The objective of this study was to develop an adaptive thermal comfort equation for naturally ventilated buildings in hot-humid climates. The study employed statistical meta-analysis of the American Society of Heating...The objective of this study was to develop an adaptive thermal comfort equation for naturally ventilated buildings in hot-humid climates. The study employed statistical meta-analysis of the American Society of Heating, Refrigerating and Air-Conditioning Engineers （ASHRAE） RP-884 database, which covered several climatic zones. The data were carefully sorted into three climate groups including hot-humid, hot-dry, and moderate and were analyzed separately. The results revealed that the adaptive equations for hot-humid and hot-dry climates were analogous with approximate regression coefficients of 0.6, which were nearly twice those of ASHRAE and European standards 55 and EN15251, respectively. The equation using the daily mean outdoor air temperature had the highest coefficient of determination for hot-humid climate, compared with other mean temperatures that considered acclimatization of previous days. Acceptable comfort ranges showed asymmetry and leaned toward operative temperatures below thermal neutrality for all climates. In the hot-humid climate, a lower comfort limit was not observed for naturally ventilated buitdings, and the adaptive equation was influenced by indoor air speed rather than indoor relative humidity. The new equation developed in this study can be applied to tropical climates and hot humid summer seasons of temperate climates.展开更多
Photovoltaic technologies provide significant capacity to electric grids,however,resource variability and production uncertainty complicate power balancing and reserve management.A crucial step in predicting solar gen...Photovoltaic technologies provide significant capacity to electric grids,however,resource variability and production uncertainty complicate power balancing and reserve management.A crucial step in predicting solar generation is determining clear-sky irradiance.Clear-sky attenuation can be modeled using broadband atmospheric turbidity factors,but model accuracy is dependent on the measurements used to determine the current and future state of aerosol loading and water vapor content,which requires close proximity measurements,in time and space,to account for turbidity variability.Such measurements,though,are only available in near real-time at a limited,and decreasing,number of sites.This paper proposes a new method for estimating time-varying local turbidity conditions from more readily available pyranometer or PV output data.The method employs a long short-term memory recurrent neural network to distill the turbidity-driven signal from global irradiance(or global irradiance driven)observations,despite an inherent dampening issue.The method is developed to operate in near real-time for solar forecasting applications.Validation examines the ability of the method to(1)reproduce turbidity estimates derived from historical measurements of beam irradiance under clear-sky conditions;and(2)provide input for clear-sky models in the form of persistence forecasts generated from daily mean values.展开更多
文摘The objective of this study was to develop an adaptive thermal comfort equation for naturally ventilated buildings in hot-humid climates. The study employed statistical meta-analysis of the American Society of Heating, Refrigerating and Air-Conditioning Engineers （ASHRAE） RP-884 database, which covered several climatic zones. The data were carefully sorted into three climate groups including hot-humid, hot-dry, and moderate and were analyzed separately. The results revealed that the adaptive equations for hot-humid and hot-dry climates were analogous with approximate regression coefficients of 0.6, which were nearly twice those of ASHRAE and European standards 55 and EN15251, respectively. The equation using the daily mean outdoor air temperature had the highest coefficient of determination for hot-humid climate, compared with other mean temperatures that considered acclimatization of previous days. Acceptable comfort ranges showed asymmetry and leaned toward operative temperatures below thermal neutrality for all climates. In the hot-humid climate, a lower comfort limit was not observed for naturally ventilated buitdings, and the adaptive equation was influenced by indoor air speed rather than indoor relative humidity. The new equation developed in this study can be applied to tropical climates and hot humid summer seasons of temperate climates.
基金This work was funded by the Office of Naval Research(ONR),United States under the Asia Pacific Research Initiative for Sustainable Energy Systems(APRISES)project,Grant Award Number N00014-16-1-2116by the U.S.Department of Energy,United States under the U.S.-India collAborative for smart diStribution System wIth STorage(UI-ASSIST)project,Award Number DE-IA0000025.
文摘Photovoltaic technologies provide significant capacity to electric grids,however,resource variability and production uncertainty complicate power balancing and reserve management.A crucial step in predicting solar generation is determining clear-sky irradiance.Clear-sky attenuation can be modeled using broadband atmospheric turbidity factors,but model accuracy is dependent on the measurements used to determine the current and future state of aerosol loading and water vapor content,which requires close proximity measurements,in time and space,to account for turbidity variability.Such measurements,though,are only available in near real-time at a limited,and decreasing,number of sites.This paper proposes a new method for estimating time-varying local turbidity conditions from more readily available pyranometer or PV output data.The method employs a long short-term memory recurrent neural network to distill the turbidity-driven signal from global irradiance(or global irradiance driven)observations,despite an inherent dampening issue.The method is developed to operate in near real-time for solar forecasting applications.Validation examines the ability of the method to(1)reproduce turbidity estimates derived from historical measurements of beam irradiance under clear-sky conditions;and(2)provide input for clear-sky models in the form of persistence forecasts generated from daily mean values.
