scholarly journals A Framework for Simultaneous Design of Wind Turbines and Cable Layout in Offshore Wind

2021 ◽  
Author(s):  
Juan-Andrés Pérez-Rúa ◽  
Nicolaos A. Cutululis
Keyword(s):  
Wind Turbines ◽  
Heuristic Algorithm ◽  
Optimization Algorithm ◽  
Cost Estimation ◽  
Offshore Wind ◽  
Distance Constraint ◽  
Collection System ◽  
Simultaneous Design ◽  
Study Results

Abstract. An optimization framework for simultaneous design of wind turbines (WTs) and cable layout for collection systemof offshore wind farms (OWFs) is presented in this paper. The typical approach used in both research and practical design is sequential, with an initial annual energy production (AEP) maximization, followed then by the collection system design. The sequential approach is robust and effective, however it fails to exploit the synergies between optimization blocks. Intuitively,one of the strongest trade-offs is between the WTs and cable layout, as they generally compete, i.e. spreading out WTs mitigates wake losses for larger AEP, but also results in longer submarine cables in the collection system and higher costs. The proposedo ptimization framework implements a gradient-free optimization algorithm to smartly move the WTs within the project area subject to minimum distance constraint, while a fast heuristic algorithm is called in every function evaluation in order to calculate a cost estimation of the cable layout. In a final stage, a refined cable layout design is obtained by iteratively solving amixed integer linear program (MILP), modelling all typical engineering constraints of this particular problem. A comprehensive performance analysis of the cost estimation from the fast heuristic algorithm with respect to the exact model is carried out.The applicability of the method is illustrated through a large-scale real-world case study. Results shows that: (i) the quality of the cable layout estimation is strongly dependent on the separation between WTs, where dense WTs layouts present better performance parameters in terms of error, correlation and computing time, and (ii) the proposed simultaneous design approach provides up to 6% of improvement on the quality of fully feasible wind farm designs, and broadly, a statistically significant enhancement is ensured in spite of the stochasticity of the optimization algorithm.

A two-step approach to damage localization at supporting structures of offshore wind turbines

2017 ◽  
Vol 17 (5) ◽  
pp. 1313-1330 ◽  
Author(s):  
Karsten Schröder ◽  
Cristian Guillermo Gebhardt ◽  
Raimund Rolfes
Keyword(s):  
Numerical Model ◽  
Objective Function ◽  
Wind Turbines ◽  
Optimization Algorithm ◽  
Measurement Data ◽  
Offshore Wind ◽  
Mode Shapes ◽  
Damage Localization ◽  
Offshore Wind Turbines ◽  
Supporting Structures

This article introduces a new adaptive two-step optimization algorithm for finite element model updating with special emphasis on damage localization at supporting structures of offshore wind turbines. The algorithm comprises an enhanced version of the global optimization algorithm simulated annealing, the simulated quenching method that approximates an initial guess of damage localization. Subsequently, sequential quadratic programming is used to compute the final solution adaptively. For the correlation of numerical model and measurement data, both a measure based on eigenfrequencies and mode shapes and a measure employing time series are implemented and compared with respect to their performance for damage localization. Phase balance of the time signals is achieved using cross-correlation. The localization problem is stated as a minimization problem in which the measures are used in time and modal domain as the objective function subject to constraints. Furthermore, the objective function value of the adjusted model is used to distinguish correct from wrong solutions. The functionality is proven using a numerical model of a monopile structure with simulated damage and a lab-scaled model of a tripile structure with real damage.

scholarly journals An Integration Optimization Method for Power Collection Systems of Offshore Wind Farms

Energies ◽  
2019 ◽  
Vol 12 (20) ◽  
pp. 3965
Author(s):  
Long Wang ◽  
Jianghai Wu ◽  
Zeling Tang ◽  
Tongguang Wang
Keyword(s):  
Wind Turbines ◽  
Cross Sections ◽  
Performance Optimization ◽  
Wind Farm ◽  
Integration Method ◽  
Voltage Drop ◽  
Integrated Design ◽  
Wind Farms ◽  
Offshore Wind ◽  
Collection System

The traditional power collection system design separately optimizes the connection topology and the cable cross sections, which may result in the inherent shortcoming of lacking the most economical solutions. In this pursuit, the present work envisages the development of an integrated design method for general wind farm power collection systems, which integrated the coupling random fork tree coding, union-find set loop identification, current and voltage drop calculation models, and a high performance optimization algorithm. The proposed coupling random fork tree coding, for the first time, realized the coupling code of the substation location, connection topology, and cable cross sections, providing the basis for the integration design of the power collection system. The optimization results for discrete and regular wind farms indicated that the proposed integration method achieved the best match of topology, substation location, and the cable cross sections, thus presenting the most economical scheme of the power collection system. Compared to the traditional two-step methods, the integration method used more branches while acquiring them, to maintain the lower number of wind turbines in each branch. Furthermore, it also employed large cross-section cables to reduce the energy loss caused by the impedance in the topology, thereby resulting in a slight increased cable cost; however, the total cost was minimized. The proposed method is very versatile and suitable for the optimization of power collection systems containing any number of wind turbines and substations, and can be combined with any evolutionary algorithm.

scholarly journals Wind Technologies for Wake Effect Performance in Windfarm Layout Based on Population-Based Optimization Algorithm

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4125
Author(s):  
Yi-Zeng Hsieh ◽  
Shih-Syun Lin ◽  
En-Yu Chang ◽  
Kwong-Kau Tiong ◽  
Shih-Wei Tan ◽  
...  
Keyword(s):  
Wind Turbines ◽  
Optimization Algorithm ◽  
Cost Minimization ◽  
Population Based ◽  
Offshore Wind ◽  
Superior Performance ◽  
Weather Data ◽  
Ant Colony Optimization Algorithm ◽  
Wake Effect ◽  
Distributed Genetic Algorithm

The focus of this study is under the auspices of China Steel Corporation, Taiwan, in carrying out the national energy policy of 2025 Non-Nuclear Home. Under this policy, an estimated 600 offshore wind turbines will be installed by 2025. In order to carry out the wind energy project effectively, a preliminary study must be conducted. In this article, we investigated the influence of the wake effect on the efficiency of the turbines’ layout in a windfarm. A distributed genetic algorithm is deployed to study the wind turbines’ layout in order to alleviate the detrimental wake effect. In the current stage of this research, the historical weather data of weather stations near the site of the 29th windfarm, Taiwan, were collected by Academia Sinica. Our wake effect resilient optimized windfarm showed superior performance over that of the conventional windfarm. Additionally, an operation cost minimization process is also demonstrated and implemented using an ant colony optimization algorithm to optimize the total length of the power-carrying interconnecting cables for the turbines inside the optimized windfarm.

scholarly journals Minimizing the Energy Cost of Offshore Wind Farms by Simultaneously Optimizing Wind Turbines and Their Layout

2019 ◽  
Vol 9 (5) ◽  
pp. 835 ◽  
Author(s):  
Longfu Luo ◽  
Xiaofeng Zhang ◽  
Dongran Song ◽  
Weiyi Tang ◽  
Li Li ◽  
...  
Keyword(s):  
Wind Speed ◽  
Case Studies ◽  
Wind Turbines ◽  
Optimization Algorithm ◽  
Wind Direction ◽  
Energy Cost ◽  
Wind Farms ◽  
Offshore Wind ◽  
Energy Costs ◽  
Offshore Wind Farms

The construction and gradual installation of turbines on wind farms has been hindered by the high cost of the energy production. An effective way to minimize energy costs is via the optimal design of wind turbines and their layout, but relevant and synthetic studies are lacking. This paper proposes a method to minimize the energy cost of offshore wind farms by simultaneously optimizing the rated wind speed, the rotor radius of wind turbines and their layout. Firstly, a new, mixed mathematical formulation of the energy cost is presented, considering the Weibull distribution for wind, the characterizing parameters of wind turbines and the distance between two turbines. Secondly, to obtain the minimum energy cost, a composite optimization algorithm was developed, which consists of an iterative method and an improved particle swarm optimization algorithm. The former was used to search the minimal energy costs that relate to the design parameters of a single wind turbine, while the latter was adopted for optimizing the layout of the wind turbines iteratively. Finally, the proposed method was applied to three case studies with variable wind speed and constant wind direction. Results of the case studies show that the reduced energy cost after optimization has a range of 0–0.001 $/kWh, which confirms the effectiveness of the proposed approach. Meanwhile, the layout of the wind turbines after optimization tends to locate the two wind turbines with the biggest spacing in the wind direction, which justifies the utilization of layout optimization. Furthermore, exploring the optimally designed parameters of wind turbines revealed that the wind farms with a high mean wind speed can have a wider range of turbine capacity than those with a low wind speed, which offers more freedom for the designers when constructing offshore wind farms at wind sites with rich wind resources.

Hurricane risk assessment of offshore wind turbines under changing climate

2021 ◽  
Author(s):  
Reda Snaiki ◽  
Teng Wu
Keyword(s):  
Wind Turbines ◽  
Risk Estimation ◽  
Structural Response ◽  
Offshore Wind ◽  
Offshore Wind Turbines ◽  
The North ◽  
Study Results ◽  
Hurricane Hazard ◽  
D Model

<p>Offshore wind energy is attracting increasing attention across the North America. However, the offshore wind turbines along the East Coast are extremely vulnerable to hurricane-induced hazards. The vulnerability to hurricanes is expected to change due to global warming’s effects. This study quantifies the risk of floating wind turbines (FWTs) subjected to hurricane hazards under current and future climate scenarios. The hurricane hazard estimation is achieved using a hurricane track model which generates a large synthetic database of hurricanes allowing for accurate risk estimation. The structural response of the FWTs during each hurricane event is obtained using an efficient physics-based 3-D model. The case study results involving a parked FWT indicate that the change in hurricane-induced risk, evaluated in terms of the magnification factor, to the FWTs would significantly increase with the intensity measure.</p>

scholarly journals Assessment of Wind Turbine Aero-Hydro-Servo-Elastic Modelling on the Effects of Mooring Line Tension via Deep Learning

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2264 ◽  
Author(s):  
Zi Lin ◽  
Xiaolei Liu
Keyword(s):  
Deep Learning ◽  
Wind Turbines ◽  
Environmental Conditions ◽  
Line Tension ◽  
Offshore Wind ◽  
Mooring Line ◽  
Offshore Wind Turbines ◽  
Wind Speeds ◽  
Study Results ◽  
Floating Offshore Wind Turbines

As offshore wind turbines are moving to deeper water depths, mooring systems are becoming more and more significant for floating offshore wind turbines (FOWTs). Mooring line failures could affect power generations of FOWTs and ultimately incur risk to nearby structures. Among different failure mechanics, an excessive mooring line tension is one of the most essential factors contributing to mooring failure. Even advanced sensing offers an effective way of failure detections, but it is still difficult to comprehend why failures happened. Unlike traditional parametric studies that are computational and time-intensive, this paper applies deep learning to investigate the major driven force on the mooring line tension. A number of environmental conditions are considered, ranging from cut in to cut out wind speeds. Before formatting input data into the deep learning model, a FOWT model of dynamics was simulated under pre-defined environmental conditions. Both taut and slack mooring configurations were considered in the current study. Results showed that the most loaded mooring line tension was mainly determined by the surge motion, regardless of mooring line configurations, while the blade and the tower elasticity were less significant in predicting mooring line tension.

Penatalaksanaan IMD pada Ibu Postpartum Sectio Caesarea Mempengaruhi Status Gizi dan Kecepatan Produksi ASI

2020 ◽  
Vol 2 (2) ◽  
pp. 112-120
Author(s):  
Nursari Abdul Syukur ◽  
Susi Purwanti
Keyword(s):  
Breast Milk ◽  
Nutritional Status ◽  
Milk Production ◽  
Quantitative Research ◽  
Milk Protein ◽  
Sectio Caesarea ◽  
Control Group ◽  
P Value ◽  
Study Results

Many mothers who give birth to Sectio Caesarea (SC) do not Initiate Early Breastfeeding (IMD), which fails exclusive breastfeeding. This study aimed to determine the effect of IMD management in postpartum SC mothers on nutritional status, speed of milk production, and quality of breast milk protein. Method: quantitative research with quasi approach experiment. The research design used was a pre-post-test control non-equivalent control group. A sampling of this study used the Consecutive method sampling with a sample of 20 mothers who gave birth by cesarean section (SC). Hypothesis testing uses the independent t-test and the Mann-Whitney test. The study results showed an influence on the management of IMD in postpartum SC mothers on the speed of ASI production (p-value=0.004) and nutritional status (p-value=0.028). There was no effect of IMD management on postpartum SC mothers on the quality of breast milk protein (p-value = 0.543). This study recommends that the hospital implement an IMD promotion program before the abdominal wall is closed as a form of intervention to increase milk production and maternal nutritional status

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