Distributed or centralized? Designing district-level urban energy systems by a hierarchical approach considering demand uncertainties

Rui Jing, Meng Wang, Zhihui Zhang, Xiaonan Wang, Ning Li, Nilay Shah and Yingru Zhao

Applied Energy, 2019, vol. 252, issue C, -

Abstract: The optimal design of urban energy system is considered as a global challenge for improving urban sustainability, efficiency and resilience. The optimization problem is normally formulated as a mixed-integer programming model. With certain spatial and temporal resolution, the model complexity will increase rapidly when the modelling scale expands. The uncertainty of demand further makes the problem more complex. Therefore, to model large-scale urban energy systems, the trade-off between modelling resolution and computational cost has to be considered. This study introduces a hierarchical based approach to decompose the district-level problem into neighborhood-level sub-problems by clustering technique. Two technical routes are further proposed, (1) the energy hub mode adopts Graph theory techniques to obtain an optimal solution rapidly with a slight sacrifice on optimality; (2) the distributed mode enables high optimality but requires significantly high computational cost. Both two routes deal with multiple uncertainties of cooling and heating demand via stochastic programming.

Keywords: Urban energy system; Energy network; Multi scale; Demand complementarity; Uncertainty; Stochastic programming (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (32)

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DOI: 10.1016/j.apenergy.2019.113424

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