Influence of global solar radiation typical days on forecasting models error

Paper presented to the 3rd Southern African Solar Energy Conference, South Africa, 11-13 May, 2015.In this work, we have led an analysis of different global solar radiation forecasting models errors according to the global solar radiation variability. Different predictions models were performed such as machine learning techniques (Neural Networks, Gaussian processes and support vector machines) in order to forecast the Global Horizontal solar Irradiance (GHI). We also include in this study a simple linear autoregressive (AR) model as well as two naïve models based on persistence of the GHI and persistence of the clear sky index (denoted herein scaled persistence model). The models are calibrated and tested with data from three French islands: Corsica (42.15°N ; 9.08°E), Guadeloupe (16.25°N ; 61.58°W) and Reunion (21.15°S ; 55.5°E). Guadeloupe and Reunion are located in a subtropical climatic zone whereas Corsica is in a tempered climatic zone hence, the global solar radiation variation differs significantly. The output error of the different models was quantified by the normalized root mean square error (nRSME). In order to quantify the influence of the global solar radiation variability on the forecasting models error we performed a classification of typical days. Each class of day is defined by a global solar radiation variability rate. For each class and for each location, forecasting models were performed and the error was quantified. With this analysis, global solar radiation forecasting models can be selected according to the location, the global solar radiation fluctuations and hence the meteorological conditions.cf201

Heat Transfer in Buildings: Application to Solar Air Collector and Trombe Wall Design

The aim of this paper is to briefly recall heat transfer modes and explain their integration within a software dedicated to building simulation (CODYRUN). Detailed elements of the validation of this software are presented and two applications are finally discussed. One concerns the modeling of a flat plate air collector and the second focuses on the modeling of Trombe solar walls. In each case, detailed modeling of heat transfer allows precise understanding of thermal and energetic behavior of the studied structures. Recent decades have seen a proliferation of tools for building thermal simulation. These applications cover a wide spectrum from very simplified steady state models to dynamic simulation ones, including computational fluid dynamics modules (Clarke, 2001). These tools are widely available in design offices and engineering firms. They are often used for the design of HVAC systems and still subject to detailed research, particularly with respect to the integration of new fields (specific insulation materials, lighting, pollutants transport, etc.). Available from: http://www.intechopen.com/books/evaporation-condensation-and-heat-transfer/heat-transfer-in-buildings-application-to-solar-air-collector-and-trombe-wall-designComment: Available from: http://www.intechopen.com/books/evaporation-condensation-and-heat-transfer/heat-transfer-in-buildings-application-to-solar-air-collector-and-trombe-wall-desig

Non-Gaussian power grid frequency fluctuations characterized by Levy-stable laws and superstatistics

Multiple types of fluctuations impact the collective dynamics of power grids and thus challenge their robust operation. Fluctuations result from processes as different as dynamically changing demands, energy trading and an increasing share of renewable power feed-in. Here we analyse principles underlying the dynamics and statistics of power grid frequency fluctuations. Considering frequency time series for a range of power grids, including grids in North America, Japan and Europe, we find a strong deviation from Gaussianity best described as Lévy-stable and q-Gaussian distributions. We present a coarse framework to analytically characterize the impact of arbitrary noise distributions, as well as a superstatistical approach that systematically interprets heavy tails and skewed distributions. We identify energy trading as a substantial contribution to today’s frequency fluctuations and effective damping of the grid as a controlling factor enabling reduction of fluctuation risks, with enhanced effects for small power grids

Experimental evaluation of insulation material in roofing system under tropical climate

International audienc