Gas Shortage Research Articles

Price responsiveness of commercial demand for natural gas in the US

To estimate price responsiveness of commercial demand for natural gas in the US, we use five parametric specifications to conduct panel data analysis of a newly developed sample of 17,280 monthly observations for the lower 48 states in 1991–2020. We find that the US commercial natural gas demand is price inelastic, with statistically significant (p-value ≤ 0.05) static own-price elasticity estimates of −0.137 to −0.245, short-run −0.152 to −0.261 and long-run −0.281 to −0.463. These estimates vary by choice of a sample period, choice of a parametric specification, treatment of cross-section dependence, assumption of partial adjustment, and exclusion of fixed effects. Further, they vary by season and region and their size has been slowly declining over time. Finally, commercial natural gas shortage cost declines with the size of own-price elasticity estimates. The policy implications of these findings are: (a) price-induced conservation's likely limited effect on the US commercial natural gas demand justifies continuation of energy efficiency standards and demand-side-management programs for deep decarbonization; and (b) demand response programs such as real time pricing and reliability differentiation efficiently allocate limited supply of natural gas during a shortage among heterogenous end-users, thus reducing an economy's aggregate natural gas shortage cost.

Formation of nanobubbles generated by hydrate decomposition: A molecular dynamics study

Natural gas hydrate is estimated to have huge reserves. Its exploitation can solve the global oil and gas shortage problem. Hydrates decompose into water and methane, and methane molecules are supersaturated to form nanobubbles. Methane nanobubbles can affect the decomposition efficiency of hydrates. They can provide abundant methane sources for the re-nucleation of hydrates. Molecular dynamics is employed in this study to investigate the decomposition process of type I methane hydrate and the formation of methane nanobubbles generated during decomposition under different methane mole fraction, pressures, and temperatures. The results indicate that external pressure inhibits the diffusion of methane molecules, thereby preventing the formation of nanobubbles. A higher mole fraction of methane molecules in the system requires a higher external pressure to generate stable nanobubbles after the decomposition of the hydrate structure. At 330 K, it is easy to form a nanobubble structure. Results of this study can help provide ideas for the study of efficient extraction and secondary nucleation of hydrates.

Price Responsiveness of Residential Demand for Natural Gas in the United States

While price responsiveness of residential demand for natural gas has important implications on resource planning and energy modelling, its estimates from prior studies are very diverse. Applying panel data analysis and five parametric specifications to monthly data for the lower 48 states in 1990–2019, we estimate own-price elasticities of residential demand for natural gas in the United States (US). Using results from cross-section dependence (CD) test, panel unit root tests, panel time-series estimators, and rolling-window analysis, we document: (1) the statistically significant (p-value ≤ 0.05) static own-price elasticity estimates are −0.271 to −0.486, short-run −0.238 to −0.555 and long-run −0.323 to −0.796; (2) these estimates vary by elasticity type, sample period, parametric specification, treatment of CD and assumption of partial adjustment; (3) erroneously ignoring the highly significant (p-value < 0.01) CD shrinks the size of these estimates that vary seasonally, regionally, and nonlinearly over time; and (4) residential natural gas shortage costs decline with the size of own-price elasticity estimates. These findings suggest that achieving deep decarbonization may require strategies that do not rely solely on prices, such as energy efficiency standards and demand-side-management programs. Demand response programs may prove useful for managing natural gas shortages.

An Asymmetric Bargaining Model for Natural-Gas Distribution

For the sustainable socio-economic growth, the energy supply is one of the foundations for any country. The gas shortage is one of the most significant impediments to any emerging country’s economic progress, making it a contested and disputed resource. In the middle of a supply–demand mismatch, distributing limited available gas across administrative units/provinces with competing requirements is a key challenge. In this work, an asymmetric gas allocation bargaining model is proposed under gas shortage to resolve natural gas-related disputes among Pakistan’s administrative units/provinces. Each administrative unit/province is characterized by its gas demand. Results show that the Nash bargaining theory, when applied under equal and bargaining weights, can address the supply–demand mismatches of the gas sector in Pakistan. Such an approach could help policymakers to make a fair gas-supply management system during gas shortage periods and would help in resolving the disputes between the provinces.

A systematic method for the optimization of gas supply reliability in natural gas pipeline network based on Bayesian networks and deep reinforcement learning

This study proposes a method based on Bayesian networks (BNs) to optimize the reliability of gas supply in natural gas pipeline networks. The method integrates probabilistic safety analysis with preventive maintenance to achieve the targets of minimizing gas shortage risk and reducing maintenance costs. For this, the tasks of unit failure probability calculation, system maximum supply capacity analysis, gas supply reliability assessment and system maintenance planning are performed. A stochastic capacity network model is coupled with a Markov model and graph theory to generate the state space of the pipeline network system. BN, is then, proposed as the modeling framework to describe the stochastic behavior of unit failures and customer gas shortage. The system maintenance problem is converted into a Markov decision process (MDP), and solved by using deep reinforcement learning (DRL). The effectiveness of the proposed method is validated on a case study of a European gas pipeline network. The results show that the proposed method outperforms others in identifying optimal maintenance strategies. The DRL-optimized maintenance strategy is capable of responding to a dynamic environment through continuous online learning, considering the randomness of the unit failures and the uncertainty in gas demand profiles.

Analysis of the social impact of heat engine and its future application

This paper aims to evaluate the social impact of the heat engine and analyze the application of heat engines in the future. This paper starts with some background information on heat engines and the challenges of gas pollution and gas shortage. The concepts of efficiency and environmental friendliness of the heat engine are widely discussed, which speeds up the development of several kinds of heat engines. We discuss the application of heat engines in different industries from three main aspects: agriculture, marine engine, and aviation. They improve our daily life and provide the required energy to the community. Thermoacoustic Heat Engine (TAHE), Liquid Air Cycle Engines (LACE), and a new class of Heat engine without the expulsion of reaction mass are introduced in this paper. Furthermore, the article will cover some futures. One is artificial intelligence, and another one is about biofuel, which helps heat engines to have higher efficiency and less pollution, and also how heat engines are involved in the next decade.

Editorial and News

Editorial and News

Multi-objective optimization of natural gas supply chain in shortage period

ABSTRACT Natural gas consumption usually has the characteristics of seasonal fluctuations. Some countries have experienced gas shortages in recent years due to the imbalance between supply and demand, especially in winter or peak gas consumption periods. Under the conditions of a gas shortage, it is necessary to ensure the benefits of marketers and improve their satisfaction from users’ perspectives, so it is difficult to find the optimal purchase and sales strategy. Considering that different pipeline transportation pricing mechanisms and different gas distribution schemes have a great impact on the benefits of marketers, this paper proposes a multi-objective optimization model that maximizes the marketer’s benefits and minimizes the hypoxia index for different pipeline transportation mechanisms because of the supply-side gas shortage in the upstream gas source. The object-weighted method is used to process the multi-objective problem. The CPLEX solver is adopted to solve the optimization problem. Finally, the model is applied to a long-distance natural gas supply chain system to prove its applicability. After multi-objective optimization, under the two pipeline transport mechanisms, profits increased by 17.5% and 6.9%, respectively, and the hypoxia index decreased by 1.11 and 1.93, respectively, which greatly improved economic benefits and user satisfaction. Overall, the optimized scheme can maintain the stable operation of the natural gas supply chain and make up for the losses caused by the gas shortage.

Peak underground gas storage efficiency in reducing the vulnerability of gas supply to consumers in an extensive gas transmission system

The paper seeks to address the questions of how to assess the comparative efficiency of peak underground gas storages (PUGSs) to reduce the vulnerability of regional gas systems in the case of emergencies in the gas industry and how to prioritize the commissioning of these PUGSs in a large-scale geographically distributed and ramified gas transmission network.The research method used to answer the posed questions involves the analysis of the natural gas consumption in regions, the technological structure of the main gas transmission network serving these regions, and the technological characteristics of PUGSs planned for construction. This research method suggests specialized multi-iteration model studies to adequately simulate the operation of all process objects of the gas transmission network. Emergencies in the gas transmission network are simulated through the failure of the critical facilities of this network. The operation of the gas transmission network under these conditions is simulated with the planned PUGSs introduced into the network (one at a time). Comparative efficiency and priority of each PUGS are determined by a relative decrease in gas shortage for consumers in the case of this PUGS commissioning during large-scale emergencies in the gas transmission network.The main research results are illustrated by the case of Russia that has a developed gas transmission system with a complex configuration and considerable amounts of gas transported. The vulnerability analysis results are presented for regional gas systems located in the operating area of the Russian gas transmission network before and after the commissioning of these PUGS facilities. All planned storage facilities are ranked according to their efficiency and priority for reducing the vulnerability of regional gas supply systems in cases of large-scale emergencies in the country's gas transmission system. The findings suggest that the proposed approach, when applied to Russia, will reduce the average expected gas shortage across the country under the grave emergencies in the gas transmission network by up to 27%.The conclusion based on the studies and obtained results indicates that the proposed approach is feasible and effective. In practical terms, for Russia, it has been inferred that it is necessary to investigate the possibilities of additional PUGSs in the northern part of the Russian gas transmission network. This will additionally decrease the vulnerability of gas systems in Russia's northern areas, which are most susceptible to gas shortages under emergencies in the gas industry.

An optimized nonlinear grey Bernoulli prediction model and its application in natural gas production

Natural gas, an efficient, eco-friendly and clean green energy, has become one of the important energy structures of various countries in the world, accurately predicting the production of natural gas can help the national energy agency solve “gas shortage” problem. To accurately predict natural gas production in China, this paper establishes an optimized grey system model with weighted fractional accumulation generation operation (abbreviated as WFNGBM(1,1,N)). The proposed model has all the advantages of the GMP(1,1,N) model, NGBM(1,1) model and weighted fractional accumulation generation operation, which makes it have excellent prediction performance. Moreover, five outstanding intelligent optimization algorithms (whale optimization algorithm, marine predators algorithm, grasshopper optimization algorithm, equilibrium optimization algorithm and arithmetic optimization algorithm) are used to solve the hyperparameters of the WFNGBM(1,1,N) model. It is found that the WFNGBM(1,1,N) model has the characteristics of convertibility and small sample modeling, which indicates that it is a small sample prediction model with strong compatibility. After confirming the feasibility of the proposed model compared with its competing models by using natural gas production in Germany, Italy and Canada as examples, the proposed model is used to study China’s natural gas production. The results show that this model is very suitable for predicting and analyzing natural gas production in China. Based on this, the WFNGBM(1,1,N) model is used to estimate China’s natural gas production in the next three years, and some reasonable suggestions are given according to the development trend of natural gas production.

Economic and environmental impacts of the coal-to-gas policy on households: Evidence from China

As the world's largest carbon emitter, China faces serious air pollution problems. Given that both carbon dioxide and air pollutants mainly come from burning of fossil fuels, the coal-to-gas policy has received widespread attention as a way to steer the public towards cleaner energy. However, inflexibility in the early implementation of the coal-to-gas policy caused a shortage of natural gas, and thus had negatively influenced households' lives. Considering the importance of clarifying the economic and environmental impacts of the coal-to-gas policy, this paper employs a dynamic recursive computable general equilibrium (CGE) model and sets different substitution scenarios, to simulate the impacts of the coal-to-gas policy on gross domestic product (GDP), sectoral output, trade, carbon emission reduction, and air quality improvement. The simulation results show that the long-term damage to GDP will be weaker than the short-term one, and carbon emissions would be reduced by 280 and 300 million tons in 2030 under the high and full substitution scenarios, respectively. The emissions of air pollutants (SO2 and NOx) would also decrease significantly. Moreover, our results indicate that it is feasible to increase the substitution ratio in a stepwise manner and eventually achieve full substitution, which can not only effectively avoid shortages of natural gas, but also promote the coordinated control of carbon dioxide and air pollution emissions.

Determination of the Most Interconnected Sections of Main Gas Pipelines Using the Maximum Clique Method

This article is devoted to the definition of the most important combinations of objects in critical network infrastructures. This study was carried out using the example of the Russian gas transmission network. Since natural gas is widely used in the energy sector, the gas transmission network can be exposed to terrorist threats, and the actions of intruders can be directed at both gas fields and gas pipelines. A defender–attacker model was proposed to simulate attacks. In this model, the defender solves the maximum flow problem to satisfy the needs of gas consumers. By excluding gas pipelines, the attacker tries to minimize the maximum flow in the gas transmission network. Russian and European gas transmission networks are territorially very extensive and have a significant number of mutual intersections and redundant pipelines. Therefore, one of the approaches to inflicting maximum damage on the system is modeled as an attack on a clique. A clique in this study is several interconnected objects. The article presents the list of the most interconnected sections of main gas pipelines, the failure of which can cause the greatest damage to the system in the form of a gas shortage among consumers. Conclusions were drawn about the applicability of the maximum clique method for identifying the most important objects in network critical infrastructures.

Potential Analysis and Technical Conception of Exploitation and Utilization of Tar-Rich Coal in Western China

The resources of tar-rich coal in Western China are abundant and are available for large-scale development. Understanding the oil and gas resource properties of tar-rich coal and promoting the development and transformation of tar-rich coal to produce oil and gas are crucial for increasing domestic oil and gas supply, relieving external dependence on oil and gas, and ensuring national energy security of China. This study estimated the potential of tar-rich coal resources in Western China based on the current exploration results of coal resources, reviewed the current status and existing problems, and proposed the basic concept and technical conception for the development and utilization of tar-rich coal in Western China considering the new requirements for carbon reduction, intelligent green development, and compensation for oil and gas shortage. The study concluded that the development and utilization of tar-rich coal needs to focus on key technologies, including high-precision comprehensive exploration, high-recovery-rate mining, underground in-situ pyrolysis, pyrolysis and gasification integration, and in-situ pyrolysis char CO₂ storage. Furthermore, we suggest that the tar-rich coal should be included in the management of unconventional oil and gas resources, scientific and technological research on the development and utilization of tar-rich coal should be strengthened, a national demonstration area should be established, and development of new energy and tar-rich coal in Western China should be coordinated, so as to maximize the special advantages of tar-rich coal as coal-based oil and gas resources and realize the low-carbon and high-value utilization of coal resources.

Changing European Energy Policy : The Challenge of the Energy Price Storm

This paper examines the roots of the European energy crisis within the period of 2021–2022, the reasons for the European gas shortage, the effect of the Russian invasion of Ukraine, and the potential EU responses. The current crisis is a result of several factors, starting from the Covid-19 pandemic in 2020 and amplified severely by the current conflict between Russia and Ukraine. In addition, five reasons were identified as worsening the EU energy situation. These include market-based gas prices, external dependency, global imbalances, the EU's climate policies, and low European energy stocks. The Russian invasion of Ukraine put pressure on the oil and gas supplies to the EU. This situation led the EU to introduce sanctions and measures that target increasing the share of renewable energy while reducing the dependence on Russian gas. Finally, we shed light on the energy transition as an opportunity to deal with climate change and limited energy resources while also showing the challenges that would hinder a just transition.

Overcoming the Energy Crisis in Europe: Collaborative and Selfish Mitigation Strategies of the Gas Shortage

Overcoming the Energy Crisis in Europe: Collaborative and Selfish Mitigation Strategies of the Gas Shortage

How price responsive is industrial demand for natural gas in the United States?

Our panel data analysis of the price responsiveness of industrial demand for natural gas in the United States utilizes five parametric specifications and 10,944 monthly observations for the lower 48 states in 2001–2019 to document statistically significant (p-value ≤ 0.05) static own-price elasticity estimates of −0.027 to −0.062, short-run −0.029 to −0.125, and long-run −0.060 to −0.179. These estimates with relatively small absolute values support the continuation of energy efficiency standards and demand-side-management programs for deep decarbonization. Further, diverse price responsiveness among heterogeneous industrial customers suggests using demand-response programs to efficiently allocate the limited supply available during a natural gas shortage.

Impact of natural gas pricing policy for energy security and macroeconomic resilience: A literature review from global perspective

Indonesia’s government has targeted 24% of natural gas in the national energy mix by 2050. However, one of the main problems in Indonesia’s natural gas development is the price mechanism. Unlike many countries, Indonesia’s natural gas market, including its pricing, is still heavily regulated and subsidized by the government. The low natural gas price has damaged the investment climate and slowed the natural gas development in the country. An overview of the global natural gas market evolution, as well as a comprehensive analysis of natural gas market transformation from China and Malaysia, were presented in this paper. The wider gap between supply and demand of natural gas and the increase of the LNG market in Asia have pushed China and Malaysia to reform their natural gas market into a liberalized system. This provides an insight to examine Indonesia’s natural gas pricing policies. The highly regulated market often fails to provide the actual cost of supply, leads to underinvestment, and causes a natural gas shortage in a country. Natural gas pricing policy transformation is mandatory to ensure supply stability and keep up with the global natural gas market dynamic. The transformation should be implemented gradually to give natural gas producers and end-users enough time to adjust to the regulations. In the end, gas-to-gas competition should be set as the long-term goal to allow retail competition in Indonesia’s natural gas market.

Residential space-heating energy demand in urban Southern China: An assessment for 2030

Residential space heating in urban Southern China has been booming in the recent decade. The massive increase in space-heating demand poses significant challenges to sustainability. A systematic assessment of energy consumption and CO2 emissions resulting from residential space heating is particularly important in guiding policymakers and market stakeholders. This study projects and assesses the energy consumption and CO2 emissions of distributed heating and centralized heating systems in urban Southern China under five different scenarios. The results suggest that by 2030, under the business-as-usual scenario, urban Southern China will consume 77–167 million tce (Mtce) of energy to support its potential space-heating demands and will generate 126–275 million tons (Mt) of CO2 emissions. The corresponding proportion of national total consumption and emissions in 2019 is 1.5–3% and 1.1%–2.4%, respectively. If aggressive decarbonization policies are adopted, the total energy consumption and CO2 emissions will be reduced by 47–53% and 54–60%, respectively. These policies include developing clean heating sources, improving heating system efficiency, and increasing electrification levels. In addition, from the regional perspective, the top 5 out of 133 cities (Shanghai, Chongqing, Hangzhou, Nanjing, and Chengdu) contribute 27% of all sample cities' energy and 23% of CO2 emissions. Some cities, such as Dali and Qianxinan, may suffer a severe gas shortage because the projected gas demand exceeds the current infrastructure capacity. The results demonstrate the importance of adapting suitable heating systems to local conditions.

Technical and Economic Assessment of a High-Quality Syngas Production Process Integrating Oxygen Gasification and Water Electrolysis: The Chinese Case.

Natural gas shortage, waste treatment, and renewable energy utilization and storage are the common issues in China. This research aims to evaluate a simple and reliable biomass and power-to-syngas process for high-quality syngas production integrating oxygen gasification and water electrolysis. The technical and economic evaluations are successively performed based on the simulation data. The single-stage and two-stage gasifiers are integrated and compared. The results show that the process with a two-stage gasifier has advantages in both technical and cost performances over that with a single-stage gasifier. Then, the optimal values of the operating variables are determined by investigating their effects on syngas composition and yield and the overall energy and exergy efficiencies. Then, by setting appropriate amounts of water for electrolysis and methanation pressures, the process can generate two typical products: thermochemical synthetic biogas (TSB) or synthetic natural gas (SNG). The overall energy and exergy efficiencies of TSB can reach 74.1 and 69.5%, respectively, while those of SNG can achieve 64.8 and 64.1%, respectively. The unit product cost of TSB is about one third of that of SNG, indicating that TSB makes a profit while SNG results in loss. A sensitivity analysis of the cost indicates that the constraints for TSB are much looser than those for SNG to gain profit. Additionally, this study proposes two indicators to characterize the electricity-storage capacities of biomass and syngas. The indicators show that SNG has big advantages over TSB in the specific capacity of electricity storage, and the capacities of SNG and TSB are approximately 52.0 and 4.7 times of the specific energy density of the lithium-ion battery pack in 2019, respectively. The work could be used as a reference for the countries lacking natural gas and valuable to guide the development of a two-stage gasifier, reduction in equipment cost, and evaluation of electricity-storage performance using biofuels.

An interval-parameter two-stage optimization model for CO2 collection, distribution, transportation, utilization, and storage planning

Geological carbon dioxide (CO2) utilization and storage have been widely recognized as one of the important options to deliver greenhouse gas emissions reduction. Reasonable planning is critical to promote CO2 utilization and storage. However, CO2 emissions gas collection exhibits a stochastic probability distribution, and CO2 utilization and storage features fluctuation demands, which have gone beyond current determine planning techniques. To fulfill the current research gap, this study develops an interval-parameter two-stage programming-based CO2 collection, distribution, transportation, utilization, and storage optimization model, integrating interval parameter planning and two-stage planning into a general framework. Therefore, the model can address uncertainties expressed as random probabilistic distributions and discrete intervals, tackle dynamic facilities capacity expansion issues, develop optimal predefined CO2 distribution policy, and generate recourse schemes to address gas shortage or gas surplus issues. The model is examined by a typical hypnotical case study in China. The results revealed that the model could generate a set of first-stage reasonable CO2 distribution and facilities capacity expansion schemes to maximum system benefits and the highest feasibility. Besides, a set of two-stage CO2 outsourcing purchases and facilities capacity expansion in reserve storage regions solutions were also generated to address the gas oversupplies and shortage issues. The modeling approach enriches the current CO2 utilization and storage distribution research content under multiple uncertainties.