Shah‐Al Emran, Bryan M. Petersen, Heather Elizabeth Roney
et al.
ABSTRACT The cultivation of sterile giant miscanthus (Miscanthus × giganteus, M × g) for bioenergy and bioproducts has expanded into grain‐cropped land in the United States (US) as local markets developed for this high‐yielding perennial grass (10–30 Mg DM ha−1). However, the magnitude of spatial and temporal variability in yield within US Corn Belt fields, along with impacts on economic return and sustainable land management, is poorly understood. This study established a diagnostic model relating remote sensing‐derived vegetation indices to ground truth data from 105 hand‐harvested stem biomass samples, which were strategically selected to represent the full range of vegetation index observations. The high‐resolution satellite‐sensed vegetation indices captured > 90% of the yield variation measured within fields. This model was then used to predict yield variability and assess economic performance across four of the first commercial M × g fields in the Corn Belt state of Iowa, US. Significant spatial variability in biomass dry matter (DM) yields (9.3–18.1 Mg DM ha−1) and net profits ($83 to $1211.5 ha−1) was observed. All fields were profitable in all site‐years. When low profit occurred, it was explained by limited management experience of the crop in Iowa. The breakeven yield at a selling price of $130 Mg−1 varied from 9.0–12.1 Mg ha−1 at 15% moisture content (7.6–10.3 Mg DM ha−1). Breakeven prices ranged from $73 to $122.4 Mg−1, matching ranges used in the Department of Energy Billion Ton Report (US Department of Energy, 2023). Notably, M × g yield and profits were commensurate with grain crops particularly with favorable precipitation. This study provides insight on the M × g management “learning curve”, performance on marginal land and in drought conditions, and demonstrates that addressing yield gaps, reducing costs, and implementing precision agriculture strategies can enhance profitability. These findings emphasize the value of remote sensing technologies in guiding sustainable and competitive commercial‐scale M × g production.
Renewable energy sources, Energy industries. Energy policy. Fuel trade
[Objective] Under the guidance of the "dual carbon" strategy, China's offshore wind power installed capacity continues to grow. Based on the analysis and summary of the design process of a wind turbine jacket foundation at an offshore deepwater site, which is typical for the 2024 offshore wind power competitive allocation, the paper summarizes the dimension optimization strategies of jacket foundation. The explicit, process-oriented and digitalized knowledge of design strategy is conducive to technology precipitation and the development of automated design tools. [Method] By analyzing the pilehead configuration of jacket in the pre-pile design, the discrete grouping principle of water depth vs pilehead elevation is determined. The optimum flow of pile diameter under a given footprint is defined by sorting out the relevant design codes of pile foundation bearing capacity and grouting connection design. According to the assembly characteristics of jacket structure, the dimension driving parameters were merged, the optimization boundary conditions were identified, and the optimization strategies were formulated. [Result] The research shows that the grouping according to the water depth is beneficial to control the number of jacket models. The pile diameter optimization should be carried out before the footprint optimization, according to the sequence of frequency-grouting connection-pile length design. The minimum independent dimension variable set is proposed and the optimization process storage matrix is constructed. [Conclusion] When the driving depth of steel piles is restricted, the bearing capacity envelope principle should be adopted, otherwise the sand proportion moment envelope principle should be adopted. Pile diameter optimization is a problem of optimizing the overall steel consumption of grouting legs and steel piles under the restrictions of the overall frequency, grouting axial force & bending moment bearing capacity and axial pile foundation bearing capacity. The cross section optimization of the member should be based on the minimum independent size variable group and be constrained by the configuration requirements. The outer diameter should be optimized first, and the optimization triggering condition, oscillation suppression mechanism and iteration exit condition should be set.
Sudarshan L. Chavan, Manjusha A. Kanawade, Rahul S. Ankushe
ABSTRACT: The increasing demand for clean transportation has propelled research and development in electric vehicles (EVs), with a crucial focus on enhancing battery technologies. This paper presents a novel approach to a battery management system by implementing a passive cell balancing system for lithium-ion battery packs. The proposed system employs a proportional-integral (PI) controller to address voltage imbalances among individual cells, aiming to improve battery life and longevity without the need for a complex active control circuit. The study explores performance evaluation under diverse conditions, considering factors such as system capacity retention, energy efficiency, and overall reliability. Safety and thermal management considerations play a crucial role in the implementation, ensuring the longevity and stability of the lithium-ion battery pack. The primary objective of this research is to extend the operational life of lithium-ion batteries, reduce maintenance costs associated with battery management, and contribute to sustainable energy solutions. In the presented study, first, a Simulation model is developed in MATLAB, and the results are verified by implementing a hardware model.
Energy industries. Energy policy. Fuel trade, Renewable energy sources
This study examines the relationship between energy transition and government debt in 15 developing countries using a dynamic generalized method of moments (GMM) estimation backed by a theoretical background. Results show that government debt is highly persistent, with past debt strongly influencing current levels, consistent with path dependency theory. An increased share of renewable energy in the energy basket modestly reduces government debt by lowering energy import costs and reducing long-term fiscal burdens from environmental and health-related expenses. The study recommends developing green finance markets, improving digital access, attracting green FDI, and establishing local renewable energy plants to reduce energy imports and promote sustainable growth.
Abstract Natural gas hydrates (NGHs) offer significant potential for energy recovery and carbon sequestration, yet the thermal stability of polycrystalline CH4-CO2 hydrates (PCCHs) which is critical for CO2-based NGH exploitation, remains poorly understood. Here, we unravel CO2’s role in reshaping the thermal dissociation behaviors of PCCHs via high-throughput molecular dynamics (MD) simulations and machine learning (ML). We demonstrate that CO2 reduces the stability of PCCHs, with a 20% increase in CO2 concentration lowering the melting point by approximately 6 K. Microstructural analysis reveals that this destabilization arises from CO2-induced distortion of 512 cage and formation of unconventional metastable cages. Thermal dissociation occurs via cage transformations and dissociations, where 4151062 and 51262 cages act as hubs for solid–solid restructuring pathway. Crucially, CH4 guest molecules facilitate simpler, faster cage transformations than CO2, which requires complex rearrangements. We further develop a GBDT ML model that accurately predicts PCCH melting points using microstructural information, identifying 512, 51262, and 51063 cages as key predictors. This model provides a practical tool for guiding CO2-based NGH exploitation and designing hydrate storage systems. These insights advance the molecular-level understanding of hydrate stability for CO2 sequestration and NGH recovery. Graphical Abstract
Energy industries. Energy policy. Fuel trade, Renewable energy sources
The Chinese new energy vehicle (NEV) industry has developed rapidly, which has become one of the largest NEV markets in the world. The Chinese government has played a pivotal role in supporting and promoting the NEV industry, leading to significant advancements in policies, technology, infrastructure, industrial chain, and market development. This support has been evident through the implementation of numerous favorable policies, including increased support in finance, taxation, and technology innovation, as well as initiatives to promote research, development, and application of NEV products. Furthermore, subsidy policies have been introduced to incentivize consumers to purchase NEVs and enhance their competitiveness in the market. Additionally, regulations mandating a certain proportion of NEV production and sales for automakers have been put in place, contributing to the widespread advancement of the Chinese NEV industry. While the Chinese NEV industry has seen substantial growth, it also faces challenges and opportunities. To further its development, it is essential for vehicle manufacturers to prioritize technological innovation, the government to continue introducing supportive policies, users to increase environmental awareness, and for collaboration between academia and industry to drive research efforts. The development of the Chinese NEV industry is not only in line with the global trend of environmental protection, energy security, and industrial transformation, but also an important link in promoting the progress of the global NEV industry.
Renewable energy sources, Energy industries. Energy policy. Fuel trade
The pressing global challenge of climate change necessitates a concerted effort to limit greenhouse gas emissions, particularly carbon dioxide. A critical pathway is to replace fossil fuel sources by electrification, including transportation. While electrification of light-duty vehicles is rapidly expanding, the heavy-duty vehicle sector is subject to challenges, notably the logistical drawbacks of the size and weight of high-capacity batteries required for range, as well as the time for battery charging. This Perspective highlights the potential of hydrogen fuel-cell vehicles as a viable alternative for heavy-duty road transportation. We evaluate the implications of hydrogen integration into the freight economy, energy dynamics, and CO2 mitigation, and envision a roadmap for a holistic energy transition.Our critical opinion presented in this Perspective is that federal incentives to produce hydrogen could foster growth in the nascent hydrogen economy. The pathway that we propose is that initial focus on operators of large fleets that could control their own fueling infrastructure. This opinion was formed from private discussions with numerous stakeholders during the formation of one of the awarded hydrogen hubs if they focus on early adopters that could leverage the hydrogen supply chain.
The power grid, as the hub connecting the power supply and consumption sides, plays an important role in achieving carbon neutrality in China. In emerging carbon markets, assessing the investment benefits of power-grid enterprises is essential. Thus, studying the impact of the carbon market on the investment and operation of power- grid enterprises is key to ensuring their efficient operation. Notably, few studies have examined the interaction between the carbon and electricity markets using system dynamics models, highlighting a research gap in this area. This study investigates the impact of the carbon market on the investment of power-grid enterprises using a novel evaluation system based on a system dynamics model that considers carbon-emissions from an established carbon-emission accounting model. First, an index system for benefit evaluation was constructed from six aspects: financing ability, economic benefit, reliability, social responsibility, user satisfaction, and carbon-emissions. A system dynamics model was then developed to reflect the causal feedback relationship between the impact of the carbon market on the investment and operation of power-grid enterprises. The simulation results of a provincial power-grid enterprise analyze comprehensive investment evaluation benefits over a 10-year period and the impact of carbon emissions on the investment and operation of power-grid enterprises. This study provides guidelines for the benign development of power-grid enterprises within the context of the carbon market.
Energy conservation, Energy industries. Energy policy. Fuel trade
Uz napredak elekroenergetskog sistema raste i njegova složenost, a samim tim i sve veća potreba za dobrom organizacijom proizvodnje i informacijama koje bi pomogle u planiranju. Kako su termoelektrane zadužene za pokriće baznog opterećenja predikcija proizvodnje termoelektrana se može znatno iskoristiti. Ovaj rad predstavlja upotrebu veštačkih neuralnih mreža za predikciju proizvodnje energije iz termoelektrana. Podaci koji su korišćeni za treniranje veštačke neuralne mreže su merenja proizvodnje energije iz termoelektrana u elektroenergetskom sistemu Srbije. Obučena neuralna mreže može da se koristi za predikciju proizvodnje na godišnjem nivou ili kraćim višednevnim ili dnevnim nivoima.
Energy industries. Energy policy. Fuel trade, Economics as a science
Chemical looping dry reforming of methane (CL-DRM) is a viable technology by converting CH4 and CO2 to various value-added products to achieve carbon neutrality. However, it is vital for the technology to find suitable oxygen carriers with high oxygen capacity and activity. La0.35Sr0.35Ba0.3Fe1-xCoxO3 perovskite-type oxides were proposed as oxygen carriers for CL-DRM. The oxygen (O2) release property and the kinetics of La0.35Sr0.35Ba0.3Fe1-xCoxO3 reduction by CH4 were investigated via thermogravimetric analysis, O2-temperature programmed desorption and then in a fixed-bed reactor. The O2 release process of La0.35Sr0.35Ba0.3Fe1-xCoxO3 OCs can be divided into two phases. The O2 release process and corresponding rate of OCs were facilitated due to the substitution of Fe with Co in B-site. The total amounts of O2 release for these OCs were enhanced about 1.5 times from 0.445 mmol/gOC to 0.706 mmol/gOC as Co atomic fraction in B-site changes from 0 to 1. The linear correlation for high temperature phase and a volcano-curve for low temperature phase was found for the correlations among total O2 release and Co content during the O2 release process. The reduction kinetics of CH4 over OCs was described using the Avrami–Erofe'ev model (A1.5 or A2). The values of apparent activation energy (Ea) for all OCs were obtained. The results indicated the best substitution proportion of Co in La0.35Sr0.35Ba0.3Fe1-xCoxO3 OCs can be set in the range of 0.2–0.4 to emerge the excellent redox performance. The kinetics models and parameters offer valuable information for CL-DRM reactor design and further development of OCs with different A or/and B-site modifications.
Fuel, Energy industries. Energy policy. Fuel trade
This study tries to explore empirically the nature of the link among energy consumption, environmental degradation, trade, industrialization, urbanization, and economic growth concerning the Kingdom of Saudi Arabia's economy for a time series of data spanning from 1971 to 2019. To investigate the cointegration, the long-run relationship, and to decide the direction of causality we apply the Autoregressive Distributed Lag and the Vector Error Correction Model technologies. Our empirical findings reveal that a rise in energy consumption and environmental degradation increases economic growth; however, energy has a significant contribution to the deteriorating environment. Besides, results show the presence of a feedback effect in the long-run among the different variables. In the short-run, energy use, trade, and urbanization, Granger causes economic growth; while growth, environment, industrialization, and urbanization Granger causes energy consumption. The Saudi policymakers must consider the leading role played by trade, urbanization, and industrialization in improving economic growth and harming environmental quality by launching efficient energy policies.
As in the whole world, renewable energies in Algeria, including photovoltaic energy, are attracting more and more attention in recent years. The integration of distributed generation (DG) into the power grid using renewable energy sources, such as PV, FC and wind, has important advantages such as low distribution losses, better continuity and power quality, and high system reliability. This paper is about a simulation study to analyze the energy assessment of a grid-connected photovoltaic system (GCPVS). The system with 1 MW capacity is simulated and analyzed based on solar resource, tilt and azimuth angles for each area and using Si-crystalline and CIS technologies under different weathers conditions in Algeria (Algiers, Chlef, Tlemcen, Tamanrasset and El Oued). The system configuration is simulated using the new version of PVGIS to account for PV plant energy output assessment. The obtained simulation results were discussed as per monthly and yearly values based on PV cell technologies and optimized tilt and azimuth angle.
Power system decarbonization is critical for combating climate change, and handling systems uncertainties is essential for designing robust renewable transition pathways. In this study, a bottom-up data-driven multistage adaptive robust optimization (MARO) framework is proposed to address the power systems’ renewable transition under uncertainty. To illustrate the applicability of the proposed framework, a case study for New York State is presented. Machine learning techniques, including a variational algorithm for Dirichlet process mixture model, principal component analysis, and kernel density estimation, are applied for constructing data-driven uncertainty sets, which are integrated into the proposed MARO framework to systematically handle uncertainty. The results show that the total renewable electricity transition costs under uncertainty are 21%-42% higher than deterministic planning, and the costs under the data-driven uncertainty sets are 2%-17% lower than the conventional uncertainty sets. By 2035, on-land wind and offshore wind would be the major power source for the deterministic planning case and robust optimization cases, respectively.