This study presents a new optimization framework of both urban morphology as well as district energy systems. It is entirely embedded within the 3D-CAD software Rhinoceros / Grasshopper. Here, Mixed Integer Linear Programming (MILP) and Simulated Annealing (SA) are applied to solve the design and operation of a district energy system (DES) as well as the geometric design of the urban morphology. Two approaches are compared: In the first, urban morphology is optimized using SA, and subsequently

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... he DES for the final urban morphology is optimized using MILP. In the second approach, the district energy system optimization using MILP is nested within the urban morphology optimization using SA. Therefore, the higher level optimizer (SA) can exploit information from the lower level optimizer (MILP) and hence find better solutions. Results show that rather than addressing urban morphology and DES consecutively, both levels should be evaluated interdependently -especially for high carbon reduction targets. It is shown that urban planning should integrate both energy systems and morphology into a holistic design process.