An improved method for predicting seasonal and annual shadowing from cooling tower plumes |
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| Institution: | 1. Department of Chemical Engineering Technology, Faculty of Engineering Technology, University Malaysia Perlis, 02100, Padang Besar, Perlis, Malaysia;2. Centre of Excellence for Biomass Utilization, School of Bioprocess Engineering, Universiti Malaysia Perlis, 02600, Arau, Perlis, Malaysia;3. School of Bioprocess Engineering & Institute of Nano Electronic Engineering, Universiti Malaysia Perlis, Perlis, Malaysia;4. Center for Renewable Energy, STT-PLN, Jalan Lingkar Luar Barat Kosambi, Jakarta, 11750, Indonesia;5. Biotech Consultants Limited (BTCL), 263 Frimley Green Road, Camberley, Surrey, GU16 6LD, UK;6. Bioenvironmental Engineering Research Center, Department of Biotechnology Engineering, Faculty of Engineering, International Islamic University Malaysia, 50728, Gombak, Kuala Lumpur, Malaysia;1. Tianjin Key Laboratory of Indoor Air Environmental Quality Control, School of Environmental Science and Technology, Tianjin University, 92 Weijin Road, Nankai District, Tianjin 300072, China;2. Key laboratory of Efficient Utilization of Low and Medium Grade Energy (Tianjin University), Ministry of Education, Tianjin 300072, China;3. Graduate School of Life and Environmental Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki 305-8572, Japan |
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| Abstract: | An improved model developed at Argonne National Laboratory and the University of Illinois (ANL/UI) for predicting long-term shadowing due to cooling tower plumes is presented, and its assumption are compared with those used in previous models. The model is based on a method for the selection of representative categories of similar plumes developed by Dunn and Policastro (Dunn, 1980, Proc. IAHR Cooling Tower Workshop, San Francisco; Policastro et al., 1984, Report EPRI CS-3403-CCM). At a given site this method reduces the large number of meteorological data cases in a season or year to a much smaller number (≈35) of representative cases, each of which will have a predicted plume substantially different from the others. Plume predictions for the reduced set of category representative cases are then made with the validated ANL/UI plume model. With category representative plume shape, wind speed, wind direction and sun angles available for each hour, full effects of sun angles for the latitude and longitude of the site to be studied are included. The ANL/UI model yields seasonal and annual isopleths of hours of additional shadowing or of percentage reduction in total and direct solar energy arriving at the ground on a horizontal surface. Results for two hypothetical sites with 500 MWe generating capacity are presented and contrasted, one at Syracuse, NY, and the other at Spokane, WA. |
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