The issue of unbalance in electrical distribution systems is a significant challenge that requires effective management to ensure stability, reliability, and safety. Load imbalance can result in overheating of transformers and other electrical equipment, reducing their operational life and increasing the risk of failure, even leading to power outages.

Battery management systems are essential in electric vehicles and renewable energy applications, especially in terms of ensuring optimal battery health and performance and regarding the state of charge (SOC) in batteries consisting of many cells. The lifetime and efficiency of the battery depend on the accuracy of the SOC parameter estimation. Moreover, systems that apply active balancing technology are able to move cells with high SOC data to cells with low SOC. Many methods have been developed, but their long execution time makes them less optimal when applied. High-speed SOC estimation is required in active balancing technology, in addition to high accuracy. Therefore, this study proposes the estimation of SOC parameters using a statistical and metaheuristic approach from voltage and current input data in each battery cell. The experimental results showed that the metaheuristic-based method (ANFIS) had better RSME and R² values compared with the polynomial and linear regression or even the machine learning-based method (recurrent neural network) for training data.

Battery management systems are essential in electric vehicles and renewable energy applications, especially in ensuring optimal battery health and performance. Especially regarding the state of charge (SOC) in batteries consisting of many cells. The lifetime and efficiency of battery depend on the accuracy of the SOC parameter estimation. Moreover, the system that applies active balancing technology will move cells that have high SOC data to cells that have low SOC. Many methods have been developed, but the long execution time makes it less than optimal when applied. The speed of SOC estimation is also required in active balancing technology in addition to the accuracy factor. Therefore, this study proposes to estimate SOC parameters using a statistical and metaheuristic approach method from voltage and current input data in each battery cell. The experimental results showed that the metaheuristic-based method (ANFIS) had better RSME and R2 values compared to the polynomial and linear regression method.

Fish cultivation in tarpaulin ponds or Biofloc Technology (BFT) has been widely practiced by the community. Net fish production at BFT is 45% higher than at others. Tarpaulin ponds with a diameter of 1-2 meters (m) can be filled with 1,000-3,000 catfish seeds. The problem is that when fish farming runs for ± 1 month, the ammonia content in the pond begins to be felt, marked by an unpleasant odor in the pond water. Excessive ammonia content can cause fish to die easily, disrupting the environment and health. The research objective is to design, manufacture, test, and implement an automatic control system for ammonia content in biofloc ponds, which will be implemented in 2022. The re-search method is an experimental method. The stages include: designing and making monitoring of ammonia content, designing and manufacturing an auto-matic water disposal system, and testing and implementing an automatic control system for ammonia content in biofloc ponds. The test results show that the au-tomatic ammonia controller can work well. When a certain level of ammonia is detected in the pool water, the ammonia sensor is active and provides information to the microcontroller to activate the solenoid and open the drain, so that the pool water is reduced and replaced with new water. The reduction in ammonia levels is done by reducing the capacity of the pool water (the old one) and adding new water automatically and adding a water neutralizer in the form of lime.

In an effort to determine the Personal Protective Equipment (PPE) required to protect against arc-flash hazards based on IEEE Std. 1584-2002, a simplified analysis technique was used with the energy limit curve method. The problem addressed was the potential inaccuracies in determining the required PPE level and maximum flash-protection distance when the traditional method does not precisely calculate the incident energy level and flash-protection limit. The purpose of this study was to evaluate a method that could be applied to various types of overcurrent protective devices in electrical systems, thus simplifying the arc-flash analysis. The method involved using the energy limit curve, which allows for quicker determination of the necessary PPE by plotting relay/fuse curves into the energy limit curve. This approach was implemented and tested at PLTU Paiton Unit 7 (PT. POMI). Important findings indicated that the energy limit curve method significantly reduced the time required to determine the appropriate PPE category compared to the IEEE 1584-2002 standard. The results showed that the process of determining the PPE category was more efficient, with fewer data requirements and shorter calculation times. The implications of this research suggest that the energy limit curve method can simplify arc-flash calculations for large industries with numerous buses, enhancing the overall safety protocols by providing a faster and potentially more accurate means of assessing arc-flash hazards and PPE requirements.

Minimnya pencahayaan di wilayah RT. 02 RW. 20 Kelurahan Purwantoro, Kecamatan Blimbing, Kota Malang, menyebabkan risiko kecelakaan dan tindak kriminalitas di malam hari. Program pengabdian ini bertujuan mengatasi masalah tersebut dengan penerapan smart lighting system yang hemat energi. Metode yang digunakan melibatkan pemasangan sistem pencahayaan di empat titik strategis menggunakan pendekatan community-based, di mana warga berpartisipasi dalam instalasi dan pemeliharaan. Survei awal dilakukan untuk mengidentifikasi kebutuhan, dilanjutkan dengan pelatihan penggunaan teknologi kepada warga. Hasil menunjukkan peningkatan keamanan dan kenyamanan warga, serta pengurangan konsumsi energi listrik. Teknologi smart lighting yang diterapkan terbukti efisien, otomatis, dan meningkatkan partisipasi warga dalam merawat fasilitas umum. Program ini juga berhasil memperluas pemahaman masyarakat tentang teknologi hemat energi. Implikasi program menunjukkan pentingnya penerapan teknologi tepat guna untuk meningkatkan kesejahteraan masyarakat, dan berpotensi dikembangkan lebih lanjut dengan integrasi energi terbarukan seperti panel surya.