Hasil untuk "Electricity"

Fernando Penaherrera, Ihsan Ünal, Lars Kühl et al.

Abstract Purpose This study examines the thermal, electrical, and mobility energy demand and supply of the residential district “Am Ölper Berge" in Lower Saxony, and evaluates potential developments of the district energy supply system and the trade-offs associated with its modernization. Methods A reference scenario for the year 2020 serves as the baseline for evaluating future development points (2030, 2040, 2050), including increasing electrification of thermal energy supply, improvements in building energy efficiency, and the integration of renewable energy sources for local generation. The scenarios include step-by-step measures such as facade insulation, implementation of photovoltaic systems, district heating supply, implementation of heat pumps, and the integration of charging infrastructure for electric vehicles. This is achieved using several control models integrated into the co-simulation platform mosaik. Results In the 2050 scenario, heat supply is provided via heat pumps and a low-temperature district heating network, supplemented by neighborhood energy storage and extensive use of photovoltaic systems. Four extended scenarios examine centralized and decentralized control strategies that monitor grid voltage across the district and optimize electric vehicle charging. The analysis includes charging strategies such as maximum charging power, night-time charging, forecast-based charging, and solar-optimized charging. The results show significant differences in external energy demands and CO $$_2$$ emissions, with solar-optimized charging of electrical vehicles combined with areal use of power flexibilities for grid control offering the greatest environmental and operational benefits. Conclusion The study provides key insights into the interactions between building energy demands, decentralized generation, and grid operation, thereby supporting the planning of energy supply for urban districts in alignment with emission reduction targets.

Sara C. Pryor, Rebecca J. Barthelmie

Summary: Hundreds of thousands of wind turbines and billions of solar photovoltaic (PV) panels are operating worldwide. Reliability, power production and operations, and maintenance costs for these electricity generation sources depend on operating conditions, including severe meteorological events such as hail frequency and size. Information necessary to undertake cost-benefit analyses of hail damage mitigation options is lacking. Novel, robust, and transferable models are presented that quantitatively describe the geospatial and temporal variability of hail damage in terms that are directly applicable to the wind and solar industries. Results are illustrated for the continental US In the south-central US, where 44% of wind turbine assets are located, blade coatings are predicted to fail at least once during the 25-year lifetime due to precipitation-induced erosion, with hail contributing 38% of the damage on average. The southeast region (28% of solar PV) is predicted to experience ≥20 potentially damaging hail events per year.

Xinwang Song, Yang Guo, Yanchang Chen et al.

Enhanced oil recovery (EOR) via CO₂ flooding is a promising strategy for improving hydrocarbon recovery and carbon sequestration, yet the influence of pH on solid–liquid interfacial interactions in quartz-dominated reservoirs remains poorly understood. This study employs molecular dynamics (MD) simulations to investigate the pH-dependent adsorption behavior of crude oil components on quartz surfaces and its impact on CO₂ displacement mechanisms. Three quartz surface models with varying ionization degrees (0%, 9%, 18%, corresponding to pH 2–4, 5–7, and 7–9) were constructed to simulate different pH environments. The MD results reveal that aromatic hydrocarbons exhibit significantly stronger adsorption on quartz surfaces at high pH, with their maximum adsorption peak increasing from 398 kg/m³ (pH 2–4) to 778 kg/m³ (pH 7–9), while their alkane adsorption peaks decrease from 764 kg/m³ to 460 kg/m³. This pH-dependent behavior is attributed to enhanced cation–π interactions that are facilitated by Na⁺ ion aggregation on negatively charged quartz surfaces at high pH, which form stable tetrahedral configurations with aromatic molecules and surface oxygen ions. During CO₂ displacement, an adsorption–stripping–displacement mechanism was observed: CO₂ first forms an adsorption layer on the quartz surface, then penetrates the oil phase to induce the detachment of crude oil components, which are subsequently displaced by pressure. Although high pH enhances the Na⁺-mediated weakening of oil-surface interactions, which leads to a 37% higher diffusion coefficient (8.5 × 10⁻⁵ cm²/s vs. 6.2 × 10⁻⁵ cm²/s at low pH), the tighter packing of aromatic molecules at high pH slows down the displacement rate. This study provides molecular-level insights into pH-regulated adsorption and CO₂ displacement processes, highlighting the critical role of the surface charge and cation–π interactions in optimizing CO₂-EOR strategies for quartz-rich reservoirs.

Nana Sartika, Rini Sulistiawati

The Covid-19 pandemic caused a negative contraction in the economic structure. In West Kalimantan province, despite negative growth, the primary and secondary sectors surprisingly showed positive growth in the mining, electricity, and agriculture sectors. Based on this situation, we investigated the possibility of the structural transformation process during the pandemic. We applied Lewis's transformation theory to the analysis of primary, secondary, and tertiary sectors to examine the general trends. We used Static-Dynamic Location Quotient, Klassen typology, and Shift Share analysis, and discovered that the negative contraction in 2020 did not significantly affect each sector. However, the pattern indicates a failure in the transformation process between the tertiary and primary sectors, with the primary sector naturally proving to be the main sector in the economic structure. The critical point of our finding is that the failure of the structural transformation process was potentially caused and locked by the failure of labour shifting. To unlock the interchange of labour to modern industries, the government must address human resource issues, identify definite interchanged sectors, choose key sectors, and ensure each stage is passed thoroughlywith all necessary resources.

Limkani Sincuba

South Africa, amidst the Fourth Industrial Revolution’s challenges, explores sustainable education intersecting with community development. Employing a mixed-methods approach, the study scrutinized educational dynamics. A case study method selected three secondary schools, involving 105 learners were purposively selected for this study. The study was underpinned by the human capital theory. This theoretical framework highlights the importance of addressing systemic inequities and promoting social justice. A questionnaire was used as a data collection tool. Qualitative data captured community perspectives, advocating for technology integration in education. Overcoming barriers like infrastructure and digital literacy was seen as crucial. The study findings highlighted integrating STEM education into South Africa’s curriculum, focusing on interdisciplinary strategies to nurture creativity, critical thinking, and problem-solving skills. STEAM courses were seen as a way which prepare students for the 4IR, fostering adaptability and future employment readiness. Lack of electricity, computers, and availability of computer training was revealed as one of the lacking factors among teachers in schools. Themes were drawn and discussed in relation to the research question. The study suggests assessing long-term impacts on community indicators like economic empowerment and health. The study concluded that police makers and curriculum designers may need to re-evaluate educational systems for STEAM. The study therefore recommended that it may be of great help if rigorous outcome evaluation measures of educational intervention would be effective in schools. Also, analyzing policy frameworks was recommended as essential for national development agendas, and bridging policy gaps

Florian Dietrich, Jia Chen, Ankit Shekhar et al.

Abstract Natural gas is considered a bridging technology in the energy transition because it produces fewer carbon emissions than coal, for example. However, when leaks exist, methane is released into the atmosphere, leading to a dramatic increase in the carbon footprint of natural gas, as methane is a much stronger greenhouse gas than carbon dioxide. Therefore, we conducted a detailed study of methane emissions from gas‐powered end‐use appliances and then compared their climate impacts with those of electricity‐powered appliances. We used the Munich Oktoberfest as a case study and then extended the study to 25 major natural gas consuming countries. This showed that electricity has been the more climate‐friendly energy source at Oktoberfest since 2005, due to the extensive use of renewable electricity at the festival and the presence of methane emissions, particularly caused by the incomplete combustion and leakages of natural gas in cooking and heating appliances. By contrast, at the global level, our study shows that natural gas still produces lower carbon emissions for end‐user appliances than electricity in 18 of the 25 countries studied. However, as the share of renewable energy in the electricity mix steadily increases in most countries, the carbon footprint of electricity will be lower than that of natural gas in these countries in the near future. These findings from our comparison of the total carbon emissions of electric and gas‐powered end‐use appliances can help inform the debate on how to effectively address climate change.

Carolina Aparicio-Fernández, M Eugenia Torner, Mar Cañada-Soriano et al.

Energy consumption in public education buildings depends on use and occupancy. To improve energy performance, energy audits are essential to identify specific solutions for each building. In this study, we conducted an energy audit of a historical building used as a public education centre. We collected gas and electricity bills and recorded indoor temperatures for over a year to determine heating and cooling set points and the schedules. Our analysis showed that 47.42% of the electricity bills were unused. To reduce energy demand and improve thermal comfort, we both developed and validated a Building Energy Modelling (BEM) approach using TRNSYS18 and weather data during year 2021. The BEM model allowed us to propose efficient measures to meet the Standard Passive requirements. Our results demonstrate the effectiveness of energy audits and BEM modelling in reducing energy consumption in public education buildings.

Aso Sammy N., Osuji Chijioke M., Iwe Madu O. et al.

Inadequate energy and water resources supply are major constraints contributing to poverty and poor health outcomes in developing economies. Low-income countries lack ready access to modern necessities such as electricity and potable water. On one hand, the scarcity of electricity and other clean energies compel reliance on traditional biomass for domestic fuels. On the other hand, harvesting firewood to meet energy needs leads to deforestation and environmental degradation. Furthermore, burning the wood for heat creates ecosystem perturbators such as toxicants, greenhouse gasses, and particulate matter. These pollutants portend adverse health concerns, including premature mortality. Globally, fine particulate matter air pollution alone causes about 3.3 million deaths annually. The contribution of this paper is to offer how circular economy targeted technologies could come to the rescue. In particular, utilizing biomass residues and wastes for briquette and pellet creation is highlighted. These densified fuel products could serve as green energies in domestic and industrial applications; and thus, help to attenuate poverty, and the adverse environmental and health consequences of traditional biomass.

Chidozie Ezekwem, Suresh Muthusamy

There is no way for developing countries to prosper economically or improve their living standards in rural areas if they lack access to energy and power. Access to electricity is frequently a disadvantage in rural areas of developing nations. This work aims to investigate rural electrification in Port Harcourt, Nigeria, using the Choba community as a case study. The investigation was divided into two stages: the first determined the current state of electrification in Choba, and the second study conducted a detailed assessment of integrating the renewable energy system for increased electricity access using the simulation software HOMER pro to estimate the number of photovoltaic modules (PVMs) and wind turbines required to ensure optimal performance. The analysis was examined by selecting the optimum configuration based on levelized cost of energy (LCOE) and net present cost (NPC). The normal energy consumption for the community is estimated to be approximately 39.12–46.80 MW for full 24-hour supply to all residents. In 2021, 6067.64 megawatt hours of electricity were supplied by Port Harcourt electricity distribution company (PHEDC). From the obtained results, this paper proposes an on-grid hybrid PVM/wind turbine system configuration that yields the optimal results in the case study to solve the power outages currently experienced in Choba. The optimal configuration has an NPC of $20.8 Million and LCOE $0.0117/kWh, with an operating cost of $204.52. This system reduce cost of energy by about 87% when compared with the non-MD customers in Band D.

Kang Chen, Hao Zhong, Liuzhang Ouyang et al.

LiBH4 has been considered as one of the most promising energy storage materials with its ultrahigh hydrogen capacity, which can supply hydrogen through hydrolysis process or realize hydrogen-to-electricity conversion via anodic oxidation reaction of direct borohydride fuel cells (DBFCs). However, the realization of practical hydrogen applications heavily depends on the effective synthesis of high-purity LiBH4 and recycling of the spent fuels (LiBO2·xH2O). The present work demonstrates a convenient and high-efficiency solvent-free strategy for regenerating LiBH4 with a maximum yield close to 80%, by retrieving its by-products with MgH2 as a reducing agent under ambient conditions. Besides, the hydrogen released from the regeneration course can completely compensate the demand for consumed MgH2. The isotopic tracer method reveals that the hydrogen stored in LiBH4 comes from both MgH2 and coordinated water bound to LiBO2. Here, the expensive MgH2 can be substituted with the readily available and cost-effective MgH2−Mg mixtures to simplify the regeneration route. Notably, LiBH4 catalyzed by CoCl2 can stably supply hydrogen to proton exchange membrane fuel cell (PEMFC), thus powering a portable prototype vehicle. By combining hydrogen storage, production and utilization in a closed cycle, this work offers new insights into deploying boron-based hydrides for energy applications.

Sofia G. Simoes, Filipa Amorim, Gildas Siggini et al.

Climate and weather conditions influence energy demand. as well as electricity generation, especially due to the strong development of renewable energy. The changes of the European energy mix, together with ongoing climate change, raise a number of questions on impact on the electricity sector. In this paper we present results for the whole of the European power sector regarding on how considering current and future climate variability affects the results of a TIMES energy system model for the whole European power sector (eTIMES-EU) up to 2050. For each member-state we consider six climate projections to generate future capacity factors for wind, solar and hydro power generation. as well as temperature impact on electricity demand for heating and cooling. These are input into the eTIMES-EU model to assess how climate affects the optimal operation of the power system and if current EU-wide RES and emissions target deployment may be affected. Results show that although at EU-wide level there are no substantial changes, there are significant differences in countries RES deployment (especially wind and solar) and in electricity trade.

L. Madhuanand, P. Sadavarte, A.J.H. Visschedijk et al.

Coal is a principal source of energy and the combustion of coal supplies around one-third of the global electricity generation. Coal mines are also an important source of CH4 emissions, the second most important greenhouse gas. Monitoring CH4 emissions caused by coal mining using earth observation will require the exact location of coal mines. This paper aims to determine surface coal mines from satellite images through deep learning techniques by treating them as a land use/land cover classification task. This is achieved using Convolutional Neural Networks (CNN) that has proven to be capable of complex land use/land cover classification tasks. With a list of known coal mine locations from various countries, a training dataset of “Coal Mine” and “No Coal Mine” image patches is prepared using Sentinel-2 satellite images with 13 spectral bands. Various pre-trained CNN network architectures (VGG, ResNet, DenseNet) are trained and validated with our prepared coal mine dataset of 3500 “Coal Mine” and 3000 “No Coal Mine” image patches. After several experiments with the VGG network combined with transfer learning is found to be an optimal model for this task. Classification accuracy of 98% has been achieved for the validation dataset of the pre-trained VGG architecture. The model produces more than 95% overall accuracy when tested on unseen satellite images from different countries outside the training dataset and evaluated against visual classification.

Mohammad H. Soliman, Hossam E.A. Talaat, Mahmoud A. Attia

Future trends are increasingly directed towards replacing traditional energy sources by new and renewable energy ones, with Wind Energy coming first in the row of these sources worldwide. The Egyptian electric power system still has a relatively low penetration level, around 3%, of Wind Energy to its generation mix. However, it is planned to increase this ratio to 14.6% by the year 2035. This paper studies the frequency dynamics associated with significant penetration levels of Wind Energy into the Egyptian grid, which leads to reducing the overall system inertia. The control strategy adopted depends on maximizing the wind energy contribution to frequency control, in order to compensate that reduction of system inertia. The Real data of the Egyptian power system model used is verified by the National Electricity Control Centre, updated to the latest values declared and tested under the lowest and highest loads recorded. A modified control loop is added to the control system in order to allow the Wind Energy Conversion System to significantly contribute to the Load Frequency Control. The PI controller gains used in that loop are tuned using three methods; Local Unimodal Sampling, Harmony Search Algorithm and Equilibrium Optimizer (EO). The Equilibrium Optimizer (EO) proved its superiority to the other methods, as it gave the best dynamic response. The simulated results are presented using MATLAB/SMULINK.

Nir Regev, Dov Wulich

Human presence detection is an application that has a growing need in many industries. Hotel room occupancy is critical for electricity and energy conservation. Industrial factories and plants have the same need to know the occupancy status to regulate electricity, lighting, and energy expenditures. In home security there is an obvious necessity to detect human presence inside the residence. For elderly care and healthcare, the system would like to know if the person is sleeping in the room, sitting on a sofa or conversely, is not present. This paper focuses on the problem of detecting presence using only the minute movements of breathing while at the same time estimating the breathing rate, which is the secondary aim of the paper. We extract the suspected breathing signal, and construct its Fourier series (FS) equivalent. Then we employ a generalized likelihood ratio test (GLRT) on the FS signal to determine if it is a breathing pattern or noise. We will show that calculating the GLRT also yields the maximum likelihood (ML) estimator for the breathing rate. We tested this algorithm on sleeping babies as well as conducted experiments on humans aged 12 to 44 sitting on a chair in front of the radar. The results are reported in the sequel.

Muhammad Alifyan Zulkarnain, Muhammad Fajri Raharjo, Meylanie Olivya

The conventional question and answer method has limited time, space and level of understanding from each student so that it becomes an obstacle to the ineffective teaching and learning process. Global pandemic events that have a negative impact on the education sector. So that the teaching and learning process is temporarily stopped at school and diverted online. This study aims to produce a chatbot application as a media for distance learning that helps the teaching and learning process of teachers and students . In practice, This research uses telegram as a chatbot media. The method used for data collection is by interview, literature study, and observation. Testing will be carried out with a black box, calculation of accuracy, and a user acceptance test in the form of distributing questionnaires. The results of this study produce a Chatbot Application as an E-Learning Media for Students that can help teachers in providing distance learning to students efficiently and easily.

Attakorn Asanakham, Thoranis Deethayat

Two types of hybrid photovoltaic/thermal (PV/T) modules, with and without glass cover for generating hot water and electricity (combined heat and power, CHP) were tested to investigate power generation performance in terms of generated power (Pe) with module temperature (Tm) and solar radiation level (IT); and thermal performance in terms of thermal efficiency (ηm) with(Tfi−Ta)∕IT. A method for calculating the hot water temperature and the generated power was also developed and the results agreed well with the experimental data. With the model, the effect of water mass flow rate on the energy outputs was carried out by exergy analysis. It could be found that low second law efficiency was found with higher mass flow rate at low solar radiation level and high inlet water temperature. Keywords: Photovoltaic/thermal module, Combined heat and power, Performance analysis, Exergy, Water flow rate

Tomasz Jasiński

The paper addresses the issue of modelling the demand for electricity in residential buildings with the use of artificial neural networks (ANNs). Real data for six houses in Switzerland fitted with measurement meters was used in the research. Their original frequency of 1 Hz (one-second readings) was re-sampled to a frequency of 1/600 Hz, which corresponds to a period of ten minutes. Out-of-sample forecasts verified the ability of ANNs to disaggregate electricity usage for specific applications (electricity receivers). Four categories of electricity consumption were distinguished: (i) fridge, (ii) washing machine, (iii) personal computer, and (iv) freezer. Both standard ANNs with multilayer perceptron architecture and newer types of networks based on deep learning were used. The simulations included over 10,000 ANNs with different architecture (number of neurons and structure of their connections), type and number of input variables, formulas of activation functions, training algorithms, and other parameters. The research confirmed the possibility of using ANNs to model the disaggregation of electricity consumption based on low frequency data, and suggested ways to build highly optimised models.

Ida Bagus Ketut Sugirianta, I Gusti Ngurah Agung Dwijaya Saputra, I Gusti Agung Made Sunaya

Generally, an off-grid solar power model was applied widely to areas with no electrical network exist for storing energy during the day and using it at night. This model uses a central inverter for several photovoltaic modules, which produces high and dangerous DC voltages, and also has large sizes and high prices. In this study, on-grid solar system model based on micro inverter is built that can use for purposes of teaching material that directly connected to the electrical grid with no batteries or chargers, thereby reducing investment costs and suitable to be applied in the community. Small sized micro inverters can be installed directly under the solar module and also generate AC voltage that can be directly used for own use or sold to PLN. The module that is built is an on-grid solar photovoltaic 300 wp model  using a 300 watt micro inverter and equipped with an electric load in the form of a light bulb and socket outlet. For data retrieval, this model is connected to the PLN network through household electricity customers with 1300 VA power. The result of measurement this solar power model cangenerate the maksimum electric power is 142.37watt and can distribute electric power to PLN  around 115,41 watt. This PLTS model is ready to be use  for purposes of teaching material and also for promotion to community  about model of on-grid PLTS that having economy value so can support goverment in achieving the national target in the renewable energy field.

Dariusz Mikielewicz, Krzysztof Kosowski, Karol Tucki et al.

The use of various biofuels, usually of relatively small Lower Heating Value (LHV), affects the gas turbine efficiency. The present paper shows that applying the proposed air by-pass system of the combustor at the turbine exit causes tan increase of efficiency of the turbine cycle increased by a few points. This solution appears very promising also in combined gas/steam turbine power plants. The comparison of a turbine set operating according to an open cycle with partial bypassing of external combustion chamber at the turbine exit (a new solution) and, for comparison, a turbine set operating according to an open cycle with a regenerator. The calculations were carried out for different fuels: gas from biomass gasification (LHV = 4.4 MJ/kg), biogas (LHV = 17.5 MJ/kg) and methane (LHV = 50 MJ/kg). It is demonstrated that analyzed solution enables construction of several kW power microturbines that might be used on a local scale. Such turbines, operated by prosumer’s type of organizations may change the efficiency of electricity generation on a country-wide scale evidently contributing to the sustainability of power generation, as well as the economy as a whole.

Wenbin Wang, Yusuf Shi, Chenlin Zhang et al.

The increasing demand for energy and clean water has become a grand global challenge. Here the authors develop a membrane-distillation device that exploits sunlight and the heat dissipated by an integrated solar cell unit, enabling simultaneous efficient production of electricity and drinkable water.