*2.4. Big Data Applied to Smart Grids*

Munshi et al. [2] presented innovative research for advancing smart grids through big data. They implemented a secure cloud-based platform. Tu et al. [37] conducted a state-of-the-art review of big data applied to smart grid integration. They reviewed big data applications for smart grids, focusing on the latest applications with the latest big data technologies. Kumar et al. [50] designed a circuit to help users take control of power consumption in their homes, improving energy savings through an intelligent method. The measured information from the monitored homes is stored in a big data server. Wang [51] proposed a localization oscillation scheme based on the theory and support of a vector machine, phase difference oscillation, and forced phase difference oscillation. Zang [52] improved the data analysis and data mining tool in energy control and improved the service quality of the electricity market through the computerization of power systems. Mostafa et al. [53] developed a framework for implementing big data analytics for smart grids and renewable energy, and implemented a five-step method to predict the stability of smart grids using five different machine learning methods.
