Potential analyses identify possible locations for renewable energy installations, such as wind turbines and photovoltaic arrays. The results of previous potential studies for Germany, however, are not consistent due to different assumptions, methods, and datasets being used. For example, different land-use datasets are applied in the literature to identify suitable areas for technologies requiring open land. For the first time, commonly used datasets are compared regarding the area and position of identified features to analyze their impact on potential analyses. It is shown that the use of Corine Land Cover is not recommended as it leads to potential area overestimation in a typical wind potential analyses by a factor of 4.7 and 5.2 in comparison to Basis-DLM and Open Street Map, respectively. Furthermore, we develop scenarios for onshore wind, offshore wind, and open-field photovoltaic potential estimations based on land-eligibility analyses using the land-use datasets that were proven to be best by our pre-analysis. Moreover, we calculate the rooftop photovoltaic potential using 3D building data nationwide for the first time. The potentials have a high sensitivity towards exclusion conditions, which are also currently discussed in public. For example, if restrictive exclusions are chosen for the onshore wind analysis the necessary potential for climate neutrality cannot be met. The potential capacities and possible locations are published for all administrative levels in Germany in the freely accessible database (Tool for Renewable Energy Potentials—Database), for example, to be incorporated into energy system models.

The Internet of Things (IoT) and LoRaWAN technology are increasingly being utilized to optimize building operations. This study evaluates the impact of LoRaWAN wireless communication on the reliability of cloud-based building automation systems (BAS) within a newly constructed hotel building. Employing simulation-based analysis, we quantitatively assess how different data sending modes and data losses affect indoor environmental quality (IEQ), energy consumption, and sensor battery lifetime. The simulation is integrated with a FIWARE-based IoT platform, allowing data communications that are close to practical deployments. The results indicate that with periodic and CO ₂ -triggered sending modes the BAS can maintain high comfort levels and energy efficiency, even under significant data loss. This study concludes that cloud-based BAS demonstrates sufficient stability when using wireless data transmission. Small packet loss rates do not significantly affect system reliability when appropriate data sending modes are employed. These findings also suggest that optimizing data transfer methods can enhance BAS performance while extending sensor battery lifetime and reducing maintenance costs.

Low-temperature district heating networks require accurate demand forecasts and active load control to operate efficiently with reduced supply temperatures and high shares of renewable heat. In practice, however, district heating operators have limited access to real-time data from customer substations and buildings due to privacy concerns, data silos, and lack of interoperability. As a result, operators must apply large safety margins, leading to higher losses and reduced overall system efficiency. This paper proposes a conceptual dataspace architecture based on IDSA-compliant components, the Eclipse Dataspace Components (EDC) together with N5GEH, a FIWARE-based IoT platform. The approach enables building owners to securely share selected substation data under strict usage policies, supporting improved forecasting and demand response while maintaining full data sovereignty.

Local Energy Markets (LEM) emerge as a promising concept to promote energy transition in the building sector. However, persisting issues in data connectivity and the information communication system hinder the adoption of LEM. This study introduces a comprehensive Information and Communication Technology (ICT) system framework, in which two open-source IoT platforms, openHAB and FIWARE, are employed. The proposed framework establishes a reusable foundation for both practical applications of LEM and future research in this field.