Different Types Of Energy Research Articles

Computational Exploration of Adsorption-Based Hydrogen Storage in Mg-Alkoxide Functionalized Covalent-Organic Frameworks (COFs): Force-Field and Machine Learning Models.

Hydrogen is a clean-burning fuel that can be converted to other forms. of energy without generating any greenhouse gases. Currently, hydrogen is stored either by compression to high pressure (>700 bar) or cryogenic cooling to liquid form (<23 K). Therefore, it is essential to develop safe, reliable, and energy-efficient storage technology that can store hydrogen at lower pressures and temperatures. In this work, we systematically designed 2902 Mg-alkoxide-functionalized covalent-organic frameworks (COFs) and performed high-throughput (HT) computational screening for hydrogen storage applications at 111, 231, and 296 K. To accurately model the interaction between Mg-alkoxide sites and molecular hydrogen, we performed MP2 calculations to compute the hydrogen binding energy for different types of functionalized models, and the data were subsequently used to fit modified-Morse force field (FF) parameters. Using the developed FF models, we conducted HT grand canonical Monte Carlo (GCMC) simulations to compute hydrogen uptakes for both original and functionalized COFs. The generated data were subsequently used to evaluate the materials' gravimetric and volumetric storage performance at various temperatures (111, 231, and 296 K). Finally, we developed machine learning (ML) models to predict the hydrogen storage performance of functionalized structures based on the features of the original structures. The developed model showed excellent performance with a mean absolute error (MAE) of 0.061 wt % and 0.456 g/L for predicting the gravimetric and volumetric deliverable capacities, enabling a quick evaluation of structures in a hypothetical COF database. The screening results demonstrated that the Mg-alkoxide functionalization yields greater improvements in volumetric H2 storage capacities for COFs with smaller pores compared to those with larger (mesoporous) pores.

Energy use and greenhouse gas emissions in selected tea factories in Kenya

Tea sector is a major contributor to Kenya’s economy through foreign exchange via export. However, extensive amount of energy is required to produce one kilogram of tea, making tea processing energy-intensive. Comparing greenhouse gas emissions from different types of energy consumed in tea factories is imperative to enable policymakers make informed intervention in emission reduction. Reducing greenhouse gas emissions in tea factories is one of the pathways to meeting Kenya’s nationally determined 32% reduction of carbon emissions by 2030 and commitment to the Paris Agreement. This paper assesses greenhouse gas emissions from different sources of energy used in four tea factories in Kenya. The Intergovernmental Panel on Climate Change emission factor is used to calculate the total emissions of each type of energy used for 5 years. Life cycle assessment using SimaPro 8 software, Eco-indicator 99 method and Eco invent database was used to assess the specific compound causing the emission. The findings reveal that the 5-year greenhouse gas emissions by biogas, solar, wood, briquettes, and electricity are 336.111, 7.108, 3057.729, and 1,338.28 kg CO2/MWh, respectively. Firewood has the highest concentration of carbon dioxide, while solar energy has the least. Analysis of variance confirms significant difference (0.05&gt;p = 0.0272) in greenhouse gas emissions from the different energy sources. Post-hoc analyses shows a significant difference in emissions between solar and firewood (p&lt;0.0125) and no significant difference between other sources of energy. The key environmental hotspot is the energy intensive processes such as drying involved in tea production and processing, which leads to consumption of fossil fuel in the factories. To reduce such key hotspot, switching to renewable energy sources is key. Sustainability in the tea sector can therefore be achieved through switching to macadamia briquettes as a source of thermal energy and a combination of electricity and solar for electrical energy.

Understanding energy transformation mechanism of rockbursts through experimental and theoretical methods

Understanding the energy transformation mechanism in rockbursts is essential for predicting and mitigating potentially catastrophic rock failures. In this study, Double Springs Release Tests (DSRTs) were proposed in a laboratory setting to investigate the energy transformation of rockbursts from inception to development. High-speed cameras and image processing algorithms were utilized to calculate different types of energy throughout the duration of the burst. Theoretical analyses, grounded in structural dynamics and stress wave equations, was conducted and cross-referenced with the experimental results. The study found that wave impedance ρE is a key indicator of burst intensity. The research demonstrated that the impact energy in DSRTs originates from both the impact medium and the surrounding medium, and explored how these two components contribute to the total impact energy of the impact medium.

Demand flexibility and its impact on a PEM fuel cell-based integrated energy supply system with humidity control

The development of efficient energy systems and renewable alternative energy sources has attracted substantial attention owing to the rise in environmental deterioration and energy usage. A combined cooling, heating, and power (CCHP) system can fully use different types of energy with low emissions and offers a viable solution to address these issues. Demand flexibility is a key issue in collaborating with different types of supplies and demands for optimal system operation. In this study, a proton-exchange membrane fuel cell driven CCHP system with humidity control is proposed to fully investigate the impact of demand flexibility on system operation. A novel flexible load regulation strategy was designed for the proposed system. The results show that flexible load regulation can reduce the thermal storage capacity by 25 %. Supplement heating and cooling do not need operate in winter and summer. With flexible regulation, the heating load can be reduced by 15.69 % in winter, and the cooling and dehumidification loads can be reduced by 30.71 % and 6.09 % in summer. The reductions in hydrogen consumption can reach 1.98 % and 7.51 % during winter and summer. The proposed method can simultaneously increase the exergy efficiency and reduce carbon emission, as well as the economy cost.

Public perceptions of fossil and alternative energy in Serbia: Between NIMBYism and nationalism

Understanding public perceptions of energy sources is essential for successful policy formulation. Our study explores the Serbian public's attitudes toward different types of energy, taking into account NIMBY (“Not In My Back Yard") sentiments, nationalist orientation, and pro-Russian attitudes. A correlational cross-sectional design utilized an online survey disseminated via social media platforms. The study examined public preferences for various energy types and their correlations with nationalist and pro-Russian tendencies. Poststratification weighting was applied to address sample representativeness. Our research revealed the public's preference for renewable energy, particularly solar and wind. Surprisingly, nationalist views did not significantly align with fossil fuel preferences, differentiating Serbia from Western European trends. Geopolitical considerations, such as Serbia's relationship with Russia, did not strongly influence public opinion. These findings underscore the importance of considering public preferences in shaping Serbia's energy policy, emphasizing the need for investment in renewables. Based on the results we offer concrete policy recommendations. This study offers a methodological approach adaptable to other countries undergoing similar energy transition.

Timescale correlation of shallow trap states increases electrochemiluminescence efficiency in carbon nitrides

Highly efficient interconversion of different types of energy plays a crucial role in both science and technology. Among them, electrochemiluminescence, an emission of light excited by electrochemical reactions, has drawn attention as a powerful tool for bioassays. Nonetheless, the large differences in timescale among diverse charge-transfer pathways from picoseconds to seconds significantly limit the electrochemiluminescence efficiency and hamper their broad applications. Here, we report a timescale coordination strategy to improve the electrochemiluminescence efficiency of carbon nitrides by engineering shallow electron trap states via Au-N bond functionalization. Quantitative electrochemiluminescence kinetics measurements and theoretic calculations jointly disclose that Au-N bonds endow shallow electron trap states, which coordinate the timescale of the fast electron transfer in the bulk emitter and the slow redox reaction of co-reagent at diffusion layers. The shallow electron trap states ultimately accelerate the rate and kinetics of emissive electron-hole recombination, setting a new cathodic electrochemiluminescence efficiency record of carbon nitrides, and empowering a visual electrochemiluminescence sensor for nitrite ion, a typical environmental contaminant, with superior detection range and limit.

THE SIMULATION AND PARAMETRIZATION OF THE LATERAL DISTRIBUTION FUNCTION IN EAS AT ULTRA HIGH ENERGIES

To characterize the features of EASs, this study used the AIRES simulation tool (Version 19.04.0) to estimate the lateral distribution function (LDF) at very high energies of different types of cosmic ray particles. An array of zenith angles spanning from 1018 to 1020 eV was used for the proton and iron primary simulations. The EASs's LDF curves are fitted with new coefficients for various primary particles and zenith angles using a polynomial fit, and these coefficients are applicable to the energy range described before. The findings of the simulation were compared with actual data from the Yakutsk EAS array, which showed decent agreement for proton and iron at 1019 eV for angled showers at θ=10ˢ.

Analyzing the Effects of Renewable and Non-renewable Energy Consumption on the Environment and Economic Growth: Panel Data from South Asian Countries

&lt;p class="MsoNormal" style="margin-top: 12pt; text-align: justify;"&gt;&lt;span lang="EN-US" style="font-family: 'times new roman', times, serif; font-size: 14pt;"&gt;The primary goal of this research is to examine how different types of energy are used in South Asian countries and how they affect the environment and economic growth. From 1990 through 2021, this research employed Panel Data from multiple sources covering the South Asian countries of Pakistan, India, Bangladesh, Sri Lanka, Nepal, Bhutan, Maldives, and Afghanistan. The results are determined by using the Fixed Effect Regression (FEM) technique in both models. Several significant findings are supported by the data. First, while using renewable energy flattens carbon dioxide effusion, using non-renewable energy sources increases it. CO2 emissions are affected negatively by gross domestic product but positively by gross domestic product square. These results provide credence to the idea that South Asian countries do experience an Environment Kuznets Curve. Furthermore, foreign direct investment has a beneficial effect on CO2 emissions, lending credence to the Pollution Haven Hypothesis. Model 2 instead finds that both renewable and non-renewable energy consumption contributes to economic expansion. Gross Fixed Capital Formation and foreign direct investment also contribute to economic growth in this area. Finally, Inflation retards economic expansion.&lt;/span&gt;&lt;/p&gt;

Solar Energy’s Importance and Role in Advancing Society

The nation is facing energy crisis at faster rate. To meet this crisis, it is the prime need of the day to seek out an alternative source of energy. Conventional and non-conventional are the two sources for obtaining different types of energy. The conventional sources are fossil fuels such as gases, oils, coals, woods etc. and non-conventional sources are wind, bio-mass, ocean tides, geothermal and solar energy. More attempts are being applied to harness the solar energy by different technologies. This energy is available in vast amount and nonpolluting and harmless to the common creatures. The amount of solar energy received on the earth per sec is 1.353 KW/m2. This energy is converted into electrical energy by using dry and wet solar cells. The present paper deals with the characteristics of the solar cell which is the major candidate for converting solar energy.

Determinants of the Behavior of Households in Ouagadougou Regarding the Choice of Cooking Energy

The Burkinabe energy context is characterized by a predominance of the use of biomass energies, the country's dependence on fossil fuels, low and inequitable access to modern energies and very low valorization of endogenous renewable energies. Households use these different types of energy for cooking, heating food and heating water. The choice of these energies depends on several criteria. The analysis of the characteristics which can influence this choice is based on the discrete choice model resulting from the hypothesis of utility maximization behavior of the economic agent. This analysis reveals that certain household characteristics including household size, high income and the level of education of the head of household have an effect on energy choice although it is weak. The environmental criterion has no effect on the choice of households and the observation is that the choice of households is mainly based on their desire for comfort. The environmental reason is rarely mentioned. Given the weakness of the vegetation cover in the country, it would be appropriate to intensify the supervision of the wood sector, to strengthen the actions already undertaken (reduction of wood consumption, promotion of energy alternatives, safeguarding and restoration of forests) and the capacities of the actors and finally placed great emphasis on the need to provide quality education to raise popular awareness of environmental issues.

The effect of RAP content on fatigue damage property of hot reclaimed asphalt mixtures.

The fatigue property of the recycled mixture affects the structural design of recycled pavement. In order to explore the effect of different reclaimed asphalt pavement (RAP) content on the fatigue properties of recycled mixtures, the fatigue properties of recycled mixtures were analyzed through an indoor fatigue test and finite element numerical simulation. Based on the phenomenological method and the dissipated energy theory, the fatigue properties of recycled mixtures with different RAP contents were analyzed and the fatigue damage of the mixtures were also studies under various strain levels. Based on the finite element numerical model of fatigue damage, the stress distribution and internal damage field distribution of trabecular specimens under different temperatures, strain levels and RAP contents were analyzed. The results showed that the anti-fatigue level of the mixture decreased as the RAP content was increased. The relative change rate of dissipated energy for different types of mixtures showed a two-stage change rule with the change of load times, that is, the value is large and decreasing, and the value is small and stable. The correlation between the plateau value (PV) and the fatigue life was established under the double logarithm coordinates, which could better analyze the influence law of the RAP content on the fatigue performance of the recycled mixture. Under different temperatures, strain levels, and RAP contents, the stress at the bottom of trabecular specimen and the overall damage field were mainly generated at the upper part under compressive stress and the bottom under tensile stress, and the damage field distribution area accounted for a small part of the whole specimen. According to the test results and fatigue damage distribution, it is recommended that the content of recycled aggregate in recycled asphalt mixtures be less than 30% to ensure good performance. The research results have important practical significance for the improvement of fatigue performance and engineering application of recycled mixtures.

КОНТРОЛЬ И УПРАВЛЕНИЕ ЭНЕРГОПОТРЕБЛЕНИЕМ ПРИ ЗАЩИТЕ ОБЪЕКТОВ АПК ОТ ВРЕДИТЕЛЕЙ

The analysis of the modern safety of crop production and protection of crops from pests is carried out. The advantages of the electrophysical control method and the need to create an effective crop protection system from pests are substantiated. The use of an integrated plant protection system based on an information and software package for monitoring and evaluating the effectiveness of plant protection against pests is proposed. The method of control and management in energy technological processes is considered. An expression has been obtained that allows you to define a resource. The article presents a new method for analyzing energy processes in each technical element and in the entire consumer energy system, which allows you to take into account the spatial structure created by the elements, enter into analysis and calculations digital indicators separating useful energy and losses, and assess the impact of this separation on the profitability of the enterprise. The novelty of the problem solved in the article lies in the fact that there are no established methods for monitoring and managing the efficiency of energy use by the consumer. This methodological gap is not taken into account when designing an enterprise (when choosing equipment), since equipment is selected by capacity, and the energy consumed then determines efficiency in the form of energy intensity of products that do not emit used energy. The method presented in the article is based on the separation of consumed and used energy, on the allocation of technological energy processes that use energy with a given technological efficiency, and on the use of fundamental knowledge for process analysis. These methodological techniques made it possible to obtain the energy intensity of products in the form of the sum of two digital indicators — an effective indicator and an indicator of an increase due to losses. The decrease in the second indicator turns the problem of increasing energy efficiency into a complex task of energy services at the enterprise. The complexity for the agro-industrial complex is explained by the work with biological objects, the use of stationary and mobile technologies, the use of fundamentally different types of energy (anthropogenic, photonic and fuel), the creation and maintenance of fundamentally different production facilities (fields and farms), which the seasonality of work cannot calm.

Analyzing the Effects of Renewable and Non-renewable Energy Consumption on the Environment and Economic Growth: Panel Data from South Asian Countries

&lt;p class="MsoNormal" style="margin-top: 12pt; text-align: justify;"&gt;&lt;span lang="EN-US" style="font-family: 'times new roman', times, serif; font-size: 14pt;"&gt;The primary goal of this research is to examine how different types of energy are used in South Asian countries and how they affect the environment and economic growth. From 1990 through 2021, this research employed Panel Data from multiple sources covering the South Asian countries of Pakistan, India, Bangladesh, Sri Lanka, Nepal, Bhutan, Maldives, and Afghanistan. The results are determined by using the Fixed Effect Regression (FEM) technique in both models. Several significant findings are supported by the data. First, while using renewable energy flattens carbon dioxide effusion, using non-renewable energy sources increases it. CO2 emissions are affected negatively by gross domestic product but positively by gross domestic product square. These results provide credence to the idea that South Asian countries do experience an Environment Kuznets Curve. Furthermore, foreign direct investment has a beneficial effect on CO2 emissions, lending credence to the Pollution Haven Hypothesis. Model 2 instead finds that both renewable and non-renewable energy consumption contributes to economic expansion. Gross Fixed Capital Formation and foreign direct investment also contribute to economic growth in this area. Finally, Inflation retards economic expansion.&lt;/span&gt;&lt;/p&gt;

Ion Trapping and Thermionic Emission across Sub-nm Pores.

Ionic transport through a graphene biomimetic subnanometer (sub-nm) pore of arbitrary shape and realistically decorated by intrinsic negatively charged sites is investigated by all-atom molecular dynamics (MD) simulations. In the presence of external electric fields, cation trapping-assisted translocation occurs in the vicinity of the 2D subnanometer pore, while the anion current is blocked by the negative charges. The adsorbed cations in such asymmetrically charged nanopores are located on the top of the nanopore instead of blocking the pore, as suggested previously in highly symmetric pores such as crown ethers. Our analysis of the different types of energy involved in ion translocations indicates that electrostatics is the dominant factor controlling ion transfer across these sub-nm pores. A physical model based on the thermionic emission formalism to account for the free energy barriers to ion flow reproduces the I-V characteristics.

Fuzzy semi-entropy based downside risk to low-carbon oriented multi-energy dispatch considering multiple dependent uncertainties

Increasing deployment of wind power into integrated energy system becomes a critical pathway for deep decarbonizing the power sector. It is imperative to investigate the impacts of uncertain wind power on integrated power system as the result of the heavy interdependencies among different types of energy in supplying the requirements of economy, low carbon and risk aversion. Here, the concept of fuzzy semi-entropy is presented to quantify the downside risk of uncertain wind power. After that, a mean-semi-entropy model for low-carbon oriented electrical-gas-heat energy system including carbon emission, carbon capture and carbon trading is proposed. In particular, the dependence of wind power outputs from different wind turbines is investigated by the multivariate Gaussian Copula. Results obtained from case studies demonstrate the feasibility of the proposed model in achieving a balanced trade-off among system economy, low carbon emission and operation risk properly. The proposed model enables the reduction in total cost and carbon emission by 2.29% and 5.18% in comparison to these of traditional cost minimization model. In addition, the accommodation level of wind power with multivariate Gaussian Copula improves by 2.17% compared to that without considering coupling.

Energy trade stability of China: Policy options with increasing climate risks

As the world's largest importer of energy, China has been facing severe energy security issues. In the context of the challenges of global energy transformation brought about by climate change and the intensification of global political risks, a survival analysis approach is used in this paper to investigate China's energy trade stability. The results show that the energy trade linkages between China and 153 other countries are complex and unstable, featuring short periods of trade with many countries. Specifically, geopolitical riskier areas, such as the Middle East and Africa, have the lowest trade stability. The survival curves also demonstrate clear heterogeneity among different types of energy. Climate risks, including both physical and transitional risks, are found to have significant effects on energy trade stability. Finally, several policy options are proposed to improve energy trade stability in China, paying special attention to the increasing globe climate risks.

Heterogeneity of the impact of energy production and consumption on national greenhouse gas emissions

This research investigates the relationship between greenhouse gas (GHG) emissions and energy production and consumption patterns in 122 countries over the period from 1990 to 2020. Particular attention is paid to the role of different types of energy, including renewable, hydro and nuclear energy, as well as oil, gas and coal, in shaping GHG emissions. Unlike previous studies, the paper analyzes the full range of energy resources and focuses on different quantiles of data using the quantile-quantile regression (QQR) method. The results of this approach are compared with traditional quantile regression (QR) to assess its validity. Among the findings of this study are: (1) different parts of the energy mix have a heterogeneous impact on GHG emissions in different quantiles; (2) energy consumption patterns play a more significant role in shaping GHG emissions than production patterns; (3) increasing production and consumption of fossil fuels does not necessarily increase GHG emissions; (4) similarly, the development of renewable energy sources is not always accompanied by a reduction in GHG emissions. Our general conclusion is that existing climate policy requires significant diversification to not be focused only on renewable energy, which impact on GHG emissions is not as homogeneous as it usually considered, and which cannot solve the problem of raising emissions solely. Instead of this, it could be more rational to focus on the searching the ways of hydrocarbon industries sustainable development and support them in this journey, especially in the field of Scope 2 and Scope 3 operations management.

Verifiable proofs for the energy supply chain: small proofs brings you a long way

We describe a solution for secure and verifiable handling of energy certificates. Such certificates are increasingly used to claim and prove responsible use of green energy, and there is a strong need for transparency and public verifiability. While the proposed solution is designed for handling electricity it applies to different types of energy as well and the concepts may also be applied to other domains. Transmission System Operators are trusted to record consumption and production of electricity. The movement from volume-based MWh yearly certificates to spot-market aligned hourly or 15 min time-volume based intervals, creates challenges in relation to handling large amounts of data and subsequent transactions. Small discrete intervals gives the certification increased accuracy of energy consumption, as a means to prevent greenwashing, with the cost of higher amounts of transactional data and complexity. To ensure trust in the certification, these certificates must in addition be unique and publicly verifiable. This paper describes how blockchain technology can be used to create the required transparency and public verifiability. We show how large amounts of data can be efficiently handled on blockchains and how confidential data such as the amount of used energy in the certificates can be protected, ensuring privacy and correctness of the certificates.

Collaborative capacity planning method of wind-photovoltaic-storage equipment in microgrids considering different energy selling incomes

A microgrid is a promising small-scale power generation and distribution system. The selling prices of wind turbine equipment (WT), photovoltaic generation equipment (PV), and battery energy storage equipment (BES) have a significant impact on microgrid profits, which, in turn, affects the planning capacity of renewable energy. However, existing research has not yet conducted in-depth modeling and analysis for different kinds of energy generation electricity prices. This paper proposes an optimal capacity planning method for wind-photovoltaic-storage equipment, considering different energy selling incomes in microgrids. Stochastic characteristics of renewable energy (WT and PV), selling prices of different types of energy, and timing coupling characteristic are considered in the proposed model. In addition, the configuration capacities of WT, PV, and BES are modeled as discrete decision variables, according to the type of specific equipment. The comprehensive life cycle cost (LCC) is considered an objective function. It can be found that the proposed collaborative capacity planning model is a mathematical programming problem with complex nonlinear constraints and integer variables. To solve this problem, a cultural gray wolf optimization algorithm (CGWO) is applied in this paper. The proposed method’s efficiency, convergence, superiority, and effectiveness are verified through a case study. Moreover, the impact of different new energy sales prices on capacity planning results is also revealed in the article.

Nuclear Energy, Economic Growth, and the Environment: Optimal policies in a model with endogenous technical change and environmental constraints

We use a model of endogenous growth with vertical innovations, in order to derive optimal energy policy under uncertainty. Innovation can be directed to dirty, green, or nuclear technologies, which in turn can be used to produce different types of energy. We show that, nuclear energy usage, is not only a necessary welfare maximizing condition, but also a crucial determinant of economic growth in the long run. Lastly, we find no evidence supporting the traditional Environmental Kuznets Curve hypothesis under optimal policy implementation.