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Wind energy has been explored as a viable alternative to fossil fuels in many small island developing states such as those in the Caribbean for a long time. Central to evaluating the feasibility of any wind energy project is choosing the most appropriate wind speed model. This is a function of the metric used to assess the goodness of fit of the statistical models tested. This paper compares a number of common metrics then proposes an alternative to the application-blind statistical tools commonly used. Wind speeds at two locations are considered: Crown Point, Tobago; and Piarco, Trinidad. Hourly wind speeds over a 15-year period have been analyzed for both sites. The available data is modelled using the Birnbaum-Saunders, Exponential, Gamma, Generalized Extreme Value, Generalized Pareto, Nakagami, Normal, Rayleigh and Weibull probability distributions. The distributions were compared graphically and their parameters were estimated using maximum likelihood estimation. Goodness of fit was assessed using the normalised mean square error testing, Chi-squared testing, Kolmogorov-Smirnov, R-squared, Akaike information criteria and Bayesian information criteria tests and the distributions ranked. The distribution ranking varied widely depending on the test used highlighting the need for a more contextualized goodness of fit metric. With this in mind, the concept of application-specific information criteria (ASIC) for testing goodness of fit is introduced. This allows distributions to be ranked by secondary features which are a function of both the primary data and the application space.

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This chapter describes a Percolator model as a framework within which ICT solutions may be contemplated for communities under threat of digital exclusion. The model partitions the problem into manageable domains, within which realistic and appropriate ICT solutions may be progressively distilled. It gives an account of the generic attributes of information and communications and the manner in which these attributes map onto technical parameters of ICT. The model places a great deal of emphasis on contextualization, drawing on the Sustainable Livelihood Approach for intervention in economically poor communities. Its domains variously take account of the national or provincial developmental objectives in particular politico-cultural contexts as well as the social character of communities and their physical nature. Ultimately, contextualized technical parameters are used as the basis on which solutions are selected from among the available range of information and communications technologies. The general framework of the Percolator model is not limited to ICT. It may be applied to intervention based on a variety of technologies. 115 C H A P T E R 61 The authors acknowledge, with gratitude, the contribution of Akash Pooransingh in the acquisition of supporting resources for this work.