# Toward a Practical Digital Twin Platform Tailored to the Requirements of Industrial Energy Systems
## 1 Introduction  
The mitigation of climate change and environmental damage due to industrial activity are regarded as some of the most pressing issues that society faces today [1]. Consequently, decarbonization and sustainable production are high-priority goals that also have huge implications for the present and the future of energy systems. There are two concurrent transformations with the common goal to make energy systems more efficient: the shift toward integrated energy systems and digitalization. Both of these transitions can mutually benefit from each other [2] since they share essential characteristics, both being highly influenced by technological innovations [3]. The key characteristics of integrated energy systems are that they utilize a high share of energy produced by intermittent renewable sources, high energy-efficient systems, and strong integration of electricity, gas, heating/cooling, mobility systems, and markets to maximize the synergies among new technical solutions [4]. The transition toward integrated energy systems is also eminent within industrial energy systems (IES), where renewable energy sources are gradually replacing fossil sources in an attempt to reduce greenhousegas emissions. Although this transition is supported by policies [5], implementation and even more so the operation of such systems confronts us with serious challenges. The interconnection between different sectors and stakeholders, diversity of demands and technology, numerous sources of uncertainty and large scales to consider require novel approaches from various disciplines. The digitalization of IES is driven by the rapid development of information and communication technologies. This paradigm shift is often referred to as the fourth industrial revolution or Industry 4.0 [6]. While there is justified concern that digitalization could increase energy consumption due to subsequent rebound effects and economic growth [7], there is undoubtedly an immense potential for digitalization and Industry 4.0 to reduce energy consumption and increase economic sustainability [8]. To realize this potential, various applications based on novel digital technologies have been proposed such as forecasting, demand response, operational and design optimization, fault prediction and predictive maintenance, to name just a few. However, today, all these digital applications are usually considered individually. By integrating these solutions into a collaborative platform, their impact could be even more significant. To realize the visions of Industry 4.0 and smart, sustainable integrated energy systems, the digital twin (DT) is considered one of the most promising concepts [9]. DTs are the key enabler for integrating the solutions mentioned in the previous paragraph [10]. DTs in the energy sector can thus fundamentally change the way IES operate, minimize energy consumption and increase the integration of renewable energy sources [11]. However, the concepts and capabilities of DTs are not yet clearly defined and still vigorously debated in contemporary scientific literature. So far, a unified DT platform has not been established but is considered to be direly needed [9]. Furthermore, most work on DTs has focused on the manufacturing domain [12; 13], which differs from the domain of energy systems in various aspects. [PERSON] et al. [9] state that the history of DTs is rather brief and that the concept was first introduced as early as 2003 by [PERSON] in the context of product lifecycle management [14]. The first actual definition of a DT was given by NASA in 2012 [15]. To date, various definitions have arisen and are still the subject of discussion in the literature [16]. [PERSON] et al. [17] and [PERSON] et al. [18] even presented tables of 16 and 21 separate definitions of the DT, which they found in the literature. The basic characteristics given by NASA [15] are still aligned with the refined definition given by [PERSON] et al. [17] and reported by [PERSON] et al. [16] and [PERSON] et al.