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Data-DrIVen Solutions for Efficient PoweR DiStribution Network OpErations

Objective

DIVERSE addresses critical challenges in modern power distribution networks as they transition to accommodate high shares of renewable energy sources (RES) and increasing electrification demands. The project develops an AI-powered framework to optimize power distribution networks, supporting robust RES integration while tackling key issues such as variability and grid reconfiguration. By combining advanced machine learning, deep learning, and adaptive grid technologies, DIVERSE introduces predictive analytics, near real-time optimization, and consumer-side flexibility to enhance grid efficiency and scalability.

The project's objectives include:
_Developing AI-driven forecasting and regulation strategies for RES integration
_Enhancing operational flexibility and efficiency through adaptive control mechanisms
_Ensuring grid resilience across different network configurations
_Optimizing multi-energy system coordination

DIVERSE's innovative approach incorporates resilience-focused design into distributed energy resource (DER) coordination, ensuring effective grid operation under dynamic scenarios. Through simulations on RTDS-based platforms, the project optimizes adaptive response strategies, enhancing long-term grid flexibility, reliability, and multi-energy integration.

The consortium unites academic institutions, SMEs, and industry partners from six countries, fostering interdisciplinary collaboration among experts in AI, power systems, and energy management. This international, intersectoral, and interdisciplinary approach ensures that DIVERSE's outcomes are scalable and adaptable to diverse grid configurations across Europe and beyond.

By addressing the urgent need for innovative solutions in power distribution networks, DIVERSE contributes significantly to the EU's energy transition goals, aligning with key agendas such as the European Green Deal and the Circular Economy Action Plan. The project's outcomes will enhance Europe's energy security, reduce reliance

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been human-validated.

Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-TMA-MSCA-SE - HORIZON TMA MSCA Staff Exchanges

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-MSCA-2024-SE-01

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Coordinator

KADIR HAS UNIVERSITESI
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 150 300,00
Address
KADIR HAS AVENUE
34230 ISTANBUL
Türkiye

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Region
İstanbul İstanbul İstanbul
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

No data

Participants (8)

Partners (2)

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