Results 151 to 160 of about 27,207 (253)

Biomass‐derived hydrochars as eco‐friendly adsorbents for wastewater treatment applications

open access: yesEnvironmental Progress &Sustainable Energy, EarlyView.
Abstract Emerging organic pollutants (EOPs), such as diethyl phthalate (DEP), bisphenol A (BPA), and methylene blue (MB), are only partially removed in conventional wastewater treatment plants. This study assesses hydrochars produced by hydrothermal carbonization (HTC) of spruce bark (SB), vine shoots (VSs), and wheat straw (WSs) for removing three ...
Emanuel Gheorghita Armanu   +6 more
wiley   +1 more source

A Novel Bipolar DC Connection Strategy for Photovoltaic Power Plants With a 50% Reduction in DC Cabling Length

open access: yesEnergy Science &Engineering, EarlyView.
Bipolar configuration is a new topology in the direct current (DC) system of photovoltaic power plants, which is topologically analogous to the bipolar configuration utilised in High‐Voltage Direct Current power transmission systems. DC cable length and copper usage are reduced by 50% using a bipolar configuration.
Duško M. Tovilović   +2 more
wiley   +1 more source

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

open access: yesEnergy 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   +5 more
wiley   +1 more source

Alleropathy in cool-seasons turf grass

open access: yesJournal of Japanese Society of Turfgrass Science, 2002
Noma., Y.   +3 more
openaire   +1 more source

Graph Neural Network‐Based Prediction of Building Energy Consumption

open access: yesEnergy 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   +4 more
wiley   +1 more source

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

open access: yesEnergy 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   +3 more
wiley   +1 more source

Integrated Solar and Wind Energy Systems for Domestic Power Generation and CO2 Emissions Reduction

open access: yesEnergy Science &Engineering, EarlyView.
A well‐structured and sequentially methodical procedure for evaluating the Wind and Photovoltaic Hybrid Energy System‐based technical, environmental, and economic viability. This study investigates the integration of solar photovoltaic(PV) and wind energy systems for domestic electricity generation in the Gaza Strip.
Mohamed Elnaggar   +9 more
wiley   +1 more source

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