On the Wave Energy Assessment in the South China Sea

This paper presents a thirty year (1976-2005) assessment of wave energy resource within the South China Sea (SCS) by simulation. Significant wave height (SWH) between simulation and observation shows good agreement. This shows the reliability of an along-side simulated wave period in estimating wave energy in the SCS. Results show that estimates of wave power density are more reliable in the north-central SCS and most sufficient during winter. The annual mean wave power density peaked at 12.7kW/m and 12.9kW/m during years 1986 and 1999 respectively while the highest seasonal mean of 29kW/m occurred in year 1999 during winter. The wave power density is most stable in winter and is generally more stable in offshore regions of SCS. Wave power density is most stable in years 1976, 1997 and 2004 with stability values of 1.96, 1.98 and 1.9 respectively. The stability value of 0.9 in year 1980 is the greatest in the winter of all years. Relative-rich energy regions occupy the largest area during winter. The relatively richest energy is generally concentrated in the central and north-central SCS. No area is identified as a relative-rich energy region during spring. Winter 1999 has the highest relative-rich energy with value of 37kW/m

Correlation of Global Solar Irradiance with some Meteorological Parameters and Validation of some Existing Solar Radiation Models with Measured Data Over Selected Climatic Zones In Nigeria.

Fourteen models comprising of 12 existing and 2 parameterized models are evaluated for predicting the global solar irradiance on a horizontal surface at six different sites representative of six different climatic zones of Nigeria namely; Mangrove swamp forest (Calabar), Sahel Savannah (Nguru), Montane Vegetation (Yola), Sudan Savannah (Kano), Tropical rain forest (Ibadan) and Guinea Savannah (Minna). Results showed that the two models from this study performed well in predicting global solar irradiance over the six different zones with slight overestimation in some cases and slight underestimation in others. However, out of the two models, model 14 had a better predictive ability. For the 12 existing models, Glover and mcCulloch model was found to be most suitable for the Mangrove swamp forest, Sahel and Montane zones while Raja and Twidell , Rietveld and Annandale et al models are respectively the most suitable models in the Sudan, Tropical rainforest and Guinea zones

On the Wind Energy Resource and Its Trend in the East China Sea

This study utilizes a 30-year (1980–2009) 10 m wind field dataset obtained from the European Center for Medium Range Weather Forecast to investigate the wind energy potential in the East China Sea (ECS) by using Weibull shape and scale parameters. The region generally showed good wind characteristics. The calculated annual mean of the wind power resource revealed the potential of the region for large-scale grid-connected wind turbine applications. Furthermore, the spatiotemporal variations showed strong trends in wind power in regions surrounding Taiwan Island. These regions were evaluated with high wind potential and were rated as excellent locations for installation of large wind turbines for electrical energy generation. Nonsignificant and negative trends dominated the ECS and the rest of the regions; therefore, these locations were found to be suitable for small wind applications. The wind power density exhibited an insignificant trend in the ECS throughout the study period. The trend was strongest during spring and weakest during autumn