Gas Consumption Research Articles

Pricing electricity from blue hydrogen to mitigate the energy rebound effect: A case study in agriculture and livestock

As the world's second largest producer of natural gas, Iran relies heavily on natural gas for 70% of its energy needs. There are, however, challenges associated with energy supply in remote regions attached to the gas pipeline network, particularly during the cold season when fuel oil is required for heating and energy provisioning. To address this issue, this research proposes the use of alternative energy sources, such as hydrogen, for non-residential energy consumption, including agriculture and livestock. A key objective of this study is to develop an optimization model for the generation of electricity from hydrogen resources, as well as formulate a robust strategy to assist electricity producers in maximizing their profits. Using this model, producers are able to set prices in accordance with their risk tolerance and present them to the market, thus mitigating price fluctuations. In the targeted sectors, the results indicate that appropriate pricing models can prevent rebound effects. Specifically, the implementation of this model can reduce natural gas consumption by up to 20% and fuel oil usage by 15% during peak seasons. Additionally, the optimal pricing strategy can lead to a 10% reduction in greenhouse gas emissions. The results of this research provide stable and reliable solutions to the energy supply challenges in these regions, thus making the energy market more resilient and environmentally friendly.

The Role of Labor Force, Physical Capital, and Energy Consumption in Shaping Agricultural and Industrial Output in Pakistan

The labor force, physical capital, and energy sources are key economic drivers that enhance the output levels of developing economies. Despite their significance, the impact of these factors on agricultural and industrial output in Pakistan remains underexplored. This study aims to address this gap by examining the effects of the labor force, physical capital, and energy consumption—including electricity, oil, and gas—on agricultural and industrial output. Additionally, we explore the combined effects of electricity and oil consumption on these sectors. Based on unit root test results, which indicate that the variables as either I(0) or I(1), the Autoregressive Distributed Lag (ARDL) technique is selected. This method is particularly effective for handling mixed integration orders and provides robust estimates in small sample sizes, allowing for a thorough examination of both short- and long-run dynamics. Using annual time-series data from Pakistan for the period 1990–2022, the empirical results reveal that higher levels of the labor force, physical capital, electricity consumption, oil consumption, and gas consumption significantly increase agricultural and industrial output in both the short and long run. Furthermore, the findings reveal that the combined effect of electricity and oil consumption has a stronger impact on agricultural and industrial output compared to their individual effects. These results are further validated using alternative econometric techniques such as DOLS and FMOLS. To enhance Pakistan’s agricultural and industrial performance, policies should prioritize investment in human capital and physical capital development, ensure reliable and efficient energy supplies, and promote integrated energy management strategies. These steps are crucial for fostering sustainable economic growth and productivity in both sectors.

Quantifying the spatial variation of the energy performance gap for the existing housing stock in England and Wales

This paper evaluates the energy performance gap between Energy Performance Certificate predictions and annual gas meter reading measurements for the existing housing stock in England and Wales. Energy Performance Certificates predict energy using the SAP model, the UK regulatory tool for existing dwellings widely used in national and local housing energy policies. The results show an energy performance gap of between + 16.6 % and + 17.9 % at the national level. Of concern is that the performance gap is shown to vary greatly across different regions of England and Wales ( − 23.7 % to + 56.4 % for local authorities) and to vary with factors such as built form, construction age and predicted gas consumption. This suggests that there may be structural errors in the EPC/SAP approach resulting in certain spatial areas or dwelling types having more errors in their EPC predictions, impacting on future planning for housing stock retrofits.

Dynamic delay-based game approach in car and petrol supply chains under government intervention

Effective decision-making in a temporal context is challenged by the enduring impacts of delays, where decisions made in a certain period are influenced by choices made in preceding periods. This paper delves into the analysis of decision-making in a dynamic game system characterized by delay impact on decisions. Notably, it pioneers the application of a game approach to detect the intricate relationship between car and petrol supply chains operating under conditions of dynamism and uncertainty. The marginal profit method is applied to deal with the dynamic game model. Furthermore, this article investigates the improvement of green car levels, on member profits. In the car supply chain, the car manufacturer sells two distinct product types: green and regular. In this paper, green cars refer to cars with low petrol consumption, and as gas consumption decreases, the green level of the car ascends. This study marks the first instance where optimal production capacity allocation is examined within the framework of delay and uncertainty. Considering the government's initiative to curtail petrol consumption in automobiles, the effects of the government's supporting role are also analyzed in this paper. As a result, the greenness level witnessed a 4.1-fold increase, leading to an 81.7% surge in the demand for green cars, consequently boosting the profit of the entire car supply chain. Several numerical experiments of a real case were examined to evaluate the performance of the proposed models. Finally, some sensitivity analyses were applied to the principal parameters of the model to extract managerial insights.

Energy consumption and dilution of toxic gases in underground infrastructures: A case study in a railway tunnel under forced ventilation

Toxic fumes are released after blasting in underground excavations. The analysis of safe re-entry times into the work areas is essential for addressing safety and productivity concerns. In this paper, a railway tunnel 2.1 km long under forced ventilation system is selected as a case study to assess the energy consumption and re-entry times after blasting under different ventilation conditions. First, three-dimensional CFD numerical models were conducted in order to predict the migration time to reduce the levels of noxious gases below the limits established in safety regulations. Field measurements were conducted to verify the accuracy of the results obtained in the simulations. Then, additional analytical models were conducted to evaluate the energy consumed by the ventilation system. The results obtained show that the accumulated re-entry time reaches 414 h for the excavation of the tunnel employing an airflow rate of 40 m3 s−1. This time increases by 33 % when the airflow rate decreases to 30 m3 s−1. However, even though the time decreases when the ventilation volume increases, energy consumption increases significantly, reaching 1,306 MWh for a ventilation volume of 40 m3 s−1 compared to 551 MWh using an airflow of 30 m3 s−1.

Development of a Controlled Humidity Differential Electrochemical Gas Monitoring System

Lithium-air batteries (LABs) represent a promising future battery technology due to their high energy density, although several challenges hinder them from achieving their theoretical performance. These challenges include clogging of the porous air cathode by insoluble discharge products and high overpotentials during cycling [1, 2]. A recent proposal to address these issues involves the reversible formation and oxidation of LiOH in nonaqueous LABs. Of course, LiOH-based LABs require a proton source to form LiOH from the electrochemical reaction of oxygen and lithium ions [3]; humidity in air is an obvious choice for the proton source, making the relative humidity of LAB feed gas an important parameter to control and monitor during LAB electrochemical analysis.For LABs, galvanostatic charge/discharge coupled with quantitative gas evolution/consumption measurement is essential to understand the electrochemical processes during battery operation. Here, we report an advanced operando pressure measurement system that allows the control and monitoring of humidity in the cell headspace while also tracing overall gas consumption and evolution. Our gas handling system generates humid air using a water-containing chamber with a temperature control vessel to generate water vapor. A mass flow controller mixes dry air with humid air to generate specific relative humidity and send it to the cell. Using various low-volume in-line sensors, our system can track headspace humidity, temperature, and pressure within a custom-modified Swagelok-type cell. The total headspace volume must be small (~mL) since gas consumption occurs on a μmol scale in our lab-scale cells. To minimize headspace and dead volume within the Swagelok-type cell, a digital humidity and temperature sensor with exceptional accuracy was integrated into a customized printed circuit board (PCB). This PCB is attached to the small dead-volume Tee connection. To control the humidity inside the cell and achieve sensor data simultaneously, all sensors in the monitoring system are controlled by a LabVIEW program (National Instruments). To show the utility of this new system, we will present analyses of nonaqueous and solid-state LAB cells that operate at various humidities and current rates, while employing various known 2 e- and 4 e- oxygen reduction catalysts.

Determining the critical time points for hydrate formation in the presence of kinetic hydrate inhibitors: A rheological and kinetic study

Kinetic hydrate inhibitors have the characteristics of delaying hydrate nucleation and reducing hydrate growth rate. The utilized of kinetic hydrate inhibitors for hydrate blockage risk management is a promising technology for hydrate prevention in oil and gas industry. In this study, the rheological and kinetic properties of gas–water systems contained pure water, polyvinyl pyrrolidone and newly-synthesized inhibitor during hydrate formation at different subcooling degrees were in situ characterized using a high-pressure rheometer. By analyzing the experimental results, the concept of ‘critical time’ have been proposed to divide the time-varying process of hydrate formation into multiple stages. The three critical times indicated distinct trends in viscosity and pressure changes, as well as varying risks of hydrate blockage in hydrate prevention. The results further compared the differences in determining critical time through pressure and viscosity. The critical time of hydrate nucleation determined by viscosity was earlier than pressure due to the hypothesis of lag in gas consumption. The critical time of rapid hydrate growth determined by viscosity was later than gas consumption, which may be due to that the sharp increase in viscosity requires the aggregation of hydrates. According to the inhibition effect evaluation results determined by three critical times, it was found that the newly-synthesized inhibitor was more effective than polyvinyl pyrrolidone in inhibiting nucleation, delaying rapid hydrate growth time and reaching high viscosity time. This study can provide a comprehensive evaluation method for assessing the performance of kinetic hydrate inhibitors from both kinetic and rheological perspectives.

Combined solar and ground source heat pump heating system with a latent heat storage tank as a sustainable system to replace an oilfield hot water station

Present study focuses on a clean energy replacement for an oilfield hot water station and develops a combined solar and ground source heat pump (GSHP) heating system with a latent heat storage tank (LHST). The effects of LHST and heat replenishment on energy and coefficient of performance (COP) are quantitatively analyzed during short-term or long-term operation of the system. The suitability of three different phase change materials for the system is compared, and the optimal one is identified. Results show that the LHST with 70 °C melting point can increase the collector efficiency to 53.91 % and reduce the total energy consumption of the system by 52344 kWh. Heat replenishment could effectively mitigate the ground temperature drop to 0.19 °C/year, reducing the annual energy consumption of GSHP by more than 4230 kWh and providing an additional thermal energy of 72 GJ. Compared to the initial heating system, the novel system efficiency increases to 51.25 %. Gas consumption and total system energy consumption decreased by 81.7 % and 75.2 %, respectively. Annual reduction of CO2 emission is about 1150 tons, showing satisfactory performance. Outcomes of this study prove the application of clean energy in oil field industrial processes, and help in achieving the goals of emission reduction and carbon neutrality.

Blockchain-Enhanced Hydrogen Fuel Production and Distribution for Sustainable Energy Management

Renewable energy projects, particularly wind and solar farms, have garnered significant attention as a potential solution to global energy challenges. Despite the energy production obstacles, the steady availability of fossil fuels continues to compete due to established distribution systems, as societies increasingly rely on electricity. Hydrogen fuel emerges as a promising avenue for energy production, storage, and distribution, involving converting surplus renewable electricity into hydrogen through electrolysis, storing it, and distributing it. Our novel approach leverages blockchain technology to enhance the efficiency and traceability of hydrogen fuel production, offering a unique synergy of transparency, security, and decentralized governance. We showcase its viability and effectiveness using the ERC-1155 token standard to tokenize renewable resources and convert them into hydrogen fuel. Within our tokenized fuel blockchain architecture, we simulate the forecasted growth in hydrogen production and vehicle demand, highlighting our approach's efficiency, traceability, and transparency. This integration showcases the potential for a sustainable hydrogen fuel ecosystem. The gas consumption data analysis indicates that the daily gas consumption remains below 194 million Gas for refilling 3245 vehicles (including the cost of one-time contract deployment), demonstrating the feasibility and efficiency of our approach.

Journalists in a circular economy: Stakeholders’ engagement in the media discourse on single-use plastics during the COVID-19 pandemic

The world faces an alarming plastic waste problem. The volume of plastic waste is rapidly and continuously increasing, mainly due to the single-use plastics overconsumption, whereas its recycling and utilization leave much to be desired. Despite the negative effects of plastic on the environment and public health, the COVID-19 outbreak shifted the public attention away from the environmental issues, potentially giving space for extended lobbyism by interest groups and industry to delay or even prevent legislation to combat plastic pollution.Our study aims to understand how the media discourse on single-use plastic (SUP) in particular, evolves in the course of the pandemic. How it vary across EU Member States? For this purpose, we specifically analyse plastic-related articles in major prestigious daily newspapers published between June 2019 and June 2021 in four EU Member States: Germany, France, Italy, and Poland, as countries with different levels of sustainable transition to form a representative model of an European context. Additionally, between November 2022 and January 2023, we conducted a series of interviews via Google Meet, with journalists who agreed to be asked on the plastic issues they upraised.Our analysis initially covered 1076 articles, out of which 198 articles were rejected due to non-compliance with the subject or repetition, leaving 878 articles forming the database for eventual analysis. Specifically, we outline a key impact of the COVID-19 pandemic followed by a clear evolution on the number of plastic-related articles, on related stakeholder engagement, and the focus on specific SUP items. Moreover, we address a research gap - presenting a media portrait of different types of SUP in more details and highlighting the significance based on several culturally and linguistically very different countries within a single supranational state (EU).A clear trend reversal towards an informed knowledge circulation across the circular economy model of single-use plastics is ultimately essential to develop sustainable solutions to reject the disposable culture, stop the waste of natural resources, and reduce the consumption of oil or gas for plastic production and thus protect the climate.

The Influence of Atmospheric Air Temperature on the Consumption of Natural Gas in Terms of Heating Costs of a Single-Family Building – A Case Study

The Influence of Atmospheric Air Temperature on the Consumption of Natural Gas in Terms of Heating Costs of a Single-Family Building – A Case Study

Natural gas consumption forecasting using a novel two-stage model based on improved sparrow search algorithm

The foundation of natural gas intelligent scheduling is the accurate prediction of natural gas consumption (NGC). However, because of its volatility, this brings difficulties and challenges in accurately predicting NGC. To address this problem, an improved model is developed combining improved sparrow search algorithm (ISSA), long short-term memory (LSTM), and wavelet transform (WT). First, the performance of ISSA is tested. Second, the NGC is divided into several high- and low-frequency components applying different layers of Coilfets’, Fejer-Korovkins’, Symletss’, Haars’, and Discretes’ orders. In addition, the LSTM is applied to forecast the decomposed components in view of the one- and multi-step, and its hyper-parameters are optimized by ISSA. At last, the final prediction results are reconstructed. The research results indicate that: (1) Comparing to other machine algorithms (e.g. fuzzy neural network), the convergence speed and stability of ISSA are stronger in view of standard deviation and mean; (2) The prediction performance of the developed model is better than that of other forecasting models; (3) The forecasting performance of the single-step forecasting is superior to that of the two-, three-, and four- step; (4) The computational load of the proposed prediction model is the highest compared to other models, and the prediction accuracy is still excellent on the extended time series.

Analyzing Regulatory Impacts on Household Natural Gas Consumption: The Case of the Western Region of Ukraine

Analyzing Regulatory Impacts on Household Natural Gas Consumption: The Case of the Western Region of Ukraine

A Novel Multiscale Transformer Network Framework for Natural Gas Consumption Forecasting

A Novel Multiscale Transformer Network Framework for Natural Gas Consumption Forecasting

APPLICATION OF THE METHOD OF GROUP ARGUMENTS ACCOUNTING FOR BUILDING MODELS OF SHORT-TERM FORECASTING OF GAS CONSUMPTION BY THE POPULATION

Problem statement. One of the most important tasks in optimizing the operation modes of urban gas distribution systems is to develop a short-term strategy for such modes. Processing of planned and statistical indicators of gas consumption modes is one of the key methods for ensuring the optimal functioning and normal operation of gas supply systems. The most promising modeling method for solving forecasting problems is the method of self-organization of models implemented as the method of group arguments accounting (MGАA). Short-term forecasting of gas consumption is the main source of information for decision-making in the process of planning consumption regimes and operational dispatch control. The MGАA method, also known as the Ivakhnenko method, is a powerful tool for obtaining highly accurate forecasting models and is gaining importance for forecasting in energy resource management and planning their use. The solution to such a problem is relevant, as it makes it possible to analyze the volume of natural gas consumption by the population for the future period. The purpose of the article is to build mathematical models for forecasting gas consumption using the method of group arguments accounting based on input data. Conclusion. To select the best models the following parameters are recommended: tomorrow's gas consumption as a function (main criterion) and arguments (additional criterion) - gas consumption to date, air temperature to date, yesterday's temperature and temperatures for the past 3, 5, 7 days, wind speed and day of the week. The resulting mathematical models of natural gas consumption by the population can be used to analyze the volume of natural gas consumption. The method allows us to find a single optimal mathematical model that best solves the problem.

Replacing Gray Hydrogen with Renewable Hydrogen at the Consumption Location Using the Example of the Existing Fertilizer Plant

The production and use of hydrogen are encouraged by the European Union through Delegated Acts, especially in sectors that are difficult to decarbonize, such as the industrial and transport sectors. This study analyzes the possibility of partial decarbonization of the existing plant in the petrochemical industry, with a partial transition from natural gas to renewable hydrogen, as a precursor to the adoption of the hydrogen economy by 2050. This study was based on the example of a plant from the petrochemical industry, namely an existing fertilizer plant. Namely, in the petrochemical industry, hydrogen is produced by steam-reforming natural gas, which is needed in the process of producing ammonia, one of the basic raw materials for mineral fertilizers. By building an electrolyzer at the location of the existing fertilizer plant, it is possible to obtain renewable hydrogen, which enters the ammonia production process as a raw material. The electricity from which hydrogen is produced in the electrolyzer is provided through Power Purchase Agreement contracts concluded with electricity producers from 12 wind power plants. The results of this study show that the production of renewable hydrogen at the location of the analyzed plant is not profitable, but due to the specificity of the process of such an industry, the high consumption of natural gas, and large savings in CO2 emissions which can be achieved by the production of renewable hydrogen, investment is needed. With a 370 MW electrolyzer, about 31,000 tons of renewable hydrogen is produced, which represents about 50% of the hydrogen needs of the analyzed plant. By producing renewable hydrogen for part of the needs of the analyzed plant, a saving of about 300,000 tons of CO2 emissions is achieved in relation to the production of gray hydrogen, which contributes to the partial decarbonization of the analyzed plant. The authors are aware that the current market opportunities do not allow the profitability of the investment without subsidies, but with the advancement of technology and a different price ratio of electricity, natural gas, and CO2 emissions, they believe that such investments will be profitable even without subsidies.

Hydrogen Blending in Natural Gas Grid: Energy, Environmental, and Economic Implications in the Residential Sector

The forthcoming implementation of national policies towards hydrogen blending into the natural gas grid will affect the technical and economic parameters that must be taken into account in the design of building heating systems. This study evaluates the implications of using hydrogen-enriched natural gas (H2NG) blends in condensing boilers and Gas Adsorption Heat Pumps (GAHPs) in a residential building in Rome, Italy. The analysis considers several parameters, including non-renewable primary energy consumption, CO2 emissions, Levelized Cost of Heat (LCOH), and Carbon Abatement Cost (CAC). The results show that a 30% hydrogen blend achieves a primary energy consumption reduction of 12.05% and 11.19% in boilers and GAHPs, respectively. The presence of hydrogen in the mixture exerts a more pronounced influence on the reduction in fossil primary energy and CO2 emissions in condensing boilers, as it enhances combustion efficiency. The GAHP system turns out to be more cost-effective due to its higher efficiency. At current hydrogen costs, the LCOH of both technologies increases as the volume fraction of hydrogen increases. The forthcoming cost reduction in hydrogen will reduce the LCOH and the decarbonization cost for both technologies. At low hydrogen prices, the CAC for boilers is lower than for GAHPs; therefore, replacing boilers with other gas technologies rather than electric heat pumps increases the risk of creating stranded assets. In conclusion, blending hydrogen into the gas grid can be a useful policy to reduce emissions from the overall natural gas consumption during the process of end-use electrification, while stimulating the development of a hydrogen economy.

An experimentally validated model for a multivariate drying industrial process

Modeling of industrial production processes is becoming increasingly challenging due to their large number of variables. These variables often are highly correlated and introduce nonlinear and complex features. In this paper, we are interested to model an industrial dicalcium phosphate (DCP) drying process. Attempting to solve this issue is motivated by the need to improve several production conditions, such as minimizing the consumption of natural gas and reducing the pollution rate. In fact, applying an advanced control approach requires a dynamic model for the monitored plant. This work proposes a multivariable mathematical model for the DCP dryer within the Tunisian Chemical Group factory. A steady-state model has been reproduced using Aspen Plus software tool to implement the different functionalities of the system as well as involved reactions. Indeed, since the main operation in the drying process is the combustion reaction of the liquified petroleum gas (LPG) in the furnace that produce the necessary heat to reach a target value of temperature at the dryer outlet, we focus on determining a dynamic model for the furnace. To do so, we have proposed two approaches. The first is based on the Aspen dynamic tool. The second is based on the left matrix fraction description (LMFD) identification approach. The obtained results have been successfully validated using real measurements.

Evaluating hybrid nuclear-thermal power systems for reduced carbon footprint: A comparative analysis

The article provides an estimated substantiation of the concept of expanding the fuel and energy base and reducing the volume of greenhouse gas emissions with the joint use of organic and nuclear fuel in the structure of hybrid nuclear-thermal power plants. It is shown that the technological scheme (the production of saturated steam in a nuclear steam-producing plant - NPPU, and then overheating to the maximum achieved parameters in the thermal power industry due to organic fuel) leads to a decrease in the specific consumption of gas fuel for the production of electrical energy by 25–30 %, emissions of combustion products by 2.5 times (compared to thermal power plants), consumption of industrial water (compared to nuclear power plants) - by 1.5 times. It is indicated that it is possible to expand the fuel base of modern nuclear energy with thermal neutron reactors through the use of technologies mastered (breeder reactors) and promising (hybrid thermonuclear reactors). The fundamental advantage of the considered complex - JPPP-TPP - its feasibility in a short period of time with a significant reduction in the carbon footprint per unit of energy produced, which is an important condition for the sustainable growth of energy production while maintaining the ecological balance in the geosphere.

Effect of complex ionic liquid additives on the formation kinetics and separation efficiency of binary gas mixture hydrates

Rising carbon emissions worldwide have necessitated the discovery of efficient CO2 separation and capture technologies. Owing to their good CO2 selectivity, imidazolium-based ionic liquids (ILs) have been used as additives in hydrate-based gas separation (HBGS) technologies. Sodium dodecyl sulfate (SDS) can notably improve the rate of hydrate formation when used as a surfactant. However, the synergistic effect of imidazolium-based ILs and SDS remains unknown. This study aimed at investigating the synergistic effect of imidazolium-based ILs and SDS on the hydrate formation kinetics of binary gas mixtures of CO2/N2 at different temperatures. The carbon capture and storage capacity was determined, and HBGS was evaluated using pure imidazolium-based IL 1-butyl-3-methylimidazolium octyl sulfate ([BMIM] [OS]) and composites of IL and SDS as additives. Compared with pure water, [BMIM] [OS] effectively promoted gas hydrate formation and increased CO2 consumption by 107.9 %. The maximum CO2 separation factor was obtained at 273.15 K, and the mixed additive significantly enhanced gas consumption by 11.1 %. X-ray diffraction and Raman spectroscopy analysis indicated that the hydrate samples were type I structural hydrates and that [BMIM] [OS] improved the mass transfer process. The results of this study provide a theoretical basis for CO2 gas separation and capture.