Results 201 to 210 of about 17,231 (264)

Optimized Dual ANN Control Technique for Efficient Energy Management System (EMS) of Microgrid

open access: yesEnergy Science &Engineering, EarlyView.
Proposed methodology. ABSTRACT The escalating global energy demand necessitates a shift towards sustainable and environmentally friendly alternatives. While renewable energy sources like solar and wind energy offer promising solutions, their intermittent nature poses significant challenges for grid integration.
Bin Li   +5 more
wiley   +1 more source

POWER: Performance Optimization With Evaluated Results for HEV Battery Selection via MCDM‐TOPSIS

open access: yesEnergy Science &Engineering, EarlyView.
ABSTRACT The increasing transportation demands and environmental concerns in India necessitate the selection of optimal battery technologies for hybrid electric vehicles (HEVs). As the fifth‐largest car market globally, India faces rising vehicle demand, while the transportation sector remains a major contributor to air pollution.
Rinku Kumar Roy   +5 more
wiley   +1 more source

Machine Learning‐Driven Classification and Production Capacity Prediction of Tight Sandstone Reservoirs: A Case Study of the Taiyuan Formation, Ordos Basin

open access: yesEnergy Science &Engineering, EarlyView.
On the basis of core and log data, a Bayesian‐Optimized Random Forest model achieved 92.76% accuracy in classifying tight sandstone reservoirs. A gray relational analysis‐derived evaluation index shows > 80% consistency with actual gas zones. ABSTRACT Tight sandstone gas (TSG), an unconventional oil–gas resource, has heterogeneous reservoirs ...
Yin Yuan   +8 more
wiley   +1 more source

Experimental Investigation of Sensitivity for Coal and Gas Outburst Risk Prediction Indexes in Raw and Tectonic Composite Coal Seams

open access: yesEnergy Science &Engineering, EarlyView.
A comparative study was conducted on gas desorption laws of raw and tectonic coals. The sensitivity of regional and local outburst prediction indexes was compared. Gas content is more sensitive than gas pressure for composite coal seams. K1 can more accurately predict the outburst danger than Δh2 $\Delta {h}_{2}$ in composite coal seams.
Haijun Guo   +4 more
wiley   +1 more source

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