Natural Gas Demand Research Articles

The TurkStream Pipeline in Light of the Security of Demand for Russian Gas

The purpose of this paper is to analyse the TurkStream project in light of the security of demand for Russian natural gas. The analysis focuses on the relations between the EU and Russia, with further focus on Eastern Europe, accompanied by a description of the power engineering actions affecting the old continent from 2014 to date. Based on the analysis, it can be established that although on the face of it, the Russian-inspired project has policy and business goals, but demand security considerations also lie in the background, fuelled by significant geopolitical endeavours.

Approximating Nonlinear Relationships for Optimal Operation of Natural Gas Transport Networks

The compressor fuel cost minimization problem (FCMP) for natural gas pipelines is a relevant problem because of the substantial energy consumption of compressor stations transporting the large global demand for natural gas. The common method for modeling the FCMP is to assume key modeling parameters such as the friction factor, compressibility factor, isentropic exponent, and compressor efficiency to be constants, and their nonlinear relationships to the system operating conditions are ignored. Previous work has avoided the complexity associated with the nonlinear relationships inherent in the FCMP to avoid unreasonably long solution times for practical transportation systems. In this paper, a mixed-integer linear programming (MILP) based method is introduced to generate piecewise-linear functions that approximate the previously ignored nonlinear relationships. The MILP determines the optimal break-points and orientation of the linear segments so that approximation error is minimized. A novel FCMP model that includes the piecewise-linear approximations is applied in a case study on three simple gas networks. The case study shows that the novel FCMP model captures the nonlinear relationships with a high degree of accuracy and only marginally increases solution time compared to the common simplified FCMP model. The common simplified model is found to produce solutions with high error and infeasibility when applied on a rigorous simulation.

Identifying policy and legal issues for shale gas development in Algeria: A SWOT analysis

In the face of declining natural gas production, depleting foreign revenue and the local and international demand for natural gas, Algeria seeks to develop its substantial shale gas potential to avoid economic decline. This paper uses a SWOT analysis method to identify key policy and legal issues for shale gas development in Algeria. It broadly investigates the internal strengths (S) and weaknesses (W) and external opportunities (O) and threats (T) facing Algeria’s shale gas development. Qualitative data from policies, laws, and reports, and literature reviews from books and journal articles are utilised in examining Algeria's external and internal environment concerning the development of its shale gas. Based on the analysis, this paper identifies alternative strategies and responses for the development of shale gas resource in Algeria. Thus, it is necessary for providing the Algerian government and other stakeholders with the relevant information to identify which course of action it could take with reference to developing the country’s shale gas. It further provides researchers with a foundational understanding of the broad context surrounding development so that future research can also assess shale gas development in Algeria.

Modeling and scenario prediction of a natural gas demand system based on a system dynamics method

Based on the study of the relationship between structure and feedback of China’s natural gas demand system, this paper establishes a system dynamics model. In order to simulate the total demand and consumption structure of natural gas in China, we set up seven scenarios by changing some of the parameters of the model. The results showed that the total demand of natural gas would increase steadily year by year and reach in the range from 3600 to 4500 billion cubic meters in 2035. Furthermore, in terms of consumption structure, urban gas consumption would still be the largest term, followed by the gas consumption as industrial fuel, gas power generation and natural gas chemical industry. In addition, compared with the population growth, economic development still plays a dominant role in the natural gas demand growth, the impact of urbanization on urban gas consumption is significant, and the promotion of natural gas utilization technology can effectively reduce the total consumption of natural gas.

Energy security for socio-economic and environmental sustainability in Pakistan

One of the prime concern of policy makers should be to ensure energy security in the country. The case of Pakistan is interesting in a sense that with the growing age of the country, the increasing reliance on imported sources of energy is resulting in huge demand-supply gap which is evident in suppressed demand for electricity and natural gas. It has social, economic and environmental consequences. Most of the countries in the world have shifted their focus from imported to indigenous resources which are more often cheap, environmental friendly and provide competitiveness. The study reveals, through exploring secondary data, descriptive analysis, Johanson Cointegration and Granger Causality test results based on error correction model, energy insecurity is damaging for environment and socio-economic conditions. The study suggests policy makers to move toward long run energy security to get environmental and socio-economic sustainability in the country through minimizing reliance on imported energy and promoting energy efficiency.

A novel self-adapting intelligent grey model for forecasting China's natural-gas demand

Natural gas plays an important role in China's sustainable economic development, and its demand is expected to increase its proportion in energy mix in the future. The aim of this present paper is to evaluate the future demand of natural gas in China, based on the historical data that is characterized by uncertainty and sparsity. To this end, a self-adapting grey prediction model having a nonlinear optimized initial value has been designed to intelligently adapt to features of natural-gas consumption. The new initial value in the modified model has the advantage of an adjustable weighted coefficient in each component of the accumulated sequences, which performs better than the previous initial values that have a fixed structure and poor adaptability to the volatility series. Moreover, to achieve high accuracy, the generating parameters in the new initial value can be optimally determined by utilizing an ant lion optimizer (ALO) algorithm. To demonstrate its efficacy and practicality, this new model is implemented to fit and forecast China's natural-gas consumption from 2002 to 2014 in comparison with a range of benchmark models. The experimental results indicated that the fitted and predicted performance of the new model is better than those of the competitors. Therefore, the novel self-adapting intelligent model is employed to predict China's natural gas demands from 2015 to 2020. The forecasted result shows that China's natural gas demand will reach more than 340 billion m3 in 2020, which is consistent with those presented by other international professional agencies and researchers in recent years. Ultimately, according to the predicted results, relevant natural gas suggestions are proposed for decision-makers.

Understanding the US natural gas market: A Markov switching VAR approach

Over the past three decades, the US natural gas market has witnessed significant changes. Utilizing a standard Bayesian model comparison method, this paper formally determines four regimes existing in the market. It then employs a Markov switching vector autoregressive model to investigate the regime-dependent responses of the market to its fundamental shocks. The results reveal that the US natural gas market tends to be much more sensitive to shocks occurring in regimes existing after the Decontrol Act 1989 than the other regimes. The paper also finds that shocks to the natural gas demand and price have negligible effects on natural gas production while the price of natural gas is mainly driven by specific demand shocks. Augmenting the model by incorporating the price of crude oil, the results show that the impacts of oil price shocks on natural gas prices are relatively small and regime-dependent.

Bacterial Biomarkers of Marcellus Shale Activity in Pennsylvania.

Unconventional oil and gas (UOG) extraction, also known as hydraulic fracturing, is becoming more prevalent with the increasing use and demand for natural gas; however, the full extent of its environmental impacts is still unknown. Here we measured physicochemical properties and bacterial community composition of sediment samples taken from twenty-eight streams within the Marcellus shale formation in northeastern Pennsylvania differentially impacted by hydraulic fracturing activities. Fourteen of the streams were classified as UOG+, and thirteen were classified as UOG- based on the presence of UOG extraction in their respective watersheds. One stream was located in a watershed that previously had UOG extraction activities but was recently abandoned. We utilized high-throughput sequencing of the 16S rRNA gene to infer differences in sediment aquatic bacterial community structure between UOG+ and UOG- streams, as well as correlate bacterial community structure to physicochemical water parameters. Although overall alpha and beta diversity differences were not observed, there were a plethora of significantly enriched operational taxonomic units (OTUs) within UOG+ and UOG- samples. Our biomarker analysis revealed many of the bacterial taxa enriched in UOG+ streams can live in saline conditions, such as Rubrobacteraceae. In addition, several bacterial taxa capable of hydrocarbon degradation were also enriched in UOG+ samples, including Oceanospirillaceae. Methanotrophic taxa, such as Methylococcales, were significantly enriched as well. Several taxa that were identified as enriched in these samples were enriched in samples taken from different streams in 2014; moreover, partial least squares discriminant analysis (PLS-DA) revealed clustering between streams from the different studies based on the presence of hydraulic fracturing along the second axis. This study revealed significant differences between bacterial assemblages within stream sediments of UOG+ and UOG- streams and identified several potential biomarkers for evaluating and monitoring the response of autochthonous bacterial communities to potential hydraulic fracturing impacts.

Natural gas consumption of urban households in China and corresponding influencing factors

Driven by the impact of economic growth, urbanization, and national strategies for low-carbon development, the TNGC of urban households in China is growing rapidly. In this paper, the feasible generalized least square method is used to investigate the consumption of natural gas and the per capita natural gas consumption of urban residents in 30 provinces in China (not including central heating and the natural gas consumption of natural gas vehicles). We study the factors influencing natural gas consumption by urban residents in China and conduct scenario forecasting. The empirical results show that the impact coefficients of PNGs and household income on average natural gas consumption are − 0.895 and 0.222, respectively, while the impact coefficients of the NGP are − 0.603 and 0.346, respectively. The scenario forecast results show that the consumption of natural gas in Chinese households reached 75.469 billion cubic meters in 2025. China's natural gas season peak pressure will continue to increase. In response to this, the following three suggestions are proposed. (1) According to the price elasticity of natural gas, the Chinese government should adjust and improve the mechanism for the formation of PNGs for residents and promote the marketization of natural gas. (2) Accelerate the construction of natural gas reserves and allocate the natural gas supply according to regional differences in natural gas consumption to enhance China's natural gas peak shaving capacity. (3) Improve and optimize natural gas development plans to achieve coordinated development of natural gas supply and demand.

A System Dynamics Model for Analyzing Future Natural Gas Supply and Demand

This paper models a natural gas supply and demand system using a system dynamics approach to determine whether current policies for a given country will sustain its long-term natural gas demand. Th...

Corroboration of sparse failure data through Bayesian estimation for natural gas cross country pipelines: A case study with reference to the Indian scenario

The rising demand for Natural Gas (NG) in India, a developing country, necessitates adequate, uninterrupted and safe transmission and distribution of the gas to consumers at various points within the country. Though pipelines are considered as the safest mode of transportation, the failure of a flammable and highly pressurized natural gas pipeline can cause fatalities and extensive damage to properties. A reliable estimation of occurrence probabilities of ‘actual’ natural gas pipeline incident scenarios helps to evaluate the safety management and control system existing in the country. Unfortunately, India does not maintain any quantitative failure data base of the natural gas pipeline incidents due to lack of operational history. This paper outlines the use of Bayesian logic for corroborating the existing sparse and imprecise occurrence proportion of natural gas pipeline incident scenarios obtained from the incident analysis reports. This is done by incorporating the specific unreported Piped Natural Gas (PNG) incident scenario frequency per year. Posterior occurrence probability estimates of the incident scenarios lie between the sparse prior proportions obtained from the published incident analysis reports and the likelihood proportion of specific PNG incidents happening in India per year. The newly generated data through the Bayesian estimation therefore can be considered more reliable and sensible and are also validated like such data available in the developed countries. The posterior estimates also necessitate more improved safety management and control system in each City Gas Distribution (CGD) entity within the country to reduce specific failure cause-consequences.

Determinants of global natural gas consumption and import–export flows

Based on the data of the BP Statistical Review of World Energy, this paper constructs the consumption and import–export of natural gas identities. It discusses the drivers of changes in global natural gas consumption and trade flows from 2008 to 2015 using the extended logarithmic mean Divisia index. The results show that differences in the natural gas supply and demand across countries or regions, as well as the distribution of energy between the domestic and international markets, can be better explained when natural gas trade movements are considered. By comparing the supply and consumption increment of natural gas, this study finds that only the energy intensity, economic growth, and demographic effects are consistent with each other. The changes in the impact of other effects mainly depend on storage variations and statistical errors. In addition, the primary drivers of the incremental changes in natural gas consumption vary in different countries. They include production scale, import scale, export scale, consumption structure proportion, energy intensity, economic growth, and population and balance effects. Finally, the consumption competitiveness of the liquefied natural gas significantly improved over the examined period.

Lessons learned from long term monitoring of a multisource heat pump system

Dual or multisource heat pumps were conceived to obviate to the defects of a single source, outside air or ground or solar radiation. Many studies simulated the possible behavior of combination of sources, but only few experimental results based on long term surveys on operating buildings are available in literature.A long term survey on a multisource heat pump system for the heating of a school building located in northern Italy gives the possibility of an evaluation based on real data. The main design features of the building incorporate a well insulated envelope, and a space heating and ventilation system driven by an innovative multisource heat pumps system. The latter incorporates outdoor air, ground, solar radiation, and heat recovery as heat sources, so enhancing the performance in terms of heating capacity and overall efficiency. The surveyed period concerns the last five heating seasons (2012–2017) allowing an assessment of the energy performance of the system based on real data monitored. The analysis permitted to identify incorrect settings, bad operation of the plant and heat pumps underutilization. The heating service was all the same assured, and the natural gas demand, almost steady if not in slight decrease, did not worry the management. Only the availability of data records and a careful analysis allowed to identify the bad working of the plant and the failure to achieve potential energy savings.The main novelty of this work is the highlighting of the paramount importance of monitoring and carefully analyzing recorded data as a guide to the plant management to keep correct operations, particularly when the plant integrates many different technologies even in the long term.

Energy recovery from wine sector wastes: A study about the biogas generation potential in a vineyard from Rio Grande do Sul, Brazil

The constant concern with the environment and the depletion of fossil fuels has attracted interest in renewable energy from bio resources and/or materials wasted incorrectly. The process of anaerobic digestion converts organic waste into valuable energy sources, while reducing the pollution potential of this waste to the environment. The study was designed to analyze the biogas and methane generation potential from organic by-products of wine. Using the methodology described in VDI 4630 and automated biogas quantification based on the displacement of fluids. The results showed the biogas and methane production potential of the wine biomasses, and the ones with greatest potentials are grape must, the mixture of all biomass and bagasse 1.151; 289 and 199 m3 biogas.tonVS−1, respectively. Likewise, it was verified that biomass energy recovery for methane production has the capacity to supply approximately 2% of the natural gas demand in Rio Grande do Sul. These results presented specifically the biomass characterization of the wine sector and as potential energy for the production of biogas and methane, verifying the possibility of using this form of clean and sustainable energy on a large scale.

Forecasting day-ahead high-resolution natural-gas demand and supply in Germany

Forecasting natural gas demand and supply is essential for an efficient operation of the German gas distribution system and a basis for the operational decisions of the transmission system operators. The German gas market is moving towards more short-term planning, in particular, day-ahead contracts. This increases the difficulty that the operators in the dispatching centre are facing, as well as the necessity of accurate forecasts. This paper presents a novel predictive model that provides day-ahead forecasts of the high resolution gas flow by developing a Functional AutoRegressive model with eXogenous variables (FARX). The predictive model allows the dynamic patterns of hourly gas flows to be described in a wide range of historical profiles, while also taking the relevant determinants data into account. By taking into account a richer set of information, FARX provides stronger performance in real data analysis, with both accuracy and high computational efficiency. Compared to several alternative models in out-of-sample forecasts, the proposed model can improve forecast accuracy by at least 12% and up to 5-fold for one node, 3% to 2-fold and 2-fold to 4-fold for the other two nodes. The results show that lagged 1-day gas flow and nominations are important predictors, and with their presence in the forecast model, temperature becomes insignificant for short-term predictions.

Natural gas in China: Development trend and strategic forecast

Based upon an analysis of global energy developing trend, a discussion was made on the natural gas developing trend in China with the following pre-estimating results from multiple perspectives. (1) Natural gas will be strongly demanded and in 2050 it will be up to 650–700 billion cubic meters (bcm). (2) The high-medium-low peaking scenarios of natural gas production rate in 2030 will be 180 bcm, 200 bcm and 220 bcm, respectively. (3) Up till now, the supply capacity of inland pipeline gas will be about 160 bcm. (4) LNG will be the main approach to filling the gap in the natural gas demand. (5) When the peak value of domestic production and pipeline gas is definite, LNG and storage gas will play an important role in the whole natural gas industrial chain in the future. Also, according to the basic condition of China, the strategies for future natural gas development were presented as follows: to enhance the capabilities of domestic gas productivity, pipeline transportation, gas storage (such as LNG terminals, UGS, etc.); to set up an early warning system for oil & gas peak security consumption with detailed supply and demand information based upon AI technology and big data analysis; to make breakthroughs in coal cleaning and new energy production technologies for lack of non-renewable oil and gas resources; and to get a better understanding of global energy developing trend and have an omni-direction strategic layout for national energy security thus to quicken the pace of a new tripartite confrontation era of coal, petroleum and new energy sources.

Gas production peaks in China: Research and strategic proposals

The peaks of natural gas production are of great significance to the planning of national energy strategy, the coordinated development of natural gas industry chain and the investment decision-making for oil and gas companies. Therefore, based on natural gas geological and development characteristics, the production peaks of conventional gas (including tight gas), CBM and shale gas in China have been systematically analyzed and forecasted using multiple methods. The following conclusions are drawn: first, the cumulative gas production in China will reach 280–330 bcm by 2035 and 330–410 bcm by 2050; second, the conventional gas production peaks will be easily predicable during the forecast period, while the peaks of CBM and shale gas production need to be further forecasted and tracked continuously; third, with the possible breakthrough of gas hydrate exploration and development being considered, gas production in China has a great potential and bright future. In order to achieve a strategic goal of energy transformation and conservation and to guarantee a safe and stable gas supply, a timely profound analysis and study will be necessary on the international political, economic and energy development situation for a global gas strategic layout. In view of this, based on the analysis of domestic natural gas supply and demand situation, the following proposals are put forward: to speed up the domestic tapping and commercial production of those deep-strata, deep-water and unconventional gas resources to consolidate the dominant position of domestic natural gas supply; to attach great importance to a strategic layout of overseas gas resources utilization and to adopt various ways to ensure the security of domestic gas market; to accelerate the evaluation of gas hydrate development in order to enlarge and consolidate the gas resource basis; and to strengthen a dynamic forecast on the peaks of gas production in order to continuously enhance the soft power in international competition.

Co-optimization scheduling of interdependent power and gas systems with electricity and gas uncertainties

The rapid growth of natural gas fuel consumption by gas-fired generators and the new emerging power-to-gas technology have intensified interdependency of electric power and natural gas systems. Consequently, such interdependency, together with heterogeneous uncertainties of the power system (e.g., power loads and renewable energy) and the gas system (e.g., gas loads), has brought new challenges to energy system operators for the secure and economic operation of interdependent power and gas systems. Specifically, uncertainties from one infrastructure could easily spread to the other, which consequently increase vulnerability and eventually lead to cascading outages of both systems. This paper proposes a two-stage adjustable robust model to study day-ahead coordinated optimal scheduling of the interdependent power and gas systems. Dual-fuel generating units are also considered for shaving gas fuel consumptions and ensuring the security of both systems during peak gas demand hours. Moreover, Weymouth gas flow constraints are linearized via Taylor series expansion, which facilitates the implementation of column-and-constraint generation algorithm to effectively solve the proposed two-stage adjustable robust model with nonlinear gas flow constraints in the second stage. Numerical case studies illustrate that dual-fuel units can enhance the secure and economical operation of interdependent power and gas systems, especially when natural gas demands present upward uncertainties. It is also demonstrated that power-to-gas facilities can facilitate a deeper penetration of volatile renewable energy by effectively converting excessive renewable generation into natural gas.

The future of natural gas infrastructure development in the United states

Changes in the natural gas market have spawned the need for pipeline infrastructure planning. Previous studies have analyzed natural gas infrastructure development largely independent of the interactions of the natural gas sector with the broader economy. However, natural gas infrastructure development is strongly influenced by broader domestic and international socioeconomic conditions. We couple a global Human-Earth system model with state-level detail in the United States (GCAM-USA) that provides the broader socioeconomic context for natural gas supply and demand with a natural gas infrastructure investment model (NANGAM) to examine inter-state natural gas pipeline infrastructure development in the U.S. under a range of socioeconomic scenarios. Here we show that existing pipeline infrastructure in the U.S. is insufficient to satisfy the increasing demand for natural gas and investments in pipeline capacity will be required. However, the geographic distribution of investments within the U.S. is heterogeneous and depends on the capacity of existing infrastructure as well as the magnitude of increase in demand. Our results also illustrate the risks of under-utilization of pipeline capacity, in particular, under a scenario characterized by long-term systemic transitions toward a low-carbon economy. More broadly, our study highlights the value of integrated approaches to facilitate informed decision-making.

Combining Grey Model and Self-Adapting Intelligent Grey Model with Genetic Algorithm and Annual Share Changes in Natural Gas Demand Forecasting

Along with the high growth rate of economy and fast increasing air pollution, clean energy, such as the natural gas, has played an important role in preventing the environment from discharge of greenhouse gases and harmful substances in China. It is very important to accurately forecast the demand of natural gas in China is for the government to formulate energy policies. This paper firstly proposes a combined forecasting model, name GM-S-SIGM-GA model, to forecast the demand of natural gas in China from 2011 to 2017, by constructing the grey model (GM(1,1)) and the self-adapting intelligent grey model (SIGM), respectively; then, it employs a genetic algorithm to determine the combined weight coefficients between these two models. Finally, using the tendency index (the annual changes of the share of natural gas consumption from the total energy consumption), which completely reveal the annual natural gas consumption share among the market, to successfully adjust the fluctuated changes for each data period. The natural gas demand data from 2002 to 2010 in China are used to model the proposed GM-S-SIGM-GA model, and the data from 2011 to 2017 are used to evaluate the forecasting accuracy. The experimental results demonstrate that the proposed GM-S-SIGM-GA model is superior to other single forecasting models in terms of the mean absolute percentage error (MAPE; 4.48%), the root mean square error (RMSE; 11.59), and the mean absolute error (MAE; 8.41), respectively, and the forecasting performances also receive the statistical significance under 97.5% and 95% confident levels, respectively.