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Grounding rods are an important component in electrical power to protect equipment from overvoltage and current disturbances. However, corrosion can cause a significant decrease in performance and reduce system efficiency. Therefore, the diagnosis of corrosion on grounding rods is important to ensure the reliability and continuity of substation operations. In this research, a corrosion structure diagnosis was done on the grounding rod in the Belawan Port area using COMSOL Multiphysics 5.3 software. The element method is used to model the electrochemical corrosion phenomena that occur in grounding rods. Corrosion-causing factor parameters such as soil resistance, pH, temperature, humidity, and salt content are measured and evaluated. The analysis results show that there is significant corrosion on the grounding rod, especially in areas exposed to sea water and corrosive environments. The potential distribution shows uneven potential along the grounding rod. Based on this research, additional maintenance and protection measures can be proposed to reduce the risk of corrosion and extend the life of grounding rod equipment. Based on the analysis results, the input parameters differentiate electrolyte reactions which further determine grounding rod.

Microgrids are small networks consisting of several renewable energy sources such as wind light, sunlight, geothermal, bioenergy, water and so on. But the drawback of this system is in fluctuating power and when the source does not produce power at a certain time. So that power storage media such as batteries and supercapacitors are needed to maintain contingency when the source does not supply enough load. The purpose of this study was toobtain the effect of adding supercapacitors with batteries and compare battery storage media without supercapacitors. From the results of the study, it was found that the addition of supercapacitors can maintain battery stability charging from 50% State of Charge (SOC) down to 47% and start It rises back by 50% at 1 second, as well as additional charging can be set to our liking. If the battery storage media is without supercapacitors, battery charging tends to drop from 50% and continue to fall without any increaseat all. So it can be concluded that with the addition of supercapacitors are able to maintain the performance of the battery in the microgrid system.

This paper proposes an Artificial Neural Network (ANN) model using a Multi-Stage method to optimize the configuration of an External Lightning Protection System (ELPS) and grounding system. ELPS is a system designed to protect an area from damage caused by lightning strikes. Meanwhile, the grounding system functions to direct excess electric current from lightning strikes into the ground. This study identifies the optimal protection system configuration, reducing the need for excessive components. The ELPS configuration includes the number of protection pole units and the height of the protection poles. In contrast, the grounding system configuration consists of the number of electrode units and the length of the electrodes. This study focuses on the protection system configuration at a Photovoltaic Power Station, where the area is highly vulnerable to lightning strikes. Several aspects need to be considered in determining the appropriate configuration, such as average thunderstorm days per year, ELPS efficiency, total area of photovoltaic module, area to be protected, soil resistivity, electrode spacing factor, and the total required electrode resistance. The proposed multi-stage ANN model consists of three processing stages, each responsible for handling a portion of the overall system tasks. The first stage is responsible for determining the protection pole configuration. In the second stage, the Lightning Protection Level (LPL) classification is performed. Then, in the third stage, the process of determining the grounding configuration is handled. The analysis results show that the Multi-Stage ANN model can effectively determine the configuration with a low error rate: MAE of 0.265, RMSE of 0.314, and MPE of 9.533%. This model can also explain data variation well, as indicated by the high R 2 value of 0.961. The comparison results conducted with ATP/EMTP software show that the configuration produced by ANN results in fewer protection pole units but with greater height. Meanwhile, ANN produces a configuration with shorter electrode lengths but fewer units in the grounding system. [ABSTRACT FROM AUTHOR]