• Energy Research
• 14. Life underwater close
• Applied Energy close

Abstract Wind energy is expected to contribute to alleviating the rise in energy demand in the Middle East that is driven by population growth and industrial development. However, variability and intermittency in the wind resource present significant challenges to grid integration of wind energy systems. These issues are rarely addressed in the literature of wind resource assessment in the Middle East due to sparse meteorological observations with varying record lengths. In this study, the wind field with consistent space–time resolution for over three decades at three hub heights ( 50 m, 80 m , 140 m ) over the whole Arabian Peninsula is constructed using the Modern Era Retrospective-Analysis for Research and Applications (MERRA) dataset. The wind resource is assessed at a higher spatial resolution with metrics of temporal variations in the wind than in prior studies. Previously unrecognized locations of interest with high wind abundance and low variability and intermittency have been identified in this study and confirmed by recent on-site observations. In particular, the western mountains of Saudi Arabia experience more abundant wind resource than most Red Sea coastal areas. The wind resource is more variable in coastal areas along the Arabian Gulf than their Red Sea counterparts at a similar latitude. Persistent wind is found along the coast of the Arabian Gulf.

Abstract In this study, the existence and variability of wave energy resource potential of the Black Sea based on 15-year hindcast data is described in detail. The hindcasts of wave parameters were carried out by using the third generation wave prediction model (Simulated WAves Nearshore – SWAN), which is one of the most popular numerical wave models and has been widely used for estimating ocean waves. The model was forced with the ECMWF ERA Interim wind fields and applied with a spatial resolution of about 0.0167° × 0.0167° and a model time step of 6 h to resolve efficiently offshore and nearshore wave conditions. The results were presented in the form of charts of the spatial distribution of significant wave height and wave power, on a monthly, seasonal and annual basis. Annual energy was calculated in the study region with the hindcast data set covering 15 years (1995–2009). The areas with the highest wave energy resource were determined and the south west coasts of the Black Sea are suggested as the best site for the installation of a wave farm. It was determined the western parts of the Black Sea (especially the south-west) are exposed to energetic waves more than the eastern parts.

The selection of the appropriate wave energy converter (WEC) and site is the basis for the installation of a wave farm in a region. For this purpose, the estimation of the energy that any WEC would produce at any location of interest is fundamental. Despite all its importance, this information or the elements required for obtaining it are currently available only at specific coastal locations or areas of interest. This work develops a tool for computing the energy that any WEC would generate at any coastal location within the Rias Baixas Region (NW Spain). With this aim, a methodology which allows the consideration of almost all the total energy available is used to characterize the coastal resource with a high spatial resolution. Then, a matlab-based application called WEDGE (Wave Energy Diagram GEnerator) is implemented for easy access to the stored data and automatic reconstruction of the resource at any coastal site in terms of a high-resolution characterization matrix (or energy diagram). As a result, the information required for accurate energy production computation throughout the region is available whereby a combined WEC-site selection can be conducted. Finally, the tool is used to compute the energy production of a total of 23 WEC-site combinations in an area within this region where a wave farm has been recently proposed. The results will underline the importance of a combined WEC-site selection for proper decision-making regarding wave energy exploitation.

Abstract Extreme weather events expose electricity industry to diverse risks. Global warming will increase vulnerability to extreme weathers, such as drought. In this paper, we examine the susceptibility of Ethiopian power systems to extreme hydrological conditions using an integrated hydro reservoir and power system dispatch model. The result shows that hydropower could help in achieving the least cost generation of electricity by 2017. However, the cost of electricity was found to significantly vary with various factors. It was found that, excluding cost of unserved energy, the low inflow scenario presents a situation where cost of electricity is approximately 4 times higher than the moderate inflow. Electricity price is currently cheap and stable due to governments pricing strategy. Consequently, the cost borne by the nation’s economy could be seen from annual cost of dispatch, which increases from approximately 1 billion USD per year at the reference scenario to about 4 Billion USD for the low inflow scenario. The dispatch cost will be above 8 folds if the cost of unserved energy is included. This shows that the power system is poorly resilient against climate change impact. Thus, we recommend that policymaking and planning focuses on transitioning to climate change adaptive system.

The assessment of wave energy resources is critical for site selection before deploying wave energy converters (WECs). Usually, a simplified wave energy assessment equation (SWEAE), using bulk wave parameters such as significant wave heights, peak periods, etc., is employed to estimate the wave energy flux. However, it neglects the effects of water depth on wave group velocities, thus being more suitable for deep waters. Considering most of the WECs are installed in nearshore zones or around islands, a more accurate wave energy assessment equation is needed. In the present work, a general wave energy assessment equation (GWEAE) for both shallow and deep waters is derived by introducing an explicit wave dispersion equation. Both GWEAE and SWEAE are applied in the assessment of wave energy fluxes in the coastal waters surrounding Qingdao City, China. Wave energy fluxes calculated by integration over all frequency and direction bins of the random waves, which can be regarded as the most accurate equation, are used for validating the two equations. It is demonstrated that the GWEAE significantly improve the accuracy of the wave energy estimation for various water depths compared with the SWEAE, especially for nearshore shallow water areas. Because the improved equation is free of integration calculations and iterative computations, it is a simple and accurate tool for estimating wave energy fluxes.

Abstract This paper is to study Weibull distribution and Maximum Entropy Principle applied to fit the wind speed frequency distribution of the intertidal zone anemometer towers. Comparisons of the results from Weibull distribution and Maximum Entropy distribution are made for the characteristics of the wind speed distribution and the variation with height in the offshore area. The Maximum Entropy distribution is found to perform adequately and accurately in fitting the wind speed frequency distribution with height. It is shown that the frequency peak value of Weibull distribution is lower than the measured maximum frequency at the same height, and the fitting accuracy of the Maximum Entropy Principle is significantly higher than that of Weibull distribution. Furthermore, the mean errors of average effective wind power density calculated from the five-parameter Maximum Entropy distribution as well as from Weibull distribution are 1.71 W m −2 and 7.48 W m −2 respectively. Except for these findings, limitations and problems existing in the procedure of fitting the annual wind speed probability distribution are also discussed.

Abstract The decrease in the oil discoveries fuels the development of innovative and more efficient extraction processes. It has been demonstrated that Enhanced Oil Recovery (EOR, or tertiary recovery technique) offers prospects for producing 30 to 60% of the oil originally trapped in the reservoir. Interestingly, oil extraction is significantly enhanced by the injection of low salinity water into oilfields, which is known as one of the EOR techniques. Surface Reverse Osmosis (SRO) plants have been adopted to provide the large and continuous amount of low salinity water for this EOR technique, especially in offshore sites. In this article, we outline an original solution for producing low salinity water for offshore EOR processes, and we demonstrate its energy convenience. In fact, the installation of reverse osmosis plants under the sea level (Deep-Sea Reverse Osmosis, DSRO) is found to have significant potential energy savings (up to 50%) with respect to traditional SRO ones. This convenience mainly arises from the non-ideality of reverse osmosis membranes and hydraulic machines, and it is especially evident – from both energy and technological point of view – when the permeate is kept pressurized at the outlet of the reverse osmosis elements. In perspective, DSRO may be a good alternative to improve the sustainability of low salinity EOR.

Abstract In this study, a long-term assessment of the wave energy resource potential for the Australian southeast shelf is performed from deep to shallow water, based on a 31-year wave hindcast. The hindcast, covering the period from 1979 to 2010, has been performed at high spatio-temporal resolution with the wave energy transformation model SWAN using calibrated source-term parameters. The model has been applied with a variable spatial resolution of up to approximately 500 m and at 1 h temporal resolution and driven with high-resolution, non-stationary CFSR wind fields and full 2D spectral boundary conditions from WaveWatch III model. Model validation was conducted against wave measurements from multiple buoy sites covering 10–31 years and showed a relatively high correlation between hindcast and measured significant wave height ( H s ) and mean wave direction ( θ m ). Maps of wave power resource distribution for annual and seasonal mean potential were generated along with the maps of resource reliability and variability. The high resolution allowed us to perform in-depth analysis of wave power characteristics, providing resource knowledge on seasonal and longer-term variability necessary for reliable and optimal design of wave technology. The most promising area for wave power exploitation was found to be the central coast of New South Wales, where various high-energy hotspots were selected for a further analysis. For each of the considered hotspots, the wave power magnitude, variability and consistency were carefully assessed and characterized by means of sea state parameters and mean wave directions. Finally, estimates of electric power outputs from different types of pre-commercial wave energy converter devices were drawn for each hotspot based on the wave data hindcast and discussed.

Abstract The use of offshore wind power is becoming increasingly important towards a sustainable growth worldwide. In Italy, as well as in other countries where wind energy is provided only by onshore plants, the interest in the deployment of offshore wind resources is rapidly growing, despite relatively modest average wind speeds, compared to typical wind conditions in the North Sea. Research efforts have, so far, addressed the exploration of the most promising locations, based on wind characteristics; however, more extended evidence of technical and economic feasibility is now needed to raise awareness in the decision makers and secure to this source of renewable energy a proper role in the future energy policies. Within such a context, the paper presents the first feasibility study for the development of an offshore wind farm off the coast of Rimini, in the Northern Adriatic Sea. The study is based on an anemometric campaign started at the site in 2008 to provide a statistical assessment of the wind characteristics and the related wind energy potential, and on a 10-year wave measurement record next to the area, together with a thorough analysis of the site geological and environmental characteristics. Environmental data are interpreted with a proper consideration of the extreme events distribution and relevant results are used to select the most appropriate commercially available wind turbine and to design the site-specific support structure. A comprehensive evaluation of the investment costs and revenues is then carried out with reference to two wind farm layouts (a first smaller, constituted of 15 elements, and another one, featuring up to 60 elements) and in relation to two different scenarios, conservative and comparatively more realistic. Results of the study clearly show that the Northern Adriatic Sea is potentially suitable for the development of a large wind farm and should encourage investments on more advanced experimental campaigns and related studies in order to prove the feasibility of innovative technological solutions that would substantially increase the profitability of such installation.