Thunderstorm Prediction Model Using SMOTE Sampling and Machine Learning Approach

Thunderstorms are one of the most destructive phenomena worldwide and are primarily associated with lightning and heavy rain that cause human fatalities, urban floods, and crop damage. Therefore, predicting thunderstorms with reasonable accuracy is one of the crucial requirements for the planning and management of many applications, including agriculture, flood control, and air traffic control. This study extensively applied the historical lightning and meteorological data from 2011 to 2018 of the southern regions of Peninsular Malaysia to predict thunderstorm occurrence. Positive CG lightning rarely occurs compared to negative CG lightning and also due to the non-linear and complex characteristics of the thunderstorm and lightning itself, leading to an imbalance in the dataset. The resampling technique called SMOTE is introduced to overcome the imbalance of the training dataset. Then the dataset is trained and tested with five Machine Learning (ML) algorithms, including Decision Trees (DT), Adaptive Boosting (AdaBoost), Random Forest (RF), Extra Trees (ET), and Gradient Boosting (GB). The results have shown a good prediction with accuracy (74% to 95%), recall (72% to 93%), precision (76% to 97%), and F1-Score (74% to 95%) with SMOTE. The SMOTE and GB model prediction model is the best algorithm for thunderstorm prediction for this region in terms of performance metrics. In the future, the prediction results based on the lightning pattern and weather dataset will likely alert the related authorities to make an early strategy to handle the occurrence of thunderstorms

A practical method for optimised earth electrode designs at transmission towers exposed to lightning

A large percentage of transmission line outages in Malaysia are due to lightning activity with backflashover being the main cause. Previous investigations have indicated that tower footing earth resistance is one of the main factors in reducing the occurrence of backflashovers. The present studies review some of the tower earthing design options. From this standard designs are proposed together with a practical method of optimising the design based on soil resistivity measurement data. The process is presented via a procedure which includes the main measurement and design steps. This allows different standard designs to be selected to suit the type of soil structure at the site of the proposed transmission tower. Where measurements indicate a high resistivity layer with underlying low resistivity soil, an electrode design relying more on driven rods is used. Conversely, a design using more horizontal electrode would be selected where the soil structure is of low resistivity above high. Trial installations using the newly designed electrode arrangements have been conducted and preliminary results indicate significant improvements in lightning performance

Environmental Analysis Of Quasi-Static Electric Field Changes Of Tropical Lightning Flashes

The environmental conditions leading to the bouncing-wave discharge and the subsequent electron beam remain to be investigated in more detailed future studies. The analysis of quasi-static initial electric field changes (IECs) were found at the beginning of all 24 lightning flashes detected within reversal distance (22 Negative Cloud-to-Ground (–CG) and 2 normal Intra-Cloud (IC) flashes) in a tropical storm on June 15th, 2017 close to our station in Malacca, Malaysia (2.314077° N, 102.318282° E). The IECs durations averaged 4.28 ms for –CG flashes (range 1.48 to 9.45 ms) and averaged 11.30 ms for normal ICs flashes (range 7.24 to 15.35 ms). In comparison to Florida storms, the duration of IECs for –CG and IC flashes were 0.18 ms (range 0.08 to 0.33 ms) and 1.53 ms (range 0.18 to 5.70 ms), respectively. Moreover, the magnitudes of E-change for tropical thunderstorm were 0.13 V/m (range 0.03 to 0.44 V/m) for –CG flashes and-0.20 V/m (range-0.13 to-0.27 V/m) for IC flashes. The E-change magnitudes of tropical flashes are significantly larger than Florida flashes

Environmental Analysis Of Quasi-Static Electric Field Changes Of Tropical Lightning Flashes

The environmental conditions leading to the bouncing-wave discharge and the subsequent electron beam remain to be investigated in more detailed future studies. The analysis of quasi-static initial electric field changes (IECs) were found at the beginning of all 24 lightning flashes detected within reversal distance (22 Negative Cloud-to-Ground (–CG) and 2 normal Intra-Cloud (IC) flashes) in a tropical storm on June 15th, 2017 close to our station in Malacca, Malaysia (2.314077° N, 102.318282° E). The IECs durations averaged 4.28 ms for –CG flashes (range 1.48 to 9.45 ms) and averaged 11.30 ms for normal ICs flashes (range 7.24 to 15.35 ms). In comparison to Florida storms, the duration of IECs for –CG and IC flashes were 0.18 ms (range 0.08 to 0.33 ms) and 1.53 ms (range 0.18 to 5.70 ms), respectively. Moreover, the magnitudes of E-change for tropical thunderstorm were 0.13 V/m (range 0.03 to 0.44 V/m) for –CG flashes and-0.20 V/m (range-0.13 to-0.27 V/m) for IC flashes. The E-change magnitudes of tropical flashes are significantly larger than Florida flashes

Characteristics of lightning trends in Peninsular Malaysia from 2011 to 2016

Lightning is a powerful natural phenomenon, known to affect power utilities, structures, and either injured or kill a number of people and might cause large financial losses to the country both directly and indirectly. Therefore, an accurate and reliable lightning detection system is essential to enhance knowledge and awareness to forecast and identify occurrences of lightning activity. This paper focusses on the lightning trends at southern region of Peninsular Malaysia from 2011-2016 which utilized historical data from Lightning Detection System Network System, operated by TNB Research Sdn Bhd. The mean distributions, the percentage and the peak current of the lightning strikes were investigated. The relationship of the lightning trends with the main monsoon season were also evaluated. The evaluation results show that the monsoonal variation due to the shift of monsoon seasons (April-May and October-November) increased the lightning activity at the studied region. Furthermore, it is also found that a significant increase in lightning activity were observed due to the system upgrades in 2016 which reflected by the sensitivity in location accuracy and detection efficiency of the system

Impulse Characteristics of Highly Wetted Soils

It has been well accepted that under high impulse conditions, ionisation process in soil would occur, causing the ground resistance value to fall to a lower value than that obtained at low voltage low current, RDC. Factors affecting the percentage of reduction of impulse impedance from its RDC values have been known to be caused by soil resistivity, ground electrode’s configuration/sizes, RDC values, magnitudes and response time of impulse current. In this paper, experimental results of sand mixed with various soils and water content filled in a cylindrical container, subjected to high impulse currents are presented. The results are discussed according to the current impulse shape, impulse impedance and the breakdown voltage of the test cell

Development of GIS-based ground flash density and its statistical analysis for lightning performance evaluation of transmission lines in Peninsular Malaysia

Malaysia is one of the world's highest lightning regions, making it an ideal location for studying lightning activities, as they cause many power outages on overhead transmission lines. This study presents ground flash density (GFD) mapping and statistical analysis of lightning flash data in Peninsular Malaysia, which will be used to evaluate the lightning performance of transmission lines. Using Geographical Information System (GIS) software, the GFD map and lightning flash data for statistical analysis were extracted. MATLAB was then used to perform statistical analysis and obtain the probability of peak lightning current using the generalized extreme value (GEV) distribution. This study analyzed six years of lightning flash data from 2012 to 2017 recorded by the Lightning Location System (LLS) and used the Peninsular Malaysia base map from the Department of Survey and Mapping Malaysia (JUPEM). Results show that the GFD mapping approach effectively classifies GFD distribution and identifies areas with high lightning activity. 81 of 4,536,380 lightning flashes were negative polarity, with a higher mean peak current magnitude than positive ones. More lightning activity was observed during the Southwest Monsoon (June-September) and the first Inter-Monsoon season (April-May). Pahang had the most lightning flashes due to its large land area. The GFD map overlaid on the transmission line demonstrated how lightning performance on the transmission line can be assessed. These findings are useful for utility and protection engineers to improve the performance of transmission lines

Impulse Characteristics of Highly Wetted Soils

It has been well accepted that under high impulse conditions, ionisation process in soil would occur, causing the ground resistance value to fall to a lower value than that obtained at low voltage low current, RDC. Factors affecting the percentage of reduction of impulse impedance from its RDC values have been known to be caused by soil resistivity, ground electrode’s configuration/sizes, RDC values, magnitudes and response time of impulse current. In this paper, experimental results of sand mixed with various soils and water content filled in a cylindrical container, subjected to high impulse currents are presented. The results are discussed according to the current impulse shape, impulse impedance and the breakdown voltage of the test cell

Effectiveness of Large Soil Grain Sizes in Studying Impulse Characteristics of Soil

There have been many published studies analysing the impulse characteristics of soil and various soil properties. Some of these published results are found to be largely different and inconsistent from one study to another. Soil properties may be complex in nature, and its characteristics under high impulse conditions are influenced by many factors, which result in inconsistency in the results. Nevertheless, it has been known that under high impulse conditions, ionisation in the soil would occur due to air discharges in the air voids within the soil, and interfaces between the soil and the ground electrodes. It is also possible that the expansion of the ionisation zone, leading to the occurrence of breakdown in soil, gives better conduction in soil, producing longer streamers and higher magnitudes of current. However, limited study on the impulse breakdown characteristics of soil is found, which was believed to have been due to voltage/current magnitudes that are not high enough to cause the occurrence of soil breakdown. It is important to determine the factors that will cause breakdown to occur in soil when subjected under high impulse conditions since this will give more effective grounding systems when subjected to high impulse conditions. This paper shows that the soil grain size contributes to the most pronounced factor in influencing the soil characteristics under high impulse conditions, in comparison to any other factors. This paper considers thirty-two soil samples containing various percentages of water contents, subjected to high impulse conditions. The soil samples are housed in a hemispherical environment with two different active electrodes, and pre-breakdown and breakdown characteristics of various soils, configurations and percentage of water content are studied

A 3-year observation on analyzing cloud-to-ground lightning in Peninsular Malaysia using graph theory

Malaysia has a high amount of lightning events due to its geographical location and tropical climate, leading to substantial destruction of electrical systems and human injuries. Despite numerous studies connecting lightning activity with environmental factors, few had explored the multi-year correlation between strike patterns and times. The present study proposed a new approach employing graph theory to express Cloud-to-Ground Lightning (CGL) strike data. Using data mapping and vertex matrices, this technique visualizes CGL behavior, offering insights into lightning characteristics. The relationship between the CGL strike data across three years (2013, 2014, and 2015) was studied by using simple matching coefficient technique. Results indicate a robust positive correlation between directed graphs created across these years, suggesting consistent CGL strike behaviors in certain regions at Malaysia. The proposed method, in the form of directed edges, reduces the complexity of computation hence making it a promising integration to existing lightning prediction systems