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A Comprehensive Artificial Intelligence-Based Approach to Hydropower Integration as a Renewable Energy Source

Year: 2024

Type: conference-paper

Abstract: A clean energy future depends on integrating renewable sources, such as hydropower. This research investigates the potential of AI to maximize hydropower’s value within the energy system. We aim to contribute to a more sustainable and efficient energy future by analyzing AI’s application in managing and optimizing hydropower systems. Research shows that AI can improve hydropower utilization, efficiency, flexibility, and reliability. Machine learning algorithms can predict river flows, optimize hydropower plant operations, and regulate control and monitoring systems in real-time. AI also supports planning and decision-making for new hydropower projects. While implementing AI requires an initial investment, the long-term economic, social, and environmental returns justify this outlay. Artificial intelligence has been proven to improve hydropower-based electricity systems’ efficiency, flexibility, and reliability as an environmentally friendly renewable energy source.

Source: Proceedings of International Conference on Multidiciplinary Research

DOI: 10.32672/picmr.v7i1.2714

Authors: Munawir, Mahidin, Yuwaldi Away, Azwar, Wan Izhan Nawawi Wan Ismail

Institutions: Universitas Syiah Kuala, Universiti Teknologi MARA System, Universiti Teknologi MARA

Language: English

Topic: Power Systems and Renewable Energy

Subfield: Energy Engineering and Power Technology

Field: Energy

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure, Climate action

Open Access status: hybrid

OpenAlex ID: W4408766373

FWCI:

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