Offshore Wind Energy Resources Research Articles

The POWER Experiment: Impact of Assimilation of a Network of Coastal Wind Profiling Radars on Simulating Offshore Winds in and above the Wind Turbine Layer

AbstractDuring the summer of 2004 a network of 11 wind profiling radars (WPRs) was deployed in New England as part of the New England Air Quality Study (NEAQS). Observations from this dataset are used to determine their impact on numerical weather prediction (NWP) model skill at simulating coastal and offshore winds through data-denial experiments. This study is a part of the Position of Offshore Wind Energy Resources (POWER) experiment, a Department of Energy (DOE) sponsored project that uses National Oceanic and Atmospheric Administration (NOAA) models for two 1-week periods to measure the impact of the assimilation of observations from 11 inland WPRs. Model simulations with and without assimilation of the WPR data are compared at the locations of the inland WPRs, as well as against observations from an additional WPR and a high-resolution Doppler lidar (HRDL) located on board the Research Vessel Ronald H. Brown (RHB), which cruised the Gulf of Maine during the NEAQS experiment. Model evaluation in the lowest 2 km above the ground shows a positive impact of the WPR data assimilation from the initialization time through the next five to six forecast hours at the WPR locations for 12 of 15 days analyzed, when offshore winds prevailed. A smaller positive impact at the RHB ship track was also confirmed. For the remaining three days, during which time there was a cyclone event with strong onshore wind flow, the assimilation of additional observations had a negative impact on model skill. Explanations for the negative impact are offered.

Global oceanic wind speed trends

This study presents the regional and seasonal climatic trends of the global oceanic sea surface wind speed for the period 1988–2011 using Cross-Calibrated, Multi-Platform (CCMP) wind data. The relationship between important factors (nino3 and soi index) and occurrences of wind speed is also calculated, in hope of providing references for the analysis of global climate change, development of offshore wind energy resources, air–sea interactions, and the basic reference helping for the mid-long term prediction of sea surface wind speed and occurrences of wind speed. The analysis results show that (1) The global oceanic sea-surface wind speeds increased at a significant overall rate of 3.35 cm s−1 yr−1 for the period 1988–2011; the maximal rate of increase, 4.15 cm s−1 yr−1, was attained between 1991 and 2007. (2) Globally, the sea-surface wind speeds significantly increased from 1988 to 2011. Only a few sporadic small water bodies exhibited decreasing wind speeds without significant variation over the 24-year interval. (3) The sea-surface wind speeds displayed obvious regional variability. The increasing wind speeds were more noticeable over the Pacific low-latitude waters than over waters of higher latitude. Wind speeds trends over the western Atlantic waters were stronger than those over the eastern Atlantic waters, while the south Indian Ocean winds were stronger than that those over the north Indian Ocean. (4) The variation in sea-surface wind speeds demonstrated noticeable seasonal differences. The increasing wind speed trend over the winter hemisphere was stronger than the one over the summer hemisphere. The variation in wind speeds over different waters was seasonally dominated. The increasing trend over the coastal waters of southern Greenland was dominated by the MAM and SON, was dominated by DJF in the Davis Strait and the Mediterranean, and was dominated by the SON 10° N over the Pacific Ocean and over the high-latitude waters in the southern Indian Ocean.

An Offshore Wind Energy Geographic Information System (OWE-GIS) for assessment of the UK's offshore wind energy potential

An Offshore Wind Energy Geographic Information System (OWE-GIS) has been developed for the purpose of assessing the economically accessible offshore wind energy resource for the United Kingdom.The UK OWE-GIS estimates the costs of energy from an offshore wind farm taking account of the major capital components; development costs dependent on water depth and distance from nearest ports or grid connection points; the potential energy production dependent on annual average wind speed, potential array losses, and turbine availability; operations and maintenance costs; and financial parameters such as discount rate and project lifetime. A sensitivity analysis is presented to show the influence of discount rate, project lifetime, and assumptions about overall capital expenditure (CAPEX), availability, and annual mean wind speed.

Potential of Offshore Wind Energy and Extreme Wind Speed Forecasting on the West Coast of Taiwan

It is of great importance and urgency for Taiwan to develop offshore wind power. However, relevant data on offshore wind energy resources are limited. This study imported wind speeds measured by a tidal station and a buoy into the software WAsP to estimate the high-altitude wind speeds in the two areas. A light detection and ranging (Lidar) system was set up near the tidal station and buoy. High-altitude wind speeds measured by the Lidar system were compared with the WAsP-estimated values, and it was discovered that the two data sets were consistent. Then, long-term wind speed data observed by buoys and tidal stations at various locations were imported into WAsP to forecast wind speeds at heights of 55–200 m on the west coast of Taiwan. The software WAsP Engineering was used to analyze the extreme wind speeds in the same areas. The results show that wind speeds at 100 m are approximately 9.32–11.24 m/s, which means that the coastal areas of west Taiwan are rich in wind energy resources. When a long-term 10-min average wind speed is used, the extreme wind speed on the west coast is estimated to be between 36.4 and 55.3 m/s.

Effects of different wind data sources in offshore wind power assessment

Currently, approximately 5.3% of electricity production in Europe comes from wind energy. The increase of the size and the improved efficiency of wind generators have permitted their utilization offshore, leading to exploitation of offshore wind energy. Although offshore wind farms are well established in northern European countries, in the Mediterranean Sea they are still in their infancy. It is expected that within the next few years, offshore wind farming will grow considerably in this area. The accurate estimation of the wind speed fields is of most importance for the assessment of offshore wind energy resources. In this work, the effects of alternative wind data sources on the wind climate analysis are examined along with the offshore wind power density estimation in four locations across the Aegean Sea. In order to develop correction relations for satellite and model wind data, taking as reference the buoy measurements, the data are analysed and calibrated using the Error-In-Variables approach. The effects of the different data sources on the wind climate analysis and the estimation of the mean wind power density before and after the calibration procedure are presented and discussed. The Error-In-Variables approach performed better and reduced significantly the uncertainties of the alternative data sources.

Offshore wind energy resource simulation forced by different reanalyses: Comparison with observed data in the Iberian Peninsula

Due to the increasing interest in the prospection of potential sites for the installation of offshore wind farms, it becomes important to extend the tests presented on Carvalho et al. (2014) to offshore areas. For that, the WRF model was used to conduct ocean surface wind simulations forced by different initial and boundary conditions (NCEP-R2, ERA-Interim, NCEP-CFSR, NASA-MERRA, NCEP-FNL and NCEP-GFS) aiming to assess which one of these datasets provides the most accurate ocean surface wind simulation and offshore wind energy estimates. Six near surface wind simulations were performed, each one of them forced by a different initial and boundary dataset. Results were evaluated using data collected at five buoys that measure the wind in the Iberian Peninsula region (Galician coast and Gulf of Cádiz).The results show that the simulation driven with ERA-Interim reanalysis provided the lowest errors in terms of offshore wind temporal variability. NCEP-R2 driven simulation showed the lowest offshore wind speed bias, mean wind speed and offshore wind energy production estimates. However, it was the one with the highest errors related to the wind temporal variability. The simulations driven with the NCEP-FNL and NCEP-GFS analyses products also showed interesting results, better than the NCEP-CFSR and NASA-MERRA reanalyses.Based on the results presented in this work and in Carvalho et al. (2014), ERA-Interim reanalysis likely provide the most accurate initial and boundary data to force near-surface wind simulations for the offshore and onshore areas. However, for offshore sites the NCEP-R2 reanalysis seem to provide the most accurate estimation of the potential wind energy production, fact that is of great importance for the wind energy industry. Furthermore, the NCEP-GFS and NCEP-FNL analyses can be considered as valid alternatives to ERA-Interim and NCEP-R2, in particular for cases where reliable forcing data is needed for real-time applications due to their fast availability.

Comparison of reanalyzed, analyzed, satellite-retrieved and NWP modelled winds with buoy data along the Iberian Peninsula coast

Offshore wind data derived from satellite measurements (CCMP, QuikSCAT, NCDC Blended Sea Winds and IFREMER Blended Wind Fields), reanalyses (NCEP-CFSR, ERA-Interim, NASA-MERRA and NCEP-RII), analyses (NCEP-FNL and NCEP-GFS) and WRF modelled offshore winds were compared to in situ measurements, in order to assess which one of these products is the best alternative to in situ offshore measured wind data. Wind speed and direction from these products were compared to measurements collected at five buoys moored along the Iberian Peninsula Atlantic coast.Results show that WRF modelled offshore winds are the best alternative to in situ measured offshore wind data, showing the highest temporal accuracy (the ability in representing the wind speed and direction at a given time instant) and lowest errors in terms of offshore wind power flux estimations. However, offshore wind data taken from CCMP shows the lowest errors in terms of the mean wind speeds and, together with IFREMER-BWF, the best wind temporal accuracy after WRF simulation. Therefore, in general CCMP and IFREMER-BWF can be considered as the best alternatives to WRF high resolution modelled offshore winds, if the latter is not available. Specifically for offshore wind energy resource assessment, NCEP-CFSR reanalysis or NCEP-GFS analysis data can also be used with confidence as an alternative to WRF modelled data, showing better wind power flux estimates than CCMP and IFREMER-BWF.Despite the best performances of WRF high resolution offshore winds, such modelling tasks require considerable computational resources and time to obtain quality results. Therefore, the value of satellite-derived wind data should not be disregarded. These remotely sensed offshore wind measurements should be seriously considered when searching for alternative sources of wind information for ocean areas, in particular for open ocean areas where they have their strength.

GOVERNING SHARED OFFSHORE ELECTRICITY INFRASTRUCTURE IN THE NORTHERN SEAS

AbstractThrough the joint ‘North Seas Countries Offshore Grid Initiative’ the states bordering the North Seas are establishing shared large-scale offshore electricity infrastructure in order to exploit their offshore wind energy resources. The article argues that this international governance of oceans space comes about legally because international law, European law and national law each fulfil a specific function. The climate regime provides the normative impetus, the law of the sea allocates competences, and European law contains principles of cooperation, which are then implemented through coordinated national law. International law, European law and national law thus become functionally integrated. This analysis has significance beyond shared offshore electricity infrastructure. It illustrates the way in which the functional integration of international law, European law and national law is emerging as a distinct legal institution in its own right, separate and distinct from the various legal orders themselves.

Assessing the China Sea wind energy and wave energy resources from 1988 to 2009

In this study, the wave field in the China Sea was simulated over the period from 1988 to 2009 using the third-generation wave model WAVEWATCH-III (WW3), with Cross-Calibrated, Multi-Platform (CCMP) wind field as the driving field. The China Sea wind energy density and wave energy density were calculated using the CCMP wind and WW3 model simulation results. The China Sea wind energy and wave energy resource were analyzed, synthetically considering the value of energy density, probability of exceedance of energy density level, exploitable wind speed and exploitable significant wave height (SWH), the stability of energy density, total storage and exploitable storage of energy resources, thus providing the guidance for the location of wind and wave power plants. Our results show that most of the China Sea contains abundant wave energy and offshore wind energy resources, with wind energy density above 150W/m2, wave energy density above 2kW/m, high occurrence of exploitable wind and wave energy in large scale waters, wind energy storage above 2×103kWhm−2, wave energy storage above 4×104kWhm−1. The richest area is in the northern South China Sea (wind energy density 350–600W/m2, wave energy density 10–16kW/m, wind energy storage 3×103–5×103kWhm−2, wave energy storage 8×104–16×104kWhm−1), followed by southern South China Sea and the East China Sea (wind energy density 150–450W/m2, wave energy density 4–12kW/m, wind energy storage 2×103–4×103kWhm−2, wave energy storage 4×104–12×104kWhm−1). The Yellow Sea and Bohai Sea resources are relatively poorer (wind energy density below 300W/m2, wave energy density below 4kW/m, wind energy storage below 2.5×103kWhm−2, wave energy storage below 6×104kWhm−1).

US East Coast offshore wind energy resources and their relationship to peak‐time electricity demand

ABSTRACTThis study characterized the annual mean US East Coast (USEC) offshore wind energy (OWE) resource on the basis of 5 years of high‐resolution mesoscale model (Weather Research and Forecasting–Advanced Research Weather Research and Forecasting) results at 90 m height. Model output was evaluated against 23 buoys and nine offshore towers. Peak‐time electrical demand was analyzed to determine if OWE resources were coincident with the increased grid load. The most suitable locations for large‐scale development of OWE were prescribed, on the basis of the wind resource, bathymetry, hurricane risk and peak‐time generation potential. The offshore region from Virginia to Maine was found to have the most exceptional overall resource with annual turbine capacity factors (CF) between 40% and 50%, shallow water and low hurricane risk. The best summer resource during peak time, in water of ≤ 50 m depth, is found between Long Island, New York and Cape Cod, Massachusetts, due in part to regional upwelling, which often strengthens the sea breeze. In the South US region, the waters off North Carolina have adequate wind resource and shallow bathymetry but high hurricane risk. Overall, the resource from Florida to Maine out to 200 m depth, with the use of turbine CF cutoffs of 45% and 40%, is 965–1372 TWh (110–157 GW average). About one‐third of US or all of Florida to Maine electric demand can technically be provided with the use of USEC OWE. With the exception of summer, all peak‐time demand for Virginia to Maine can be satisfied with OWE in the waters off those states. Copyright © 2012 John Wiley & Sons, Ltd.

Where is the ideal location for a US East Coast offshore grid?

This paper identifies the location of an “ideal” offshore wind energy (OWE) grid on the U.S. East Coast that would (1) provide the highest overall and peak‐time summer capacity factor, (2) use bottom‐mounted turbine foundations (depth ≤50 m), (3) connect regional transmissions grids from New England to the Mid‐Atlantic, and (4) have a smoothed power output, reduced hourly ramp rates and hours of zero power. Hourly, high‐resolution mesoscale weather model data from 2006–2010 were used to approximate wind farm output. The offshore grid was located in the waters from Long Island, New York to the Georges Bank, ≈450 km east. Twelve candidate 500 MW wind farms were located randomly throughout that region. Four wind farms (2000 MW total capacity) were selected for their synergistic meteorological characteristics that reduced offshore grid variability. Sites likely to have sea breezes helped increase the grid capacity factor during peak time in the spring and summer months. Sites far offshore, dominated by powerful synoptic‐scale storms, were included for their generally higher but more variable power output. By interconnecting all 4 farms via an offshore grid versus 4 individual interconnections, power was smoothed, the no‐power events were reduced from 9% to 4%, and the combined capacity factor was 48% (gross). By interconnecting offshore wind energy farms ≈450 km apart, in regions with offshore wind energy resources driven by both synoptic‐scale storms and mesoscale sea breezes, substantial reductions in low/no‐power hours and hourly ramp rates can be made.

Offshore wind energy potential in China: Under technical, spatial and economic constraints

This paper investigates available offshore wind energy resources in China’s exclusive economic zone (EEZ) with the aid of a Geographical Information System (GIS), which allows the influence of technical, spatial and economic constraints on offshore wind resources being reflected in a continuous space. Geospatial supply curves and spatial distribution of levelised production cost (LPC) are developed, which provide information on the available potential of offshore wind energy at or below a given cost, and its corresponding geographical locations. The GIS-based models also reflect the impacts of each spatial constraint as well as various scenarios of spatial constraints on marginal production costs of offshore wind energy. Furthermore, the impacts of differing Feed-in-tariff (FIT) standards on the economic potential are calculated. It confirms that economic potential of offshore wind energy could contribute to 56%, 46% and 42% of the coastal region’s total electricity demands in 2010, 2020 and 2030. The shallow waters along the coasts of Fujian, Zhejiang, Shanghai, Jiangsu and northern Guangdong are identified as suitable areas for developing offshore wind energy in terms of wind resources and economic costs. However, the influence of tropical cyclone risks on these regions and detailed assessments at regional or local scale are worth of further discussions. Nevertheless, the models and results provide a foundation for a more comprehensive regional planning framework that would address additional infrastructure, planning and policy issues.

Investigation on installation of offshore wind turbines

Wind power has made rapid progress and should gain significance as an energy resource, given growing interest in renewable energy and clean energy. Offshore wind energy resources have attracted significant attention, as, compared with land-based wind energy resources, offshore wind energy resources are more promising candidates for development. Sea winds are generally stronger and more reliable and with improvements in technology, the sea has become a hot spot for new designs and installation methods for wind turbines. In the present paper, based on experience building offshore wind farms, recommended foundation styles have been examined. Furthermore, wave effects have been investigated. The split installation and overall installation have been illustrated. Methods appropriate when installing a small number of turbines as well as those useful when installing large numbers of turbines were analyzed. This investigation of installation methods for wind turbines should provide practical technical guidance for their installation.

Exploring the potential of wind energy for a coastal state

Adequate recognition of the wind energy potential of coastal states may have far-reaching effects on the development of the energy systems of these countries. This study evaluates wind energy resources in Taiwan with the aid of a geographic information system (GIS), which allows local potentials and restrictions such as climate conditions, land uses, and ecological environments to be considered. The findings unveiled in this study suggest a significant role for offshore wind energy resources, which may constitute between 94% and 98% of overall wind resources in Taiwan. Total power yield from wind energy could reach between 150 and 165 TWh, which would have, respectively, accounted for between 62% and 68% of Taiwan's total power generation of 243 TWh in 2007. Based on the Taiwan's current emission factor of electricity, wind energy has the potential to reduce CO 2 emissions by between 94 and 102 million ton per year in Taiwan, which is, respectively, equivalent to 28% and 31% of the national net equivalent CO 2 emissions released in 2002. However, the challenge of managing the variability of wind power has to be addressed before the considerable contribution of wind energy to domestic energy supply and CO 2 reduction can be realized.

Exploring wind energy potential off the California coast

[1] Wind energy represents the nearest term cost-effective renewable energy source. While efforts have been made to assess wind energy potential over land around the world, offshore wind energy resources are largely unexplored, in part because these regions have relatively sparse wind observations. In this study, the wind energy potential offshore of the California coast is evaluated using a well-tested high-resolution numerical model dataset. We found that along the coastline, the low-level winds exhibit strong spatial variation and are characterized by alternating windspeed maxima and minima near coastal promontories associated with the interaction between the marine boundary layer and coastal topography. Further analysis highlights the enormous and reliable wind energy development potential in these persistent offshore windspeed maxima.

A Regional Assessment of the U.S. Offshore Wind Energy Resource through the Use of Mesoscale Modeling

Interest in offshore wind power is rapidly developing in the United States. Estimates of the potential offshore wind resource in U.S. waters exceed 900 GW. Thus, there is a need for tools to accurately evaluate and depict wind power availability. This necessitates observation and modeling strategies that focus on describing the physical and dynamical processes that operate within and just above the marine atmospheric boundary layer over a spectrum of spatial and temporal scales. Here, we discuss the data assimilation and modeling methods used to characterize the offshore wind environment through examples of resource mapping, observational studies, and model simulations. We present high resolution (200 m) offshore wind resource maps for New England, Texas, Louisiana, and the Great Lakes. Finally, we discuss the results of a recent intensive field measurement campaign in the waters south of Long Island, NY, and a modeling analysis and verification study of the coastal atmospheric regime.

The 44-year Mediterranean HIPOCAS wind database: A useful tool to analyse offshore extreme wind events from a long-term regional perspective

Nowadays, many efforts are leading to use the high potential offshore wind energy resources. A detailed assessment of the offshore wind resources arises as a first-rate requirement. Most of such assessment is based on extreme offshore wind atlas generated mainly from global reanalysis and satellite data. Both sort of data show certain shortcomings related, among others, to coarse spatial resolution and time inhomogeneity issues, respectively. This snag seems to be crucial over areas such as the Mediterranean Basin, which is characterized by a complex land–sea distribution and a significant orography. The HIPOCAS Mediterranean long-term (1958–2001) wind database comes to overcome the aforementioned reanalysis shortcoming and provides a Mediterranean wind data set useful to perform extreme wind analysis. This contribution also deals with a statistical extreme wind analysis over the whole Mediterranean offshore areas. Extreme return periods and levels are obtained from annual maxima using a number of distributions. Additionally, an alternative regional statistical method based on regional L-moment statistics is also proposed. The regional technique is applied to reduce uncertainty and allows a higher number of measurements to be included in the analysis, using data from a homogeneous region instead of from a single location. The herein performed extreme wind analysis provides a detailed assessment of high wind offshore areas over the Mediterranean and constitutes a subject of great interest for evaluation of wind resources.

Offshore Wind Electricity: A Viable Energy Option for the Coastal United States

U.S. offshore wind energy resources are abundant, indigenous, and broadly dispersed among the most expensive and highly constrained electricity load centers. Economic capacity expansion models developed at the National Renewable Energy Laboratory show that offshore wind energy can compete in future U.S. electric energy markets without major changes in the market variables or revolutionary technological breakthroughs. However, significant research, development, and deployment will be needed to bring the current technology through a course of cost reductions. To maximize the resource potential, these reductions need to be made along parallel technology paths that will expand the available resource by allowing wind turbines to be installed in deep water. Analysis shows that incremental technology improvements leading to moderate cost reductions, and reasonable increases in the cost of conventional energy will help offshore wind achieve cost competitiveness by 2030 and become a major contributor to the energy supply of the United States. This paper describes a wide range of technical research and development that can reduce costs and improve technology for deep water deployment.

Bibliographic Review of FACTS and HVDC Applications in Wind Power Systems

With more emphasis being laid on clean and renewable sources of energy, engineers look for the best possible ways to harness the wind energy to the maximum extent. FACTs controllers that were earlier being used at the transmission level find their use at generation level when it comes to extracting reliable and quality power from Wind Energy Conversion Systems (WECS). This article presents a review of the important modeling techniques employed for developing FACTs controllers and examines the role of HVDC-Light transmission in exploiting the Off-shore wind energy resources.

A year 2000 summary of offshore wind development in the United States

This paper presents an overview of the status of offshore wind energy development in the United States. It includes an overview of the research conducted at the University of Massachusetts in the early 1970s on large floating offshore systems and designs for offshore systems sited in the Great Lakes. It also presents a summary of the present US work on offshore energy, including the most recent work in New England as well as national and regional efforts to define the potential offshore wind energy resource. Also included is a review of the regulatory and permitting issues that must be addressed for offshore wind energy systems development. The paper concludes with a summary of current commercial and developmental activities in the US.