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.
This paper examines the stability of a weak island namely Sumbawa-Lombok of Indonesian grid, interconnected with two infeed HVDC links facilitating 2 x 120 MW power transfer from Sumba and Flores Island. Through power flow, short circuit, small signal stability, resonance stability, and transient stability analyses, it is demonstrated that the existing infrastructure fails to support such transfer due to voltage drops, overloading, and stability limitations. Upgrading to 150 kV and its subsequent component resolves the small-signal and transient stability constraint as its grid strength is increasing. The current findings underscore that the primary limitation lies in the grid's infrastructure, not in dynamic or control constraints. The current result establishes the need for strategic grid reinforcements to support HVDC integration in weak systems and sets the stage for future research on optimizing the extent of such reinforcements.
This paper proposes an economic and resilient operation architecture for a coupled hydrogen-electricity energy system operating at port. The architecture is a multi-objective optimization problem, which includes the energy system optimal economy as the goal orientation and the optimal resilience as the goal orientation. The optimal resilience orientation looks for the best resilience performance of the port through reasonable energy management including (1) reducing the amount of electricity purchased by the port power grid from the external power grid (2) improving the energy level of electric energy storage (3) improving the energy level of hydrogen energy storage. Taking the actual coupled hydrogen-electricity energy system of Ningbo-Zhoushan Port as an example, four typical scenarios were selected according to renewable generation and load characteristics, and a comparative analysis was carried out during the oriented operation. The results show that although the resilience orientation increases the operating cost compared with the economic orientation, the four scenarios reduce the load shedding by 44.84%, 30.26%, 48.49% and 34.37% respectively when the external power grid is disconnected. The impact of changes in resilience-oriented weight coefficients and hydrogen price on system resilience performance was investigated to provide more references for decision makers.
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.
The importance of reliable battery energy storage systems (BESS) is key to the sustainability of many applications such as renewable power, smart grids, and electric vehicles (EVs). Due to decreasing cost and maturing technology, the Li-ion batteries are now widely used for grid-level storage, grid support for improved power quality, integration with photovoltaic systems, and EV applications. A Li-ion battery pack typically comprises Li-ion cells connected in a suitable combination of series and parallel structure. A battery management system (BMS) is required for charging and discharging, monitoring the current and voltage of each cell or string, battery protection, and temperature control. The system's reliability depends on the BESS reliability and is affected by many factors, including temperature, C-rate, DOD. This research aims to improve BESS reliability by using accurate lifetime modelling for various BMS and converter topologies to identify real-time BESS health and ensure reliability through a suitable control strategy. In particular, the reliability of the BESS for centralized, modularised, distributed, and decentralized topology will be explored along with its cost-reliability trade-off. I will focus on control strategies for optimizing BESS reliability for different applications.
Hydrogen energy is a promising solution for prompting low-carbon port development. This study introduces two hydrogen utilization strategies: hydrogen consumption-driven strategy (HCDS) and hydrogen storage-driven strategy (HSDS). Using data from a real port and a life-cycle assessment approach, a case study is conducted to compare their economic and ecological performances. The results show that HCDS enhances economic benefits, with an annualized cost of 66.1 million CNY, which is 11% lower than HSDS. Additionally, HCDS is sensitive to electricity prices and grid carbon emission factor. In contrast, HSDS offers superior ecological benefits, with an annualized carbon footprint of 31,300 tons of CO₂, which is 12% lower than HCDS, and is mainly sensitive to purchase prices and emission factors of electricity and hydrogen. This study provides critical insights into the trade-offs between economic and ecological performance under different hydrogen utilization strategies, offering practical guidance for implementing hydrogen energy system applications in ports.
Offshore wind power offers a viable solution to the challenge of reducing fossil fuel dependency. However, certain offshore wind projects encounter challenges in meeting expected returns, particularly over the medium to long term. This study addresses the discrepancy between assumed and actual cost behaviors in techno-economic assessments of wind farm projects. The present study evaluates their impact of operational loss trends (eg increased failure rates, aging, potential curtailment) on project viability through a comprehensive techno-economic assessment. To this end, key metrics including Net Present Value and Levelized Cost of Energy, complemented by stochastic analyzes are explored through Monte Carlo Simulation and sensitivity analysis. Results indicate that costs may exceed those of the reference scenario by up to 21.6% in the worst-case scenario, highlighting the critical need for proactive monitoring and management of operational losses.
As more offshore wind energy projects are implemented, the risk of interactions between farms becomes more pronounced. While reduced surface roughness over water enhances airflow stability, it can also extend wake effects on downstream turbines. The study aims to enhance the understanding of wake interactions and efficiency variations based on the distance between neighboring farms. To assess the impact of neighboring farms across different scenarios and features, a methodology is developed to achieve computational optimality using an open-source Python-based library, PyWake, then verified by a well-established CFD software, Meteodyn. Then, the methodology is applied to a Brazilian offshore wind project currently under licensing as a reference point. The results indicate a 1–3% reduction in Annual Energy Production following the current Brazilian regulation for onshore projects of 20 times the blade tip height, as the minimum distance. This reduction translates to an approximate 3% increase in the Levelized Cost of Energy and a nearly 24% decrease in Net Present Value. These findings are crucial for offshore wind energy planning and its sustainable growth, indicating the need to define a minimum distance for the regulatory bodies. This would not only avoid future disputes but also enhance investor confidence.
In the current transition of power industry from conventional sources to renewable energy sources, wind power generation is becoming one of the key sources of electrical energy. Although the development of wind power plants (WPPs) has made a significant contribution to addressing the demand for clean and cheap energy, the integration of large-scale WPPs introduces a series of technical challenges to power system operations. These challenges involved control, protection, and adherence to specified power quality standards. Particularly, power quality plays a vital role in utility systems and industries having direct technical and economic impact on both power consumers and suppliers. To tackle such issues, various grid codes have been initiated by regulation authorities. Moreover, different ancillary devices and control approaches have been adopted to comply with the established grid code. This article aims to review the state-of-the-art research and progress, while considering the main challenges related to dynamic performance and power quality enhancement of emerging grid-forming wind power plants. Various topologies of wind energy conversion systems (WECSs) are examined and compared, and their control strategies are investigated. A comprehensive review on power quality and dynamic response issues caused by large-scale wind power integration is presented. Moreover, the evolving grid code requirements for grid-connected WPPs in most leading countries including Denmark, U.K., Australia, Germany, and the USA are analyzed and compared. Furthermore, the improvement approaches proposed in the literature are investigated and classified on different basis and their pros and cons are discussed. A brief discussion on the solutions and future directions is presented. Finally, some conclusive considerations about the overall study are provided.
This paper proposes a multi-time scale scheduling strategy for a practical port coupled hydrogen-electricity energy system (CHEES) to optimize the integration of renewable energy and manage the stochasticity of port power demand. An optimization framework based on day-ahead, intra-day and real-time scheduling is designed. The framework allows coordinating adjustable resources with different rates to reduce the impact of forecast errors and system disturbances, thus improving the flexibility and reliability of the system. The effectiveness of the proposed strategy is verified by a case study of the actual CHEES in the Ningbo Zhoushan Port, and the impact of equipment anomalies on the port power system operation is studied through simulation of different scenarios. The results show that compared with a scheduling scheme without energy management strategy, CHEES with multi-time scale scheduling can save 25.42% of costs and reduce 14.78% of CO 2 emissions. A sensitivity analysis is performed to highlight the impact of hydrogen price and soft open points (SOP) rated power on the system economy. This study not only provides a new perspective for the optimal scheduling of port energy systems, but also provides a practical framework for managing port energy systems to achieve green transformation and sustainable development.