Results 141 to 150 of about 276 (163)
Energy Science &Engineering, EarlyView.ABSTRACT Accurate long‐term wind speed forecasting is pivotal for the strategic planning of renewable energy infrastructure, particularly for assessing the techno‐economic feasibility of wind‐powered green hydrogen facilities. However, capturing the complex spatiotemporal dependencies in climate data remains a significant challenge. This study proposes
Iman Baghaei +2 more
wiley +1 more source
Energy Consumption and CO2 Emissions Forecasting of Transport Sector Using Machine Learning
Energy Science &Engineering, EarlyView.The transport sector accounts for approximately one‐quarter of Iran's final energy consumption. The energy demand in this sector has the least variation, with petroleum products accounting for more than 85% of the demand. Furthermore, the accelerated growth of energy consumption and the sector's reliance on fossil fuels, which are the main cause of ...
Amir Hossein Akbari +2 more
wiley +1 more source
Energy Science &Engineering, EarlyView.This study establishes an environmental thermoeconomic cost model to investigate the impact of two IAC technologies on the performance of a GSCC from three aspects of energy, economy, and environment. Under arid climate conditions, the SEC technology demonstrates superior performance in terms of cost‐effectiveness and environmental impact.
Zhen Wang, Li Zhang, Yu Ni, Liqiang Duan
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Energy Science &Engineering, EarlyView.This graphical abstract summarizes the proposed framework for improving short‐term residential natural gas consumption forecasting by integrating a novel socioeconomic indicator, the subscription growth ratio (SGR), with conventional meteorological variables.
Ali Pirzad, Mostafa Khanzadi
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Energy 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
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Energy 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
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Energy 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
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 +4 more
wiley +1 more source
Food Chemistry International, EarlyView.ABSTRACT Rice (Oryza sativa L.) is a vital staple crop for nearly half the world's population. This study investigates the levels of aflatoxins (AFB1, AFB2, AFG1, and AFG2) and selected heavy metals (Cd, Pb, and Cr) and essential elements (Mn, Fe, Mg, Cu, and Zn) in rice varieties cultivated in Fogera, Amhara Region, Ethiopia.
Melese Tilahun +3 more
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Colonial and gendered peace: Decolonial perspectives on peace in Nagorno‐Karabakh
Feminist Anthropology, EarlyView.Abstract This article critically interrogates peace processes in the aftermath of the First Nagorno‐Karabakh War by centering the lived experiences and political voices of Armenian and Azerbaijani internally displaced and refugee women, based on ethnographic fieldwork and in‐depth interviews conducted in 2019.
Ramil Zamanov
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