Solar chimney power plant is a sustainable alternative for electricity generation using solar as the source of energy. In general, the main body of a solar chimney plant requires a tall structure which is costly and challenging to construct. Thus, it is important to increase the performance of the solar chimney power plant and have a better energy-cost ratio. This study aims to experimentally investigate the influence of divergent solar chimney as opposed to a cylindrical chimney on solar chimney performance. Three divergent scaled-down solar chimney model at 1-meter, 1.5-meter and 2-meter were fabricated and tested for its performance at various simulated heat loads. The test results were compared with similar heights cylindrical solar chimney. The experiments show that divergent solar chimney increases the theoretical power generation potential and improves the stalk effect and have higher outlet velocity compared to a cylindrical solar chimney. The power potential of the divergent chimney is increased up to 18 times with the maximum theoretical power obtain at 0.183W on the 2-meter divergent chimney. Higher temperature was recorded on the 2-meter divergent chimney outlet at 341.3k compared to 330.4k on the cylindrical chimney indicates better stack effect. The highest average velocities in the divergent and cylindrical chimneys were recorded under the electric heat load of 2 kW at 0.994 m/s and 0.820 m/s respectively in the 1-meter configuration. It is also observed that the air velocity in a shorter divergent chimney is higher than taller divergent chimney models while better compared to all cylindrical height. This study finds that a shorter divergent solar chimney produces greater energy compared to a higher cylindrical solar chimney. Therefore, it is possible to reduce the overall cost of solar chimney by reducing the height of the main structure without sacrificing the performance of the solar chimney.

This experimental study aimed to determine the effect of airflow velocity on the performance of a direct evaporative cooling system. Rectangular-shaped honeycomb cooling pads with a length of 34 cm, a width of 25 cm, and a thickness of 3.5 cm are used as cooling media. The main parameters of the study are low air velocity (2.3 ms−1), medium (3.2 ms−1), and high velocity (3.7 ms−1). The data collected include dry bulb temperature, wet bulb temperature, output air temperature, input and output air velocity, input and output humidity, and solar radiation. These data are used to determine saturation efficiency, cooling capacity, temperature decreases, and feasibility index. The experimental results are presented in the form of tables and graphs and analysed based on existing theories. The results showed that the evaporative cooling system could produce output temperatures up to 27.5°C with input 31.4°C at low airspeed, 27.97°C with input 31.47oC at medium speed, and 27.7°C with input 31.30°C at high air speed. It was concluded that a low airflow rate would add to the cooling efficiency, and the higher the airflow rate, the lower the cooling efficiency. The results showed that evaporative cooling is achievable with a feasibility index of 19.89 ≤ F*≤ 20.67. The results also affirmed that cooling capability is higher where the feasibility indexes are comparatively low.

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The quantity of palm oil fruits supplied from palm oil estates often affects the number of workers required and the area to be harvested. Thus, the ultimate objective of this research is to develop a system to forecast monthly delivery quantities such that the companys profit will increase through proper balance between supply and demand. This research is limited to 10 years of monthly deliveries from a palm oil estates deliver to only one palm oil mill as the case study. Two forecast techniques were chosen; the linear regression and additive forecast methods. Based on theories and formulations of the selected forecast techniques, forecast software was developed. For this software, user only needs to specify the year to be forecasted and choose one forecast technique to be used. Then, the forecasted values and errors were calculated and the results were displayed on the GUI. The performance of each technique was compared based on the mean absolute percentage error (MAPE). The generated results showed that the additive method produced lower MAPE compared to the linear regression method. This proved that the additive method is a better technique to predict the monthly delivery quantities of the palm fruits by the estate.