Natural Gas Pipeline Network Research Articles

Review on the development of China's natural gas industry in the background of “carbon neutrality"

At the 75th UN General Assembly, the Chinese government declared to strive to reach peak carbon dioxide emission by 2030 and achieve “carbon neutrality” by 2060. The establishment of this goal not only brings opportunities but also challenges to the development of China's natural gas industry. In order to comprehensively understand the whole chain of China's natural gas industry under the goal of “carbon peak and carbon neutrality”, this paper sorts out the recent related research results and discusses the development prospect of China's natural gas industry in the background of “carbon neutrality”. And the following research results are obtained. First, compared with other low-carbon or carbon-free energies, the foundation for the large-scale stable supply of natural gas in China is the most solid, so natural gas is the most practical option to replace coal and realize “low carbon”. Second, in the process of “carbon neutrality”, natural gas will play an important role in different stages. Finally, several suggestions are proposed to promote the development of China's natural gas industry. First, it is necessary to further strengthen the construction of natural gas infrastructure, especially the construction of emergency peak shaving capacity. Second, market-oriented pipe capacity distribution and two-part pricing will be the reform direction of the operation mode of natural gas pipeline network, but they shall be promoted gradually and appropriately according to the development degree of China's natural gas industry. Third, under the goal of “carbon neutrality”, much attention shall be paid to the development of natural gas fired power generation, especially the development of peak-shaving gas power. Fourth, it is necessary to sufficiently grasp the opportunity period and window period of industry development and strengthen cooperation among upstream, middle and downstream to jointly promote the healthy development of China's natural gas industry.

Construction of natural gas energy-measuring system in China: A discussion

During the 13th Five-Year Plan, China's natural gas industry developed rapidly, and a diversified supply and marketing pattern was formed, including domestic conventional gas, unconventional gas (shale gas, tight sandstone gas, coalbed methane, etc.), coal-based synthetic natural gas, imported LNG and imported pipeline gas. The gross calorific value of gas sources ranged from 34 MJ/m3 to 43 MJ/m3, and the maximum difference of calorific value between different gas sources exceeded 20%. On May 24th, 2019, the National Development and Reform Commission and other three ministries/commissions jointly issued the Supervision Regulation on the Fair Access of Oil and Gas Pipeline Network Facilities and required that a natural gas energy measuring and pricing system shall be established within 24 months from the implementation date of this Regulation. In order to speed up the construction of China's natural gas energy measuring system, this paper summarizes domestic achievements in the construction of natural gas energy measuring system from the aspects of value traceability and energy measurement standard, and analyzes natural gas flowrate measurement technology, calorific value determination technology, value traceability, localization, intelligentization and application technology of key energy measurement equipment, natural gas pipeline network energy balancing technology based on big data analysis, multi-source quality tracking and monitoring technology, and energy measurement standard system, the need of new energy detection and measurement technology, and put forward strategy for the development of natural gas measuring in China. And the following research results are obtained. First, China's natural gas energy measuring system can basically meet the requirements of implementing natural gas energy measurement, but it still falls behind the international leading level in terms of calibration and application of high-level flowmeter (such as 0.5 class), high-accuracy gas reference material, level of calorific value reference equipment, and measurement standard system, and needs to be further improved. Second, it is necessary for China to speed up the research and application of the localization and intelligentization technologies of key energy measurement equipment. Third, natural gas pipeline network shall be equipped with measurement check method, energy balancing system based on big data analysis, and multi-source quality tracking and monitoring system, so that the energy transmission loss index of natural gas pipeline network can be superior to the international leading level (0.10%). Fourth, to realize the large-scale application of hydrogen energy and bio-energy and the mixed transportation of hydrogen, bio-methane and natural gas, it is necessary to carry out research on new technology and standardization of hydrogen/bio-methane blended natural gas detection and measurement.

A deep reinforcement learning-based method for predictive management of demand response in natural gas pipeline networks

With the increase of natural gas in the world's energy consumption, the efficient and reliable management of natural gas pipeline networks is becoming even more important than before. In recent years, Demand Response (DR) is considered an effective approach for cleaner production and economic strategy, by introducing the participation of customers (CUs).This paper proposes a novel DR method for predictive management in multi-level natural gas markets with different stakeholders. This method is able to make a better trade-off among supplier's profits, gas demand volatility and CU satisfaction. This method includes three parts: dynamic pricing model, intelligent decision making and data-driven demand forecasting. A Markov decision process-based model is developed to illustrate the process of dynamical optimizing energy prices. Then, deep learning and reinforcement learning are integrated to efficiently solve the sequential decision-making problem, based on the physics constraints of natural gas pipeline networks. Besides, to realize the function of predictive optimization, an energy demand forecasting model is developed based on the deep recurrent neural network model. The proposed dynamic pricing method is able to optimize the pricing strategies in accordance to the demand patterns, and dynamically improve the system stability and energy efficiency. Finally, we apply the developed method to a natural gas network with relatively complex topology and different CUs. The results indicate that the proposed method can achieve the targets of peak shaving and valley filling under different pricing periods. Besides, the sensitivity analysis of the critical parameters in the dynamic pricing model is analyzed in detail, which can give a solid criterion for ensuring the effectiveness of this framework.

Optimization of long-distance and large-scale transmission of renewable hydrogen in China: Pipelines vs. UHV

The reverse distribution of renewable energy resources and load centers makes exploring the optimal transmission mode of long-distance and large-scale renewable hydrogen the key to solving the bottleneck of renewable hydrogen development. This study incorporates hydrogen pipeline (HGP), natural gas pipeline (NGP), and Ultra High Voltage (UHV) into an optimal planning model framework and analyzes the optimal transmission mode, quantity, network, and cost of large-scale renewable hydrogen in China. Constructing a sensitivity analysis framework, this study also investigates the optimal transmission mode changes under different scenarios. The results show that the optimal mode of large-scale renewable hydrogen transmission in the province is NGP, and 5.4% of supply level is the critical point to export renewable hydrogen inter-provincially. It switches to the combination of NGP and HGP when the unit transmission costs of these elements decrease to a certain proportion simultaneously or switches to HGP when the unit transmission cost of HGP decreases more than that of NGP. The complementary transmission mode of NGP and UHV is the optimal mode for inter-provincial transmission, and the HGP can be put into use for inter-provincial transmission only when the unit transmission cost of which is reduced to less than 25%. Jilin is the key node in the NGP network, and Tibet and Gansu are the key nodes in UHV network, and the participation or absence of which will have significant impact on the renewable hydrogen transmission system. Only minor adjustments to the transmission technical parameters of NGP or HGP can promote the qualitative overflight of the optimal transmission volume of them so as to achieve the target optimization at the minimum cost.

Study on leak localization for buried gas pipelines based on an acoustic method

As an important part of a city’s “lifeline,” an urban underground natural gas pipeline network is an integral part of the infrastructure, facilitating energy transmission. If the source of a leak is not located accurately, explosive incidents may occur owing to the highly flammable nature of natural gas, causing casualties and property damage. Thus, this study presents a new method of leak identification in buried natural gas pipelines. The proposed method achieves this goal through leak noise in the soil, and this is verified through experiments conducted as part of this research. The surrounding soil of the buried pipeline was considered as the propagation medium of the noise associated with leaks. For four microphones, placed in detection holes, were used to capture leak noise within the soil. Multi-layer wavelet packet decomposition was performed on the collected time domain signal of leak noise and was reconstructed on the characteristic frequency band of 0–200 Hz. Leak localization was completed by estimating the time difference of arrival between each pair of microphones on the buried natural gas pipeline. In the experimental scenario, the leak location error of the buried gas pipeline was 8 %–12 %. Therefore, the proposed method can successfully be applied to realize leak localization for buried natural gas pipelines.

An evaluation index system of the user satisfaction for the natural gas pipeline network

With the intent of making up for the lack of gas supply reliability in evaluating the ability of the natural gas pipeline network to provide users with gas supply services, the concept of the user satisfaction for the natural gas pipeline network is proposed in this study. The definition of the user satisfaction is firstly illustrated and the relationship and difference between gas supply reliability and user satisfaction are clarified from two aspects of definition and mathematical expression. The evaluation index system of the user satisfaction for the natural gas pipeline network is then constructed, which includes six indicators, namely user satisfaction for gas amount, user satisfaction for gas pressure, user satisfaction for gas quality, user satisfaction for gas supply strategy, user satisfaction for emergency, and user satisfaction for gas price. The process of determining the weight of each indicator based on the analytic hierarchy process method is proposed. Moreover, considering the user characteristics, natural gas users are classified into four types, namely the users whose demand need to be fully satisfied, the users whose demand can be shed by a small amount, the users whose demand can be shed, and the users whose demand can be interrupted. The results of the weight of each indicator for the above four types of the natural gas users are calculated.

Multidimensional risk classification with global sensitivity analysis to support planning operations in a transportation network of natural gas pipelines

Multidimensional risk assessment for natural gas pipelines has proved to be an efficient approach for companies to evaluate multiple risk perspectives and to determine different mitigation actions. Therefore, making decisions to ensure the system's best performance, taking into account safety issues, is a challenging task. This paper proposes a multidimensional risk classification with global sensitivity analysis by making a structured analysis of uncertainty that uses a Monte Carlo Simulation and visualization tools. For this analysis, five scenarios of a group of parameters are set according to operational and technical issues, consequences and the preferential properties of the model for pipeline sections. Then, sensitivity levels are statistically validated and defined for each section, thereby generating information on modifications to the classification of levels of risk. For example, 10% variation in the group of parameters related to the Critical Danger Radius (CDR), 6 out of 8 pipeline sections present high sensitivity levels; showing that their original risk classifications do not remain the same. Also, 4 sections are expected to be in the high risk class, while 1 section is expected to be in medium class and 3 sections in the low risk class. Consequently, managers should prioritize mitigation strategies to those sections with significant risk categories The advantages of our proposals are twofold. First, the proposed methodology enables decisions to be made on classifying risks which incorporate evidence on the sensitivity and uncertainties of natural gas pipelines. Secondly, effective information on classifying risk is provided to the decision-maker by using statistical validations and visualization tools. Thus, managers can enhance their perception of risks with regard to a natural gas pipeline, can generate insights to control mitigations and allocate resources to ensure safety for people, and can avoid losses regarding the environment and their companies' properties.

Research Progress on Calculation and Control of Unaccounted for Gas of Natural Gas Pipeline Network

At present, volume measurement is still used in transfer measurement of natural gas in China, so the calculation and management of Unaccounted for Gas are based on volume measurement. With the change of natural gas measurement method from volume measurement to energy measurement, the calculation and management of Unaccounted for Gas based on energy measurement will be paid more and more attention. This paper investigates the calculation methods and management measures of Unaccounted for Gas based on volume measurement in China and Unaccounted for Gas based on energy measurement in other countries, and compares the research progress. The results show that: the general principles of Unaccounted for Gas calculation in China and other countries are basically the same, but the calculation formulas are not completely the same. All countries consider the input gas, output gas, line pack variation and self-consumption gas. On this basis, Italy considers the known leakage, and Britain considers the known leakage and the daily calorific value shrinkage caused by its settlement rules. In order to reduce Unaccounted for Gas, the UK regularly verifies meter, carries out the research on Unaccounted for Gas baseline, and actively participates in the global Unaccounted for Gas benchmarking. Australia replaces the old main line and reduces the operation pressure of pipeline, which significantly reduces Unaccounted for Gas. The calculation methods and control measures of Unaccounted for Gas based on energy measurement in Italy, Britain and Australia can be used for reference in China.

Vulnerability analysis method based on risk assessment for gas transmission capabilities of natural gas pipeline networks

The crucial part of vulnerability analysis is identifying the critical components of a pipeline network. In this study, we proposed a novel analysis method- “Risk-Vulnerability,” which combines the characteristics of risk assessments and vulnerability analyses methods. Risk-Vulnerability identifies the critical components of a pipeline network from three perspectives: pipeline operating status, transmission performance, and network characteristics. The formulas of the importance value of each component were established. Then the component risk indicators were established, and the component risk values were calculated. And a utility theory was introduced to calculate the severity of the consequences. Finally, the component importance and risk values were multiplied to obtain the vulnerability of the component. The feasibility and effectiveness of the method were verified by comparing the identification results of this method to those from the weighted flow capacity rate (WFCR). The Risk-Vulnerability method provides an improved insight into the pipeline criticality compared to the WFCR and improves the calculation formulae based on the identification content, which can not only be used to identify critical components, but also can be used to formulate research on risk reduction measures for pipeline network systems.

A framework for the resilience analysis of complex natural gas pipeline networks from a cyber-physical system perspective

The vulnerability of gas pipeline networks to physical and cyber-attacks calls for a resilience analysis based on models, capable of quantifying the network robustness and recovery from failures.This work proposes an original resilience analysis framework for a complex gas pipeline transmission network, considering the cybernetic interdependence of the physical gas pipeline network with the SCADA system. The maximum flow algorithm computes the gas network supply capacity and when a failure occurs, the pressure of the network nodes and the gas supply capacity change, leading to dissatisfaction of customer demands. The framework allows quantifing the value of resilience through specific performance metrics.The SCADA communication network, implemented in Network Simulator®, provides the necessary information regarding the delay of data packets coming from the sensors located along the pipelines. The packet delay value allows to evaluate the actual time at which the SCADA system blocks the remote control valves, ready to keep the pipelines under pressure when a failure occurs.Important insights on the resilience model are obtained through a systematic sensitivity analysis (SA) framework, customized for gas pipeline transmission networks. Specifically, we investigate the influence of model inputs to the network robustness and recovery uncertainty. The effects of individual parameters and groups formed by inputs with similar functionalities provide useful information, such as to what extent the supervisory SCADA system interconnection affects the degradation and the recovery process of the physical gas pipeline network.The results of the case study confirm, as expected, that gas transmission networks are vulnerable to both cyber and physical failures, pointing at the need for systemic methods of analysis for managing the system resilience.

A Robustness Evaluation Method of Natural Gas Pipeline Network Based on Topological Structure Analysis

As the total mileage of natural gas pipeline network continues to increase, the topological structure of natural gas pipeline network will become more and more complex. The complicated topological structure of natural gas pipeline network is likely to cause inherent structural defects, which have serious impacts on the safe operation of natural gas pipeline network. At present, related researches mainly focused on the safe and reliable operation of natural gas pipeline network, which has become a research hotspot, but few of them considered the complexity of natural gas pipeline network and its potential impacts. In order to understand the complexity of natural gas pipeline network and its behaviors when facing structural changes, this paper studied the robustness of natural gas pipeline network based on complex network theory. This paper drew on the methods and experience of robustness researches in other related fields, and proposed a robustness evaluation method for natural gas pipeline network which is combined with its operation characteristics. The robustness evaluation method of natural gas pipeline network is helpful to identify the key components of the pipeline network and understand the response of the pipeline network to structural changes. Furthermore, it can provide a theoretical reference for the safe and stable operation of natural gas pipeline network. The evaluation results show that natural gas pipeline network shows strong robustness when faced with random disturbances represented by pipeline accidents or component failures caused by natural disasters, and when faced with targeted disturbances represented by terrorist disturbances, the robustness of natural gas pipeline network is very weak. Natural gas pipeline network behaves differently in the face of different types of random disturbances. Natural gas pipeline network is more robust when faced with component failures than pipeline accidents caused by natural disasters.

An Electronically Stabilized Multi-Color Multi-Ring Structured Light Sensor for Gas Pipelines Internal Surface Inspection

Natural gas pipeline network extends over 2.5 million miles in the united states of America. The aging of these infrastructures combined with damage from various external threats are creating safety concerns for both operators and residents in the vicinity of these pipelines. In this paper, we are presenting a miniaturized structured light based three-dimensional (3D) imaging sensor for the inspection of internal walls of plastic natural gas distribution pipelines. The sensor is an 18-mm diameter optical inspection device that can be inserted inside the pipe to provide the operator with a 3D map of the internal surface of the inspected pipe. The introduction of the 3D map simplifies the identification of damages like deformations and material loss and leads to a better evaluation of the damage severity when compared to LED assisted cameras. The sensor is also accompanied with an embedded electronic stabilization algorithm to reduce the effect of misalignment when the sensor is attached to a scanning platform, and to facilitate the registration of consecutive frames from the sensor. The algorithm exploits the geometry constraints provided by the cylindrical shape of the pipe to estimate the orientation and position of the sensor with each collected frame.

An integrated, systematic data-driven supply-demand side management method for smart integrated energy systems

Different energy systems become highly connected to provide better flexibility. However, this change poses new challenges for system management considering the diversity of demands, complexities of the energy networks, uncertainties, etc. This work develops a smart Supply-Demand Side Management method to overcome these challenges. The main objectives of this Supply-Demand Side Management framework are improving system efficiency and smoothing energy load, through flexible supply planning and dynamic pricing. Firstly, the customer response analysis method is proposed by combining the Deep Learning model and the economic model. Then, the energy network simulation model is used to coordinate the Supply-Demand Side Management strategies and the overall energy system capacity. A method is proposed to introduce the compressibility of natural gas in the management framework to offset the uncertain disturbances. Finally, a multi-objective decision method is developed to find the optimal strategy. The results of the application on a typical integrated energy system show that the proposed method can reduce the energy load fluctuation by 4%–8% under different planning horizons, and improve the system efficiency by reducing energy loss and increasing the profitability. The results also present a possibility of the development toward resilient Integrated Energy Systems by managing the buffer capacity of natural gas pipeline networks.

Data-driven reliability assessment method of Integrated Energy Systems based on probabilistic deep learning and Gaussian mixture Model-Hidden Markov Model

Reliability analysis of IESs (Integrated Energy System) is complicated because of the complexity of system topology and dynamics and different kinds of uncertainties. Reliability is often calculated based on statistic methods, which always focus on historical performances and neglect the importance of their dynamics and structure. To overcome this problem, in this paper, a systematic framework for dynamically analysing the real-time reliability of IESs is proposed by integrating different machine learning methods and statistics. Firstly, the bootstrap-based Extreme Learning Machine is developed to forecast the conditional probability distributions of the productions of renewable energies and the energy consumptions. Then, the dynamic behaviour of IESs is simulated based on a stacked auto-encoder model, instead of using traditional mechanism-based simulation models, for improving computational efficiency. Besides, the variables representing the transient properties of natural gas pipeline networks, such as delivery pressures and flow rates, are taken as the indicators for quantifying the energy supply security in natural gas pipeline networks. The time-dependent relationships among these indicators and their statistic correlations are modelled for improving the effectiveness of the analysis results. Finally, the reliability assessment is performed by estimating the probability distribution of each functional state of the target IES. A case study of a realistic bi-directional IES is carried out to demonstrate the effectiveness of the proposed method. The results show that the method is able to effectively evaluate the reliability of IESs, which can provide useful information for system operation and management.

The method for leakage detection of urban natural gas pipeline based on the improved ITA and ALO

To solve the problems of the difficulty in early leakage monitoring and larger positioning error for urban hazardous chemicals pipelines, the optimized method based on the improved Inverse Transient Analysis (ITA) and Ant Lion Optimizer (ALO) was proposed. Firstly, based on the obtained experiment's results of leakage of natural gas in the non-metallic pipeline, the segment classification method was incorporated into the pressure gradient calculation. The modified method can adapt to the multi-node characteristics of urban pipe networks and help to obtain the preliminary positioning calculation results after optimization. Then the calculation results were embedded in the ITA calculation model. The input parameters of the gas pipeline such as boundary conditions, leakage rate and friction coefficient were used to establish the characteristic linear equations. Then the objective function of the least-squares criterion was defined, and the improved ITA model suitable for leakage detection of urban natural gas pipeline networks was constructed. Finally, the ALO was used to optimize the calculation process of the improved ITA model, and iteratively optimize the optimal friction coefficient and its corresponding minimum objective function (OF) value. As a result, a more precise location of the leakage source was calculated. The validation of the modified method is conducted by comparing the calculated values with the experiment's results. The results show that the method can accurately predict the location where the pipeline leakage occurs. The minimum error is 3.17%. Compared with the traditional ITA, this method not only accelerates the convergence speed of the objective function, but also improves the accuracy of location calculation.

Operation of Natural Gas Pipeline Networks With Storage Under Transient Flow Conditions

We formulate a nonlinear optimal control problem for intra-day operation of a natural gas pipeline network that includes storage reservoirs. The dynamics of compressible gas flow through pipes, compressors, reservoirs, and wells are considered. In particular, a reservoir is modeled as a rigid, hollow container that stores gas under isothermal conditions and uniform density, and a well is modeled as a vertical pipe. For each pipe, flow dynamics are described by a coupled partial differential equation (PDE) system in density and mass flux variables, with momentum dissipation modeled using the Darcy-Wiesbach friction approximation. Compressors are modeled as scaling up the pressure of gas between inlet and outlet. The governing equations for all network components are spatially discretized and assembled into a nonlinear differential-algebraic equation (DAE) system, which synthesizes above-ground pipeline and subsurface reservoir dynamics into a single reduced-order model. We seek to maximize an objective function that quantifies economic profit and network efficiency subject to the flow equations and inequalities that represent operating limitations. The problem is solved using a primal-dual interior point solver and the solutions are validated in computational experiments and simulations on several pipeline test networks to demonstrate the effectiveness of the proposed methodology.

An integrated gas supply reliability evaluation method of the large-scale and complex natural gas pipeline network based on demand-side analysis

The fluctuation characteristics of the gas demand and the effect of the user importance are usually ignored in previous gas supply reliability research. With the intent of overcoming these deficiencies, an integrated method based on the demand-side analysis is proposed in this study to assess the gas supply reliability of the large-scale and complex natural gas pipeline network. The method is composed of the establishment of the indicator system, the demand-side analysis, the estimation of the unit failure probability, and the calculation of the gas supply. Among them, the demand-side analysis focuses on the market demand forecasting and user importance research. Moreover, the coupling effect of the user importance, the hydraulic and pressure constraints, and the unit failure on the gas supply calculation is considered. Furthermore, a real natural gas pipeline network located in China is applied to confirm the feasibility of the method. According to the evaluation results of the gas supply reliability, the weakest nodes and key links of the natural gas pipeline network are identified, and the suggestions to improve the gas supply reliability are proposed as well. At last, the significance of the demand side in the gas supply reliability is elaborated and validated.

Robust Kalman Filter-Based Dynamic State Estimation of Natural Gas Pipeline Networks

To obtain the accurate transient states of the big scale natural gas pipeline networks under the bad data and non-zero mean noises conditions, a robust Kalman filter-based dynamic state estimation method is proposed using the linearized gas pipeline transient flow equations in this paper. Firstly, the dynamic state estimation model is built. Since the gas pipeline transient flow equations are less than the states, the boundary conditions are used as supplementary constraints to predict the transient states. To increase the measurement redundancy, the zero mass flow rate constraints at the sink nodes are taken as virtual measurements. Secondly, to ensure the stability under bad data condition, the robust Kalman filter algorithm is proposed by introducing a time-varying scalar matrix to regulate the measurement error variances correctly according to the innovation vector at every time step. At last, the proposed method is applied to a 30-node gas pipeline network in several kinds of measurement conditions. The simulation shows that the proposed robust dynamic state estimation can decrease the effects of bad data and achieve better estimating results.

A Systematic Methodology to Assess Hydraulic Reliability and Gas Supply Reliability of the Natural Gas Pipeline Network

Abstract Reliability of the natural gas pipeline network is related to security of gas supply directly. According to the different required functions of the natural gas pipeline network, its reliability is divided into three aspects, namely mechanical reliability, hydraulic reliability, and gas supply reliability. However, most of the previous studies confused the definitions of the hydraulic reliability and gas supply reliability. Moreover, the uncertainty in the process of supplying natural gas to the targeted market and the hydraulic characteristic of the natural gas pipeline network are often ignored. Therefore, a methodology to assess hydraulic reliability and gas supply reliability of the natural gas pipeline network is developed in the study, and the uncertainty and hydraulic characteristic of the natural gas pipeline network are both considered. The methodology consists of four parts: establishment of the indicator system, calculation of the gas supply, prediction of the market demand, and assessment of the hydraulic reliability and gas supply reliability. Moreover, a case study is applied to confirm the feasibility of the methodology, and the reliability evaluation results provide a comprehensive picture about the abilities of the natural gas pipeline network to perform the specified gas supply function and satisfy consumers' demand, respectively. Furthermore, a comparison between these two types of reliability is presented. The results indicate that the natural gas pipeline network may not be able to meet the market demand even if the system completes the required gas supply tasks due to the impact of the market demand uncertainty.

Interoperability of LNG terminals and gas pipeline networks

The interchangeability between natural gas of different sources and LNG have been concerned and tackled to a certain extent at home, and the interconnection of gas infrastructures including LNG terminals and gas pipeline networks have also been lifted up to the national level since 2018. However, the research on the interoperability with overall-planning interchangeability and interconnection at a higher level is still in the blank stage at home. By extensively investigating EU's regulations and practices related to interoperability in the field of natural gas pipeline network, this paper put forward the conceptual definition of the interoperability of gas infrastructures including LNG terminals and gas pipeline networks for the first time. Then, the basic implementation framework and components of interoperability were set up. Finally, domestic latest typical cases which have presented the characteristics of interoperability in the recent two years were analyzed. And the following research results were obtained. First, interoperability and third-party access are two independent themes. Second, the target of interoperability is to realize the cross-system unimpeded flow of natural gas of all facility users between different facilities according to the uniform specification of specific technical standards, operation criteria and operation procedures of various facilities, based on interconnection, coordination and information interaction. Third, the framework of interoperability consists of 8 key elements, including gas quality standard & interchangeability, facility interconnection, facility interconnection agreement, unified measurement unit, unified electronic data exchange platform, technical capacity calculation method, approval procedure of LNG carrier entering the port and ship–shore compatibility unique to LNG terminals, and gas quality based LNG storage and tank loading rules. Fourth, it is recommended to give consideration to both target and requirement of interoperability and fully integrate 3 elements that are discussed more deeply and more crucial in EU countries (i.e., facility interconnection agreement, unified electronic data exchange platform and technical capacity calculation method) into the practice system of treatment reform of domestic natural gas industry chain.