Operation Of Offshore Wind Farms Research Articles

Optimal Pitch Angle Strategy for Energy Maximization in Offshore Wind Farms Considering Gaussian Wake Model

This paper presents a new approach based on the optimization of the blade pitching strategy of offshore wind turbines in order to maximize the global energy output considering the Gaussian wake model and including the effect of added turbulence. A genetic algorithm is proposed as an optimization tool in the process of finding the optimal setting of the wind turbines, which aims to determine the individual pitch of each turbine so that the overall losses due to the wake effect are minimised. The integration of the Gaussian model, including the added turbulence effect, for the evaluation of the wakes provides a step forward in the development of strategies for optimal operation of offshore wind farms, as it is one of the state-of-the-art analytical wake models that allow the evaluation of the energy output of the project in a more reliable way. The proposed methodology has been tested through the execution of a set of test cases that show the ability of the proposed tool to maximize the energy production of offshore wind farms, as well as highlights the importance of considering the effect of added turbulence in the evaluation of the wake.

Comprehensive Application of Multi-beam Sounding System and Side-scan Sonar in Scouring Detection of Underwater Structures in Offshore Wind Farms

In recent years, the installed capacity and power generation of offshore wind power have continued to grow rapidly, operation and maintenance testing has faced many technical challenges. Among them, the monitoring of the scour status of the underwater structure of the wind turbine and the complete basic data of the wind turbine's full life cycle management system are of great significance to ensuring the long-term safe and stable operation of the offshore wind farm. This paper introduces the application of a combined multi-beam bathymetric system and side-scan sonar in the scour detection of underwater structures of wind farms based on an example of offshore wind farm detection in the East China Sea. The combination of the two can effectively achieve complementary advantages and obtain more detailed and accurate water depth data and underwater structure images. It provides reliable basic data support for the operation and maintenance of offshore wind farms and the establishment of life cycle management system.

Coordinate control strategy for stability operation of offshore wind farm integrated with Diode-rectifier HVDC

Due to low investment cost and high reliability, a new scheme called DR-HVDC (Diode Rectifier based HVDC) transmission was recently proposed for grid integration of large offshore wind farms. However, in this scheme, the application of conventional control strategies for stability operation face several challenges due to the uncontrollability of the DR. In this paper, a coordinated control strategy of offshore wind farms using the DR-HVDC transmission technology to connect with the onshore grid, is investigated. A novel coordinated control strategy for DR-HVDC is proposed based on the analysis of the DC current control ability of the full-bridge-based modular multilevel converter (FB-MMC) at the onshore station and the input and output characteristics of the diode rectifier at the offshore. Considering the characteristics of operation stability and decoupling between reactive power and active power, a simplified design based on double-loop droop control for offshore AC voltage is proposed after power flow and voltage–current (I–V) characteristics of the offshore wind farm being analyzed. Furthermore, the impact of onshore AC fault to offshore wind farm is analyzed, and a fast fault detection and protection strategy without relying on communication is proposed. Case studies carried out by PSCAD/EMTDC verify the effectiveness of the proposed control strategy for the start up, power fluctuation, and onshore and offshore fault conditions.

Statistical models for improving significant wave height predictions in offshore operations

Installation and maintenance strategies regarding offshore wind farm operations involve extensive logistics. The main focus is the right temporal and spatial placement of personnel and equipment, while taking into account forecasted meteorological and ocean conditions. For these operations to be successful, weather windows characterized by certain permissive wave conditions are of enormous importance, whereas unforeseen events result in high cost and risk of safety. Numerical modelling of waves, water levels and current related variables has been used extensively to forecast ocean conditions. To account for the inherited model uncertainty, several error modelling techniques can be implemented for the numerical model forecasts to be corrected. In this study, various Bayesian Network (BN) models are incorporated, in order to enhance the accuracy of the significant wave height predictions and to be compared with other techniques, in conditions resembling the real-time nature of the application. The implemented BN models differ in terms of training and structure and provide overall the most satisfying performance. Supplementary, it is shown that the BN models illustrate significant advantages as both quantitative and conceptual tools, since they produce estimates for the underlying uncertainty of the phenomena, while providing information about the incorporated variables’ dependence relationships through their structure.

Analysis and Control of Offshore Wind Farms Connected With Diode Rectifier-Based HVDC System

This paper analyzes the control and operation of offshore wind farms connected with diode rectifier based HVDC (DR-HVDC) system. A small-signal state-space model of the offshore wind turbines (WTs) connected with DR-HVDC system is developed to design the WT Q–f droop control. The use of WT P–V and Q–f control during individual WT active power variation is clearly clarified. In order to reduce the interaction between WT active power and reactive power, an angle feedforward control is proposed where an additional phase shift is directly added to the WT output voltage based on the WT's active power output. The effectiveness of the proposed control on improving dynamic response and reducing active and reactive power interaction is verified by frequency-domain analysis and time-domain simulations in PSCAD/EMTDC.

Real-Time Determination of Depth of Burial Profiles for Submarine Power Cables

The safe operation of submarine power cables at high load is of highest relevance for an economic and reliable operation of offshore wind farms and submarine interconnection systems. Burial of power cables at a certain minimum depth is often required for mechanical protection of the cable and to avoid too strong heating of the seafloor surface. The depth of burial (DoB) of those cables may vary over time by movements of sand and the cables themselves. Monitoring such changes so far requires, costly yearly surveys using submarine robots. In this study, we present a method to permanently analyze the DoB of submarine power cable formations by using distributed temperature sensing, electric load data, and thermal models of the submarine cable installation. An analysis of field data shows that our method has the capability to detect comparatively fast variations of DoB and also cable exposure events in real installations.

Hierarchical control of offshore wind farm connected by parallel diode‐rectifier‐based HVDC and HVAC links

This article investigates the operation of offshore wind farm connected by parallel diode-rectifier-based HVDC (DR-HVDC) and HVAC links. A secondary voltage control is proposed to control the offshore AC voltage amplitude by regulating the DC voltage of the DR-HVDC link. A secondary frequency control and a phase angle control are proposed to adjust the reactive power reference in the primary control, which synchronise the offshore point of common coupling (PCC) frequency and phase angle to those of the HVAC link. Such secondary voltage control, frequency control, and phase angle control enable seamless transition from DR-HVDC mode to parallel mode. A tertiary power control scheme is further proposed to control the active power flow distribution between DR-HVDC and HVAC links through the regulation of PCC phase angle. To ensure smooth transition from HVAC mode to parallel mode, a virtual DC power control is proposed to control the virtual DC power at zero prior to the connection of the DR-HVDC link. A small-signal model of the parallel system is developed, and the stability analysis is carried out for the proposed control scheme. Simulation results in PSCAD/EMTDC verify the proposed control under normal and fault conditions.

Development of Optimal Maintenance Policies for Offshore Wind Turbine Gearboxes Based on the Non-homogeneous Continuous-Time Markov Process

Gearbox in offshore wind turbines is a component with the highest failure rates during operation. Analysis of gearbox repair policy that includes economic considerations is important for the effective operation of offshore wind farms. From their initial perfect working states, gearboxes degrade with time, which leads to decreased working efficiency. Thus, offshore wind turbine gearboxes can be considered to be multi-state systems with the various levels of productivity for different working states. To efficiently compute the time-dependent distribution of this multi-state system and analyze its reliability, application of the non-homogeneous continuous-time Markov process (NHCTMP) is appropriate for this type of object. To determine the relationship between operation time and maintenance cost, many factors must be taken into account, including maintenance processes and vessel requirements. Finally, an optimal repair policy can be formulated based on this relationship.

Operation of offshore wind farms connected with DRU-HVDC transmission systems with special consideration of faults

The diode rectifier unit (DRU)-based high-voltage DC (DRU-HVDC) system is a promising solution for offshore wind energy transmission thanks to its compact design, high efficiency, and strong reliability. Herein we investigate the feasibility of the DRU-HVDC system considering onshore and offshore AC grid faults, DC cable faults, and internal DRU faults. To ensure safe operation during the faults, the wind turbine (WT) converters are designed to operate in either current-limiting or voltage-limiting mode to limit potential excessive overcurrent or overvoltage. Strategies for providing fault currents using WT converters during offshore AC faults to enable offshore overcurrent and differential fault protection are investigated. The DRU-HVDC system is robust against various faults, and it can automatically restore power transmission after fault isolation. Simulation results confirm the system performance under various fault conditions.

Optimizing vessel fleet size and mix to support maintenance operations at offshore wind farms

This paper considers the problem of determining the optimal vessel fleet to support maintenance operations at an offshore wind farm. We propose a two-stage stochastic programming (SP) model of the problem where the first stage decisions are what vessels to charter. The second stage decisions are how to support maintenance tasks using the chartered vessels from the first stage, given uncertainty in weather conditions and the occurrence of failures. To solve the resulting SP model we perform an ad-hoc Dantzig–Wolfe decomposition where, unlike standard decomposition approaches for SP models, parts of the second stage problem remain in the master problem. The decomposed model is then solved as a matheuristic by apriori generating a subset of the possible extreme points from the Dantzig–Wolfe subproblems. A computational study in three parts is presented. First, we verify the underlying mathematical model by comparing results to leading work from the literature. Then, results from in-sample and out-of-sample stability tests are presented to verify that the matheuristic gives stable results. Finally, we exemplify how the model can help offshore wind farm operators and vessel developers improve their decision making processes.

Decision Support Models for Operations and Maintenance for Offshore Wind Farms: A Review

This paper reviews the state of the art in offshore wind farm operations and maintenance with a focus on decision support models for the scheduling of maintenance. Factors influential to maintenance planning are collected from the literature and their inclusion in state-of-the-art models is discussed. Methods for modeling and optimization are presented. The methods currently used and possible alternatives are discussed. The existing models are already able to aid the decision-making process. They can be improved by applying more advanced mathematical methods, including uncertainties in the input, regarding more of the influential factors, and by collecting, analyzing, and subsequently using more accurate data.

A Review on the Planning Problem for the Installation of Offshore Wind Farms

Offshore wind farms provide a promising technology to produce renewable and sustainable energy. Nevertheless, the installation and operation of offshore wind farms pose a particular challenge to the planning and execution of operations. This article aims to identify requirements towards a decision support tool for the installation planning. Therefore, it provides a review of existing research in planning approaches and summarizes the overall planning problem. Afterwards this problem is decomposed into single tasks, according to their planning horizons. This decomposition shows a high level of interconnection between tasks across all levels. Higher levels provide constraints for the tasks on lower levels, while the results of these tasks are incorporated at higher levels. Finally, the article discusses the advantages and disadvantages of different approaches to solve these tasks.

국내 해상풍력발전 운영·관리 산업의 발전 전략에 관한 연구

국내 해상풍력발전 운영·관리 산업의 발전 전략에 관한 연구

A Study on Building an Offshore Wind Farm using Genetic Algorithm

해상풍력단지 조성작업은 선박을 이용한 해상작업이 요구됨에 따라 해상의 기상여건에 매우 민감하다. 이는 해상여건이 악화 하면 해상풍력단지 완공 시기가 지연되면서 선박임대료, 인건비 등의 추가적인 비용이 발생하고, 궁극적으로 해상풍력단지 운영의 경제성에 영향을 끼치게 된다. 따라서 본 연구에서는 변화하는 해상여건에 따른 해상작업의 불확실성을 고려하여 해상풍력단지 조성에 관한 일정계획을 참고할 수 있는 분석모델을 개발하였다. 이를 위해 먼저 분석모델 구축을 위해 국내 해상풍력단지 조성을 위한 해상물류 프로세스를 정의하였다. 국내의 해상풍력단지 조성을 위한 해상물류는 항만을 중계지로 활용하는 체계이다. 항만에서 해상풍력 시스템의 구성품이 집화되고, 이를 반 조립한 후 선박을 이용하여 운송하고 해상에서 설치하는 방식이다. 다음 으로 정의된 해상물류 프로세스에 기초한 수리적 모델을 개발하였다. 또한, 개발된 수리적 모델이 NP-hard 문제에 속하므로 휴리 스틱 기법인 유전자 알고리즘을 개발하여 국내 서남해안 해상풍력단지 조성 프로젝트 사례에 적용하였다. 그 결과 해상풍력터빈 1기당 평균 설치작업 일수는 3.13∼3.29일로 분석되었다. 그리고 해상풍력 시스템의 설치 대수가 적으면 해저작업을 선행한 후 해상작업을 하는 것이 타당한 것으로 나타났다. 반면에 대규모의 해상풍력단지를 조성할 경우는 해상여건을 고려하여 전략적으로 일정을 관리하는 것이 필요한 것으로 분석되었다.The construction of offshore wind farms is very sensitive to the weather conditions due to the demand for maritime work using ships. If the delay of completion of offshore wind farm is occurred depending on the weather and marine conditions, additional costs will be incurred, which will eventually affect the economics of offshore wind farm operation. Therefore, in this study, we tried to developed a schedule analysis model for the construction of offshore wind farm considering the uncertainty of marine work according to the changing marine conditions. For this purpose, we firstly defined maritime logistics processes for the construction of offshore wind farms with respect to the situation in Korea. In fact, the maritime logistics system for the construction of offshore wind farms was a system that utilized ports as relay stations. The components of the offshore wind power system were collected in the port, semi-assembled, transported by ship, and installed at sea. Next, a mathematical model was developed based on the marine logistics process defined. In addition, since the developed mathematical model belonged to the NP-hard problem, the genetic algorithm was developed as an heuristic technique and applied to the example problem. As a result, the average installation work days per offshore wind turbine were analyzed to be 3.13∼3.29 days. If the number of offshore wind turbines to be installed was small, it was found that the submarine works were on the priority compared to the works above the water. On the other hand if the number was large, it was necessary to strategically adjust the work schedule of installing offshore wind turbines considering the maritime conditions.

Ocena ryzyka eksploatacji morskich elektrowni wiatrowych w Polsce dla potrzeb ich ubezpieczenia od wybranych zdarzeń losowych

Starting in the late 20 th century, we are seeing increased interest in obtaining energy from renewable sources. One of those sources is wind energy and its use. Increased interest in offshore wind farms in Poland is caused by the introduction of numerous restrictions on the construction of terrestrial power plants. The purpose of this article is to assess the operational risk of offshore wind farms from the point of view of their ability to be covered by insurance. The article discusses the principles of their functioning, the accompanying natural hazards as well as the general conditions of their coverage by indicating the subject of insurance, the scope of insurance and the sum insured. General conditions of operation of offshore wind farms were discussed.

Integration of Degradation Processes in a Strategic Offshore Wind Farm O&M Simulation Model

Decision support models for offshore wind farm operation and maintenance (O&M) are required to represent the failure behavior of wind turbine components. Detailed degradation modelling is already incorporated in models for specific components and applications. However, component degradation is only one of many effects that must be captured in high-level strategic decision support models that simulate entire wind farms. Thus, for practical applications, a trade-off is needed between detailed degradation modelling and the level of simplicity of input data representation. To this end, this paper discusses two alternative approaches for taking into account component degradation processes in strategic offshore wind farm O&M simulation models: (1) full integration of the degradation process in the O&M simulation model; and (2) loose integration where the degradation process is translated into simplified input to the O&M model. As a proof-of-concept, a Markov process for blade degradation has been considered. Simulations using the NOWIcob O&M model show that the difference between full and loose integration is small in terms of aggregated output parameters such as average wind turbine availability and O&M costs. Although loose integration models some effects less accurately than full integration, the former is more flexible and convenient, and the accuracy is for most purposes sufficient for such O&M models.

Exploring the wakes of large offshore wind farms

Offshore meteorological characteristics set specific conditions for the operation of offshore wind farms. One specific feature is low turbulence intensity which on the one hand reduces loads on turbines but on the other hand is the reason for much longer turbine and farm wakes than over land. The German Government is presently funding a research project called WIPAFF (Wind PArk Far Field) which heads for the analysis of properties and impacts of offshore wind park far fields. The focus is on the analysis of wind farm wakes, their interaction among each other and their regional climate impact. This is done by in-situ, extensive aircraft and satellite measurements and by operating meso-scale wind field models and an analytical wind farm model.

A parametric whole life cost model for offshore wind farms

Life cycle cost (LCC) considerations are of increasing importance to offshore wind farm operators and their insurers to undertake long-term profitable investments and to make electricity generation more price-competitive. This paper presents a cost breakdown structure (CBS) and develops a whole life cost (WLC) analysis framework for offshore wind farms throughout their life span (∼25 years). A combined multivariate regression/neural network approach is developed to identify key cost drivers and evaluate all the costs associated with five phases of offshore wind projects, namely pre-development and consenting (P&C), production and acquisition (P&A), installation and commissioning (I&C), operation and maintenance (O&M) and decommissioning and disposal (D&D). Several critical factors such as geographical location and meteorological conditions, rated power and capacity factor of wind turbines, reliability of sub-systems and availability and accessibility of transportation means are taken into account in cost calculations. The O&M costs (including the cost of renewal and replacement, cost of lost production, cost of skilled maintenance labour and logistics cost) are assessed using the data available in failure databases (e.g. fault logs and O&M reports) and the data supplied by inspection agencies. A net present value (NPV) approach is used to quantify the current value of future cash flows, and then, a bottom-up estimate of the overall cost is obtained. The proposed model is tested on an offshore 500-MW baseline wind farm project, and the results are compared to experimental ones reported in the literature. Our results indicate that the capital cost of wind turbines and their installation costs account for the largest proportion of WLC, followed by the O&M costs. A sensitivity analysis is also conducted to identify those factors having the greatest impact on levelized cost of energy (LCOE). The installed capacity of a wind farm, distance from shore and fault detection capability of the condition monitoring system are identified as parameters with significant influence on LCOE. Since the service lifetime of a wind farm is relatively long, a small change in interest rate leads to a large variation in the project’s total cost. The presented models not only assist stakeholders in evaluating the performance of ongoing projects but also help the wind farm developers reduce their costs in the medium–long term.

Sensitivity analysis of offshore wind farm operation and maintenance cost and availability

Operation and Maintenance (O&M) costs are estimated to account for 14%–30% of total Offshore Wind Farm (OWF) project lifecycle expenditure according to a range of studies. In this respect, identifying factors affecting operational costs and availability are vital for wind farm operators to achieve the most profitable decisions. Many OWFs are built in stages and the important factors may not be consistent for the different phases. To address this issue, three OWF case studies are defined to represent two phases and a complete project. An initial qualitative screening sensitivity analysis was conducted to identify the most important factors of O&M affecting operating cost and availability. The study concluded that the important factors for total O&M cost were access and repair costs along with failure rates for both minor and major repairs. For time-based availability, the important factors identified were those related to the length of time conducting the maintenance tasks, i.e. the operation duration and the working day length. It was found that the two stages had similar results, but these were different compared to the complete project. In this case, the results provide valuable information to OWF operators during the project development and decision making process.

Flexible threshold selection and fault prediction method for health monitoring of offshore wind farm

The reliable operation of offshore wind farms requires suitable real-time, automated and remote structural-health monitoring of the wind farm using wireless sensor networks (WSNs) for ensuring consistent power supply to the grid. This study presents a novel WSN packet-size reduction technique using flexible thresholds for real-time fault prediction in wind farms which is an extension to the authors work proposing application-specific network-lifetime enhancing tri-level clustering and routing protocol for increasing the network lifetime. The selection of flexible threshold utilises the degree of correlation between data samples collected at different times of the day. Using combination-summation and flow direction of received data, accurate fault prediction is achieved. The method is compared with the primitive mean method. The proposed method flexible threshold selection and fault prediction (FTSFP) provides a simple means for predicting real-time fault occurrences in the towers and helps in reducing the message size considerably, thereby increasing the network lifetime of the system nearly by ten times. The results confirm that FTSFP has better fault-prediction accuracy over the existing method.