Search Results (42)

To facilitate both the installation and the removal of floating offshore wind turbines (FOWTs), a novel tension-leg dual-module offshore wind turbine system has been proposed. This system primarily consists of a DTU 10 MW wind turbine (WT) module and a supporting tension-leg platform (TLP) module. Considering both mechanical and hydrodynamic coupling effects of the dual-module system, this study focuses on its dynamic responses during both the installation and the removal of the WT module under typical sea states. The effect of different installation vessel positions and key parameters of the clamping device on the dynamic response of the system during the WT module removal has been clarified. Based on the findings, preliminary recommendations are provided regarding the optimal positioning of the installation vessel and the optimal design parameters of the clamping device. Furthermore, an auxiliary sleeve has been proposed to facilitate the WT module removal. The results indicate that the application of the auxiliary sleeve can significantly improve the dynamic response of the system. The results of this study can serve as a reference for the design, installation, and removal of floating offshore wind turbines. Full article

Offshore wind turbine (WT) wake interference will reduce power generation and increase the fatigue loads of downstream WTs. Wake interference detection based on aeroacoustic noise is believed to solve these challenges in offshore wind farms. However, aeroacoustic noise is closely related to the aerodynamics around WT blades, and the acoustic detection method requires the mastery of noise emission characteristics. In this paper, FAST.Farm, combined with the acoustic model in OpenFAST, is utilized to investigate the acoustic noise emission characteristics from two 3.4 MW-130 WTs with wake interference. Multi-microphone positions were investigated for the optimal reception selection under 8 m/s and 12 m/s wind speeds with a typical offshore atmospheric turbulence intensity of 6%. The numerical simulation results indicate that wake deficit reduces the total noise emission by about 6 dBA in the overall sound pressure level (OASPL) at 8 m/s, while wake turbulence marginally increases it and its fluctuation. There is a mutual influence between these effects, and the wake deficit effect can be 100% compensated for in the OASPL at 12 m/s. Additionally, downstream observer locations are suggested based on comparisons. These investigations provide new insights into wake interference in offshore wind farms. Full article

The deployment of offshore wind turbines (WTs) has emerged as a pivotal strategy in the transition to renewable energy, offering significant potential for clean electricity generation. However, these structures’ operation and maintenance (O&M) present unique challenges due to their remote locations and harsh marine environments. For these reasons, it is fundamental to promote the development of autonomous solutions to monitor the health condition of the construction parts, preventing structural damage and accidents. This paper explores the application of Unmanned Aerial Vehicles (UAVs) in the inspection and maintenance of offshore wind turbines, introducing a new strategy for autonomous wind turbine inspection and a simulation environment for testing and training autonomous inspection techniques under a more realistic offshore scenario. Instead of relying on visual information to detect the WT parts during the inspection, this method proposes a three-dimensional (3D) light detection and ranging (LiDAR) method that estimates the wind turbine pose (position, orientation, and blade configuration) and autonomously controls the UAV for a close inspection maneuver. The first tests were carried out mainly in a simulation framework, combining different WT poses, including different orientations, blade positions, and wind turbine movements, and finally, a mixed reality test, where a real vehicle performed a full inspection of a virtual wind turbine. Full article

Over the past few decades, wind energy has expanded to become a widespread, clean, and sustainable energy source. However, integrating offshore wind energy with the onshore AC grids presents many stability and control challenges that hinder the reliability and resilience of AC grids, particularly during faults. To address this issue, current grid codes require offshore wind farms (OWFs) to remain connected during and after faults. This requirement is challenging because, depending on the fault location and power flow direction, DC link over- or under-voltage can occur, potentially leading to the shutdown of converter stations. Therefore, this necessitates the proper understanding of key technical concepts associated with the integration of OWFs. To help fill the gap, this article performs an in-depth investigation of existing alternating current fault ride through (ACFRT) techniques of modular multilevel converter-based high-voltage direct current (MMC-HVDC) for OWFs. These techniques include the use of AC/DC choppers, flywheel energy storage devices (FESDs), power reduction strategies for OWFs, and energy optimization of the MMC. This article covers both scenarios of onshore and offshore AC faults. Given the importance of wind turbines (WTs) in transforming wind energy into mechanical energy, this article also presents an overview of four WT topologies. In addition, this article explores the advanced converter topologies employed in HVDC systems to transform three-phase AC voltages to DC voltages and vice versa at each terminal of the DC link. Finally, this article explores the key stability and control concepts, such as small signal stability and large disturbance stability, followed by future research trends in the development of converter topologies for HVDC transmission such as hybrid HVDC systems, which combine current source converters (CSCs) and voltage source converters (VSCs) and diode rectifier-based HVDC (DR-HVDC) systems. Full article

The diode-rectifier unit (DRU)-based high-voltage direct current (HVDC) transmission system offers an economical solution for offshore wind power transmission. However, this approach requires offshore wind farms to establish a strong grid voltage. To meet this requirement while fulfilling the dynamic characteristics of the DRU, this paper proposes an advanced grid-forming (GFM) control strategy for offshore wind turbines connected to DRU-HVDC. The strategy incorporates a P-U controller and a Q-$\omega$ controller based on reactive power synchronization. Furthermore, a novel virtual power-based pre-synchronization method and an adaptive virtual impedance technique are integrated into the proposed GFM control to improve system performance during wind turbine (WT) integration and low-voltage ride-through (LVRT) scenarios. The virtual power-based pre-synchronization method reduces voltage spikes during the integration of new wind turbines, while the adaptive virtual impedance technique effectively suppresses fault currents during low-voltage faults, enabling faster recovery. Simulation results validate the effectiveness of the proposed GFM control strategy, demonstrating improved start-up and LVRT performance through the pre-synchronization and adaptive virtual impedance methods. Full article

This paper presents a novel reference model designed to optimize the integration of preventive and predictive maintenance strategies for offshore wind farms (OWFs), enhancing operational decision-making. The model’s flexible and declarative architecture facilitates the incorporation of new constraints while maintaining computational efficiency, distinguishing it from existing methodologies. Unlike previous research that did not explore the intricate cost dynamics between predictive and preventive maintenance, our approach explicitly addresses the balance between maintenance expenses and wind turbine (WT) downtime costs. We quantify the impacts of these maintenance strategies on key operational metrics, including the Levelized Cost of Energy (LCOE). Using a constraint programming framework, the model enables rapid prototyping of alternative maintenance scenarios, incorporating real-time data on maintenance history, costs, and resource availability. This approach supports the scheduling of service logistics, including the optimization of vessel fleets and service teams. Simulations are used to evaluate the model’s effectiveness in real-world scenarios, such as handling the maintenance of up to 11 wind turbines per business day using no more than four service teams and four vessels, achieving a reduction in overall maintenance costs in simulated case of up to 32% compared to a solution that aims to prevent all downtime events. The prototype implementation as a task-oriented Decision Support System (DSS) further shows its potential in minimizing downtime and optimizing logistics, providing a robust tool for OWF operators. Full article

The decarbonization goals of each country necessitate the utilization of renewable resources, with photovoltaic (PV) and wind turbine (WT) generators being the most common forms. However, spatial constraints, especially on islands, can hinder the expansion of PV and WT installations. In this context, wave energy emerges as a viable supplementary renewable source. Islands are candidate regions to accommodate wave power resources due to their abundant wave potential. While previous studies have explored the wave energy potential of the Aegean Sea, they have not focused on the electricity production and techno-economic aspects of wave power facilities in this area. This paper aims to fill this knowledge gap by conducting a comprehensive techno-economic analysis to evaluate the feasibility of deploying an offshore wave power facility in the Aegean Sea, Greece. The analysis includes a detailed sensitivity assessment of CAPEX and OPEX variability, calculating key indicators like LCOE and NPV to determine the economic viability and profitability of wave energy investments in the region. Additionally, the study identifies hydraulic efficiency and CAPEX thresholds that could make wave power more competitive compared with traditional energy sources. The techno-economic analysis is conducted for a 45 MW offshore floating wave power plant situated between eastern Crete and Kasos—one of the most wave-rich areas in Greece. Despite eastern Crete’s promising wave conditions, the study reveals that with current techno-economic parameters—CAPEX of 7 million EUR/MW, OPEX of 6%, a 20-year lifetime, and 25% efficiency—the wave energy in this area yields a levelized cost of energy (LCOE) of 1417 EUR/MWh. This rate is significantly higher than the prevailing LCOE in Crete, which is between 237 and 300 EUR/MWh. Nonetheless, this study suggests that the LCOE of wave energy in Crete could potentially decrease to as low as 69 EUR/MWh in the future under improved conditions, including a CAPEX of 1 million EUR/MW, an OPEX of 1%, a 30-year lifetime, and 35% hydraulic efficiency for wave converters. It is recommended that manufacturing companies target these specific thresholds to ensure the economic viability of wave power in the waters of the Aegean Sea. Full article

To address the reactive power optimization control problem in offshore wind farms (OWFs), this paper proposes an adaptive reactive power optimization control strategy based on an improved Particle Swarm Optimization (PSO) algorithm. Firstly, an OWF multi-objective optimization control model is established, with the total sum of voltage deviations at wind turbine (WT) terminals, active power network losses, and reactive power margin of WTs as comprehensive optimization objectives. Innovatively, adaptive weighting coefficients are introduced for the three sub-objectives, enabling the weights of each optimization objective to be adaptively adjusted based on real-time operating conditions, thus enhancing the adaptability of the reactive power optimization model to changes in operating conditions. Secondly, a Uniform Adaptive Particle Swarm Optimization (UAPSO) algorithm is proposed. On one hand, the algorithm initializes the particle swarm using a uniform initialization method; on the other hand, it improves the particle velocity update formula, allowing the inertia coefficient to adaptively adjust based on the number of iterations and the fitness ranking of particles. Simulation results demonstrate the following: (1) Under various operating conditions, the proposed adaptive multi-objective reactive power optimization strategy can ensure the stability of node voltages in offshore wind farms, reduce active power losses, and simultaneously improve reactive power margins. (2) Compared with the traditional PSO algorithm, UAPSO exhibits an approximately 10% improvement in solution speed and enhanced solution accuracy. Full article

The operation and maintenance (O&M) issues of offshore wind turbines (WTs) are more challenging because of the harsh operational environment and hard accessibility. As sudden component failures within WTs bring about durable downtimes and significant revenue losses, condition monitoring and predictive fault diagnostic approaches must be developed to detect faults before they occur, thus preventing durable downtimes and costly unplanned maintenance. Based primarily on supervisory control and data acquisition (SCADA) data, thirty-three weighty features from operational data are extracted, and eight specific faults are categorised for fault predictions from status information. By providing a model-agnostic vector representation for time, Time2Vec (T2V), into Long Short-Term Memory (LSTM), this paper develops a novel deep-learning neural network model, T2V-LSTM, conducting multi-level fault predictions. The classification steps allow fault diagnosis from 10 to 210 min prior to faults. The results show that T2V-LSTM can successfully predict over 84.97% of faults and outperform LSTM and other counterparts in both overall and individual fault predictions due to its topmost recall scores in most multistep-ahead cases performed. Thus, the proposed T2V-LSTM can correctly diagnose more faults and upgrade the predictive performances based on vanilla LSTM in terms of accuracy, recall scores, and F-scores. Full article

Growing population, industrialization, and power requirements are adversely affecting the environment through increased greenhouse gases resulting from fossil fuel burning. Global greenhouse gas mitigation targets have led nations to promote clean and self-renewable sources of energy to address this environmental issue. Offshore wind power resources are relatively more attractive due to high winds, less turbulence, minimal visualization effects, and no interaction of infrastructure. The present study aims at conducting an offshore wind power resource assessment (OWPRA) at some locations in the Gulf of North Suez. For this purpose, the long-term hourly mean wind speed (WS) and wind direction above mean sea level (AMSL), as well as temperature and pressure data near the surface, are used. The data is obtained from ERA5 (fifth generation global climate reanalysis) at six (L1–L6) chosen offshore locations. The data covers a period of 43 years, between 1979 and 2021. The WS and direction are provided at 100 m AMSL, while temperature and pressure are available near water-surface level. At the L1 to L6 locations, the log-term mean WS and wind power density (WPD) values are found to be 7.55 m/s and 370 W/m², 6.37 m/s and 225 W/m², 6.91 m/s and 281 W/m², 5.48 m/s and 142 W/m², 4.30 m/s and 77 W/m², and 5.03 and 115 W/m² and at 100 m AMSL, respectively. The higher magnitudes of monthly and annual windy site identifier indices (MWSI and AWSI) of 18.68 and 57.41 and 12.70 and 42.94 at the L1 and L3 sites, and generally lower values of wind variability indices, are indicative of a favorable winds source, which is also supported by higher magnitudes of mean WS, WPD, annual energy yields, plant capacity factors, and wind duration at these sites. The cost of energy for the worst and the best cases are estimated as 10.120 USD/kWh and 1.274 USD/kWh at the L5 and L1 sites, corresponding to wind turbines WT1 and WT4. Based on this analysis, sites L1, L3, and L2 are recommended for wind farm development in order of preference. The wind variability and windy site identifier indices introduced will help decision-makers in targeting potential windy sites with more confidence. Full article

To address the complexity of siting and sizing for the renewable energy and energy storage (ES) of offshore oil–gas platforms, as well as to enhance the utilization of renewable energy and to ensure the power-flow stability of offshore oil–gas platforms, this paper proposes a hierarchical clustering-and-planning method for wind turbine (WT)/photovoltaic (PV) ES. The proposed strategy consists of three stages. First, the WT/PV power generation is forecast by a LightGBM model. The WT/PV siting and sizing at each node of the distribution network is optimized with a particle swarm optimization (PSO) algorithm, with the objectives of economy and stability. In the second stage, the distribution network is partitioned into sub-clusters, based on a voltage and loss-sensitivity index. Finally, the ES siting and sizing is optimized with PSO to minimize the line loss and the voltage fluctuation for each sub-cluster. The relationship between the economic and stability indicators is conducted quantitatively in the joint-planning approach. Considering the 10 kV distribution network of an oil–gas platform in the Bohai Sea of China as an example, our experiments demonstrated that by adjusting the WT/PV ES capacity for different gas-turbine power outputs, line losses can be reduced by 55–66% and voltage fluctuations can be reduced by 30.4–47.5%. Full article

Offshore wind energy is a renewable energy source that is developing fast. It is considered to be the most promising energy source in the next decade. Besides, the expanding trend for this technology requires the consideration of diversified seabeds. In deep seabeds, floating offshore wind technology (FOWT) is needed. For this latter technology, such as for conventional WT, we need to consider aspects related to performance, aerodynamic force, and forces during operation. In this paper, a two-bladed downwind wind turbine model is utilized to conduct experiments. The collective pitch and cyclic pitch angle are adjusted using swashplated equipment. The fluid forces and moments acting on the rotor surface are measured by a six-component balancing system. By changing the pitch angle of the wind turbine blades, attempts are made to manage the fluid forces generated on the rotor surface. Under varied uniform wind velocities of 7, 8, 9, and 10 m/s, the effect of collective pitch control and cyclic pitch control on the power coefficient and thrust coefficient of FOWT is then discussed. Furthermore, at a wind speed of 10 m/s, both the power coefficient and loads are investigated as the pitch angle and yaw angle change. Experimental results indicate that the combined moment magnitude can be controlled by changing the pitch-angle amplitude. The power coefficient is adjusted by the cyclic pitch-angle controller when the pitch-angle phase changes. In addition, the thrust coefficient fluctuated when the pitch angle changed in the oblique inflow wind condition. Full article

With the active development of offshore wind power worldwide, the development of a green and ecofriendly grouting material (GEGM) has garnered global attention. Such a material must also be developed in Taiwan. Therefore, in this study, a series of environmentally friendly recycled materials were mixed in different proportions to develop a GEGM which can be implemented in the future construction of offshore wind turbines. To evaluate the mechanical properties of the GEGM, low water-to-binder (W/B) ratios (i.e., 0.21, 0.27, and 0.35) were used; cement was replaced with fixed amounts (20%) of ground granulated blast-furnace slag and fly ash; 2%, 2.5%, and 3% superplasticizers (SPs) were added; and two levels of sand content (60% and 70%) were used. The setting time of the GEGM was used to evaluate its workability; its compressive strength and flexural strength were used to evaluate its mechanical properties; and its sulfate resistance, length changes, and four-terminal resistance were used to evaluate its durability. The relationship between the durability and drying shrinkage of the GEGM was subsequently evaluated, and the ratio of final to initial setting times (F/I value) was calculated to determine the effects of the amount of SP added on workability. The highest F/I value (7.7) was achieved when 2 wt.% modified lignin sulfonate (MLS) was added because of the high viscosity of MLS, which compromised the workability of the concrete. The optimal compressive strength (83.62 MPa) was achieved when a W/B ratio of 0.21 was used, when the sand content was 70%, and when a 2% polycarboxylate superplasticizer (PCE) was added, whereas the optimal flexural strength (20.86 MPa) was achieved when 2.5% PCE was added. According to the nondestructive test results and the R2 value (>0.7) obtained from regression analyses of mechanical properties, the study results are reliable and may serve as a reference for future construction projects. Full article

Manufacturing and energy sectors provide vast amounts of maintenance data and information which can be used proactively for performance monitoring and prognostic analysis which lead to improve maintenance planning and scheduling activities. This leads to reduced unplanned shutdowns, maintenance costs and any fatal events that could affect the operations of the overall system. Performance and condition monitoring are among the most used strategies for prognostic and health management (PHM), in which different methods and techniques can be implemented to analyse maintenance and online data. Offshore wind turbines (WTs) are complex systems increasingly needing maintenance. This study proposes a performance monitoring system to monitor the performance of the WT power generation process by exploiting artificial neural networks (ANN) composed of different network designs and training algorithms, using simulated supervisory control and data acquisition (SCADA) data. The performance monitoring is based on different operating modes of the same type of wind turbine. The degradation models were developed based on the generated active power resulting from different degradation levels of the gearbox, which is a critical component of the WTs. The deviations of the wind power curves for all operating modes over time are monitored in terms of the resulting power residuals and are modelled using ANN with a unique network architecture. The monitoring process uses the recursive form of the cumulative summation (CUSUM) change detection algorithm to detect the state change point in which the gearbox efficiency is degraded by evaluating the power residuals predicted by the ANN model. To increase the monitoring effectiveness, a second ANN model was developed to predict the gearbox efficiency to monitor any failure that could happen once the efficiency degrades below a threshold. The results show a high degree of accuracy in power and efficiency prediction in addition to monitoring the abnormal state or deviations of the power generation process resulting from the degraded gearbox efficiency and their corresponding time slots. The developed monitoring method can be a valuable tool to provide maintenance experts with alarms and insights into the general state of the power generation process, which can be used for further maintenance decision-making. Full article

Voltage source converter based high voltage DC system (VSC-HVDC) has become a very promising solution to integrate offshore wind farm. However, the equivalent inertia of the modern power system with large renewable energy integration becomes small, which will arouse some frequency stability problems. To tackle this problem, this paper proposes an improved frequency regulation strategy for VSC-HVDC integrated offshore wind farm. Firstly, in the frequency decrease stage, the rotor kinetic energy of wind turbines (WTs) is used to suppress the decrease of the frequency, and the control parameters are determined to make full use of the mechanical power and rotor kinetic energy of WTs, the frequency nadir is improved. Secondly, in the rotor speed recovery stage, the DC capacitors of VSC-HVDC are used to release power to compensate the deficiency value of wind farm output power and avoid the secondary frequency drop (SFD) problem. Lastly, the simulation is conducted in PSCAD/EMTDC to validate the effectiveness of the proposed coordinated frequency control strategy. Full article