Stochastic energy management of large industrial-scale aquaponics considering robust optimization-based demand response program
Yingying Zheng,
Wenjing Zhao,
Monika Varga and
Daoliang Li
Applied Energy, 2024, vol. 374, issue C, No S0306261924013655
Abstract:
Large industrial-scale aquaponics systems, which combine industrial water recycling aquaculture technology with soilless culture technology, are innovative and sustainable alternatives for food production in regions with limited agricultural land and water resources. Industrial-scale aquaponics is heavily dependent on fossil fuels and the electricity expenditures account for a high percentage of operating costs. The differentiated operating characteristics of the electrical facility and varying ideal environment conditions of the paired fish and vegetables create challenges when it comes to devising an optimization strategy. By analyzing the flexible characteristics of the dispatchable units, this study proposes a demand response-based load scheduling approach that optimizes the unit operating schemes for cost minimization. Based on the assumptions, the case study exhibits that the optimized operation scheme decreases the energy consumption by 11.73% and 8.49%, and reduces the operating costs by 18.15% and 16.37% for 3 typical summer days and winter days, respectively. The proposed approach was applied to scenarios integrating varying fish species and plant choices to demonstrate the efficiency and effectiveness of the proposed energy-saving technique.
Keywords: Industrial-scale aquaponics; Energy management strategies; Demand response; Energy conservation (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0306261924013655
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:appene:v:374:y:2024:i:c:s0306261924013655
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/bibliographic
http://www.elsevier. ... 405891/bibliographic
DOI: 10.1016/j.apenergy.2024.123982
Access Statistics for this article
Applied Energy is currently edited by J. Yan
More articles in Applied Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().