4.8 Article Proceedings Paper

Quantifying the impact of urban climate by extending the boundaries of urban energy system modeling

Journal

APPLIED ENERGY
Volume 222, Issue -, Pages 847-860

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2018.04.004

Keywords

Urban energy systems; Energy hub; Urban climate; Building simulation; Energy system optimization; Performance gap

Funding

  1. EPFL Middle East
  2. Swiss Competence Center for Energy Research SCCER FEEB&D of the Swiss Innovation Agency Innosuisse [CTI.2014.0119]

Ask authors/readers for more resources

Rapid growth of cities, concerns on global warming and depletion of fossil fuel resources call for sustainable energy solutions for cities. Distributed energy systems such as energy hubs offer promising solutions in this context. Evaluating the energy demand at urban scale is vital to support the design of energy hubs. However, most of the recent studies are based on bottom-up models and do not consider the energy demand in detail. More specifically, the influence of the urban climate on urban energy demand has not been considered so far in the energy system design process. In order to address this research gap, a novel computational platform is developed in the first part of this study, combining an urban climate model with a building simulation tool and an energy system optimization model. The second part of the manuscript is devoted to quantifying the impact of urban climate on energy system design and assessing the consequences of neglecting this specific aspect on energy system performance. Three case studies are conducted considering three building densities for the city of Nablus (building density at the periphery, center and future center of the city) in Palestine. Three scenarios representing (1) standalone buildings (present practice) (2) shadowing and longwave reflection (radiation heat transfer from the walls and the roofs of the buildings to the urban climate and to the sky) of neighboring buildings and (3) urban climate are considered for each case study when computing the energy demand. Subsequently, the energy system is optimized considering Net Present Value (NPV) and system autonomy level as the objective functions (Pareto optimization). The results of the study reveal that the urban climate has a notable impact on the energy demand and energy system design. More importantly, it is shown that the influence of urban climate results in higher fluctuations in the energy demand, which in turn results in a notable increase in the NPV (by up to 40%). This further magnifies the increase in annual or peak demand. The study reveals that neglecting the influence of urban climate in the energy system design process can result in a performance gap in NPV, grid integration level, and greenhouse gas emissions and can impose reliability issues. The design tool introduced in this study can be used for urban planning to mitigate the aforementioned adverse effects.

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