| Summary: | 碩士 === 國立中央大學 === 能源工程研究所 === 107 === In addition to the large-scale onshore and offshore wind farms, urban wind energy has gradually drawn attention among green energy resources because of creative wind energy technology and rapid increase of urban development in recent years. In order to assess the potential of urban wind energy, this study first compared various wind field correction methods in WRF model and combines CALMET wind diagnostic model to obtain the best final wind field. Then, we assessed urban wind energy based on final wind farm data and discussed the economic benefits and the demand/supply of power system.
This study took Taichung City as an example and simulates wind field during the January, April, April, and October 2017. First, the sensitivity test was conducted for the WRF model, including adjustment of urban roughness length in land use data, Four-Dimensional Data Assimilation. (FDDA), urban parameterization in WRF such as Urban Canopy Model (UCM), Building Effect Parameterization (BEP), and Building Energy Modeling (BEM). We found that the overall performance of FDDA plus BEP parameterization is the best in the test and significantly improved the simulated wind field in areas where building density is high in the city center. Then we used the WRF/BEP derived wind field as the initial guess and combined the observation data for the CALMET diagnosis modeling. The coupling WRF/BEP and CALMET can strongly pull simulations toward observations, especially in the suburban area with relatively high terrain complexity nearby.
This study then analyzed the distribution of urban wind speed and wind energy density. It is found that the 2.5kW rooftop small wind turbine is suitable for building above 4th floor in Chingshuei, Wuchi, Longjing and Shalu districts (Average wind speed 2~6 m s-1, annual power generation 5500~12000 kWh), or the buildings above 120 meters in Bei Tun, Si Tun, Tai Jhong and Nantun districts (Average wind speed is 3~5 m s-1, annual power generation 4500-9000 kWh). The 15 kW ground type small wind turbine is suitable in the open area of Chingshuei, Wuchi, Longjing and Shalu districts (average wind speed is 2~6 m s-1, annual power generation 38000~72000kWh). According to the renewable energy procurement policy of the Bureau of Energy in Taiwan, the annual power generation of all small wind turbine locations in this study is higher than the annual sales cap (1650kWh/kW), so the payback period is 13 years. If there is no electricity sales cap, the payback period can be shortened to 6~12 years. From the standpoint of economic investment, all the locations mentioned above are very valuable for wind energy development.
From the perspective of power supply, 2.5 kW rooftop small wind turbine can only support a small amount of lighting or small-load project power consumption for construction purposes such as service industry, public institutions, or colleges. It implied the 2.5 kW rooftop small wind turbine is suitable for promoting green energy. The use of 15kW ground-type small wind turbines can support more than 35% of lighting power in service industries, public institutions or educational organizations. The power generation of the 15kW ground-type small wind turbines can supply the residential electricity. The annual power generation of 15kW small wind turbines can also support the electricity consumption of 5 to 10 households, as well as the 2.5kW rooftop small wind turbines can fully support the annual electricity consumption of 1 household. From the perspective of seasonal changes, 2.5kW rooftop small wind turbines can fully support residential electricity consumption in the autumn and winter months (January and October). However, in spring and summer months (April and July) the power generation is insufficient (The monthly power generation is less than half of that in autumn and winter). It needs the support of other power supply systems to stabilize the supply of residential electricity. The main challenge of the 2.5kW rooftop small wind turbine is that the trend of its hourly generation is opposite to the electricity consumption. For the spots with the highest power generation, the residential power consumption peaks between 6 p.m. to 1 a.m. and nearly meets the power generation. Therefore, the deployment of power supply and intellectual energy storage technology to maintain power supply stability will help the operation of small wind turbines in urban area.
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