TY - JOUR
T1 - Optimal Sizing of Shipboard Carbon Capture System for Maritime Greenhouse Emission Control
AU - Fang, Sidun
AU - Xu, Yan
AU - Li, Zhengmao
AU - Ding, Zhaohao
AU - Liu, Lu
AU - Wang, Hongdong
N1 - Funding Information:
The authors would like to thank the Key Laboratory of Maritime Intelligent Equipment and System, Ministry of Education, Shanghai Jiao Tong University, for providing funding support and valuable data for the research.
Funding Information:
Manuscript received February 15, 2019; revised June 19, 2019; accepted July 31, 2019. Date of publication August 7, 2019; date of current version October 18, 2019. Paper 2019-ESC-0229.R1, presented at the 2019 IEEE 55th Industrial and Commercial Power System Conference, Calgary, AB, Canada, May 6–9, and approved for publication in the IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS by the Energy Systems Committee of the IEEE Industry Applications Society. This work was supported in part by Ministry of Education (MOE), Republic of Singapore, under Grant AcRF TIER 1 2019-T1-001-069 (RG75/19). The work of Y. Xu was supported by Nanyang Assistant Professorship from Nanyang Technological University, Singapore. (Corresponding author: Yan Xu.) S. Fang, Y. Xu, and Z. Li are with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798 (e-mail: [email protected]; [email protected]; [email protected]).
Publisher Copyright:
© 1972-2012 IEEE.
PY - 2019/11/1
Y1 - 2019/11/1
N2 - Under increasingly stringent emission regulations, carbon capture system (CCS) is a feasible alternative to reduce the shipping greenhouse gas (GHG) emission before the maturity of renewable energy technology. In this sense, this article proposes an optimal sizing method to determine the capacity of shipboard CCS under strict energy efficiency operating index (EEOI) constraint. The proposed model is formulated as a two-stage planning problem, where the first stage is to determine the capacity of CCS and the expanded capacity of energy storage system to sustain the operation of CCS, and the second stage is a joint shipboard generation and demand-side management model to address the power shortage issue led by the CCS integration. Extensive simulations demonstrate that under EEOI constraint, the CCS integration is feasible to reduce the shipping GHG emission, and the proposed joint generation and demand-side management method is able to relieve the power shortage issue of shipboard CCS. The corresponding average carbon capture level increases 11.9% with the joint management.
AB - Under increasingly stringent emission regulations, carbon capture system (CCS) is a feasible alternative to reduce the shipping greenhouse gas (GHG) emission before the maturity of renewable energy technology. In this sense, this article proposes an optimal sizing method to determine the capacity of shipboard CCS under strict energy efficiency operating index (EEOI) constraint. The proposed model is formulated as a two-stage planning problem, where the first stage is to determine the capacity of CCS and the expanded capacity of energy storage system to sustain the operation of CCS, and the second stage is a joint shipboard generation and demand-side management model to address the power shortage issue led by the CCS integration. Extensive simulations demonstrate that under EEOI constraint, the CCS integration is feasible to reduce the shipping GHG emission, and the proposed joint generation and demand-side management method is able to relieve the power shortage issue of shipboard CCS. The corresponding average carbon capture level increases 11.9% with the joint management.
KW - All-electric ship (AES)
KW - carbon capture system (CCS)
KW - greenhouse gas (GHG) emission
KW - joint management
KW - optimal sizing
UR - http://www.scopus.com/inward/record.url?scp=85075416485&partnerID=8YFLogxK
U2 - 10.1109/TIA.2019.2934088
DO - 10.1109/TIA.2019.2934088
M3 - Article
AN - SCOPUS:85075416485
SN - 0093-9994
VL - 55
SP - 5543
EP - 5553
JO - IEEE Transactions on Industry Applications
JF - IEEE Transactions on Industry Applications
IS - 6
M1 - 8792387
ER -
