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International audience; Many health campaigns are designed to reduce dangerous binge drinking by challenging the drinking perceived norm. Both information about health risks and statements that only a few people binge drink (descriptive norm) threaten self-integrity for individuals targeted. So, to combat this self-threat and preserve their positive self-integrity, drinkers discredit the message as a coping strategy. An alternative to the coping strategy is a procedure of self-affirmation to protect self-integrity. Across three experiments, we found that self-affirmation does indeed reduce (Experiment 1) or delete (Experiments 2 and 3) discrediting, but only provided that there is no normative information in the health message. Individuals continued to use the discrediting strategy despite the fact that the participants were self-affirmed when they are told that few people binge drink among their age group. The theoretical implications for self-affirmation are discussed

The ‘Foot-in-the-door’ (FITD) is a well-known compliance technique that increases compliance with a request. Many investigations on this paradigm have generally used prosocial requests to test the effect of the technique. A new evaluation of the effect of the FITD technique was carried out on tobacco deprivation. A two feet-in-the-door technique in which the target request was preceded by two small target requests was used to encourage students to stop smoking for 24 h. The results were compared with two single foot-in-the- door procedures in which the final request was only preceded by one small request, as well as with a control condition using only a 24 h stop-smoking request. Results showed that the single FITD and the two feet-in-the-door procedures were effective to increase verbal compliance (accepting to stop smoking) but only the two feet-in-the-door technique significantly increased behavioural compliance (not smoking for 24 h) with the request.

Data collection forms (original French version). (PDF 334 kb)

Consent form (original French version). (PDF 253 kb)

International audience; In this paper a techno-economic comparison of an energy storage system (ESS) sizing for three intermittent renewables, wind, wave and PV power, with regard to two electricity grid services is presented. The first service consists of output hourly smoothing, based on day-ahead power forecasts (S1). The second service supplies year-round guaranteed power (S2). This leads to an annual default time rate (DTR) for which the actual power supplied to the grid does not match the day-ahead power bid within a given tolerance. A heuristic optimization based on an Adaptive Storage Operation (ASO) scheduling is developed in this study. ASO enables the minimal 5%-DTR ESS capacity, power, energy and feed-in-tariffs to be inferred from the operating conditions, depending on tolerance. The simulations assess and compare the techno-economic viability and efficiency of every renewable sources coupled with ESS. PV power is more efficient with daylight hours restricted services and higher power levels can be guaranteed for S1. Wind and wave power are more suitable than PV for services dedicated to full-day power delivery, as in the case of S2. For hourly smoothing the forecast accuracy influence is studied and yields a high impact on techno-economic sizing.

Due its intermittency, the large-scale integration of solar energy into electricity grids is an issue and more specifically in an insular context. Thus, forecasting the output of solar energy is a key feature to efficiently manage the supply-demand balance. In this paper, three short term forecasting procedures are applied to island locations in order to see how they perform in situations that are potentially more volatile than continental locations. Two continental locations, one coastal and one inland are chosen for comparison. At the two time scales studied, ten minute and hourly, the island locations prove to be more difficult to forecast, as shown by larger forecast errors. It is found that the three methods, one purely statistical combining Fourier series plus linear ARMA models, one combining clear sky index models plus neural net models, and a third using a clear sky index plus ARMA, give similar forecasting results. It is also suggested that there is great potential of merging modelling approaches on different horizons. Refereed/Peer-reviewed

International audience; Research has reported that the foot-in-the-door technique is effective at increasing helping behavior. However, the effect of this technique on negative social behavior has never been examined. A field experiment was conducted to explore whether this technique could reduce aggressiveness. Drivers waiting at a traffic light were blocked by an experimental car. In the Foot-in-the-door condition, when the traffic light was red, a passerby confederate asked the driver for directions to a well-known store located in the area of the experiment. The confederate then thanked the driver and walked off in the direction indicated. In the control condition, no request was addressed to the car driver. When the traffic light turned green, the experimental car pretended to be blocked by an engine problem. The number of drivers who honked at the target car and the amount of time that elapsed before the drivers responded by honking their horns were the dependent variables. It was found that fewer drivers honked in the Foot-in-the-door condition and drivers who honked displayed their behavior later than those in the control condition. Self-perception theory was used to explain these results.

SPIRIT checklist. (DOC 122 kb)

International audience; This paper investigates the relationship between two parameters characterizing a given location on a given day: the daily clear skyindex KT* and the intraday variability given by the standard deviation of the changes in the hourly clear sky index rðDktDtÞ. Empiricalevidence assembled from twenty climatically distinct locations led us to derive a simple model to infer intraday variability from the day’sclear sky index. Although the model shows little dependence on location, we did observe a systematic difference traceable to a location’sprevailing cloud formation regime. Therefore, we also propose two alternative models for sites where cloud formations is influenced bylocal orography and sites where cloud formation is traceable to weather events only. Finally, we present a possible application of themodels to enhance the informative content of day(s) ahead NWP forecasts.

International audience; Forecasting of the solar irradiance is a key feature in order to increase the penetration rate of solar energy into the energy grids. Indeed, the anticipation of the fluctuations of the solar renewables allows a better management of the production means of electricity and a better operation of the grid-connected storage systems. If numerous methods for forecasting the mean of the solar irradiance were recently developed, there are only few works dedicated to the evaluation of prediction intervals associated to these point forecasts. Time series of solar irradiance and more specifically of clear sky index show some similarities with that of financial time series. The aim of this paper is to assess the performances of a commonly used combination of two linear models (ARMA and GARCH) in econometrics in order to provide probabilistic forecasts of solar irradiance. In addition, a recursive estimation of the parameters of the models has been set up in order to provide a framework that can be applied easily in an operational context. A comprehensive testing procedure has been used to assess both point forecasts and probabilistic forecasts. Using only the past records of the solar irradiance, the proposed model is able to perform point forecasts as accurately as other methods based on machine learning techniques. Moreover, the recursive ARMA-GARCH model is easier to setup and it gives additional information about the uncertainty of the forecasts. Even if some strong assumption has been made regarding the statistical distribution of the error, the reliability of the probabilistic forecasts stands in the same order of magnitude as other works done in the field of solar forecasting.

International audience; Short Term Load Forecasting (STLF) is essential for planning the day-to-day operation of an electric power system. As this forecasting leads to increased security operation's conditions and economic cost savings, numerous techniques have been used to improve the STLF. We propose in this paper the comparison of two nonlinear regression techniques namely Gaussian Process (GP) regression models and Neural Network (NN) models. While the Bayesian approach to NN modelling offers significant advantages over the classical NN learning methods, it will be shown that the use of GP regression models will improve the performances of the forecasting. The proposed techniques are applied to real load data.

International audience; Solar shades are efficient architectural elements in order to reduce the thermal loads inside buildings. In one way, they can reduce significantly the energy needs of cooling systems. But in other way, they can decrease the visual comfort and increase the energy consumption of artificial lighting. Actually, the sizing of shading devices is mainly a thermal optimization process. The efficacy of solar shades must be assess taking into account both thermal and visual point of view. In this paper simple indices were proposed to compare the thermal and visual efficacy of different types of solar shadings in non-residential buildings. These indices can be derived from the results of numerical simulations that include thermal and daylighting analysis such as the EnergyPlus software. A typical office is studied in order to assess the efficacy of different types of solar protections. The use of the proposed indices made obvious the choice and the sizing of the most efficient solar shade for the case study.

Facing the demand in electricity for houses or buildings provided by mean of photovoltaic panels is relatively tricky, especially because of the stochastic character of the solar radiation. There exists some solutions in terms of storage and among them, the one consisting in converting electricity in high-pressure compressed air seems promising. This option is under investigation in a building of teaching classes at Reunion University (a French island situated in the Indian Ocean, at the east of Madagascar. The aim in terms of consumption is 25 kWhPE.m-2.year-1 leading, if possible to a NetZEB (Zero Energy Building). So, it has been envisaged to produce the electricity by mean of PV panels, to consume the major and to store the extra production in order to be used at night and during lower shinning periods. The solution that has been investigated consists in compressing air in high pressure storage tanks and to produce electricity later thanks to a turbine. A dynamic numerical model has been built, considering a specific given load profile and local climatic data in order to estimate the production. The whole system depends mainly on the PV panel area, the storage tank volume and the pressure range. The objective is to reduce the amount of energy provided by the external network to the minimum leading to the maximum autonomy of this system. First results have been obtained and are explained in a last part, in terms of pressure and power evolution.

International audience; Because of their low cost, small air conditioning systems (AC) like split air conditioning systems are often installed without a proper study of building envelope performance. Furthermore, these systems are sometimes installed by tradesmen who neglect to comply with the appropriate rules and regulations. Finally, when routine maintenance is not rigorously carried out (as so often happens), the energetic performance of the system is compromised over time. This article presents a practical, global approach to diagnose the performance of existing small airconditioning installations in buildings applied in Reunion Island. This tropical Island aspires to become electricity self-sufficient.. This approach relies on a numerical tool and dynamic simulations of buildings equipped with AC. The simulations, which take account of the building envelope, a description of the system as well as the practices of the users, are based on the kernel calculation EnergyPlus. They also take into account the climatic conditions and provide an estimate of the annual electricity consumption related to the cooling of the zone. This global analysis helps to qualify the entire system by assigning an energy label. In addition to the tool, a diagnostic procedure is proposed, helping an auditor defining guidance to improve the building envelope and to install and maintain the system.

Earlier research reported that using pictures in a fundraising request increases donations by legitimizing the solicitation. The present study tested the effectiveness of a solicitation for money made in the street when an object that legitimated the request was present or not. Male confederates asked passersby for money to buy a stamp while either holding or not holding an envelope in one hand. With a high effect-size, it was reported that the presence of the envelope increased compliance with the request. The legitimation of the request associated with the presence of the envelope is used to explain the results.

International audience; This paper presents a technico-economical analysis of a Pelamis wave power generator coupled with a proposed air compression storage system. Ocean wave measurements and forecasts are used from a site near the city of Saint-Pierre in Réunion island, France. The insular context requires both smoothing and forecast of the output power from the wave power system. The storage system is a solution to meet this requirement. Several power network services are defined by the utility operator in order to meet different load needs. The goal is to analyze the role of the proposed storage device for each desired network service. An optimization procedure, from previous works, based on available wave energy forecast, is used to compute the optimal storage size for each service. An economical analysis shows the feasibility from the addition of the storage device, as the hybrid source power output may be economically profitable compared to a raw wave power production.

International audience; In this paper, we propose a benchmarking of supervised 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 benchmark a simple linear autoregressive (AR) model as well as two naive models based on persistence of the GHI and persistence of the clear sky index (denoted herein scaled persistence model). The models are calibrated and validatedwith data from three French islands: Corsica (41.91°N; 8.73°E), Guadeloupe (16.26°N; 61.51°W) and Reunion (21.34°S ; 55.49°E). The main findings of this work are, that for hour ahead solar forecasting,the machine learning techniques slightly improve the performances exhibited by the linear AR and the scaled persistence model. However, the improvement appears to be more pronounced in case of unstable sky conditions.These nonlinear techniques start to outperform their simple counterparts for forecasting horizons greater than one hour.

International audience; In this paper, two ways of increasing the integration of wind and solar energy into the electricity grid through energy storage are analyzed. The first service (S1) to the electricity grid is related to a smoothed and hourly scheduled daily production while the second one (S2) concerns a constant and guaranteed minimal production. A power bid, based on meteorological forecasts, is transmitted a day ahead by the producer to the utility grid operator. This leads to a yearly default time rate for which the actual power supplied does not meet the announcement within a given tolerance. The modelling approach developed in this study enables to infer the optimal operation of the system and more specifically the optimal size of the energy storage, aiming at reducing the default time rate (DTR) under 5%. The simulations consider PV or wind with storage systems having discharge time in the range of minutes. Two real test cases are examined: Guadeloupe Island for wind and Reunion Island for PV. The results show that both of the two services can be achieved under specific conditions and that an optimal day-ahead power bid with a 2% DTR is possible with a storage capacity of 1 MWh per installed MWp. In addition, a linear strategy of forecasting this optimal power is highly correlated to the precision of upstream meteorological forecast.