Energy Configuration Research Articles

Life Cycle Assessment of Green Methanol Production Based on Multi-Seasonal Modeling of Hybrid Renewable Energy and Storage Systems

This study evaluates the environmental implications of green methanol production under seasonal energy variability through a dual-comparative analytical framework. The research employs ReCiPe 2016 Endpoint (H) methodology to assess four seasonal renewable energy configurations (with varying solar–wind ratios across seasons) against conventional grid-based production, utilizing a hybrid battery storage system combining lithium-ion and vanadium redox flow technologies. The findings reveal significant environmental benefits, with seasonal renewable configurations achieving 24.38% to 28.26% reductions in global warming potential compared to conventional methods. Monte Carlo simulation (n = 20,000) confirms these improvements across all impact categories. Our process analysis identifies hydrogen production as the primary environmental impact contributor (74–94%), followed by carbon capture (5–13%) and methanol synthesis (0.5–4.5%). Water consumption impacts show seasonal variation, ranging from 16.55% in summer to 11.62% in winter. There is a strong positive correlation between hydrogen production efficiency and solar energy availability, suggesting that higher solar energy input contributes to improved production outcomes. This research provides a framework for optimizing sustainable methanol production through seasonal renewable energy integration, offering practical insights for industrial implementation while maintaining production stability through effective energy storage solutions.

Structure of the Se4 Isomers─An Ab Initio Study.

This study investigates the equilibrium geometries of four different Se4 isomers using the coupled cluster single and double perturbative (CCSD(T)) method, extrapolating to the complete basis sets. The ground-state geometry of the Se4 isomer with the C2v structure (2.8715 Å, 2.1750 Å, and 88.4°) is found to be very close to other theoretical values (2.910 Å, 2.224 Å, and 90.0°) for the Se═Se and Se-Se bond lengths and valence angle. Additionally, the adiabatic electron affinity, vertical electron affinity, and vertical ionization energy are calculated. The multireference configuration interaction method was used to calculate transitions from the singlet ground state to some excited counterparts, including the vertical excitation energy, oscillator strength, and main electronic configuration. The predicted wavelengths of electronic transitions to 11Bu, 11Au with C2h symmetry, and 11B1 state with the C2V symmetry could match the experimental NIR absorption band at 710-850 nm. These transitions and electronic properties may provide insights into the role of selenium in astrophysical environments, where 74Se in the solar system has been confirmed to originate from the supernova explosion process. The theoretical results offer a deeper understanding of Se4 electronic and geometric structures while also providing crucial spectroscopic data that could aid in the identification of selenium-containing molecules in extraterrestrial environments.

Optimal Allocation of Community Distributed Energy and Storage Based on Regional Autonomous Balance and Sharing Mechanism

In the context of new power systems, the rapid development of distributed renewable energy and the drive of dual carbon targets have prompted community-level clean energy and energy storage configuration to become the key to improving energy efficiency and reducing carbon emissions. Based on the regional autonomy balance and sharing mechanism, this paper establishes a community distributed energy and energy storage optimization configuration model. With the goal of minimizing the total operating cost of the community, the established model is linearized by using the Big-M method and the McCormick method and transformed into a mixed integer linear programming model that is easy to solve. In order to comprehensively evaluate the comprehensive benefits of the established optimization scheme, this paper introduces the indicators of clean energy self-consumption rate, load self-supply rate, static investment payback period, and static CO2 investment payback period from the aspects of energy utilization, the economy, and the environment. Finally, a calculation example analysis is conducted, and the results show that, compared with the scenario where energy storage is configured separately and distributed energy resources are not shared, the configuration strategy proposed in the article can reduce the energy storage configuration capacity by 46.6% and the distributed energy configuration capacity by 21.1%. Investment costs can be reduced by 15.6%. At the same time, 91.75% of distributed energy self-consumption and 96.80% of load self-supply are achieved, reducing grid interaction and promoting regional autonomy and balance. The static CO2 investment payback period is also significantly shortened, and the carbon emission reduction effect is significant, providing an important reference for community energy system optimization planning and green and low-carbon development.

Few-to-many-particle crossover of pair excitations in a superfluid

Motivated by recent advances in the creation of few-body atomic Fermi gases with attractive interactions, we study theoretically the few-to-many-particle crossover of pair excitations, which for large particle numbers evolve into a mode that describes amplitude fluctuations of the superfluid order parameter (the “Higgs” mode). Our analysis is based on the hypothesis that salient aspects of the excitation spectrum are captured by interactions between time-reversed pair states in a harmonic oscillator potential. Microscopically, this assumption leads to a Richardson-type pairing model, which is integrable and thus allows a systematic quantitative study of the few-to-many-particle crossover with only minor numerical effort. We first establish a parity effect in the ground-state energy, i.e., a spectral convexity in the energy of open-shell configurations compared to their closed-shell neighbors, which is quantified by a so-called Matveev-Larkin parameter discussed for mesoscopic superconductors, which generalizes the pairing gap to mesoscopic ensembles and which behaves quantitatively differently in a few-body and a many-body regime. The crossover point for this quantity is widely tunable as a function of interaction strength. We then compute the excitation spectrum and demonstrate that the pair excitation energy shows a minimum that deepens with increasing particle number and shifts to smaller interaction strengths, consistent with the finite-size precursor of a quantum phase transition to a superfluid state. We extract a critical finite-size scaling exponent that characterizes the decrease of the gap with increasing particle number. Published by the American Physical Society 2024

Effect of Ionic and Nonionic Compounds Structure on the Fluidity of Model Lipid Membranes: Computer Simulation and EPR Experiment.

This article investigates the influence of dopant molecules on the structural and dynamic properties of lipid bilayers in liposomes, with a focus on the effects of dopant concentration, size, and introduced electric charge. Experimental studies were performed using electron paramagnetic resonance (EPR) spectroscopy with spin probes, complemented by Monte Carlo simulations. Liposomes, formed via lecithin sonication, were doped with compounds of varying concentrations and analyzed using EPR spectroscopy to assess changes in membrane rigidity. Parallel simulations modeled the membrane's surface layer as a system of electric dipoles on a 20 × 20 rectangular matrix. As in the EPR experiments, the simulation explored the effects of dopant molecules differing in size and charge, while gradually increasing their concentrations in the system. Minimum binding energy configurations were determined from the simulations. The results revealed a strong correlation between the EPR data and simulation outcomes, indicating a clear dependence of membrane stiffening on the concentration, size, and charge of dopant molecules. This effect was most pronounced at low dopant concentrations (~1-1.5% for q = 2 and 1.5-2% for q ≥ 3). No significant stiffening was observed for neutral molecules lacking charge. These findings offer valuable insights into the mechanisms of membrane modulation by dopants and provide a quantitative framework for understanding their impact on lipid bilayer properties.

Study of equi-energetic effects on the low-velocity impact and compression after impact response of carbon fiber composite tube structures

This study investigates the equi-energetic low-velocity impact (LVI) and compression after impact (CAI) response of tubular CFRP structures. Various layups and geometries are employed to understand the effects of impact energy, configurations, and damage on the CAI behavior. Low mass-high velocity (LMHV) impact results in greater absorbed energy than high mass-low velocity (HMLV). Impact damage formation, especially circumferentially, significantly affects CAI strength. Braided tubes show higher impact resistance, but weaker compressive strength compared to unidirectional/twill tubes. A new analytical model provides accurate prediction of CAI strength. This study emphasizes the importance of impact energy and lay-up configurations in CFRP design.

Electron beam-splitting effect with crossed zigzag graphene nanoribbons in high-spin metallic states

Here, we analyze the electron transport properties of a device formed of two crossed graphene nanoribbons with zigzag edges (ZGNRs) in a spin state with total magnetization different from zero. While the ground state of ZGNRs has been shown to display antiferromagnetic ordering between the electrons at the edges, for wide ZGNRs—where the localized spin states at the edges are decoupled and the exchange interaction is close to zero—in the presence of relatively small magnetic fields, the ferromagnetic (FM) spin configuration can become the state of lowest energy due to the Zeeman effect. In these terms, by comparing the total energy of a periodic ZGNR as a function of the magnetization per unit cell, we obtain the FM-like solution of the lowest energy for the perfect ribbon, the corresponding FM-like configuration of the lowest energy for the four-terminal device formed of crossed ZGNRs, and the critical magnetic field needed to excite the system to this spin configuration. By performing transport calculations, we analyze the role of the distance between layers and the crossing angle of this device in the electrical conductance, at small gate voltages. The problem is approached employing the mean-field Hubbard Hamiltonian in combination with non-equilibrium Green’s functions. We find that ZGNR devices subject to transverse magnetic fields may acquire a high-spin configuration that ensures a metallic response and tunable beam-splitting properties, making this setting promising for studying electron quantum optics with single-electron excitations.

A technology to solve the water-energy-food crisis? Mapping sociotechnical configurations of agrivoltaics using Q-methodology

“Agrivoltaics” are solar photovoltaic panels mounted above productive farmland so that energy and food production can occur simultaneously on the same plot. Agrivoltaics are proffered as a means to reduce food-energy land use conflicts, and to ameliorate rural community opposition to ground-mounted solar farms. In this study we examine the socio-economic and environmental claims around agrivoltaics as a set of competing sociotechnical configurations, assessed through a Q-methodology and qualitative analysis of 30 responses from technical, NGO and social opposition respondents from 14 different countries. We find three emergent sociotechnical configurations, labelled: 1) Agrivoltaics for livelihood diversification and poverty alleviation; 2) Opposing agrivoltaics – asserting community control and procedural justice, and 3) Scaling up a ‘triple win’ for agrivoltaics – centring innovation and ownership models. We identify strong support for agrivoltaics in livelihood diversification across rural communities, and for meeting multiple food, energy and water security goals simultaneously. However, stakeholder opposition from technological intrusion of agrivoltaics in rural places and a lack of consensus on what role governmental authorities, landowners and community cooperatives can play are key barriers to deployment and upscaling of this niche technology. We find that agrivoltaics can stimulate diverse sociotechnical configurations of energy and agriculture, with great potential for improving energy and food security, though issues of visual intrusion and perceived ‘technology in the wrong place’, lack of clarity on funding and planning models, and improper scales of governance and procedural injustice could potentially stymie rollout for both smallholders and larger agribusiness schemes.

Probing the energy landscapes and adsorption behavior of asphaltene molecules near the silica surface: Insights from molecular simulations

Enhanced oil recovery (EOR) is a promising solution to meet the increasing energy demands. However, the efficiency of EOR processes is hindered by the deposition and precipitation of heavy oil components, such as asphaltenes, at various stages of oil extraction. Therefore, a detailed understanding of asphaltene molecules (AMs)–rock interactions is important for designing novel solvents and enhancing the efficiency of existing solvents in oil recovery. Using molecular dynamics simulations, we have investigated the structural and energetic behavior of model AMs in dodecane solvent near the silica surface representing the sandstone reservoirs. We obtained the potential of mean force of AMs (containing three island-type and two archipelago-type AMs), calculated their adsorption–desorption barriers, and compared them among themselves and with solvent molecules. We found a competition between AMs and solvent, where AMs with higher configurational energy than the solvent molecules exhibit preferential surface adsorption. We observed that the heteroatom-surface interactions play a pivotal role in the adsorption of AMs, such that AMs with polar heteroatoms prefer to adsorb onto the surface. Further, the desorption barrier of AMs was found to be proportional to the number of hydrogen bonds formed. We observed that the AMs anchored to the surface through the aliphatic chains lie parallel, whereas those with heteroatom adopt an orientation nearly perpendicular to the surface.

Analyzing lump-type solutions in scalar field models through configurational information measure

In this paper we employ a configurational information measure, specifically the differential configurational complexity (DCC), to quantify the information content of lump-type solutions in various scalar field models, including two modified inverted ϕ4 models, the modified ϕ3 model, as well as two additional families of lump models. Our objective is to complement previous studies by providing an informational perspective that distinguishes different solutions based on their energy configurations. We explore how the DCC measure relates to energy and its applicability in analyzing degenerate states. Our findings indicate that DCC effectively correlates with the energy parameters of the solutions, offering significant insights into their informational properties. This study underscores the value of using informational metrics like DCC to deepen our understanding of the structural and dynamic characteristics of complex systems in theoretical physics.

Supply chain configuration and total factor productivity of renewable energy

In the context of a highly uncertain global economic environment, exploring the relationship between supply chain allocation and total factor productivity (TFP) of renewable energy enterprises not only helps to optimize the support policy for renewable energy but also ensures the resilience of supply chain and promotes the micro foundation of energy transition. Based on the data of listed renewable energy enterprises in China from 2010 to 2022, this research systematically verifies the impact of the relative choice of diversification and concentration on the TFP of renewable energy enterprises from the perspective of the enterprise supply chain. The results show that: (1) Supply chain diversification can improve the TFP of renewable energy enterprises, but the impact of supply chain configuration on small and medium-sized enterprises is more significant. (2) Through mechanism analysis, it is revealed that supply chain diversification can improve the TFP of renewable energy enterprises mainly through three channels: improving the asset turnover, reducing the performance fluctuation, improving the knowledge absorptive capacity. (3) Compared with other industries, it is found that renewable energy enterprises are more vulnerable to the impact of climate change, which is the main reason for the heterogeneous impact of renewable energy supply chain configuration. Based on the above research, this study proposes policy suggestions to optimize the supply chain of renewable energy enterprises, so that renewable energy enterprises can reduce the potential fluctuation risk, by taking into account the cost reduction and efficiency increase.

Chemical reaction and radiation analysis for the MHD Casson nanofluid fluid flow using artificial intelligence

This study examines the boundary layer flow of a Casson nanofluid over an inclined extending surface, addressing the critical issue of heat and mass transmission in nanofluid applications. The research is motivated by the need to understand the thermal efficiencies of fluid fluxes influenced by Brownian motion and thermophoresis, particularly in the presence of Soret and Dufour effects. To tackle this complex problem, we employ the Buongiorno model to analyze the nonlinear dynamics of Casson nanofluid flow within an inclined channel, focusing on the intensified boundary layer's critical flow parameters. An innovative approach utilizing Artificial Neural Networks (ANNs) is introduced to solve the intricate nonlinear differential equations governing the heat transfer and flow characteristics of Casson nanofluids. The bvp4c built-in MATLAB function is utilized to assess the performance of the acquired current physical model across various scenarios, and a correlation of the results with a reference data set is conducted to verify the validity and efficiency of the proposed algorithm. This method demonstrates a high level of efficiency and accuracy, achieving a mean squared error in the range of 10−9 to 10−10. The results of this research not only enhance computational efficiency but also improve solution accuracy, making significant contributions to the understanding of coupled heat and mass transfer phenomena. The findings have broad applications across various industries, including biomedical devices, lubrication, energy systems, food processing, and cooling for electronics, where nanofluid flows are prevalent. The inclusion of Soret and Dufour effects further enriches the applicability of this analysis, providing valuable insights into the complex interactions within nanofluid systems. The effect of specific physical parameters is stated in terms of energy, velocity, and mass configuration; the velocity outline decreases with an increase in magnetic parameter. The concentration profile is lowered by an increase in the chemical reaction parameter and thermophoresis factor. As the Brownian motion factor rises, mass diffusion shows increases.

Revealing significant changes in electronic energy configurations via cation atom positions in Co(Gaₓ,Al1-x)₂O₄ spinel oxides

Revealing significant changes in electronic energy configurations via cation atom positions in Co(Gaₓ,Al1-x)₂O₄ spinel oxides

News Consumption, Partisanship, and Energy Preferences in Brazil and the United States

ABSTRACT The transition to a more sustainable energy system must consider public perceptions of energy sources and the influences that shape them. This study compares support for renewable and non-renewable sources that make up the energy grid in Brazil and the United States (US), two nations with different energy mixes, political histories, and media systems. Through national surveys, we assess how different national energy configurations impact attitudes about renewables and non-renewable sources. Then, we analyze what attitudes are influenced by each nation’s partisan identities and media consumption habits. Results indicate that attitudes reflect the fact that some energy sources are more politicized than others. In the US, polarization regarding coal and renewables manifests strong partisan differences, which are amplified by media consumption choices. In Brazil, since hydropower was adopted by both left- and right-leaning governments, the impact of partisanship on support for energy sources is more limited. Results suggest attitudes about energy are subjected to processes of partisan polarization, with media messages amplifying those effects. Findings underscore the need to invest in policies promoting media literacy and fact-based science communication, empowering the public to recognize when energy debates are manipulated to fit partisan narratives, often at the expense of evidence.

Self-assembled properties of water cuboids

Although liquid water and ice are characterised by predominantly tetrahedral coordination, small water clusters often exhibit a cubic structural motif. In this article, the stability of hydrogen-bonded water nanostructures in the form of n 1×n 2×n 3 cuboids is investigated. The requirement for complete hydrogen bonding imposes a strong constraint on their structure. The equations of the donor–acceptor balance are derived, from which all possible forms of completely hydrogen-bonded cuboids are deduced. The flexible non-additive AMOEBA potential is used for geometric optimisation of the set of configurations with different directions of hydrogen (H-) bonds. It has been established that the majority of completely hydrogen-bonded structures are formed by one layer of fused cubes. The lowest energy configurations of the, in fact, bilayer structures are formed by trans-configurations of transverse pairs of molecules, although some H-bonds are broken in this case. It is noted that the structure of the cuboids may result from the assembly of short nanotubes and smaller cuboids. On the other hand, unrealised H-bonds at the corners of the cuboids make it possible to assemble larger bilayer structures.

Size optimization of standalone wind-photovoltaics-diesel-battery systems by Harris hawks optimization (HHO): Case study of a wharf located in Bushehr, Iran

The global increase in energy demand has led to a growing focus on renewable energy sources as a potential solution. This study examines the annual total cost of optimized off-grid hybrid multi-resource systems, considering various configurations of Wind Turbines (WT), Photovoltaics (PV), Diesel Generators (DG), and Batteries (Bat). The research focuses on an oil dock in Bushehr, Iran, as a case study. The optimization process employs the Harris Hawk Optimization (HHO) algorithm – which is used for the first time for hybrid configuration and optimal sizing in this paper-, a nature-inspired, population-based optimization technique. This algorithm’s performance is compared to conventional optimization methods to assess its efficiency. The study’s methodology involves: (1) Explaining the economic relationships for each energy source, (2) Formulating a cost function, (3) Using the HHO algorithm to minimize the total cost of the renewable energy-based hybrid systems. The HHO algorithm is inspired by the hunting behavior of Harris hawks, specifically their “wonder attack” strategy. This novel approach to optimization aims to find the most cost-effective configuration of energy sources for the given scenario. Key findings of the study include the HHO algorithm demonstrated superior efficiency compared to Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO) across all configurations tested. The most cost-effective configuration was found to be a combination of photovoltaics, batteries, and diesel generators. This setup had the lowest total annual cost among all configurations examined. The optimal system consisted of 450 photovoltaic units, 9 battery units, and 2 diesel generator units, with a minimum annual cost of approximately $355,525. These results highlight the potential of the HHO algorithm in optimizing renewable energy systems and demonstrate the complex trade-offs between cost and environmental impact in hybrid energy configurations. The study contributes valuable insights to the field of renewable energy system design and optimization, particularly for off-grid applications in industrial settings.

Transient investigation of a residential building air conditioning system with heat pump and PV/T modules

Abstract Nowadays, in response to the European energy crisis and the imperative to reduce carbon emissions, the study of energy systems plays a crucial role. New energy systems and configurations have been studied in the recent years to improve the energy efficiency and reduce greenhouse gases emissions. This study investigates the dynamic performance of a residential HVAC system integrating photovoltaic thermal (PV/T) modules and a heat pump. The system aims to harness thermal energy from solar radiation using PV/T modules to generate electricity and heat water. The case study is performed considering a building located in Caserta. According to the authors knowledge, there is a lack of information regarding the modeling of PV/T systems with a heat pump. Inside the studied system, the thermal energy is stored in a storage tank for later use. An auxiliary heater is activated to produce domestic hot water (DHW) when the PV/T cannot provide it. The system components are modeled using TRNSYS. A dynamic simulation approach is adopted to assess the system performance under varying environmental conditions and building load demands. These load demands are used to model real-world scenarios. This kind of system offers several advantages. Firstly, the PV/T modules serve a dual purpose of electricity generation and water heating, maximizing energy utilization. Secondly, the heat pump enhances the overall efficiency of the system by extracting heat from the water stored in the puffer tank, thereby reducing reliance on conventional heating methods. The findings of this study provide valuable insights into the performance and feasibility of integrating PV/T in residential HVAC systems. During the winter season, the solar fraction, the ratio between energy supply from PV/T and total energy demand, averages about 25%. When heating is not required, the PV/T panels manage to ensure the production of approximately 75% of DHW.

A balanced optimization method for energy storage capacity allocation in new power systems under the background of carbon reduction

Abstract Under the combined effects of national carbon reduction requirements, strong volatility and randomness at the new energy end, and a large amount of source load at the load end, the planning and operation characteristics of the new power system will also undergo fundamental changes, and energy storage planning and configuration will become the most suitable solution. This paper explores the optimal configuration of energy storage capacity within emerging power systems. Using a distribution network heavily reliant on renewable energy as a case study, we employed an echo state network to optimize the balance of energy storage capacity. Numerical experiments and case studies were conducted to validate the efficacy of this approach. Our research aims to furnish a robust and practical methodology for optimizing energy storage capacity in power systems, thereby offering substantial support towards achieving carbon reduction targets and fostering sustainable development within the energy sector.

Investigating the photocatalytic efficacy of a porous cuprous gallate (CuGa2O4) thick film

Abstract The study aimed to investigate the photocatalytic activity of porous copper gallate (CuGa2O4) thick film with significant wall dimensions. The thick film was meticulously fabricated using tape casting systems, with CuGa2O4 nanoparticles synthesized by Sol–Gel technique and subsequently transformed into gels for the tape casting process. Rietveld refinements were employed to elucidate the crystal structure and lattice parameters of the CuGa2O4 spinel oxide lattice. Moreover, electronic energy configurations and optical transmittance measurements were acquired through UV-visible spectrophotometry. The correlations between the crystal structure, band gap change and formation of electronic energy levels in relation to the photocatalytic performance of CuGa2O4 were explored. The comprehensive examination provides valuable insights into the complex interaction between material properties and photocatalytic behavior, offering a nuanced understanding of the potential applications of porous CuGa2O4 thick films in various technological fields.

Research on the Possibilities of Expanding the Photovoltaic Installation in the Microgrid Structure of Kielce University of Technology Using Digital Twin Technology

Global challenges related to sustainable development are increasingly focusing on the use of digital twin technology as a universal tool for optimizing and monitoring renewable energy installations. This article discusses digital twin technology as a support for sustainable development based on the analysis of microgrid structures. Digital twins allow the creation of virtual models of physical systems. This capability facilitated the accurate replication of the microgrid model at Kielce University of Technology using ETAP (Electrical Transient Analyzer Program) software (version 22.5). The operational parameters of the microgrid structure were analyzed for the examined power range of the photovoltaic installation to determine the possibilities of expanding the existing installation. The impact of the photovoltaic installation’s power on the operational parameters of the microgrid structure was visualized, and final conclusions were formulated. Moreover, the integration of digital twin technology into renewable energy systems not only enhances operational efficiency but also plays a pivotal role in advancing sustainability objectives. Through real-time monitoring and predictive maintenance, digital twin technology facilitates the optimization of energy production and distribution, thereby reducing waste and contributing to the overall sustainability of energy systems. This technology enables the simulation of various scenarios, such as fluctuations in energy demand or the integration of new renewable sources, which can inform more sustainable decision-making processes. In the context of microgrids, digital twin technology ensures that energy production is closely aligned with consumption patterns, minimizing energy losses and enhancing grid resilience. Furthermore, digital twin technology supports the sustainable expansion of renewable installations by providing detailed insights into potential environmental impacts and the long-term sustainability of various energy configurations. As the demand for clean energy continues to grow, digital twin technology will be indispensable in achieving a balance between energy needs and environmental stewardship, ensuring that the expansion of renewable energy sources contributes positively to global sustainability objectives.