Green smart grid predictive analysis to integrate sustainable energy of emerging V2G in smart city technologies

Abstract

In recent years, the volume of data has grown exponentially. Big data analytic platforms for the smart grid have enormous potential since they play an essential role in the decision-making process and help to prevent disasters or instabilities in the grid. Vehicle to Grid (V2G) technology has become a buzzword in the industry. It is posited as a forthcoming technology to be grasped in a distant, ultimately green, and future. However, this view is now being challenged as V2G is being deployed at a large scale. The severe challenges of rapid population growth, ecological pollution, and energy deficiency have encouraged the design of smart grids and electric transport systems, especially electric vehicles containing central energy utilization systems in a smart city. This paper proposes a robust and distributed approach to balance supply and demand. This study have constructed a unique framework to manage the ambiguous performances of vehicles and supplied energy resources in a smart city. Furthermore, it analyze the influence of network topology by evaluating the strength of solid network motifs using predictive analysis for the whole system.