The electricity-gas transformation problem and related intrinsic mechanisms are considered. First, existing schemes for the optimization of electricity-gas integrated energy systems are analyzed through consideration of the relevant literature, and an Electricity Hub (EH) for electricity-gas coupling is proposed. Then, the distribution mechanism in the circuit of the considered electricity-gas integrated system is analyzed. Afterward, a mathematical model for the natural gas pipeline is elaborated according to the power relationship, a node power flow calculation method, and security requirements. Next, the coupling relationship between them is implemented, and dedicated simulations are carried out. Through experimental data, it is found that after 79 data iterations, the optimization results of power generation and gas purchase cost in the new system converge to $54,936 in total, which is consistent with the data obtained by an existing centralized optimization scheme. However, the new proposed optimization scheme is found to be more flexible and convenient.

In today’s era, the rapid development of science and technology has improved the overall social productivity level substantially. Various industries, such as information and communication, Artificial Intelligence (AI), aerospace, and medical technology, have made continuous breakthroughs in their respective fields [

People have tasted some bad fruits out of the long-term excessive exploitation and utilization of the earth’s resources. Nowadays, the global climate is changing more dramatically and unpredictably. Countries worldwide begin to carry out energy reform, hoping to alleviate the trend of environmental deterioration by exploring new energy and using clean energy [

Under this background, an integrated electricity-gas energy scheduling optimization system is proposed based on spatial coupling by analyzing the shortcomings of traditional electrical energy scheduling. The mutual transformation and the complementarity of multi-energy forms can be realized through comprehensive energy scheduling and utilization in a region. A coupling mechanism is constructed based on Energy Hub (EH) by modeling the energy flow in an integrated electricity-gas energy network. Additionally, a multi-agent collaborative optimal scheduling model is proposed according to the distribution characteristics of natural gas energy to optimize the existing centralized interconnected integrated energy system. There are two research innovations:

1. A integrated electricity-gas energy scheduling optimization system based on spatial coupling is proposed through spatial coupling EH. 2. The mathematical models of distribution network and natural gas pipeline are implemented respectively according to the energy conservation principle and fluid mechanics. The optimization effect is quantitatively analyzed by mathematical means.

The urgency for ecological environment protection is forcing all countries to start exploring renewable and clean energy to provide for industrial production and reduce the exploitation and use of nonrenewable energy for the sustainable development of human civilization [

Fluid dynamics is a rigorous scientific discipline, which can be used to solve fluid motion equations by establishing the concepts of force, acceleration, and flow field in fluid mechanics analysis based on classical mechanics [

Electricity-gas energy scheduling is a rich research topic, involving many related studies. Tang et al. [

In these studies, it is more or less pointed out that the planning of traditional power grid systems, natural gas networks, thermal networks, and transportation network is very rigid and has great defects in system operation and information transmission and processing; meanwhile, these traditional systems are inefficient and lack sound interaction functions. Hence, the overall scheduling and utilization of integrated energy are difficult to reach a high level, because these power grids are scheduled disorderly, and the management systems of different market entities are mixed for different energy sources. However, the management channels among various types of energy are relatively independent and have not been clearly planned and integrated, lacking interactions and relevancy. Under such situations, a multi-regional integrated energy system has to depend on multiple interconnected and autonomous EH to realized integrated energy scheduling. Moreover, the complexity and diversity of multi-energy scheduling decision-making bring greater difficulties to the energy transmission and integration of multiple decision-makers and even affect the centralized energy allocation and scheduling of the whole integrated energy system. To sum up, the proposed integrated energy scheduling system can avoid the following defects of a centralized optimization method: 1. Large amounts of data collection and low efficiency of information processing; 2. The complex model increasing the difficulty of multi-energy coupling and transformation; 3. The chaotic management unmatching the actual operation mode.

EH is a crucial part of the multi-energy system. It can accommodate various energy coupling relationships and realize the mutual transformation between various energy.

In

The distribution network of the region should be analyzed and studied to optimize the integrated electricity-gas energy scheduling system in a certain region. The coupling relationship in the integrated electricity-gas energy scheduling system is very complex. It includes electricity-gas coupling, electrothermal coupling, and electromagnetic coupling [

As shown in

The mathematical model is as follows:

_{e−e,i} refers to the electricity distribution coefficient of the _{e−g,i} refers to the distribution coefficient when electricity is converted into gas; _{g−e}_{,i} refers to the distribution coefficient of the _{g−g,i} denotes the natural gas distribution coefficient of the _{g−e,i} is the unit conversion coefficient when electricity is converted into gas; Δ_{e−g,i} is the unit conversion coefficient when natural gas is converted into electricity; _{g−e,i} represents the gas generation efficiency of the _{e−g,i} is the efficiency of converting electricity into gas in the

The distribution network needs to be modeled to optimize the integrated electricity-gas energy system based on spatial coupling.

First, the power output constraints of the unit are modeled.

The equation reads:

Ω_{ENG,i} is the set of generator units at the input end of the _{m} is the active output of the

The first part of distribution network modeling is node power flow calculation, which is modeled according to the power conservation equation [

Ω_{,i} represents the collection of power nodes adjacent to node _{f,ij} indicates the active power of the circuit transmitted from node

Safety should also be considered in circuit simulation. Hence, the power flow modeling of the distribution network is carried out based on the security problem [

The mathematical modeling of the natural gas transmission pipeline is implemented after the mathematical modeling of the distribution network. The motion state of natural gas is analyzed according to fluid mechanics and transformed into vectors for more accurate testing and quantification [

Ω_{EHS,i} is the collection of air sources at the input end of the _{p,n} of the gas source n in the EH, and _{GB,i} stands for the set of natural gas nodes adjacent to node

The output end after coupling needs to be modeled after the modeling of the distribution network and natural gas distribution pipeline is completed, respectively, and the EH is responsible for scheduling and distributing the converted natural gas and electricity resources, respectively [

_{U} is the conventional unit, and _{G} signifies the gas unit; _{b} represents the power node set; _{Lx} denotes the power load; _{p} stands for the power transmission distribution coefficient matrix of the integrated electricity-gas energy system [_{CB} means the node active power input column vector of the electrical integrated energy system;

_{s} represents the gas source set; _{N} is the node set of natural gas network; _{H} is the flow through the pipeline h; _{p} and _{L} are the natural gas source and load column vectors, respectively; _{C} signifies the flow column vector of the compressor branch; _{NL} presents the node-pipeline correlation matrix; _{NC} is the node-compressor correlation matrix; _{NS} refer to the node-source correlation matrix; _{ND} is the node-load correlation matrix. max and min represent their respective limit values.

_{1} and _{G} refer to the natural gas consumption of gas generating units, and _{m}, _{m} and _{m} denote the consumption coefficient of gas generating units.

According to the energy coupling, a mathematical model centered on the EH is implemented.

In _{E,m} is the fuel price coefficient of generator set m; _{G,n} represents the price coefficient of gas source n; in _{f,ij}, and _{e} and _{g} are the penalty factors; the superscript

After the completion of mathematical modeling, to test the optimization effect, the centralized optimization method (derived from the “13th five-year plan for energy development” document of the National Development and Reform Commission and the National Energy Administration) and Alternating Direction Method of Multipliers (ADMM) optimization method are adopted to set the control group [

This experiment is based on the computer windows system, the MATLAB platform is employed for coding, and the IPOPT solver is adopted to help solve the problems in the optimization of EH [

As shown in

The experimental data are processed by the ADMM algorithm proposed in [

Based on the experimental results, the residual convergence curve based on ADMM step-by-step algorithm is drawn as in

According to the experimental data, the operation cost convergence curves of EH 1, EH 2, and EH 3 are drawn in

To sum up, the proposed optimization method of the integrated electricity-gas energy system based on spatial coupling has good practical results in terms of convergence speed and electrical transformation. Moreover, the EH is adopted to directly interconvert power and natural gas, avoiding the complex operation of scheduling based on information collected in the traditional centralized optimization method, as well as large amounts of information, complex model, and chaotic management. Thus, the proposed optimization scheme is relatively successful.

This paper explores the optimization mechanism of integrated electricity-gas energy scheduling systems by studying the coupling relationship between power supply systems and natural gas systems. First, the existing problems of the traditional centralized scheduling optimization methods are analyzed through a literature review. According to the analysis results, an optimal scheduling algorithm is proposed for an integrated electricity-gas energy system based on EH and the step-by-step algorithm. The mathematical models of the circuit and natural gas circuit are implemented based on the analysis of aerodynamics. The feasibility of the proposed system is proved by data iteration. The mechanism of electricity-gas mutual transformation in EH is studied. The results show that the proposed optimization scheme takes EH as the scheduling center to schedule power resources and natural gas resources, and there is no need for the traditional single power scheduling center and single natural gas scheduling center. This avoids the defects of massive information, complex model, and chaotic management, and has stronger flexibility. Thus, the proposed optimization scheme is successful. However, the scheduling cost of power resources is often affected by the price of natural gas, which, however, is not involved in this paper, thereby pointing out the research deficiency. The design and optimization of the integrated energy system is a research hotspot of new energy reform. The network of the integrated electricity-gas energy scheduling system is complex, and the transportation line is long. Combining computer technology to build a multi-agent cooperative scheduling platform is also a research direction in the future.