A Review of Methodological Approaches for the Design and Optimization of Wind Farms

This article presents a review of the state of the art of the Wind Farm Design and Optimization (WFDO) problem. The WFDO problem refers to a set of advanced planning actions needed to extremize the performance of wind farms, which may be composed of a few individual Wind Turbines (WTs) up to thousands of WTs. The WFDO problem has been investigated in different scenarios, with substantial differences in main objectives, modelling assumptions, constraints, and numerical solution methods. The aim of this paper is: (1) to present an exhaustive survey of the literature covering the full span of the subject, an analysis of the state-of-the-art models describing the performance of wind farms as well as its extensions, and the numerical approaches used to solve the problem; (2) to provide an overview of the available knowledge and recent progress in the application of such strategies to real onshore and offshore wind farms; and (3) to propose a comprehensive agenda for future research

Technical-economic analysis, modeling and optimization of floating offshore wind farms

The offshore wind sector has grown significantly during the last decades driven by the increasing demand for clean energy and to reach defined energy targets based on renewable energies. As the wind speeds tend to be faster and steadier offshore, wind farms at sea can reach higher capacity factors compared to their onshore counterparts. Furthermore, fewer restrictions regarding land use, visual impact, and noise favors the application of this technology. However, most of today's offshore wind farms use bottom-fixed foundations that limit their feasible application to shallow water depths. Floating substructures for offshore wind turbines are a suitable solution to harness the full potential of offshore wind as they have less constraints to water depths and soil conditions and can be applied from shallow to deep waters. As several floating offshore wind turbine (FOWT) concepts have been successfully tested in wave tanks and prototypes have been proven in open seas, floating offshore wind is now moving towards the commercial phase with the first floating offshore wind farm (FOWF) commissioned in 2017 and several more are projected to be constructed in 2020. This transition increases the need for comprehensive tools that allow to model the complete system and to predict its behavior as well as to assess the performance for different locations. The aim of this thesis is to analyze from a technical and economic perspective commercial scale FOWFs. This includes the modeling of FOWTs and the study of their dynamic behavior as well as the economic assessment of different FOWT concepts. The optimization of the electrical layout is also addressed in this thesis. The first model developed is applied to analyze the performance of a Spar type FOWT. The model is tested with different load cases and compared to a reference model. The results of both models show an overall good agreement. Afterwards, the developed model is applied to study the behavior of the FOWT with respect to three different offshore sites. Even at the site with the harshest conditions and largest motions, no significant loss in energy generation is measured, which demonstrates the good performance of this concept. The second model is used to perform a technical-economic assessment of commercial scale FOWFs. It includes a comprehensive LCOE methodology based on a life cycle cost estimation as well as the computation of the energy yield. The model is applied to three FOWT concepts located at three different sites and considering a 500MW wind farm configuration. The findings indicate that FOWTs are a high competitive solution and energy can be produced at an equal or lower LCOE compared to bottom-fixed offshore wind or ocean energy technologies. Furthermore, a sensitivity analysis is performed to identify the key parameters that have a significant influence on the LCOE and which can be essential for further cost reductions. The last model is aimed to optimize the electrical layout of FOWFs based on the particle swarm optimization theory. The model is validated against a reference model at first and is then used to optimize the inter-array cable routing of a 500MW FOWF. The obtained electrical layout results in a reduction of the power cable costs and a decrease of the energy losses. Finally, the use of different power cable configurations is studied and it is shown that the use of solely dynamic power cables in comparison to combined dynamic and static cables results in decreased acquisition and installation costs due to the avoidance of cost-intensive submarine joints and additional installation activities.El sector eólico marino ha crecido significativamente durante las últimas décadas impulsado por la creciente demanda de energía limpia. Los parques eólicos en el mar pueden alcanzar factores de capacidad más altos en comparación a los parques eólicos en la tierra debido a que las velocidades del viento tienden a ser más altas y constantes en el mar. Ademas, existen menos restricciones con respecto al uso de la tierra, el impacto visual y el ruido. Sin embargo, la mayoría de los parques eólicos actuales utilizan subestructuras fijas que limitan su aplicación factible a aguas poco profundas. Las subestructuras flotantes para turbinas eólicas marinas (FOWTs en inglés) son una solución adecuada para aprovechar todo el potencial de la energía eólica, ya que tienen menos restricciones para las profundidades del agua y el fondo marino. Dado que varios prototipos de FOWTs se han probado con éxito en el mar, la industria ahora esta entrando a la fase comercial con el primer parque eólico flotante (FOWF en inglés) operativo y se proyecta que se pondrán en marcha más en los próximos anos. Esta transición aumenta la necesidad de herramientas integrales que permitan modelar el sistema completo y predecir su comportamiento, así como evaluar el rendimiento para diferentes lugares. El objetivo de esta tesis es analizar desde una perspectiva técnica y económica los FOWFs a escala comercial. Esto incluye el modelado de FOWTs, el estudio de su comportamiento dinámico, y la evaluación económica de diferentes conceptos. La optimización del diseño eléctrico también se aborda en esta tesis. El primer modelo desarrollado se aplica para analizar el rendimiento de un FOWT tipo Spar. El modelo se prueba con diferentes tipos de carga y se compara con un modelo de referencia. Los resultados de ambos modelos muestran una buena concordancia. Posteriormente, el modelo se aplica para estudiar el comportamiento con respecto a tres lugares diferentes. Los resultados muestran que incluso en el sitio con las condiciones más severas, no se mide ninguna pérdida significativa en la generación de energía, lo que demuestra el buen rendimiento de este concepto. El segundo modelo se utiliza para realizar una evaluación técnico-económica de los FOWF a escala comercial. Esto incluye una metodología integral del costo nivelado de energía (LCOE en ingles). El modelo se aplica a tres conceptos de FOWTs ubicados en tres lugares diferentes y considerando un parque eólico de 500MW. Los resultados indican que los FOWTs son una solución altamente competitiva y que la energía se puede producir con un LCOE igual o inferior en comparación con los parques eólicos con subestructuras fijas o las tecnologías de energía oceánica. Asimismo, se realiza un análisis de sensibilidad para identificar los parámetros claves que tienen una influencia significativa en el LCOE y que pueden ser esenciales para reducciones de costos. El último modelo se aplica para optimizar el diseño eléctrico en función de la teoría de optimización por enjambre de partículas. Inicialmente el modelo se valida contra un modelo de referencia y luego se utiliza para optimizar la conexión de los cables entre los FOWTs. El diseño eléctrico obtenido da como resultado una reducción de los costos de cables y una disminución de las pérdidas de energía. Finalmente, se estudia el uso de diferentes configuraciones de cables y se demuestra que el uso de cables únicamente dinámicos en comparación con los cables dinámicos y estáticos combinados da como resultado una disminución de los costos de adquisición e instalación debido a que evitan la necesidad de juntas submarinas costosas y costos adicionales de instalación.Postprint (published version

Collection grid optimization of a floating offshore wind farm using particle swarm theory

Floating substructures for offshore wind turbines is a promising solution in order to harness the vast wind potential of deep water sites where bottom-fixed turbines are not feasible. The electrical system of large scale floating offshore wind farms will experience the application of new technologies and installation procedures that likely affect the cost-competitiveness. Thus, in this work, an optimization model based on the particle swarm theory is presented that allows optimizing the collection grid of a floating offshore wind farm. The developed model is applied to a study case consisting of a 500MW floating offshore wind farm located at the Golfe de Fos in the Mediterranean Sea. The resulting layout allows to reduce the total cost of the collection grid by more than 6% and to decrease the energy losses by 8% compared to the actual layout. Besides this, a further study analyzes the effect of a quantity discount with a reduced number of power cable cross sections.Postprint (published version

State of the Art in the Optimisation of Wind Turbine Performance Using CFD

Wind energy has received increasing attention in recent years due to its sustainability and geographically wide availability. The efficiency of wind energy utilisation highly depends on the performance of wind turbines, which convert the kinetic energy in wind into electrical energy. In order to optimise wind turbine performance and reduce the cost of next-generation wind turbines, it is crucial to have a view of the state of the art in the key aspects on the performance optimisation of wind turbines using Computational Fluid Dynamics (CFD), which has attracted enormous interest in the development of next-generation wind turbines in recent years. This paper presents a comprehensive review of the state-of-the-art progress on optimisation of wind turbine performance using CFD, reviewing the objective functions to judge the performance of wind turbine, CFD approaches applied in the simulation of wind turbines and optimisation algorithms for wind turbine performance. This paper has been written for both researchers new to this research area by summarising underlying theory whilst presenting a comprehensive review on the up-to-date studies, and experts in the field of study by collecting a comprehensive list of related references where the details of computational methods that have been employed lately can be obtained

Optimized Placement of Onshore Wind Farms Considering Topography

As the scale of onshore wind farms are increasing, the influence of wake behavior on power production becomes increasingly significant. Wind turbines sittings in onshore wind farms should take terrain into consideration including height change and slope curvature. However, optimized wind turbine (WT) placement for onshore wind farms considering both topographic amplitude and wake interaction is realistic. In this paper, an approach for optimized placement of onshore wind farms considering the topography as well as the wake effect is proposed. Based on minimizing the levelized production cost (LPC), the placement of WTs was optimized considering topography and the effect of this on WTs interactions. The results indicated that the proposed method was effective for finding the optimized layout for uneven onshore wind farms. The optimization method is applicable for optimized placement of onshore wind farms and can be extended to different topographic conditions

Application of an offshore wind farm layout optimization methodology at Middelgrunden wind farm

This is the author accepted manuscript. The final version is freely available from Elsevier via the DOI in this record.This article explores the application of a wind farm layout evaluation function and layout optimization framework to Middelgrunden wind farm in Denmark. This framework has been built considering the interests of wind farm developers in order to aid in the planning of future offshore wind farms using the UK Round 3 wind farms as a point of reference to calibrate the model. The present work applies the developed evaluation tool to estimate the cost, energy production, and the levelized cost of energy for the existing as-built layout at Middelgrunden wind farm; comparing these against the cost and energy production reported by the wind farm operator. From here, new layouts have then been designed using either a genetic algorithm or a particle swarm optimizer. This study has found that both optimization algorithms are capable of identifying layouts with reduced levelized cost of energy compared to the existing layout while still considering the specific conditions and constraints at this site and those typical of future projects. Reductions in levelized cost of energy such as this can result in significant savings over the lifetime of the project thereby highlighting the need for including new advanced methods to wind farm layout design.This work is funded in part by the Energy Technologies Institute (ETI) 699 and RCUK energy program for IDCORE (EP/J500847/1)

Optimal capacity density of offshore wind farms : An analysis for the prospective wind energy projects in the North Sea

The North Sea and Norwegian continental shelf have been identified to possess some of the world's best wind resources. Nine countries, including Norway, have signed the Ostend Declaration and established their offshore wind development targets for 2050. However, space constraints, current consumption, siting regulations, and spatial planning risks accentuate the need for finding an optimum design parameter, i.e., capacity density (MW/km2) for offshore wind farms. A thorough understanding of this optimization problem seems to be missing in the offshore wind energy industry including leading offshore wind developers. Achieving an optimal capacity density involves a collaborative effort while also considering the potential economic and environmental benefits of the project. This master’s thesis aims to create guidelines and identify the levers that drive the optimal capacity density of an offshore wind farm in the North Sea by assessing wind characteristics, evaluating net annual energy production, computing economic indices, and performing sensitivity analysis. The work emphasizes better understanding of the input and output parameter sensitivities pertaining to techno-economic factors under eleven different scenarios using PyWake simulation and cross-linking the simulation results to create a sensitivity analysis tool for economic indices. The focus is on in-depth study to document the procedure involved in identifying the optimal windfarm capacity density and not simply objectifying the results based on the most accurate wake model. The study found that different offshore wind developers may reach different optimum capacity densities depending on their assumptions, methodologies and technologies used for estimation and reporting the financial metrics. For example, the study shows that the choice of wake model can lead to a significantly different optimum capacity density between 4.76 and 9.10 MW/km2 with the motive to maximize profit using a conservative and optimistic approach. Moreover, some developers may have more advanced or sophisticated methods for wind farm simulation and power production estimation, leading to more accurate and precise capacity density estimates. Based on a comprehensive analysis of various parameters and their impact on sensitivity, the optimal capacity density is anticipated to lie between 3.62 and 6.05 MW/km2 for a typical wind farm located in the North Sea. In some extreme cases where wind resources are scarce or strike prices are below levelized energy cost, the optimal capacity density could be as low as 2.64 MW/km2

Offshore wind farm layouts designer software's

Offshore wind energy can be considered one of the renewable energy sources with high force potential installed in marine areas. Consequently, the best wind farm layouts identified for constructing combined offshore renewable energy farms are crucial. To this aim, offshore wind potential analysis is essential to highlight the best offshore wind layouts for farm installation and development. Furthermore, the offshore wind farm layouts must be designed and developed based on the offshore wind accurate assessment to identify previously untapped marine regions. In this case, the wind speed distribution and correlation, wind direction, gust speed and gust direction for three sites have been analyzed, and then two offshore wind farm layout scenarios have been designed and analyzed based on two offshore wind turbine types in the Northwest Persian Gulf. In this case, offshore wind farm layouts software and tools have been reviewed as ubiquitous software tools. The results show Beacon M28 and Sea Island buoys location that the highest correlation between wind and gust speeds is between 87% and 98% in Beacon M28 and Sea Island Buoy, respectively. Considerably, the correlation between wind direction and wind speed is negligible. The Maximum likelihood algorithm, the WAsP algorithm, and the Least Squares algorithm have been used to analyze the wind energy potential in offshore buoy locations of the Northwest Persian Gulf. In addition, the wind energy generation potential has been evaluated in different case studies. For example, the Umm Al-Maradim buoy area has excellent potential for offshore wind energy generation based on the Maximum likelihood algorithm, WAsP algorithm, and Least Squares algorithm