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International audience; Nowadays, sustainability is gaining importance in territorial policies. Yet, no substantial efforts have been deployed for systematically integrating environmental, social and economic aspects in early stages of urban service co-design. While Life Cycle Assessment (LCA) is a suitable method for impact assessment of products and services, Landscape-Urban Planning (LUP) provides information on how these products and services interact at the territorial scale. Our understanding of urban systems’ needs could go a step further towards better consumption patterns and resources optimization by coupling both approaches. This work explores the synergy between Life Cycle Thinking and Landscape-Urban Planning by their application to an essential urban service: logistics. The challenging metabolism of high-density urban systems is taken as an opportunity to consider emergent logistic solutions, specifically electric tricycle technologies for last kilometer delivery. Firstly, we start by applying each approach individually; following LUP perspective, we define a territorial reading grid, based on a set of criteria describing physical, socio-cultural, and economic resources of a landscape. Then, using LCA, we quantify potential impacts or benefits of electric tricycles technology compared to the existing delivery technologies. Electricity for tricycle batteries’ charging is provided by photovoltaic systems. In a second step, results from both approaches are coupled to determine local urban hotspots that describe the main aspects to meet stakeholders’ needs and improve their living conditions. Sustainability design parameters are, thus, defined to optimize the tricycle technology. Finally, the design and optimization of the electric tricycle-based delivery system is carried out. The Geographical Information System (i.e .Quantum GIS) is used to explore local data on solar energy potential spots, cycling infrastructures, potential urban logistic platforms, etc. Energy required has been computed to determine adequate charging infrastructures, taking topography and climate conditions into account. Intelligent logistic planning is performed to improve efficiency, optimize the streamline to reduce environmental impacts and simulate interaction with other urban transportation flows. Based on the current case study, the urban service co-design framework has been fully established in order to gain sustainability in a territorial management scale through LCA and LUP perspectives.

International audience; Downward-facing shadow cameras might play a major role in future energy meteorology. Shadow cameras directly image shadows on the ground from an elevated position. They are used to validate other systems (e.g. all-sky imager based nowcasting systems, cloud speed sensors or satellite forecasts) and can potentially provide short term forecasts for solar power plants. Such forecasts are needed for electricity grids with high penetrations of renewable energy and can help to optimize plant operations. In this publication, two key applications of shadow cameras are briefly presented.

International audience

International audience

International audience; A growing interest concerns the study of the temporal variability of solar irradiance which operates at different time and space scales. The exploitation and management of solar energy are directly impacted by this variability and may have negative impacts on the grid or on photovoltaic power plants that have means of storage or sell on the spot market. The objective is then to anticipate, at a given space scale, the temporal fluctuations of the incident solar irradiance which explain the variability on the electrical production. An increasing number of solar forecasting methods have been published in the literature to cope with this issue at different time horizons. To compare the performances of the methods, it is necessary to have a range of metrics along with a standardized procedure, allowing characterizing and comparing the performances of these forecasts. This poster illustrates some limitations of the widely used metric RMSE on a concrete example. In this work we propose a review of the literature related to metrics for solar forecasting, and we propose two new metrics that we deem relevant and innovative: a new ramp and time alignment metric.

International audience; Solar resource and forecasting in very short spatial and timescales (0–100 m, 0–30 min) is a challenging task that cannot be accurately achieved by satellite products or numerical weather predictions due to technical and methodological restrictions. For this reason, sky images from ground-based cameras are widely used during the last decade to deal with the high spatial and temporal variability of clouds and provide the needed inputs for numerical models for the current and forecasted (in short-term) solar irradiance. In this chapter, the available types of all-sky cameras/imagers are shortly presented. The chapter is focused on the state-of-the-art methodologies used to derive parameters needed for the estimations of solar resource and forecasting by a calibrated all-sky camera: cloud coverage, type, height, and velocity as well as aerosol optical properties. The application of these methodologies at Plataforma Solar de Almeria, in the frame of project: “Direct Normal Irradiance Nowcasting methods for optimized operation of concentrating solar technologies” (DNICast, http://www.dnicast-project.net/) is discussed. Finally, the chapter finishes with some propositions for future work in the recent, but quickly, developed research area.

International audience; Life Cycle Assessment (LCA) has been widely applied over the last three decades as a standardized tool for the comprehensive environmental impact assessment of products and processes. While LCAs have traditionally been based on available data from existing processes at pilot or large scale, it is estimated that 80% of environmental impacts of a process are linked to decisions at the design phase. It is therefore worth to develop tools that allow adapting the current LCA framework for the application to early-stage schemes and emerging technologies. Several difficulties hinder LCA practitioners from conducting such studies. In particular, emerging technologies tend to differ significantly from the existing processes they aim to substitute and may have unknown future applications. They present a wider data gap linked to the lack of information on the life cycle phases. Moreover, many of these systems are still at the laboratory stage, which involves substantial differences compared to industrial scale procedures. As a result, LCAs of emerging technologies are subject to an increased level of uncertainty that needs to be estimated to contribute to the reliability and credibility of the results. Global sensitivity analysis (GSA) has been proposed by several authors as a tool to evaluate the global uncertainty of LCA results and the influence of each variable input on the total variability of the model output. However, the GSA results and their corresponding parameter ranking depend on the description of each input’s variability, namely the corresponding probability distribution used by the practitioner to model the range of values that an input may assume. In this study, we propose a protocol to evaluate the effect of the choices in the selection of inputs’ distribution functions on GSA results and provide recommendations for LCA practitioners.

The best way to determine the production from a solar facility is to take the 10 – 20 – 30 years of data that are available and run a simulation with that data. If time of day or capacity matter, those parameters can be factored in at this time. Now the variation in generation over the time span under consideration can be seen and it is possible to select the typical year’s production and get a feeling for the variation from year to year and month to month. If available, use of one year of high quality measured data can be used as input and a more detailed analysis of the plant generation can be performed. Adjustments can be made if the more detailed analysis shows that it is necessary. Trying to select one year that is typical before running the data might be fine for an initial survey, but a universal typical year dataset that is applicable for all types of generation probably is not be the best solu-tion because different facilities can react differently to the same input irradiance. Storage and the ability to adapt to rapidly changing irradiance are likely factors that can influence the selection of the most typical solar year. The annual DNI is likely to vary less than 10% from year to year, so the characteristics of the incident solar radiation and how the plant handles variations in the resource are likely to play as important a role in the annual production of the solar facility as the annual DNI. In addition, I have never been a fan of breaking the production down into monthly blocks and selecting the most typical monthly production. Weather comes in waves and patterns and cutting and splicing break up these patterns. This is how some TMY files can create annual irradiance estimates that are above or below any experienced at the site. A moving average approach can yield a full range of generation estimates although the beginning and ending year are underrepresented.

International audience

International audience

International audience

L’objet de ce document est de proposer une synthèse ainsi que les perspectives de mes activités de recherche depuis 2007 à MINES ParisTech. Cette recherche est bien sûr le fruit d’un travail collectif mené par l’équipe dont j’ai actuellement la responsabilité. Mon apport scientifique dans ce groupe réside essentiellement dans l’aide à la formalisation mathématique des problèmes et à leurs résolutions au moyen d’algorithmes mettant en oeuvre le traitement d’image, du signal, l’analyse statistique ou, de manière générale, les mathématiques appliquées. J’y apporte également mes connaissances dans la mesure du rayonnement par des instruments de mesures in-situ acquises ces dernières années.

This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications; This report presents detailed information about solar resource data and the resulting data products needed for each stage of a solar energy project, from initial site selection to systems operations. It also contains a summary of solar forecasting and its development throughout the last few years. The U.S. Department of Energy's Solar Energy Technologies Office, project developers, engineering procurement construction firms, utility companies, system operators, energy suppliers, financial investors, and others involved in solar energy systems planning and development will find this handbook to be a valuable resource for the collection and interpretation of solar resource data. This handbook is expected to be used as a reference during each project stage.

International audience; In order to correctly perform Concentrated Solar Power (CSP) plant electric energy output estimation, a standard approach is to consider Typical Meteorological Year (TMY) as a reference input data in CSP simulation software such as System Advisor Model or Greenius. These TMYs may be built from satellite derived irradiation databases. In order to correctly estimate the CSP electricity production, it is highly recommended to use sub-hourly DNI information. Due to limitation in spatial and temporal resolution of geostationary satellite images, satellite-based irradiation data lack good representativity in term of any sub-hourly temporal variability. To overcome this limitation, we propose an innovative fusion method to combine a one year short time series of ground-based sub-hourly irradiation data and the long-term satellite-based one to create calibrated, sub-hourly and long-term based TMY irradiation data. This method has been successfully applied in the planning of the CSP plant project in Morocco: one year and a half of high quality 10-minute irradiation data from pyranometric ground stations belonging to the Moroccan Agency for Solar Energy (MASEN) has been used with long-term hourly satellite-based irradiation data to create calibrated 10-minute DNI based TMY. The ground-based irradiation data have passed the standard quality check procedure recommended by the Baseline Solar Radiation Network for the World Climate Research Program. The satellite hourly irradiation data has been calibrated on a one year learning period of ground station data and this calibration has been verified on a subsequent half year ground station data. This calibration has been applied to the hourly long-term satellite irradiation time series from which a TMY was computed. The final and innovative step consists in introducing the site specific sub-hourly variability into the whole set of hourly daily profiles of irradiation of the TMY time series, as needed to obtain a better estimation of the CSP producible. The method uses the whole 10-minute measured irradiation data as a store of available days, normalized in terms of time between sunrise and sunset.

International audience; This communication deals with a prototype of a low- cost fish-eye camera developed by EDF R&D, meant to be an alternative for local and very short term solar forecasting to standard total sky imagers. The paper presents the results of a preliminary study demonstrating a very important pre-requisite for the use of fish-eye camera for solar forecasting purpose: the relationship between hemispheric sky images and the different components (global, diffuse and direct) of the surface solar irradiance (SSI). This study has been carried out with high quality "BSRN quality level" radiometric data and hemispheric sky images from a EDF R&D's test site on Reunion Island, in the Indian Ocean. This experimental study leads to very concluding and promising results on sub-hourly estimation of diffuse, direct and global SSI from sky images provided by the fish-eye camera.

International audience

Several earth observation satellites bear optical imaging sensors whose outputs are essential in many environmental aspects. This paper focuses on two parameters of the quality of the imaging system: the Modulation Transfer Function (MTF) and Signal to Noise Ratio (SNR). These two parameters evolve in time and should be periodically monitored in-flight to control the quality of delivered images and possibly mitigate defaults. Only a very limited number of past and current sensors have an on-board calibration device fully appropriate to the assessment of the noise and none of them has capabilities for MTF assessment. Most often, vicarious techniques should be employed which are based on the Earth-viewing approach: an image, or a combination of images, is selected because the landscape offers certain properties, e.g., well-marked contrast or on the contrary, spatial homogeneity, whose knowledge or modeling permit the assessment of these parameters. Several methods have been proposed to perform in-flight assessments. This paper proposes a review of the principles and techniques employed in this domain.