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Atmospheric environmental capacity and urban atmospheric load in China's Mainland 被引量:8
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作者 XU DaHai WANG Yu ZHU Rong 《Science China Earth Sciences》 SCIE EI CAS CSCD 2018年第1期33-46,共14页
Daily and annual average atmospheric environmental capacity coefficient(A-value) sequences for China's Mainland are calculated from hourly data recorded at 378 ground stations over 1975–2014. A-values at differen... Daily and annual average atmospheric environmental capacity coefficient(A-value) sequences for China's Mainland are calculated from hourly data recorded at 378 ground stations over 1975–2014. A-values at different recurrence intervals are calculated by fitting the sequences to Pearson type III distribution curves. Based on these A-values and source-sink balance(reference concentration 100 μg m^(-3)), atmospheric environmental capacities at the recurrence intervals are calculated for all of China's Mainland and each provincial administrative region. The climate average atmospheric environmental capacity reference value for the entire mainland is 2.169×10~7 t yr^(-1). An urban atmospheric load index is defined for analyses of the impact of population density on the urban atmospheric environment. Analyses suggest that this index is also useful for differentiating whether air quality changes are attributable to varying meteorological conditions or variations of artificial emission rate.Equations guiding the control of unorganized emission sources are derived for preventing air quality deterioration during urban expansion and population concentration. 展开更多
关键词 Atmospheric environmental capacity Pearson type III distribution Recurrence interval Urban atmospheric load index Emission rate density
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Energy Management System Design and Testing for Smart Buildings Under Uncertain Generation (Wind/Photovoltaic) and Demand
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作者 Syed Furqan Rafique Jianhua Zhang +3 位作者 Muhammad Hanan Waseem Aslam Atiq Ur Rehman Zmarrak Wali Khan 《Tsinghua Science and Technology》 SCIE EI CAS CSCD 2018年第3期254-265,共12页
This study provides details of the energy management architecture used in the Goldwind microgrid test bed. A complete mathematical model, including all constraints and objectives, for microgrid operational management ... This study provides details of the energy management architecture used in the Goldwind microgrid test bed. A complete mathematical model, including all constraints and objectives, for microgrid operational management is first described using a modified prediction interval scheme. Forecasting results are then achieved every 10 min using the modified fuzzy prediction interval model, which is trained by particle swarm optimization.A scenario set is also generated using an unserved power profile and coverage grades of forecasting to compare the feasibility of the proposed method with that of the deterministic approach. The worst case operating points are achieved by the scenario with the maximum transaction cost. In summary, selection of the maximum transaction operating point from all the scenarios provides a cushion against uncertainties in renewable generation and load demand. 展开更多
关键词 microgrid economic optimization generation forecast load forecast energy management system fuzzy prediction interval heuristic optimization
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