Abstract

The energy sector is undergoing a transformative shift, driven by the integration of artificial intelligence (AI) and advanced data engineering techniques. At the heart of this evolution lies smart grid technology, which leverages real-time data to optimize energy distribution, enhance grid reliability, and promote sustainability. This paper examines the critical role of data engineering in enabling AI-powered energy systems, addressing challenges such as data silos, real-time processing, and scalability. Through a comprehensive exploration of methodologies, including data pipelines, scalable architectures, and machine learning applications, this study proposes innovative solutions for overcoming existing limitations. The findings, validated through simulations and real-world case studies, underscore the potential of combining data engineering with AI to advance the capabilities of smart grids and foster a more resilient and efficient energy infrastructure.

Keywords

  • Smart Inventory
  • ABC Classification
  • Digital Dashboard
  • Supply Chain Technology
  • Inventory Management
  • Pertamina

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