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NEW TECHNOLOGY TO PRODUCE HYDROGEN FROM RENEWABLE ENERGY SOURCES BASED ON AI WITH OPTIMIZED COSTS FOR ENVIRONMENTAL APPLICATIONS

(HydroG(re)EnergY-Env)

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HydroG(re)EnergY-Env approaches a novel technology which consist in demonstration and validation in OITBs of an economically competitive digitalized solution for the process chain of hydrogen production from RES (when this type of energy is produced in excess). A low energy capacity hydrogen production demonstrator will be made using an electrolyzer with an AI-controlled “smart” system integrated, which will be scaled up at medium and high production capacity, ensuring its replicability due to the modular equipment’s. Solutions for eco-friendly use of hydrogen will be developed both for the reduction of the pollution in protected wetlands areas and CO2 emissions for the domestic and industrial users of methane. The project will be an in-depth engagement of stakeholders, represented by small and medium enterprises, by providing tools for new joint transnational business models, new investment opportunities, training sessions, workshops and a Policy Brief.

about project
Drops of Water

ABOUT PROJECT

PROJECT VALUE: 1.034.755 EUR

IMPLEMENTATION PERIOD: May 2022-April 2024

PROJECT OBJECTIVES

The main objective is to achieve and validate in Open Innovation Test Beds (OITBs) of the efficiency of a hydrogen production technology obtained from RES integrated in a diversified AI control system and to provide solutions for hydrogen eco-friendly use in the energy and naval sector, offering business models for the naval sector and environmental protection, useful to the future society.

SPECIFIC OBJECTS:

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  Energy sector

  1. Development of a small-scale capacity prototype (TRL 4 to TRL 8) for the production of Hydrogen by hydrolysis from RES, virtually accessible.

  2. Development of a monitoring and control system based on AI, calibrated and validated on low hydrogen production capacity prototype (automatic management, optimization of operating parameters, control of water quality and hydrogen parameters, etc.

 

Energy sector correlated with environment requirements

  1. Elimination of water quality restrictions used for the hydrogen production electrolyser supply, maintaining the economic efficiency yield.

  2. Numerical simulations of phenomena related to hydrogen injection in the methane gas network to reduce CO2 emissions with about 10%. Demonstrative experiments.

  3. Modular scale up of the integrated hydrogen production system based on AI control at medium and high production capacity, calibrated and validated in real-time operation mode for RES producers (solar and wind).

  4. Elaboration of hydrogen eco-friendly use solutions in the energy and naval sector correlated with environmental protection requirements.

  5. Stakeholder's involvement through development of business models, training organization for SMEs and large enterprises and elaboration of a Policy Brief.

 

The overall mission of the project is to align with the targets set by the European Union to achieve climate neutrality by 2050 by reducing CO2 emissions and the impact of climate change, through a transition to the green energy and to contribute to the targets of production of an annual hydrogen capacity of 1 million tons by 2025 and 10 million tons by 2030 set by EU.

activities

WP1 - Scaling the efficient hydrogen production technology obtained from RES in a demonstrator for low, medium, and high energy capacity

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Tasks

T1.1. Scaling of the hydrogen production demonstrator for low energy capacity independent of water quality supply of the electrolyser

T1.2. Electrolyser validated thermal model

T1.3. Smart Energy System interface with 'need-owners’ requirements

T1.4. Development of a reduced model and coupling with the control system

T1.5. Modelling and simulation of the Smart Energy System functionality for the medium and high energy capacity

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WP2 - Integration of the AI based control component within the electrolyser demonstrator

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Tasks

T2.1. Data collection and analysis of the hydrogen production process for the low energy capacity demonstrator

T2.2. Scaling up the data for the medium and high size hydrogen production process

T2.3. Development of the AI and avatar based control strategy for low energy capacity

T2.4. Modelling and simulating hydrogen injection in the natural gas network using AI based control

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WP3 - Business model to engage small and medium enterprises based on the smart energy AI control system for hydrogen production

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Tasks

T3.1. Business model for small enterprises with "on-site'' test runs for parameters optimization in OITBs to ensure solution replicability for hydrogen production medium energy capacity

T3.2. Scale up the business model for SMEs based on OITBs to ensure solution replicability for hydrogen production high energy capacity system

T3.3. Tools suit to size the business cases for the decision-making stakeholders

T3.4. Life Cycle Assessment and Life Cycle Cost of hydrogen demonstrator system

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WP4 - Innovative solutions of eco-friendly hydrogen use in environmental protection among stakeholders through a Policy Brief

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Tasks

T4.1. Development of eco-friendly solutions based on the use of hydrogen for special naval propulsion systems in protected wetlands areas.

T4.2. Numerical simulations for flow dynamics of the gas mixture H2/NH3 and CH4 for reduction of CO2 emissions in domestic and industrial heating sector – demonstrative experiments

T4.3. Development of a Policy Brief for SMEs and large enterprises

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WP5 - Knowledge Community Standard, Project Management and Dissemination

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Tasks

T5.1. Involvement in formative evaluation – Profiling and feedback

T5.2. Crosscutting Knowledge Community activities - Working groups, Living documents.

T5.3. Cooperation on communication and dissemination activities. IPR management plan.

T5.4. Reporting to the joint call initiative

T5.5. Project management

T5.6. Organizing trainings/workshops for SMEs/large companies - Business model

T5.7. Organizing trainings/workshops for SMEs/large companies to use eco-friendly hydrogen solutions

T5.8. Policy Brief Debate

Petri Dish

ACTIVITIES

Chart analysis

MAIN EXPECTED RESULTS

  • Demonstrator of hydrogen production – integrated in Smart Energy System for low energy capacity;

  • Smart Energy System models (medium & high energy capacity)

  • AI and avatar based control system for the hydrogen electrolyser of low energy capacity;

  • Numerical models for hydrogen/ammonia injection in the natural gas network

  • Business Models for Small & Medium Enterprises;

  • Tools suit to size the business decision software

  • Eco-friendly solution for hydrogen use

  •  Better practices for the hydrogen injection in the natural gas transport network and CO2 reduction emissions;

  • Policy Brief with innovative solutions into RES for stakeholders.

main expected results
partners

The overall aim of the DIGITAL TRANSFORMATION FOR GREEN ENERGY TRANSITION (MICALL20), part of the SMART ENERGY SYSTEMS –ERA-NET, is to support transnational research and innovation activities, unleashing the potential of digital transformation for a sustainable energy society. By accelerating the implementation, adaption and knowledge creation of digital solutions also in energy systems and networks, this call supports the following objectives:

  • Advance the green energy transition in all sectors of the energy system while ensuring security of supply

  • Shaping new transnational business and investment opportunities by sector coupling and development of new value chains in innovative and cost-effective energy solutions, thereby creating new employment opportunities and contributing to the development of an environmentally sustainable financial growth

  • Ensuring social sustainability and coherence with digitalisation in other sectors in the progression of the green energy transition

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For more information:

https://www.eranet-smartenergysystems.eu

https://uefiscdi.gov.ro

SMART ENERGY SYSTEMS
ERA-NET

era-net
news

NEWS & EVENTS

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Bucharest

21-22 September 2022

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Goslar, Germany

26 May 2023              

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