@article{Danish2023, 
author = {Mir Sayed Shah Danish and Tomonobu Senjyu},
title = {Shaping the future of sustainable energy through AI-enabled circular economy policies},
year = {2023},
journal = {Circular Economy},
volume = {2},
number = {2},
pages = {100040},
keywords = {Energy policy, Circular economy, AI-enabled energy policy, Decarbonization, Policy tools},
url = {https://www.sciopen.com/article/10.1016/j.cec.2023.100040},
doi = {10.1016/j.cec.2023.100040},
abstract = {The energy sector is enduring a momentous transformation with new technological advancements and increasing demand leading to innovative pathways. Artificial intelligence (AI) is emerging as a critical driver of the change, offering new ways to optimize energy systems operations, control, automation, etc. Developing a competitive policy framework aligned with circular economy practices to adapt to the trends of the rapid revolution is crucial, shaping the future of energy and leading the sector in a sustainable, equitable, and impartial direction. This study aims to propose an AI-driven policy framework that aligns with the circular economy business model to address the transformation trend in the development of energy policies through a multidisciplinary approach. The study identifies key trends, various approaches, and evaluates the potential of AI in addressing the challenges. The AI-driven policy paradigm outlines a comprehensive framework and roadmap to harness the potential of AI through a forward-looking policy framework that considers the rapidly changing landscape and the essence of the circular economy. The proposed novel framework provides a roadmap for researchers, governments, and other stakeholders to navigate the future of energy and unlock the potential of AI for a sustainable energy future.}
}