Search Results (3,660)

Driven by the need for sustainable and efficient energy systems, the optimal management of distributed generation, including photovoltaic systems and battery energy storage systems within prosumer households, is of crucial importance. This requires a comprehensive cost–benefit analysis to assess their viability. In this study, an optimization model formulated as a mixed-integer linear programming problem is proposed to evaluate the integration of battery storage systems for 10 prosumers on the radial feeder in Croatia and to quantify the benefits both from the prosumers’ perspective and that of the reduction in grid losses. The results show significant annual cost reductions for prosumers, totaling EUR 1798.78 for the observed feeder, with some achieving a net profit. Grid losses are significantly reduced by 1172.52 kWh, resulting in an annual saving of EUR 216.25 for the distribution system operator. However, under the current Croatian market conditions, the integration of battery storage systems is not profitable over the entire lifetime due to the high initial investment costs of EUR 720/kWh. The break-even analysis reveals that investment cost needs to decrease by 52.78%, or an inflation rate of 4.87% is required, to reach prosumer profitability. This highlights the current financial barriers to the widespread adoption of battery storage systems and emphasizes the need for significant cost reductions or targeted incentives. Full article

The literature clearly indicates that both academia and industry are strongly committed to developing comprehensive processes for spent Li-ion battery (LIB) recycling. In this regard, the current study presents an original contribution by providing a quantitative assessment of a large-scale recycling plant designed for the treatment of completely spent LIBs. In addition to a concept of the basic process, this assessment also considers a case study of a thermal integration and CO₂ capture subsystem. Process flow modeling software was used to evaluate the contribution of all process steps and equipment to overall energy consumption and to mass balance the data required for the technical assessment of the large-scale recycling plant. To underline the advantages and identify the optimal novel process concept, several key performance indicators were determined, such as recovery efficiency, specific energy/material consumption, and specific CO₂ emissions. In addition, the economic potential of the recycling plants was evaluated for the defined case studies based on capital and O&M costs. The results indicate that, even with CO₂ capture applied, the thermally integrated process with the combustion of hydrogen produced in the recycling plant remains the most promising large-scale configuration for spent LIB recycling. Full article

This study presents a comprehensive analysis of the long-term energy performance and economic viability of offshore wind farms planned for locations within the Polish Exclusive Economic Zone of the Baltic Sea. It focuses on the impact of wind farm layout, aerodynamic wake effects, and rotor blade surface degradation. Using the Jensen wake model, modified Weibull wind speed distributions are computed for various turbine spacing configurations (5D, 8D, and 10D) and wake decay constants $k_w\in \{0.02;0.03;0.05\}$. The results reveal a trade-off between turbine density and individual turbine efficiency: tighter spacing increases the total annual energy production (AEP) but also intensifies wake-induced losses. The study shows that cumulative losses due to wake effects can range from 16.5% to 38%, depending on the scenario considered. This corresponds to capacity factors ranging from 33.4% to 45.2%. Finally, lifetime productivity scenarios over 20 and 25 years are analyzed, and the levelized cost of electricity (LCOE) is calculated to assess the economic implications of design choices. The analysis reveals that, depending on the values of the considered parameters, the LCOE can range from USD 116.3 to 175.7 per MWh produced. The study highlights the importance of early stage optimization in maximizing both the energy yield and cost-efficiency in offshore wind farm developments. Full article

The goals of the European Union towards the energy transition imply profound changes in the energy field, so as to promote sustainable energy development while fostering economic growth. To achieve these changes, the incorporation of sustainable technologies supporting decentralisation, energy efficiency, renewable energy production, and demand flexibility is of vital importance. Blockchain has the potential to change energy services towards this direction. To optimally exploit blockchain, innovative business models need to be designed, identifying the opportunities emerging from unmet needs, while also considering potential risks so as to take action to overcome them. In this context, the scope of this paper is to examine the opportunities and the risks that emerge from the adoption of blockchain in four innovative business models, while also identifying mitigation strategies to support and accelerate the energy transition, thus proposing optimal approaches of exploitation of blockchain in energy services. The business models concern Energy Performance Contracting with P4P guarantees, improved self-consumption in energy cooperatives, energy efficiency and flexibility services for natural gas boilers, and smart energy management for EV chargers and HVAC appliances. Firstly, the value proposition of the business models is analysed and results in a comprehensive SWOT analysis. Based on the findings of the analysis and consultations with relevant market actors, in combination with the examination of the relevant literature, risks are identified and evaluated through a qualitative assessment approach. Subsequently, specific mitigation strategies are proposed to address the detected risks. This research demonstrates that blockchain integration into these business models can significantly improve energy efficiency, reduce operational costs, enhance security, and support a more decentralised energy system, providing actionable insights for stakeholders to implement blockchain solutions effectively. Furthermore, according to the results, technological and legal risks are the most significant, followed by political, economic, and social risks, while environmental risks of blockchain integration are not as important. Strategies to address risks relevant to blockchain exploitation include ensuring policy alignment, emphasising economic feasibility, facilitating social inclusion, prioritising security and interoperability, consulting with legal experts, and using consensus algorithms with low energy consumption. The findings offer clear guidance for energy service providers, policymakers, and technology developers, assisting in the design, deployment, and risk mitigation of blockchain-enabled business models to accelerate sustainable energy development. Full article

A comprehensive techno-economic assessment was undertaken to determine the viability of bioethanol production from sugarcane bagasse in Thailand through organosolv fractionation, incorporating three distinct catalytic systems: sulfuric acid, formic acid, and sodium methoxide. Rigorous process simulations were executed using Aspen Plus, facilitating the derivation of detailed mass and energy balances, which served as the foundational input for downstream cost modeling. Economic performance metrics, including the total annualized cost and minimum ethanol selling price, were systematically quantified for each scenario. Among the evaluated configurations, the formic acid-catalyzed organosolv system exhibited superior techno-economic attributes, achieving the lowest unit production costs of 1.14 USD/L for ethanol and 1.84 USD/kg for lignin, corresponding to an estimated ethanol selling price of approximately 1.14 USD/L. This favorable outcome was attained with only moderate capital intensity, indicating a well-balanced trade-off between operational efficiency and investment burden. Conversely, the sodium methoxide-based process configuration imposed the highest economic burden, with a TAC of 15.27 million USD/year, culminating in a markedly elevated MESP of 5.49 USD/kg (approximately 4.33 USD/L). The sulfuric acid-driven system demonstrated effective delignification performance. Sensitivity analysis revealed that reagent procurement costs exert the greatest impact on TAC variation, highlighting chemical expenditure as the key economic driver. These findings emphasize the critical role of solvent choice, catalytic performance, and process integration in improving the cost-efficiency of lignocellulosic ethanol production. Among the examined options, the formic acid-based organosolv process stands out as the most economically viable for large-scale implementation within Thailand’s bioeconomy. Full article

The cement industry is a significant contributor to global carbon dioxide emissions, primarily due to the energy demands of its production process and its reliance on clinker, a material formed through the high-temperature calcination of limestone. Strategies to reduce emissions include the adoption of low-carbon fuels, the use of carbon capture and storage (CCS) technologies, and the integration of supplementary cementitious materials (SCMs) to reduce the clinker content. The effectiveness of these measures depends on a complex set of interactions involving technological feasibility, market dynamics, and regulatory frameworks. This study presents a system dynamics model designed to assess how various decarbonization approaches influence long-term emission trends within the cement industry. The model accounts for supply chains, production technologies, market adoption rates, and changes in cement production costs. This study then analyzes a number of scenarios where there is large-scale sustained investment in each of three carbon mitigation strategies. The results show that CCS by itself allows the cement industry to achieve carbon neutrality, but the high capital investment results in a large cost increase for cement. A combined approach using alternative fuels and SCMs was found to achieve a large carbon reduction without a sustained increase in cement prices, highlighting the trade-offs between cost, effectiveness, and system-wide interactions. Full article

Given the urgent need to decarbonize the global energy system, green hydrogen has emerged as a key alternative in the transition to renewables. However, its production via electrolysis demands high water quality and raises environmental concerns, particularly regarding reject water discharge. This study employs an experimental and analytical approach to define optimal water characteristics for electrolysis, focusing on conductivity as a key parameter. A pilot water treatment plant with reverse osmosis and electrodeionization (EDI) was designed to simulate industrial-scale pretreatment. Twenty water samples from diverse natural sources (surface and groundwater) were tested, selected for geographical and geological variability. A predictive algorithm was developed and validated to estimate useful versus reject water based on input quality. Three conductivity-based categories were defined: optimal (0–410 µS/cm), moderate (411–900 µS/cm), and restricted (>900 µS/cm). Results show that water quality significantly affects process efficiency, energy use, waste generation, and operating costs. This work offers a technical and regulatory framework for assessing potential sites for green hydrogen plants, recommending avoidance of high-conductivity sources. It also underscores the current regulatory gap regarding reject water treatment, stressing the need for clear environmental guidelines to ensure project sustainability. Full article

Forest volume is an important information for assessing the economic value and carbon sequestration capacity of forest resources and serves as a key indicator for energy flow and biodiversity. Although remote sensing technology is applied to estimate volume, optical remote sensing data have limitations in capturing forest vertical height information and may suffer from reflectance saturation. While LiDAR data can provide more detailed vertical structural information, they come with high processing costs and limited observation range. Therefore, improving the accuracy of volume estimation through multi-source data fusion has become a crucial challenge and research focus in the field of forest remote sensing. In this study, we integrated Sentinel-2 multispectral data, Resource-3 stereoscopic imagery, UAV-based LiDAR data, and field survey data to quantitatively estimate the forest volume in Saihanwula Nature Reserve, located in Inner Mongolia, China, on the southern part of Daxing’anling Mountains. The study evaluated the performance of multi-source remote sensing features by using recursive feature elimination (RFE) to select the most relevant factors and applied four machine learning models—multiple linear regression (MLR), k-nearest neighbors (kNN), random forest (RF), and gradient boosting regression tree (GBRT)—to develop volume estimation models. The evaluation metrics include the coefficient of determination (R²), root mean square error (RMSE), and relative root mean square error (rRMSE). The results show that (1) forest Canopy Height Model (CHM) data were strongly correlated with forest volume, helping to alleviate the reflectance saturation issues inherent in spectral texture data. The fusion of CHM and spectral data resulted in an improved volume estimation model with R² = 0.75 and RMSE = 8.16 m³/hm², highlighting the importance of integrating multi-source canopy height information for more accurate volume estimation. (2) Volume estimation accuracy varied across different tree species. For Betula platyphylla, we obtained R² = 0.71 and RMSE = 6.96 m³/hm²; for Quercus mongolica, R² = 0.74 and RMSE = 6.90 m³/hm²; and for Populus davidiana, R² = 0.51 and RMSE = 9.29 m³/hm². The total forest volume in the Saihanwula Reserve ranges from 50 to 110 m³/hm². (3) Among the four machine learning models, GBRT consistently outperformed others in all evaluation metrics, achieving the highest R² of 0.86, lowest RMSE of 9.69 m³/hm², and lowest rRMSE of 24.57%, suggesting its potential for forest biomass estimation. In conclusion, accurate estimation of forest volume is critical for evaluating forest management practices and timber resources. While this integrated approach shows promise, its operational application requires further external validation and uncertainty analysis to support policy-relevant decisions. The integration of multi-source remote sensing data provides valuable support for forest resource accounting, economic value assessment, and monitoring dynamic changes in forest ecosystems. Full article

Using waste biomass as a raw material for the combined production of electricity and heat offers corresponding energy, economic, environmental and resource efficiency benefits. The study examines both the performance of a system for combined energy production based on the Organic Rankine Cycle (ORC) utilizing wood biomass and the market interest in its deployment within Bulgaria. Its objective is to propose a technically and economically viable solution for the recovery of waste biomass through the combined production of electricity and heat while simultaneously assessing the readiness of industrial and municipal sectors to adopt such systems. The cogeneration plant incorporates an ORC module enhanced with three additional economizers that capture residual heat from flue gases. Operating on 2 t/h of biomass, the system delivers 1156 kW of electric power and 3660 kW of thermal energy, recovering an additional 2664 kW of heat. The overall energy efficiency reaches 85%, with projected annual revenues exceeding EUR 600,000 and a reduction in carbon dioxide emissions of over 5800 t/yr. These indicators can be achieved through optimal installation and operation. When operating at a reduced load, however, the specific fuel consumption increases and the overall efficiency of the installation decreases. The marketing survey results indicate that 75% of respondents express interest in adopting such technologies, contingent upon the availability of financial incentives. The strongest demand is observed for systems with capacities up to 1000 kW. However, significant barriers remain, including high initial investment costs and uneven access to raw materials. The findings confirm that the developed system offers a technologically robust, environmentally efficient and market-relevant solution, aligned with the goals of energy independence, sustainability and the transition to a low-carbon economy. Full article

The detection of seabed boulders is a critical step in mitigating geological hazards during the planning and construction of offshore wind energy infrastructure, as well as in supporting benthic ecological and palaeoglaciological studies. Traditionally, side-scan sonar (SSS) has been favoured for such detection, but the growing availability of high-resolution multibeam echosounder (MBES) data offers a cost-effective alternative. This study presents a semi-automated, hybrid GIS-AI approach that combines bathymetric position index filtering and a Random Forest classifier to detect boulders and delineate boulder fields from MBES data. The method was tested on a 0.24 km² site in Long Island Sound using 0.5 m resolution data, achieving 83% recall, 73% precision, and an F1-score of 77—slightly outperforming the average of expert manual picks while offering a substantial improvement in time-efficiency. The workflow was validated against a consensus-based master dataset and applied across a 79 km² study area, identifying over 75,000 contacts and delineating 89 contact clusters. The method enables objective, reproducible, and scalable boulder detection using only MBES data. Its ability to reduce reliance on SSS surveys while maintaining high accuracy and offering workflow customization makes it valuable for geohazard assessment, benthic habitat mapping, and offshore infrastructure planning. Full article

Effective in situ H₂S removal is essential for the utilization of small, remote natural gas wells, where centralized treatment is often unfeasible. This study presents an integrated environmental–economic assessment of two such processes, LO-CAT^® and triazine-based absorption, using a scenario-based framework. Environmental impacts were assessed via the Waste Reduction Algorithm (WAR), considering both Potential Environmental Impact (PEI) generation and output across eight categories, while economic performance was analyzed based on equipment, chemical, energy, environmental treatment, and labor costs. Results show that the triazine-based process offers superior environmental performance due to lower toxic emissions, whereas LO-CAT^® demonstrates better economic viability at higher gas flow rates and H₂S concentrations. An integrated assessment combining monetized environmental impacts with economic costs reveals that the triazine-based process becomes competitive only if environmental impacts are priced above specific thresholds. This study contributes a practical evaluation framework and scenario-based dataset that support sustainable process selection for decentralized sour gas treatment applications. Full article

Some of nuclear power’s primary detractors are the unique environmental challenges and impacts of radioactive wastes generated during fuel cycle operations. Key benefits of spent fuel reprocessing (SFR) are reductions in primary high active waste (HAW) masses, volumes, and lengths of radiotoxicity at the expense of secondary waste generation and high capital and operational costs. By employing advanced waste management and resource recovery concepts in SFR beyond the existing standard PUREX process, such as minor actinide and fission product partitioning, these challenges could be mitigated, alongside further reductions in HAW volumes, masses, and duration of radiotoxicity. This work assesses various current and proposed SFR and fuel cycle options as base cases, with further options for fission product partitioning of the high heat radionuclides (HHRs), rare earths, and platinum group metals investigated. A focus on primary waste outputs and the additional energy that could be generated by the reprocessing of high-burnup PWR fuel from Gen III(+) reactors using a simple fuel cycle model is used; the effects of 5- and 10-year spent fuel cooling times before reprocessing are explored. We demonstrate that longer cooling times are preferable in all cases except where short-lived isotope recovery may be desired, and that the partitioning of high-heat fission products (Cs and Sr) could allow for the reclassification of traditional raffinates to intermediate level waste. Highly active waste volume reductions approaching 50% vs. PUREX raffinate could be achieved in single-target partitioning of the inactive and low-activity rare earth elements, and the need for geological disposal could potentially be mitigated completely if HHRs are separated and utilised. Full article

Modernizing irrigation systems (ISs) from traditional gravity methods to sprinkler and drip technologies has significantly improved water use efficiency. However, it has simultaneously increased electricity demand and operational costs. Integrating photovoltaic generators into ISs represents a promising solution, as solar energy availability typically aligns with peak irrigation periods. Despite this potential, photovoltaic pumping systems (PVPSs) often face reliability issues due to fluctuations in solar irradiance, resulting in frequent start/stop cycles and premature equipment wear. The IEC 62253 standard establishes procedures for evaluating PVPS performance but primarily addresses steady-state conditions, neglecting transient regimes. As the main contribution, the current paper proposes a non-intrusive, high-resolution monitoring system and a methodology to assess the performance of an isolated, high-power PVPS, considering also transient regimes. The system records critical electrical, hydraulic and environmental parameters every second, enabling in-depth analysis under various weather conditions. Two performance indicators, pumped volume efficiency and equivalent operating time, were used to evaluate the system’s performance. The results indicate that near-optimal performance is only achievable under clear sky conditions. Under the appearance of clouds, control strategies designed to protect the system reduce overall efficiency. The proposed methodology enables detailed performance diagnostics and supports the development of more robust PVPSs. Full article

A healthy vasculature with well-regulated perfusion and pulsatility is essential for the brain. One vascular structure that has received little attention is the carotid siphon. The proximal portion of the siphon is stiff due to the narrow location in the skull base, whilst the distal portion is highly flexible. This flexible part in combination with the specific curves lead to lower pulsatility at the cost of energy deposition in the arterial wall. This deposited energy contributes to damage and calcification. Severe siphon calcification stiffens the distal part of the siphon, leading to less damping of the pulsatility. Increased blood flow pulsatility is a possible cause of stroke and cognitive disorders. In this review, based on comprehensive multimodality imaging, we first describe the anatomy and physiology of the carotid siphon. Subsequently, we review the in vivo imaging data, which indeed suggest that the siphon attenuates pulsatility. Finally, the data as available in the literature are shown to provide convincing evidence that severe siphon calcifications and the calcification pattern are linked to incident stroke and dementia. Interventional studies are required to test whether this association is causal and how an assessment of pulsatility and the siphon calcification pattern can improve personalized medicine, working to prevent and treat brain disease. Full article

Efficient planning of train crew rosters is a key factor in ensuring operational reliability and promoting long-term sustainability in railway transport, both economically and socially. This article presents a systematic approach to developing a crew rostering model in passenger rail transport, with a focus on the operational setting of the train crew depot in Česká Třebová, a city in the Czech Republic. The seven-step methodology includes identifying available train shifts, defining scheduling constraints, creating roster variants, and calculating personnel and time requirements for each option. The proposed roster reduced staffing needs by two employees, increased the average shift duration to 9 h and 42 min, and decreased non-productive time by 384 h annually. These improvements enhance sustainability by optimizing human resource use, lowering unnecessary energy consumption, and improving employees’ work–life balance. The model also provides a quantitative assessment of operational feasibility and economic efficiency. Compared to existing rosters, the proposed model offers clear advantages and remains applicable even in settings with limited technological support. The findings show that a well-designed rostering system can contribute not only to cost savings and personnel stabilization, but also to broader objectives in sustainable public transport, supporting resilient and resource-efficient rail operations. Full article