L.S. Blunden

Tidal energy resource assessment for tidal stream generators

Abstract This article is a review of the current understanding of tidal energy resources in the context of the emerging technology of tidal stream power generation. The geographical focus is on the north-west European continental shelf, the scope of a number of published reports on exploitable tidal stream energy resources. These estimates are reviewed as are some analytical models of energy extraction by tidal stream generators.

Comparing Energy Yields From Fixed and Yawing Horizontal Axis Marine Current Turbines in the English Channel

At many locations with high tidal stream velocities – and potential for tidal stream energy generation – the flow is approximately rectilinear, that is to say the flow direction is always 0 degrees or 180 degrees with respect to a particular orientation. At some sites, however, there is an appreciable change in flow direction (‘swing’) away from 180 degrees between the two maxima of flow speed. In order to assess the performance of horizontal axis marine current turbines in non rectilinear currents, measurements of a model rotor have been made in a towing tank. Curve fits have been calculated as a function of the cosine of the yaw angle squared and the thrust as cosine of the yaw angle. The curve fits have been used in a case study to investigate the impact of fixed-orientation or yawing rotor designs on average annual energy output, at three locations in the English Channel. All three sites are of the type where flow is accelerated around a headland or cape, but their tidal streams vary in deviation from rectilinearity. For two of the sites - Portland Bill (Dorset, UK) and Race of Alderney (Alderney, Channel Islands/Normandy, France) - available data consisted of tidal stream diamonds printed on Admiralty navigational charts. These rely on local tidal elevations for interpolation of tidal streams. At the other site – St. Catherine’s Point, Isle of Wight, Hampshire – current meter measurements of duration one month were available from the British Oceanographic Data Centre (BODC), allowing a direct tidal analysis. …

Dataset of the livability performance of the City of Birmingham, UK, as measured by its citizen wellbeing, resource security, resource efficiency and carbon emissions

This data article presents the UK City LIFE1 data set for the city of Birmingham, UK. UK City LIFE1 is a new, comprehensive and holistic method for measuring the livable sustainability performance of UK cities. The Birmingham data set comprises 346 indicators structured simultaneously (1) within a four-tier, outcome-based framework in order to aid in their interpretation (e.g., promote healthy living and healthy long lives, minimize energy use, uncouple economic vitality from CO2 emissions) and (2) thematically in order to complement government and disciplinary siloes (e.g., health, energy, economy, climate change). Birmingham data for the indicators are presented within an Excel spreadsheet with their type, units, geographic area, year, source, link to secondary data files, data collection method, data availability and any relevant calculations and notes. This paper provides a detailed description of UK city LIFE1 in order to enable comparable data sets to be produced for other UK cities. The Birmingham data set is made publically available at http://epapers.bham.ac.uk/3040/ to facilitate this and to enable further analyses. The UK City LIFE1 Birmingham data set has been used to understand what is known and what is not known about the livable sustainability performance of the city and to inform how Birmingham City Council can take action now to improve its understanding and its performance into the future (see “Improving city-scale measures of livable sustainability: A study of urban measurement and assessment through application to the city of Birmingham, UK” Leach et al. [2]).

City-wide building height determination using light detection and ranging data

The research presented in this paper addresses a current gap in the availability of building geometry data and provides estimates of individual building characteristics at city scale. Such data are crucial for a wide range of subjects such as modelling building energy consumption as well as regional housing market studies. However, such data are currently not available in the UK. In this work, a new approach was developed to automatically estimate the geometric characteristics of buildings, including height and floor count. A wide range of datasets have been brought together including high-resolution light detection and ranging data to accurately estimate building elevation and to obtain the external dimension of buildings. In the UK, most of the datasets required for this model are available for urban areas, allowing the model to be widely applied both in cities and beyond. The paper presents the results of building height and floor count determined from this model and compares these with the actual data obtained from a survey of 108 representative buildings in the city of Southampton. The results show good accuracy of the model with 97% of the estimates having an error under ±1 floor and an absolute mean error of 0.3 floors. These results provide confidence in utilising this model for future building studies at a city scale.