The cold ironing system is gaining interest as a promising approach to reduce emissions from ship transportation at ports, enabling further reductions with clean energy sources coordination. While cold ironing has predominantly been applied to long-staying vessels like cruise ships and containers, feasibility studies for short-berthing ships such as ferries are limited. However, the growing demand for short-distance logistics and passenger transfers highlights the need to tackle emissions issues from ferry transportation. Incorporating electrification technology together with integrated energy management systems can significantly reduce emissions from ferry operations. Accordingly, this paper proposes a cooperative cold ironing system integrated with clean energy sources for ferry terminals. A two-stage energy management strategy combining sizing and scheduling optimization is employed to reduce the port's emissions while minimizing system and operational costs. The proposed system configuration, determined through the sizing method, yields the lowest net present cost of $9.04 M. The applied energy management strategy managed to reduce operational costs by up to 63.402 %, while significantly decreasing emissions from both shipside and shoreside operations. From the shipside, emissions reductions of 38.44 % for CO2, 97.7 % for NOX, 96.69 % for SO2, and 92.1 % for PM were achieved. From the shoreside, the approach led to a 28 % reduction across all emission types. Thus, implementing cold ironing powered by clean energy sources is a viable solution for reducing emissions generated by ferry operations. The proposed energy management approach enables emissions reduction and delivering cost-effectiveness at ferry terminals.
The maritime industry is a crucial hard-to-abate sector that is expected to depend on high-energy density renewable liquid fuels in the future. Traditionally, decarbonization pathways have been assessed assuming exogenous cost trajectories for renewable liquid fuels based on an exogenous learning curve. While past studies have looked at the impact of endogenizing learning curves for a specific technology utilizing linear approximation, a fully endogenous direct non-linear implementation of learning curves in a detailed sectoral model (maritime industry) that explores dynamics concerning sensitive parameters does not yet exist. Here, we apply an open-source optimization model for decarbonizing the maritime industry and further develop the model by encompassing a nonconvex mixed-integer quadratically constrained programming approach to analyze the impact of endogenized learning curves for renewable fuel costs following an experience curve approach. We find that global greenhouse gas emissions are significantly lower (up to 25% over a 30 year horizon) when utilizing endogenously modeled prices for renewable fuels compared to commonly used exogenous learning frameworks. Furthermore, we find that conventional modeling approaches overestimate the cost of climate mitigation, which can have significant policy implication related to carbon pricing and fuel efficiency requirements. In a broader context, this emphasizes the potential opportunities that can be achieved if policymakers and companies accelerate investments that drive down the costs of renewable technologies efficiently and thus trigger endogenous experience-based learning in real life.
This paper presents an assessment of the energy harvesting potential from wave-induced motions when producing electricity by linear generators installed on ships. The study estimates an upper maximum energy extraction potential by not considering the electro-mechanical coupling; neither is mechanical and electrical dissipation considered. The analysis of the harvested energy is made using simulated data in a case study investigating three different ships (by size). Specifically, the case study reveals that, in moderate to mildly severe sea states, the power harvested from the environment using linear generators may reach values around 1–2 kW/tons of seismic mass. Thus, it is unrealistic to imagine ship designs where linear generators are thought to provide a ship's necessary propulsion power but, on the other hand, they may serve to supplement the main engine for auxiliary power generation.
The International Maritime Organization employs technical and operational indicators to assess ship energy efficiency. Weather conditions significantly impact ship fuel consumption during voyages, necessitating the consideration of this influence in energy efficiency calculations. This study aims to design models for estimating the impact of weather components on fuel consumption and develop correction factors to cope with the weather effect on the fuel consumption of container ships for different sea states. Using model-based machine learning, the study analyzes noon reports and hindcasted weather data from two sister container ships. It quantifies weather-induced fuel consumption across various sea states, ranging from 2% to 20%, with an average of 7%–13% depending on the model used. Correction factors specific to each sea state are derived, and different approaches for their integration into energy efficiency indicators are proposed. This study advocates tailored weather correction factors for energy efficiency metrics tied to specific sea states, emphasizing the need for standardized weather impact assessments. Prior to any formal policy application, future work is needed to address the limitations of the present study and extend this approach to various ship types and sizes and different geographical regions.
Maritime transportation is an essential pillar of modern societies, serving as the backbone of global trade. The shipping industry relies heavily on fossil fuels, significantly impacting the environment and contributing to climate change. The International Maritime Organization (IMO) has introduced a strategy to reduce greenhouse gas emissions from international shipping and decarbonize the industry to combat this issue. This strategy aims to accomplish energy efficiency gains, transition to alternative fuels, and implement market-based measures.
Various energy efficiency indicators are in use to monitor the performance of ships, both from technical and operational perspectives. Building upon previous research that identified shortcomings in these indicators, this thesis investigates alternative methods of assessing the energy efficiency of ships. Emphasizing the importance of a benchmarking tool, the primary objective of this thesis is to contribute to the policy debate on reducing emissions in international shipping by developing a comprehensive carbon intensity indicator.
The thesis comprises four articles addressing various approaches to monitoring ship carbon emissions. The first article focuses on the influence of weather conditions on a ship’s energy efficiency, thereby contributing to the ongoing discussion on weather correction factors. Using model-based machine learning techniques, this article illustrates the diverse sea conditions encountered, their impact on energy efficiency, and the necessity of accounting for this diversity through multiple correction factors.
The second and third articles introduce and develop the concept of operational cycles for maritime transportation, drawing inspiration from the driving cycles employed in the automotive industry. The second article describes the process of generating operational cycles for the maritime sector as a novel concept. It validates this concept using real-world data obtained from a fleet of container ships. Building upon this foundation, the third article extends the concept by elaborating more comprehensive cycles that better represent real-world indicators.
The fourth article explores voluntary reporting frameworks in the shipping industry. It focuses on the Clean Cargo case and investigates the needs and interests of its members regarding this private initiative and related reporting framework. The discussion revolves around the role of these voluntary frameworks as complementary approaches to regulatory frameworks towards maritime decarbonization.
Based on the methodology developments and analysis through the thesis, the following key findings and recommendations are presented:
• The weather impact on ships’ fuel consumption prevents an accurate and real assessment of ships’ efficiency. Multiple weather correction factors for energy efficiency indicators introduce a novel approach.
• Inspired by the automotive industry, maritime operational cycles improve the assessment of technical and operational aspects of a ship’s energy efficiency. The cycles reduce the variability inherent to energy
efficiency indicators and are suitable as benchmarking tools.
• Although the IMO regulatory framework remains at the core of the maritime decarbonization strategy, regional regulatory frameworks and private initiatives have demonstrated their capacity to enhance industry
practices and facilitate regulatory developments.
This thesis contributes to enhancing carbon emissions monitoring in the maritime industry by introducing new methodologies and assessments. The resulting proposals are designed to enrich ongoing discussions within the IMO and complement the existing regulatory frameworks.
Existing energy management strategies (EMSs) for hybrid power systems (HPSs) in hydrogen fuel cell vessels (FCVs) are not applicable to scenarios with multiple hydrogen fuel cells (FCs) and lithium batteries (LBs) in parallel, and are difficult to achieve real-time control and optimization for multiple objectives. In this paper, a bi-layer real-time energy management strategy (BLRT-EMS) is proposed. Compared with existing EMSs, the proposed BLRT-EMS implements different control/optimization objectives distributed in the execution layer EMS (EL-EMS) and the decision layer EMS (DL-EMS), which can significantly reduce bus voltage fluctuations, decrease hydrogen consumptions, improve the system efficiency, and have potential for engineering applications. In the first EL-EMS, a decentralized optimal power allocation strategy is proposed, which allows each FC system to allocate the output power ratio according to their generation costs, ensuring consistent performance of multiple FC systems (MFCS) under long-term operating conditions, and thus delaying the degradation rate of FCs. In the second EL-EMS, a distributed cooperative control strategy is proposed to achieve dynamic SoC equalization, proportional output power allocation, and accurate bus voltage restoration among multiple battery storage systems (MBSS) to extend the service life of batteries. In the DL-EMS, an energy coordination optimization strategy between MFCS and MBSS is proposed to achieve hydrogen consumption reduction and system efficiency improvement, thus enhancing the endurance performance of FCV. Finally, test results based on the StarSim experimental platform show that the proposed BLRT-EMS has faster SoC convergence speed, smaller bus voltage deviation, lower hydrogen consumption, higher system efficiency, and lower operation stress than the state-of-the-art methods.
Benchmarking the energy efficiency of ships is not a straightforward task, mainly due to the diversity of operations. Although driving cycles have been used for decades in evaluating the performance of road vehicles, these do not exist in formal policy-making for maritime transport. This work builds on a previously proposed methodology. It uses noon reports of 327 vessels for 2019 to construct operational cycles for seven size classes of container ships using the main engine power as the main parameter. Concerning the main engine emissions, the resulting cycles reduce variation in the carbon intensity indicator values by more than 30% while maintaining an average accuracy of 97.7% in absolute emissions. These figures show that the concept can improve operational carbon intensity indicators in terms of robustness and their technical counterparts in optimizing ship design. The paper also proposes further work required for benchmarking applications in policy-making.
There have been a number of recent papers in the literature that investigate the relationship between ship speed and required power, or between ship speed and fuel consumption. Using regression analyses for selected case studies these papers show that in many cases the traditional “cube law” is not valid, and exponents lower than 3 (and in some cases lower than 2 or even below 1) are more appropriate. Perhaps more important, they use these results to derive implications on the validity (or lack thereof) of policies to reduce greenhouse gas (GHG) emissions from ships through slow steaming. This paper reviews some of these papers and shows that their results are partially based on pitfalls in the analysis which are identified. Policy implications particularly on the quest to reduce GHG emissions from ships are also discussed.
The purpose of this paper is to revisit speed optimization and speed reduction models for liner shipping in a multi/flexible fuel context with regards to the current ongoing speed limit debate at the International Maritime Organization (IMO). The focus is mainly on analyzing the influence of a maximum average speed limit on the optimal speeds, carbon intensity and emissions in conjunction with fleet deployment for dual fuel (DF) Neopanamax container vessels utilizing liquefied natural gas (LNG).
To mitigate climate change due to international shipping, the International Maritime Organization (IMO) requires shipowners and ship technical managers to improve the energy efficiency of ships’ operations. This paper studies how voyage planning and execution decisions affect energy efficiency and distinguishes between the commercial and nautical components of energy efficiency. Commercial decisions for voyage planning depend on dynamic market conditions and matter more for energy efficiency than nautical decisions do for voyage execution. The paper identifies the people involved in decision-making processes and advances the energy-efficiency literature by revealing the highly networked nature of agency for energy efficiency. The IMO’s current energy efficiency regulations fail to distinguish between the commercial and nautical aspects of energy efficiency, which limits the ability to mitigate climate change through regulatory measures. Policymakers should expand their regulatory focus beyond shipowners and technical managers to cargo owners to improve energy efficiency and reduce maritime transport emissions.