A Brief Investigation for Techniques of Deep Learning Model in Smart Grid

Over the last few years, smart grid has gained a tremendous attention from the research community. To ensure the effective acquisition, transmission, protection and control of various data in the smart grid, so that the smart grid can realize the dynamic exchange and interaction of information and meet the sustainable requirements of power development, which has gradually become a realistic choice for the construction and development of smart grid. Various soft and hardware techniques have been proposed for efficient smart grid. Deep learning techniques are one of the soft computing approaches which can be applied to automate and further improve the performance of the smart grid. Although, this research domain of deep learning model in smart grid is gaining some attention, there is a strong need for a motivation to encourage researchers to explore more in this area. In this paper, we have investigated on recent development in the field of deep learning techniques in smart grid. In the study, various performance metrics including total papers, total citations, and citation per paper are calculated. Further, top 10 or 20 of most productive and highly cited authors, discipline, source journals, countries, institutions, and highly influential papers are also evaluated. Later, a comparative analysis is performed on the deep learning techniques in smart grid after analyzing the most influential works in this field.