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.
A new proposed framework to assess sustainability impacts of maritime spatial plans (MSP-SA) utilizes the ecosystem service (ES) concept to address the often-lacking social sustainability of the plans. This study departs from the MSP-SA framework and applies it to the (emerging) sea use of mussel farming. Informed by a literature review and two surveys, it is investigated whether the benefits and impacts of mussel farming can be related to underlying ES and relevant planning questions. The results show that most benefits and impacts of mussel farming can be connected to ES and reveal different user-environment-beneficiary interactions, ranging from conflicts to synergies. The marine planning framework is structured into different planning phases and it is shown that the ES concept can contribute to a normative vision, strategic objectives, and site-specific operational questions. Studying the different user-environment-beneficiary interactions can reveal who benefits and who loses from planning decisions. While the marine planning framework developed in this study is targeted at mussel farming, the approach can be adapted to other uses and planning areas and can contribute to social and equity aspects in MSP by considering the receivers of (dis)benefits.
In order to enhance sustainability in maritime shipping, shipping companies spend good efforts in improving the operational energy efficiency of existing ships. Accurate fuel consumption prediction model is a prerequisite of such operational improvements. Existing grey-box models (GBMs) are found with significant performance potential for ship fuel consumption prediction, although having a limitation of separating weather directions. Aiming to overcome this limitation, we propose a novel genetic algorithm-based GBM (GA-based GBM), where ship fuel consumption is modelled in a procedure based on basic principles of ship propulsion and the unknown parameters in this model are estimated with a GA-based procedure. Real ship operation data from a crude oil tanker over a 7-year sailing period are used to demonstrate the accuracy and reliability of the proposed model. To highlight the contribution of this work, we compare the proposed model against the latest GBM. The results show that the fitting performance of the proposed model is remarkably better, especially for oblique weather directions. The proposed model can be employed as a basis of ship energy efficiency management programs to reduce fuel consumption and greenhouse gas (GHG) emissions of a ship. This is beneficial to achieve the goal of sustainable shipping.
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.
This paper describes a new high-order composite numerical model for simulating moored floating offshore bodies. We focus on a floating offshore wind turbine and its static equilibrium and free decay. The composite scheme models linear to weakly nonlinear motions in the time domain by solving the Cummins equations. Mooring forces are acquired from a discontinuous Galerkin finite element solver. Linear hydrodynamic coefficients are computed by solving a pseudo-impulsive radiation problem in three dimensions using a spectral element method. Numerical simulations of a moored model-scale floating offshore wind turbine were performed and compared with experimental measurements for validation, ultimately showing a fair agreement.
Linear potential flow (LPF) models remain the tools-of-the-trade in marine and ocean engineering despite their well-known assumptions of small amplitude waves and motions. As of now, nonlinear simulation tools are still too computationally demanding to be used in the entire design loop, especially when it comes to the evaluation of numerous irregular sea states. In this paper we aim to enhance the performance of the LPF models by introducing a hybrid LPF-ML (machine learning) approach, based on identification of nonlinear force corrections. The corrections are defined as the difference in hydrodynamic force (viscous and pressure-based) between high-fidelity CFD and LPF models. Using prescribed chirp motions with different amplitudes, we train a long short-term memory (LSTM) network to predict the corrections. The LSTM network is then linked to the MoodyMarine LPF model to provide the nonlinear correction force at every time-step, based on the dynamic state of the body and the corresponding forces from the LPF model. The method is illustrated for the case of a heaving sphere in decay, regular and irregular waves – including passive control. The hybrid LPF model is shown to give significant improvements compared to the baseline LPF model, even though the training is quite generic.
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.
This paper studies the Quay Crane Scheduling Problem (QCSP). The QCSP determines how a number of quay cranes should be scheduled in order to service a vessel with minimum makespan. Previous work considers the QCSP to be a combinatorially hard problem. For that reason, the focus has been on developing efficient heuristics. Our study shows, however, that the QCSP is tractable in the realistic setting, where quay cranes can share the workload of bays. We introduce a novel linear time algorithm that solves the QCSP and prove its correctness.
This paper aims to conduct an updated literature survey on the Market-Based Measures (MBMs) currently being proposed by various member states and organizations at the International Maritime Organization (IMO) or by the scientific and grey literature as a cost-effective solution to reduce greenhouse gas (GHG) emissions from ships. Τhe paper collects, summarizes, and categorizes the different proposals to provide a clear understanding of the existing discussions on the field and also identifies the areas of prior investigation in order to prevent duplication and to avoid the future discussion at the IMO to start from scratch. Relevant European Union (EU) action on MBMs is also described. Furthermore, the study identifies inconsistencies, gaps in research, conflicting studies, or unanswered questions that form challenges for the implementation of any environmental policy at a global level for shipping. Finally, by providing foundational knowledge on the topic of MBMs for shipping and by exploring inadequately investigated areas, the study addresses concrete research questions that can be investigated and resolved by the scientific and shipping community
This paper aims to conduct an updated literature survey on the Market-Based Measures (MBMs) currently being proposed by various member states and organizations at the International Maritime Organization (IMO) or by the scientific and grey literature as a cost-effective solution to reduce greenhouse gas (GHG) emissions from ships. The paper collects, summarizes, and categorizes the different proposals to provide a clear understanding of the existing discussions on the field and also identifies the areas of prior investigation in order to prevent duplication and to avoid the future discussion at the IMO to start from scratch. Relevant European Union (EU) action on MBMs is also described. Furthermore, the study identifies inconsistencies, gaps in research, conflicting studies, or unanswered questions that form challenges for the implementation of any environmental policy at a global level for shipping. Finally, by providing foundational knowledge on the topic of MBMs for shipping and by exploring inadequately investigated areas, the study addresses concrete research questions that can be investigated and resolved by the scientific and shipping community.