Defrosting at evaporator panel is one of working cycles in freezer. Power consumption in defrosting does not meet the objective of using freezer therefore the approach to decrease power consumption in defrosting is one strategy for energy saving. Normally the cycle of defrosting in freezer is a constant time that specify by referring to the highest humidity period. With this control concept the problem of temperature exchange is not occurred from ice accumulation at evaporator panel but it makes the over necessity of defrosting process in the low humidity season and cause the unnecessary power usage in freezer. This research presents the control approach for defrosting by using the difference of the temperature at evaporator and the temperature at chilling area. By using this approach the defrosting process is operated depend on load and the fan is on or off relate to defrosting time. Test results demonstrate that about 12% of power can be saved by this control approach when compared to constant time control.

The objectives of this research were to propose a model with some functions including CAR spatial effects and to select a proper model for predicting rince and rubber yields in southern provices of Thailand. A linear mixed model (LMM) with spatial effects and dummy varables and Fourier seasonal effects was proposed. Bayesian estimation was used and the estimated rice and rubber yields were used for prediction. The dependent variables were rice and rubber yields in southern provinces of Thailand. Factors considered were rain temperature soil fertilizer soil organic matter trend and also sesonal effects. The results show that rain temperature soil fertilizer soil organic matter trend and sesonal effects influence on rice and rubber yields. The proposed model with Fourier seasonal term is the most appropriate comparing to the model with dummy variable for season effects and the Holt-Winters model. Therefore the proposed model with Fourier sesaonal term should be the first consideration for prediction.

The objectives of this research were to propose a spatial analysis using Bayesian generalized linear mixed model for predicting drought in Thailand. The spatial effect was assumed to be a conditional autoregressive model (CAR model). The dependent variables was a drought or non-drought occurrence which was assumed to have a Bernolli distribution with logistic link function. Factors considered were rain temperature number of rainy days number of large reservoirs and number of medium reservoirs. The results show that the rain temperature number of rainy days number of large reservoirs and number of medium reservoirs influence on the drought occurrence. This study is useful for planning making decision preventing and remedying the drought problem.

The objectives of this research were to create a model for time sereries data prices and yields of natural rubber to be more accurate prediction and to compare the proposed model with the classical time series models such as the Holt-Winters Additive Exponential smoothing model (Holt-Winters ES) and the seasonal autoregressive integrated moving average model (SARIMA). The proposed model was a linear mixed model (LMM) consisting with trend autoregression outliers and sesonal terms. Dummy varialbles and Fourier seasonal effects were studied. Bayesian estimation was used and the estimated prices and yields were used for prediction. The results show that the proposed model with a Fouries seasonal effect is the most appropriated comparing with the dummy seasonal effect the Holt-Winters ES and the SARIMA having the least mean absolute values (MAE) both fiting and validating parts. The proposed model with sesaonal dummy variables should be the first consideration for forecasting spatial time series with a seasonal component.

This research project presents about wind turbine simulation for connected single phase grid system using hysteresis current control technique to generate PWM signals for controlling a single-phase voltage source inverter. The simulation system presented here uses the program. MATLAB/Simulink in the simulation of the wind turbine connected to the shaft of a three-phase permanent magnet generator is produced by alternating current through the full bridge rectifier circuit. Then the power supply is applied to the single-phase inverter circuit which is connected to the single-phase autotransformer to power transfer to the single-phase grid system. The simulation results confirm the validity of the proposed system with satisfaction under various conditions.