Results 191 to 200 of about 3,125 (265)

Reducing Trade‐Offs of Net Zero Carbon Transitions Through Entrepreneurship and Coordinated Innovation: A Spatially Disaggregated Analysis Across Countries and World Regions

open access: yesSustainable Development, Volume 34, Issue 4, Page 4787-4805, August 2026.
ABSTRACT Transition processes towards a sustainable future benefit from historic perspectives, since feasible changes of socio‐technological conditions and processes depend on a holistic assessment of how actors are embedded in existing institutions, routines, and structures. Building on the Income–Population–Affluence–Technology equation and utilizing
Jessica Kluge, Marcus Wagner
wiley   +1 more source

Climatic Impacts of Large‐Scale Wind Farms in Arid and Semi‐Arid Region in China: A Case Study of the Huitengxile Wind Farm in Inner Mongolia

open access: yesWind Energy, Volume 29, Issue 8, August 2026.
ABSTRACT With the rapid expansion of China's wind power industry, the local climatic impacts of large‐scale wind farms, particularly in arid and semi‐arid regions, have attracted increasing attention. This study investigates the effects of the Huitengxile wind farm in Inner Mongolia, which hosts over 1,200 wind turbines, using high‐resolution numerical
Xiashu Su, Entao Yu, Dongwei Liu
wiley   +1 more source

Energy Infrastructure Futures: A Multiscale Evaluation of Projected Power Plant Siting Across the Western Interconnection

open access: yesEarth's Future, Volume 14, Issue 8, August 2026.
Abstract The US Western Interconnection is facing unprecedented challenges in the form of less predictable peak energy demand, increasingly diverse generating resources, and fast‐growing loads due to the onset of artificial intelligence, hyperscale computing, and electrification.
Kendall Mongird   +7 more
wiley   +1 more source

CESAR: A Convolutional Echo State AutoencodeR for High‐Resolution Wind Forecasting

open access: yesJournal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 4, August 2026.
Abstract An accurate and timely assessment of wind speed and energy output allows an efficient planning and management of this resource on the power grid. Wind energy, especially at high resolution, calls for the development of nonlinear statistical models able to capture complex dependencies in space and time. This work introduces a Convolutional Echo
Matthew Bonas   +3 more
wiley   +1 more source

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