Mahmod Othman

Mathematical modelling of a finned bi-fluid type photovoltaic/thermal (PV/T) solar collector

The results of integrating photovoltaic (PV) cells and solar thermal components are found attractive. This type of solar collector is known as a hybrid-PV system or photovoltaic/thermal (PV/T) solar collector. In the development of a PV/T solar collector, mathematical model and simulation play important roles due to the design and environmental parameters dependency of the performance of the collector. In this study, two dimensional (2D) steady state thermal modelling of a finned bi-fluid type photovoltaic/thermal (PV/T) solar collector is discussed. For the thermal model without the working fluids, the model is validated against the normal operating condition (NOCT) available from the manufacturers module datasheet. Meanwhile with the cooling element utilized, the model is validated against results from previous research. Using the validated model, the performance of the collector is simulated. When both fluids are to be operated simultaneously, at stagnant water and stagnant air, for radiation ranged from (500-800) W/m2, the average temperature of the PV cells is predicted to be approximately 20°C, 16°C and 14°C respectively lower in comparison to the system without cooling. The low average temperature of PV cells leads to the increase in cells efficiency. The overall energy efficiency of the collector is also predicted to be at almost 40 % higher owing to the additional thermal energy produced by the system over the same collector surface area. The PV/T solar collector discussed in this study has potential applications in various fields with the introduced fins will further enhance the heat transfer rate to the air flow. The 2D steady state analysis developed contributes to a more accurate prediction for the collector performance and optimization.

Fuzzy Index Poverty (FIP): Measuring poverty in rural area of Terengganu

Previously, several attempts have been made to find a suitable way of measuring poverty. The current practice in measuring poverty is based on assumption that the poor can be identified by determining a poverty line. As pointed out by Cerioli and Zani (1990) and by Cheli et al. (1994), among others, the problem is due to the fact that a sharp division of the total population between poor and non-poor is unrealistic. The traditional approaches usually assess the poverty status of an individual based solely on a unique indicator of such income or expenditure. Thus there is a need for an efficient poverty measures to be developed. Due to the weaknesses of traditional poverty measurement, the research introduces a composite of multidimensional poverty indicators. Data collected from the questionnaire on Household Income Survey/ Basic Amenities (HIS/ BA) year 2004 and 2007 which was conducted by the Department of Statistics Malaysia, Terengganu (DOS) were used. Fuzzy set was used to calculate poverty index to assess the living condition of households in rural areas of Terengganu. The results show that the use of Fuzzy Index Poverty on several poverty indicators provides a more complete picture of poverty than the traditional approach that use common indicators such as disposable income or expenditure.

Fuzzy Multi Criteria Evaluation for Performance of Bus Companies

A multi criteria decision making in ranking the bus companies using fuzzy rule is proposed. The proposed method uses the application of fuzzy sets and approximate reasoning in deciding the ranking of the performance of several bus companies. The proposed method introduces data normalization using similarity function which dampens extreme values that exist in the data. The use of the model is suitable in evaluating situation that involves subjectivity, vagueness and imprecise information. Experimental results are comparable to several previous methods.

Fuzzy similarity function for ranking river basin planning alternatives

Abstract A fuzzy evaluation method is proposed for the ranking of the river basin planning and development alternatives. The ranking of the alternatives involves subjectivity, vague and imprecise information is determined by utilizing the application of fuzzy membership sets and approximate reasoning. The method automatically generates membership function to develop the multicriteria combination rule. The aim of utilizing this rule is to capture the main criteria that exist in the alternatives. It is found that membership functions derived from the data explain the data pattern in a better way.

A Fuzzy Learning Algorithm for Harumanis Maturity Classification

This paper presents an approach to classify the fruit maturity of fruit grading system when a higher level of accuracy and easy interpretability of the estimate model is desired. The proposed method automatically generates membership functions (MFs) and constructs the associated fuzzy rules (FRs). The proposed approach is applied to a case study of Harumanis mango fruit grading system. The task is to classify the fruit maturity and grade using agronomic image data set acquired by digital camera. The parameters of the MFs are adjusted by the learning algorithm for the training data. This MF is then used to generate the MFbox using hyperbox-type fuzzy partition of feature space to generate FRs from training instance to deal with the features data. FRs are extracted from the flexible MFs and MFbox. As a case study, the proposed method is applied to Harumanis data set with 108 instances (input–output pairs), two real-valued inputs, and one output. Analysis results show that the proposed maturity classifier yields an accuracy of 98 %. The developed maturity classifier can act as an instrument in determining the correct mango fruit maturity category.

Bi-fluid Photovoltaic/Thermal PV/T Solar Collector with Three Modes of Operation: Experimental Validation of a Theoretical Model

This chapter discusses theoretical and indoor experimental studies of a bi-fluid type photovoltaic/thermal (PV/T) solar collector. Two-dimensional steady-state analysis was developed and computer simulations were performed using MATLAB. Experiments were conducted for steady-state analysis under the solar simulator at Solar Energy Research Lab UiTM, Perlis, Malaysia, and under real sky conditions of Northern Peninsular Malaysia, to validate the model. The solar collector and the test rig facilities were fabricated to be suitable for mathematical validation purposes in both indoor and outdoor testing. For indoor collector testing, at an average wind speed of 1 m/s and average solar radiation of 700 W/m2, the air and water mass flow rate was varied from 0.0074 to 0.09 kg/s and 0.0017 to 0.0265 kg/s respectively. The thermal efficiency increased as the mass flow rate increased. At a mass flow rate of 0.0262 and 0.0066 kg/s for air and water respectively, the thermal efficiency curves tended to plateau, which marked the optimum point of the fluid flow. For the simultaneous mode of fluid operation, testing was conducted with air and water fixed at a flow rate of 0.0262 and 0.0066 kg/s respectively, while the fluids’ mass flow rate was varied according to the range used during the independent mode. The range of the computed efficiencies for the simultaneous mode were higher than for the independent mode. In this study, collector outdoor testing was conducted for each mode of operation on a typical day in January in Perlis, Northern Peninsular Malaysia. Based on the outdoor monitoring analysis for simultaneous mode, the performance of the collector was also higher overall than the independent mode. The test was conducted by monitoring the performance of the collector with the air mass flow rate and water mass flow rate fixed at 0.0262 and 0.0066 kg/s respectively. Theoretical analysis was also performed and then validated against the experimental results by a direct comparison of the plotted curves and using mean absolute percentage error (MAPE) analysis. For the air, water and simultaneous modes, by taking into account both indoor and outdoor collector testing, the theoretical and experimental curves were found to be in good agreement, and the computed MAPE values for the fluids’ output temperature were less than 2 %. Thus, the two-dimensional mathematical model was proven valid. The PV/T collector designed in this study has a variety of applications because it can be operated in three different modes of fluid operation, and the theoretical model is useful in modelling all three modes without further modification.

Performance Analysis and Parametric Studies of a Bi-fluid Type Photovoltaic/Thermal (PV/T) Solar Collector in Simultaneous Mode Under Tropical Climate Conditions

Performance analysis of a photovoltaic/thermal solar collector with a bi-fluid configuration (air and water) was conducted under real sky conditions in the tropical climate of Perlis, Northern Peninsular Malaysia. In addition to the electricity generated, this type of collector has enabled three different modes of fluid operation: air mode, water mode and simultaneous (bi-fluid) mode. The third mode of fluid of operation is the primary focus in this chapter. This chapter highlights the performance of the collector outdoors, in terms of the experimental and two-dimensional theoretical analysis at steady state. For collector testing under real sky conditions, analyses of the collector for varying sets of mass flow rates under environmental conditions of an average wind speed of 3 m/s and average solar radiation of 700 W/m2 were conducted. To obtain suitable data, experiments were conducted for each of the mass flow rates on ten different days of testing. For the simultaneous mode, when air flow rate was fixed at 0.0262 kg/s, at a water mass flow rate that varied from 0.0017 to 0.010 kg/s, the electrical efficiency and total thermal efficiency ranged from 8.13 to 8.60 % and 44.36 to 47.45 % respectively. When the water flow rate was fixed at 0.0066 kg/s, at an air mass flow rate that varied from 0.0092 to 0.0753 kg/s, the efficiencies ranged from 8.10 to 8.56 % and 44.06 to 50.37 % respectively. Theoretical analysis was then conducted and compared with the experimental analysis by comparing the trend of the curves and using mean absolute percentage error (MAPE) analysis. The curves were found to be in good agreement, and the computed MAPE for the fluids’ output temperature was less than 2 %. Parametric studies were then conducted to investigate the performance of the collector with the change in air channel depth and performance with the change in collector length. The feasibility of incorporating two different types of working fluid into the same PV/T solar collector was demonstrated based on the thermal and electrical energy output of the collector under real sky conditions. Therefore, this research will serve as a starting point for further research into a bi-fluid type PV/T solar collector, both experimentally and theoretically.

Investigation on the Thermal Characteristics of a Bi-fluid-Type Hybrid Photovoltaic/Thermal (PV/T) Solar Collector

Known as a photovoltaic/thermal (PV/T) solar collector, this type of hybrid solar collector involves the integration between conventional PV cells and a solar thermal component. Up to now, the research in this field has tended to focus on either air or water as the working fluid. When both water and air are utilised under the same PV/T solar collector, it is seen as more appealing due to its space-saving design and range of potential applications. Known as a bi-fluid-type PV/T solar collector, this type of hybrid system is the subject of this research. For collector optimisation purposes, thermal modelling is considered important and hence, 2-dimensional (2-D) steady-state energy balance equations are derived to model the bi-fluid PV/T system during the simultaneous mode of fluid operation. However, when the fluids are to be operated simultaneously, the equations are not solvable analytically, and hence the numerical method is employed. Following this, the common useful thermal characteristic parameters of the collector, that is, the collector efficiency factor Fʹ, heat removal F R and also the overall heat transfer loss coefficient U1 cannot be determined analytically. Nevertheless, these quantities can be evaluated experimentally and graphically through computer simulations using the derived 2-D steady-state analysis. Theoretically, using the results obtained from the modelling, suitable curves are plotted of which the values of FR for the hybrid solar collector during independent mode of fluid operation for water and air and for bi-fluid configuration are computed as 0.59, 0.71 and 0.82 respectively. Meanwhile, at zero reduced temperature, the predicted thermal efficiencies are at 42.8, 51.3 and 59.2 % respectively. Experiments are then performed for steady-state analysis under the solar simulator at the Solar Energy Research Lab UiTM Perlis, Malaysia. The results obtained are found to be in good agreement with the values predicted by the mathematical model. From this study it can be concluded that the utilisation of both water and air as the working fluid under the same hybrid solar collector is seen as promising in order to optimise solar energy utilisation. The validated 2-D steady-state analysis is very useful in order to predict the collector performance under the influence of important environmental and design parameters. This study contributes as the starting platform in a research on a bi-fluid-type hybrid PV/T solar collector covering both theoretical and experimental studies.

Mango Size Classification Using RGB Color Sensor and Fuzzy Logic Technique

Fruit size is one of the most important criteria for classification and grading of mangoes. Currently, the size of a mango is determined by weight. In this project, a new model for classifying mango size using RGB color sensor and fuzzy logic are designed as an alternative automated grading of fruit size based on weight. RGB color sensor was used to measure the dimensions of mango such as major length, width and height in terms of reference color intensity value. Then, the fuzzy logic was used to classify mango size into small, medium, and large size. The proposed model is able to distinguish the three different classes of mango size automatically with more than 85 % accuracy.

Fuzzy Spatial Forecasting Model of Rainfall Distribution for Flood Early Warning

Flood is commonly known as one of the most frequent type of natural disaster worldwide that occurred when the ground is not able to absorb and accommodate the heavy rainfall. Flood might be caused by increased levels of river water more than the river bank or the dams. Many methods have been proposed to forecast the rainfall distribution but mostly the forecasting accuracy of the existing method are questionable. In this paper, a fuzzy time series method was proposed to forecast the rainfall distribution. The objectives of this paper, first is to formulate fuzzy spatial forecasting model for rainfall distribution for each month in Perlis. Second, to predict the accurate rainfall values in future for early warning of flood in order to reduce flood issues. Using the fuzzy spatial forecasting method, the historical data of rainfall in Perlis were used to forecast. After that, several rules was applied to determine whether the rainfall forecasting trend value goes downward or upward movement Then, the mean square error (MSE) was calculated to compare the forecasting rainfall results of various forecasting method. The smaller the value of MSE, the better the forecasting model. The monthly historical rainfall distribution in Perlis for 4 years had been used to illustrate the forecasting algorithm of the new fuzzy time series method. The experimental results of this research exhibited higher forecasting accuracy for forecasting rainfall compare to existing methods.