# The Applications and Challenges of Digital Twin Technology in Smart Grids: A Comprehensive Review
## 1 Introduction  
In today's world, no one can deny the fact that the power industry plays a crucial role in the progress of society. It can be seen as an engine driving the global economy forward and therefore directly influencing the day-to-day life of individuals. Thus, ensuring safe, stable and sufficient power supply is one of the keys for the sustainable development of our nations. However, we are facing many important challenges in meeting the growing demand for energy with the limited resources we have and the issue of climate change. Projections indicate an anticipated increase of 50% in demand by the year 2050 [1]; this presents a huge challenge for our existing infrastructure as we have to adapt as soon as possible to meet this requirement in a short time. Moreover, a significant portion of the power grids in developed countries have origins tracing back to the early to mid-20 th century, and as such, a considerable segment of this foundational infrastructure is nearing the end of its intended lifecycle [2]. To deal with these issues, there arises an urgent need for the modernization and strengthening of our power grids. One promising avenue for progress manifests in the form of the smart grid concept and the seamless integration of renewable energy resources into the grid framework. As the landscape of the power system undergoes a significant transformation and embraces innovative technologies, the complexity of its structural framework increases exponentially. These new technologies require supplementary functionalities such as computational ability and communication capabilities, which cannot be fully represented in the physical layer. The increased sophistication of power systems necessitates the development of new approaches to address these challenges by providing enhanced information about the physical infrastructure. The main difference between smart grids and conventional power grids relies on the flow of information. What used to be unidirectional transmission from the grid to consumers has evolved into a bidirectional exchange between both parties [3]. Alongside necessitating prompt compliance from consumers with grid commands, smart grids must also adapt their power supply based on user-reported data. The fluid nature of grid networks means their topology can shift continuously due to factors like new generation sources, overloads and outages [4]. Despite remarkable progress, the current state of smart grid development remains incomplete, with anticipated changes on the horizon [5]. Thus, Digital Twin (DT) technology is emerging as a potential remedy for this complexity, facilitating improved network element interaction and aiding grid operators in decision-making, especially during faults and cyber-attacks [6]. DTs are virtual replicas initially conceptualized a decade ago to mimic physical objects like aircraft engines, and have since evolved into comprehensive representations of organizational dynamics. For instance, NASA's Digital Twin initiative, detailed in [7], integrates high-fidelity simulations with health management systems, historical maintenance records, and operational data onboard spacecraft for predictive maintenance, ensuring unparalleled safety and reliability. Similarly, Dassault employs Digital Twins for refined product design and production quality [8]. As shown in Figure 1, earlier models like [PERSON] three-dimensional Digital Twin [9] focused on basic connections between physical and virtual spaces. This concept was then expanded by [10] into a model with five dimensions for manufacturing applications, as shown in Figure 2a. Building on these foundations, [11] proposed a new five-dimensional DT system. This model, illustrated in Figure 2b, consists of five key dimensions: the physical system, digital system, updating engine, prediction engine, and optimization engine.