Fadhilah Yusof

In the global energy context, renewable energy sources such as wind is considered as a credible candidate for meeting new energy demands and partly substituting fossil fuels. Modelling and forecasting wind speed are noteworthy to predict the potential location for wind power generation. An accurate forecasting of wind speed will improve the value of renewable energy by enhancing the reliability of this natural resource. In this paper, the wind speed data from year 1990 to 2014 in 18 meteorological stations throughout Peninsular Malaysia were modelled using the Autoregressive Integrated Moving Average (ARIMA) to forecast future wind speed series. The Ljung-Box test was used to determine the presence of serial autocorrelation, while the Engle’s Lagrange Multiplier (LM) test was used to investigate the presence of Autoregressive Conditional Heteroscedasticity (ARCH) effect in the residual of the ARIMA model. In this study, three stations showed good fit using the ARIMA modelling since ...

Flood duration, volume, and peak flow are important considerations in flood risk analysis and management of hydraulic structures. The conventional flood frequency analysis assumed that the marginal distribution functions of flood parameters follow a certain pattern. However, such assumption is impractical because a flood event is multivariate and the flood parameter distributions can be different. These discrepancies were addressed using bivariate joint distributions and Copula function which allow flood parameters having different marginal distributions to be analyzed simultaneously. The analysis used hourly stream flow data for 45 years recorded at the Rantau Panjang gauging station on the Johor River in Malaysia. It was found that flood duration and volume are best fitted by the generalized extreme value distribution while peak flow by the Generalized Pareto. Inference function for margin (IFM) method was applied to model the joint distributions of correlated flood variables for each pair and the results showed that all the calculated θ values were in acceptable range of Gaussian Copula. By horizontally cutting the joint cumulative distribution function (CDF), a set of contour lines were obtained for Gaussian Copula which represented the occurrence probabilities for the joint variables. Also the joint return period for pair of flood variables was calculated.

Electrical treeing is a common insulation pre-breakdown phenomenon. Due to prolonged stresses, polymeric insulating material cannot withstand the aging and degradation from voltage application, environmental factors and from several influenced factors. Therefore, this phenomenon needs to be explored from the initial stage for better understanding of its early inception. However, previous studies have shown that some initial parameters were analysed by using still-can-improved statistical techniques. Thus, in this paper, a more accurate statistical technique was performed in order to determine the value, the distribution and distribution statistical rank of tree inception voltage of silicone rubber and epoxy resin by fitting method. The electrical tree inception voltage was measured and recorded by applying a sequential of AC voltage between the point-to-plane electrodes via a camera-equipped online monitoring system. The experiment was performed based on IEC 1072:1991 “Methods of Test for Evaluating the Resistance of Insulating Materials Against the Initiation of Electrical Trees”. The experimental results were analysed satistically and comparison was made between the best fitted distribution and Weibull distribution. Obtained results have shown that tree inception voltage depends on the material composition since other factors were kept constant. Based on the statistical analysis, the tree inception voltage of silicone rubber and epoxy resin were best fitted with Johnson SB distribution rather than Weibull distribution which showed higher fitting error. Based on the fitted distribution, the values of tree inception voltage of silicone rubber and epoxy resin were calculated and found to be 3.1529 kV and 4.6528 kV respectively. The results of fitting using Anderson-Darling goodness-of-fit test and Kolmogorov-Smirnov goodness-of-fit were compared. It was found that the Johnson SB statistical distribution holds good for silicone rubber and epoxy resin for electrical treeing initiation. Therefore, it has been proved that Johnson SB distribution is better than Weibull distribution in representing the tree inception voltage distribution.

Sub-daily timescale data such as hourly data are needed for modeling urban systems. However such series are not readily available as compared to daily rainfall series. Stochastic rainfall models are useful in estimating input for design work. One of the models that applies the clustered point process theory is the Neyman-Scott Rectangular Pulses (NSRP) model. The model uses a flexible

The ability of Fourier Series to exhibit seasonal fluctuation of rainfall process is presented. The Neyman Scott Rectangular Pulse Model with mixed ex- ponential distribution for cell intensity is selected to describe the rainfall process. The model's parameters were estimated by employing the Shuffle Complex Evolution (SCE-UA) method. Seasonal variation is dealt with by fitting Fourier Series to the parameters.

ABSTRACT This study assessed the performance of Fourier series in representing seasonal variation of tropical rainfall process in Malaysia. Fourier series is incorporated into a spatial temporal stochastic model in an attempt to make model parsimonious and at the same time, capture the annual variation of rainfall distribution. In view of Malaysia’s main rainfall regime, the model is individually fitted at two regions with distinctive rainfall profiles; one is an urban area receiving rainfall from convective activities whilst the other receives from monsoonal activities. Since both regions are susceptible to floods, the study focuses on rainfall process at fine resolution. Fourier series equations are developed to represent model’s parameters to describe their annual periodicity. The number of significant harmonics for each parameter is determined by inspecting the cumulative fraction of total variance explained by the significant harmonics. Results revealed that the number of significant harmonics assigned for the parameters is slightly higher in region with monsoonal rains. The overall simulation results showed that the proposed model is capable of generating tropical rainfall series from convective and monsoonal activities. For full paper, http://www.tandfonline.com/eprint/gH6zQ2rvXV59XNYK7eC4/full or email me at : zaida.kl@utm.my