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"energy requirements"
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Comprehensive review of VPPs planning, operation and scheduling considering the uncertainties related to renewable energy sources
The penetration of renewable energies in the energy market has increased significantly over the last two decades due to environmental concerns and clean energy requirements. The principal advantage of renewable energy resources (RESs) over non‐RESs is that it has no direct carbonisation impact on the environment and that it has none of the global warming effects which are caused by carbon emissions. Furthermore, the liberalisation of the energy market has led to the realisation of the virtual power plant (VPP) concept. A VPP is a unified platform for distributed energy resources that integrates the capacities of various renewable energies together for the purpose of improving power generation and management as well as catering for the buying and selling of energy in wholesale energy markets. This review study presents a comprehensive review of existing approaches to planning, operation and scheduling of the VPP system. The methodologies that were adopted, their advantages and disadvantages are assessed in detail in order to benefit new entrants in the power system and provide them with comprehensive knowledge, techniques and understanding of the VPP concept.
Journal Article
Turkey as an energy hub? : contributions on Turkey's role in EU energy supply
Guaranteeing energy security is one of the most important challenges for Europe today. Especially since the crises in Ukraine, Europe's interest in an additional supply line of gas and oil to Europe through Turkey has been growing steadily. In both political and academic discourse the question of whether Turkey can develop into a possible future 'energy hub' is a hotly debated issue. The country's geographical position is a big advantage as more than 70 per cent of the world's oil and gas reserves are located close by. The country may thus hold a key position in the distribution of oil and gas. Will Turkey, itself almost fully dependent on imports, be capable of becoming an energy hub? This edited volume examines Turkey's prospects as a possible energy hub and in its role in the EU's energy security. The contributions it contains reflect geopolitical dynamics and interests, economic trends, and the prevailing perceptions of this issue in Turkey and the European Union.-- Provided by Publisher.
BOOK
Exploring the bounds of methane catalysis in the context of atmospheric methane removal
Methane, a potent greenhouse gas, is a significant contributor to global warming, with future increases in its abundance potentially leading to an increase of more than 1 ∘ C by 2050 beyond other greenhouse gases if left unaddressed. To remain within the crucial target of limiting global warming to 1.5 ∘ C, it is imperative to evaluate the potential of methane removal techniques. This study presents a scoping analysis of different catalytic technologies (thermal, photochemical and electrochemical) and materials to evaluate potential limitations and energy requirements. An analysis of mass transport and reaction rates is conducted for atmospheric methane conversion system configurations. For the vast majority of catalytic technologies, the reaction rates limit the conversion which motivates future efforts for catalyst development. An analysis of energy requirements for atmospheric methane conversion shows minimum energy configurations for various catalytic technologies within classic tube or parallel plate architectures that have analogs to ventilation and industrial fins. Methane concentrations ranging from 2 ppm (ambient) to 1000 ppm (sources, such as wetlands, fossil-fuel extraction sites, landfills etc) are examined. The study finds that electrocatalysis offers the most energy efficient approach (∼0.2 GJ tonne −1 CO 2 e) for new installations in turbulent ducts, with a total energy intensity < 1 GJ tonne −1 CO 2 e. Photocatalytic methane removal catalysts are moderately more energy intensive (∼2 GJ tonne −1 CO 2 e), but could derive much of their energy input from ‘free’ solar energy sources. Thermal systems are shown to be excessively energy intensive ( > 100 GJ tonne −1 ), while combining photovoltaics with electrochemical catalysts (∼1 GJ tonne −1 CO 2 e) have comparable energy intensity to photocatalytic methane removal catalysts.
Journal Article
Estimation of daily energy requirements using a hybrid artificial intelligence model
Accurately estimating energy requirements is critical for individuals to maintain a healthy life. Traditional methods may be time-consuming, complex, low in accuracy, and costly, thus creating a need for new approaches. This study explores the applicability of hybrid artificial intelligence models for calculating daily energy requirements based on individuals’ anthropometric measurements and demographic data. The study’s primary goal is to develop a model that offers a reliable and practical solution with higher accuracy than existing methods while ensuring ease of use in field settings. This study used data collected from volunteer individuals at Sakarya University between September 2023 and February 2024. Anthropometric measurements were performed by a bioelectrical impedance analysis (BIA) device, and demographic data were obtained through face-to-face surveys. Eighty-seven features were analyzed using the Spearman feature selection algorithm, and these were utilized to estimate energy requirements. Based on collaborative hybridization, the hybrid artificial intelligence model integrates three distinct Gaussian Process Regression (GPR) models using squared exponential, rational quadratic, and Matern52 kernels. These models were structured based on gender, and performance evaluation was carried out using criteria such as MAPE, MAD, MSE, R, and R². The best model performance in males was achieved at level 10 with 100% R², while the highest accuracy in females was observed at level 15. To increase model simplicity, the PCA method was applied; however, a decrease in performance was detected (
R
= 0.48, R² = 0.23). The accuracy of the artificial intelligence models proposed in this study was significantly higher than that of traditional formulas commonly preferred in the current literature. Hybrid artificial intelligence models offer practicality, accuracy, and flexibility in estimating energy requirements. Gender-based modeling has enhanced prediction performance while providing more reliable results by accounting for individual differences. This approach holds significant potential for advancing health and nutritional sciences.
Journal Article
Mathematical Modeling of Thin-Layer Drying Kinetics of Tomato Peels: Influence of Drying Temperature on the Energy Requirements and Extracts Quality
Tomato drying implies high energy consumption due to the high moisture content, and limiting drying temperatures is necessary to avoid carotenoid degradation. To explain the mechanism of moisture transport through the material and to scale up the drying process, drying experiments are needed and supported by mathematical modeling. For the Rila tomato peel drying process, ten thin-layer mathematical models were formulated based on experimental data for six temperatures (50–75 °C) and validated by statistical analysis. Considering the slab geometry of the peels sample and Fick’s second law of diffusion model, the calculated effective moisture diffusivity coefficient values Deff varied between 1.01 × 10−9–1.53 × 10−9 m2/s with R2 higher than 0.9432. From the semi-theoretical models, Two-term presents the best prediction of moisture ratio with the highest R2 and lowest χ2 and RMSE values. Using the experimental data on extract quality (carotenoid content), two degradation models were formulated. Increasing the drying temperature from 50 °C to 110 °C, a degradation of 94% for lycopene and 83% for β-carotene were predicted. From the energy analysis, a specific energy consumption of 56.60 ± 0.51 kWh is necessary for hot-air drying of 1 kg of Rila tomato peel at 50 °C to avoid carotenoid degradation.
Journal Article
Which is the best route to achieve nutritional goals in pediatric ECMO patients?
Estimating caloric intake and choosing route of administration are fundamental in the nutritional support of patients being supported by extracorporeal membrane oxygenation (ECMO). The aim of this study was to review the nutritional intervention carried out in a pediatric cohort in a third-level hospital.
This was a prospective descriptive study. Age, sex, underlying pathology, Pediatric Risk of Mortality score, ECMO indication, type of care, duration of ECMO support, and prognosis were collected. Type of nutritional support, route of administration, kcal/kg achieved, estimated energy requirements, and percentage of caloric objective (%CO) reached on days 3 and 5 after cannulation were recorded.
Twenty-four venoarterial ECMO runs in 23 patients over a period of 2 y were recorded. Of the 23 patients, 15 were <1 y of age. The underlying pathology in 56.5% was cardiac disease. Three groups were identified: parenteral nutrition (group 0, n = 7), enteral nutrition (group 1, n = 8), and mixed nutrition (group 2, n = 7). The median of the %CO was 33.34 (0–84) on day 3 and 87.75% (78.4–100) on day 5 of ECMO, respectively for group 0; 75.5 (42.25–98.5) and 85% (24.4–107.7) in group 1 and 68.7 (44.4–82.2) and 91.2% (35.5–92) in group 2 (P > 0.05). Children <12 mo of age and cardiac patients represented 85.71% and 71.43% of total patients in group 0. Among the eight episodes of exclusive enteral nutrition, no complications were identified.
Enteral nutrition appears to be safe in the setting of hemodynamic stability and absence of contraindications and is equivalent to other nutritional interventions in terms of compliance with estimated energy requirements.
Journal Article
Numerical investigation into wave energy harvesting performance of fish-finding buoy with inner vertical pendulum
A fish-finding buoy (FFB) with an inner vertical pendulum is designed and manufactured to capture wave energy to power its global navigation satellite system (GNSS) module. To evaluate the energy harvesting performance of the FFB, a numerical model of the hull-pendulum system (HPS) is established and embedded in the hydrodynamic model (DXFlow) developed based on OpenFOAM. Using the numerical model, the pendulum motion and power are analyzed, the power take-off coefficient is optimized, and the energy conversion efficiency is evaluated. The results indicate that the maximum response amplitude operator (RAO) for the pendulum rotation is near 4 when the incident wave period approaches the natural period of the HPS; otherwise, it stabilizes at approximately 1.8. The heave of the FFB introduces high-frequency components to the pendulum rotation, while the surge of the FFB prolongs the HPS motion period, disadvantageous to the FFB’s energy harvesting performance. The optimized range of the damping coefficient is 0.25 N·s to 0.45 N·s. Alternatively, an amplitude ratio ranging from 0.8–1.6 is recommended for the pendulum and hull rotation. Within the recommended range, significant variations are noted in terms of the first conversion efficiency of the FFB. However, the time-averaged power output of the FFB pendulum is generally greater than 100 mW, adequate for the GNSS module of marine navigation and observation devices. These findings offer a new thought for addressing the limited energy requirements of ocean navigation and observation devices through wave energy utilization.
Journal Article
Animals selected for postweaning weight gain rate have similar maintenance energy requirements regardless of their residual feed intake classification
Data of comparative slaughter were used to determine Nellore bulls’ net energy requirements classified as efficient or inefficient according to residual feed intake (RFI) and selection lines (SL). Sixty-seven Nellore bulls from the selected (SE) and control (CO) lines of the selection program for postweaning weight gain were used. The animals underwent digestibility trials before being submitted to the finishing trial. Sixteen bulls were slaughtered at the beginning of the finishing trial, and their body composition was used as the baseline for the remaining animals. For body composition determinations, whole empty body components were weighed, ground, and subsampled for chemical analyses. Initial body composition was determined with equations developed from the baseline group using shrunk body weight, fat, and protein. The low RFI (LRFI) and CO animals had a lower dry matter (DMI) and nutrient intake (P < 0.05) than high RFI (HRFI) and SE animals, without alterations in digestibility coefficients (P > 0.05). During the finishing trial, DMI remained lower for LRFI and CO animals. Growth performance was similar between RFI classes, except for empty body weight gain that tended to be higher for LRFI than HRFI (P = 0.091). The SE animals had less fat content on the empty body (P = 0.005) than CO. Carcasses tended to be leaner for LRFI than HRFI (P = 0.080) and for SE than CO (P = 0.066) animals. LRFI animals retained more energy (P = 0.049) and had lower heat production (HP; P = 0.033) than the HRFI ones. Retained energy was not influenced by SL (P = 0.165), but HP tended to be higher for SE when compared to CO (P = 0.075) animals. Net energy requirement for maintenance (NEm) was lower for LRFI than HRFI (P = 0.009), and higher for SE than CO (P = 0.046) animals. There was an interaction tendency between RFI and SL (P = 0.063), suggesting that NEm was lower for LRFI+CO than HRFI+CO (P = 0.006), with no differences for SE (P = 0.527) animals. The efficiency of ME utilization for maintenance (km) of LRFI and HRFI animals were 62.6% and 58.4%, respectively, and for SE and CO were 59.0% and 62.1%, respectively. The breeding program for postweaning weight has not improved feed efficiency over the years, with RFI classification not being a promising selection tool for SE animals. Classification based on RFI seems to be useful in animals that have not undergone the breeding program, with LRFI animals having lower energy requirements than the HRFI ones.
Journal Article