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Modelling and Optimisation of Ship Energy Systems II
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Modelling and Optimisation of Ship Energy Systems II

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 13438

Image courtesy of Kari Tammi

Special Issue Editors

Prof. Dr. Kari Tammi

E-Mail Website
Guest Editor
Department of Mechanical Engineering, Aalto University, Espoo, Finland
Interests: mechatronics; electric machines; energy efficiency; dynamics; control; adaptive systems; new machine concepts; innovation management
Special Issues, Collections and Topics in MDPI journals
Dr. Dimitrios V. Lyridis

E-Mail Website
Guest Editor
Laboratory for Maritime Transport, School of Naval Architecture and Marine Engineering, National Technical University of Athens, 15780 Athens, Greece
Interests: maritime transport; economics and finance; energy and the environment
Special Issues, Collections and Topics in MDPI journals
Dr. Charis Ntakolia

E-Mail Website
Guest Editor
Laboratory for Maritime Transport, School of Naval Architecture and Marine Engineering, National Technical University of Athens, 15780 Athens, Greece
Interests: applied mathematical sciences; optimization techniques; operational research techniques; numerical analysis; linear and non-linear programming and machine learning
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Stringent environmental regulations, the volatility of fuel prices, alternative fuels, the development of emerging technologies, artificial intelligence methods, big data analytics, ship system autonomy and 4th industrial revolution concepts provide the ship-energy-system designer and operator with both challenges and opportunities, which if appropriately addressed will result in step changes in the way ships’ energy systems are perceived today.

This Special Issue aims to address the modern challenges of comprehensive system design, leveraging existing data and virtualization in the field of ship-energy-system design and operation. It provides a platform for academics, scientists and professionals from industry to exchange the most contemporary ideas, techniques, methods and experience in the area of ship energy systems including modelling, optimisation, control, maintenance, safety, autonomy/automation, environmental friendliness, regulatory framework and sustainability.

This Special Issue mainly intends to accommodate studies and papers presented at the 3rd International Conference on Modelling and Optimisation of Ship Energy Systems (MOSES2021) held on 19–20 May 2021 in Espoo, Finland. However, taking into account the importance and impact of the topics as well as the variety of academic and industrial groups working worldwide in the discipline of the ship energy systems, we invite all interested authors to submit novel/original studies and reviews that advance the scientific/technical understanding of the addressed topics.

Prof. Dr. Kari Tammi
Prof. Dr. Dimitrios V. Lyridis
Dr. Charis Ntakolia
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Ship energy systems—modelling, optimisation, control, design, and operation
  • Big data analytics
  • Maintenance
  • Safety
  • Automation/autonomy
  • Environmental friendliness
  • Sustainability

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Published Papers (4 papers)

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Research

14 pages, 4614 KiB  
Article
A Swarm Intelligence Graph-Based Pathfinding Algorithm Based on Fuzzy Logic (SIGPAF): A Case Study on Unmanned Surface Vehicle Multi-Objective Path Planning
by Charis Ntakolia and Dimitrios V. Lyridis
J. Mar. Sci. Eng. 2021, 9(11), 1243; https://doi.org/10.3390/jmse9111243 - 9 Nov 2021
Cited by 17 | Viewed by 2945
Abstract
Advances in robotic motion and computer vision have contributed to the increased use of automated and unmanned vehicles in complex and dynamic environments for various applications. Unmanned surface vehicles (USVs) have attracted a lot of attention from scientists to consolidate the wide use [...] Read more.
Advances in robotic motion and computer vision have contributed to the increased use of automated and unmanned vehicles in complex and dynamic environments for various applications. Unmanned surface vehicles (USVs) have attracted a lot of attention from scientists to consolidate the wide use of USVs in maritime transportation. However, most of the traditional path planning approaches include single-objective approaches that mainly find the shortest path. Dynamic and complex environments impose the need for multi-objective path planning where an optimal path should be found to satisfy contradicting objective terms. To this end, a swarm intelligence graph-based pathfinding algorithm (SIGPA) has been proposed in the recent literature. This study aims to enhance the performance of SIGPA algorithm by integrating fuzzy logic in order to cope with the multiple objectives and generate quality solutions. A comparative evaluation is conducted among SIGPA and the two most popular fuzzy inference systems, Mamdani (SIGPAF-M) and Takagi–Sugeno–Kang (SIGPAF-TSK). The results showed that depending on the needs of the application, each methodology can contribute respectively. SIGPA remains a reliable approach for real-time applications due to low computational effort; SIGPAF-M generates better paths; and SIGPAF-TSK reaches a better trade-off among solution quality and computation time. Full article
(This article belongs to the Special Issue Modelling and Optimisation of Ship Energy Systems II)
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28 pages, 9323 KiB  
Article
MPC Framework for the Energy Management of Hybrid Ships with an Energy Storage System
by Spyros Antonopoulos, Klaas Visser, Miltiadis Kalikatzarakis and Vasso Reppa
J. Mar. Sci. Eng. 2021, 9(9), 993; https://doi.org/10.3390/jmse9090993 - 11 Sep 2021
Cited by 25 | Viewed by 3137
Abstract
This paper proposes an advanced shipboard energy management strategy (EMS) based on model predictive control (MPC). This EMS aims to reduce mission-scale fuel consumption of ship hybrid power plants, taking into account constraints introduced by the shipboard battery system. Such constraints are present [...] Read more.
This paper proposes an advanced shipboard energy management strategy (EMS) based on model predictive control (MPC). This EMS aims to reduce mission-scale fuel consumption of ship hybrid power plants, taking into account constraints introduced by the shipboard battery system. Such constraints are present due to the boundaries on the battery capacity and state of charge (SoC) values, aiming to ensure safe seagoing operation and long-lasting battery life. The proposed EMS can be used earlier in the propulsion design process and requires no tuning of parameters for a specific operating profile. The novelties of the study reside in (i) studying the impact of mission-scale effects and integral constraints on optimal fuel consumption and controller robustness, (ii) benchmarking the performance of the proposed MPC framework. A case study carried out on a naval vessel demonstrates near-optimal and robust behaviour of the controller for several loading sequences. The application of the proposed MPC framework can lead to up to 3.5% consumption reduction due to utilisation of long term information, considering specific loading sequences and charge depleting (CD) battery operation. Full article
(This article belongs to the Special Issue Modelling and Optimisation of Ship Energy Systems II)
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21 pages, 3670 KiB  
Article
Emission Abatement Technology Selection, Routing and Speed Optimization of Hybrid Ships
by Antti Ritari, Kirsi Spoof-Tuomi, Janne Huotari, Seppo Niemi and Kari Tammi
J. Mar. Sci. Eng. 2021, 9(9), 944; https://doi.org/10.3390/jmse9090944 - 30 Aug 2021
Cited by 10 | Viewed by 3081
Abstract
This paper evaluates the effect of a large-capacity electrical energy storage, e.g., Li-ion battery, on optimal sailing routes, speeds, fuel choice, and emission abatement technology selection. Despite rapid cost reduction and performance improvement, current Li-ion chemistries are infeasible for providing the total energy [...] Read more.
This paper evaluates the effect of a large-capacity electrical energy storage, e.g., Li-ion battery, on optimal sailing routes, speeds, fuel choice, and emission abatement technology selection. Despite rapid cost reduction and performance improvement, current Li-ion chemistries are infeasible for providing the total energy demand for ocean-crossing ships because the energy density is up to two orders of magnitude less than in liquid hydrocarbon fuels. However, limited distance zero-emission port arrival, mooring, and port departure are attainable. In this context, we formulate two groups of numerical problems. First, the well-known Emission Control Area (ECA) routing problem is extended with battery-powered zero-emission legs. ECAs have incentivized ship operators to choose longer distance routes to avoid using expensive low sulfur fuel required for compliance, resulting in increased greenhouse gas (GHG) emissions. The second problem evaluates the trade-off between battery capacity and speed on battery-powered zero-emission port arrival and departure legs. We develop a mixed-integer quadratically constrained program to investigate the least cost system configuration and operation. We find that the optimal speed is up to 50% slower on battery-powered legs compared to the baseline without zero-emission constraint. The slower speed on the zero-emission legs is compensated by higher speed throughout the rest of the voyage, which may increase the total amount of GHG emissions. Full article
(This article belongs to the Special Issue Modelling and Optimisation of Ship Energy Systems II)
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23 pages, 870 KiB  
Article
Convex Optimisation Model for Ship Speed Profile: Optimisation under Fixed Schedule
by Janne Huotari, Teemu Manderbacka, Antti Ritari and Kari Tammi
J. Mar. Sci. Eng. 2021, 9(7), 730; https://doi.org/10.3390/jmse9070730 - 1 Jul 2021
Cited by 8 | Viewed by 2771
Abstract
We present a novel convex optimisation model for ship speed profile optimisation under varying environmental conditions, with a fixed schedule for the journey. To demonstrate the efficacy of the proposed method, a combined speed profile optimisation model was developed that employed an existing [...] Read more.
We present a novel convex optimisation model for ship speed profile optimisation under varying environmental conditions, with a fixed schedule for the journey. To demonstrate the efficacy of the proposed method, a combined speed profile optimisation model was developed that employed an existing dynamic programming approach, along the novel convex optimisation model. The proposed model was tested with 5 different ships for 20 journeys from Houston, Texas to London Gateway, with differing environmental conditions, which were retrieved from actual weather forecasts. As a result, it was shown that the combined model with both dynamic programming and convex optimisation was approximately 22% more effective in developing a fuel saving speed profile compared to dynamic programming alone. Overall, average fuel savings for the studied voyages with speed profile optimisation was approximately 1.1% compared to operation with a fixed speed and 3.5% for voyages where significant variance in environmental conditions was present. Speed profile optimisation was found to be especially beneficial in cases where detrimental environmental conditions could be avoided with minor speed adjustments. Relaxation of the fixed schedule constraint likely leads to larger savings but makes comparison virtually impossible as a lower speed leads to lower propulsion energy needed. Full article
(This article belongs to the Special Issue Modelling and Optimisation of Ship Energy Systems II)
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