Hasil untuk "Electricity"

P. McCarty, J. Bae, Jeonghwan Kim

I. Ozturk

D. Pant, Gilbert Van Bogaert, L. Diels et al.

G. Strbac

L. Bell

N. Cambridge

Christie Claire D. BOISER, Lance Arthur Lim CARPIO, Philip Jun S. CELERINOS et al.

The key role of the gravitational water vortex turbine (GWVT) is to generate electricity to support modern civilization in their essential daily needs by harnessing kinetic energy from flowing water. With this, the lack of access to electricity can be addressed by utilizing the potential of the Philippines’ abundant bodies of water. This study evaluates the impact of low-density turbine blades on the GWVT with reference to the selected parameters: rotational speed and mechanical efficiency. The ANSYS simulation and laboratory test both found that the 0.55 ratio between the diameters of the nylon rod blade and the optimized basin with guide vanes achieved the highest rotational speed of 205.95 RPM and 120.1 RPM, respectively. Conversely, the design with a 0.60 ratio between the diameters of the steel blade and the normal basin provided optimum performance, achieving an average of 98.2 RPM and the highest mechanical efficiency of 43.75%, thereby preventing energy loss and maximizing output performance. Results also indicated a significant difference in the performance of the GWVT using the normal basin compared to the optimized basin with guide vanes. Lastly, there was a considerable difference in the performance of the GWVT for the design ratios of 0.55, 0.60, and 0.65 for the runner blade and basin, and further analysis showed that torque and rotational speed have a linear relationship. Thus, this study could serve as a benchmark for identifying alternative materials and optimizing the design of GWVT to help improve power generation using hydropower as a source of electricity.

Abdul Muin, Moh. Zaiful Rosyid, Habibur Rahman et al.

The escalating global environmental crisis demands active participation from educational institutions, particularly Islamic institutions with unique theological foundations for environmental stewardship. This research addresses the gap between Islamic values and modern environmental management by analyzing the innovative “Eco-Pesantren Model” at SMPI Mambaul Ulum, identifying implementation mechanisms, and evaluating impacts on students’ environmental awareness. Using qualitative case study methodology with participatory observation, in-depth interviews with 25 key informants, and document analysis, this research develops an integrated model combining spiritual transformation with practical environmental management. The study introduces “Ecological Tauhid” concept, integrating modern environmental principles with Islamic values through Contextual Environmental Fiqh. Implementation includes four programs: Zero Waste Islami (85% consistent waste sorting), Blessed Energy (40% electricity reduction), Water of Life (ablution water reduction from 12 to 3 liters), and Islamic value-based environmental curriculum (environmental fiqh understanding increased from 72 to 86 points). The “Environmentally Conscious Family” program achieved 78% family participation with 60% plastic waste reduction. This research contributes the “Ecological Tauhid” paradigm as a new framework for Islamic environmental education, providing a replicable model supporting SDGs 4, 13, and 15.

Mukilan P, Balasubramanian M, Jan Petrov et al.

This study introduces a novel method for sustainable energy solutions by creating eco-friendly energy-harvesting tiles that combine renewable energy production with environmental preservation. The suggested tiles include a 30 % replacement of M-sand with torched fly ash, reducing dependence on natural resources while preserving structural integrity and improving thermal performance. The energy-harvesting capability is realised by integrating Solar Photovoltaic (PV) cells, Thermoelectric Generators (TEG), and Piezoelectric crystals, which jointly convert solar radiation, temperature differentials, and mechanical stress into electricity. The performance study indicates that the tiles possess a solar absorption of 0.256, solar reflectance of 0.81, thermal emissivity of 0.86, and a water absorption rate of 5.37 %, assuring durability and resilience against environmental variables. Furthermore, predictive techniques like Support Vector Regression (SVR), Gradient Boosting, and Neural Networks enhanced energy production, with the Neural Networks model exhibiting greater prediction accuracy. The suggested tiles provide a sustainable construction solution by integrating energy production with efficient material use, rendering them appropriate for urban infrastructure and innovative building applications. This dual-focus design tackles energy and environmental issues, fostering sustainable building techniques.

Neska Mirosław, Mrozek Mirosław, Majcher Andrzej

Dwindling fossil fuel resources and the drive to create a closed-loop economy in technological systems are forcing the development of systems managing low-temperature waste heat. This paper presents a system equipped with thermoelectric cells that convert heat into electricity. The prototype system comprises individual MTEG modules and a DC-AC power converter. The MTEG module is a sandwich-like layered structure. The core of the MTEG module consists of twenty TEG thermoelectric elements, with liquid heat exchangers positioned on the hot and cold sides of the TEGs, respectively. The paper presents the results of the verification and validation of the system. The results, which demonstrate the high efficiency of the exchangers and the converter and the flexibility to combine and expand, with the goal to maximise the use of available low-temperature heat. The solution exhibits an energy conversion efficiency of a few per cent, primarily attributable to the low efficiency of the TEGs. However, in numerous industrial applications, it can enhance the exergy of ongoing processes, where substantial amounts of low-temperature heat are dissipated.

Aykut Fatih Güven, Onur Özdal Mengi, Mohit Bajaj et al.

This study proposes an integrated optimization framework for the techno-economic sizing and performance evaluation of a grid-connected hybrid renewable energy system (HRES) comprising photovoltaic (PV) panels, wind turbines (WT), battery storage (BTS), and a diesel generator (DG). A real-world case study is conducted on a university campus in Turkey using high-resolution hourly meteorological and load data over a full year (8760 h). The objective is to minimize the annualized cost of the system (ACS), levelized cost of energy (LCOE), and total net present cost (TNPC), while ensuring high reliability through a constraint on the loss of power supply probability (LPSP) at 0.5 %. The decision variables include the optimal capacities of PV, WT, DG, BT, and inverter components, bounded by technical, economic, and operational constraints, including a minimum renewable energy fraction (REF) requirement. The system's energy production, storage, and grid interactions are modeled using detailed mathematical formulations. Optimization is performed using the Moth-Flame Optimization Algorithm (MFOA) and benchmarked against the Whale Optimization Algorithm (WOA), Flower Pollination Algorithm (FPA), and Genetic Algorithm (GA). Simulation results identify the PV/WT/BT configuration as the most cost-effective and reliable, achieving an LCOE of $0.1342/kWh, a TNPC of $3.2542 × 10⁶, and an ACS of $2.9214 × 10⁵. These values reflect a 33 % cost reduction compared to the off-grid configuration. Additionally, the system enables annual grid electricity purchases of up to 4.4086 × 10⁵ kWh and sales of up to 1.2114 × 10⁶ kWh. Notably, the achieved LCOE is significantly lower than the prevailing commercial grid tariff of $0.35/kWh in Turkey, demonstrating the financial competitiveness of the proposed system for institutional and commercial users. In terms of algorithmic performance, MFOA outperforms the other methods by delivering the fastest convergence, highest optimization stability, and a fully renewable solution (REF = 100 %) without DG operation. This solution achieves an LCOE of $0.1443/kWh and a TNPC of $3.5085 × 10⁶, which is slightly higher than the absolute minimum cost but demonstrates the ability to reach 100 % renewable penetration without diesel usage. The system also reports the shortest execution time (336.5 s), confirming its suitability for real-time or iterative design tasks. Overall, the proposed HRES configuration offers a technically feasible, economically advantageous, and environmentally sustainable solution for campus electrification and broader smart grid applications, and serves as a replicable decision-support model for renewable energy planning in regions with high electricity tariffs.

Lam Do, Le Viet Phu

Hafiz Ahsan Said, Demian Garcia-Violini, Nicolas Faedo et al.

Optimal control of wave energy converters (WECs), while converting wave energy into a usable form, such as electricity, may <italic>inject</italic> (reactive) power into the system at various points in the wave cycle. Though somewhat counter-intuitive, this action usually results in improved overall energy conversion. However, recent experimental results show that, on occasion, reactive power peaks can be significantly in excess of active power levels, leaving device developers with difficult decision in how to rate the power take-off of the system i.e. whether to cater for these high reactive power peaks, or limit power flow to rated (active) levels. The origins of these excessive power peaks are currently poorly understood, creating significant uncertainty in how to deal with them. In this paper, we show that, using both theoretical results and an illustrative simulation case study, <italic>under matched controller conditions</italic> (impedance-matching optimal condition), for both monochromatic and panchromatic sea-states, that the maximum peak reactive/active power ratio <italic>never exceeds unity</italic>. However, under mismatched WEC/controller conditions, this peak power ratio can exceed unity, bringing unrealistic demands on the power take-off (PTO) rating. The paper examines the various origins of system/controller mismatch, including modelling error, controller synthesis inaccuracies, and non-ideal PTO behaviour, highlighting the consequences of such errors on reactive power flow levels. This important result points to the need for accurate WEC modeling, while also showing the folly of catering for excessive reactive power peaks.

Yun-Sheng Tsai, Chi-Wen Chen, Cheng-Chien Kuo et al.

In recent years, the escalating electricity demand in Taiwan has heightened the prominence and discourse surrounding the issue of power supply. With the enactment of the European climate law, global commitment to achieving net-zero emissions has gained momentum. Concurrently, the Taiwanese government has articulated the Taiwan 2050 net-zero emissions policy. To realize this objective, Taiwan has vigorously promoted renewable energy in recent years, increasing the proportion of renewable energy in its energy mix. However, confronted with the intermittent and unpredictable nature of renewable energy generation, challenges arise concerning the stability and quality of power supply. In response to the impact of integrating renewable energy into the grid, the Taiwan Power Company (Taipower) has introduced the day-ahead ancillary service market. Through this platform, power generation and battery energy storage systems (BESSs) engage in competitive bidding, fostering the integration of diverse distributed energy resources into the system. These resources serve as dispatchable assets for Taipower, contributing to grid stability by providing ancillary services. This study has developed an advanced dynamic regulation reserve controller by employing an industrial PC (IPC) in conjunction with a multifunctional power meter. Through real-time measurement of the power grid frequency by the multifunctional power meter, a sophisticated dynamic frequency reserve control strategy has been devised, taking into account the charging state of energy storage systems. This strategy exhibits high operational quality, effectively regulating the charging and discharging of energy storage systems. In addition to swiftly adjusting the current grid frequency, it encompasses the capability to facilitate the transfer of peak electrical energy. This effectively stabilizes the power grid, alleviating supply pressures during nighttime peaks and enhancing the overall supply stability of the power system.

Aigerim Mamirova, Valentina Pidlisnyuk

<i>Miscanthus</i> × <i>giganteus</i> (<i>M</i> × <i>g</i>) is a promising energy crop in phytotechnology with biomass production. Despite considerable vegetation and harvest under varying climate conditions and across different soils, field-scale studies on utilising <i>M</i> × <i>g</i> remain scarce. Analysing the literature and our own findings, this study intends to highlight the potential of <i>M</i> × <i>g</i> phytotechnology for revitalising non-agricultural lands (NAL), including brownfields, and illustrate the expediency of applying biochar to enhance biomass yield, energy efficiency, and economic feasibility. To validate the feasibility of <i>M</i> × <i>g</i> production on brownfields, two scenarios within the value chain “biomass–biogas–electricity” for green harvest were examined. The assumptions were as follows: (1) a methane yield of 5134 m³ ha⁻¹ y⁻¹, and (2) substrate-specific methane yields of 247 and 283 mL (g oDM)⁻¹ for the first and subsequent years, respectively. The findings suggest that Scenario 2 is better suited for cultivating <i>M</i> × <i>g</i> on brownfields/NAL, being more sensitive and eliminating inaccuracies and the generalisations of results. From the third year onward, the revenue of <i>M</i> × <i>g</i> production on biochar-amended brownfields showed greater potential for future profitability. Future research should confirm the positive trend in the energy efficiency ratio of <i>M</i> × <i>g</i> phytotechnology on a larger scale, particularly in real brownfield applications.

Jan Martin Specht, Reinhard Madlener

This study utilizes machine learning and, more specifically, reinforcement learning (RL) to allow for an optimized, real-time operation of large numbers of decentral flexible assets on private household scale in the electricity domain. The potential and current obstacles of RL are demonstrated and a guide for interested practitioners is provided on how to tackle similar tasks without advanced skills in neural network programming. For the application in the energy domain it is demonstrated that state-of-the-art RL algorithms can be trained to control potentially millions of small-scale assets in private households. In detail, the applied RL algorithm outperforms common heuristic algorithms and only falls slightly short of the results provided by linear optimization, but at less than a thousandth of the simulation time. Thus, RL paves the way for aggregators of flexible energy assets to optimize profit over multiple use cases in a smart energy grid and thus also provide valuable grid services and a more sustainable operation of private energy assets.

Raymond Li, Chi-Keung Woo

M. Basuki Rahmat, Joessianto Eko P, Annas Singgih S et al.

The ship electrification process is the process of installing or providing electric power to supply all the electrical power needs for ships. In general, main electricity supply will be provided, and emergency supplies in the form of batteries or emergency generators that are able to survive supplying emergency loads such as navigation equipment, navigation lights, and emergency lighting for about 3 hours. Another consideration in the electrification process on fishing vessels is also aimed at reducing dependence or even replacing conventional fuel. Of course, not all machines or equipment that are usually operated with conventional fuel can be directly replaced with electrical energy. The implementation of electrification on fishing boats takes into account the technological and cultural aspects of fishermen so that not all of them will be directly replaced by electrical energy.

Qiyou LIN, Wenliang JIANG, Yuanyuan LI et al.

In a DC microgrid system, distributed units are usually connected to the DC bus in a decentralized manner, and distributed power sources and loads are easily affected by the external environment, which degrades the bus voltage stability of the DC microgrid. In order to solve this problem, a coordinated control strategy for DC microgrid system based on bus voltage stratification is proposed in this paper. The strategy builds a DC microgrid system structure mainly based on photovoltaic power generation, and then divides the bus voltage into five levels. Under the corresponding operation mode of each level, the operation mode and the control strategy are studied. Finally, the effectiveness of the proposed control strategy in suppressing the fluctuation of the system bus voltage is verified when the fluctuation of the photovoltaic power generation and the load is caused by the change of environmental factors.

Wei Tan, Xiaoyan Wang, Hongyan He et al.

The absolute radiometric accuracy of earth-observing camera is crucial for the applications of natural resources, environment, agriculture and other industries. To continue the progress in this filed, a lunar surface reflectance based radiometric calibration approach is given in this paper. We chose IIM, M3, SP lunar models as references and GF-4 VNIR camera as sensor under calibrating. The lunar calibration sites were MS-2 site, Apollo-16 site and CE-3 site. The equivalent reflectance models of lunar were retrieved by Multiplying and integrating with the spectral response function of VNIR camera. Absolute radiometric calibrations with the equivalent reflectance models of lunar were carried out for 520–590nm, 630–690nm and 770–890nm spectral bands. The ground-based validation experiments were conducted with low, medium and high reflectance targets. The calibration accuracy was evaluated by comparing the relative errors of derived radiance after radiometric calibration with the benchmarks of TOA radiance transferred by in-situ measured reflectance. Lunar-based calibration models, lab and on-orbit filed-based models were used to compare the relative errors between proposed method and traditional way. The results showed that using IIM lunar model had better radiometric accuracy than other models, and SP model had the similar performance with traditional on-orbit filed-based model. The results indicated that using lunar to calibrate the earth-observing camera had the capability to improve the radiometric calibration accuracy.