COGS Thesis and Dissertations

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https://irepository.uniten.edu.my/handle/123456789/10212

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Ecological and condition-based assessment for mini hydro life extension in Peninsular Malaysia
(2022-04)
Mohamad Faizal Basri Nair, Mr.
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With major emerging trends like demographic change, population increase, and industrial growth, it is time to rethink strategies and to embark on renewable energy resources as an important source of energy amongst the energy mix in Peninsular Malaysia. Mini hydropower based on run-of-river systems is one such source [1]. In 2012, there were thirty-nine units of mini hydro plants in Peninsular Malaysia [2] and a significant fraction of these plants' equipment inventory is approaching an initial design life of over forty (40) years by 2021. A condition-based assessment is essential to monitor effective functioning of the equipment to identify and suggest ways to improve functional quality and reliability of the plants. This paper entitled, “Ecological and Condition-Based Assessment for Mini Hydro Life Extension in Peninsular Malaysia,” aims to identify the current status and actual conditions of operational and non-operational plants. Twenty plants located in the states of Peninsular Malaysia are identified for this study. The assessment is based on civil and electro-mechanical structures and components of mini hydropower plants namely, turbine, generator, pressurized water conveyance, intake, governor, exciter and raw water system. The renewable energy analysis tool, RETScreen Expert, is used as the software to perform desired computations for verification of current power output of the small hydropower project. The overall findings shall help to determine the plants’ strengths and weaknesses based on the performance indicators. It shall serve as a platform to plug this sector back into Peninsular Malaysia’s electricity grids and clinch the 20% target set for 2025, besides dominating the renewable energy market.
Performance evaluation of gross pollutant trapping devices versus life cycle cost for best pollutant management practices in Klang River basin
(2021-12)
Nur Farazuien Binti Md Said, Ms.
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Due to rapid and uncontrolled development in Sg Klang, it leads to the production of increased amounts of waste material and garbage. Sg Klang has been identified as major contributor of waste that contributes over 67,000 metric tonnes of floating waste from 2016 until 2020. Thus, government has installed 119 units of Gross Pollutant Trap (GPT) in Sg Klang as a initiatives to trap gross pollutants from getting into the river system under River of Life (ROL) Project. ROL project is a project under the Economic Transformation Program (ETP) by the Malaysia Government, to reach greater Klang valley by transforming Sg Klang into a vibrant and liveable waterfront by 2020. In achieving this target, three components of the transformation program have been set up for Sg. Klang and the main tributaries within ROL area namely river cleaning, river beautification, and property development. Installation of GPT is one of the components under river cleaning component. Fundamentally, GPT is an engineered sediment trap built to capture stormwater and rising flow energy through its self-cleaning capacity. However, it was found that the GPT design criteria, efficiencies as well as operation and maintenance including life cycle cost (LCC) and cost effectiveness ratio (CER) of available GPT based on local data and experience are limited in information. Therefore, this study aims to evaluate the performance of GPTs in terms of wet load by 5 types of proprietary GPTs from 3 different types of land use (Residential, Commercial and Mix Development; to characterize gross pollutants trapped by 5 types of proprietary GPTs from 3 different types of land use at selected locations and to quantify life cycle costs (LCC) and cost effectiveness ratio (CER) with 5 types of proprietary GPTs. The study area includes 5 sub-catchments under ROL project, namely Sg Klang, Sg Kemensah, Sg Gisir and Sg Sering. The data collection is sourced from Pejabat Lembangan Sg Klang (PLSK) during the GPT maintenance every month. The wet load then stored in plastic bag and immediately weighed and recorded by following the ASCE standard method. The gross pollutant characterization was done at 14 selected sampling locations based on the amount of gross pollutant trapped in the GPT and the site suitability, which is availability of open space to conduct the sorting process. The gross pollutant trapped is sorted into its respective categories, then measured in terms of weight based on different landuse. Furthermore, this study takes into consideration the associated cost with regard to LCC and CER of installed GPTs in the study area. The highest annual gross pollutant wet load captured by year is from Sg Klang, with the value of 20372.5 kg/ha/yr for year 2015 and 17112.3 kg/ha/yr for year 2016. Total number of GPTs installed in this study area is 59, and most of the GPTs were installed in the residential area. In terms of gross pollutant characterization ̧ it shows a significant trend for residential area, where 72% of gross pollutants trapped in GPTs is vegetation due to surrounding trees around the residential area. In contrast, for commercial area, it was found that sediments has the most highest proportion for all sampling location, with a percentage range from 53% to 96% from 3 sampling locations. From the analysis, LCC of GPTs in the study area is ranging from RM 113,130 to RM 297,086 and RM 138,092 to RM 403,622 for project duration of 10 years and 20 years respectively. For CER analysis, in average NTVS is having a lowest average CER with value of RM 36.65 per kg per year manual method. However, it is found that GPT/SK/CDS/94 is having the lowest CER out of 119 proprietary GPTs with value of RM105.97. Additionally, the GPT inventory database for all catchment has been developed for future reference and will be uploaded into web based ArcGIS Online System and assist the authority through the GPT knowledge database system (DeGPTs) as well added value to the technical reference for MSMA Guidelines Chapter 10 enable better management of gross pollutant traps, in terms of cost and maintenance. Ultimately, the data and result obtained in this study provides information that can help future decision for GPTs installation and maintenance program and assist the engineers and local authorities to implement appropriate strategies for trapping gross pollutants in urban area, in terms of management and preparing budget allocation for GPTs operation & maintenance.
Vegetation detection using a hybrid method of vegetation indices and convolutional neural network
(2021-11)
Lim Soon Eng, Mr.
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Vegetation inspection and monitoring is time-consuming. Unmanned aerial vehicle (UAV) or drone can be used for the tasks but most drones has limited spectral bands (such as RGB camera) which restricts advanced vegetation analysis. Additional spectral bands can produce more accurate analysis but are costly. Vegetation indices (VI) is a technique to maximize detection sensitivity related to vegetation characteristics while minimizing others. Machine learning (ML) may also improve detection accuracy in vegetation analysis. This study explores VI techniques in identifying vegetation objects including hybrid VI and ML to overcome the limitation of existing VI techniques. The hybrid methods were analysed and evaluated to find the strengths and limitations to improve detection accuracy. Several VI methods such as Visible Atmospheric Resistant Index (VARI), Green Leaf Index (GLI), and Vegetation Index Green (VIgreen) were combined with the ML technique; You Only Look Once (YOLO). Data for testing were collected from aerial images of a number of locations. Hybrid segmentation, a process to divide the targeted pixels and then eliminate the non-vegetation pixel in the image were performed. Selected VI techniques were applied on several objects of the same images with varied performance. The performance of hybrid methods developed in this study was measured by the accuracy of vegetation detection. The results obtained showed that >70% of the vegetation objects in the images were accurately detected. The hybrid segmentation has generally increased the accuracy compared to the initial hybrid method. Mixture of VARI and YOLO in hybrid segmentation method performs best at 84% detection accuracy. GLI and YOLO on the other hand, gave 81% detection accuracy and VIgreen with YOLO gave 78% detection accuracy. There are several limitations with the proposed methods identified throughout the experiments. GLI + YOLO combination is less sensitive in detecting tiny tree and occasionally misdetect tree shadow as vegetation. Despite the limitations, hybrid segmentation shows an improvement in reducing misdetection of greenfield as vegetation compared to the initial hybrid method. Overall, the proposed hybrid segmentation method and hybrid detection method have the ability to better detect vegetation objects from aerial images data, as compared to the VI techniques alone.
Investigation on the location and sizing for solar PV using LQ_LT index and exact loss formula for heavily loaded transmission systems
(2022-05)
Mohamad Razin Naim Mohd Alias, Mr.
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Voltage stability indices (VSI) are indicators that have been developed to identify weak buses in the power system. Maintaining voltage within safe operating limits at each bus is crucial to avoid voltage collapse. Integrating renewable distributed generation (DG) into the system can help maintain the voltage within the security limits during congestion and heavy loading. The first objective is to investigate the performance of reactive power tracing capable index, named LQP_LT in identifying the weak load buses that are present in IEEE 14 bus and IEEE 30 bus systems. All the simulations were carried out using MATLAB via MATPOWER optimal power flow. The LQP_LT index incorporates proportional sharing methods to identify the weak load buses and generates a priority ranking list. The identification of weak buses was done by creating a contingency scenario whereby simulations carried out on heavily loaded buses. The performance of the LQP_LT index was validated by comparing the ranking results obtained with other established voltage stability indices, namely, FVSI, NLSI and VSLI. In addition, the weak load buses identified via LQP_LT were also compared with the exact loss formula. The second objective is to determine the sizing for solar PV placement using exact loss formula. In the literature, the exact loss formula is also capable to determine the location and sizing for solar PV. Results obtained highlight that both LQP_LT and the exact loss method have consistent data regarding on bus allocated for PV installation results for the solar PV placements. Moreover, the utilization of solar PV has significantly improved the overall system voltage stability. In the IEEE 14 bus system, voltage per unit for bus 14 is enhanced by 0.74% at a loading factor of 1.90. In the IEEE 30 bus system, bus 8 voltage level was improved by 11.17 % at a loading factor of 1.60. Solar PV also helps in reducing the transmission losses available at the critical branch. For instance, the percentage of reactive loss lessened in branch 14 (bus 7 and bus 8) in the IEEE 14 bus system at maximum loading is 15.7%. On the other hand, for the IEEE 30 bus system, branch 2 (bus 1 and bus 3) at maximum loading (load factor 1.60) had its reactive losses reduced by 43.83% with the assistance of solar PV.
Estimation and forecasted water demand for consumption at Kenyir Lake, Terengganu
(2022-01)
Nor Najwa Irina Binti Mohd Azlan, Ms.
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Lake is one of the water sources that has a vast variety of economic potential including water supply, water-based recreational activities, and fishing activities. Kenyir Lake in Terengganu has benefited the country economically due to its numerous functions as a water body. Rapid development within Kenyir Lake caused higher water demand and lowering the water quality. To ensure the sustainability of water usage for activities and development within Kenyir Lake, this study aims to estimate water demand study using Micro-Component Analysis (MCA) method. In line with water requirements in Malaysia, water demand is also estimated using Suruhanjaya Perkhidmatan Air Negara (SPAN) Guidelines. The methods of MCA and SPAN Guidelines implement detailed parameters of activities and development at Kenyir Lake. Results of estimated water demand at Kenyir Lake using MCA and SPAN Guidelines are 1250.0 m3/day and 1254.1 m3/day respectively. The value of total water demand estimated using SPAN Guidelines was slightly higher than MCA since the average daily water demand adopted has been standardised by SPAN according to the type of premises. The second purpose of the study is to forecast the estimated water demand (MCA and SPAN Guidelines) using Fuzzy Inference System (FIS) and Multiple Linear Regression (MLR). The purposes of these forecasts were conducted to validate the amount of water demand estimated and to establish the relationship between variables used. Water demand values for houseboats from FIS-Micro-Component Analysis, FIS-SPAN Guidelines, MLRMicro-Component Analysis, and MLR-SPAN Guidelines were found to be 350.0 m3/day, 425.0 m3/day, 622.2 m3/day and 718.8 m3/day respectively. The third aim of the study was to compare estimated water demands (MCA and SPAN Guidelines) and forecasted water demands (FIS and MLR) using statistical evaluations. The estimated water demands are compared with metered water by Syarikat Air Terengganu (SATU) conducted at Pengkalan Gawi, Kenyir Lake. Results of Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE) were found lower in SPAN Guidelines at 18.02, 1947.60, and 44.13 respectively than Micro-Component Analysis. The forecasted water demands (FIS and MLR) compared with estimated water demand (MCA) resulted in lower MAD, MSE, and RMSE at 8.96, 244.97, and 15.65 respectively for MLR. MCA and MLR are more prone in estimating and forecasting water demand at Kenyir Lake. Although the forecasting error for MCA is slightly higher than SPAN Guidelines, the method is better because of the detail parameters considered. The outcomes of the study are beneficial to SATU in ensuring the amount of water supply always meet the demand. Also, the methods applied in this study can be implemented by SATU to revise the water demand at Kenyir Lake regularly. Finally, government can encourage premises owners to practice rainwater harvesting to balance the water sources available at Kenyir Lake.

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