• Energy Research
• 7. Clean energy close
• 13. Climate action close
• 11. Sustainability close
• FR close
• CA close

Cette modélisation présente la partie de contrôle d'une pile à combustible à membrane d'échange de protons (PEMFC). L'objectif du modèle de représenter la chaîne de contrôle de la tension de la PEMFC. Ce modèle est basé sur une représentation macroscopique énergétique (REM) de la pile à combustible, puis conduit à une structure dite de contrôle maximal (SCM). La SCM est une inversion étape par étape de la REM (structure de contrôle basée sur un modèle d'inversion). Le processus de conception de la commande est basé sur une définition explicite du problème. Par exemple, les entrées de réglage, les objectifs du système ou les contraintes sont mises en évidence pour organiser la commande. De plus, le SMC montre les endroits où les capteurs sont nécessaires et où les contrôleurs sont requis. Malheureusement, le SCM n'est qu'une structure de contrôle théorique. Par conséquent, une structure réaliste nécessite certaines simplifications, ce qui conduit à une structure de contrôle dite pratique. This modeling presents the control part of a proton exchange membrane fuel cell (PEMFC). The objective of the model is to represent the voltage control chain of the PEMFC. This model is based on an energetic macroscopic representation (EMR) of the fuel cell and then leads to a so-called maximum control structure (MCS). The SCM is a step-by-step inversion of the REM (control structure based on an inversion model). The control design process is based on an explicit problem definition. For example, control inputs, system objectives, or constraints are highlighted to organize the control. In addition, the MSC shows where sensors are needed and where controllers are required. Unfortunately, the SCM is only a theoretical control structure. Therefore, a realistic structure requires some simplifications, which leads to a so-called practical control structure. AdditionnalInformation: Modèle créé lors d'une thèse en génie électrique, par Loïc Boulon (ses recherches portent sur la modélisation et le contrôle des véhicules électriques hybrides, des sources d'énergie et d'énergie et de puissance, et des systèmes de piles à combustible). Il a travaillé en vue de l'obtention du diplôme de doctorat à l'Université de Franche-Comté, Belfort, France, où sa thèse de doctorat a été réalisée en collaboration avec le FEMTO-ST, Belfort, et les Laboratoires L2EP, Lille. Co-encadrement par Daniel Hissel (PU au laboratoire FEMTO-ST), Alain Bouscayrol (PU au laboratoire L2EP) et Marie-Célie Péra (PU au laboratoire FEMTO-ST) AdditionnalInformation: Model created during a thesis in electrical engineering, by Loïc Boulon (his research focuses on the modeling and control of hybrid electric vehicles, energy and power sources, and fuel cell systems). He worked towards his Ph.D. degree at the University of Franche-Comté, Belfort, France, where his dissertation was complet in collaboration with the FEMTO-ST, Belfort, and the L2EP Laboratories, Lille. Co-supervision by Daniel Hissel (PU at FEMTO-ST laboratory), Alain Bouscayrol (PU at L2EP laboratory) and Marie-Célie Péra (PU at FEMTO-ST laboratory) Données computationnelles ou de simulation: - Langage de programmation : Langage Matlab - Plate-forme/OS : Microsoft Windows, Mac OS, Linux,... - Version : MATLAB R2018a - Statut de développement : Actif Simulation or computational data: - Programming language: Matlab language - Platform/OS: Microsoft Windows, Mac OS, Linux,... - Version: MATLAB R2018a - Development status: Active Project: Thèse de doctorat en génie électrique - Loïc Boulon, Contrat doctoral (Region Bourgogne Franche-Comté) Label: PHE (Plateforme Hydrogène-Energie) Audience: Research

Abstract. An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochronological requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation–climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. This manuscript forms part of the wider LOng-Term multi-proxy climate REconstructions and Dynamics in South America – 2k initiative that provides the ideal framework for the integration of the various palaeoclimatic subdisciplines and palaeo-science, thereby jump-starting and fostering multidisciplinary research into environmental change on centennial and millennial timescales.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.C4MIP.CNRM-CERFACS.CNRM-ESM2-1' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The CNRM-ESM2-1 climate model, released in 2017, includes the following components: aerosol: TACTIC_v2, atmos: Arpege 6.3 (T127; Gaussian Reduced with 24572 grid points in total distributed over 128 latitude circles (with 256 grid points per latitude circle between 30degN and 30degS reducing to 20 grid points per latitude circle at 88.9degN and 88.9degS); 91 levels; top level 78.4 km), atmosChem: REPROBUS-C_v2, land: Surfex 8.0c, ocean: Nemo 3.6 (eORCA1, tripolar primarily 1deg; 362 x 294 longitude/latitude; 75 levels; top grid cell 0-1 m), ocnBgchem: Pisces 2.s, seaIce: Gelato 6.1. The model was run by the CNRM (Centre National de Recherches Meteorologiques, Toulouse 31057, France), CERFACS (Centre Europeen de Recherche et de Formation Avancee en Calcul Scientifique, Toulouse 31057, France) (CNRM-CERFACS) in native nominal resolutions: aerosol: 250 km, atmos: 250 km, atmosChem: 250 km, land: 250 km, ocean: 100 km, ocnBgchem: 100 km, seaIce: 100 km.

This chapter focuses on the evaluation of adaptive capacities of community-level human systems related to agriculture and food security. It highlights findings regarding approaches and domains to monitor and evaluate behavioral changes from CGIAR’s research program on climate change, agriculture and food security (CCAFS). This program, implemented in five West African countries, is intended to enhance adaptive capacities in agriculture management of natural resources and food systems. In support of participatory action research on climate-smart agriculture, a monitoring and evaluation plan was designed with the participation of all stakeholders to track changes in behavior of the participating community members. Individuals’ and groups’ stories of changes were collected using most significant change tools. The collected stories of changes were substantiated through field visits and triangulation techniques. Frequencies of the occurrence of characteristics of behavioral changes in the stories were estimated. The results show that smallholder farmers in the intervention areas adopted various characteristics of behavior change grouped into five domains: knowledge, practices, access to assets, partnership and organization. These characteristics can help efforts to construct quantitative indicators of climate change adaptation at local level. Further, the results suggest that application of behavioral change theories can facilitate the development of climate change adaptation indicators that are complementary to indicators of development outcomes. We conclude that collecting stories on behavioral changes can contribute to biophysical adaptation monitoring and evaluation.

This article proposes an effective evolutionary hybrid optimization method for identifying unknown parameters in photovoltaic (PV) models based on the northern goshawk optimization algorithm (NGO) and pattern search (PS). The chaotic sequence is used to improve the exploration capability of the NGO algorithm technique while evading premature convergence. The suggested hybrid algorithm, chaotic northern goshawk, and pattern search (CNGPS), takes advantage of the chaotic NGO algorithm’s effective global search capability as well as the pattern search method’s powerful local search capability. The effectiveness of the recommended CNGPS algorithm is verified through the use of mathematical test functions, and its results are contrasted with those of a conventional NGO and other effective optimization methods. The CNGPS is then used to extract the PV parameters, and the parameter identification is defined as an objective function to be minimized based on the difference between the estimated and experimental data. The usefulness of the CNGPS for extraction parameters is evaluated using three distinct PV models: SDM, DDM, and TDM. The numerical investigates illustrate that the new algorithm may produce better optimum solutions and outperform previous approaches in the literature. The simulation results display that the novel optimization method achieves the lowest root mean square error and obtains better optima than existing methods in various solar cells.

This paper presents an experimental study of indoor thermal environment near a full-scale glass facade with different types of shading devices under varying climatic conditions in winter. Interior glazing and shading temperature, operative temperature and radiant temperature asymmetry were measured for facade sections with roller shades and venetian blinds at different positions. Interior glass surface temperatures can be high during sunny days with low outdoor temperature. Shading systems significantly improved operative temperature and radiant temperature asymmetry during cold sunny days, depending on their properties and tilt angle. During cloudy days the impact was smaller, however the shading layers could still decrease the amount of heat loss through the facade. A transient building thermal model, which also calculates indoor environmental indices under the presence of solar radiation, was developed and compared with the experimental measurements. Part II of this paper uses this validated model with a transient, two-node thermal comfort model (including transmitted solar radiation) for assessment of indoor environmental conditions with different building envelope and shading properties, facade location and orientation.

SLOs are the CGIAR's highest level goals, aligned with the United Nations Sustainable Development Goals (SDGs). To access CGIAR's Strategy and Results Framework

A vehicle model is used to evaluate a novel powertrain that is comprised of a dual energy storage system (Dual ESS). The system includes two battery packs with different chemistries and the necessary electronic controls to facilitate their coordination and optimization. Here, a lithium-ion battery pack is used as the primary pack and a Zinc-air battery as the secondary or range-extending pack. Zinc-air batteries are usually considered unsuitable for use in vehicles due to their poor cycle life, but the model demonstrates the feasibility of this technology with an appropriate control strategy, with limited cycling of the range extender pack. The battery pack sizes and the battery control strategy are configured to optimize range, cost and longevity. In simulation the vehicle performance compares favourably to a similar vehicle with a single energy storage system (Single ESS) powertrain, travelling up to 75 km further under test conditions. The simulation demonstrates that the Zinc-air battery pack need only cycle 100 times to enjoy a ten-year lifespan. The Zinc-air battery model is based on leading Zinc-air battery research from literature, with some assumptions regarding achievable improvements. Having such a model clarifies the performance requirements of Zinc-air cells and improves the research community's ability to set performance targets for Zinc-air cells.

This paper presents the direct power control (DPC) of asymmetrical six-phase permanent magnet synchronous generator (A6PMSG) which supplied the isolated load via two PWM rectifiers. The study concerns the method of control by the converter (DPC). The proposed method is around two hysteresis controllers that enable the adjustment of active and reactive power. The research in this paper is verified by MATLAB SIMULINK software. It has been demonstrated through the simulation results that the proposed strategy can be an attractive and practical solution to multi-phase machines applications.

Biodiesel can be produced from vegetable oils, animal fats, and waste cooking oils by transesterification with ethanol (also called ethanolysis) in order to substitute fossil fuels. In this work, the batch ethanolysis of high oleic sunflower oil was transferred into a continuous microstructured device, which induces a better control of heat and mass transfers. Various parameters were studied, notably the initial ethanol to oil molar ratio. An innovative method using NIR spectroscopy was also developed to on-line monitor the transesterification reaction of high oleic sunflower oil with ethanol in microreactors (circular PFA tube 1/1600 OD, 0.0200 ID). The reactions were monitored directly in the microreactors through sequential scans of the reaction medium by the means of an adequate probe. The asset of the method is that no sample collection or preparation is necessary. Partial Least Squares regression was used to develop calibration and prediction models between NIR spectral data and analytical data obtained by a reference method (gas chromatography with flame ionization detection, GC–FID). This method is fast, safe, reliable, nondestructive and inexpensive contrary to conventional procedures, such as gas chromatography and high performance liquid chromatography generally used to determine the composition of crude transesterification medium.