling element device are:

[0117]

[0118] In the formula: f t This represents the gas flow rate consumed by the gas turbine; α, β, and υ are the energy consumption coefficients of the gas turbine, respectively.

[0119] The constraints of the coupling element device P2G are:

[0120]

[0121] In the formula: f P2G P represents the natural gas flow rate output by the P2G system; P2G η is the electrical power consumed by the P2G; t is the device operating time; η is the electrical power consumed by the P2G. P2G For conversion efficiency; γ E H is the coefficient for converting electrical energy to heat. G This refers to the calorific value of natural gas.

[0122] Step S3) Solving and comparing the optimal scheduling of the integrated energy system with the power grid: The optimal scheduling problem of the integrated energy system with the power grid is simplified to first performing power flow calculation using the NL method on the power flow model established in the mathematical model of the integrated energy system with the power grid to obtain the active power and power angle of the power grid, and the flow and pressure of the natural gas network. Then, the interior point method is used to optimize the scheduling of the integrated energy system with the power grid, specifically including:

[0123] S31) Optimized scheduling of integrated energy systems with electrical interconnection

[0124] S311) Power flow solution using the NL method.

[0125] This paper analyzes the unified energy path theory of the integrated energy system of electric-gas interconnection. Based on the analogy of natural gas circuits, network analysis and power flow calculations are performed on the integrated energy system of electric-gas interconnection. The one-dimensional flow of natural gas in the pipeline is expressed by the mass conservation equation and the momentum conservation equation. Then, two commonly used approximations, "ignoring the convection term" and "approximating the velocity square term of the resistance term with incremental linearization", are introduced into the momentum conservation equation. A linear equation is derived that rewrites the resistance term as velocity. Then, based on the equation of state of natural gas and the definition of pipeline flow rate, the circuit analogy of natural gas is summarized, and this summary is extended and equivalent.

[0126] Table 1 Comparison of Natural Gas Circuits

[0127]

[0128] Due to the different selection methods of the power grid and gas grid balance nodes, there are four operating modes of the power-gas interconnected integrated energy system: (1) The power grid selects the gas turbine as the balance node and the gas grid selects the P2G gas source as the balance node, and the two networks are fully coupled; (2) The power grid selects a non-gas turbine as the balance node and the gas grid selects the P2G gas source as the balance node, and the two networks are not fully coupled; (3) The power grid selects the gas turbine as the balance node and the gas grid selects a non-P2G gas source as the balance node, and the two networks are not fully coupled; (4) The power grid selects a non-gas turbine as the balance node and the gas grid selects a non-P2G gas source as the balance node, and the two networks are completely decoupled.

[0129] The flowchart of the hybrid power flow calculation for an integrated energy system with interconnected electrical and gas systems is as follows: Figure 4 As shown:

[0130] S312) Parameter values ​​for the integrated energy system with electrical interconnection

[0131] The following section uses an extended NL method to perform hybrid power flow calculations on an interconnected power system based on an IEEE 9-node power grid and a 7-node natural gas grid. The example network structure of the interconnected power system is shown below. Figure 5 As shown in the figure. GA1 is the external gas source of the gas network, G1 and G2 are external coal-fired power units of the power grid, GT1 is a gas turbine, and WP1 is a P2G. The network coefficients of the 7-node gas network system are shown in the table below.

[0132] Table 2 Natural Gas Network Node Parameters

[0133]

[0134] Table 3 Natural Gas Network Pipeline Parameters

[0135]

[0136] S313) Solving optimal scheduling using interior point method

[0137] The basic idea of ​​the interior-point method is to start with an interior point, find subsequent interior points that decrease the objective function value in feasible directions, and then, starting from the obtained interior points, find interior points that decrease the objective function value in another feasible direction. Repeating these steps yields a sequence of interior points that ensure the objective function value decreases strictly monotonically, stopping the iteration when a termination condition is met. This avoids the aforementioned handling of inequality constraint sets.

[0138] A notable characteristic of this type of algorithm is that the number of iterations is almost independent of the system size. It was originally used to solve linear programming problems, but has now been extended to solve quadratic programming and direct nonlinear programming models.

[0139] S32) Analyze and optimize existing scheduling problems

[0140] Depending on whether there is a unified dispatch center at the higher level, the optimal dispatch schemes for integrated energy systems with interconnected power and gas networks are divided into centralized optimal dispatch and distributed optimal dispatch. Distributed optimal dispatch algorithms calculate and solve for the two networks separately, then perform collaborative analysis based on the coupling parameters and related parameters of the two systems. Centralized optimal dispatch refers to centrally processing and analyzing the relevant parameters of the power grid and gas network from the start of operation, constructing a composite Jacobian matrix for unified calculation, thereby obtaining the optimal power flow of the system.

[0141] Although the optimization scheduling algorithm in this paper separates the two networks, treating P2G as grid load and gas turbine as gas grid load for calculation, it essentially still uses the NL method for calculation. Here, due to the large system scale, the final number of iterations is too large, and the initial system input parameters will greatly affect the calculation time and accuracy. The Jacobian matrix is ​​not simple enough, so we need to consider simplifying the Jacobian matrix to shorten the system iteration time.

[0142] S33) Improved Optimization Scheduling Method

[0143] To improve the computational speed of the NL method, it is planned to preprocess the Jacobian matrix. To reduce the condition number of this matrix and accelerate convergence, existing methods include: incomplete LU decomposition, block diagonal matrix method, PQ decomposition, coefficient approximate inverse preprocessing method, and Jacobian inverse preprocessing method. The incomplete LU decomposition method suffers from the problem of choosing the filler amount, the PQ method is relatively cumbersome in obtaining the preprocessing matrix, and the principle of the inverse preprocessing method is slightly more complex.

[0144] The condition number (Cond(J)) gradually decreases non-monotonically with the increase of the number of iterations and approaches 1. At this point, if the condition number can be reduced through preprocessing, the convergence of the Jacobian matrix can be made simpler. It would be even better if the condition number of the Jacobian matrix could be directly reduced to 1 using the Schmitt orthogonal method.

[0145] Currently, the Schmitt orthogonal method is mainly used for orthogonal matrix transformations.

[0146] A power flow algorithm for an integrated energy system with interconnected electricity and gas networks is proposed, based on the Schmidt orthogonal method for preprocessing the Jacobian matrix. First, the locations of the slack nodes in the power network (natural gas network) are determined. Then, the power flow is calculated using the NL method to form the Jacobian matrix. This matrix is ​​then preprocessed using the Schmidt orthogonal method, followed by iterative calculations. The algorithm checks if the output conditions are met. If so, it outputs the power and power angle of the power network, the flow rate of the natural gas network, and the gas pressure of each node, and continues with the next step of interior-point optimization scheduling. The improved power flow calculation flowchart is shown below. Figure 6 As shown.

[0147] Step S4) involves simulation analysis of the optimized scheduling of the integrated energy system with electricity and gas interconnection. This simulation focuses on the improved optimized scheduling algorithm and compares it with existing distributed optimization algorithms in terms of matrix condition number, iteration time, number of iterations, and final optimization results. First, simulation analysis of distributed power flow calculation using the NL method is performed on an integrated energy system with an IEEE 9-node power grid and a 7-node natural gas grid. Then, based on the effectiveness of preprocessing the Jacobian matrix using the Schmidt orthogonal method for the optimized scheduling of the integrated energy system with electricity and gas interconnection, the algorithm is compared and analyzed by comparing the matrix condition number and number of iterations between the improved optimization with Schmidt orthogonal optimization and the distributed optimization without Schmidt orthogonal optimization. Finally, using Matlab 2016a, the optimized scheduling simulation of the integrated energy system with electricity and gas interconnection, decoupled into two network systems (electricity grid and gas grid), is performed using the interior-point method.

[0148] The following section provides a detailed explanation of the simulation analysis for the optimized scheduling of an integrated energy system with interconnected electrical and gas systems, based on practical applications. The specific content includes:

[0149] S41) Simulation Analysis of Optimized Scheduling Algorithm

[0150] Simulation Case Introduction

[0151] To verify the actual effect of the distributed optimization method for the integrated energy system with electric and gas interconnection proposed in Chapter 3 on system optimization, this invention conducts simulation analysis of distributed power flow calculation using the NL method on an electric and gas interconnection system based on an IEEE 9-node power grid and a 7-node natural gas grid.

[0152] The computational network structure of the integrated energy system with electrical-gas interconnection is as follows: Figure 7 As shown.

[0153] The diagram shows the IEEE 9-node system. The original system contained 3 generators. G1 and G2 are coal-fired power units outside the power grid as power sources, and GT1 is a gas turbine as power source. They are connected to nodes 3, 2, and 1 of the power grid, respectively. The input of GT1 is connected to node 1 of the natural gas network, and the output is connected to node 1 of the power grid. WP1 is a P2G, with its input connected to node 8 of the power grid and its output connected to node 4 of the natural gas network. GA1 is an external gas source for the gas network and is connected to node 1 of the gas network.

[0154] The network coefficients of the 7-node gas network system are shown below:

[0155] Table 4 Natural Gas Network Node Parameters

[0156]

[0157]

[0158] Table 5 Natural Gas Network Pipeline Parameters

[0159]

[0160] The cost of energy supply from three natural gas sources is $14 / m³. 3 and $15 / m 3 The energy supply costs of the three power sources are $11 / MW·h, $8.5 / MW·h, and $12.25 / MW·h, respectively.

[0161] Based on the parameter correspondence between the natural gas network and the power grid, after decoupling, from the perspective of the gas network, the gas turbine is considered as a load connected to node 1. The gas source flow rate can be equivalent to the active power of the power source in the power grid, the gas load flow rate can be equivalent to the active power injected into the load by the bus in the power grid, and the gas load inertial flow rate can be equivalent to the reactive power injected into the load by the bus in the power grid. The maximum and minimum gas pressure values ​​are equivalent to the node voltage constraints, the pipeline parameter M is equivalent to the square of the line resistance value in the power grid, and the pipeline inertial parameter K is equivalent to the square of the line reactance value in the power grid. After decoupling, the power-to-gas conversion device is considered as an 8-node load in the power grid. Based on the parameter correspondence, the active power and resistance of this load can be calculated and converted into a capacitor connected in parallel with the bus.

[0162] Based on the above equivalent relationships, the node, branch, and power source (gas source) parameter matrices of the two decoupled systems can be calculated as follows:

[0163] (1) Power grid system parameter matrix:

[0164] Node parameter matrix

[0165]

[0166] Branch parameter matrix

[0167]

[0168] Generator parameter matrix

[0169]

[0170] (2) Natural gas network system parameter matrix (equivalent to power grid):

[0171] Node parameter matrix

[0172]

[0173] Branch parameter matrix

[0174]

[0175] Gas source parameter matrix

[0176]

[0177] Comparative Analysis of Simulation Examples and Algorithms

[0178] The simulation analysis mainly focuses on the effectiveness of the preprocessing of the Jacobian matrix using the Schmidt orthogonal method for the optimal scheduling of the integrated energy system with electrical-gas interconnection. In the simulation process, the algorithm is compared and analyzed by comparing the matrix condition number and the number of iterations of the improved optimization with Schmidt orthogonal method and the distributed optimization without Schmidt orthogonal method.

[0179] (1) Unimproved power flow calculation

[0180] Simulations were performed using the decoupled power grid and gas grid parameters described above, and the results are as follows:

[0181] Table 6 shows the calculation results of the system using the unimproved calculation method.

[0182] System Network Number of iterations Iteration time (s) Jacobian matrix condition number IEEE 9-bus system for power grids 4 1.26 21.6448 7-node gas network system 3 0.78 43.5441

[0183] (2) Improved power flow calculation

[0184] Simulations were performed using the decoupled power grid and gas grid parameters described above, and the results are as follows:

[0185] Table 7. Calculation results of the system using the improved calculation method.

[0186] System Network Number of iterations Iteration time (s) Jacobian matrix condition number IEEE 9-bus system for power grids 2 0.78 1.0000 7-node gas network system 2 0.06 1.0000

[0187] (3) Algorithm Comparison and Analysis

[0188] Table 8 compares the condition numbers calculated using two different methods.

[0189] System Network Before improvement Improved IEEE 9-bus system for power grids 21.6448 1.0000 7-node gas network system 43.5441 1.0000

[0190] As shown in the table above, when the Jacobian matrix is ​​preprocessed using the orthogonal method, the condition number decreases significantly, directly dropping to 1. Since the condition number of a typical system's Jacobian matrix gradually decreases to 1 with the increase of the system iterations, and this process is non-monotonic, directly reducing the condition number to 1 can significantly reduce the computational difficulty. At this point, if the time for matrix transformations is not considered, the power flow calculation time is also greatly shortened.

[0191] Table 9 compares the number of iterations calculated using two different methods.

[0192] System Network Before improvement Improved IEEE 9-bus system for power grids 4 2 7-node gas network system 3 2

[0193] It is obvious that the number of system iterations is significantly reduced after using the improved method, which also improves the convergence speed.

[0194] Table 10 compares the iteration times calculated using two different methods.

[0195] System Network Before improvement (s) Improved (s) Time difference (s) IEEE 9-bus system for power grids 1.26 0.53 0.73 7-node gas network system 0.78 0.26 0.52

[0196] In theory, due to the quadratic convergence property of the NL method, the convergence speed will increase from slow to fast. It is precisely because of this property that the number of iterations of the NL method in normal calculations is independent of the system size, and the iteration time will only increase as the system size increases.

[0197] Based on the data comparison in the table above, the Schmidt orthogonal method significantly reduces the system power flow time. However, as the system size increases, the orthogonal transformation time also increases, and the system difference also continues to increase. It can be foreseen that if the system is too large, the Schmidt orthogonal method may not be able to function properly.

[0198] S42) Analysis of Simulation Results for Optimized Scheduling

[0199] An optimal scheduling simulation was performed using the interior-point method to solve the power flow model of an integrated energy system with decoupled power grid and gas grid networks. The model and solution program were written in Matlab 2016a. The results are as follows:

[0200] Table 11 Optimization scheduling results of the unimproved electricity-interconnected integrated energy system

[0201] System Network Number of iterations Iteration time (s) Operating costs ($ / hr) IEEE 9-bus system for power grids 4 1.26 10089.1 7-node gas network system 3 0.78 7713.5

[0202] The total operating cost of the two systems is $17,802.6 per hour.

[0203] Table 12 Optimization scheduling results of the improved electric-electric interconnected integrated energy system

[0204] System Network Number of iterations Iteration time (s) Operating costs ($ / hr) IEEE 9-bus system for power grids 2 0.53 10102.0 7-node gas network system 2 0.26 7698.3

[0205] The total operating cost of the two systems is $17,800.3 per hour.

[0206] Based on the model of this invention, a comparative analysis was conducted using simulation results of the unmodified and improved electric-gas interconnected integrated energy system models. The results showed that the two methods did not significantly affect the accuracy of the optimized scheduling results, but the iteration time and number of iterations were optimized.

[0207] Based on the conclusions of the previous section, the improved method proposed in this invention reduces the condition number to 1 through preprocessing, thereby reducing the number of iterations, shortening the computation time of iterations, and thus improving computational efficiency.

[0208] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An improved method for optimized scheduling of an integrated energy system with interconnected electricity and gas systems, characterized in that... Includes the following steps: S1) Analyze the structure of the integrated energy system with electrical-electrical interconnection; S2) Establish a mathematical model for the optimal scheduling of an integrated energy system with interconnected electrical and gas systems; S3) Solve and compare the optimal scheduling of the integrated energy system with electrical-gas interconnection; S4) Simulation analysis of optimal scheduling of integrated energy system with electrical-gas interconnection; Step S3) involves solving and comparing the optimal scheduling of the integrated energy system with electrical interconnection, including: S31) Optimized scheduling of integrated energy systems with electrical interconnection S311) Power flow solution using the NL method. This paper analyzes the unified energy path theory of the integrated energy system of electric and gas interconnection. Based on the analogy of natural gas circuits, network analysis and power flow calculations are performed on the integrated energy system of electric and gas interconnection. The one-dimensional flow of natural gas in the pipeline is expressed by the mass conservation equation and the momentum conservation equation. Then, two commonly used approximations, "ignoring the convection term" and "approximating the velocity square term of the resistance term with incremental linearization", are introduced into the momentum conservation equation. A linear equation that rewrites the resistance term as the velocity term is summarized. Then, based on the equation of state of natural gas and the definition of pipeline flow, the circuit analogy of natural gas is summarized. The summary is extended and equivalent. Due to the different selection methods of the balance nodes of the power grid and the gas grid, the hybrid power flow calculation process of the integrated energy system of electric and gas interconnection is given according to the operation mode of the integrated energy system of electric and gas interconnection. S312) Parameter values ​​for the integrated energy system with electrical interconnection Extended NL method hybrid power flow calculation is performed using an electric-gas interconnected system based on a selected node power grid and another selected node natural gas grid. The example network structure of the electric-gas interconnected integrated energy system is drawn, and the network coefficients of the selected node gas grid system are given. S313) Solving optimal scheduling using interior point method The basic idea of ​​the interior point method is to start from an interior point, find subsequent interior points that decrease the objective function value in a feasible direction, and then start from the obtained interior point, find the interior point that decreases the interior point, and repeat the above steps in another feasible direction to obtain a sequence of interior points, so that the objective function value decreases strictly monotonically, and stop iterating when the termination condition is met. S32) Analyze and optimize existing scheduling problems Since the computation is essentially still performed using the NL method, there are issues such as the large system size leading to an excessive number of iterations, the initial system input parameters significantly affecting computation time and accuracy, and the Jacobian matrix not being simplified enough. Therefore, it is necessary to consider simplifying the Jacobian matrix to shorten the system iteration time. S33) Improved Optimization Scheduling Method The power flow algorithm for an integrated energy system with interconnected electricity and gas networks, based on the Schmidt orthogonal method for preprocessing the Jacobian matrix, first determines the location of the slack nodes in the power network, then uses the NL method to calculate the power flow and form the Jacobian matrix. The Jacobian matrix is ​​then preprocessed using the Schmidt orthogonal method, followed by iterative calculations to determine if the output conditions are met. If met, the algorithm outputs the power and power angle of the power network, the flow rate of the natural gas network, and the gas pressure of each node, and continues with the next step of interior-point optimization scheduling.

2. The improved method for optimized scheduling of an integrated energy system with interconnected electrical and gas systems according to claim 1, characterized in that, The content of step S1) analyzing the structure of the electric-gas interconnected integrated energy system includes the composition architecture of the electric-gas interconnected integrated energy system, the main equipment and energy information flow path of the electric-gas interconnected integrated energy system, and the analysis of the coupling equipment of the electric-gas interconnected integrated energy system.

3. The improved method for optimized scheduling of an integrated energy system with interconnected electrical and pneumatic systems according to claim 1, characterized in that, The method for building a mathematical model for the optimal scheduling of an integrated energy system with interconnected electricity and gas in step S2) includes the following steps: S21) Mathematical Model of Electric-Interconnected Integrated Energy System The model of the integrated electric-gas energy system includes two energy networks: the power grid and the natural gas pipeline network. The modeling of the natural gas network includes the pipeline pressure drop formula, the nodal flow equation, and the ring energy equation, which are analogous to Ohm's law, Kirchhoff's current law, and Kirchhoff's voltage law for the power grid, respectively, thus applying the analogy of the gas network to the power grid analysis. S211) Power Grid Model The power network modeling in an integrated energy system with interconnected electricity and gas is analogous to that of a conventional power system. Based on the nodal and loop equations of the power grid, branch and nodal admittance matrices are derived, and the active power P at each node is determined. i and reactive power Q i It can be represented as follows: In the formula, V i and V j Let δ be the node voltages of i and j; ij G is the phase angle difference between the two nodes; while G ij and B ij These are the conductance and susceptance of the line between nodes i and j, respectively. S212) Natural Gas Network Model When solving for natural gas network flow, the main focus is on pipeline pressure and node flow. Because natural gas is compressible and a fluid, the conditions in different parts of the network vary, making the gas network less stable than a power grid. The parameters determining natural gas flow are: gas pressure, gas density, and gas velocity within the pipeline. All three are related to pipeline length and time. Considering that natural gas networks are mostly ring-shaped, the model uses the pipeline pressure drop formula, node flow equation, and ring energy equation, as follows: In the formula, M ij d is the pipe resistance coefficient; ij Characterizes the direction of natural gas flow within the pipeline; f ij The flow rate in the same pipe; while π i Indicates the node air pressure at point i in the pipeline network; a ij For node branch association elements, representing whether pipeline branch j and node i are associated; F i External energy injected into node i; b ij For loop association elements, M represents whether branch j is in the i-th loop; j Let π be the resistance coefficient of pipe branch j. i π represents the node air pressure at point i in the pipeline network; j f represents the nodal air pressure at point j in the pipeline network; j This represents the flow rate in branch i of the pipeline network; Equation (6) represents the flow equation of a pipeline node with n branches, and Equation (7) represents the ring energy equation of a network loop with n pipeline branches. S213) Mathematical Model of Coupled Element Device (1) Gas turbine modeling The power generation conversion rate of a single-cycle gas turbine is 30-40%, while that of a combined-cycle gas turbine is 50-60%. The gas turbine is modeled in an integrated electric-gas energy system as follows: In the formula, P t and f t These represent the output power of the gas turbine and the gas flow rate it consumes, respectively; α, β, and υ are the energy consumption coefficients of the gas turbine, respectively. Equation (9) can characterize the coupling relationship between the power grid and the natural gas grid to a certain extent; (2) Modeling of the electro-gas conversion device An electro-gas converter is a device that uses electrical energy as input, employs water electrolysis technology to produce hydrogen, and then uses the hydrogen to produce methane through the incomplete combustion of carbon. If we consider the power-to-gas converter as a load on the power grid, the mathematical model for the power-to-gas converter is as follows: E P2G =P P2G the P2G c E (10) In the formula, P P2G η represents the electrical power consumed by the electro-gas conversion device, t represents the equipment operating time, and η represents the total electrical power consumed by the device. P2G For conversion efficiency, γ E E is the coefficient for the conversion of electrical energy to heat. P2G H represents the output energy value of the electro-gas conversion device. G f represents the calorific value of natural gas. P2G The output flow rate of natural gas from the electro-gas conversion unit; Based on the analysis of various aspects of the mathematical model of the integrated energy system with interconnected electrical and gas systems, the mathematical model of the integrated energy system with interconnected electrical and gas systems with n nodes is summarized as follows: In the integrated energy system network of electric-gas interconnection, gas turbines burn natural gas to generate electricity, and electric-to-gas converters consume electricity to produce natural gas. S22) Optimize the scheduling objective function The interior-point method is used to solve this problem. Based on the price curves of electricity purchased from external sources and gas purchased from internal sources, the optimization objective is to minimize the system's 24-hour operating cost. The objective function is expressed as: minC E +C G (17) Where C E and C G The total operating costs of the power grid and the natural gas grid over 24 hours are respectively expressed as: In the formula, Here are the parameters and price of the i-th coal-fired power unit; For the hourly output of the i-th coal-fired unit, Let i be the cost of the i-th gas source in the natural gas network. Let i be the hourly flow rate of the i-th gas source; S23) Operational constraints of the integrated energy system with electrical interconnection (1) Power grid constraints There are two types of grid constraints: power balance constraints and generator output constraints. These two constraints are as follows: ∑ d∈i P Gd，t +∑ d∈i P GTD，t +∑ d∈i P WTd，t =∑ d∈i P P2Gd，t +∑ d∈i P Ld，i (20) In the formula, P G For the hourly output of the coal-fired unit, P GT To provide power to the gas turbine unit, P WT P contributes power to the wind farm P2G For the power consumption of the electro-gas conversion device, P L For electrical load; P Gi P represents the hourly output of the coal-fired unit at node i; GTi This represents the hourly output of the gas turbine at node i; This represents the minimum output per hour of the coal-fired unit at node i; This represents the maximum hourly output of the coal-fired unit at node i; This represents the minimum output per hour of the gas turbine at node i; This represents the maximum output per hour of the gas turbine at node i; (2) Natural gas network constraints There are five types of constraints in a natural gas network: gas source constraints, gas load constraints, pipeline pressure constraints, pressure-flow relationship constraints at nodes in the gas transmission pipeline, and node flow balance equations. π min ≤π≤π max (24) E×f G =F×f L +A×f P (26) In the formula, f G f is the gas source flow rate. L Here, E represents the natural gas load flow rate, F represents the node-gas source correlation matrix, F represents the node-load correlation matrix, and A represents the node-pipeline correlation matrix; π represents the gas pressure at the pipeline node; f ij f ij The flow rate in the same pipe; M ij d ij π i The meaning is the same as before; f p Indicates the pipeline natural gas flow rate; (3) Constraints of coupling element device The constraints of the gas turbine with coupling element device are: In the formula: f t This represents the gas flow rate consumed by the gas turbine; α, β, and υ are the energy consumption coefficients of the gas turbine, respectively. The constraints of the coupling element device P2G are: In the formula: f P2G P represents the natural gas flow rate output by the P2G system; P2G η is the electrical power consumed by the P2G; t is the device operating time; η is the electrical power consumed by the P2G. P2G For conversion efficiency; γ E H is the coefficient for converting electrical energy to heat. G This refers to the calorific value of natural gas.

4. The improved method for optimized scheduling of an integrated energy system with interconnected electrical and pneumatic systems according to claim 1, characterized in that, Step S4) of the simulation analysis for the optimized scheduling of the integrated energy system with electrical-gas interconnection includes: S41) Simulation Analysis of Optimized Scheduling Algorithm The simulation analysis mainly focuses on the effectiveness of the Schmidt orthogonal method for preprocessing the Jacobian matrix for the optimal scheduling of the electric-gas interconnected integrated energy system; During the simulation, the algorithm is compared and analyzed by comparing the condition number and number of iterations of the Jacobian matrix with the improved optimization of the Jacobian matrix using Schmidt orthogonal optimization and the matrix without Schmidt orthogonal distributed optimization. S42) Analysis of Simulation Results for Optimized Scheduling For the power flow model of the integrated energy system with electricity-gas interconnection, which is decoupled into two network systems, the interior point method is used to perform optimization scheduling simulation and solution. The model and solution program are written in Matlab2016a.

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