Exploring the Role of Generative Artificial Intelligence in the Energy Sector: A Comprehensive Literature Review

Generative Artificial Intelligence (GenAI) enhances productivity by creating data, forecasting, optimizing, and understanding human language. In the energy sector, it is projected to have a $240 billion global economic impact, though research remains limited. This paper reviews GenAI's benefits, challenges, and research gaps in the energy sector, also focusing on climate change efforts. A PRISMA-SCR-based literature review from January 2022 to May 2024 was conducted using IEEE Xplore, ScienceDirect, ACM Digital Library, and Google Scholar. GenAI tools extracted data, verified by researchers. Analysis of 33 papers shows GenAI excels in knowledge integration and prediction. It generates synthetic electricity demand data, manages grids, forecasts energy demand, and optimizes renewable energy systems. Key challenges include hallucinations, data biases, privacy concerns, misuse, and system errors. Solutions involve improving training data, system fine-tuning, human oversight, and security measures. Research gaps include synthetic data realism, model evaluation standards, and integrating GenAI with blockchain and IoT.