Erkata Yandri from Indonesia (PPRE 2003-04), RE lecturer in the graduate program of Renewable Energy at Darma Persada University in Jakarta published two articles together with his PG students last year with respect to: Hybrid Energy Solutions for Sustainable Offshore Oil and Gas Operations: Leveraging Thermoelectric, Solar, and Wind Potential and Predictive Maintenance with Machine Learning: A Comparative Analysis of Wind Turbines and PV Power Plants.

Article: Hybrid Energy Solutions for Sustainable Offshore Oil and Gas Operations: Leveraging Thermoelectric, Solar, and Wind Potential

As the offshore oil and gas industry seeks sustainable energy solutions, integrating renewable sources is no longer an option, it’s a necessity. This study presents a hybrid energy system combining thermoelectric generators (TEGs) with solar and wind power to reduce carbon emissions, enhance efficiency, and cut fossil fuel dependence. Through a comprehensive analysis, the research highlights how this innovative hybrid approach can revolutionize offshore operations, ensuring energy resilience while mitigating environmental impact. Dive into the future of offshore energy sustainability with this groundbreaking study.

Read it here.

Article: Predictive Maintenance with Machine Learning: A Comparative Analysis of Wind Turbines and PV Power Plants

As the renewable energy sector expands, ensuring the reliability and efficiency of wind turbines and PV power plants is more critical than ever. This study explores how machine learning-driven predictive maintenance (PdM-ML) can revolutionize failure prediction, optimize operational costs, and enhance energy efficiency. By comparing PdM-ML models for wind and solar technologies, the research highlights key advantages, challenges, and best practices for predictive maintenance in renewable energy systems. Discover how AI-powered maintenance strategies are paving the way for a more sustainable and resilient energy future.

Read it here.