The energy sector is undergoing a major transformation, driven by the need to decarbonize and meet the growing demand for electricity. Digital twin technology is emerging as a key enabler of this transformation, offering the potential to improve the efficiency, reliability, and sustainability of energy systems. This thesis investigates the use of digital twins and digital shadows in the context of energy systems. The thesis begins by providing clear and concise definitions for these terms, highlighting their importance in understanding and optimizing energy systems. The thesis then conducts a thorough software analysis of the energy system provided by KISTERS, and writes objectives and use cases for the software product. These use cases are then stored in a database using MongoDB and Elasticsearch, providing a more accessible and searchable resource. The results of this study have several implications for the design and development of digital twins for energy systems. First, the proposed definitions provide a clear framework for understanding and implementing these technologies. Second, the exercise of reverse requirements engineering for the KISTERS energy system has illuminated the main requirements and functionalities of the system through use cases. Third, the use of a database to store use cases provides a more accessible and searchable resource, which can be used to improve the design and development of digital twins for energy systems.