4.7 Article

An inexact optimization model for distributed multi-energy systems management in sustainable airports

Journal

INTERNATIONAL JOURNAL OF ENERGY RESEARCH
Volume 45, Issue 9, Pages 13071-13087

Publisher

WILEY
DOI: 10.1002/er.6634

Keywords

distributed energy resource; multi‐ energy; optimization model; sustainable airports; uncertainty

Funding

  1. Fundamental Research Funds for the Central Universities [3122019175]
  2. Scientific Research Foundation [2020KYQD61]

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This paper introduces a fuzzy chance-constrained fractional programming (FCFP) method for planning distributed multi-energy systems (DMES), which was applied to a real airport in a case study. Results showed that the combined cooling, heat, and power were the primary distributed energy resource, providing significant heating, cooling, and electricity in different seasons. A comparison between conventional energy system (CES) and DMES revealed differences in energy consumption, economic aspects, and environmental performance, with DMES showing better environmental performance and peak shaving function.
This paper proposes a fuzzy chance-constrained fractional programming (FCFP) method for planning distributed multi-energy systems (DMES). FCFP can deal with uncertainties expressed as fuzzy information, probability distributions, and multiple objectives. The FCFP-DMES model was applied to a real airport in a case study, and a series of scenarios were selected to examine the effects of the uncertainty on the energy supply and technology selection. Additionally, a comparison related to conventional energy system (CES) and DMES are discussed from energy consumption, economic, and environmental aspects. The results revealed the following: the combined cooling, heat, and power would serve as a primary distributed energy resource providing heating, cooling, and electricity in different seasons, accounting for approximately 40% of the total; among different alternative technologies, heating supplied by gas-fired boiler and thermal storage would serve as auxiliary heaters to cover 6.6% and 15.2% of the heating load, respectively, under high-level demand; although the DMES cannot bring cost-cutting, it has better environmental performance and a peak shaving function. Compared with the DMES, the CES would almost double the electricity purchasing cost (reaching $9.56 million), and an additional 136.24 MW of electricity would be needed, which would result in 127.5 tons/year of pollutant emissions. The findings of this study indicate that the FCFP-DMES model can provide a comprehensive and systematic strategy considering the multi-energy, multi-technology, and multi-uncertainty within the DMES.

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