Research Article
AnEfficientandCost-EffectivePowerSchedulingin
Zero-EmissionFerryShips
ArminLetafat,
1
MehdiRafiei,
2
MasoudArdeshiri,
1
MortezaSheikh,
2
MohsenBanaei ,
3
JalilBoudjadar,
4
andMohammadHassanKhooban
4
1
Department of Electronics and Electrical Engineering, Islamic Azad University, Kazerun Branch, Kazerun, Iran
2
Department of Electrical and Electronic Engineering, Shiraz University of Technology, Shiraz, Iran
3
Faculty of Engineering, Ferdowsi University of Mashhad, P.O. Box 91775-1111, Mashhad, Iran
4
Department of Engineering, Aarhus University, Aarhus 8200, Denmark
Correspondence should be addressed to Mohammad Hassan Khooban; mhkhoban@gmail.com
Received 7 November 2019; Revised 6 February 2020; Accepted 25 February 2020; Published 17 April 2020
Guest Editor: Viet-anh Pham
Copyright © 2020 Armin Letafat et al. is is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Today’s remarkable challenge of maritime transportation industry is the detrimental contamination generation from fossil fuels.
To tackle such a challenge and reduce the contribution into air pollution, different power solutions have been considered; among
others, hybrid energy-based solutions are powering many ferry boats. is paper introduces an energy management strategy
(EMS) for a hybrid energy system (HES) of a ferry boat with the goal to optimize the performance and reduce the operation cost.
HES considered for the ferry boat consists of different devices such as proton exchange membrane fuel cell (PEMFC), LI-ION
battery bank, and cold ironing (CI). PEMFC systems are appropriate to employ as they are not polluting. e battery bank
compensates for the abrupt variations of the load as the fuel cell has a slow dynamic against sudden changes of the load. Also, CI
systems can improve the reduction of the expenses of energy management, during hours where the ferry boat is located at the
harbor. To study the performance, cost and the pollution contribution (CO
2
, NO
X
, SO
X
) of the proposed hybrid energy
management strategy (HEMS), we compare it against three various types of HEM from the state-of-the-art and also available rule-
based methods in the literature. e analysis results show a high applicability of the proposed HES. All results in this paper have
been obtained in the MATLAB software environment.
1.Introduction
Renewable energy resources (RESs) have received growing
attention in supplying the required energy of different
systems during the last years. e marine industry has also
been affected by this trend. Application of renewable and
clean energies for supplying the required energy of the
marine vessels like small ships and boats is growing and this
has led to introducing the concept of Electric Ferry Boats
(EFBs) in the marine industry. Different combinations of
fossil fuel-based resources and RESs such as diesel gener-
ators (DGs), fuel cells (FCs), solar panels, storage batteries
(SBs),andcoldironing(CI)[1–3]canbeusedintheEFBsfor
supplying the demand and providing the propulsion force of
these boats. In this situation, optimal energy management of
the EFB is an important subject from the viewpoint of both
ship owners and reliability concerns that should be con-
sidered to reduce the operation cost while considering the
operation constraints of the equipment.
Optimal energy management of the marine vessels has
been studied before in the literature. e authors of [4]
provided an energy management schedule in the electric
ship according to the Model Predictive Control (MPC) to
optimize the concordance between power generators and
batteries’ energy-saving under high-power ramp rate loads.
e authors of [5] proposed manner-based energy man-
agement by means of Fuzzy Logic (FL) and Proportional-
Integration (P-I) control in an all-electric ship with only
electric storage devices. Abkenar et al. [6] apply a genetic
algorithm to find the proper and safe operation of fuel cells
Hindawi
Complexity
Volume 2020, Article ID 6487873, 12 pages
https://doi.org/10.1155/2020/6487873