Energy Demand Research Articles

High‐Throughput Screening Technologies of Efficient Catalysts for the Ammonia Economy

AbstractDriven by the growing global demand for sustainable energy, ammonia is gaining recognition as a crucial energy carrier with the potential for widespread manufacturing. This has spurred the emergence of a “sustainable ammonia economy”. Efficient catalyst development is paramount to achieving this purpose. Although the traditional trial‐and‐error methods have led to substantial progress, they are inherently time‐consuming. In recent years, high‐throughput screening strategies are revolutionizing catalyst discovery, offering an efficient and cost‐effective approach for identifying high‐performance catalysts across various processes within the ammonia economy. This review explores recent advancements in these rapid catalyst screening techniques for ammonia‐based processes. By outlining the general screening principles and the key steps involved in the computational analysis of catalysts relevant to different stages of the ammonia economy, this review aims to provide fundamental insights for the development of novel catalysts using these accelerated methods.

Prioritizing Energy Performance Improvement Factors for Senior Centers Based on Building Energy Simulation and Economic Feasibility

This study examined energy performance improvement factors by analyzing both energy performance and the economic impacts to reduce energy costs for senior centers. A fact-finding survey was conducted on 20 senior centers in a metropolitan area, identifying key energy improvement factors. Energy simulations of the buildings were performed using ECO2, an officially certified energy assessment program in Korea, comparing the energy requirements before and after the improvements. The energy demand, energy consumption, and floor area were analyzed, with the J, K, and S standard models selected based on the median values of these factors. To assess the impact of the improvements, blower door tests were conducted on two senior centers before and after window upgrades. Based on the ECO2 simulations and the blower door test results, improvement priorities were identified in the following order: windows, exterior walls, boilers, roofs, and doors. Finally, an economic feasibility analysis applied the construction and heating costs to the standard models. Over a 40-year period, only boiler improvements generated a net profit. Without government support, this study recommends prioritizing boiler upgrades when selecting energy performance improvements.

Empirical insights into India’s energy demand: unveiling elasticity dynamics for strategic policy initiatives

Empirical insights into India’s energy demand: unveiling elasticity dynamics for strategic policy initiatives

Vehicle-To-Grid (V2G) Charging and Discharging Strategies of an Integrated Supply–Demand Mechanism and User Behavior: A Recurrent Proximal Policy Optimization Approach

With the increasing global demand for renewable energy and heightened environmental awareness, electric vehicles (EVs) are rapidly becoming a popular clean and efficient mode of transportation. However, the widespread adoption of EVs has presented several challenges, such as the lagging development of charging infrastructure, the impact on the power grid, and the dynamic changes in user charging behavior. To address these issues, this paper first proposes a vehicle-to-grid (V2G) optimization framework that responds to regional dynamic pricing. It also considers power balancing in charging and discharging stations when a large number of EVs are involved in scheduling, with the aim of maximizing the benefits for EV owners. Next, by leveraging the interaction between environmental states and the dynamic behavior of EVs, we design an optimization algorithm that combines the recurrent proximal policy optimization (RPPO) algorithm and long short-term memory (LSTM) networks. This approach enhances system convergence and improves grid stability while maximizing benefits for EV owners. Finally, a simulation platform is used to validate the practical application of the RPPO algorithm in optimizing V2G and grid-to-vehicle (G2V) charging strategies, providing significant theoretical foundations and technical support for the development of smart grids and sustainable transportation systems.

Thermal performance analysis of the novel medium-depth borehole heat exchanger (MDBHE) coupled photovoltaic photothermal (PV/T) heat pump domestic hot water supply system

ABSTRACT As global energy demand continues to rise and traditional energy sources increasingly fail to meet sustainability targets, conventional domestic hot water systems that rely exclusively on either geothermal or solar energy face inefficiencies and seasonal limitations. To tackle these issues, this study introduces an innovative domestic hot water supply system combining MDBHE with a PV/T heat pump and investigates its thermal performance. This system utilizes thermal energy to elevate the temperature of water extracted from the MDBHE, while supplying power through photovoltaic electricity. The results indicate that increasing the circulating water flow rate improves the heat extraction capacity of the MDBHE. However, this also leads to higher flow resistance and an increased power requirement for the circulating water pump. Additionally, at a circulating water flow rate of 32 m3/h, the system fails to extract heat from geothermal energy when the inlet temperature exceeds 34.5°C. Furthermore, with a PV/T module area of 2000 m2, solar radiation intensity of 600 W/m2, and MDBHE depth of 2000 m, the system can attain a maximum water supply temperature of 50.9°C, with solar energy contributing 63%. Moreover, the coefficient of performance (COP) of the system can reach 5.8, outperforming conventional systems.

Seasonal changes in the dietary patterns and reproductive aspects of deep-water rose shrimp Parapenaeus longirostris in the central Adriatic Sea

The deep-water rose shrimp Parapenaeus longirostris is one of the most important commercial species caught by trawl fisheries in the Mediterranean Sea. The species has a warm-water affinity and its landings are increasing in the whole basin. Detailed information on its trophic ecology, niche width and role within demersal food webs is dated or lacking in the Adriatic Sea, the most exploited basin of the Mediterranean. Therefore, to detect seasonal changes in diet and trophic levels, seasonal samplings were conducted in this area from January to December 2021, collecting 400 specimens, and integrating information from both stomach content analysis and stable isotope analyses (SIA). To identify potential links between the biological cycle of the species and fluctuations in energy demand, seasonal changes in fullness, as a proxy of feeding intensity, and gonadosomatic and hepatosomatic indices were assessed. The deep-water rose shrimp is confirmed to be a benthic feeder that predominantly preys on molluscs, crustaceans, fish, echinoderms and polychaetes. According to SIA, P. longirostris is defined as a secondary consumer. Observed seasonal dietary changes precede the reproductive periods, likely due to the need for more energetic prey.

Apple Pomace Integrated Biorefinery for Biofuels Production: A Techno-Economic and Environmental Sustainability Analysis

The combination of techno-economic process modelling and life cycle assessment is an integrated methodology that addresses quantitative operational data, and evaluates the emissions associated with any process under development. In particular, the valorisation of waste streams within the context of the circular economy could be considered a valid and promising approach, especially regarding techno-economic and environmental indicators. This manuscript aims to evaluate the integral valorisation of apple pomace from the processing industry into bioethanol, and vinasses (a byproduct of the distillation process) into biogas and digestate as biofertiliser. In addition to biogas production, lagooning and composting were considered as strategies for vinasse management. After the conceptual design of the process options was completed, the environmental profile of bioethanol production was estimated across different scenarios. When biogas production was integrated to reduce the biorefinery’s energy demand, the carbon footprint was 1.13 kg CO2eq∙kg−1. This footprint increased to values around four when lagooning and composting were used as vinasse management strategies. Although the economic dimension posed a significant limitation due to high investment costs, the eco-efficiency analysis showed that the scenario of the co-production of bioethanol and biogas is the best alternative. Despite the promising results, further research is needed to explore the recovery of additional co-products to develop a high-potential strategy for apple pomace.

Review and prospect on Metal-organic framework-based Separators for Lithium–Sulfur Battery

With the continuous advancement of technology, wearable smart devices and electric vehicles (EVs) have become an integral part of our daily lives. The increasing demand for energy from these devices and vehicles has driven the pursuit of high-performance rechargeable battery technology. In particular, the widespread adoption of electric vehicles has set higher standards for the energy density and cycle life of batteries. However, the energy density of the widely used lithium-ion batteries is currently limited by the theoretical capacity of commercial cathode materials, and there are certain challenges in terms of safety and cost-effectiveness. Therefore, the development of a new generation of rechargeable batteries with higher energy density, better safety, and more economical cost is particularly urgent. Lithium-sulfur batteries, due to their high energy density, high economic benefits, and high environmental friendliness, are considered to be one of the most promising successors to the widely used lithium-ion batteries. However, in practical applications, the electrochemical performance of lithium-sulfur batteries still needs to be improved. In particular, the poor conductivity of sulfur/lithium and the shuttle effect of polysulfides make the cycle life of the battery less than ideal, and lithium-sulfur batteries (LSB) are still far from achieving large-scale commercialization. The separator used in lithium-sulfur batteries plays a crucial role in its cycle performance and safety. The current commercial separator lacks the ability to effectively regulate the shuttle of polysulfides and is prone to thermal runaway at high temperatures. Therefore, to improve these issues, various functional materials have been used to modify the separator. Among them, as a new type of porous coordination polymer, metal organic frameworks (MOFs) have become a promising material for modifying separators due to their large specific surface area and highly ordered tunable nano-holes.At the same time, their rich inorganic nodes and designable organic ligands allow for the customization of pore chemistry at the molecular level, which can interact with the electroactive components in lithium-sulfur batteries in a tunable manner. This article reviews the reaction mechanism of lithium-sulfur batteries and the structural advantages of MOFs in terms of pore chemistry and morphology and briefly introduces the research progress of MOF-based interfacial layers for the functionalization of LSB separators in recent years. It elaborates on the mechanisms by which various modified separators improve electrochemical performance and provides a prospect for the development prospects of the field.

An exploratory study of metabolomics in endogenous and cannabis-use-associated psychotic-like experiences in adolescence

In adolescence, psychotic-like experiences (PLE) may indicate potential prodromal symptoms preceding the onset of psychosis. Metabolomic studies have shown promise in providing valuable insights into predicting psychosis with enhanced precision compared to conventional clinical features. This study investigated metabolomic alterations associated with PLE in 76 depressed adolescents aged 14–20 years. Serum concentrations of 92 metabolites were analyzed with liquid chromatography–mass spectrometry. PLE were assessed using the Youth Experiences and Health (YEAH) questionnaire. The associations between PLE symptom dimensions (delusions, paranoia, hallucinations, negative symptoms, thought disorder, and dissociation) and metabolite concentrations were analyzed in linear regression models adjusted for different covariates. The symptom dimensions consistently correlated with the metabolome in different models, except those adjusted for cannabis use. Specifically, the hallucination dimension was associated with 13 metabolites (acetoacetic acid, allantoin, asparagine, decanoylcarnitine, D-glucuronic acid, guanidinoacetic acid, hexanoylcarnitine, homogentisic acid, leucine, NAD+, octanoylcarnitine, trimethylamine-N-oxide, and valine) in the various linear models. However, when adjusting for cannabis use, eight metabolites were associated with hallucinations (adenine, AMP, cAMP, chenodeoxycholic acid, cholic acid, L-kynurenine, neopterin, and D-ribose-5-phosphate). The results suggest diverse mechanisms underlying PLE in adolescence; hallucinatory experiences may be linked to inflammatory functions, while cannabis use may engage an alternative metabolic pathway related to increased energy demand and ketogenesis in inducing PLE. The limited sample of individuals with depression restricts the generalizability of these findings. Future research should explore whether various experiences and related metabolomic changes jointly predict the onset of psychoses and related disorders.

Influence of the Conditions of Alkaline Pretreatment of Vegetable Raw Material before Hydrolysis in a Rotor Pulsation Device on the Cellulose Conversion

Introduction. The growing global energy demand, limited fossil fuel resources, and increasing greenhouse gasemissions highlight the need for expanded use of renewable energy sources, particularly biomass.Problem Statement. A significant drawback in the production of bioethanol is its high cost, primarily due tothe presence of hemicellulose and lignin.Purpose. This study aims to determine the effect of treating an alkaline suspension of wheat straw in a rotary pulsation device on the degree of cellulose conversion during enzymatic hydrolysis, a critical step in the productionof fuel ethanol.Materials and Methods. The raw material is pre-crushed wheat straw. The experiments have been conductedwith the use of a rotary pulsation device in an experimental plant.Results. It has been found that the combined physical effects of the discrete pulse energy input method andreduced straw particle size significantly increase the lignin extraction, from 40.0% at an average particle size of2—1 mm to 62.0% at an average particle size of 0.4—0.1 mm. Additionally, the treatment of an alkaline suspension of wheat straw at 90 оC for one hour, at alkali concentrations ranging from 1 to 4% (wt./wt.), results in anincrease in the cellulose conversion during enzymatic hydrolysis from 38% to 65.8%. Additionally, a corresponding decrease in the lignin content, from 17.1% to 3.16% has been reported.Conclusions. Increasing alkali concentration during the alkaline pretreatment of wheat straw using the discrete-pulse energy input method in a rotary pulsation device enhances the rate of cellulose conversion duringsubsequent enzymatic hydrolysis.

Foreign Direct Investment and Energy Demands: What Drives Economic Growth in Emerging Economies?

This study addresses two central questions: (a) Do inward foreign direct investment (FDI) spillovers drive economic growth in emerging economies? and (b) How do the interconnectedness of inward FDI and energy demands cause economic growthin emerging economies? For the analysis, the study uses data from the World Development Indicators and Penn World Table 10.0, covering the period between 1994 and 2019. The results show evidence of bi-directional causality between inward FDI spillover and economic growth, and the relationships are negative. These results indicate that FDI inflows are less critical in economic growth in emerging economies and vice versa. Furthermore, non-renewable energy positively causes both economic growth and FDI inflows, whereas renewable energy negatively causes economic growth. More so, our results reveal a presence of bi-directional causality between FDI inflows and renewable energy in emerging economies. Finally, as these empirical insights have profound implications for governments and policymakers in these economies, the article proposes policies targeting sustainable economic growth and diffusions of renewable energy technologies through inward FDI spillover. JEL Codes: 047, F35, P18, P52, C10

Plasma essential amino acid levels in first episode psychosis at baseline and after antipsychotic treatment

This study assessed plasma levels of essential amino acids (EAA) in drug-naïve first episode psychosis (FEP) patients at diagnosis and after 10 weeks of antipsychotic treatment. Forty FEP patients were enrolled at baseline, with blood samples collected before and after a 10-week antipsychotic treatment period. Plasma EAA levels were measured using an LC/MS/MS method. Psychotic symptoms were evaluated using standardized inventories before and after treatment. A decrease in BPRS score of more than 40% was used to indicate treatment response. Thirty-five healthy volunteers served as the control group. Baseline plasma levels of Thr, Met, Leu, Lys, His, and Tyr were higher in FEP patients than in healthy controls. After 10 weeks of treatment, Leu, His, and Tyr increased further, primarily in treatment-responsive patients. Conversely, Val level was lower than controls in patients at baseline and remained unchanged after treatment. Increased EAA levels were correlated with lower (less severe) scores in positive symptom scales. Treatment non-responders had persistently low Tyr/large neutral amino acid (LNAA) ratio. Tyr/LNAA ratio increased after treatment, specifically in treatment-responders. Phe/Tyr ratio decreased post-treatment in both responder and non-responder groups. Elevated EAA levels in FEP patients may signify compensatory responses to increased physiological demand for neurotransmitters or energy. Combining specific EAA supplementation with antipsychotic treatment may enhance treatment response in these patients.

Multi-objective optimal configuration of CCHP system containing hybrid electric-hydrogen energy storage system

In order to cope with the increasing energy demand and achieve the “double carbon “goal of China’s 14th Five-Year Plan,” combined with hydrogen energy storage technology, it has the characteristics of zero pollution, high efficiency and rich source. In the context of reducing energy consumption and the vigorous development of hydrogen energy storage technology, a multi-objective optimization configuration model with economy, energy consumption index and carbon emission index is proposed, which takes into account the working characteristics of the hydrogen energy storage system, and the exothermic heat release from the electrolysis tanks and fuel cells when they are working to provide the loads with an additional heat source of the Combined Cooling, Heating and Power (CCHP) system, to reduce energy consumption and carbon emission. Finally, taking a region as an example, a multi-objective optimization algorithm based on decomposition is used to solve the model, so as to obtain a series of alternatives with better optimization effect. At the same time, the two-way projection method based on interval intuitionistic fuzzy information is used to make decisions, and the scheme that optimizes the economy, energy consumption index and carbon emission index is obtained, which verifies the feasibility of the system proposed in this paper.

Exploring advanced microwave strategy for the synthesis of two-dimensional energy materials

The rapid pace of technology and increasing energy demands underscore the urgent need for eco-friendly materials with exceptional energy conversion and storage capabilities. Two-dimensional (2D) energy materials, characterized by unique physicochemical properties, hold great promise in renewable energy conversion, catalysis, and electronics. Nevertheless, conventional synthesis methods often falter in balancing high quality, high yield, and cost-effectiveness, presenting substantial obstacles to their large-scale application. Microwave-assisted synthesis, characterized by its rapid and efficient process, emerges as a promising approach to surmount these limitations. This review meticulously examines the pivotal role of microwave-assisted synthesis in the preparation of 2D materials, highlighting its profound impact on enhancing material quality and production efficiency. By scrutinizing the unique physical properties of microwaves and their applications in material synthesis, the review elucidates the innovative contributions of microwave technology to materials science. Furthermore, it delves into the intricate influence of microwave parameter control on the synthesis process and resultant material properties, offering insight into the potential of microwave technology for the precise modulation of material structure and functionality. This comprehensive analysis underscores microwave-assisted synthesis as a viable solution for overcoming current challenges, thereby advancing the development of high-performance 2D energy materials.

Toward Carbon‐Negative Methanol Production from Biogas: Intensified Membrane Reactor

AbstractThe modern world's major challenges, such as global warming, air pollution, and increasing energy demands, escalate the importance of sustainable development and transition toward renewables using innovative and environmentally friendly solutions, such as intensifying chemical processes, to reduce carbon footprints effectively. Aiming to enhance the process toward negative carbon emissions, this perspective explores the intensified membrane reactors for reducing the energy intensity of converting biogas into methanol, a versatile chemical feedstock, and renewable liquid fuel. Syngas and methanol synthesis processes, catalysts, and membranes were explored, and novel reactor designs were proposed. Introduction of selective membranes into the catalytic reaction zone to combine synthesis separation steps could enhance the system efficiency and intensify the process by recycling energy and materials, besides reducing costs and required energy for the separation process: the continuous harnessing of products shifts reactions toward desired species while recycling energy and materials enhances the process efficiency, and separating water from methanol reduces the required energy and costs of extra processes for methanol separation. The successful implementation of this technology holds significant promise for sustainable developments in producing chemicals and renewable fuel from renewable biogas and reducing methane and carbon dioxide emissions toward achieving carbon‐negative technologies.

A Deep Learning-Based Approach for High-Dimensional Industrial Steam Consumption Prediction to Enhance Sustainability Management

The continuous increase in industrialized sustainable development and energy demand, particularly in the use of steam, highlights the critical importance of efficient energy forecasting for sustainability. While current deep learning models have proven effective, they often involve numerous hyperparameters that are challenging to control and optimize. To address these issues, this research presents an innovative deep learning model, automatically fine-tuned using an improved RIME optimization algorithm (IRIME), with the aim of enhancing accuracy in energy forecasting. Initially, the bidirectional gated recurrent unit (BiGRU) exhibited promising results in prediction tasks but encountered difficulties in handling the complexity of high-dimensional time-series data related to industrial steam. To overcome this limitation, a bidirectional temporal convolutional network (BiTCN) was introduced to more effectively capture long-term dependencies. Additionally, the integration of a multi-head self-attention (MSA) mechanism enabled the model to more accurately identify and predict key features within the data. The IRIME-BiTCN-BiGRU-MSA model achieved outstanding predictive performance, with an R2 of 0.87966, MAE of 0.25114, RMSE of 0.34127, and MAPE of 1.2178, outperforming several advanced forecasting methods. Although the model is computationally complex, its high precision and potential for automation offer a promising tool for high-precision forecasting of industrial steam emissions. This development supports broader objectives of enhancing energy efficiency and sustainability in industrial processes.

A NOVEL FAULT-TOLERANT GENERALIZED SYMMETRICAL TOPOLOGY FOR RENEWABLE ENERGY AND ELECTRIC VEHICLE APPLICATIONS

Multilevel inverters are a versatile and powerful technology for applications such as motor drives, high voltage direct current transmission (HVDC), renewable energy systems, and grid-connected applications. As the demand for high-quality, clean energy and low distortion continues to grow, multilevel inverters are preferred over traditional square wave inverters. This paper proposes a generalized 13-level symmetrical topology to meet the power quality requirements. It consists of six DC sources and twelve semiconductor devices. Further, the topology has cascaded to increase the number of levels, but the cost and circuit complexity increase with the number of units. The gate pulses for switches are produced by the nearest-level modulation technique. The performance comparison of the topology with recent literature provides comprehensive information about the novelty of the configuration. The MLI performance parameters are number of switches, number of gates driving circuits, total harmonic distortion (THD), cost function per level (CCPL), total standing voltage (TSV), and efficiency (η). MATLAB/Simulink investigates the proposed topology, and further, to validate its simulation output, the hardware prototype model has been implemented in the laboratory.

Multi-agent based optimal sizing of hybrid renewable energy systems and their significance in sustainable energy development

This paper delves into the enhancement and optimization of on-grid renewable energy systems using a variety of renewable energy sources, with a particular focus on large-scale applications designed to meet the energy demand of a certain load. As global concerns surrounding climate change continue to mount, the urgency of replacing traditional fossil fuel-based power generation with cleaner, more cost-effective and dependable alternatives becomes increasingly apparent. In this context, a comprehensive investigation is conducted on grid connected hybrid energy system that combines photovoltaic, wind, and fuel cell technologies. The study employs three state-of-the-art optimization algorithms, namely Walrus Optimization Algorithm (WaOA), Coati Optimization Algorithm (COA), and Osprey Optimization Algorithm (OOA) to determine the optimal system size and energy management strategies, all aimed at minimizing the cost of energy (COE) for grid-based electricity. The results of the optimization process are compared with the results obtained from the utilization of the Particle swarm optimization (PSO) and Grey Wolf optimizer (GWO). The findings of this study underscore both the practical feasibility and the critical importance of adopting on-grid renewable energy systems to decrease the dependence on traditional energy sources within the grid. The proposed WaOA succeeded to reach the optimal solution of the optimal design process with a COE of 0.51758129611 $//kwh while keeping the loss of power supply probability (LPSP), the reliability index, at 7.303681e-19. The practical recommendations and forward-looking insights provided within this research hold the potential to foster sustainable development and effectively mitigate carbon emissions in the future.

Atomic catalysis meets heterostructure synergy: Unveiling the trifunctional efficacy of transition Metal@WS2/ReSe2

Integrating and advancing renewable energy storage and conversion technologies such as water splitting and rechargeable air-based batteries face significant challenges in finding appropriate catalysts that offer both high activity and low cost. This paper successfully designed efficient, cost-effective, and eco-friendly catalysts that meet the requirements for hydrogen evolution reaction (HER), oxygen evolution reaction (OER), and oxygen reduction reaction (ORR) catalytic activity by employing two-dimensional (2D) transition metal dichalcogenides (TMDs) interface engineering combined with a single-atom doping strategy. First, the heterostructure was constructed, and its optimal layer spacing (3.13 Å) was determined by calculating the most negative binding energy. These materials were theoretically evaluated using density functional theory (DFT), demonstrating that transition metal (TM) can all be firmly attached to the S1 site of the WS2/ReSe2 Z-scheme heterostructure with favorable binding energies and excellent electronic properties. By comparing the catalysts doped with different metals (Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, and Zn), the three functional catalysts with the best performance were finally selected: Mn@WS2/ReSe2, Ni@WS2/ReSe2, and Cu@WS2/ReSe2. In particular, Mn@WS2/ReSe2 exhibited exceptional promise as multifunctional catalysts, with overpotentials for the HER/OER/ORR of 0.05/0.29/0.35 V, respectively. The superior catalytic performance of this WS2/ReSe2 Z-scheme heterostructure was attributed to the introduction of TM atoms and the synergistic interaction between rhenium and the TM atoms. This interaction facilitated more efficient electron transfer between the catalyst and the reactants, enhancing the overall catalytic activity. This research is a successful attempt to combine interface engineering with single-atom catalysis (SACs). It provided valuable insights into the design of next-generation multifunctional electrocatalysts, offering a novel approach to address the growing energy demands in an environmentally benign and economically viable way.

Control of Large Wind Energy Converters for Aeroacoustic Noise Mitigation with Minimal Power Reduction

The population is often opposed to wind turbines being erected near their homes, mainly because the machines are noisy, especially at night. In an effort to establish a compromise between the needs of the people and the fulfilment of energy demands, wind turbines have the ability to switch between day and night operation by reducing the rotation speed during the night, resulting in a loss of generated power. The present study investigates simple models for noise emission, propagation, and prediction, with the objective of proposing a control system configuration that continuously adjusts the rotational speed as much as necessary until it matches sound level regulations while minimising power losses. Thus, several approaches are implemented and tested with a very large reference wind turbine. The simulation results of a reference wind turbine show that the approaches provide significant improvements in sound reduction as well as in power conversion.