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.
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.
Implementation of alternative energy supply solutions requires the broad involvement of local communities. Hence, smart energy solutions are primarily investigated on a local scale, resulting in integrated community energy systems (ICESs). Within this framework, the distributed generation can be optimally utilised, matching it with the local load via storage and demand response techniques. In this study, the boat demand flexibility in the Ballen marina on Samsø—a medium-sized Danish island—is analysed for improving the local grid operation. For this purpose, suitable electricity tariffs for the marina and sailors are developed based on the conducted demand analysis. The optimal scheduling of boats and battery energy storage system (BESS) is proposed, utilising mixed-integer linear programming. The marina’s grid-flexible operation is studied for three representative weeks—peak tourist season, late summer, and late autumn period—with the combinations of high/low load and photovoltaic (PV) generation. Several benefits of boat demand response have been identified, including cost savings for both the marina and sailors, along with a substantial increase in load factor. Furthermore, the proposed algorithm increases battery utilisation during summer, improving the marina’s cost efficiency. The cooperation of boat flexibility and BESS leads to improved grid operation of the marina, with profits for both involved parties. In the future, the marina’s demand flexibility could become an essential element of the local energy system, considering the possible increase in renewable generation capacity—in the form of PV units, wind turbines or wave energy
Integrated community energy systems are an emerging concept for increasing the self-sufficiency and efficiency of local multi-energy systems. This idea can be conceptualized for the smart island energy systems due to their geographical and socioeconomic context, providing several benefits through this transformation. In this study, the energy system of the Ballen marina—located on the medium-sized Danish island of Samsø— is investigated. Particular consideration is given to the integration of PV, BESS, and—in the future—flexible loads. For this purpose, the BESS is modelled, incorporating the battery degradation process. The possibilities to improve energy utilization and maximize self-consumption from the marina's PV units are identified and evaluated, demonstrating a substantial enhancement of the local system operation.
The design of wave energy converters should rely on numerical models that are able to estimate accurately the dynamics and loads in extreme wave conditions. A high-fidelity CFD model of a 1:30 scale point-absorber is developed and validated on experimental data. This work constitutes beyond the state-of-the-art validation study as the system is subjected to 50-year return period waves. Additionally, a new methodology that addresses the well-known challenge in CFD codes of mesh deformation is successfully applied and validated. The CFD model is evaluated in different conditions: wave-only, free decay, and wave–structure interaction. The results show that the extreme waves and the experimental setup of the wave energy converter are simulated within an accuracy of 2%. The developed high-fidelity model is able to capture the motion of the system and the force in the mooring line under extreme waves with satisfactory accuracy. The deviation between the numerical and corresponding experimental RAOs is lower than 7% for waves with smaller steepness. In higher waves, the deviation increases up to 10% due to the inevitable wave reflections and complex dynamics. The pitch motion presents a larger deviation, however, the pitch is of secondary importance for a point-absorber wave energy converter.
The International Energy Agency Technology Collaboration Program for Ocean Energy Systems (OES) initiated the OES Wave Energy Conversion Modeling Task, which focused on the verification and validation of numerical models for simulating wave energy converters (WECs). The long-term goal is to assess the accuracy of and establish confidence in the use of numerical models used in design as well as power performance assessment of WECs. To establish this confidence, the authors used different existing computational modeling tools to simulate given tasks to identify uncertainties related to simulation methodologies: (i) linear potential flow methods; (ii) weakly nonlinear Froude–Krylov methods; and (iii) fully nonlinear methods (fully nonlinear potential flow and Navier–Stokes models). This article summarizes the code-to-code task and code-to-experiment task that have been performed so far in this project, with a focus on investigating the impact of different levels of nonlinearities in the numerical models. Two different WECs were studied and simulated. The first was a heaving semi-submerged sphere, where free-decay tests and both regular and irregular wave cases were investigated in a code-to-code comparison. The second case was a heaving float corresponding to a physical model tested in a wave tank. We considered radiation, diffraction, and regular wave cases and compared quantities, such as the WEC motion, power output and hydrodynamic loading.
Under complex sea conditions, the energy demand for each device of renewable-energy ships presents a random situation, which makes the complex energy demand of the ship integrated energy system (SIES) uncertain during ship navigation. To ensure the economical, stable, and efficient operation of the SIES, this paper proposes a distributed stochastic energy management method to solve the energy management problem (EMP). Firstly, a framework for the SIES including both renewable energy and traditional energy is constructed. Based on the energy efficiency operation index (EEOI) and the operation mode of energy supply devices during navigation, the EMP of the SIES is raised. Then, considering the distributed structure and limited computing resources of the SIES, a distributed stochastic energy management method is proposed. Through this method, the disturbances of load demand can be effectively suppressed, and a stable energy supply is provided for devices such as power propellers. Furthermore, it is analyzed that the proposed method can converge to the O(η) (η is the fixed step size of the proposed method) neighborhood of the optimal energy management decision in the mean-square-error sense. Finally, the simulation results verify that the mean-square-error-optimal energy management decision of the SIES can be obtained by the proposed method in different scenarios, and the proposed method can solve the EMP of SIES under complex sea conditions.
The energy system needs a range of forecast types for its operation in addition to the narrow wind power forecast that has been the focus of considerable recent attention. Therefore, the group behind the former IEA Wind Task 36 Forecasting for Wind Energy has initiated a new IEA Wind Task with a much broader perspective, which includes prospective interaction with other IEA Technology Collaboration Programmes such as the ones for PV, hydropower, system integration, hydrogen etc. In the new IEA Wind Task 51 (entitled "Foreacsting for the Weather Drive Energy System") the existing Work Packages (WPs) are complemented by work streams in a matrix structure. The Task is divided in three WPs according to the stakeholders: WP1 is mainly aimed at meteorologists, providing the weather forecast basis for the power forecasts. In WP2, the forecast service vendors are the main stakeholders, while the end users populate WP3. The new Task 51 started in January 2022. Planned activities include 4 workshops. The first will focus on the state of the art in forecasting for the energy system plus related research issues and be held during September 2022 in Dublin. The other three workshops will be held later during the 4-year Task period and address (1) seasonal forecasting with emphasis on Dunkelflaute, storage and hydro, (2) minute-scale forecasting, and (3) extreme power system events. The issues and conclusions of each of the workshops will be documented by a published paper. Additionally, the Recommended Practice on Forecast Solution Selection will be updated to reflect the broader perspective.
In 2017, Energinet and TenneT, the Danish and Dutch Transmission System Operators (TSOs), have announced the North Sea Wind Power Hub (NSWPH) project. The project aims at increasing by 36 GW the North Sea offshore wind capacity, with an artificial island collecting all the power produced by wind turbines and several HVDC links transmitting this power to the onshore grids. This project brings together new opportunities and new challenges, both from a technical and economic point of view. In this regard, this paper presents three analyses regarding the design and operation of such an offshore system. First, we perform a techno-economic assessment of different grid configurations for the collection of the power produced by wind farms and its transmission to the hub. In this analysis, two frequencies and two voltage levels for the operation of the offshore grid are investigated. Our findings show that the nominal-frequency high-voltage option is the more suitable, as lowfrequency does not bring any advantage and low-voltage would results in higher costs. The second analysis is related to the differences in operating the system with low- or zero-inertia; different dynamic studies are performed for each configuration to identify proper control actions and their stability properties. Comparing the outcomes of the simulations, we observed that voltage and frequency oscillations are better damped in the zero-inertia system; however, the risk of propagating offshore faults in the connected onshore grids is mitigated with the inclusion of the synchronous condensers. Lastly, a comparison of ElectroMagnetic Transient (EMT) and phasor-mode (also known as RMS) models is presented, in order to understand their appropriateness of simulating low- and zeroinertia systems. The results show that phasor approximation modelling can be used, as long as eigen-frequencies in power network are well damped.
This study proposes a novel tower damping system to enhance the structural performance of the NREL 5 MW semi-submersible wind turbine under operational and extreme load conditions. Environmental load data from the Norwegian MET center was analyzed to characterize the loading conditions for floating offshore wind turbines (FOWT). The probability density spectrum of sea state data was employed to identify operational load conditions. At the same time, the Inverse First-Order Reliability Method (IFORM) was used to derive the 50-year extreme sea state. Perform a fully coupled Aero-Hydro-Servo-Elastic simulation of the FOWT dynamic model with a damping system using OrcaFlex software. The results reveal that: Under operational sea states, the turbine tower-top displacement was reduced by 60–70%, and acceleration by 30–40%, enhancing tower-top stability. Under extreme loads, tower-top acceleration was reduced by 5–7%, and displacement by 6–8%. Cumulative damage assessments indicate a reduction in fatigue damage of up to 72%, with the effective fatigue life of the tower base extended by 136%. The proposed damping system significantly reduces vibration under fatigue and extreme load conditions.