Results 151 to 160 of about 678,166 (199)

A Resilience‐Based Reward‐Penalty Scheme for Hardening Electricity Distribution Assets Against High‐Impact, Low‐Probability Disasters

open access: yesEnergy Science &Engineering, EarlyView.
This paper introduces a novel resilience‐based reward‐penalty scheme (RPS) for electricity grids facing high‐impact, low‐probability (HILP) disasters. By modeling the costs of proactive asset immunization against reactive RPS penalties, our analysis conclusively demonstrates that long‐term investment in grid resilience is the more economically rational
Amirhossein Yousefi Joobeni, Reza Dashti
wiley   +1 more source

A Simplified Two‐Vector Approach for Common‐Mode Voltage Reduction in Model Predictive Control Drives of Permanent Magnet Synchronous Motor

open access: yesEnergy Science &Engineering, EarlyView.
In this study, a modified model predictive control scheme is proposed, in which a dedicated weighting factor is incorporated into the cost function to explicitly account for common‐mode voltage (CMV) effects during the control process. This modification leads to a significant reduction—up to 40%—in the magnitude of the generated CMV.
Javad Amini, Reza Roshanafekr
wiley   +1 more source

Selecting Between Hydrogen and Methanol for Fuel Cell‐Organic Rankine Cycle Hybrid Power Systems: A Comparative 4E Analysis

open access: yesEnergy Science &Engineering, EarlyView.
A 4E comparison of PEMFC‐ORC and DMFC‐ORC systems shows that PEMFC‐ORC achieves 21% higher energy efficiency, while DMFC‐ORC obtains 31% higher exergy efficiency and 57% lower levelized cost of electricity. However, DMFC‐ORC emits nearly twice the annual carbon dioxide equivalent of PEMFC‐ORC.
Zahra Piryaei   +2 more
wiley   +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

Use of medicinal herbs in an Iranian population: cross-sectional findings from the Fasa PERSIAN Cohort Study. [PDF]

open access: yesBMJ Open
Mosavat SH   +9 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

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

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