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An inexact optimization model for distributed multi‐energy systems management in sustainable airports
Author(s) -
Jin Shuwei,
Li Yongping,
Yu Lei
Publication year - 2021
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.6634
Subject(s) - environmental science , electricity , computer science , environmental economics , process engineering , engineering , electrical engineering , economics
Summary 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.