Presentation

Objectives

The H2RUN project aims to develop a complete value chain for the production of alternative fuels from organic waste, based on several specific objectives:

1. Characterisation of local resources

Identify and quantify the organic waste deposits that can be mobilised on the territory, and assess their hydrogen and methane production potential.

2. Development and optimisation of biological processes

Implement and improve dark fermentation processes for hydrogen production, coupled with anaerobic digestion for methane production, while optimising yields through pre-treatments and the use of biochar.

3. Scale-up and process integration

Study the transition from laboratory to larger-scale systems, as well as coupling with complementary technologies such as water electrolysis.

4. Feasibility assessment and end uses

Analyse the techno-economic and environmental viability of a local supply chain, particularly for applications in heavy mobility (passenger and freight transport).

Dessimination

The H2RUN project aims to produce concrete results that can be directly mobilised at the territorial level.

The main expected results are:

• A better understanding of local resources: characterisation of organic waste deposits and their energy potential, enabling the steering of valorisation strategies.
• Technological advances: optimisation of biohydrogen and biomethane production processes, improvement of yields and experimentation with innovative hybrid solutions.
• An assessment of territorialised energy scenarios: analysis of the conditions for deploying an alternative fuel supply chain in Réunion Island, integrating the technical, economic and logistical constraints specific to the territory.
• Scientific outcomes: production of scientific articles, participation in conferences and strengthening of the positioning of the laboratories involved in the field of bioenergies.
• An environmental and socio-economic impact: contribution to the reduction of greenhouse gas emissions, valorisation of local waste and support for the emergence of an energy circular economy.

Through these results, the H2RUN project contributes to building a more sustainable energy model, adapted to island specificities, and to the structuring of a hydrogen supply chain in Réunion Island.

Partners

Partenaires financiers

Academic partners

• CIRAD : BioWooEB

• IHE Delft Institute for Water Education

Contact

Scientific project leader:
dominique.grondin@univ-reunion.fr
laetitia.adelard@univ-reunion.fr

Management team associated with the project at ENERGY-Lab:
michel.benne@univ-reunion.fr
dominique.grondin@univ-reunion.fr

Management team associated with the project at the PIMENT Laboratory:
mathieu.david@univ-reunion.fr
laetitia.adelard@univ-reunion.fr

Presentation

Our century is defined by a race against time to limit global warming to 1.5 °C above pre-industrial levels, as agreed in the Paris Agreement by 192 Parties in December 2015. In this context, the massive deployment of intermittent renewable energies (RE) is a national and European priority, particularly in non-interconnected island territories such as La Réunion, where grid stability relies on energy storage and decarbonized hydrogen production.

Proton Exchange Membrane Water Electrolysis (PEMWE) is a key technology for converting surplus renewable electricity into hydrogen. However, the accumulation of oxygen bubbles at the anode significantly reduces system performance and durability. These complex two-phase phenomena (bubbly, slug, and stagnated regimes) lead to partial coverage of the active surface, increased overpotentials, and accelerated component degradation.

To overcome these bottlenecks, artificial intelligence represents a breakthrough innovation. Pioneering work carried out by Idriss Sinapan led to the development of deep learning-based bubble detection and recognition tools (YOLO), initially in single-class and then in multi-class configurations, combined with a transparent PEMWE cell and a high-resolution video acquisition system on the SysPacRevers test bench. These approaches have already enabled precise quantification of coverage rates, bubble counts, and flow dynamics, as well as the identification of counter-intuitive phenomena related to water flow rate and current density.

The H2-DurabilitAI project – Improving H2 system durability through AI, led by Idriss Sinapan as principal investigator, builds on this body of work. It aims to establish a comprehensive experimental database, develop an advanced AI pipeline (multi-class detection/segmentation, non-uniformity heat maps, bubble residence time estimation), and propose new component topologies and optimizations, in partnership with Fraunhofer ISE for experimental validation.

The H2-DurabilitAI project is funded by the European Union in the amount of €167,924.67 under the ERDF-ESF+ Réunion 2021–2027 programme, for which the Région Réunion serves as the Managing Authority. Europe is committed to La Réunion through ERDF funding. The Région Réunion supplements this funding with a national counterpart contribution.

This project strengthens local expertise in artificial intelligence applied to hydrogen and contributes to the decarbonization and energy resilience of the Réunion territory, while promoting open innovation through the public release of the database and the AI model on GitHub.

Objectives

1. Large-scale data acquisition and establishment of an experimental database

• Recommissioning and calibration of the SysPacRevers test bench;
• High-resolution video acquisition synchronized with operating signals (current density, water flow rate, temperature, pressure, channel and porous medium topologies);
• Structuring, organization, and open sharing of data via a NAS system.

2. Development of an artificial intelligence pipeline for bubble analysis

• Development of a multi-class bubble detection/segmentation model (bubbly, slug, stagnated);
• Generation of coverage non-uniformity heat maps;
• Implementation of bubble tracking to compute dynamic indicators such as residence time and mean evacuation time;
• Post-processing and performance evaluation (mAP, IoU, etc.).

3. Analysis of results and proposal of new topologies and optimizations

• Comparative analysis of bubble regimes according to operating conditions and topologies;
• Proposal of component modifications (channels, porous transport layer, MEA assembly);
• Validation in partnership with Fraunhofer ISE.

4. Dissemination, outreach, and preparation of future projects

• Publication of results in a Category A scientific journal;
• Public release of the AI model and database on GitHub;
• Preparation of analysis reports and recommendations;
• Prefiguration of a Horizon Europe consortium.

Dissemination

• A rich and open experimental database: Collection and structuring of a large volume of high-resolution videos synchronized with operating conditions (current density, flow rates, temperature, pressure, topologies). This database will constitute a valuable resource for the international scientific community working on two-phase phenomena in PEMWE electrolyzers.
• An advanced artificial intelligence tool: Development of a high-performance AI pipeline for multi-class bubble detection (bubbly, slug, stagnated), generation of non-uniformity heat maps, and computation of dynamic indicators (residence time, coverage rate, etc.). The model and source code will be made available as open source on GitHub to promote reproducibility and collaborative innovation.
• Scientific and technological advances: Publication of results in a Category A scientific journal, including a comparative analysis of bubble regimes and component optimization recommendations (flow channels, porous transport layer, MEA assembly). This work will significantly improve the performance and durability of PEM electrolyzers.
• Strengthening of local expertise and international outreach: Development of computer vision expertise applied to hydrogen within ENERGY-Lab, strengthening of the partnership with Fraunhofer ISE, and preparation of a consortium for Horizon Europe projects.

Partners

Financial partners

Academic partners

Contact

• Project coordinator:
  • idriss.sinapan@univ-reunion.fr
• Project leader:
  • amangoua.kadjo@univ-reunion.fr
• Management team associated with the project at ENERGY-Lab:
  • michel.benne@univ-reunion.fr
  • dominique.grondin@univ-reunion.fr
  • cedric.damour@univ-reunion.fr

Presentation

Objectives

The LIGHTEN-IO project builds on the achievements of the SWIO-Energy partnership (2020-2023) and the IOS-net network (2019-2022) to move from bilateral scientific exchanges to the structuring of a genuine regional network dedicated to green hydrogen. It is organised around four specific objectives:

1. Structuring and coordinating a SWIO stakeholder network

The objective is to design a concerted strategy for the deployment of green hydrogen across the South-West Indian Ocean. Several tasks are carried out:

• Organisation of a kick-off seminar in Réunion and definition of deliverables, roles and milestones;
• Development of a shared regional strategy among SWIO partners;
• Establishment of a monitoring system for territorial initiatives;
• Coordination of regular training workshops and working meetings with partners.

2. Generation of regionalised climate and energy data

The objective is to produce harmonised, open datasets enabling the fine-grained assessment of renewable resources. Several tasks are carried out:

• Collection, ingestion and normalisation of climate, meteorological and energy data from in-situ observations, satellite products and climate simulations;
• Training in downscaling tools (LSCE) and development of a statistical downscaling tool based on U-Net architectures (Keras/TensorFlow);
• Production of climate fields at high spatial and temporal resolution from global model outputs;
• Distribution of data via an open-access THREDDS Data Server, accompanied by a data management plan and a data paper.

3. Assessment of green hydrogen potential and decarbonisation scenarios

The objective is to leverage regionalised data to support specific case studies and inform public decision-making. Several tasks are carried out:

• Training in the RESkit tool (IEK-3, Jülich) and assessment of green hydrogen development potential;
• Study of climate change impacts and land-use changes;
• Comparative analysis of SWIO territories and development of sectoral decarbonisation scenarios;
• Organisation of scientific conferences on the regionalisation of renewable energies and green hydrogen production in the SWIO area.

4. Dissemination, outreach and regional structuring

The objective is to ensure the dissemination of results and the sustainability of the network. Tasks include:

• Publication of scientific articles (statistical downscaling, green hydrogen potential, decarbonisation scenarios);
• Open-source release of source code and datasets;
• Production of a project website and a documentary series for outreach purposes;
• Organisation of the final seminar and training workshops in target territories.

Dissemination

The LIGHTEN-IO project aims to deliver concrete, reusable outputs with strong scientific and territorial impact across the SWIO region.

The main expected outcomes are:

• An open, interoperable database: collection, harmonisation and distribution of a significant volume of climate, meteorological and energy data through a THREDDS Data Server, accompanied by enriched metadata and a data management plan. This resource will provide a valuable asset for the scientific community and energy-transition stakeholders across the South-West Indian Ocean.
• A deep-learning-based statistical downscaling tool: development of a pipeline using U-Net architectures, enabling the generation of regionalised climate projections at high spatial resolution with lower computational cost compared to traditional dynamical downscaling approaches. The source code will be released as open source to foster reproducibility and replicability to other island regions facing similar challenges.
• Territorialised energy and decarbonisation scenarios: assessment of green hydrogen production potential across SWIO territories, analysis of climate change impacts on renewable resources, and development of sectoral decarbonisation scenarios designed to inform public policy.
• Scientific advances and regional outreach: publication of scientific articles (statistical downscaling, green hydrogen potential, decarbonisation scenarios), organisation of two thematic conferences, and delivery of a final seminar. These outputs will strengthen ENERGY-Lab’s positioning as a regional hub on green hydrogen issues in insular environments.
• Capacity building and regional structuring: cross-training between partners (LSCE, IEK-3/Jülich), workshops in target territories, and the establishment of shared regional governance. In doing so, the project transforms a still-blurred regional vision into a precise, operational local strategy for the deployment of the green hydrogen value chain.

Through these deliverables, LIGHTEN-IO will contribute to reducing the cost of access to strategic climate information, assessing the viability of green hydrogen as a regional energy carrier, and enhancing the energy resilience of the island territories of the South-West Indian Ocean.

Contact

• Scientific coordinator:
  • beatrice.morel@univ-reunion.fr
• ENERGY-Lab management team involved in the project:
  • michel.benne@univ-reunion.fr
  • dominique.grondin@univ-reunion.fr
  • cedric.damour@univ-reunion.fr

Partners

Financial partners

Academic partners

• Université des Mascareignes (UdM) — Mauritius: expertise in renewable energies (solar, wind), energy efficiency and dynamical downscaling. Previous SWIO-Energy partner (2020-2023).
• University of Mauritius (UoM) — Mauritius: expertise in renewable energies and both dynamical and statistical downscaling. Previous SWIO-Energy partner (2020-2023).
• Institut Supérieur de Technologie d’Antananarivo (IST-T) — Madagascar: expertise in renewable energy systems and energy transition in Madagascar; gateway to local energy professionals.
• University of Nairobi (UoN) — Kenya: expertise in hydrogen production pathways and artificial-intelligence methods applied to statistical downscaling.
• Université des Comores (UC) — Comoros: gateway to academic and professional energy stakeholders in the Comoros. Previous IOS-net partner (2019-2022).

Institutional partners

• Forschungszentrum Jülich (IEK-3) — Germany: expertise in renewable potential assessment tools (GLAES, RESkit) and associated training.
• Météo-France — Réunion Island: access to regional meteorological data.
• Seychelles Meteorological Authority (SMA) — Seychelles: provision of SMA station data and expertise on South-West Indian Ocean climate. Previous IOS-net partner (2019-2022).

Presentation

Within the framework of the European ERDF-ESF+ Programme 2021-2027, Action Sheet 1.1.13 “Supporting Réunion’s integration into the European Research Area (ERA), Indian Ocean and international spaces”, the beneficiary commits to carrying out the following operation, funded by the ERDF:

“BECOME: BEnefits of COmplementarity of interMittent Energies”

The purpose of this operation is to contribute to Réunion’s energy transition towards a 100% renewable electricity mix, by examining the potential benefits of complementarity between solar and wind resources, as well as their hybridisation in future energy systems.

The content of the operation referred to in this article, as well as its implementation arrangements, are described in the attached annexes — specifying in particular the objective, the eligible cost of the subsidised operation, the description of investments supported by structural funds, the provisional implementation schedule, project-related indicators and publicity obligations. These annexes, together with this document, constitute the contractual components of the agreement.

Objectives

1. General objective To quantitatively characterise the complementarity properties of solar and wind resources and explore the economic, environmental and technical benefits of their hybridisation, in order to facilitate Réunion’s energy transition towards a 100% renewable electricity mix.
2. Specific objectives
   • Building a high-resolution database for renewable energy studies in Réunion
   • Quantifying solar-wind complementarity (temporal, spatial, spatio-temporal)
   • Identifying the benefits of hybrid solar-wind-battery power plants for Réunion
3. Scientific / technological challenges Lack of a consistent high-resolution database for solar and wind resources in Réunion. Solar-wind complementarity insufficiently documented in non-interconnected zones (NIZ). Optimisation of hybrid configurations under tropical island meteorological constraints. Integration of intermittent energies into an isolated electrical grid with high energy dependency.
4. Work packages (WP) Action 1: Data collection and processing (M1-M8) Action 2: Complementarity analysis and hybrid system optimisation (M6-M24)

Dissemination

1. Scientific impacts
   • First comprehensive study of solar-wind complementarity in Réunion
   • Contribution to the knowledge of renewable resources in tropical non-interconnected zones
   • Reproducible methodologies for complementarity analysis applicable to other island territories
2. Socio-economic impacts
   • Reduction of storage needs through optimisation of solar-wind combinations
   • Potential decrease in electricity costs (currently ~€300/MWh)
   • Decision-support for renewable energy investments
3. Territorial / environmental impacts
   • Contribution to Réunion’s energy self-sufficiency
   • Increase in the share of local intermittent energies in the electricity mix
   • Reduction of dependency on imported fossil fuels (target: 100% renewable)
   • Mitigation of greenhouse gas emissions
4. Valorisation activities
   • Open-access databases for research and industry
   • Complementarity index mapping for siting guidance
   • Optimal hybrid power plant configurations adapted to local conditions
5. Dissemination activities
   • Project web page
   • Open-access scientific publications
   • Final dissemination seminar open to energy transition stakeholders

Partners

Financial partners

Academic partners

The project involves a partnership with DTU Wind Energy, part of the Technical University of Denmark, a Danish academic partner. Its central role focuses on wind energy expertise, particularly through internationally recognised tools such as the Global Wind Atlas, WAsP and HyDesign, which will support resource analyses and hybrid configuration optimisation within the project.

Contact

• Project coordinator:
  • chao.tang@univ-reunion.fr
• Scientific lead for ENERGY-Lab:
  • Beatrice.Morel@univ-reunion.fr
• Associate professors on the project at ENERGY-Lab:
  • michel.benne@univ-reunion.fr

Presentation

This century is marked by a race against time to limit global warming to 1.5 °C above pre-industrial levels, as agreed in the Paris Agreement by 192 Parties in December 2015 [1]. In this context, technologies using decarbonized hydrogen have become a national priority for many countries [2, 3]. As disruptive innovations, they promise to decarbonize the most energy-intensive sectors (industry, transport, energy storage) and to reduce the real costs (environmental, climatic, health-related) across the energy value chain, from conversion to end-use [4]. In particular, they play a crucial role in decarbonizing the steel and fertilizer industries, electrifying heavy transport, and storing electricity from intermittent or seasonal renewable energy sources (RES). On the scale of non-interconnected grids, such as those in island territories, the hybridization of multi-source conversion units relies on the deployment of storage systems, both to decouple energy production and demand from the availability of local RES and to manage the complementarity of variable and flexible resources. Storing energy in the form of hydrogen and its stationary reconversion into electricity help mitigate the intermittency of variable RES by optimizing electrical production capacity.

Currently, the proton exchange membrane fuel cell (PEMFC) is the most widely adopted fuel cell technology [6]. However, it faces technological challenges that must be overcome for large-scale commercialization, such as low power densities, high costs, and limited lifespan [7]. In particular, the transient operating conditions induced by RES variability lead to performance, reliability, and durability issues in hydrogen systems: cell degradation, premature aging, or the occurrence of faults (water management, corrosion, etc.). To address these challenges, global institutions have set several development targets for PEMFCs. Regarding power and current density improvements, the European Union aims to reach 1.2 W·cm⁻² at 0.675 V by 2030 [8], while Japan targets 6 kW·L⁻¹ and 3.8 A·cm⁻² for the same year [7]. For cost reduction, the European Union seeks a price below €50/kW by 2030 for fuel cells in heavy-duty vehicles [8]. Finally, concerning lifespan, the European Union aims for 30,000 operating hours for hydrogen buses by 2030 [8].

Numerical modeling of fuel cells contributes to achieving these development goals. Indeed, models provide insights into the internal states of cells that traditional sensors cannot capture, as placing them directly inside the ultra-thin cell layers is impractical. With this precise information, PEMFC diagnostics can be enhanced [9, 10]. This enables more effective real-time control of fuel cells by adjusting operating conditions—such as pressure, temperature, humidity, and gas flow rates—which can improve performance, prevent faults like cell flooding, and reduce degradation.

The general objectives of the OPUS-H2: « Optimization of Performance and dUrability of hydrogen Systems using an advanced digital twin » project, led by Prof. Michel Benne and running from May 2025 to May 2027, are to significantly contribute to the development of numerical models for PEM fuel cells in order to improve their performance and durability, as well as to build experimental expertise in collaboration with ZSW, a well-established European partner in the field, with the aim of transferring these skills to Réunion Island. The sharing of knowledge and cross-disciplinary expertise within this partnership will foster innovation and research.

The OPUS-H2 project is funded by the European Union with a grant of €136,060.78 under the FEDER-FSE+ Réunion program, with the Réunion Region acting as the managing authority. Through the FEDER fund, Europe is committed to supporting Réunion. The Région Réunion complements this funding with a national co-financing contribution of €24,010.72.

Objectives

This project builds upon the doctoral work of Raphaël Gass, which led to the development of a dynamic 1D physical model of a PEM cell with auxiliaries, named AlphaPEM, serving as a building block for a fuel cell digital twin. Based on this model, a control strategy for inlet humidity was formulated, theoretically enabling a 60% increase in cell power output or a 15% improvement in efficiency.

The OPUS-H2 project advances this work through five specific objectives:

1. Development of the digital twin and inlet humidity control strategy by adding new functionalities to AlphaPEM.

   • The first aim is to improve the accuracy of the AlphaPEM model by enabling it to simulate additional physical phenomena. Six tasks are implemented to achieve this:
     • refining the model simulating electrochemical impedance spectroscopy (EIS) curves,
     • adding a thermal phenomena model to AlphaPEM,
     • incorporating the microporous layer (MPL) into the PEM cell modeling,
     • using improved auxiliary control tools,
     • increasing the spatial dimension of the single-cell model to 1D+1D,
     • precisely characterizing multiple cells forming a stack.
   • The second aim is to enhance the inlet humidity control strategy developed in previous work. Three tasks are implemented to achieve this:
     • using improved tools for controlling operating conditions,
     • further developing the theory on the limiting liquid water quantity (slim), established in prior work, linking voltage drop at high current densities, liquid water content in the cell, and its operating conditions,
     • refining the inlet humidity control strategy based on the results of this action.

2. Conducting experiments on test benches to validate AlphaPEM and verify performance gains obtained through simulations.

   • The objective is to perform experimental tests on the European partner’s equipment to validate AlphaPEM improvements and the proposed inlet humidity control strategy. Three tasks are implemented to achieve this:
     • generating polarization and EIS curves under different fixed operating conditions on near-single-cell stacks,
     • generating polarization and EIS curves under model-controlled operating conditions on near-single-cell stacks,
     • repeating tests on stacks of around one hundred cells.

3. Integration of models into the digital twin to estimate cell degradation state and remaining system lifespan.

   • The objective is to enable AlphaPEM to account for the current degradation state of an experimental stack and incorporate this impact into the results. Two tasks are implemented to achieve this:
     • integrating a model to estimate electrochemical surface area (ECSA) degradation in the catalytic layer into AlphaPEM,
     • integrating a model to calculate the system’s remaining useful life (RUL).

4. Development of model-based control strategies to maintain optimal performance and reduce degradation over the cell’s lifetime.

   • The objective is to apply the theory produced in the objective 3 to create an operating condition control strategy that maximizes performance and minimizes future degradation in an aged stack. Two tasks are implemented to achieve this:
     • developing a control strategy for operating conditions, based on AlphaPEM, to maintain maximum performance of an aged stack at all stages of its life,
     • developing a control strategy for operating conditions, based on AlphaPEM, to minimize future degradation of an aged stack at all stages of its life.

5. Conducting accelerated degradation experiments on test benches (single cells and stacks) to validate digital twin enhancements and formulated control strategies.

   • The objective is to perform experiments on the European partner’s test benches to validate the proposals from objectives 4 and 5. Three tasks are implemented to achieve this:
     • conducting accelerated degradation experiments without modifying operating conditions on near-single-cell stacks,
     • conducting accelerated degradation experiments with operating condition control strategies on near-single-cell stacks,
     • repeating tests on stacks of around one hundred cells.

Dissemination

The OPUS-H2 project : « Optimization of Performance and Durability of Hydrogen Systems using an Advanced Digital Twin » aims to promote the sustainable development of hydrogen systems and the energy transition toward a low-carbon economy. This will strengthen energy security in territories while reducing their dependence on imported energy resources. Knowledge sharing and cross-disciplinary expertise within the European Union network, combined with regional initiatives, will foster innovation and research in this field. The project’s outcomes (open-access digital twin and control strategies) will benefit all stakeholders in the energy transition (research institutes, industries, economic actors, etc.).

From a scientific perspective, the project will first provide the scientific community with an open-source fuel cell simulator, specialized for control applications—something not currently available at such an advanced level in the literature. Next, it will deepen the understanding of the relationship between voltage drop at high currents, liquid water content in the cell, and operating conditions through theoretical developments and experimental testing. Following this, control strategies to improve fuel cell performance will be experimentally validated. Additionally, the project will integrate and experimentally test cell degradation physics into the simulator to develop a model accounting for fuel cell aging. Resulting control strategies to extend fuel cell lifespan will then be experimentally assessed. Finally, the project will enable the candidate to acquire technical expertise on modern hydrogen test benches from the European partner, allowing these skills to be transferred to Réunion Island.

Partners

Funding partners

Academic partners

The OPUS-H2 project aims to sustainably connect Réunion Island to the European research ecosystem by promoting interoperability and collaboration. Its main objective is to establish strong links to fully integrate the island into the European network. To this end, a new partnership has been formed with the ZSW research center (The Centre for Solar Energy and Hydrogen Research Baden-Württemberg) in Ulm, Germany. This laboratory is one of the most significant in the European Union for fuel cell modeling and testing on experimental benches.

Contact

• Project Coordinator:
  • raphael.gass@univ-reunion.fr
• Scientific Manager for Energy-Lab:
  • michel.benne@univ-reunion.fr
• Associated professors at Energy-Lab:
  • dominique.grondin@univ-reunion.fr
  • cedric.damour@univ-reunion.fr

Presentation

Objectives

• Development and research of a deep learning tool that meets the operating constraints of the Reunionese territory.
• Multi-scale application of the developed method, fine detection of crop types on a plot scale, and recognition of bubble/drop regimes.
• Availability of research results to the scientific community and society.

R&D

• Bibliography on multi-scale Deep Learning image recognition tools
• Development of a scientific tool specific to the conditions of the Reunionese territory
  • Operation of hydrogen converters in a tropical environment (humidity and temperature)
  • Diversity of Reunionese cultures and steep relief
• Creation of databases with satellite images (Pléiades) and new truth maps from the DEAL REUNION / IGN
• Creation of databases for hydrogen converters

• Detection of crop types and generation of fine maps of land use (1 per year)
• Cross-referencing of maps (risks, deposits, uses) for photovoltaic decision making

• Creation of databases and detection of bubbles/droplets, then determination of operating regimes
• Coupling of the obtained spatial distributions to models and design of a multimodal diagnostic tool

Equipement

• Local computing stations at ENERGY-lab and CIRAD
  • GPU: 2 x Nvidia Quadro RTX 4000 (8 Go) + 1 x Nvidia RTX 5500 (24 Go)
  • RAM: 128 Go
  • Storage: 4 To

• Mésocentre HPC et données Meso@LR
  • GPU: 2 modified Nvidia RTX 6000 (48 GB) visualisation nodes
  • RAM post: 3 To
  • Storage: 15 Po

• Supercalculateur HPE CNRS IDRIS Jean-Zay
  • GPU: 7 accelerated partitions, Nvidia V100 (16-32 Go), Nvidia A100 (40-80 Go), max 1024 GPUs/job
  • RAM post: 3 To
  • Storage: 30 Po

Partenariats

Scientific partners

• CIRAD
  • Pierre Todoroff (pierre.todoroff@cirad.fr)
  • Lionel Le Mézo (lionel.le_mezo@cirad.fr)
  • Mickaël Mezino (mickael.mezino@cirad.fr)
  • Bertrand pitollat (bertrand.pitollat@cirad.fr)

• CNRS IDRIS (advanced support)
  • Maxime Song (maxime.song@idris.fr)
  • Pierre Cornette (pierre.cornette@idris.fr)

Financial partners

Valorisation

• Christophe Lin-Kwong-Chon, Cedric Damour, Michel Benne, Jean-Jacques Amangoua Kadjo, et Brigitte Grondin-Pérez, « Adaptive neural control of PEMFC system based on data-driven and reinforcement learning approaches », Control Engineering Practice, vol. 120, p. 105022, mars 2022, doi: 10.1016/j.conengprac.2021.105022.
• Christophe Lin-Kwong-Chon, Pierre Todoroff, Lionel Le Mezo, Michel Benne et Jean-Jacques Amangoua Kadjo, « Multi-level deep-based classification of land use and land cover: A case study on Réunion Island », Proceedings of the International Society of Sugar Cane Technologists, volume 31, xx–xx, 2023 (à paraitre)

• Christophe Lin-Kwong-Chon, Kenza Benlamlih, Pierre Todoroff, Jean-Jacques Amangoua Kadjo, « Deep learning et imagerie satellitaire pour cartographier l’occupation du sol : performances et perspectives », RGR2021, 17 novembre 2021, sciencesconf.org:rgr2021:374451.
• Idriss Sinapan, Christophe Lin-Kwong-Chon, Cédric Damour, Michel Benne, Jean-Jacques Amangoua Kadjo, Optimisation des interfaces fluidiques dans un système de production d’hydrogène par électrolyse à partir des outils de reconnaissance d’images Deep Learning, CNRS Aussois FRH2, 2 juin 2022
• Christophe Lin-Kwong-Chon, Idriss Sinapan, Dominique Grondin, Michel Benne, Segmentation d’images pour la classification de données massives, TEMERGIE ValoREn, 1^er decembre 2022
• Christophe Lin-Kwong-Chon, Pierre Todoroff, Lionel Le Mezo, Michel Benne et Jean-Jacques Amangoua Kadjo, « Multi-level deep-based classification of land use and land cover: A case study on Réunion Island », ISSCT2023, Hyderabad, 2023

• Pierre Todoroff, Christophe Lin-Kwong-Chon, Kenza Benlamlih, Deep Learning et imagerie satellitaire pour cartographier l’occupation du sol : performances et perspectives, CST SIAAM, 15 novembre 2021
• Pierre Todoroff, Christophe Lin-Kwong-Chon et Kenza Benlamlih, Modèle d’apprentissage profond pour cartographier l’occupation du sol en zone tropicale à partir d’images THRS, SEAS-OI, 13 juin 2022
• Christophe Lin-Kwong-Chon, Pierre Todoroff, Mickaël Mezino, Lionel Le Mezo, Cartographie de l’occupation du sol par imagerie satellitaire et apprentissage profond : Premiers résultats, CST CapTerre, 24 novembre 2022

• Reunion 2018 A2 300dpi
• Reunion 2020 A2 300dpi

• DeepRun-GUI : A GUI application for deep learning model generation, model training and images inference. Source code.

• Fête de la Sciences, 17 novembre 2022, 30ème édition, Université de La Réunion

Team

Contact

Contact : 

Laboratoire ENERGY-lab
Jean-Jacques Amangoua Kadjo
amangoua.kadjo@univ-reunion.fr
Tel : +262(0)262 938216

15, Avenue
René Cassin
CS 92003
97744 Saint-Denis Cedex 9
La Réunion

Objective 1

• Industrial monitoring reports

Objective 2

• Journal article: Aubras, F., Damour, C., Benne, M., Bessafi, M., Grondin-Perez, B., Kadjo, A. J. J., & Deseure, J. (2021). A Non-Intrusive Signal-Based Fault Diagnosis Method for Proton Exchange Membrane Water Electrolyzer Using Empirical Mode Decomposition. Energies, 14(15), 4458.

• International conference: Aubras, F., Lin-Kwong-Chon, C., Damour, C., Benne, M., Bessafi, M., Grondin-Perez, B., Deseure, J., & Kadjo, J. J. A. (2020, November). Empirical Mode Decomposition Applied to Proton Exchange Membrane Electrolyzer for Non-Intrusive Diagnosis. In ECS Meeting Abstracts (No. 53, p. 3762). IOP Publishing.

• National conference (FRH2): Farid Aubras, Cedric Damour, Michel Benne, Christophe Lin-Kwong-Chon, Jonathan Deseure, Amangoua J-J Kadjo, “Non-intrusive diagnostic method applied to proton exchange membrane electrolysers: Multi-scale entropic analysis”, FRH2 2021

Objective 3

• A single-phase regime occurring at low current densities (before the water-splitting reaction takes place), characterised by a laminar Reynolds number and a uniform presence of water in the channels.
• A two-phase regime in which the water-splitting reaction produces a mixture of oxygen bubbles and water in the channel.

• Journal article: Aubras, F., Rhandi, M., Deseure, J., Kadjo, A. J. J., Bessafi, M., Majasan, J., … & Chabriat, J. P. (2021). Dimensionless approach of a polymer electrolyte membrane water electrolysis: Advanced analytical modelling. Journal of Power Sources, 481, 228858.
• International conference: Rhandi, M., Aubras, F., Kadjo, A. J. J., Druart, F., Grondin-Perez, B., & Deseure, J. (2019, September). Dimensionless approach of a pressurized proton exchange membrane water electrolysis. In 12th European Congress of Chemical Engineering, ECCE12 (pp. pp-1903).

Partners

Academic partners

Local stakeholders

Funding partners

Contact

Pr Brigitte Perez

brigitte.grondin@univ-reunion.fr

Dr Jean Jacques Kadjo

amangoua.kadjo@univ-reunion.fr

Dr Farid Aubras

farid.aubras@univ-reunion.fr

Dissemination and communications

1. Aubras, F., Rhandi, M., Deseure, J., Kadjo, A. J. J., Bessafi, M., Majasan, J., … & Chabriat, J. P. (2021). Dimensionless approach of a polymer electrolyte membrane water electrolysis: Advanced analytical modelling. Journal of Power Sources, 481, 228858.
2. Aubras, F., Damour, C., Benne, M., Bessafi, M., Grondin-Perez, B., Kadjo, A. J. J., & Deseure, J. (2021). A Non-Intrusive Signal-Based Fault Diagnosis Method for Proton Exchange Membrane Water Electrolyzer Using Empirical Mode Decomposition. Energies, 14(15), 4458.

1. Rhandi, M., Aubras, F., Kadjo, A. J. J., Druart, F., Grondin-Perez, B., & Deseure, J. (2019, September). Dimensionless approach of a pressurized proton exchange membrane water electrolysis. In 12th European Congress of Chemical Engineering, ECCE12(pp. pp-1903).
2. Aubras F Lin-Kwong-Chon, C., Damour, C., Benne, M., Bessafi, M., Grondin-Perez, B., Deseure, J., & Kadjo, J. J. A. (2020, November). Empirical Mode Decomposition Applied to Proton Exchange Membrane Electrolyzer for Non-Intrusive Diagnosis. In ECS Meeting Abstracts(No. 53, p. 3762). IOP Publishing.
3. Non-intrusive diagnostic method applied to proton exchange membrane electrolysers: Multi-scale entropic analysis, GDR HYSPAC.

Présentation

Objectives

• Energy autonomy of the grid
• Realization of an electromagnetic sensor of power levels
• Storage and visualization of measured data on a 3D visualization tool.

Equipements

Helical Antenna

Waspmote node

Advanced analyzer

Hand-portable spectrum analyzer

Patch antennas

3GHz signal generator – SM300

Digital multimeter

Mechanical engraver

Test Bench

Anechoic foam

PNA-X

Anechoic chamber

R & D

Action 1 : Network Energy Autonomy.

• Wireless communication interfaces to communicate either between them or with the base station, which retrieves the information transmitted by the nodes to the database
• Sensors, that can be of different natures (temperature, movement, light, wind, etc…). These sensors will provide the information that will be fed back into the database.

Enable the network to be autonomous

• Network software optimization : various methods relating to the transmission of information in the network are the subject of doctoral work at the LE²P laboratory , in order to optimize the energy consumed by a node through time.
• Low power protocols are used by the nodes in order to minimize the energy consumption; then some additionnal wake-up mechanism can be implemented using external signals .

Energy recovery for on-board batteries

Action 2 : Electromagnetic power level sensor implementation

Action 3 : 3d storage and visualization of measured data

Manipulations

WiFi signal in anechoic space measurement

Brazing of components

Integration of an environmental sensor

LORA network test

LORA network test at Mafate-1

Mapping of the measured power of electromagnetic waves

LORA network test in Mafate-2

Valorization

Communications

• Rochefeuille E., Alicalapa F., Douyère A., Vuong T. (2017). Rectenna Design for RF Energy Harvesting using CMOS 350nm and FDSOI 28nm, IEEE Radio and Antenna Days of the Indian Ocean (RADIO), 25-28 septembre 2017, Le Cap (Afrique du Sud). 2017 IEEE Radio and Antenna Days of the Indian Ocean (RADIO),. doi: https://doi.org/10.23919/RADIO.2017.8242246. Réf. HAL: hal-01696046
• Douyère A., Rivière J., Rochefeuille E., Dubard J.-L., Lan Sun Luk J.-D. (2017). Etude du couplage et analyse des performances d’une rectenna PIFA à faibles niveaux de puissance, Assemblée Générale GDR Ondes, 23-25 octobre 2017, Sophia Antipolis (France).. Réf. HAL: hal-01630705
• Rochefeuille E., Alicalapa F., Douyère A., Vuong T. (2017) FDSOI 28nm performances study for RF energy scavenging , IEEE Radio and Antenna Days of the Indian Ocean (IEEE RADIO 2017), Sep 2017, Cape Town, South Africa. IOP, IOP Conference S eries: Materials Science and Engineering, pp.012009, 2018, DOI : https://doi.org/10.1088/1757-899X/321/1/012009〉

Media

• The weekly magazine “Regard’Ensemble”, which covers the island’s economic activities: from 2’35 of the video : http://www.antennereunion.fr/info-et-magazines/regard-ensemble/replay/replay-regard-ensemble-vendredi-07-juin-2019
• News Report on the TV news FranceTvinfo La 1ère : https://la1ere.francetvinfo.fr/reunion/emissions/journal-de-12h30 from 3’30
• Zinfo974 website : https://www.zinfos974.com/%E2%96%B6%EF%B8%8F-Wifi-4G-Bluetooth-Des-scientifiques-de-l-universite-parviennent-a-cartographier-des-ondes-electromagnetiques_a142400.html

Events

• CARERC special participation in the Sustainable Energy Forum organized by IOC, 04/ 9-11/2019
• Participation in the GdR RSD (CNRS); LPWAN thematic days, Lyon, 07/11-12/2019 and Scientific Poster presentation

Posters

Staff

• Ariste Boutchama, Project Engineer circuits and systems
• Marie-Laure Pérony-Charton, Valorization Project Engineer
• Jérôme Rivière, Project Engineer High Frequency Sensor
• Pierre-Olivier pierre Lucas de Peslouan, Research Engineer Circuit Design and Development

Contact

Presentation

Objectives

R & D

ACTIONS

Action 1: Microgrid simulator

A real-time (RT) simulation platform is deployed at LE2P to emulate microgrids composed of energy conversion units (PV), storage and consumption units. This platform will enable real-time testing of energy management strategies applied to various microgrid architectures under real operating conditions.

Action 2: Connected and controllable production and storage units

Action 3: Aggregation platform

Action 4: Energy Management System

Deliverables

Equipements

OPAL R-T

Partnerships

Partnerships with academics

Partnerships with local stakeholders

Valorization

Staff

• Chao Tang, IGR, Data management and analysis
• Nicolas Coquillas, Project Engineer, Real-Time Simulation Platform
• Taher Issoufaly, IGE, Multi Agent System
• Marie-Laure Perony-Charton, Valorization Engineer

Contact

Presentation

Objectives

R & D

Step 1 : Modeling and installation of an experimental equipment

• Action 1: Dimensioning and installation of a test bench for PàC-R

  • Implementation of a specific experimental system for characterizing the performance of PàC-R. This experimental device will be fully automated, including diagnosis, data logging, settings, alarm and security functions.

• Action 2 : Semi-transparent PàC-R cell designs

  • For the understanding and characterization of PàC-R, Physico-chemical phenomena multiphysical and multi-scale modelling under the COMSOL Multiphysics software environment.
  • Design of functional PàC-R cells guided by modelling performed in the COMSOL Multiphysics environment.

Step 2 : Assembling and instrumentation

• Action 1: PàC-R assembly

  • Optimization of tightening, tightness and preliminary tests of electrical performances.

• Action 2: Semi-transparent PàC-R cells Instrumentation

  • Fast camera imaging system Implementation
  • Image acquisition and processing system Implementation

Step 3 : PàC-R Experiments

• Action 1: Real-time testing of a PàC-R in electrolyser mode.

  • The influence of sunlight and PàC-R operating parameters study

• Action 2: Real-time test of the PàC-R in PàC mode

  • Study of the influence of the operating parameters of PàC-R in humid tropical environments

Step 4 : PàC-R Optimization

• Action 1: PàC-R demonstrator optimal design Conception

  • Exchanges Modelisation and Exchange surfaces optimization

• Action 2: Optimized PàC-R Demonstrator Assembly and tests

  • Optimization of tightening, tightness and preliminary tests of the electrical performance of the optimized demonstrator.

EQUIPEMENTS

Test bench for electrolyzer

Système de caméra haute densité haute fréquence

Semi-transparent electrolyser cell

PARTNERSHIPS

Partnerships with academics

Partnerships with Local stakeholders

Funding partners

Valorization

Staff

Scientific Staff

Scientific Supervisors :

• Brigitte GRONDIN PEREZ
• Jean-Jacques KADJO

Project staff

Contact

Scientific Managers :

Project Manager:

Presentation

R & D

1. Expansion of the actual network to the IOC territories (Comoros, Madagascar, Mauritius and Seychelles). All partners will be equipped with identical stations.
2. All data collected will be freely available in a TDS server within a special file size designed for mapping. Data quality control will be ensured by ENERGY-Lab.

• The development of a smartphone application that displayed all data2 collected in a nearly ”real-time”.
• Innovators, scientists and populations to take over the developed tools through workshops and knowledge sharing.

• Action 1: Network expansion to the IOC territories.
• Action 2: The opening of a database and TDS server.
• Action 3: Promotion, communication and knowledge transfer.

OBJECTIVES

1. The solar radiation ground-based measurements existing network in Reunion Island extension to the IOC territories (Comoros, Madagascar, Mauritius and Seychelles) – and other standard meteorological parameters. In concrete terms, the 4 partners will be equipped with identical stations to those that LE2P has been developing for more than 7 years now in and around Reunion Island.
2. The accessibility of the data collected in open data on a TDS server (offering a file format specifically designed for mapping), the quality of this data being controlled by the LE2P research laboratory.
3. Training of local populations through knowledge transfer workshops on solar resource management : a mini-series describing the project and a smartphone application allowing to consult in real time the data of the stations will be realized.

Equipements

 Pyranometer  SPN1

 Weather transmitter WXT530

 UV radiometer

 Central acquisition unit

 Wind turbine

 Solar Panel

 Solar Charge controller

 Lead battery 20 AH

 Galvanized steel frame

Deploiement des stations

La Réunion

Comoros

Mauritius

Madagascar

Seychelles

Partnerships

Scientific partners

Financial partners

VALORIZATION

• Information to the population: the data collected will be public, through a free smartphone application (near real-time display of sunshine and weather on a territory map).
• The transfer of skills, by training business owners and scientists in the tools developed areas.

Events

Medias

Communication Tools

Project Presentation Video

Brochure

Plaquette_fr_v2

Staff

Scientific Team

Team Project

• Nicolas Hassambay, Métrology Design Engineer
• Alexandre Graillet, Database and TDS server IT Design Engineer
• Patrick Jeanty, Research Engineer
• Mathieu Delsaut, Scientific computation Engineer
• Christian Brouat, Research and Training Technician
• Yannis Hoarau, Research and Training Technician

Contact

Presentation

• The ENERGY-lab / LE2P laboratory, University of La Réunion
• The Department of Physics, University of Mauritius
• The Renewable Energy and Energy Efficiency Laboratory, University of Mascareignes, Mauritius.

Objectives

R & D

• University of Mauritius
• University of Mascarene, Mauritius.

• Processing and analysis of all observation data (ground-based, satellite) for the study of scale interactions and climate variability of solar radiation and wind:
  • Deployment of new sensors for the measurement of solar radiation and wind in Reunion and Mauritius as part of the radiometric network IOS-net of the laboratory ENERGYlab/LE2P
  • Validation of satellite data by comparison with ground data

• Processing and analysis of global and regional climate model outputs:
  • Dynamic approach: regional simulations of recent and future climate of Reunion and Mauritius using the WRF model
  • Statistical approach: use of machine-learning techniques.

EQUIPMENT

PARTNERSHIPS

Partnerships with academics

• The Department of Physics, University of Mauritius and the Renewable Energy and Energy Efficiency laboratory of the University of Mascareignes, Mauritius
• Several laboratories and universities in France and South Africa: LACy and OIES (University of La Réunion), CRC-Biogéosciences (University of Bourgogne Franche-Comté, France), CSAG (University of Cape Town, South Africa)
• The meteorological services of La Réunion (Météo-France), Mauritius (MMS) and South Africa (SAWS)
• Observation networks (Reunion: IOS-net, SEAS-OI, OPAR-OSUR; international: BSRN)
• Companies locally established in Reunion ( EDF renewable,..).

Partnerships with Local stakeholders

Valorization

• Scientific communications,
• The organization of a scientific seminar,
• Communications towards the general public, …

Events

Medias

Communication tools

Staff

Scientific Leaders

• Béatrice Morel, Dr HDR, beatrice.morel@univ-reunion.fr
• Patrick Jeanty, IGR, Project Technical Manager, patrick.jeanty@univ-reunion.fr

Project staff

• Chao Tang, Research Engineer, Senior Regional Climate Modeling, chao.tang@univ-reunion.fr

• Swati Singh, Research Engineer Regional climate simulations, swati.singh@univ-reunion.fr
• Remy Ineza Mugenga,Research Engineer Regional climate simulations, ineza.mugenga@univ-reunion.fr
• Tina Herimino Andriantsalama, Study Engineer Database, tina.andriantsalama@univ-reunion.fr
• Elodie Marpinard, Study Engineer Project Management Assistance, elodie.marpinard@univ-reunion.fr
• Marie-Laure Pérony-Charton, Study Engineer Communication and Valorization, mperony@univ-reunion.fr

Videos

Episode 1 : climatic stations on top of Indianocéany :

Contact

Contact :

Presentation

Objectives

R&D

Equipments

Partnerships

Valorization

Team

Scientific Team :

• Michel Benne, michel.benne@univ-reunion.fr
• Béatrice Morel, beatrice.morel@univ-reunion.fr
• Cédric Damour, cedric.damour@univ-reunion.fr
• Miloud Bessafi, miloud.bessafi@univ-reunion.fr
• Dominique Grondin, dominique.grondin@univ-reunion.fr

Contact

Contact :

Présentation

Objectives

• Improve the adaptation of equipment to improve RUE (Rational Use of Energy)
• Participate in efforts to reduce energy dependency
• Promote the integration of intermittent energies into the electrical mix.

R & D

DETECT provides several answers for improved energy efficiency:

• Quantify and locate local energy resources (regionalisation of the solar resource using a high spatial resolution regional climate model)
• Develop equipment instrumentation to improve rational energy use (PV system diagnostics)
• Use ICT for the development of smart energy devices (real-time distributed diagnostics)
• Improve the mastery of a key technology by local stakeholders (decision support for PV system maintenance planning)
• Promote the integration of solar energy (PV system reliability)
• Strengthen knowledge in the field of renewable energies (aggregation of electrical and climatic data into a database).

EQUIPMENT

PHIL Test Bench (Power Hardware In the Loop)

		OPAL-RT: real-time simulator OP4510
		Programmable power supply usable for generator emulation
		4-quadrant power amplifier enabling DC/AC electrical grid simulation as well as motor and converter simulation: DC/DC, DC/AC, AC/AC, and power supplies
		Electronic board enabling the implementation of a control algorithm.

PARTNERSHIPS

Partnerships with academics

• FEMTO-ST de la fédération FCLAB
• CRC de l’Université de Bourgogne Franche Comté
• Météo France Réunion – DIROI.

Financial Partners

Valorization

• Scientific communications,
• The organization of a scientific seminar,
• Communications towards the general public, …

Events

Medias

• Le journal de 19h du samedi 20 novembre 2021, présenté par Gaëlle Malet [RE (francetvinfo.fr) (from 19:09)
• https://www.facebook.com/watch/?v=432815908234691

Communication Tools

Presentation video :

Brochure :

Team

Scientific Team

Scientific Leaders :

• Cédric Damour, cedric.damour@univ-reunion.fr
• Michel Benne, michel.benne@univ-reunion.fr
• Béatrice Morel, beatrice.morel@univ-reunion.fr
• Patrick Jeanty, patrick.jeanty@univ-reunion.fr
• Frédéric Alicalapa, frederic.alicalapa@univ-reunion.fr
• Pierre-Olivier Lucas-de-Peslouan, pierre-olivier.lucas-de-peslouan@univ-reunion.fr
• Dominique Grondin, dominique.grondin@univ-reunion.fr

Project Team

• Fabrice K/BIDI, Research Engineer, Emulation & Implementation, fabrice.kbidi@univ-reunion.fr

• Alexandre GRAILLET, Research Engineer, Database, alexandre.graillet@univ-reunion.fr
• Carole Lebreton, Research Engineer, Diagnosis, Carole.lebreton@univ-reunion.fr
• Elodie Marpinard, Study Engineer Project Management Assistance, elodie.marpinard@univ-reunion.fr
• Marie-Laure Pérony-Charton, Study Engineer, Communication and Valorization, mperony@univ-reunion.fr
• Chandra Shekhar Azad Kashyap, Research Engineer Regional Climate Modeling, chandra.kashyap@univ-reunion.fr
• Chao Tang, Senior Regional Climate Modeling chao.tang@univ-reunion.fr

Videos

Episode 1 : Diagnosis of electric systems

Contact

CONTACT: