4.8 Article

Quantifying demand flexibility based on structural thermal storage and comfort management of non-residential buildings: A comparison between hot and cold climate zones

Journal

APPLIED ENERGY
Volume 195, Issue -, Pages 1047-1054

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.apenergy.2017.03.004

Keywords

Demand flexibility; Flexibility; Grid integration of the demand side; Building energy simulations

Funding

  1. Partners for International Business Program Smart Cities Texas, under the Energy Efficient Building project as part of the Smart Energy Regions-Brabant program - Province of Noord Brabant, the Netherlands

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Recently, demand flexibility has been highlighted as a promising distributed resource from the customer side, especially from industrial customers like commercial buildings, capable of providing grid support services. However, the quantification of demand flexibility is a complex process that requires a methodology including the requirements of both the grid operators and the customers. This paper proposes a novel approach to quantify the available demand flexibility of individual buildings, while taking into account the underlying building energy physics. The proposed approach constructs on the operational flexibility concept from the power systems, and extends it to include a comfort domain, identifying different flexibility parameters with the aim of giving a better insight into the flexibility potential of commercial buildings. This method includes a development of building energy simulations to assess the effects of weather variations, construction types, and comfort constrains on demand flexibility. The proposed quantification method has been validated using 15 different office building models and two different climate zones, i.e., the Netherlands and Texas, US. The results presented in this paper suggest that buildings located in a hot climate could offer higher flexibility potential during shorter time ranges, while buildings in a cold climate could offer lower flexibility potential but during longer time ranges. Determining these differences could potentially facilitate the dispatch of flexible demand resources, to assess their real potential, and to schedule demand flexibility between stakeholders. (C) 2017 Elsevier Ltd. All rights reserved.

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