Results 171 to 180 of about 41,512 (263)

Lifetime Analysis of Grid‐Tied Photovoltaic System Considering DC–DC Converter Ripple and Efficiency

Energy Science &Engineering, EarlyView.
This work presents a comprehensive lifetime analysis of a two‐stage grid‐tied photovoltaic (PV) system by incorporating critical factors such as input current ripple and operating voltage variations, which are often neglected in conventional studies.
Surla Vishnu Kanchana Naresh, Sankar Peddapati, Praveen Kumar Bonthagorla   +2 more
wiley   +1 more source

Response of a <i>Chloroidium saccharophilum</i> Strain to Extreme Conditions of the Atacama Desert. [PDF]

Biology (Basel)
Lobos N, Igor D, Cepeda N, Ramirez L, Díaz JP.   +4 more
europepmc   +1 more source

Influence of Structural and Environmental Parameters on Solar Air Collector Performance

Energy Science &Engineering, EarlyView.
Increasing air gap depth and mass flow rate significantly enhances the thermal performance of solar air collectors, with optimal performance achieved at an 8.5 cm air gap and 0.01318 kg/s mass flow rate. Air gap depth is identified as the dominant factor influencing system efficiency.
Quankun Zhu, István Farkas, János Buzas   +2 more
wiley   +1 more source

Treatment of periodontal biofilms via nitric oxide-augmented phototherapy. [PDF]

J Oral Microbiol
Johnson CR, Ramrattan TD, Schaefer CJ, Kumar R, Reinhard SJ, Wallet SM, Schoenfisch MH.   +6 more
europepmc   +1 more source

Tree‐Boost–Guided CNN–BiLSTM–Transformer for Solar Irradiance Forecasting: Cross‐Regional Evidence for Sustainable Energy Planning

Energy Science &Engineering, EarlyView.
This graphical abstract illustrates a reproducible pipeline that combines gradient‐boosting‐based feature selection with a CNN–BiLSTM–Transformer model to forecast solar irradiance across multi‐site satellite and ground datasets, delivering robust, high‐accuracy predictions that support sustainable grid planning and reliable PV integration.
Muhammad Farhan Hanif, Usama Hassan, Javid Hussain, Irfan Ali Khan, Yuldasheva Gulora, Syed Masood Arif Bukhari   +5 more
wiley   +1 more source

Harnessing artificial neural networks for accurate PV system parameters determination: radiation, temperature, and MPPT. [PDF]

Sci Rep
Abdelqawee IM, Selmy M, Ali MN, Abdelfattah AA, Mamdouh W.   +4 more
europepmc   +1 more source

Graph Neural Network‐Based Prediction of Building Energy Consumption

Energy Science &Engineering, EarlyView.
A graph neural network that encodes a multi‐zone building as a graph accurately predicts hourly cooling and heating loads across three distinct climates, outperforming Random Forest and XGBoost baselines and serving as a fast surrogate to EnergyPlus simulations for scalable building energy management.
Ali Maboudi Reveshti, Jamal Dabbagh, Jhila Nasiri Reveshti, Karim Farajeyan Bonab, Farid Hosseini Mansoub   +4 more
wiley   +1 more source

Photocatalytic Hydrogen Production Driven by Solar Energy: Performance Under Central European Climatic Conditions. [PDF]

Int J Mol Sci
Kluba W, Hauza K, Lewandowska-Andralojc A.   +2 more
europepmc   +1 more source

Hybrid Simulation–Machine Learning Surrogates for Coordinate‐Based Solar and Wind Energy Yield Assessment in Iraq: A Streamlit Decision‐Support Tool

Energy Science &Engineering, EarlyView.
This study integrates climatic simulations with machine learning to predict solar and wind energy across Iraq. Results show Random Forest excels for solar (R2 = 0.98) and neural networks for wind (R2 = 0.97), enabling a practical web tool for renewable energy planning. ABSTRACT Driven by the global shift away from fossil fuels, solar and wind resources
Bassam Musheer Kareem, Abdolsalam Ebrahimpour, Jafar Ghafouri, Roghayyeh Motallebzadeh   +3 more
wiley   +1 more source

Application of optimal power point tracking technology in distributed grid-connected photovoltaic systems. [PDF]

PLoS One
Yang P, Weng H, Zhong Y.
europepmc   +1 more source