Simulation of Variable Air Volume System with Different Duct Layout

The duct static pressure reset (DSPR) control method is a popular modern control method widely applied to variable air volume (VAV) systems of commercial buildings. In this paper, a VAV system simulation program was used to predict the system performance and zone air temperature of two kinds of layouts that were applied to a typical floor of an existing building office in Hong Kong. The position where the static pressure sensor was placed should affect the zones temperature and energy consumption. The comparison of predictions of the two kinds of layouts indicates that with the same DSPR control method the layout of the air duct might influence the fan control result and energy savings.

Design of Control Scheme for Variable Air Volume Air- conditioning System

The air quantity of variable air volume system for the rooms and the total air quantity of the system changes with the change of room load. Combined with the system composition in the laboratory, the paper determines the control scheme of the variable air volume system, that is, indoor temperature-control, indoor positive pressure control, air distribution static pressure control, air-supply temperature control and new air volume control. The dotted lines with arrows mean the output signals from the control unit to actuator, and the solid lines with arrows represent the input signals from the actuator to the control unit.

Genetic Optimization Algorithm of PID Decoupling Control for VAV Air-Conditioning System

Variable-air-volume (VAV) air-conditioning system is a multi-variable system and has multi coupling control loops. While all of the control loops are working together, they interfere and influence each other. A multivariable decoupling PID controller is designed for VAV air-conditioning system. Diagonal matrix decoupling method is employed to eliminate the coupling between the loop of supply air temperature and that of thermal-space air temperature. The PID controller parameters are optimized by means of an improved genetic algorithm in floating point representations to obtain better performance. The population in the improved genetic algorithm mutates before crossover, which is helpful for the convergence. Additionally the micro mutation algorithm is proposed and applied to improve the convergence during the later evolution. To search the best parameters, the optimized parameters ranges should be amplified 10 times the initial ideal parameters. The simulation and experiment results show that the decoupling control system is effective and feasible. The method can overcome the strong coupling feature of the system and has shorter governing time and less over-shoot than non-optimization PID control.

On Multi-Timescale Variability of Temperature in China in Modulated Annual Cycle Reference Frame

The traditional anomaly （TA） reference frame and its corresponding anomaly for a given data span changes with the extension of data length. In this study, the modulated annual cycle （MAC）, instead of the widely used climatological mean annual cycle, is used as an alternative reference frame for computing climate anomalies to study the multi-timescale variability of surface air temperature （SAT） in China based on homogenized daily data from 1952 to 2004. The Ensemble Empirical Mode Decomposition （EEMD） method is used to separate daily SAT into a high frequency component, a MAC component, an interannual component, and a decadal-to-trend component. The results show that the EEMD method can reflect historical events reasonably well, indicating its adaptive and temporally local characteristics. It is shown that MAC is a temporally local reference frame and will not be altered over a particular time span by an exten-sion of data length, thereby making it easier for physical interpretation. In the MAC reference frame, the low frequency component is found more suitable for studying the interannual to longer timescale variability （ILV） than a 13-month window running mean, which does not exclude the annual cycle. It is also better than other traditional versions （annual or summer or winter mean） of ILV, which contains a portion of the annual cycle. The analysis reveals that the variability of the annual cycle could be as large as the magnitude of interannual variability. The possible physical causes of different timescale variability of SAT in China are further discussed.

Opposing Trends of Winter Cold Extremes over Eastern Eurasia and North America under Recent Arctic Warming

Under recent Arctic warming,boreal winters have witnessed severe cold surges over both Eurasia and North America,bringing about serious social and economic impacts.Here,we investigated the changes in daily surface air temperature(SAT)variability during the rapid Arctic warming period of 1988/89–2015/16,and found the daily SAT variance,mainly contributed by the sub-seasonal component,shows an increasing and decreasing trend over eastern Eurasia and North America,respectively.Increasing cold extremes(defined as days with daily SAT anomalies below 1.5 standard deviations)dominated the increase of the daily SAT variability over eastern Eurasia,while decreasing cold extremes dominated the decrease of the daily SAT variability over North America.The circulation regime of cold extremes over eastern Eurasia(North America)is characterized by an enhanced high-pressure ridge over the Urals(Alaska)and surface Siberian(Canadian)high.The data analyses and model simulations show the recent strengthening of the high-pressure ridge over the Urals was associated with warming of the Barents–Kara seas in the Arctic region,while the high-pressure ridge over Alaska was influenced by the offset effect of Arctic warming over the East Siberian–Chukchi seas and the Pacific decadal oscillation(PDO)–like sea surface temperature(SST)anomalies over the North Pacific.The transition of the PDO-like SST anomalies from a positive to negative phase cancelled the impact of Arctic warming,reduced the occurrence of extreme cold days,and possibly resulted in the decreasing trend of daily SAT variability in North America.The multi-ensemble simulations of climate models confirmed the regional Arctic warming as the driver of the increasing SAT variance over eastern Eurasia and North America and the overwhelming effect of SST forcing on the decreasing SAT variance over North America.Therefore,the regional response of winter cold extremes at midlatitudes to the Arctic warming could be different due to the distinct impact of decadal SST anomalies.

Spatial and Temporal Variability of PM_(2.5) Concentration in China

PM_（2.5） has become an increasing public concern recently because of its visibility reduction and severe health risks. For the whole year of 2013, hourly PM_（2.5） data of 496 monitoring sites scattered in 74 cities of China are collected to analyze temporal and spatial variability of PM_（2.5） concentration. Different temporal scales（seasonal variation, monthly variation and daily variation） and spatial scales（urban versus rural, typical areas and national scale） are discussed. Results show that PM_（2.5） concentration changes significantly in both long-term and short-term scales. An apparent bimodal pattern exists in daily variation of PM_（2.5） concentration and the daytime peak appears around 10：00 am while the lowest concentration appears around 16：00 pm. Spatial autocorrelation analysis and Ordinary Kriging are used to characterize spatial variability. Moran＇s I of PM_（2.5） concentration in three typical regions, the Beijing-Tianjin-Hebei region, the Yangtze River Delta region and the Pearl River Delta region, is 0.906, 0.693, 0.746, respectively, which indicates that PM_（2.5） is strong spatial correlated. Spatial distribution of annual PM_（2.5） concentration simulated by Ordinary Kriging shows that 7.94 million km2（83%） areas fail in meeting the requirement of China＇s National Ambient Air Quality Standards Level-2（35 mg/m3） and there are at least three concentrated highly polluted areas across the country.