Smart Grids ideally interconnect intelligent grid members. One big share of grid presence is with buildings. Flexible and grid-friendly buildings would improve grid management and are an important contribution to the integration of renewable energy sources. Classical buildings, however, are passive and not cooperative. This article describes how electro-thermal processes in buildings can be used for demand response and how such intelligent behavior can be enabled via communication technology. Experiments and simulations on typical mid-European buildings were done to estimate the potential time constants.

The paper explains a workflow to simulate the food energy water (FEW) nexus for an urban district combining various data sources like 3D city models, particularly the City Geography Markup Language (CityGML) data model from the Open Geospatial Consortium, Open StreetMap and Census data. A long term vision is to extend the CityGML data model by developing a FEW Application Domain Extension (FEW ADE) to support future FEW simulation workflows such as the one explained in this paper. Together with the mentioned simulation workflow, this paper also identifies some necessary FEW related parameters for the future development of a FEW ADE. Furthermore, relevant key performance indicators are investigated, and the relevant datasets necessary to calculate these indicators are studied. Finally, different calculations are performed for the downtown borough Ville-Marie in the city of Montréal (Canada) for the domains of food waste (FW) and wastewater (WW) generation. For this study, a workflow is developed to calculate the energy generation from anaerobic digestion of FW and WW. In the first step, the data collection and preparation was done. Here relevant data for georeferencing, data for model set-up, and data for creating the required usage libraries, like food waste and wastewater generation per person, were collected. The next step was the data integration and calculation of the relevant parameters, and lastly, the results were visualized for analysis purposes. As a use case to support such calculations, the CityGML level of detail two model of Montréal is enriched with information such as building functions and building usages from OpenStreetMap. The calculation of the total residents based on the CityGML model as the main input for Ville-Marie results in a population of 72,606. The statistical value for 2016 was 89,170, which corresponds to a deviation of 15.3%. The energy recovery potential of FW is about 24,024 GJ/year, and that of wastewater is about 1,629 GJ/year, adding up to 25,653 GJ/year. Relating values to the calculated number of inhabitants in Ville-Marie results in 330.9 kWh/year for FW and 22.4 kWh/year for wastewater, respectively.

Effective weed management is crucial in the critical period of sugar beet production, but often lacks sustainability and environmental protection. Recent advancements in sensor-based weed control systems have rendered the latter a realistic prospect, which demands detailed analyses, especially under suboptimal field conditions. The present study analysed six robotic-assisted weed control systems (RAWS) in three experiments on sugar beets in 2024, conducted under dry soil and high weed pressure. The experiments included sensor-based inter-row and intra-row hoeing, spot-and band-spraying and were compared to a broadcast herbicide treatment and an untreated control. Weed control efficacy (WCE) in the intra-and inter-row areas, as well as weed species composition and crop plant damage, were assessed after treatment. The data show that intra-row WCE of two hoeing robots (Farming GT® and Robovator®) equipped with