Storm Anatol over Europe in December 1999: impacts on societal and energy infrastructure

Storm Anatol impacted the North Sea and northern Europe on 3–4 December 1999. It brought hurricane force winds to Denmark and northern Germany, and high winds also in Sweden and countries around the Baltic Sea. For many meteorological stations in Denmark, the wind speeds were the highest on record and the storm was ranked as a century event. The storm impacts included extensive forest damage, fatalities, hundreds of injuries, power outages, transportation interruptions, as well as storm surge flooding on the west coast of Denmark. Strongly committed to wind energy, Denmark lost 13 onshore wind turbines destroyed during the storm. An important industry insurer noted that this was a remarkably low number, considering the storm intensity and the large number of turbines (>3500) installed in the country. In 1999, offshore wind energy was just getting started in Europe, and the storm provided an important test of environmental extreme conditions impacting offshore infrastructure. This contribution takes a closer look at the regional met-ocean conditions during the storm. A brief overview is made of the wind field and available wave measurements from the North Sea. An examination is made of water level measurements from around the North Sea to characterize the storm surge and identify possible meteo-tsunamis and infragravity waves. Offshore accidents are briefly discussed to assess if there had been unusual wave strikes on shipping or platforms. At the time of the storm in 1999, there was a growing awareness in the scientific community of possible changes in ambient sea state conditions and the increasing threat of rogue waves. The offshore wind energy community had become aware from the impact of rogue waves from damage at the research platform FINO1 in the southern North Sea during severe storms in 2006, 2007, 2009, and 2013. Storm Anatol may have been another rogue wave storm at an earlier stage of offshore wind energy development.

Main Trends and Criteria Adopted in Economic Feasibility Studies of Offshore Wind Energy: A Systematic Literature Review

Offshore wind energy has been identified as one of the most promising and increasingly attractive sources of energy. This technology offers a long-term power-generation source, less environmental impact, and fewer physical restrictions. However, given the complexity of this technology, economic feasibility studies are essential. Thus, this study aims to identify the main trends and criteria or the methods used in the economic feasibility studies of offshore wind energy, providing a review of the state of the art in this literature. For this, a Systematic Literature Review was carried out. The article shows the growing interest in offshore wind power generation and highlights how recently the interest in the studies that assess the technical–economic feasibility of this source has grown; it presents the main milestones of the topic. Based on a structured literature review, this article identifies the main trends in this topic: (i) wind farms, (ii) risk, (iii) floating offshore wind farms, (iv) decommissioning and repowering, (v) net present value, (vi) life cycle cost, and (vii) multi-criteria decision-making; it provides a broad view of the methodological possibilities and specificities for investors and researchers interested in conducting studies on the economic feasibility of offshore wind generation. In addition, finally, a research agenda is proposed.

Evaluating Technological Innovation Impact. An Empirical Analysis of The Offshore Wind Sector.

This study analyses the drivers that impact innovation on offshore wind energy for a select group of countries, applying the quantile and GMM approaches for a period between 2010-2019. The OLS results from the quantile analysis say the log of trademark, Carbon emissions, offshore wind capacity, and electricity from renewable energy are significant and impact on innovation regarding offshore wind energy. Generally, the Breusch-Pagan / Cook-Weisberg test for heteroskedasticity test reveals the variables have a constant variance, confirming the robustness of the findings. The quantile regression depicts that at 25th and 75th quantiles levels, the log of trademark, the log of trade flows, the log of scientific and technical journals quantile coefficients is significantly different from zero and exhibit varied effects on the explained variable patent.Similarly, the analysis applied the IV-GMM estimation in ivreg2 to identify the over restrictions, the Hansen J statistic, and give the robust moment of conditions analysis. The findings are consistent with prior analysis with the log of trademark, the log of offshore wind capacity, the log of carbon emissions, Scientific and technology journals, the log of patent, electricity from renewables to be significant and impact on innovation.The robustness was done on the GMM models, by applying the Huber-White-Sandwich estimator of the variance of the GMM linear models approximators. The ivreg2 robust analysis revealed that the estimates are efficient for homoskedasticity and Statistics robust to heteroskedasticity.Ultimately, the interaction term ‘’cross’’ came out significant in the analysis. Signifying the importance of the interaction variables in scaling innovation.This study will sever as a reference document for policy formulators regarding scaling up innovation for offshore wind energy.

THE POTENTIAL OF OFFSHORE WIND ENERGY IN THE EAST COAST OF PENINSULAR MALAYSIA, TERENGGANU

A detailed understanding of wind characteristics is very important for offshore wind energy development. A 26 years of wind speed data (1993-2018) were retrieved using Radar Altimeter Database System (RADS) to assess the potentiality of offshore wind energy in Terengganu waters. Seasonal assessment and wind energy density derivation was carried out to choose the potential location for wind energy development. This study highlights the multi-criteria site suitability analysis using Analytical Hierarchy Process (AHP) and is supported by the geographical information system (GIS) by developing a suitability map. The site suitability analysis considered a few criteria, such as seasonal assessment, physical, environmental, and wind resources. Theoretically, the Terengganu area possessed strong wind during the Northeast monsoon with an average of 3.46m/s and experienced up to 6 m/s during this monsoon. For offshore areas, which is more than 50km from the coastline, Terengganu waters experienced a maximum of wind speed more than 5m/s and the average wind power density varied from 40W/m2 to 60W/m2. While Tenggol Island possessed a maximum wind speed between 3m/s to 5m/s and produce up to 40W/m2 of average wind energy density. From the suitability analysis, a few areas are identified as the potential location with an optimum resource of wind energy. Even though, Malaysia is located at low wind area, this research will help organisation or governments to plan suitable technology and policy for harvesting wind energy.

Determining the Optimal Offshore Wind Power Station Using a Two-Stage MCDM-Based Spherical Fuzzy Set Approach

In response to challenges from the COVID-19 pandemic and climate change to achieve the goal of ensuring sustainable economic growth, offshore wind power development not only provides a clean and sustainable source of energy but also provides opportunities for economic growth and job creation. Offshore wind energy projects have been promptly suggested in Vietnam as a result of policy advancement, with the country's excellent wind resources. The success of an offshore wind energy project is decided mainly by choosing the best location for offshore wind power station (OWPS) construction, which is a complex multicriteria decision-making (MCDM) problem with the coexistence of conflicting factors. There is a problem with incomplete decision information use and information loss during the decision-making process, and it is easy to overlook the interaction difficulty in a fuzzy environment. To address the complex nature of the prioritization problem posed, this study proposes a hybrid MCDM framework combining the spherical fuzzy analytical hierarchy process (SF-AHP) and weighted aggregated sum product assessment (WASPAS). SF-AHP is used in the first stage to determine the significance levels of OWPS evaluation criteria. WASPAS is then utilized to rank locations of OWPS. A comprehensive set of evaluation criteria developed based on the concept of sustainable development has been recognized by reviewing the literature review and interviewing experts to practice the two-stage MCDM model. A real case study for Vietnam is conducted to test the effectiveness of the proposed method. The best location schemes have been determined by using the decision framework. The results of the sensitivity analysis and a comparison analysis demonstrate that the decision framework is practical and robust. Ultimately, the evaluation criteria and methodology presented in this work can serve as a theoretical foundation for the advancement of offshore wind energy and coastal development.

Effect of Climate Variability Events over the Colombian Caribbean Offshore Wind Resource

The need for reducing the CO2 emissions and fossil fuel dependence of several countries generated a growing interest for the Renewables. The Caribbean Sea is characterized by persistent and high magnitude winds, which suggest an important source of offshore wind energy. Recent studies reported that the Colombian Caribbean has a relevant opportunity for developing the offshore wind technology which could complement the energy production when the hydroelectric system is under low generation due to persistent dry conditions generated by El Niño events. The offshore wind energy may complement the energy offer of Colombia. Hence, understanding the impact of climate variability events in the Caribbean over the wind magnitude, contributes to the knowledge of the resource availability for a better planning of future offshore wind farms. In this sense, this study analyzed 39 years of Reanalysis wind data through a time series analysis of the Caribbean to identify the lowest wind speed velocities and when and why they occurred. The results showed that winds of the study area represented by the Caribbean Low level, showed the lowest wind speeds in the short, mid, and long term due to the influence of the seasons, El Niño-Southern Oscillation (ENSO) and the Atlantic Multidecadal Oscillation (AMO).