Current status and future of ocean energy sources: A global review

Major transformation of the global energy system is required for climate change mitigation. However, energy demand patterns and supply systems are themselves subject to climate change impacts. These impacts will variously help and hinder mitigation and adaptation efforts, so it is vital they are well understood and incorporated into models used to study energy system decarbonisation pathways. To assess the current state of understanding of this topic and identify research priorities, this paper critically reviews the literature on the impacts of climate change on the energy supply system, summarising the regional coverage of studies, trends in their results and sources of disagreement. We then examine the ways in which these impacts have been represented in integrated assessment models of the electricity or energy system. Studies tend to agree broadly on impacts for wind, solar and thermal power stations. Projections for impacts on hydropower and bioenergy resources are more varied. Key uncertainties and gaps remain due to the variation between climate projections, modelling limitations and the regional bias of research interests. Priorities for future research include the following: further regional impact studies for developing countries; studies examining impacts of the changing variability of renewable resources, extreme weather events and combined hazards; inclusion of multiple climate feedback mechanisms in IAMs, accounting for adaptation options and climate model uncertainty.

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Climate change impacts on the energy system: a review of trends and gaps.

Assessment of wave energy resource of the Black Sea based on 15-year numerical hindcast data

Given the current background of ongoing environmental and resource issues, the increased exploitation of clean and renewable energy could help to alleviate the energy crisis, as well as contributing to emissions reduction and environmental protection, and so promote future sustainable development. This study explores to reveal the climatic long term trends of the China Sea wave power and significant wave height (SWH) for the period 1988–2011, using a WAVEWATCH-III (WW3) hindcast wave data. The regional difference and seasonal difference of the variation are also presented firstly. Results show that, (1) The China Sea exhibits a significant overall increasing trend in the wave power density (0.2012 (kW/m)/yr) and the SWH (1.52 cm/yr) for the period 1988 to 2011. (2) There is a noticeable increasing trend in most parts of the China Sea, of 0.1–0.7 (kW/m)/yr in wave power density and 0.5–4.5 cm/yr in SWH. Areas with strong increasing trend distribute in the Ryukyu Islands waters, Taiwan Strait and north of the South China Sea (SCS), especially in the Dongsha Islands waters. (3) There is a noticeable seasonal difference in the variation of both SWH and wave power density. The variation in different waters is dominated by the different seasons. The increasing trend of SWH in DJF and MAM is obviously stronger than that in JJA and SON. The increasing trend of wave power density in DJF is stronger than that in other seasons.

Variation of the wave energy and significant wave height in the China Sea and adjacent waters

Water quality is a big concern for the humankind as it is the most important natural resource. However, the non-controlled growth of rural and urban areas in rapidly developed countries suc...

Assessment of heavy-metal pollution in three different Indian water bodies by combination of multivariate analysis and water pollution indices

Wave modeling and extreme value analysis off the northern coast of the Persian Gulf

Assessment of wave energy variation in the Persian Gulf

Sustainability of wave energy resources in southern Caspian Sea

Developing an optimum hotspot identifier for wave energy extracting in the northern Persian Gulf

The main goal of this study is to develop an efficient approach for the assimilation of the hindcasted wave parameters in the Persian Gulf. Hence, the third generation SWAN model was employed for wave modeling forced by the 6-h ECMWF wind data with a resolution of 0.5°. In situ wave measurements at two stations were utilized to evaluate the assimilation approaches. It was found that since the model errors are not the same for wave height and period, adaptation of model parameter does not result in simultaneous and comprehensive improvement of them. Therefore, an approach based on the error prediction and updating of output variables was employed to modify wave height and period. In this approach, artificial neural networks (ANNs) were used to estimate the deviations between the simulated and measured wave parameters. The results showed that updating of output variables leads to significant improvement in a wide range of the predicted wave characteristics. It was revealed that the best input parameters for error prediction networks are mean wind speed, mean wind direction, wind duration, and the wave parameters. In addition, combination of the ANN estimated error with numerically modeled wave parameters leads to further improvement in the predicted wave parameters in contrast to direct estimation of the parameters by ANN.

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Vahid Chegini

Papers

Wave modeling and extreme value analysis off the northern coast of the Persian Gulf

Assessment of wave energy variation in the Persian Gulf

Sustainability of wave energy resources in southern Caspian Sea

Developing an optimum hotspot identifier for wave energy extracting in the northern Persian Gulf

Wave data assimilation using a hybrid approach in the Persian Gulf