The role of Distributed Energy Resources (DER) is increasing significantly in electrical power systems due to many environmental, economic, and political drivers. This transition has also put the electrical distribution grid in a central role. The challenges arising from this transition are largely being addressed under Smart Grid (SG) initiatives. Although there is no standard definition, in general, a SG refers to a method of incorporating intelligence into the operation of a distribution grid to increase flexibility and performance. For electrical power systems, Alternating Current (AC) distribution grids are a well-known infrastructure that has been in use for a long time. This infrastructure can be assisted by Direct Current (DC) technologies as a possible backbone to increase, for example, Renewable Energy Sources (RES) hosting capacity; however, they must be designed on a solid basis to allow for rapid roll-out and integration. It is critical to provide and test suitable methodologies and resources to lower entry barriers for early adoption processes to maximize the implementation capability of new DC technologies. The HYPERRIDE project aims to support this transition toward the transformation in the electrical grid infrastructure by laying the groundwork for widespread adoption of DC technology. The future distribution grid both at the Low Voltage Direct Current (LVDC) component to Medium Voltage Direct Current (MVDC) backbone is planned to be demonstrated at three pilot sites (Germany, Italy, and Switzerland) implementing relevant use cases. These pilots will provide valuable insights and help identify the gaps in knowledge and possible solutions for the various focus areas. The use cases for the implementation are documented in this deliverable along with the standards and background, the methodology, and the analysis. Interoperability among the components and sub-systems of the developed AC/DC hybrid power system solution is a key goal in the HYPERRIDE project, as having an interoperable solution has numerous benefits for all stakeholders. In general, interoperability implies that information conveyed from a sender system to a receiver system can be used meaningfully by the latter, necessitating at least some interpretation and contextualization of the data. One of the main goals of the HYPERRIDE project is to achieve a higher level of interoperability Interoperability is a challenging quality attribute to achieve because it necessitates a thorough understanding of the problem, the solution, and its interrelation. Data is at the center of interoperability, necessitating its consideration in any effort to achieve a higher level of interoperability. In most circumstances, data interoperability is a challenge to be addressed when two systems are unable to communicate because the information they share is either encoded differently or using a different data structure. This points out that interoperability is concerned with how the two communicating systems use some data model that is abstracted and updated to meet the needs of the two systems. An ontology is a formal description of knowledge as a set of concepts within a domain and their interrelationships and provides an abstract model that can describe, in a formal language based on mathematical logic, relevant aspects (concepts, relationships, properties, facts, rules) of a phenomenon or domain of interest that is intended to be represented for some purpose. Apart from being useful for many other aspects, an ontology provides a sound basis for developing an interoperable data model. Development of an ontology for AC/DC hybrid power system is the goal of this task. This deliverable reports the background, motivation, state-of-the-art, development methodology, and description of the ontology itself. Developing data models in a heterogeneous and uncoordinated manner typically results in data stovepipes/data silo issues, which can be challenging for attaining interoperability and impede the ontology’s reusability potential while also making integration difficult. Ontological realism is a method of developing an ontology to be more like a reality model than a data model in order to maximize its utility and stability. It is being advocated as one of the best practices for ontology development and is used to create models for most of the data sources in the world. HADGO is being developed using the ontological realism technique based on basic hybrid AC/DC grid models in conjunction with expert knowledge, judgments, and opinions from the involved experts.