Offshore wind farm electrical design: a review

Wind energy will be indispensable as Europe advances towards a low carbon energy future. Offshore locations in the North and Baltic seas are expected to host large arrays of wind farms that plan to export formidable amounts of electricity to the continent. The design of such plants is an intricate task where the electrical layout plays a crucial role. This complexity calls for the use of advanced optimization tools to support investment and operation decisions. This paper reviews the main approaches already developed in the literature and discusses their implications. Copyright © 2012 John Wiley & Sons, Ltd.     

Reliability-based topology optimization for offshore wind farm collection system

An optimization framework for global optimization of the cable layout topology for offshore wind farm (OWF) is presented. The framework designs and compares closed-loop and radial layouts for the collection system of OWFs. For the former, a two-stage stochastic optimization program based on a mixed integer linear programming (MILP) model is developed, while for the latter, a hop-indexed full binary model is used. The purpose of the framework is to provide a common base for assessing both designs economically, using the same underlying contingency treatment. A discrete Markov model is implemented for calculating the cable failure probability, useful for estimating the time under contingency for multiple power generation scenarios. The objective function supports simultaneous optimization of (i) initial investment (network topology and cable sizing), (ii) total electrical power loss costs and (iii) operation costs due to energy curtailment from cable failures. Constraints are added accounting for common engineering aspects. The applicability of the full method is demonstrated by tackling three differently sized real-world OWFs. Results show that (i) the profitability of either topology type depends strongly on the project size and wind turbine rating. Closed loop may be a competitive solution for large-scale projects where large amounts of energy are potentially curtailed. (ii) The stochastic model presents low tractability to tackle large-scale instances, increasing the required computing time and memory resources. (iii) Strategies must be adopted in order to apply stochastic optimization for modern OWFs, intending analytically or numerically simplification of mathematical models.     

Integrated offshore wind farm design: Optimizing micro‐siting and cable layout simultaneously

Electrical layout and turbine placement are key design decisions in offshore wind farm projects. Increased turbine spacing minimizes the energy losses caused by wake interactions between turbines but requires costlier cables with higher rates of failure. Simultaneous micro‐siting and electrical layout optimization are required to realize all possible savings. The problem is complex, because electrical layout optimization is a combinatorial problem and the computational fluid‐dynamics calculations to approximate wake effects are impossible to integrate into classical optimization. This means that state‐of‐the‐art methods do not generally consider simultaneous optimization and resort to approximations instead. We extend an existing model that successfully optimizes cable design to simultaneously consider micro‐siting. We use Jensen's equations to approximate the wake effect in an efficient manner, calibrating it with years of mast data. The wake effects are precalculated and introduced into the optimization problem. We solve simultaneously for turbine spacing and cable layout, exploiting the tradeoffs between these wind farm features. We use the Barrow Offshore Wind Farm as a case study to demonstrate realizable savings up to 6 MEUR over the lifetime of the plant, although it is possible that unforeseen design constraints have implications for whether the savings seen in our model are fully realizable in the real world. In addition, the model provides insights on the effects of turbine spacing that can be used to simplify the design process or to support negotiations for surface concession at the earlier stages of a project.     

Variable‐sized wind turbines are a possibility for wind farm optimization

The potential benefits associated with harnessing available momentum and reducing turbulence levels in a wind farm composed of wind turbines of alternating size are investigated through wind tunnel experiments. A variable size turbine array composed of 3 by 8 model wind turbines is placed in a boundary layer flow developed over both a smooth and rough surfaces under neutrally stratified thermal conditions. Cross‐wire anemometry is used to capture high resolution and simultaneous measurements of the streamwise and vertical velocity components at various locations along the central plane of the wind farm. A laser tachometer is employed to obtain the instantaneous angular velocity of various turbines. The results suggest that wind turbine size heterogeneity in a wind farm introduces distinctive flow interactions not possible in its homogeneous counterpart. In particular, reduced levels of turbulence around the wind turbine rotors may have positive effects on turbulent loading. The turbines also appear to perform quite uniformly along the entire wind farm, whereas surface roughness impacts the velocity recovery and the spectral content of the turbulent flow within the wind farm. Copyright © 2013 John Wiley & Sons, Ltd.     

TOPFARM: Multi‐fidelity optimization of wind farms

A wind farm layout optimization framework based on a multi‐fidelity optimization approach is applied to the offshore test case of Middelgrunden, Denmark as well as to the onshore test case of Stag Holt – Coldham wind farm, UK. While aesthetic considerations have heavily influenced the famous curved design of the Middelgrunden wind farm, this work focuses on demonstrating a method that optimizes the profit of wind farms over their lifetime based on a balance of the energy production income, the electrical grid costs, the foundations cost, and the cost of wake turbulence induced fatigue degradation of different wind turbine components. A multi‐fidelity concept is adapted, which uses cost function models of increasing complexity (and decreasing speed) to accelerate the convergence to an optimum solution. In the EU‐FP6 TOPFARM project, three levels of complexity are considered. The first level uses a simple stationary wind farm wake model to estimate the Annual Energy Production (AEP), a foundations cost model depending on the water depth and an electrical grid cost function dictated by cable length. The second level calculates the AEP and adds a wake‐induced fatigue degradation cost function on the basis of the interpolation in a database of simulations performed for various wind speeds and wake setups with the aero‐elastic code HAWC2 and the dynamic wake meandering model. The third level, not considered in this present paper, includes directly the HAWC2 and the dynamic wake meandering model in the optimization loop in order to estimate both the fatigue costs and the AEP. The novelty of this work is the implementation of the multi‐fidelity approach in the context of wind farm optimization, the inclusion of the fatigue degradation costs in the optimization framework, and its application on the optimal performance as seen through an economical perspective. Copyright © 2013 John Wiley & Sons, Ltd.     

Survey of wind farm control—power and fatigue optimization

The main goal of this paper is to establish the present state of the art for wind farm control. The control area that will be focused on is the mechanical/aerodynamic part, which includes the wind turbines, their power production, fatigue and wakes affecting neighbouring wind turbines. The sub‐objectives in this area of research are as follows: (i) maximizing the total wind farm power production; (ii) following a reference for the total wind farm active power; and (iii) doing this in a manner that minimizes fatigue loading for the wind turbines in the farm. Each of these sub‐objectives is discussed, including the following important control issues: choice of input and output, control method and modelling used for controller design and simulation. The available literature from industry is also considered. Finally, a conclusion is presented discussing the established results, open challenges and necessary research. Copyright © 2014 John Wiley & Sons, Ltd.     

Resonant overvoltage assessment in offshore wind farms via a parametric black‐box wind turbine transformer model

The protection of offshore wind farms (OWFs) against overvoltages, especially resonant overvoltage, is of paramount importance because of poor accessibility and high repair costs. In this paper, we study how switching overvoltages at the wind turbine transformer (WTT) medium voltage (MV) side can lead to high overvoltages on the low voltage (LV) side. The effect of overvoltage protective devices is analyzed. A detailed model of an OWF row is developed in electromagnetic transients program–alternative transients program (EMTP‐ATP), including interconnecting cables, WTT, surge arresters and resistive–capacitive filters. A parameterized black‐box WTT model is obtained from measurements and is used for investigating the transfer of resonant overvoltages from the MV to the LV side. The model is capable of shifting systematically the frequencies and adjusting the transformer input impedance. Simulation results show that wind turbine energization in an OWF can lead to overvoltages on the LV terminals. The rate of rise of overvoltages (du/dt) is in the range of 300–500 pu/µs. It is found that resistive–capacitive filters should be installed on both MV and LV terminals of WTTs to decrease both resonant overvoltages and du/dt, which is unachievable by surge arrester alone. Copyright © 2014 John Wiley & Sons, Ltd.     

Large‐eddy simulations of the Lillgrund wind farm

The power production of the Lillgrund wind farm is determined numerically using large‐eddy simulations and compared with measurements. In order to simulate realistic atmospheric conditions, pre‐generated turbulence and wind shear are imposed in the computational domain. The atmospheric conditions are determined from data extracted from a met mast, which was erected prior to the establishment of the farm. In order to allocate most of the computational power to the simulations of the wake flow, the turbines are modeled using an actuator disc method where the discs are imposed in the computational domain as body forces which for every time step are calculated from tabulated airfoil data. A study of the influence of imposed upstream ambient turbulence is performed and shows that higher levels of turbulence results in slightly increased total power production and that it is of great importance to include ambient turbulence in the simulations. By introducing ambient atmospheric turbulence, the simulations compare very well with measurements at the studied inflow angles. A final study aiming at increasing the farm production by curtailing the power output of the front row turbines and thus letting more kinetic energy pass downstream is performed. The results, however, show that manipulating only the front row turbines has no positive effect on the farm production, and therefore, more complex curtailment strategies are needed to be tested. Copyright © 2014 John Wiley & Sons, Ltd.     

基于CFO的海上风电场微观选址优化算法研究

海上风电场用海面积有限,尾流影响比陆上大,微观选址是其规划设计的关键技术。传统优化算法大多采用离散化变量,使得潜在解空间减少到有限个,难以达到最优化的效果。为了提高海上风电场微观选址优化效率,文章提出了一种基于中心引力优化(CFO)算法的海上风电场微观选址方法。该算法使用实数编码,通过将微观选址优化的变量假设为天体,各个天体之间相互作用,达到平衡的原理,具有可能得到全局最优解和效率高的优点。使用该算法对海上风电场微观选址优化进行仿真,并与现有方法比较。结果表明,所提出的算法得到的排布方式发电量最高,并具有优化精度高、速度快和优化排布较为均匀的特点。该研究结果可以为实际工程应用提供参考。     

Technoeconomic study for the optimization of turbine size and wind farm layouts

A technoeconomic analysis and optimization of wind turbine size and layout are performed using WAsP software. A case study of a 100‐MW wind farm located in Egypt is considered. Wind atlas for Egypt was used as the input data of the WAsP software. Two turbine models of powers 52 and 80 MW are considered for this project. The wind turbine size and distributions are selected based on the technoeconomic optimization, namely minimum wake effect, maximum annual energy production (AEP) rate, optimum cash flow, and payback period. The future worth method is adopted in economic comparison between the two alternatives, and the cash flow diagram provided the payback period and future worth after the lifetime of the plant. The results showed that (1) the AEP dramatically decreases for a wind farm area less than 15 km²; (2) the turbine spacing, spacing‐to‐diameter ratio, and the setback distances decrease and the wind turbine density and wake losses increase with decreasing the wind turbines size; (3) the total net AEP using G52 is lower than that of using G80 by about 16%; (4) the technoeconomic analysis recommended using G80 as it has higher profit than those of G52 by about $20 million.     

Investigating the possibility of using different hub height wind turbines in a wind farm

Many researchers have focused on the layout design of a wind farm using the computational methods. Most of previous researches focused on relevant large cell size and using same hub height wind turbines. In this paper, the authors investigate the possibility of using different hub height wind turbines in a wind farm. A limited area (2?km?×?2?km) with constant wind speed and direction is considered as the potential wind farm area, and a nested genetic algorithm is used as optimisation algorithm. Two different hub height wind turbines are introduced with two different cell sizes. Power output, cost, payback period, and total profit are selected as evaluation criteria when comparing the layouts with same hub height wind turbines with the layouts with different hub height wind turbines. The results demonstrate that it is feasible and possible to use different hub height wind turbines in a wind farm.     

Offshore wind speed estimates from a high‐resolution rapidly updating numerical weather prediction model forecast dataset

In association with the Department of Energy–funded Position of Offshore Wind Energy Resources (POWER) project, we present results from compositing a 3‐year dataset of 80‐m (above ground level) wind forecasts from the 3‐km High‐Resolution Rapid Refresh (HRRR) model over offshore regions for the contiguous United States. The HRRR numerical weather prediction system runs once an hour and features hourly data assimilation, providing a key advantage over previous model‐based offshore wind datasets. On the basis of 1‐hour forecasts from the HRRR model, we highlight the different climatological regimes of the nearshore environment, characterizing the mean 80‐m wind speed as well as the frequency of exceeding 4, 12, and 25 m s^?1 for east and west coast, Gulf of Mexico, and Great Lake locations. Preliminary verification against buoy measurements demonstrates good agreement with observations. This dataset can inform the placement of targeted measurement systems in support of improving resource assessments and wind forecasts to advance offshore wind energy goals both in New England and other coastal regions of the United States.     

Optimum design of transmissions systems for offshore wind farms including decision making under risk

The power transmission system of an offshore wind farm constitutes the infrastructure that allows the electricity produced by the power plant to be injected into the onshore power transmission network. The design of this transmission system depends on numerous factors: the rated power of the wind farm, wind conditions at the location, the distance from the shore, the cost of electrical equipment, the price of energy, the maintenance costs, the failure rate of the equipment, and so forth. At the design stage, most of these factors remain defined with a degree of uncertainty that, in many cases, may lead to major deviations (risk) with respect to the planned economic performance of the facility. The objective for the project team of the transmission system is the determination of the most suitable configuration of the evacuation infrastructure by selecting the technology, either HVAC or HVDC, and by sizing the electrical equipment: the cables, substations or converter stations, compensation units, among other pieces. To this end, the approach developed in this work includes the assessment of a broad range of feasible scenarios (probabilistic approach) and then the selection of the optimal configuration based on a method of decision-making, taking into account the main technical and economic aspects of the infrastructure.     

Design and analysis of an aging‐aware energy management system for islanded grids using mixed‐integer quadratic programming

The rapid increase of renewable energy sources made coordinated control of the distributed and intermittent generation units a more demanded task. Matching demand and supply is particularly challenging in islanded microgrids. In this study, we have demonstrated a mixed‐integer quadratic programming (MIQP) method to achieve efficient use of sources within an islanded microgrid. A unique objective function involving fuel consumption of diesel generator, degradation in a lithium‐ion battery energy storage system, carbon emissions, load shifting, and curtailment of the renewable sources is constructed, and an optimal operating point is pursued using the MIQP approach. A systematic and extensive methodology for building the objective function is given in a sequential and explicit manner with an emphasis on a novel model‐based battery aging formulation. Performance of the designed system and a sensitivity analysis of resulting battery dispatch, diesel generator usage, and storage aging against a range of optimization parameters are presented by considering real‐world specifications of the Semakau Island, an island in the vicinity of Singapore.     

Forecasting aggregated wind power production of multiple wind farms using hybrid wavelet‐PSO‐NNs

This paper describes the problem of short‐term wind power production forecasting based on meteorological information. Aggregated wind power forecasts are produced for multiple wind farms using a hybrid intelligent algorithm that uses a data filtering technique based on wavelet transform (WT) and a soft computing model (SCM) based on neural network (NN), which is optimized by using particle swarm optimization (PSO) algorithm. To demonstrate the effectiveness of the proposed hybrid intelligent WT + NNPSO model, which takes into account the interactions of wind power, wind speed, wind direction, and temperature in the forecast process, the real data of wind farms located in the southern Alberta, Canada, are used to train and test the proposed model. The test results produced by the proposed hybrid WT + NNPSO model are compared with other SCMs as well as the benchmark persistence method. Simulation results demonstrate that the proposed technique is capable of performing effectively with the variability and intermittency of wind power generation series in order to produce accurate wind power forecasts. Copyright © 2014 John Wiley & Sons, Ltd.     

Aero‐structural design optimization of vertical axis wind turbines

In the last decade, vertical axis wind turbines acquired notable interest in the renewable energy field. Different techniques are available to perform aerodynamic and structural simulation of these complex machines, but, to the authors' best knowledge, a comprehensive approach, which includes an automatic optimization algorithm, has never been developed. In this work, a methodology to conduct an efficient aero‐structural design of Darrieus vertical axis wind turbine is presented. This relies on a code‐to‐measurement validated simulation tool based on Blade Element‐Momentum algorithm adopting a particular set of aerodynamic coefficients, and a code‐to‐code validated structural model based on the Euler–Bernoulli beam theory. The algorithms are coupled with a Genetic Algorithm to perform the optimization. The adopted decisional parameters allow to completely vary the blade shape and the airfoil geometry to reduce the structural stress and improve the aerodynamic performance. Different individuals are explored to perform a wide aerodynamic and structural analysis of improved configurations. Copyright © 2016 John Wiley & Sons, Ltd.     

Optimization‐based power management of a wind farm with battery storage

This paper presents an optimization‐based control strategy for the power management of a wind farm with battery storage. The strategy seeks to minimize the error between the power delivered by the wind farm with battery storage and the power demand from an operator. In addition, the strategy attempts to maximize battery life. The control strategy has two main stages. The first stage produces a family of control solutions that minimize the power error subject to the battery constraints over an optimization horizon. These solutions are parameterized by a given value for the state of charge at the end of the optimization horizon. The second stage screens the family of control solutions to select one attaining an optimal balance between power error and battery life. The battery life model used in this stage is a weighted Amp‐hour throughput model. The control strategy is modular, allowing for more sophisticated optimization models in the first stage or more elaborate battery life models in the second stage. The strategy is implemented in real time in the framework of model predictive control. Copyright © 2012 John Wiley & Sons, Ltd.     

Coordinated control of series‐connected offshore wind park based on matrix converters

Optimization and reliability are two important aspects in design and operation of wind parks either for offshore as for onland emplacements. However, offshore locations demand conscientious effort in optimizing the size and the weight of each component in the energy conversion system because of the high investment and maintenance costs related with the supporting structures and transportation respectively. Achieving these two objectives requires the combination of different optimization stages, which consider a suitable design of the entire conversion system with innovative and more e?cient power electronic devices, optimized topology of the offshore grid and customized control strategies for optimizing the operation of the park. This paper presents an energy conversion concept for wind turbines on the basis of a reduced matrix converter (RMC) that will enable series direct current architecture in offshore wind parks thus preventing the need for offshore platforms. The RMC is built with bidirectional semiconductors that give reduced losses because of both superior topology and more e?cient semiconductors. The proposed conversion topology is tested in stationary state and transient operation. In addition to operational features of the concept, control and operation of a wind park with several turbines are presented. Dynamic operation of the turbine as well as the high‐voltage direct current transmission line effects are considered. Three types of models are therefore developed. First, an accurate and detailed model for analyzing one single turbine with the converter operated at high‐frequency switching is presented. This model considers a new modulation for the RMC. A second and simpli?ed model is used for small signal analysis. This model permits to simulate several series‐connected cluster during transient. Finally, an optimal direct current load ?ow model is used for evaluating stationary state operation. Results show the technical feasibility of the proposed concept and their advantages over conventional topologies. The paper also discusses the technological challenges that this type of offshore grid architecture will bring. Copyright © 2011 John Wiley & Sons, Ltd.     

Modeling turbine wakes and power losses within a wind farm using LES: An application to the Horns Rev offshore wind farm

A modeling framework is proposed and validated to simulate turbine wakes and associated power losses in wind farms. It combines the large-eddy simulation (LES) technique with blade element theory and a turbine-model-specific relationship between shaft torque and rotational speed. In the LES, the turbulent subgrid-scale stresses are parameterized with a tuning-free Lagrangian scale-dependent dynamic model. The turbine-induced forces and turbine-generated power are modeled using a recently developed actuator-disk model with rotation (ADM-R), which adopts blade element theory to calculate the lift and drag forces (that produce thrust, rotor shaft torque and power) based on the local simulated flow and the blade characteristics. In order to predict simultaneously the turbine angular velocity and the turbine-induced forces (and thus the power output), a new iterative dynamic procedure is developed to couple the ADM-R turbine model with a relationship between shaft torque and rotational speed. This relationship, which is unique for a given turbine model and independent of the inflow condition, is derived from simulations of a stand-alone wind turbine in conditions for which the thrust coefficient can be validated. Comparison with observed power data from the Horns Rev wind farm shows that better power predictions are obtained with the dynamic ADM-R than with the standard ADM, which assumes a uniform thrust distribution and ignores the torque effect on the turbine wakes and rotor power. The results are also compared with the power predictions obtained using two commercial wind-farm design tools (WindSim and WAsP). These models are found to underestimate the power output compared with the results from the proposed LES framework.     

Wind hybrid electrical supply system: behaviour simulation and sizing optimization

Using a global approach, a wind hybrid system operation is simulated and the evolution of several parameters is analysed, such as the wasted energy, the fuel consumption and the role of the wind turbine subsystem in the global production. This analysis shows that all the energies which take part in the system operation are more dependent on the wind turbine size than on the battery storage capacity. A storage of 2 or 3 days is sufficient, because an increase in storage beyond these values does not have a notable impact on the performance of the wind hybrid system. Finally, a cost study is performed to determine the optimal configuration of the system conducive to the lowest cost of electricity production. Copyright © 2001 John Wiley & Sons, Ltd.