French National Solar Energy Institute
French National Solar Energy Institute
Quoc-Tuan T.,French National Solar Energy Institute
IEEE PES Innovative Smart Grid Technologies Conference Europe | Year: 2017
In a distribution network with the presence of PV systems, islanding phenomena can occur. Such isolated islands may cause a serious danger for workers and equipment. Therefore, islanding must be detected and the islanded PV systems must be disconnected from the principal network. This paper gives a review of different islanding detection methods for grid-connected PV inverters. These methods can be divided into three categories: passive methods, active methods and methods with communications. In order to improve the islanding detection performance, this paper proposes two new methods of islanding detection for PV inverters. The first proposed method is based on the rate of change of Voltage Unbalance (RoCoVU) weighted by the rate of change of Frequency (RoCoF). The second proposed method is based on the rate of change of Voltage Unbalance (RoCoVU) weighted by the rate of change of Reactive Power (RoCoQ) and the rate of change of Frequency (RoCoF). In order to evaluate the performance of the proposed methods, simulations are carried out. The results obtained by simulations have shown the advantages of the proposed methods. © 2016 IEEE.
Amrouche B.,Renewable Energy Development Center Algeria |
Le Pivert X.,French National Solar Energy Institute
Applied Energy | Year: 2014
When a part of the power is generated by grid connected photovoltaic installations, an effective global solar irradiation (GSI) forecasting tool becomes a must to ensure the quality and the security of the electrical grid. GSI forecasts allow the quantification of generated photovoltaic (PV) power and helps electrical grid operators anticipate problems related to the nature of PV power and the planning for adequate solutions and decisions. In this study, a new methodology for local forecasting of daily global horizontal irradiance (GHI) is proposed. This methodology is a combination of spatial modelling and artificial neural networks (ANNs) techniques. An ANN based model is developed to predict the local GHI based on daily weather forecasts provided by the US National Oceanic and Atmospheric Administration (NOAA) for four neighbouring locations. The methodology was tested for two locations; Le Bourget du Lac (45°38'44″N, 5°51'33″E), which is located in the French Alps and Cadarache (43°42'28″N, 05°46'31″E), which is located in the south of France. The model's forecasts were compared to measured data for the two locations and validation results indicate that the ANN-based method presented in this study can estimate daily GHI with satisfactory accuracy. © 2014 Elsevier Ltd.
Le Perchec J.,French National Solar Energy Institute
Optics Express | Year: 2012
We investigate the dual optical behaviour of a photonic grating interface presenting a more or less important index contrast, showing either efficient broadband reflectivity, either high transmittance within the same spectral window, depending on the direction of the incident light. This behaviour is reminiscent of a diode one and could find interesting applications. A typical example is given for thin crystalline silicon solar cells where the rear side is directly nano-textured to trap light without metal reflector (bifacial device), well compatible with an integration in a photovoltaic module. © 2012 Optical Society of America.
Grosjean C.,French National Solar Energy Institute |
Herrera Miranda P.,French National Solar Energy Institute |
Perrin M.,French National Solar Energy Institute |
Poggi P.,University of Corsica
Renewable and Sustainable Energy Reviews | Year: 2012
Electric vehicles (EVs) are on the verge of breaking through, most presumably flooding the automotive market with lithium-ion batteries as energy storage systems. This paper investigates the availability of world lithium resources and draws conclusions on its actual impact on the EV industry. Apart from lithium deposits geographic distribution, our contributions to the global knowledge range from a short-term forecast of lithium price evolution to a picture of the existing lithium industry and market plus a detailed explanation of the geologic origins of all the inventoried lithium resources. © 2011 Elsevier Ltd. All rights reserved.
Oury A.,French National Solar Energy Institute |
Kirchev A.,French National Solar Energy Institute |
Bultel Y.,CNRS Physical Eletrochemistry Materials and Interfaces Lab
Electrochimica Acta | Year: 2012
This work examines the oxygen evolution reaction (OER) taking place on α-PbO 2 electrode in methanesulfonic acid (MSA) medium and in sulphuric acid as a comparison, by means of cyclic voltammetry (CVA) and electrochemical impedance spectroscopy (EIS), for soluble lead acid flow battery applications. The influence of MSA concentration on OER is studied. EIS measurements highlighted the impact of the hydrated lead dioxide layer upon decreasing MSA or sulphuric acid concentration. The evolution of the Tafel curves plotted from EIS measurements and quasi-stationary currents while varying acid concentration was interpreted in the light of this hydrated layer which could enhance the electrocatalytic activity when it is thin, and on the contrary act as an electronic barrier when growing for low acid concentration. Both EIS and CVA revealed that OER on lead dioxide is less favoured in MSA than in sulphuric acid. It is finally concluded that a high-concentrated MSA electrolyte is better for lead acid flow battery application in terms of oxygen evolution. © 2011 Elsevier Ltd. All rights reserved.
Sicurella F.,French National Center for Scientific Research |
Evola G.,French National Center for Scientific Research |
Wurtz E.,French National Solar Energy Institute
Energy and Buildings | Year: 2012
In recent years, the study of indoor environmental comfort during the warm season has been one of the most attractive and hard tasks for architects and energy designers. Nowadays, thanks to the available high-performance utilities, the dynamic energy simulation of a building is relatively easy. Nevertheless, since it should simultaneously account for thermal, visual and air quality issues, a global approach, often neglected, becomes necessary. In the present work, an approach based on simple indicators calculated on a statistical basis will be presented; it can be useful for the simultaneous evaluation of the indoor thermal and visual comfort on a more comprehensive perspective, and it can be applied in any building energy analysis where a comparison between different solutions or strategies is required. At the end of the paper this approach is tested on a simple case study in order to show how the approach can be used to evaluate the influence of the size and the typology of a window on indoor comfort. © 2012 Elsevier B.V. All rights reserved.
Baudrit M.,French National Solar Energy Institute |
Algora C.,Technical University of Madrid
IEEE Transactions on Electron Devices | Year: 2010
Multijunction solar cells (MJCs) based on IIIV semiconductors constitute the state-of-the-art approach for high-efficiency solar energy conversion. These devices, consisting of a stack of various solar cells, are interconnected by tunnel diodes. Reliable simulations of the tunnel diode behavior are still a challenge for solar cell applications. In this paper, a complete description of the model implemented in Silvaco ATLAS is shown, demonstrating the importance of local and nonlocal trap-assisted tunneling. We also explain how the measured doping profile and the metalization-induced series resistance influence the behavior of the tunnel diodes. Finally, we detail the different components of the series resistance and show that this can help extract the experimental voltage drop experienced by an MJC due to the tunnel junction. The value of this intrinsic voltage is important for achieving high efficiencies at concentrations near 1000 suns. © 2006 IEEE.
Eustathopoulos N.,Grenoble Institute of Technology |
Drevet B.,French National Solar Energy Institute
Journal of Crystal Growth | Year: 2013
Sixty years after the first measurement of capillary properties of silicon, experimental results on the surface tension and temperature coefficient of liquid silicon are still divergent. The reason for this persisting divergence is discussed by examining the effect on these quantities of (i) oxygen contained as an impurity in the gas, (ii) impurities in Si and (iii) contamination by the supporting material (substrate or crucible). From the analysis of experimental data, the following expression is derived for the temperature dependence of the surface tension σ: σ(mN/m) = 840(±45)-0.19(± 0.09)(T(K)-1685). © 2013 Elsevier B.V. All rights reserved.
Lespinats S.,French National Solar Energy Institute |
Aupetit M.,CEA Saclay Nuclear Research Center
Computer Graphics Forum | Year: 2011
Multidimensional scaling is a must-have tool for visual data miners, projecting multidimensional data onto a two-dimensional plane. However, what we see is not necessarily what we think about. In many cases, end-users do not take care of scaling the projection space with respect to the multidimensional space. Anyway, when using non-linear mappings, scaling is not even possible. Yet, without scaling geometrical structures which might appear do not make more sense than considering a random map. Without scaling, we shall not make inference from the display back to the multidimensional space. No clusters, no trends, no outliers, there is nothing to infer without first quantifying the mapping quality. Several methods to qualify mappings have been devised. Here, we propose CheckViz, a new method belonging to the framework of Verity Visualization. We define a two-dimensional perceptually uniform colour coding which allows visualizing tears and false neighbourhoods, the two elementary and complementary types of geometrical mapping distortions, straight onto the map at the location where they occur. As examples shall demonstrate, this visualization method is essential to help users make sense out of the mappings and to prevent them from over interpretations. It could be applied to check other mappings as well. © 2010 The Authors Computer Graphics Forum © 2010 The Eurographics Association and Blackwell Publishing Ltd.
Foucquier A.,CEA Saclay Nuclear Research Center |
Robert S.,CEA Saclay Nuclear Research Center |
Suard F.,CEA Saclay Nuclear Research Center |
Stephan L.,French National Solar Energy Institute |
Jay A.,French National Solar Energy Institute
Renewable and Sustainable Energy Reviews | Year: 2013
In the European Union, the building sector is one of the largest energy consumer with about 40% of the final energy consumption. Reducing consumption is also a sociological, technological and scientific matter. New methods have to be devised in order to support building professionals in their effort to optimize designs and to enhance energy performances. Indeed, the research field related to building modelling and energy performances prediction is very productive, involving various scientific domains. Among them, one can distinguish physics-related fields, focusing on the resolution of equations simulating building thermal behaviour and mathematics-related ones, consisting in the implementation of prediction model thanks to machine learning techniques. This paper proposes a detailed review and discussion of these works. First, the approaches based on physical (white box) models are reviewed according three-category classification. Then, we present the main machine learning (black box) tools used for prediction of energy consumption, heating/cooling demand, indoor temperature. Eventually, a third approach called hybrid (grey box) method is introduced, which uses both physical and statistical techniques. The paper covers a wide range of research works, giving the base principles of each technique and numerous illustrative examples. © 2013 Elsevier Ltd.