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A. Mahdavi, N. Ghiassi, M. Vuckovic, M. Taheri, F. Tahmasebi:
"High-resolution representations of internal and external boundary conditions in urban energy modelling";
Talk: Building Simulation 2017 - 15th International Conference of the International Building Performance Simulation Association, San Francisco, USA; 2017-08-07 - 2017-08-09; in: "Proceedings of the 15th IBPSA Conference San Francisco, CA, USA, Aug. 7-9, 2017", IBPSA (ed.); IBPSA, (2017), 28 - 37.

Integrative computational environments that can support
effective planning of urban-level energy management
activities are indispensable to the development of
sustainable cities. These environments rely on urban
energy models, which, bound to achieve computational
efficiency, have in the past frequently relied on
simplified procedures. However, the temporal dynamics
of load patterns and their dependency on transient
phenomena (e.g., inhabitants´ presence and actions)
cannot be realistically represented when using simplified
models. To address this circumstance, we have
conceived the framework of an integrative urban
decision support environment, relying on simulation. In
this regard, we have designed, implemented, and
documented an urban energy modelling approach that
combines cluster analysis and sampling techniques to
enable full dynamic numeric simulation capability. The
latter capability enables in principle the processing of
highly resolved time series data pertaining both to
external (microclimatic) and internal (user-dependent)
boundary conditions. In this paper, we elaborate on the
framework of the envisaged environment, introduce its
various components, and report on our current
developmental activities.

(no german version) Integrative computational environments that can support
effective planning of urban-level energy management
activities are indispensable to the development of
sustainable cities. These environments rely on urban
energy models, which, bound to achieve computational
efficiency, have in the past frequently relied on
simplified procedures. However, the temporal dynamics
of load patterns and their dependency on transient
phenomena (e.g., inhabitants´ presence and actions)
cannot be realistically represented when using simplified
models. To address this circumstance, we have
conceived the framework of an integrative urban
decision support environment, relying on simulation. In
this regard, we have designed, implemented, and
documented an urban energy modelling approach that
combines cluster analysis and sampling techniques to
enable full dynamic numeric simulation capability. The
latter capability enables in principle the processing of
highly resolved time series data pertaining both to
external (microclimatic) and internal (user-dependent)
boundary conditions. In this paper, we elaborate on the
framework of the envisaged environment, introduce its
various components, and report on our current
developmental activities.