  To meet carbon emission reduction goals in line with the Paris agreement,
planning resilient and sustainable energy systems has never been more
important. In the building sector, particularly, strategic urban energy
planning engenders large optimization problems across multiple spatiotemporal
scales leading to necessary system scope simplifications. This has resulted in
disconnected system scales, namely, building occupants and smart-city energy
networks. This paper intends on bridging these disjointed scales to secure both
resilient and more energy-efficient urban planning thanks to a holistic
approach. The intent is to assess the aggregated impact of user behavior
stochasticities on optimal urban energy planning. To this end, a stochastic
energy community sizing and operation problem is designed, encompassing
multi-level utilities founded on energy hub concepts for improved energy and
carbon emission efficiencies. To secure the scalability of our approach, an
organic spatial problem distribution suitable for field deployment is put
forth, validated by a proof of concept. Uncertainty factors affecting urban
energy planning are particularly examined through a local sensitivity analysis,
namely, economic, climate, and occupant-behavior uncertainties. Founded on
historical measurements a typical Dutch energy community composed of 41
residential buildings is designed. Results disclose a fast-converging
distributed stochastic problem, where boilers are showcased as the preferred
heating utility, and distributed renewable energy and storage systems were
identified as unprofitable for the community. Occupant behavior was
particularly exposed as the leading uncertainty factor impacting energy
community planning. This demonstrates the relevance and value of our approach
in connecting occupants to cities for improved, and more resilient, urban
energy planning strategies.
