Building and construction sector is responsible for 40% of the total energy consumption and 36% of the total greenhouse gas emissions in the European Union. Digital twin is an emerging digital tool that facilitates building management through data interactions using sensor readings between a physical building and its digital model and improves operation and enhances transparency. However, since the digital twin technologies are not mature and has several challenges associated with it, such as need for extensive data, it is necessary to conduct a systematic literature review on its application to buildings and smart grids. The majority of the current studies look into how digital twins can be used for the management of normal residential or commercial buildings that are connected to conventional electricity grids with little scope for bidirectional power flow. This study conducts a systematic literature review to map the current landscape of research on digital twins in grid-interactive buildings, with a focus on identifying the software tools used in the creation of digital twins for improving energy efficiency. The study uses scientific databases like Scopus and Web of Sciences and has been carried out in accordance with PRISMA guidelines that specify the different steps involved in the methodology to conduct systematic reviews. Autodesk Revit and Artificial Neural Networks emerged as the most common software and technique, based on previous works.