Wind Power

In a significant advancement for the wind energy sector, researchers have unveiled a new method for optimizing epicyclic gearboxes, a crucial component in enhancing the efficiency of wind turbines. Led by Željko Vrcan from the Department of Engineeri

In an era where the urgency of addressing climate change is palpable, a groundbreaking study published in ‘Atmosphere’ sheds light on how machine learning can transform the renewable energy landscape. Led by Bankole I. Oladapo from the School of Scie

In a significant advancement for the renewable energy sector, new research has shed light on the impacts of wind farms on land surface temperature (LST) in northern Zhangjiakou, Hebei. Conducted by Xingyue Ma and colleagues from the Key Laboratory of

Recent research conducted by Xin Xia from the Key Laboratory of Land Surface Process and Climate Change in Cold and Arid Regions at the Northwest Institute of Eco-Environment and Resources has unveiled significant insights into the impact of wind far

The expansion of wind power generation has sparked a growing interest in understanding its broader implications, particularly on local climates. A recent study led by Ze Ai from the National Climate Center of China Meteorological Administration sheds

Colombia, a country traditionally reliant on hydroelectric power, is now exploring the vast potential of wind energy, particularly in the arid region of La Guajira. A recent study led by Juan Carlos Perafan-Lopez from

A new research article has unveiled a groundbreaking approach to optimizing integrated energy systems, focusing on the uncertainties associated with distributed generation (DG) from renewable sources like wind and solar power. This study, led by Jian

In a significant advancement for the wind energy sector, a recent study led by Xin Wang has introduced an improved methodology for cleaning wind speed and power data collected from wind turbines. This research, published in the journal “Journal of In

In a significant advancement for the renewable energy sector, researchers have introduced an innovative method for forecasting wind power using an emotional neural network (ENN). This approach, spearheaded by Guoling Zhang, aims to enhance the accura

Recent advancements in energy harvesting networks are promising to reshape the landscape of renewable energy utilization, as highlighted in a groundbreaking study published in ‘Tongxin xuebao’ (Journal of Communication). The research, led by Zhe Wang