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This paper develops the temporal-spatial distribution of wave energy at the Beibu Gulf at a monthly, seasonal, and annual base using the Simulated WAves Nearshore (SWAN) model, which is called third generation wave prediction model. The model is forced with the ECMWF ERA Interim wind field data covering 34 years at a time interval of 6 h. Wave parameters, including significant wave height ( Hs ), peak wave period ( Tp ), and wave direction (θ) are simulated by SWAN model. Simulated data are validated against the altimeter data using Bias, MSE, and R, and the validation results show that the simulated data can effectively be used to calculate the wave energy in Beibu Gulf. This paper highlights the temporal-spatial distributions of monthly, seasonal, and annual of wave energy. The results reveal that (1) the wave energy propagations in inner waters are dominantly along northeast and west-northwest; (2) the high-energy areas are located at the middle and the southern Beibu Gulf; (3) the biggest monthly wave energy is from January through March with approximately 2.5 kW/m, and the biggest seasonal wave energy is from winter through spring with approximately 1.7 kW/m, and the biggest annual wave energy is about 1.5 kW/m. Additionally, the quantitative analysis, in which the total storage of wave energy vs. the percentage of wave energy greater than 2 kW/m is mapped at a 0.5° × 0.5° grid, identifies those grids used for wave energy convertor deployment. Finally some suggestions are drawn up for decision-makers of the local government. [ABSTRACT FROM AUTHOR]

In recent years, Chinese Government paid more attention to the exploitation of offshore wind power, and it became an important trend in the development of wind power industry. However, the development of offshore wind power in China was still in the initial stage. Compared with land-based wind power, the development of off-shore wind power had not only weaknesses and uncertainties, but also strengths and opportunities. In order to research the development of offshore wind power, this paper summarized the aspects on policy, market, technology and development planning of offshore wind power in China, and then adopted SWOT method to analyze the influencing factors, which impact on the development of China's offshore wind power. At last, this article analyzed the internal and external factors that affect the golden period of offshore wind power development, and drew a conclusion that the golden period of offshore wind power in China will come in the future, and most likely around 2020. [ABSTRACT FROM AUTHOR]

Abstract: Liaoning province, located in Northeast China – one of China''s three most wind-rich areas, possesses abundant wind resources. Along with China''s rapid development of wind power in recent years, the issue of how to integrate more wind power to the grid, and how to balance the conflict between pollutant and GHG emission reduction and economic cost increase by dispatch model adjustment becomes a big challenge. Based on the GAMS simulation method, by using the real data of thermal power units, wind power and hydropower generation, and load in Liaoning province, this paper studies a joint environmental and economic power dispatch considering wind power integration at valley load and peak load. The results show that the pumped storage power station played an important role in promoting wind power integration. And the power dispatch across thermal power, wind power and hydropower is more favorable than the power dispatch only across thermal power and wind power in terms of reducing pollutant and GHG emission. It is also proved that a comparatively better environmental improvement can be made at a relatively lower economic loss by a joint environmental and economic dispatch across thermal, wind and hydropower. [Copyright &y& Elsevier]