Malaysian Meteorological Department Research Articles

Estimating the global solar radiation in Putrajaya using the Angstrom-Prescott model

Global solar radiation (GSR) studies are essential in enhancing the use of solar PV systems especially for Building Integrated PV system (BIPV). Various studies on GSR had been carried out in Malaysia including Penang, Kuala Lumpur and Kota Bharu at the earlier stage. Afterward, data from the Malaysian Meteorological Department (MET) and the Malaysian National University were used to estimate the monthly average daily global radiation for various locations in Malaysia including Kuala Lumpur, Kuala Lumpur, Petaling Jaya, Bandar Baru Bangi, Kota Baru, Senai, Bayan Lepas, Kuching and Kota Kinabalu. GSR in Putrajaya, a location which has identified to implement Malaysian Building Integrated Photovoltaic (MBIPV) projects has yet to be estimated. The conventional method to obtain the amount of GSR at a location is to install a measuring device like a pyranometer at the site to observe and document its day-to-day recordings. However, this is a time-consuming and costly practice. The models used to estimate the GSR are usually based on astronomical factors, geometrical factors, physical factors and meteorological factors. There are numerous models used to predict GSR which can be categorized based on sunshine, cloud, temperature and other meteorological parameters. Additionally, the global solar energy models can be grouped by its modelling techniques such as linear, nonlinear, artificial intelligence and fuzzy logic modelling techniques. The reviews discovered that the models used to estimate GSR were mostly correlated to sunshine duration (SD), air temperature, relative humidity and geographical parameters like latitude, longitude and altitude. In this paper, the GSR in Putrajaya is estimated from the hourly solar radiation and daily sunshine hours data from the Malaysian Meteorological Department. The data, along with the calculated monthly average daily extraterrestrial radiation on a horizontal surface and monthly average maximum possible daily sunshine is used to plot a scatter graph that is linearly fitted. The gradient and vertical axis cut-off from the linear fit is used to obtain the coefficients in the Angstrom-Prescott (A-P) model. Subsequently, the coefficients were used to estimate the GSR in Putrajaya. In line with the government’s initiative, this study will provide an estimation of the GSR in Putrajaya where the finding will be beneficial to the stakeholders, policy maker, developer and investor and energy authority. The average monthly GSR was obtained for nine out of twelve months with highest at 21.18 MJ/m2 in March and lowest at 18.34 MJ/m2 in June.

Optimal Techno-Economic Design of Standalone Hybrid Renewable Energy System Using Genetic Algorithm

This paper presents a methodology to size Standalone Hybrid Renewable Energy System (SHRES) which combines solar PV, wind turbine (WT) and battery energy storage (BES) for application in rural areas. These sources are integrated via an AC bus to support the load demand. SHRES is simulated under varying load demand, solar radiation, temperature and wind speed obtained from the Malaysian Meteorological Department. A Multi-objective Optimization using Non-dominate Sorting Genetic Algorithm (NSGA-II) was utilized to determine the best sizing of PV / wind turbine / battery, and minimize Cost of Energy (COE) and Loss of Power Supply Probability (LPSP). The results show that the NSGAII optimization of the model is able to determine the best techno-economic sizing for the suggested location. For the case study, the optimum COE was 0.1099 (USD/kWh) and LPSP was 0.0865. The proposed tool can be used to size the SHRES for rural electrification and enhance energy access within remote locations.

Potential Evaluation of Wind Energy in Kuala Terengganu, Malaysia through Weibull Distribution Method

Malaysia faces many challenges in the development of wind energy as it is located in areas with slower wind speeds. Malaysia is located on the equator line where land and sea breezes can affect the wind regime. The wind does not blow uniformly and fluctuate by month and area. Therefore, the objective of this study is to determine the potential of the latest wind power in Kuala Terengganu. The scope of the study was not comprehensive because it focused only on Kuala Terengganu, Malaysia which is located at latitude 5° 23′ N and longitude 103° 06′ E. The wind data used in this study was obtained from the Malaysian Meteorological Department. The wind data that had been observed and collected was the wind direction and wind speed for year 2017 where the height of the sea level is 5.2 meters. This study uses the Weibull Distribution method as it shows a good consideration to estimate the density of wind power in Malaysia [1] The daily wind speed pattern for year 2017 can be seen that it has a corresponding pattern where it shows high wind speed at the beginning and end of the year. The wind speed frequency is also variable for the winds of the Northeast Monsoon and is almost constant during the south monsoon of the Southwest Monsoon and the Transition Monsoon. Overall, the potential of wind power in Kuala Terengganu is not too large. The annual average for 2017 is 2.01 m/s only. Wind power is high during the Northeast Wind Monsoon season.

Analysis and Prediction of Temperature Time Series Using Chaotic Approach

Analysis and prediction of temperature time series is important because temperature changes can affect human’s health. The objectives of this study are to analyse and predict the temperature series in Jerantut, Pahang, Malaysia using chaotic approach. Modelling through chaotic approach divided into two stages; reconstruction of phase space and prediction processes. Through the reconstruction of phase space, a single scalar time series is rebuilt into a multi-dimensional phase space. This multi-dimensional phase space is used to detect the presence of chaotic dynamics through phase space plot and Cao method. The results show that the observed time series is chaotic in dynamic. Therefore, one hour ahead prediction through local mean approximation method is done. The correlation coefficient value obtained is 0.9789. The value which is approaching one reflected that the predicted time series and observed time series are close to each other. Thus, the modelling through chaotic approach is considered succeed. It is hoped that the model can help Malaysian Meteorological Department and Department of Environment Malaysia in order to improve their weather services.

Oil palm dry season analysis based on moderate-resolution imaging spectroradiometer (MODIS) satellite indices

ABSTRACTOil palm is the most important crop in Malaysia. It plays a key role in maintaining carbon balance and it possesses high economic value. However, oil palm productivity is really sensitive to environmental changes especially during the long-term dry season. This has warranted studies on frequent observation of dry season for the plantation of oil palm. In this study, Moderate-Resolution Imaging Spectroradiometer (MODIS) surface reflectance data were utilized to generate an index for the crop assessment at Felcra Mendom Oil Plantation area, Negeri Sembilan. The indices of Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and shortwave indices, namely Shortwave Infrared Water Stress Index (SWISI), at three different channels of 2, 5, and 6 were utilized. The main aim is to identify drought year based on MODIS-SPI-based index calculated and evaluated indices developed from MODIS images. The precipitation data retrieved from Malaysia Meteorology Department starting from year 1997 until 2017 and later are classified using Standardised Precipitation Index (SPI). Then by using the data from precipitation and SPI, the MODIS images were extracted from Land Process Distributed Active Archive Center (LP DAAC). Next, the images were processed and analysed by using ENVI Version 5.3 software to extract the indices used. The SPI-3 and SPI-1 were classified year 2015 as extreme drought with ‘extreme’ and ‘mild’, respectively. Meanwhile, the vegetation indices were calculated and average showed both NDVI and EVI approaching +1.00 value at the highest NDVI is 0.79 during 2017 and the highest EVI is 0.62 during years 2005 and 2013, respectively. Both SIWSI showed similar pattern, indicating high-moisture content as the index approaching −1.00. The result does not represent the overall condition of the specific study area, but the SPI is reliable to display the whole area and the utilization of MODIS and SPI can be used in further study.

Impact of rain weather over free space optic communication transmission

<span>This paper focuses the rain effect over FSO link medium in Malaysia environment. In this work, a rain data samples that collected from Malaysian Meteorological Department (MMD) to determine the scattering coefficient, atmospheric attenuation and total attenuation. From the analysis, the precipitation rate give different impact over FSO link which can cause the attenuation and bit error rate increase. The results also show the comparison parameter for optimal geometrical loss such as beam divergence, aperture size and receiver sensitivity.</span>

THE EFFECTS OF EQUINOX PHENOMENON ON CLIMATE CHANGE

In recent years, Malaysia has been experienced with the weather changes especially in increasing of the temperature. The highest temperature usually occurs during equinox. Equinox is the phenomenon when the sun is directly above the Earth's equator and this happens twice a year. Therefore, this study is carried out to determine the effects of equinox on climate change for five consecutive years. The information of this study was obtained from Malaysian Meteorological Department. The study involved three states and one federal territory in Peninsular Malaysia, namely Alor Setar (Kedah), Kota Bharu (Kelantan), Johor Bahru (Johor) and Kuala Lumpur. These states were chosen based on their location in North, East, South and West of Peninsular Malaysia. As a result, the overall mean temperature at all stations is in the range of 27°C to 30°C. The analysis revealed that the mean temperature in March showed significant increase from year 2011 to 2015 in all stations and Alor Setar recorded the highest mean temperature. However, other factors are also needed to be considered to the rising of the temperature such as El Nino phenomenon, amount of rainfall, number of rain days, Southwest and Northeast Monsoon seasons and others.
 Keywords: Equinox, climate, peninsular Malaysia, temperature, pollution

Unity check of typical offshore wellhead platform in Malaysia using Aceh earthquake loading data and SAP2000

One of the most significant regional earthquakes which brought catastrophic impacts is the magnitude of Mw = 9.1 earthquake which occurred on the western coast of Banda Aceh, North Sumatera had generated a massive Indian Ocean tsunami on December 26th, 2004. Apart from that, several local earthquakes also occurred in Bukit Tinggi, Pahang and Ranau, Sabah according to Malaysian Meteorological Department (METMalaysia). However, oil and gas industry plays a vital role in Malaysian economy due to the significant contribution to the country’s gross domestic product. In fact, the existing fixed offshore structure in Malaysia region only take into considerations the wind load, wave load, and current load rather than earthquake load. The objective of this study is to perform unity check for every element of offshore wellhead platform when subjected to 2004 Aceh earthquake loading. All the environmental loads such as wave, wind, and current load have been designed by referring the American Petroleum Institute (API) design criteria. The computer software SAP2000 is selected to model and analyse the offshore structure. There are three types of analysis that have been performed in this study which are the free vibration analysis, time history analysis, and response spectrum analysis. The time history of earthquake data from 2004 Aceh earthquake has been used in performing time history analysis. For the response spectrum analysis, the analysis was performed by using response spectra curves in Eurocode 8. As a result, the offshore wellhead platforms in Malaysia are situated under a safe condition when subjected to low seismic activity based on the study.

Radio Frequency Interference on Nearby Radio Astronomical Lines: Relationship between Wind Speed and Radio Signal Strength Measured at East Coast of Peninsular Malaysia

The East coast of Peninsular Malaysia receives a strong wind speed, heavy rain and high humidity during the Northeast monsoon. The Malaysian Meteorological Department claims that the wind speed during the Northeast season could reach 55.56 km/h or more. This strong wind speed and heavy rain could contribute to the attenuation of radio signals. This paper investigated the relationship between wind speed (km/h) and radio signal strength, RSS (dBm). The statistical correlation was employed to identify the correlation value and strength between them. The wind speed and RSS were collected during wet and dry seasons at Kusza Observatory, while the Spectrum analyser was used for measuring RSS (dBm) and the weather station for wind speed (km/h). The result showed that the wet season has strong and significant correlation compared to the dry season. Frequencies of 382.5 MHz, 945 MHz and 2160 MHz with correlation values of r = -0.583;-0.631 and -0:514, respectively, showed strong, negative and significant correlations with wind speed in the wet season. As for the dry season, only a frequency of 382.5 MHz showed a strong, positive and significant correlation with r = 0.555, while small and medium for others. This finding is useful to a radio astronomer to help determine the best period for radio astronomy observation with the lowest interference considering the weather in the East Coast of Peninsular Malaysia. Besides, this finding benefits a spectrum of users involved in mobile telecommunication, wireless internet, radio TV transmission and satellite broadcasting.

Binary Particle Swarm Optimization for Scheduling MG Integrated Virtual Power Plant Toward Energy Saving

This paper introduces a novel optimal schedule controller to manage renewable energy resources (RESs) in virtual power plant (VPP) using binary particle swarm optimization (BPSO) algorithm. It is crucial to minimize the costs giving priority for sustainable resources use instead of purchasing from the national grid. The effectiveness of the proposed approach is examined by the IEEE 14 bus system containing microgrids (MGs) integrated with RESs in the form of VPP. Real load demand recorded is used to model and simulate the test case studies of the system for 24 h in Perlis, Malaysia. Moreover, weather data collected from the Malaysian Meteorological Department such as wind, solar, fuel, and battery status data are used in the BPSO to find the best ON and OFF schedules. The results found that the developed BPSO algorithm is robust in reducing energy consumption and emissions of the VPP. This study contributes to the development of an optimization algorithm for an optimal scheduling controller of MG integrated VPP in order to reduce carbon emissions and manage sustainable energy. Finally, a comparative analysis of the optimal algorithms over conventional justifies the use of RESs integration and validates the developed BPSO for sustainable energy management and emissions reduction.

A Theoretical Review on the Preventive Measures to Landslide Disaster Occurrences in Penang State, Malaysia

Based on the frequently unanticipated occurrences of natural landslide disaster across Malaysia, it can be seen that Malaysia is still not fully prepared for occurrences of natural landslide disaster. The lack of predictive and warning systems for the disaster in the country is creating panic and apprehension among citizens alongside with both economic and property losses. The general objectives of this research are: to identify the meteorological factors that cause landslide natural disaster occurrences in Malaysia and to suggest a predictive model for landslide disaster occurrence in Malaysia. This research therefore explored modelling disasters occurrences in order to predict, warn, and prevent huge impact of landslide disasters in Penang, Malaysia. This research shall make use of past literatures and data from Malaysian Meteorological department considering climatic parameters such as daily mean temperature and daily rainfall only. Data mining and Artificial Neural Networks (ANN) shall be suggested to predict landslide disaster occurrences in Malaysia. Thus, the need for a predictive model for occurrence of landslide natural disaster is imperative to the safety of lives and protection of both environmental and economy of the region.

Predicting the Occurrence of Landside at Penang Island, Malaysia, through Artificial Neural Networks Model

The occurrence of recurring landsidesthat plagued Penang Island in 2017 hasattracted much attention across Malaysia since the incident puts people’s life in danger and worsensthe economy of state and country. Based on the harmful effects, the requirement for predicting the occurrence of landslide is deemed crucial for disaster management agencies to promote awareness and prepare for necessary action. Therefore, this study aims to investigate the meteorological factors, and finally to develop a predictive model based on Artificial Neural Networks (ANN). Two meteorological factors, which are daily mean temperature and daily rainfall are considered in this study based on current data from Malaysian Meteorological Department. As a result, only two percent misclassification rate is recorded by the model compared to the actual data,while its prediction performance is better than regression method. Besides, the correlation between the rangeof daily rainfall amount withcorresponding daily mean temperature for the occurrence of landslide is anovel contribution of this research as little attention had been given by previous studies. The developed ANN model is helpful in predicting the occurrence of landslide inPenang Island and provides beneficial guidance for the disaster management agencies to save properties and people’s lives.Â

PARAMETRIC ESTIMATION METHODS FOR BIVARIATE COPULA IN RAINFALL APPLICATION

This study focuses on the parametric methods: maximum likelihood (ML), inference function of margins (IFM), and adaptive maximization by parts (AMBP) in estimating copula dependence parameter. Their performance is compared through simulation and empirical studies. For empirical study, 44 years of daily rainfall data of Station Kuala Krai and Station Ulu Sekor are used. The correlation of the two stations is statistically significant at 0.4137. The results from the simulation study show that when the sample size is small (n <1000) for correlation level less than 0.80, IFM has the best performance. While, when the sample size is large (n ≥ 1000) for any correlation level, AMBP has the best performance. The results from the empirical study also show that AMBP has the best performance when the sample size is large. Thus, in order to estimate a precise Copula dependence parameter, it can be concluded that for parametric approaches, IFM is preferred for small sample size and has correlation level less than 0.80 and AMBP is preferred for larger sample size and for any correlation level. The results obtained in this study highlight the importance of estimating the dependence structure of the hydrological data. By using the fitted copula, Malaysian Meteorological Department will able to generate hydrological events for a system performance analysis such as flood and drought control system.

Feasibility of LoRa Implementation for Remote Weather Monitoring System through Field Measurement and Case Study Analysis

This paper discusses the feasibility of Long Range Wide-area network (LoRa-WAN) implementation for weather data collection and transmission in remote locations, specifically in east Malaysia. Currently, Malaysia Meteorological Department (MetMalaysia) has installed more than 100 weather stations around Malaysia, and out of this number, there are many stations, mostly in east Malaysia that are dependent on Very Small Aperture Terminal (VSAT) services for data transmission due to unavailability of mobile coverage. Due to significant cost of VSAT subscription, LoRa communication is proposed as an alternative solution due to its low power, low-cost, and long range characteristics. In this paper, the study has been performed through two stages; first, technical performance of LoRa network was validated through field measurement in urban areas to determine the actual LoRa characteristics in real condition. In the measurement, a LoRa module operating at 433 MHz was used to demonstrate a single channel LoRa gateway that acted as a bridge to communicate between LoRa node to IP network. Parameters such as received power spectrum and free space path loss were recorded for analysis. Second, based on the measured data, extrapolation of maximum feasible distance of LoRa signal propagation was done to analyze the viability of implementing LoRa in various locations of existing weather stations in Sabah and Sarawak. Two case studies are presented in this paper, with the aim to evaluate the suitable location of LoRa gateway to establish communication with the existing weather stations when LoRa network is used. Detailed link budget analysis was performed for each scenario. Based on the comparison between theoretical and measurement, the power transmitted from LoRa node shows inconsistent readings throughout the day, suspected due to the changes in spread factor that has been automatically set by the module. Nevertheless, taking into account this factor, it was found that the transmission range was adequate for some remote locations. Meanwhile, for some locations that are separated too far from each other, higher power is needed to allow consistent communication.

An Application of Radial Basis Function Neural Network for Short Term Load Forecasting Solution

This paper proposes an approach to solve short term load forecasting (STLF) problem by using radial basis function neural network (RBFNN). STLF is one of the main issues for power system scheduling since it can help the utility company to manage the generation of power system economically and reliably. For this purpose, electric load forecast needs to be as accurate as possible to meet the utilities’ need as well as it also can help to select the proper amount of reserve margin which can contribute to the efficiency improvement of the power supply. However, many factors can influence electric load such as day of the week, month of the year, and etc. which makes a complex process for obtaining accurate forecasting. In this paper, input of RBFNN are the real historical load data collected from local utility in Kuantan, Pahang that utilized together with Malaysia Meteorology Department (MetMalaysia) data such as weather, temperature, dew point and humidity and the output is load forecasting for the given day. The performances of RBFNN are analyzed by investigating the combination of input-output of mentioned data that contribute to the best result. Comparison with artificial neural network (ANN) also given in this paper.

Interpolation Using Cubic Bѐzier Triangular Patches

Spatial interpolation is a method that can be used to estimate the unknown value (or parameter) at certain time or location. Besides of that, shape preserving interpolation especially positivity preserving interpolation play an important role for data visualization where the resulting interpolating surface must be positive everywhere. In this study, we use a triangulation based method consists of positivity preserving cubic Bezier triangular patches to estimate the unknown value of rainfall amount at spatial localization. This scheme is useful for spatial data interpolation compared to the mesh free methods which are required the optimization technique in order to ensure the positivity of basis functions.The data is triangulated by using Delaunay’s triangulation algorithm and from there the triangular surfaces are constructed piecewisely comprising three local schemes that are blended together via convex combination to form a scattered interpolating surface. Sufficient conditions on Bezier ordinates are derived in order to preserve the positivity of the surface. Validation of the propose schemes are conducted by using well-known test function used in previous researches. Then, the best the scheme is selected to visualize a rainfall data distribution based on secondary data collected at various meteorology stations in Malaysia obtain from Malaysian Meteorology Department. Finally, we estimate the unknown rainfall amount at certain locations that lies inside the convex hull formed by all given stations. The finding shows that positivity preserving cubic triangular patches is able to preserve the positivity of rainfall distribution surface and has a significant application in estimating the rainfall amount at unallocated meteorology stations in Malaysia.

Revisiting seismic hazard assessment for Peninsular Malaysia using deterministic and probabilistic approaches

Abstract. Seismic hazard assessments, both deterministic and probabilistic, for Peninsular Malaysia have been carried out using peak ground acceleration (PGA) data recorded between 2004 and 2016 by the Malaysian Meteorological Department using triaxial accelerometers placed at 19 seismic stations on the peninsula. Seismicity source modelling for the deterministic seismic hazard assessment (DSHA) used historical point sources whereas in the probabilistic (PSHA) approach, line and areal sources were used. The earthquake sources comprised the Sumatran subduction zone (SSZ), Sumatran fault zone (SFZ) and local intraplate (LI) faults. Gutenberg–Richter law b value for the various zones identified within the SSZ ranged between 0.56 and 1.06 (mean=0.82) and for the zones within the SFZ, between 0.57 and 1.03 (mean=0.89). Suitable ground motion prediction equations (GMPEs) for Peninsular Malaysia along with other pertinent information were used for constructing a logic tree for PSHA of the region. The DSHA “critical-worst” scenario suggests PGAs of 0.07–0.80 ms−2 (0.7–8.2 percent g), whilst the PSHA suggests mean PGAs of 0.11–0.55 ms−2 (0.5–5.4 percent g) and 0.20–1.02 ms−2 (1.9–10.1 percent g) at 10 % and 2 % probability of exceedance in 50 years, respectively. DSHA and PSHA, despite using different source models and methodologies, both conclude that the central-western cities of Peninsular Malaysia, located between 2 and 4∘ N, are most susceptible to high PGAs, due to neighbouring active Sumatran sources, SFZ and SSZ. Of the two Sumatran sources, surprisingly, the relatively less active SFZ source with low magnitude seismicity appeared as the major contributor due to its proximity. However, potential hazards due to SSZ mega-earthquakes should not be dismissed. Finally, DSHA performed using the limited LI seismic data from the Bukit Tinggi fault at a reasonable moment magnitude (Mw) value of 5.0 predicted a PGA of ∼0.40 ms−2 at Kuala Lumpur.

Investigation on the occurrence of positive cloud to ground (+CG) lightning in UMP Pekan

This paper is going to find the direction of +CG lightning and its relationship with monsoon season in Malaysia by using data obtained from Malaysia Meteorological Department (MMD) for 2015. Analysis from this study found that a high numbers of lightning occur during dry season compares to rainy season. This is contradicted with general perception in Malaysia where lightning only occurs during rainy day. It is also understood that +CG lightning makes up approximately 20% of total lightning and the rest is −CG lightning events. The occurrence of +CG lightning during day and night will be discussed. From this, the direction where most +CG lightning occurs will be determined and used as a guide in order to observe TLEs afterward.

Southwest monsoon onset dates over Malaysia and associated climatological characteristics

In Malaysia precipitation prevails throughout the year. However, the southwest monsoon (late May to September) is characterised with low precipitation, less cloud, high outgoing long-wave radiation (OLR) and often featured by dry epochs. Therefore, onset of the monsoon here is best determined by considering multiple onset parameters such as wind, OLR, rainfall and relative humidity. We used modified Malaysian Meteorological Department wind shear index based on major convection centres during the monsoon onset. The 850 hPa winds were chosen to investigate the onsets of the monsoon in view of the marked orographic and mesoscale processes. The next criterion was the presence of sustained westerlies averaged between 850 hPa and 600 hPa from all the available radiosonde stations data over Malaysia for at least 5 days. As the strongest convective activity in the tropics is represented by OLR of less than 220 W m-2, the third criterion was to check whether the value of OLR was greater than 220 W m-2 over the region. The mean date of the summer monsoon onset over Malaysia is found to be 19 May, with a standard deviation of 8 days. Further, climatological composites show that there is a gradual change from easterlies to westerlies from the surface up to 500 hPa in Malaysian stations both in Peninsular Malaysia and East Malaysia during May. OLR and rainfall analysis reveal that, the southwest monsoon daily rainfall over Malaysia is less than 10 mm and OLR is greater than 220 W m-2. Additionally, monsoon onset tends to be late during the El Niño years and earlier during the La Niña years.

A New Discordancy Test on a Regression for Cylindrical Data

A cylindrical data set consists of circular and linear variables. We focus on developing an outlier detection procedure for cylindrical regression model proposed by Johnson and Wehrly (1978) based on the k-nearest neighbour approach. The procedure is applied based on the residuals where the distance between two residuals is measured by the Euclidean distance. This procedure can be used to detect single or multiple outliers. Cut-off points of the test statistic are generated and its performance is then evaluated via simulation. For illustration, we apply the test on the wind data set obtained from the Malaysian Meteorological Department.