Modelling and Assessment of Renewable Energy Production and Utilisation

The growing global need for energy together with negative effects of fossil fuel combustion has been driving humanity to switch to renewable energy resources. This research paper is dedicated to modelling and assessing the use of renewable energy, with an emphasis on reliable prediction, optimization, and performance assessment methods. The types of renewable energy, such as solar, wind, hydropower, biomass, and other forms, will be considered in light of their generation capability, effectiveness, and implementation within the energy industry. This paper covers a wide range of modelling techniques, from traditional mathematical modelling to modern machine learning and artificial intelligence-based approaches that can help to forecast energy generation and demands. Also, assessment tools and performance indices (energy efficiency, economic sustainability, environmental impacts, reliability) will be reviewed with a focus on hybrid energy systems and advanced smart grids. Moreover, challenges of renewable energy intermittency, storage solutions, grid connectivity, and regulatory frameworks will be addressed, with particular attention paid to innovations in energy storage technologies and digital energy systems.

Renewable Energy, Sustainability, Energy Storage Modelling Techniques, Machine Learning, Optimization, Regulatory Frameworks

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