Search Results (12)

This study presents a comprehensive techno-economic assessment of offshore wind projects in the Colombian Caribbean, emphasizing the impact of site-specific parameters on development costs and performance. Wind resource conditions were evaluated in four coastal regions (La Guajira, Magdalena, Atlántico, and Bolívar) using hourly meteorological data from 2015 to 2024, adjusted to 100 m above ground level through logarithmic and power law wind profile models. The analysis included wind speed, bathymetry, distance to shore, distance to substation, foundation type, wind power density (WPD), and capacity factor (C_f). Based on these parameters, annual energy generation was estimated, and both capital expenditures (CAPEX) and operational expenditures (OPEX) were calculated, considering the technical and cost differences between fixed and floating foundations. Results show that La Guajira combines excellent wind conditions (WPD of 796 W/m² and C_f of 61.5%) with favorable construction feasibility (bathymetry of −32 m), resulting in the lowest CAPEX among the studied regions. In contrast, Magdalena and Atlántico, with bathymetries exceeding 200 m, require floating foundations that more than double the investment costs. Bolívar presents an intermediate profile, offering solid wind potential and fixed foundation feasibility at a moderate cost. The findings confirm that offshore wind project viability depends not only on wind resource quality but also on physical site constraints, which directly influence the cost structure and energy yield. This integrated approach supports more accurate project prioritization and contributes to strategic planning for the sustainable deployment of offshore wind energy in Colombia. Full article

Currently, YOLO-based object detection is widely employed in intelligent inspection robots. However, under interference factors present in dimly lit substation environments, YOLO exhibits issues such as excessively low accuracy, missed detections, and false detections for critical targets. To address these problems, this paper proposes HSS-YOLO, a lightweight object detection model based on YOLOv11. Initially, HetConv is introduced. By combining convolutional kernels of different sizes, it reduces the required number of floating-point operations (FLOPs) and enhances computational efficiency. Subsequently, the integration of Inner-SIoU strengthens the recognition capability for small targets within dim environments. Finally, ShuffleAttention is incorporated to mitigate problems like missed or false detections of small targets under low-light conditions. The experimental results demonstrate that on a custom dataset, the model achieves a precision of 90.5% for critical targets (doors and two types of handles). This represents a 4.6% improvement over YOLOv11, while also reducing parameter count by 10.7% and computational load by 9%. Furthermore, evaluations on public datasets confirm that the proposed model surpasses YOLOv11 in assessment metrics. The improved model presented in this study not only achieves lightweight design but also yields more accurate detection results for doors and handles within dimly lit substation environments. Full article

Substation equipment defect detection has always played an important role in equipment operation and maintenance. However, the task scenarios of substation equipment defect detection are complex and different. Recent studies have revealed issues such as a significant missed detection rate for small-sized targets and diminished detection precision. At the same time, the current mainstream detection algorithms are highly complex, which is not conducive to deployment on resource-constrained devices. In view of the above problems, a small target and lightweight substation main scene equipment defect detection algorithm is proposed: Efficient Attentional Lightweight-YOLO (EAL-YOLO), which detection accuracy exceeds the current mainstream model, and the number of parameters and floating point operations (FLOPs) are also advantageous. Firstly, the EfficientFormerV2 is used to optimize the model backbone, and the Large Separable Kernel Attention (LSKA) mechanism has been incorporated into the Spatial Pyramid Pooling Fast (SPPF) to enhance the model’s feature extraction capabilities; secondly, a small target neck network Attentional scale Sequence Fusion P2-Neck (ASF2-Neck) is proposed to enhance the model’s ability to detect small target defects; finally, in order to facilitate deployment on resource-constrained devices, a lightweight shared convolution detection head module Lightweight Shared Convolutional Head (LSCHead) is proposed. Experiments show that compared with YOLOv8n, EAL-YOLO has improved its accuracy by 2.93 percentage points, and the mAP50 of 12 types of typical equipment defects has reached 92.26%. Concurrently, the quantity of FLOPs and parameters has diminished by 46.5% and 61.17% respectively, in comparison with YOLOv8s, meeting the needs of substation defect detection. Full article

Floating offshore wind (FOW) is rapidly gaining interest due to its large potential. In this regard, it is of special interest to determine the best locations for its installation. One of the main aspects when evaluating the feasibility of a project is the levelised cost of energy (LCOE), but there are many variables to consider when calculating it for FOW, and plenty of them are hard to find when the scope is all the suitable areas worldwide. This paper presents the calculation and analysis of the global LCOE with particular focus on the best countries and territories from an economic point of view, considering four types of platforms: semi-submersible, barge, spar, and tension leg platform (TLP). The model takes into account, on the one hand, wind data, average significant wave height, and distance to shore for an accurate calculation of delivered energy to the onshore substation and, on the other hand, bathymetry, distances, and existing data from projects to find appropriate functions for each cost with regression models (e.g., manufacturing, installation, operation and maintenance (O&M), and decommissioning costs). Its results can be used to assess the potential areas around the world and identify the countries and territories with the greatest opportunities regarding FOW. The lowest LCOE values, i.e., the optimal results, correspond to areas where wind resources are more abundant and the main variables of the site affecting the costs (water depth, average significant wave height, distance to shore, and distance to port) are as low as possible. These areas include the border between Venezuela and Colombia, the Canary Islands, Peru, the border between Western Sahara and Mauritania, Egypt, and the southernmost part of Argentina, with LCOEs around 90 €/MWh. Moreover, there are many areas in the range of 100–130 €/MWh. Full article

In general, a high voltage (HV) substation can be made up of multiple insulation subsystems: an air insulation subsystem (AIS), gas insulation subsystem (GIS), liquid insulation subsystem (power transformers), and solid insulation subsystem (power cables), all of them with their grounding structures interconnected and linked to the substation earth. Partial discharge (PD) pulses, which are generated in a HV apparatus belonging to a subsystem, travel through the grounding structures of the others. PD analyzers using high-frequency current transformer (HFCT) sensors, which are installed at the connections between the grounding structures, are sensitive to these traveling pulses. In a substation made up of an AIS, several non-critical PD sources can be detected, such as possible corona, air surface, or floating discharges. To perform the correct diagnosis, non-critical PD sources must be separated from critical PD sources related to insulation defects, such as a cavity in a solid dielectric material, mobile particles in SF6, or surface discharges in oil. Powerful diagnostic tools using PD clustering and phase-resolved PD (PRPD) pattern recognition have been developed to check the insulation condition of HV substations. However, a common issue is how to determine the subsystem in which a critical PD source is located when there are several PD sources, and a critical one is near the boundary between two HV subsystems, e.g., a cavity defect located between a cable end and a GIS. The traveling direction of the detected PD is valuable information to determine the subsystem in which the insulation defect is located. However, incorrect diagnostics are usually due to the constraints of PD measuring systems and inadequate PD diagnostic procedures. This paper presents a diagnostic procedure using an appropriate PD analyzer with multiple HFCT sensors to carry out efficient insulation condition diagnoses. This PD procedure has been developed on the basis of laboratory tests, transient signal modeling, and validation tests. The validation tests were carried out in a special test bench developed for the characterization of PD analyzers. To demonstrate the effectiveness of the procedure, a real case is also presented, where satisfactory results are shown. Full article

The present study evaluates the feasibility of using a fully suspended inter-array cable system for an offshore wind farm. It includes both numerical simulations and a scaled-down experiment, conducted at a 1:49 scale, to validate the numerical results. To achieve the goal, a 15 MW floating offshore wind turbine (FOWT) and a floating offshore substation (FOSS) are involved to simulate the wind farm array. This study incorporates the 50-year return period conditions of the Taiwan Hsinchu offshore area, which has a water depth of about 100 m, to validate the specifications related to the platform motion and mooring line tension. Additionally, an analysis of the tension, curvature, and fatigue damage of the dynamic cable system is discussed in this research. Because a fully suspended cable is a relatively new concept and may be more frequently considered in a deeper water depth area, numerical simulation software Orcina Orcaflex 11.4 has been chosen to conduct the fully coupled simulation, determining whether the fully suspended cable system could effectively withstand the challenges posed by extreme sea conditions. This is due to the reason that a fully suspended cable would occupy a larger space in the ocean, which may pose a risk by influencing the navigation of the vessels. Therefore, the cable laying depth under normal sea states is also discussed to evaluate the influence over vessel navigation. This study also collects the long-term environmental data from the Central Weather Bureau, Taiwan, to calculate the accumulative cable fatigue damage under different sea states. To integrate the results, this research applies fitness parameters to evaluate the feasibility of each cable configuration. Covering the cable performance under extreme sea states and regular operating sea states offers valuable insights for applications in ocean engineering. Full article

The development of artificial intelligence technology provides a new model for substation inspection in the power industry, and effective defect diagnosis can avoid the impact of substation equipment defects on the power grid and improve the reliability and stability of power grid operation. Aiming to combat the problem of poor recognition of small targets due to large differences in equipment morphology in complex substation scenarios, a visual fault detection algorithm of substation equipment based on improved YOLOv5 is proposed. Firstly, a deformable convolution module is introduced into the backbone network to achieve adaptive learning of scale and receptive field size. Secondly, in the neck of the network, a simple and effective BiFPN structure is used instead of PANet. The multi-level feature combination of the network is adjusted by a floating adaptive weighted fusion strategy. Lastly, an additional small object detection layer is added to detect shallower feature maps. Experimental results demonstrate that the improved algorithm effectively enhances the performance of power equipment and defect recognition. The overall recall rate has increased by 7.7%, precision rate has increased by nearly 6.3%, and mAP@0.5 has improved by 4.6%. The improved model exhibits superior performance. Full article

Offshore wind is planned to become the first source of energy by 2050. That requires installing turbines in deeper seas. It is shown that only floating wind turbines will allow dealing with this challenge while keeping a reasonable cost of energy production and transport according to the levelized cost of electricity. A Floating Offshore Substation will be needed in many sites. This technology is still at a low technology readiness level. This paper aims to analyze the system reliability of such a structure for which the failure rates of structural components such as mooring lines and dynamic power cables are close to the ones of electro-technical systems. Consequently, only a system reliability assessment of the floating offshore substation will allow accurately quantifying its availability and the most sensitive components. Usually, structural reliability aims at quantifying the probability of failures, while electro-technical reliability relies on feedback and observed failure rates. The paper first unifies these two concepts in a single formulation and then evaluates the system’s reliability and availability. This methodology is illustrated in a study case localized in the French coasts of the Mediterranean Sea, where the effect of several mooring and substation designs on the system reliability is compared. Full article

Electrical grid layout optimization should consider the placements of turbines and substations and include effects such as wake losses, power losses in cables, availability of different cable types, reliability-based power losses and operational/decommissioning cost besides the initial investment cost. Hence, optimizing the levelized cost of energy is beneficial capturing long-term effects. The main contribution of this review paper is to identify the current works and trends on electrical layout optimization for offshore wind farms as well as to analyze the applicability of the found optimization approaches to commercial-scale floating wind farms which have hardly been investigated so far. Considering multiple subproblems (i.e., micrositing and cabling), simultaneous or nested approaches are advantageous as they avoid sequential optimization of the individual problems. To cope with this combinatorial problem, metaheuristics seems to offer optimal or at least close-to-optimal results while being computationally much less expensive than deterministic methods. It is found that floating wind brings new challenges which have not (or only insufficiently) been considered in present optimization works. This will also be reflected in a higher complexity and thus influence the suitability of applicable optimization techniques. New aspects include the mobility of structures, the configurations and interactions of dynamic cables and station-keeping systems, the increased likelihood of prevailing heterogeneous seabeds introducing priority zones regarding anchor and riser installation, the increased importance of reliability and maintainability due to stricter weather limits, and new floating specific wind farm control methods to reduce power losses. All these facets are crucial to consider when thoroughly optimizing the levelized cost of energy of commercial-scale floating offshore wind farms. Full article

As the backup power supply of power plants and substations, valve-regulated lead-acid (VRLA) batteries are the last safety guarantee for the safe and reliable operation of power systems, and the batteries’ status of health (SOH) directly affects the stability and safety of power system equipment. In recent years, serious safety accidents have often occurred due to aging and failure of VRLA batteries, so it is urgent to accurately evaluate the health status of batteries. Accurate estimation of battery SOH is conducive to real-time monitoring of single-battery health information, providing a reliable guarantee for fault diagnosis and improving the overall life and economic performance of the battery pack. In this paper, first, the floating charging operation characteristics and aging failure mechanism of a VRLA battery are summarized. Then, the definition and estimation methods of battery SOH are reviewed, including an experimental method, model method, data-driven method and fusion method. The advantages and disadvantages of various methods and their application conditions are analyzed. Finally, for a future big data power system backup power application scenario, the existing problems and development prospects of battery health state estimation are summarized and prospected. Full article

Offshore floating hybrid wind and wave energy is a young technology yet to be scaled up. A way to reduce the total costs of the energy production process in order to ensure competitiveness in the sustainable energy market is to maximize the farm’s efficiency. To do so, an energy generation and costs calculation model was developed with the objective of minimizing the technology’s Levelized Cost of Energy (LCOE) of the P80 hybrid wind-wave concept, designed by the company Floating Power Plant A/S. A Particle Swarm Optimization (PSO) algorithm was then implemented on top of other technical and decision-making processes, taking as decision variables the layout, the offshore substation position, and the export cable choice. The process was applied off the west coast of Ireland in a site of interest for the company, and after a quantitative and qualitative optimization process, a minimized LCOE was obtained. It was then found that lower costs of ~73% can be reached in the short-term, and the room for improvement in the structure’s design and materials was highlighted, with an LCOE reduction potential of up to 32%. The model serves usefully as a preliminary analysis. However, the uncertainty estimate of 11% indicates that further site-specific studies and measurements are essential. Full article

Partial discharge (PD) measurement and its pattern recognition are vital to fault diagnosis of transformers, especially to those traction substation transformers undergoing repetitive traction load shocks. This paper presents the primary factors induced by traction load shocks including high total harmonics distortion (THD), transient voltage impulse and high-temperature rise, and their effects on the feature parameters of PD. Experimental tests are conducted on six artificial PD models with these factors introduced one by one. Results reveal that the maximum PD quantity and the PD repetitive rate are favorable to be enlarged when the oil temperature exceeds 80 °C or the THD is higher than 16% with certain orders of harmonic. The decline in PD inception voltage can mainly be attributed to the transient voltage impulse. The variation in central frequency of the fast Fourier transformation (FFT) spectra transformed from ultra-high frequency signals can mainly be attributed to high THD, especially when it exceeds 20%. The temperature rise has no significant influence on the FFT spectra; the transient voltage impulse, however, can result in a central frequency shift of the floating particle discharge. With the rapid development of high-speed railways, the study presented in this paper will be helpful for field PD detection and recognition of traction substation transformers in the future. Full article