Big Data and Smart Grid

Abstract

In the systems of Industry 4.0, data analytics increasingly plays a bigger role. Big data has the potential to create unique, groundbreaking opportunities for the power grid industry, enhancing a global range of societal and economic benefits. A layer of information has been added to the traditional approach for transmission of electricity and scattered network, and as a result of that, it increases the installation of smart meters and sensors, which is being driven by the advancement of information and communication technology. The gathering, storing, and processing of data will be done using this layer. In the energy sector, the big data utilization or use is more. Particularly when it comes to the integration of renewable energy sources with smart networks, there are significant and encouraging obstacles. This chapter discusses the benefits and challenges of using big data analytics for renewable energy power facilities. A crucial component is the capacity to gather facts and apply them effectively for better judgment. A framework was developed for potential big data analytics applications in smart grids and renewable energy power plants. Five different machine learning approaches are used in five steps to anticipate the smart grid’s stability. The dataset’s extremely small amount of data is the work’s primary shortcoming, but the real-time event analysis and cloud computing that were provided were acceptable for the big data analytics framework. Future studies should use larger datasets that reflect global demand for a variety of renewable energy sources.