Urban wind resource assessment : predicting the turbulence intensity, excess energy available and performance of roof mounted wind turbines in a built environments

De-centralised renewable energy power generation is proposed to be a significant part of the future of electricity generation technology, with wind energy playing a significant role. With half of the global population residing in urban and suburban areas, the opportunity for individuals or small org...

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Bibliographic Details
Main Author: Emejeamara, Francis Chimeziri
Other Authors: Tomlin, Alison S.
Published: University of Leeds 2017
Subjects:
Online Access:https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.714293
Description
Summary:De-centralised renewable energy power generation is proposed to be a significant part of the future of electricity generation technology, with wind energy playing a significant role. With half of the global population residing in urban and suburban areas, the opportunity for individuals or small organisations to generate power locally facilitates the decrease in losses associated with long distance electricity generation and transmission. Small-scale wind turbine applications within suburban/urban areas are exposed to high level of gust and turbulence compared to flow over less rough surfaces (e.g. coastal/offshore areas, open grasslands, rural areas, etc.). There is, therefore, a need for such systems not only to cope with, but to thrive under such rapidly fluctuating, complex urban wind conditions. Assessing the potential of a proposed urban wind turbine project is hindered by insufficient assessment of both the urban wind resource and power capabilities of certain turbine designs within a potential suburban/urban site. This, however, requires estimation of important factors such as local atmospheric turbulence, total energy available to the turbine system and the potential power output to be generated should a certain turbine system design be installed within a potential site. The research presented in this thesis proposes a methodology for scoping the potential of small wind turbines within a built environment through effective assessment of the urban wind resource and power capabilities of small turbine systems. The aim is to address the lack of accurate and affordable methods for site viability assessment of small wind turbines within a built environment. This methodology encompasses three sub-models which estimate the local atmospheric turbulence (represented by the turbulence intensity, T.I.), additional energy within the gusty urban wind (represented by the excess energy content, EEC) and the turbine power capability at different heights within a potential site. Firstly, to quantify the influence of location on the total energy available to a small wind turbine at a potential site, an in-depth evaluation of the urban wind resource is completed. This includes the development of methods to predict the local atmospheric turbulence at a given turbine mast height, and the additional energy available to the turbine which is usually under represented when using assessments based only on mean wind speeds. This is achieved using high temporal resolution wind measurement datasets from eight potential turbine sites within the urban and suburban environments and LiDAR building height datasets from three major UK cities namely, Leeds, Manchester and London. Subsequently, new analytical models are developed that allow the mapping of atmospheric turbulence and excess energy at different heights over Leeds, Edinburgh, Manchester and London by combining the T.I. and EEC estimation models with currently available methods of predicting mean wind speeds over urban areas. The results from these two models highlight the importance of including building height variation and changes in wind direction within the assessment, and also the value of employing detailed building geometric data as model inputs. A simple low-cost 2-D multiple streamtube vertical axis wind turbine (VAWT) model capable of simulating turbine performance in a fluctuating wind isdeveloped. Combining this VAWT model with dynamic stall features and variable speed control strategy, enables a system based design of wind turbines operating within suburban/urban environment. A method of estimating the performance of a turbine operation within an urban wind resource is developed by assessing the power capabilities of the VAWT model using high-resolution wind measurement datasets as model inputs. This is combined with the T.I. and EEC estimation models in developing a new model known as the turbine power estimation (TPE) model used in mapping turbine performance at different heights over Leeds, Edinburgh, Manchester and London. Comparison between the TPE model and a generic power curve is made, hence suggesting the possibility of using a simple model to estimate the power capabilities of a certain turbine design while accounting for local turbulence within an urban wind resource. Finally, the investigation of the cumulative potential of small wind turbine power generation in Leeds, Edinburgh, Manchester and London indicates a largely untapped wind resource available (represented by high EEC values estimated within small distances in each city) which could be harnessed if gust tracking solutions were to be commercially available. It also highlights the importance of site viability assessment and its financial implications illustrated by capacity factor maps over the four cities, which has practical value for turbine manufacturers and urban planners alike. Thus, for urban wind applications to achieve their optimum deployment potential, this research study proposes a simple, effective and affordable tool for preliminary scoping the potential of certain small wind turbine designs within a suburban/urban environment, and hence encouraging effective carbon savings. In order to maximize the impact of this research study, it would be valuable that these maps be extended to other towns/cities and made available and easily accessible to individuals and interested parties, and hence this is a major objective of future work.