Overview

Small wind turbines can contribute substantially to both a low-carbon energy system, as well as to the autarky and resilience of rural or remote communities and facilities. They can be deployed on building roofs as well as on the ground, and are a useful complement to photovoltaic systems, because they can generate power overnight or in cloudy weather. A range of technologies and designs are available, and suitability depends on the situation, so systematic modelling combined with collection of experience are necessary in making successful, efficient and cost-effective selection decisions. This book is intended for researchers from academia and industry involved with small wind turbines, for small wind turbine manufacturers, as well as for wind power experts and power grid operators. Edited by two renowned wind power experts and written by an international author team, chapters cover standard development, aeroelastic modelling, tail fin dynamics, small blade manufacturing, from sustainable materials, small ducted wind turbines, low tip speed ratio design, high latitude and arid area applications, distributed wind systems, small wind turbines in microgrids, as well as planning and siting, and including case studies describing the manufacture and installation of small wind turbines.

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9781837249923

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Author Information

Mark Runacres is a professor of fluid mechanics at the Faculty of Engineering of the Vrije Universiteit Brussel in Belgium. His main research interest is in the physical and data-driven modelling of unsteady fluid mechanics. He is a past member of IEA Task 27 on small wind turbines in high-turbulence sites and a present member of IEA Task 41 on distributed wind energy. David Wood is an emeritus professor of renewable energy with the Department of Mechanical and Manufacturing Engineering, University of Calgary, Canada. He received his PhD degree in aerodynamics from Imperial College London in 1980. His research interests are in small wind turbines and other forms of renewable energy, including resource assessment and forecasting.

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