scholarly journals A Minimalistic Prediction Model to Determine Energy Production and Costs of Offshore Wind Farms

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 448
Author(s):  
Jens Nørkær Sørensen ◽  
Gunner Christian Larsen
Keyword(s):  
Prediction Model ◽  
Wind Turbines ◽  
Water Depth ◽  
Energy Production ◽  
Wind Farm ◽  
Cost Model ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
The Cost

A numerical framework for determining the available wind power and associated costs related to the development of large-scale offshore wind farms is presented. The idea is to develop a fast and robust minimal prediction model, which with a limited number of easy accessible input variables can determine the annual energy output and associated costs for a specified offshore wind farm. The utilized approach combines an energy production model for offshore-located wind farms with an associated cost model that only demands global input parameters, such as wind turbine rotor diameter, nameplate capacity, area of the wind farm, number of turbines, water depth, and mean wind speed Weibull parameters for the site. The cost model includes expressions for the most essential wind farm cost elements—such as costs of wind turbines, support structures, cables and electrical substations, as well as costs of operation and maintenance—as function of rotor size, interspatial distance between the wind turbines, and water depth. The numbers used in the cost model are based on previous but updatable experiences from offshore wind farms, and are therefore, in general, moderately conservative. The model is validated against data from existing wind farms, and shows generally a very good agreement with actual performance and cost results for a series of well-documented wind farms.

scholarly journals Towards the North Sea wind power revolution

2018 ◽  
Author(s):  
Jens N. Sørensen ◽  
Gunner C. Larsen
Keyword(s):  
Wind Power ◽  
North Sea ◽  
Wind Turbines ◽  
Wind Farm ◽  
Cost Model ◽  
Offshore Wind ◽  
Meteorological Model ◽  
The North ◽  
The North Sea ◽  
The Cost

Abstract. The present work assesses the potential of a massive exploitation of offshore wind power in the North Sea by combining a meteorological model with a cost model that includes a bathymetric analysis of the water depth of the North Sea. The overall objective is to assess if the wind power in the North Sea can deliver the total consumption of electricity in Europe and to what prize as compared to conventional onshore wind energy. The meteorological model is based on the assumption that the exploited area is so large, that the wind field between the turbines is in equilibrium with the atmospheric boundary layer. This makes it possible to use momentum analysis to determine the mutual influence between the atmospheric boundary layer and the wind farm, with the wind farm represented by an average horizontal force component corresponding to the thrust. The cost model includes expressions for the most essential wind farm cost elements, such as costs of wind turbines, support structures, cables and electrical substations, as well as operation and maintenance as function of rotor size, interspatial distance between the turbines, and water depth. The numbers used in the cost model are based on previous experience from offshore wind farms, and is therefore somewhat conservative. The analysis shows that the lowest energy cost is obtained for a configuration of large wind turbines erected with an interspatial distance of about eight rotor diameters. A part of the analysis is devoted to assessing the relative costs of the various elements of the cost model in order to determine the components with the largest potential for reducing the cost price. As an overall finding, it is shown that the power demand of Europe, which is 0.4 TW or about 3500 TWh/year, can be fulfilled by exploiting an area of 190.000 km2, corresponding to about 1/3 of the North Sea, with 100.000 wind turbines of generator size 13 MW on water depths up to 45 m at a cost price of about 7.5 €cents/kWh.

scholarly journals A Spatial Analysis of the Potentials for Offshore Wind Farm Locations in the North Sea Region: Challenges and Opportunities

2020 ◽  
Vol 9 (2) ◽  
pp. 96 ◽  
Author(s):  
Gusatu ◽  
Yamu ◽  
Zuidema ◽  
Faaij
Keyword(s):  
Protected Areas ◽  
North Sea ◽  
Water Depth ◽  
Wind Farm ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
The North ◽  
Challenges And Opportunities ◽  
The North Sea

Over the last decade, the accelerated transition towards cleaner means of producing energy has been clearly prioritised by the European Union through large-scale planned deployment of wind farms in the North Sea. From a spatial planning perspective, this has not been a straight-forward process, due to substantial spatial conflicts with the traditional users of the sea, especially with fisheries and protected areas. In this article, we examine the availability of offshore space for wind farm deployment, from a transnational perspective, while taking into account different options for the management of the maritime area through four scenarios. We applied a mixed-method approach, combining expert knowledge and document analysis with the spatial visualisation of existing and future maritime spatial claims. Our calculations clearly indicate a low availability of suitable locations for offshore wind in the proximity of the shore and in shallow waters, even when considering its multi-use with fisheries and protected areas. However, the areas within 100 km from shore and with a water depth above –120 m attract greater opportunities for both single use (only offshore wind farms) and multi-use (mainly with fisheries), from an integrated planning perspective. On the other hand, the decrease of energy targets combined with sectoral planning result in clear limitations to suitable areas for offshore wind farms, indicating the necessity to consider areas with a water depth below –120 m and further than 100 km from shore. Therefore, despite the increased costs of maintenance and design adaptation, the multi-use of space can be a solution for more sustainable, stakeholder-engaged and cost-effective options in the energy deployment process. This paper identifies potential pathways, as well as challenges and opportunities for future offshore space management with the aim of achieving the 2050 renewable energy targets.

Analysis of Wind Turbine Capacity Factor Improvement by Correcting Yaw Error Using LIDAR

2017 ◽  
Author(s):  
Roozbeh Bakhshi ◽  
Peter Sandborn
Keyword(s):  
Energy Production ◽  
Wind Farm ◽  
Production Capacity ◽  
Wind Farms ◽  
Power Production ◽  
Capacity Factor ◽  
Offshore Wind ◽  
The Common ◽  
Turbine Capacity ◽  
The Cost

Yaw error is the angle between a turbine’s rotor central axis and the wind flow. The presence of yaw error results in lower power production from turbines. Yaw error also puts extra loads on turbine components, which in turn, lowers their reliability. In this study we develop a stochastic model to calculate the average capacity factor of a 50 turbine offshore wind farm and investigate the effects of minimizing the yaw error on the capacity factor. In this paper, we define the capacity factor in terms of energy production, which is consistent with the common practice of wind farms (rather than the power production capacity factor definition that is used in textbooks and research articles). The benefit of using the energy production is that it incorporates both the power production improvements and downtime decreases. For minimizing the yaw error, a nacelle mounted LIDAR is used. While the LIDAR is on a turbine, it collects wind speed and direction data for a period of time, which is used to calculate a correction bias for the yaw controller of the turbine, then it will be moved to another turbine in the farm to perform the same task. The results of our investigation shows that although the improvements of the capacity factor are less than the theoretical values, the extra income from the efficiency improvements is larger than the cost of the LIDAR.

Scheduling and Routing Optimization of Maintenance Fleet for Offshore Wind Farms Using Duo-ACO

2014 ◽  
Vol 1039 ◽  
pp. 294-301 ◽  
Author(s):  
Zhen You Zhang
Keyword(s):  
Wind Farm ◽  
Optimal Solution ◽  
Wind Farms ◽  
Daily Basis ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Routing Optimization ◽  
Renewable Power ◽  
Operation And Maintenance ◽  
The Cost

Wind energy is one of the fast growing sources of renewable power production currently and there is a great demand to reduce the cost of operation and maintenance to achieve competitive energy price in the market especially for offshore wind farms. An offshore wind farm usually comprises a large number of turbines and thus needs a number of service vessels for maintenance. It is already a complicated task to plan the schedule and route for each of the vessels on a daily basis, dealing with several constraints, such as weather window and maintenance demand, at the same time. Even more challenging is to find an optimal solution. This paper propose a method, i.e. Duo Ant Colony Optimization (Duo-ACO), to improve the utilization of the maintenance resources, specifically the efficient scheduling and routing of the maintenance fleet and thus reduce the operation and maintenance (O&M) cost. The proposed metaheuristic method can help operator to avoid a time-consuming process of manually planning the scheduling and routing.

scholarly journals The Relation between Migratory Activity of Pipistrellus Bats at Sea and Weather Conditions Offers Possibilities to Reduce Offshore Wind Farm Effects

Animals ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 3457
Author(s):  
Robin Brabant ◽  
Yves Laurent ◽  
Bob Jonge Poerink ◽  
Steven Degraer
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Negative Relationship ◽  
Wind Farms ◽  
Weather Conditions ◽  
Seasonal Migration ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Offshore Wind Farms ◽  
Migratory Activity

Bats undertaking seasonal migration between summer roosts and wintering areas can cross large areas of open sea. Given the known impact of onshore wind turbines on bats, concerns were raised on whether offshore wind farms pose risks to bats. Better comprehension of the phenology and weather conditions of offshore bat migration are considered as research priorities for bat conservation and provide a scientific basis for mitigating the impact of offshore wind turbines on bats. This study investigated the weather conditions linked to the migratory activity of Pipistrellus bats at multiple near- and offshore locations in the Belgian part of the North Sea. We found a positive relationship between migratory activity and ambient temperature and atmospheric pressure and a negative relationship with wind speed. The activity was highest with a wind direction between NE and SE, which may favor offshore migration towards the UK. Further, we found a clear negative relationship between the number of detections and the distance from the coast. At the nearshore survey location, the number of detections was up to 24 times higher compared to the offshore locations. Our results can support mitigation strategies to reduce offshore wind farm effects on bats and offer guidance in the siting process of new offshore wind farms.

scholarly journals Floating Offshore Vertical Axis Wind Turbines: Opportunities, Challenges and Way Forward

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8000
Author(s):  
Abel Arredondo-Galeana ◽  
Feargal Brennan
Keyword(s):  
Wind Turbines ◽  
Deep Water ◽  
Wind Farm ◽  
Structural Integrity ◽  
Wind Farms ◽  
Vertical Axis ◽  
Offshore Wind ◽  
Small Scale ◽  
Offshore Wind Farms ◽  
Vertical Axis Wind Turbines

The offshore wind sector is expanding to deep water locations through floating platforms. This poses challenges to horizontal axis wind turbines (HAWTs) due to the ever growing size of blades and floating support structures. As such, maintaining the structural integrity and reducing the levelised cost of energy (LCoE) of floating HAWTs seems increasingly difficult. An alternative to these challenges could be found in floating offshore vertical axis wind turbines (VAWTs). It is known that VAWTs have certain advantages over HAWTs, and in fact, some small-scale developers have successfully commercialised their onshore prototypes. In contrast, it remains unknown whether VAWTs can offer an advantage for deep water floating offshore wind farms. Therefore, here we present a multi-criteria review of different aspects of VAWTs to address this question. It is found that wind farm power density and reliability could be decisive factors to make VAWTs a feasible alternative for deep water floating arrays. Finally, we propose a way forward based on the findings of this review.

Modeling underwater sound from future offshore wind farms southeast of Gran Canaria Island

2021 ◽  
Author(s):  
Melania Cubas Armas ◽  
Alonso Hernández-Guerra ◽  
Eric Delory ◽  
David Dellong ◽  
Verónica Caínzos ◽  
...  
Keyword(s):  
Wind Turbines ◽  
Marine Mammals ◽  
Wind Farm ◽  
Transmission Loss ◽  
Wind Farms ◽  
Clean Energy ◽  
Offshore Wind ◽  
Acoustic Model ◽  
Offshore Wind Farms ◽  
Gran Canaria

<p>The European Union aims to achieve carbon neutrality by 2050. Therefore, it is crucial to increase the use of renewable energy. One clean energy source is the wind, and during the last decades, several countries have developed wind farms, not only on land but also in the ocean. Most offshore wind farms have been installed in shallow waters; however, recently, open ocean offshore floating wind farms are being installed in deep waters due to stronger and steadier wind occurring in these areas. Thus, offshore wind turbines are a potential new source of underwater noise. Noise can propagate underwater having the potential to affect marine mammals and fish, among others. Floating wind turbines are known to reduce the installation and decommissioning noise in contrast to fixed-bottom turbines but, nevertheless, the noise produced by the operation of the turbines and the anchoring systems have been scarcely studied, and it is still unknown whether added noise could significantly affect behavior or even hearing capacity in the long term. In the framework of the JONAS European project we anticipate a regional use case with a future installation of a commercial offshore wind farm, to determine how noise would propagate in the region, from installation to operation, and potentially impact (or not) local fauna, focusing initially on mammal groups. In this study, we use the RAM model (Range-dependent acoustic model) which is a parabolic equation (PE) code that calculates the propagation of sound in the ocean using the split-step Padé solution. RAM needs information about the temperature and salinity in the water column to calculate sound speed profiles, as well as the bathymetry and a geo-acoustic model of the bottom. It returns the transmission loss depending on the depth and distance to the source. We have applied the RAM model to an area located in the southeast of Gran Canaria Island, where a plan for a floating wind farm is under consideration. Results and suggestions about the negative impact on marine mammals known to live in this location are presented.</p>

scholarly journals Foundation Types for Land and Offshore Sustainable Wind Energy Turbine Towers

2020 ◽  
Vol 184 ◽  
pp. 01094
Author(s):  
C Lavanya ◽  
Nandyala Darga Kumar
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Wind Speeds ◽  
Deep Waters ◽  
Wind Turbine Towers

Wind energy is the renewable sources of energy and it is used to generate electricity. The wind farms can be constructed on land and offshore where higher wind speeds are prevailing. Most offshore wind farms employ fixed-foundation wind turbines in relatively shallow water. In deep waters floating wind turbines have gained popularity and are recent development. This paper discusses the various types of foundations which are in practice for use in wind turbine towers installed on land and offshore. The applicability of foundations based on depth of seabed and distance of wind farm from the shore are discussed. Also, discussed the improvement methods of weak or soft soils for the foundations of wind turbine towers.

scholarly journals An equivalent modeling method for Offshore Wind Farms based on fault characteristics analysis

2019 ◽  
Vol 107 ◽  
pp. 01004
Author(s):  
Haiyan Tang ◽  
Guanglei Li ◽  
Linan Qu ◽  
Yan Li
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Wind Farms ◽  
Modeling Method ◽  
Operating Conditions ◽  
Offshore Wind ◽  
Equivalent Model ◽  
Offshore Wind Farm ◽  
Offshore Wind Farms ◽  
Characteristics Analysis

A large offshore wind farm usually consists of dozens or even hundreds of wind turbines. Due to the limitation of the simulation scale, it is necessary to develop an equivalent model of offshore wind farms for power system studies. At present, the aggregation method is widely adopted for wind farm equivalent modeling. In this paper, the topology, electrical parameters, operating conditions and individual turbine characteristics of the offshore wind farms are taken into consideration. Firstly, the output power distribution of offshore wind farm, the voltage distribution of the collector system and the fault ride-through characteristics of wind turbines are analyzed. Then, a dynamic equivalent modeling method for offshore wind farms is developed based on the fault characteristics analysis. Finally, the proposed method is validated through time-domain simulation.

scholarly journals An analysis of offshore wind farm SCADA measurements to identify key parameters influencing the magnitude of wake effects

2017 ◽  
Vol 2 (2) ◽  
pp. 477-490 ◽  
Author(s):  
Niko Mittelmeier ◽  
Julian Allin ◽  
Tomas Blodau ◽  
Davide Trabucchi ◽  
Gerald Steinfeld ◽  
...  
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Average Power ◽  
Atmospheric Stability ◽  
Wind Farms ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Offshore Wind Farms ◽  
Partial Load ◽  
Wake Effects

Abstract. For offshore wind farms, wake effects are among the largest sources of losses in energy production. At the same time, wake modelling is still associated with very high uncertainties. Therefore current research focusses on improving wake model predictions. It is known that atmospheric conditions, especially atmospheric stability, crucially influence the magnitude of those wake effects. The classification of atmospheric stability is usually based on measurements from met masts, buoys or lidar (light detection and ranging). In offshore conditions these measurements are expensive and scarce. However, every wind farm permanently produces SCADA (supervisory control and data acquisition) measurements. The objective of this study is to establish a classification for the magnitude of wake effects based on SCADA data. This delivers a basis to fit engineering wake models better to the ambient conditions in an offshore wind farm. The method is established with data from two offshore wind farms which each have a met mast nearby. A correlation is established between the stability classification from the met mast and signals within the SCADA data from the wind farm. The significance of these new signals on power production is demonstrated with data from two wind farms with met mast and long-range lidar measurements. Additionally, the method is validated with data from another wind farm without a met mast. The proposed signal consists of a good correlation between the standard deviation of active power divided by the average power of wind turbines in free flow with the ambient turbulence intensity (TI) when the wind turbines were operating in partial load. It allows us to distinguish between conditions with different magnitudes of wake effects. The proposed signal is very sensitive to increased turbulence induced by neighbouring turbines and wind farms, even at a distance of more than 38 rotor diameters.

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