• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.12 no.4
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• pp.354-362
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• 2000

Optimal supervisory control strategy for the set points of controlled variables in the central cooling system has been studied by computer simulation. A quadratic linear regression equation for predicting the total cooling system power in terms of the controlled and uncontrolled variables was developed using simulated data collected under different values of controlled and uncontrolled variables. The optimal set temperatures such as supply air temperature, chilled water temperature, and condenser water temperature, are determined such that energy consumption is minimized as uncontrolled variables, load, ambient wet bulb temperature, and sensible heat ratio, are changed. The chilled water loop pump and cooling tower fan speeds are controlled by the PID controller such that the supply air and condenser water set temperatures reach the set points designated by the optimal supervisory controller. The influences of the controlled variables on the total system and component power consumption was determined. It is possible to minimize total energy consumption by selecting the optimal set temperatures through the trade-off among the component powers. The total system power is minimized at lower supply, higher chilled water, and lower condenser water set temperature conditions.

• Water for future
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• v.9 no.2
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• pp.87-100
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• 1976

These studies are aimed at the analysis of systematic variation pattern of water resources in Korean river catchments and the development of their simulation models from the stochastic analysis of monthly and annual hydrologic data as main elements of water resources, i.e. rainfall and streamflow. In the analysis, monthly & annual rainfall records in Soul, Taegu, Pusan and Kwangju and streamflow records at the main gauging stations in Han, Nakdong and Geum river were used. Firstly, the systematic variation pattern of annual streamflow was found by the exponential function relationship between their standard deviations and mean values of log-annual runoff. Secondly, stochastic characteristics of annual rainfall & streamflow series were studied by the correlogram Monte Carlo method and a single season model of 1st-order Markov type were applied and compared in the simulation of annual hydrologic series. In the simulation, single season model of Markov type showed better results than LN-model and the simulated data were fit well with historical data. But it was noticed that LN-model gave quite better results in the simulation of annual rainfall. Thirdly, stochastic characteristics of monthly rainfall & streamflow series were also studied by the correlogram and spectrum analysis, and then the Model-C, which was developed and applied for the synthesis of monthly perennial streamflow by lst author and is a Markov type model with transformed skewed random number, was used in the simulation of monthly hydrologic series. In the simulation, it was proved that Model-C was fit well for extended area in Korea and also applicable for menthly rainfall as well as monthly streamflow.