Leveraging Big Data Technologies for Smart Grid Development: Frameworks and Implementation

Abstract

As the urgency to ensure energy sustainability and environmental preservation grows in response to climate change and escalating energy demands, transitioning from conventional grid systems to technologically advanced systems become imperative. The proliferation and complexity of data generated during energy production, conversion, measurement, and calculation pose significant challenges to traditional power system management methods. Consequently, the development of a new advanced grid system, which is named smart grid, is proposed. This system incorporates big data technologies to effectively manage the vast amounts of data that were previously cumbersome and difficult to handle. This study introduces the background and fundamental concepts of smart grids and big data, providing a comprehensive overview of mainstream data processing frameworks such as Apache Spark, Apache Storm, and Hadoop. The characteristics and capabilities of these frameworks are demonstrated and compared. The paper summarizes the contributions of these big data technologies to the development of smart grids, identifies the difficulties encountered during implementation, and proposes Apache Flink as a solution to meet the evolving requirements.