Renewable Energy Supply Concepts for Next Generation Cities Using the Integrated Urban Modeling Platform Insel 4D
Abstract
To decarbonize the urban energy system, a maximum amount of renewable energy generation is crucial in addition to demand reduction strategies. Depending on the density of urban areas, the contribution of local renewable energy generation varies. It is still an open question whether local or regional renewable generation or import from further locations has the best cost and life cycle performance. To model such scenarios, an urban data management and modeling platform is under development to provide a software infrastructure for smart and sustainable city planning and operation. Today such platforms are mostly designed to handle and analyze large urban data sets from very different domains. Modeling and optimization is usually not part of the software concepts. However, such functionalities are considered crucial for transformation scenario development and optimized smart city operation. The paper discusses the required software architecture concepts for energy demand and renewable energy generation modeling. The main driver is to derive zero carbon strategies for cities while including all major sectors of CO2 generation. The platform needs to handle multiple scales in the time and spatial domain, ranging from long term population and land use change to hourly or sub-hourly matching of renewable energy supply and urban energy demand. The methodology and software concepts are applied to the case study district Brooklyn Borough Hall in New York. Based on the building energy demand modeled from the 3D city geometry, various renewable energy supply scenarios are simulated. The results show that 80 percent of the building heating and cooling demand can be covered by local and nearby renewables at double the cost of today´s electricity.