The abatement of greenhouse gas emissions represents a major global challenge and an important topic for transportation research. Several studies have argued that energy efficiency measures for virtual arrival and associated reduced anchorage time can significantly reduce emissions from ships by allowing for speed reduction on passage. However, virtual arrival is uncommon in shipping. In this paper, we examine the causes for waiting time for ships at anchor and the limited uptake of virtual arrival. We show the difficulties associated with the implementation of virtual arrival and explain why shipping is unlikely to achieve the related abatement potential as assumed by previous studies. Combining onboard observations with seafarers and interviews with both sea-staff and shore-based operational personnel we show how charterers’ commercial priorities outweigh the fuel saving benefits associated with virtual arrival. Moreover, we demonstrate how virtual arrival systems have unintended, negative consequences for seafarers in the form of fatigue. Our findings have implications for the IMO’s greenhouse gas abatement goals.
The utilization of green energy resources for supplying energy to ships in the marine industry has received increasing attention during the last years, where different green resource combinations and control strategies have been used. This article considers a ferry ship supplied by fuel cells (FCs) and batteries as the main sources of ship's power. Based on the designers' and owners' preferences, different scenarios can be considered for managing the operation of the FCs and batteries in all-electric marine power systems. In this article, while considering different constraints of the system, six operating scenarios for the set of FCs and batteries are proposed. Impacts of each proposed scenario on the optimal daily scheduling of FCs and batteries and operation costs of the ship are calculated using a mixed-integer nonlinear programming model. Model predictive control (MPC) is also applied to consider the deviations from hourly forecast demand. Moreover, since the efficiency of FCs varies for different output powers, the impacts of applying a linear model for FCs' efficiency are compared with the proposed nonlinear model and its related deviations from the optimal operation of the ship are investigated. The proposed model is solved by GAMS software using actual system data and the simulation results are discussed. Finally, detailed real-time hardware-in-the-loop (HiL) simulation outcomes and comparative analysis are presented to confirm the adaptation capability of the proposed strategy.
Maritime transport is the most energy-effective mode to move large amounts of goods around the world. Hauling cargo via waterway produces an enormous quantity of greenhouse gas emissions. Vessel fuel efficiency directly influences ship emissions by affecting the amount of burnt fuel. Optimizing ships operating in waves rather than in calm water conditions could decrease the fuel consumption of vessels. In particular, ship propellers are traditionally designed neglecting dynamic conditions such as time-varying wake distribution and propulsion factors, propeller speed fluctuations, ship motions, and speed loss. The effect of waves on the propeller performance can be evaluated using both a quasi-steady and a fully-unsteady approach. The former is a fast computational approximation method based on the assumption that the ratio of propeller angular frequency to wave encounter frequency is sufficiently large. The latter provides a complete representation of the propeller dynamics, but it is computationally expensive. The purpose of this paper is to compare the propeller performance in the presence of waves using the quasi-steady and the fully unsteady approach. This analysis is performed by observing the differences in unsteady propeller forces, cavitation volume, and hull pressure pulses between the two approaches. The full-scale KVLCC2 propeller is utilized for the investigation. Results show a good agreement between the quasi-steady and the fully-unsteady approach in the prediction of the temporal mean and the fluctuation amplitude of KT and KQ, the cavity volume variation, and the hull pressure pulses. Therefore, for the considered operating conditions, the quasi-steady approach can be used to compute the propeller performance in waves.
The climate emergency has prompted rapid and intensive research into sustainable, reliable, and affordable energy alternatives. Offshore wind has developed and exceeded all expectations over the last 2 decades and is now a central pillar of the UK and other international strategies to decarbonise energy systems. As the dependence on variable renewable energy resources increases, so does the importance of the necessity to develop energy storage and nonelectric energy vectors to ensure a resilient whole-energy system, also enabling difficult-to-decarbonise applications, e.g. heavy industry, heat, and certain areas of transport. Offshore wind and marine renewables have enormous potential that can never be completely utilised by the electricity system, and so green hydrogen has become a topic of increasing interest. Although numerous offshore and marine technologies are possible, the most appropriate combinations of power generation, materials and supporting structures, electrolysers, and support infrastructure and equipment depend on a wide range of factors, including the potential to maximise the use of local resources. This paper presents a critical review of contemporary offshore engineering tools and methodologies developed over many years for upstream oil and gas (O&G), maritime, and more recently offshore wind and renewable energy applications and examines how these along with recent developments in modelling and digitalisation might provide a platform to optimise green hydrogen offshore infrastructure. The key drivers and characteristics of future offshore green hydrogen systems are considered, and a SWOT (strength, weakness, opportunity, and threat) analysis is provided to aid the discussion of the challenges and opportunities for the offshore green hydrogen production sector.
The approach documented in this paper employs system identification (SI), or data-based modelling, techniques as an alternative to model determination from first principles for modelling a vented oscillating water column wave energy converter, using real wave tank data gathered at Danmarks Tekniske Universitet. In SI, the parameters of the model are obtained from the experimental input/output data by minimizing a cost function, related to model fidelity. The main advantage of SI is its simplicity, as well as its potential validity range, where the dynamic model is valid over the full range for which the identification data was recorded. Furthermore, SI models are somewhat flexible, since they can be solely based on data (black-box models), or else can incorporate some physics-based information (grey-box models). However, a suitable excitation signal is of primary importance for the parametric model to be representative over a wide range of operating conditions.
Seaports consume a large amount of energy and emit greenhouse gas and pollutants. Integrated multiple renewable energy systems constitute a promising approach to reduce the carbon footprint in seaports. However, the intermittent nature of renewable resources, stochastic dynamics of the demand in seaports, and unbalanced structure of seaport energy systems require a proper design of energy storage systems. In this paper, a framework for multi-objective optimization of hybrid energy storage systems in stochastic unbalanced integrated multi-energy systems at sustainable mega seaports is proposed to minimize life-cycle costs and minimize carbon emissions. The optimization problem is formulated with reference to the energy management of the integrated multi-energy system at the seaport and considering both distributed and centralized hybrid energy storage configurations. Wavelet decomposition and double-layer particle swarm optimization are proposed to solve the multi-objective optimization problem. The real power system of the largest port worldwide, i.e., the Ningbo Zhoushan Port, was selected as a case study. The results show that, with respect to a situation with no energy storage system, the proposed approach can save 81.29 million RMB in electricity purchases and eliminate approximately 497,186 tons of carbon emissions over the entire lifecycle of the energy storage system. The findings suggest that the proposed hybrid energy storage framework holds the potential to yield substantial economic and environmental advantages within mega seaports. This framework offers a viable solution for port authorities seeking to implement hybrid energy storage systems aimed at fostering greater sustainability within port operations.
Decentralization of the electricity sector has mainly been studied in relation to its infrastructural aspect, particularly location and size of the generation units, and only recently more attention has been paid to the governance aspects. This article examines power sector (de)centralization operationalized along three functional dimensions: political, administrative and economic. We apply this framework to empirically assess the changes in California’s electricity market, which saw the emergence of institutional innovation in the form of community choice aggregation (CCA). Unpacking the Californian case illustrates how decision-making has moved from central state government and regulators to the municipal level in uneven ways and without decentralized generation keeping pace. We also explore the impacts this multidimensional and diversified decentralization has on the ultimate goals of energy transition: decarbonization and energy security. Our framework and empirical findings challenge the conventional view on decentralization and problematize the widespread assumptions of its positive influence on climate mitigation and grid stability.
Hydrogen-electricity integrated multi-energy systems are promising approaches to reduce carbon emissions in ports. However, the stochastic nature of renewable energy and the imbalance between the renewable generation and load demand in ports necessitate the design of an appropriate coupled hydrogen-electricity energy storage systems (CHEESS). This paper proposes a multi-objective optimization model for CHEESS configuration in random unbalanced port integrated multi-energy systems (PIMES), aiming to minimize its life-cycle cost and carbon emissions through co-optimization of sizing and energy management. A hierarchical two-stage framework is proposed to solve the multi-objective model. The proposed optimization framework is applied to a real PIMES at the Ningbo-Zhoushan Port. The results show that the proposed method can save 10.54% of the monetary cost and 19.67% of carbon emissions over the entire life-cycle of the system. The study demonstrates that the proposed framework has the potential to generate significant economic and environmental benefits and provides a feasible solution for port authorities seeking to implement CHEESS, aiming to promote sustainability in port operations.
Port Integrated Multi-Energy Systems (PIMES) play a critical role in advancing sustain-ability at ports. Assessing the dynamic contribution of PIMES to port sustainability is essential for guiding future developments. This research introduces an innovative multi-criteria dynamic sustainability assessment framework tailored to evaluate the performance of PIMES. The framework employs a diverse set of indicators covering multiple criteria to comprehensively assess different aspects of PIMES. A game theory-based combined weighting approach is uniquely applied to integrate subjective and objective evaluations, ensuring a balanced and robust assessment. Furthermore, the cloud model is utilized for an in-depth evaluation of the overall sustainability of PIMES, offering a novel perspective on managing uncertainty. The framework's applicability and effectiveness are demonstrated through a case study of the Ningbo-Zhoushan Port, with a sensitivity analysis of the indicators conducted to enhance reliability and confirm the robustness of the proposed method. The evaluation results indicate that during the development of the PIMES, the sustainability performance of the studied port improves progressively, with ratings of “average”, “poor”, “average”, “average”, “good”, and “excellent”. The sensitivity analysis shows that the sustainability of ports is most influenced by the failure loss rate and operation & maintenance cost of PIMES. This framework can serve as a decision-making tool for port authorities to enhance energy efficiency, reduce emissions, and achieve long-term sustainability objectives at ports.
Even though that there has been increasing focus on the energy-efficient operation of vessels and that the knowledge of cost-effective improvements is widespread in the industry, energy-efficient operation is only a minor topic on board many working vessels. A significant reduction in fuel can be achieved through changes in the operational practices, but to establish a successful system for best practices within energy-management the installation of a decision support system is essential. This article presents a decision support system for working vessels to determine best practice for the reduction of fuel consumption. Requirements for the system are defined through interviews with crew and observations on board vessels. Case studies are used for illustrating the usefulness. The use of generators onboard is analyzed using the software. It is found that the generators are not running optimally, but the crew can use the software to re-organize and find the most fuel-efficient loading range for the generators on board.