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Implementation design of energy trading monitoring application for blockchain technology-based wheeling cases Rezi Delfianti; Bima Mustaqim; Fauzan Nusyura; Ardyono Priyadi; Imam Abadi; Adi Soeprijanto
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 3: June 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i3.pp2931-2941

One obstacle to the energy industry’s tendency toward adopting renewable energy is the requirement for a monitoring system for energy transactions based on microgrids in the wheeling scheme (shared use of utility networks). The quantity of transaction expenses for each operational generator is not monitored in any case. In this project, a mobile phone application is developed and maintained to track the total amount of fees paid and received by all wheeling parties and the amount of electricity produced by the microgrid. In the wheeling case system research, the number of transaction costs, such as network rental fees, loss costs, and profit margins, must be pretty calculated for all wheeling participants. The approach created in this study uses a blockchain system to execute transactions, and transactions can only take place if the wheeling actor and the generator have an existing contract. The application of energy trading is the main contribution of this research. The created application may track energy transfers and track how many fees each wheeling actor is required to receive or pay. Using a security system to monitor wheeling transactions will make energy trades transparent.

Adaptive virtual inertia controller based on machine learning for superconducting magnetic energy storage for dynamic response enhanced Herlambang Setiadi; Muhammad Abdillah; Yusrizal Afif; Rezi Delfianti
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i4.pp3651-3659

The goal of this paper was to create an adaptive virtual inertia controller (VIC) for superconducting magnetic energy storage (SMES). An adaptive virtual inertia controller is designed using an extreme learning machine (ELM). The test system is a 25-bus interconnected Java Indonesian power grid. Time domain simulation is used to evaluate the effectiveness of the proposed controller method. To simulate the case study, the MATLAB/Simulink environment is used. According to the simulation results, an extreme learning machine can be used to make the virtual inertia controller adaptable to system variation. It has also been discovered that designing virtual inertia based on an extreme learning machine not only makes the VIC adaptive to any change in the system but also provides better dynamics performance when compared to other scenarios (the overshoot value of adaptive VIC is less than -5×10-5).

Kontrol Tegangan pada Sistem Hybrid Panel Surya-Turbin Angin Menggunakan Manajemen Penyimpanan Baterai Soedibyo Soedibyo; Rezi Delfianti; Feby Agung Pamuji; Mochamad Ashari
Jurnal Rekayasa Elektrika Vol 16, No 3 (2020)
Publisher : Universitas Syiah Kuala

The purpose of this paper is to determine the control strategy of the renewable energy systems of hybrid solar panel power and wind turbines in maximizing voltage balance. The voltage control strategy needs to be designed, mainly when different load changes occur. If it is not done, it will affect the balance of power supplied to the load and usually damage the equipment used. Solar and wind energy sources significantly influence the stability of the applied voltage’s quality due to the fluctuating nature of renewable energy. This paper proposes control strategies for the use of PIs and the signal conditioning devices that are modified using the battery charging and discharging modeling while taking into account battery lifetime using PSIM software so that optimal voltage results from hybrid solar panel and wind turbine systems are obtained. The battery will be used as energy storage when the hybrid output power is over, which will then be used again when the hybrid output power is less than the load requirement. The signal conditioning device in this study uses five power converters, one AC to DC converter, two DC-DC boost converters, one bidirectional converter, 1 DC-AC bidirectional converter. Maximum output power uses MPPT, which is applied to the boost converter, whereas to regulate the voltage through charging and discharging the battery through the bidirectional buck-boost converter. This strategy provides the appropriate voltage on the AC side.

OPTIMALIZATION AND SOCIALIZATION OF INTERNET-BASED AQUACULTURE MEDIA CONDITION MONITORING TECHNOLOGY, ARSENIK 2 Prisma Megantoro; Rezi Delfianti; Rizki Putra Prastio; Nayu Nurrohma Hidayah; Marwan Fadhilah; Ahmad Rahmad Muzadi; Muhammad Hudzaifah Abdillah; Heru Dwi Cahyono; Hafizh Alauddin Atallah; Muhammad Rafi Nabil Arsalan
Jurnal Layanan Masyarakat (Journal of Public Services) Vol. 7 No. 3 (2023): JURNAL LAYANAN MASYARAKAT
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jlm.v7i3.2023.332-342

Indonesia's geographical condition, as a maritime country, has a wealth of natural resources in the form of water, which has the potential to support the economy in the aquaculture sector. One of them is the cultivation of freshwater fish ponds as has been carried out by the Maju Rukun Community Group (PokMas) in Ngerong Village, Pasuruan. Lack of equipment and knowledge in monitoring pond water conditions, resulting in problems with the fish nursery process. This is because water is a living medium for aquatic organisms, thus determining the survival of cultivated fish. Therefore, community service activities were held in the form of implementing an appropriate technology device "Arsenik version 2" and a mobile application that can be downloaded on Android to support water quality monitoring in aquaculture. In addition, socialization, training, and seminars regarding parameters of good pond water quality for fish farming were also provided to the Maju Rukun PokMas and the local community. Based on the positive response from the community, the implementation of the Arsenic device version 2 is considered very helpful in terms of monitoring the condition of pond water quality because it has informative parameter values and an easy presentation to understand so that the public can maintain the health of aquatic media for the aquaculture ecosystem in it.

Kontrol Tegangan pada Sistem Hybrid Panel Surya-Turbin Angin Menggunakan Manajemen Penyimpanan Baterai Soedibyo Soedibyo; Rezi Delfianti; Feby Agung Pamuji; Mochamad Ashari
Jurnal Rekayasa Elektrika Vol 16, No 3 (2020)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v16i3.16010

The purpose of this paper is to determine the control strategy of the renewable energy systems of hybrid solar panel power and wind turbines in maximizing voltage balance. The voltage control strategy needs to be designed, mainly when different load changes occur. If it is not done, it will affect the balance of power supplied to the load and usually damage the equipment used. Solar and wind energy sources significantly influence the stability of the applied voltage’s quality due to the fluctuating nature of renewable energy. This paper proposes control strategies for the use of PIs and the signal conditioning devices that are modified using the battery charging and discharging modeling while taking into account battery lifetime using PSIM software so that optimal voltage results from hybrid solar panel and wind turbine systems are obtained. The battery will be used as energy storage when the hybrid output power is over, which will then be used again when the hybrid output power is less than the load requirement. The signal conditioning device in this study uses five power converters, one AC to DC converter, two DC-DC boost converters, one bidirectional converter, 1 DC-AC bidirectional converter. Maximum output power uses MPPT, which is applied to the boost converter, whereas to regulate the voltage through charging and discharging the battery through the bidirectional buck-boost converter. This strategy provides the appropriate voltage on the AC side.

Diagnosis of fault brush winding stator induction motor using external sensor flux of three axes Delfianti, Rezi; Afif, Yusrizal; Prahesti, Fidya Eka; Mustaqim, Bima; Silalahi, Bolas Boy
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i1.pp213-221

This research investigates short-circuit problems in induction motor stators by constructing a motor with a changing winding and leaking flux data. The data is used to evaluate X, Y, and Z axes and map motor waves under normal and abnormal conditions. This study is expected to compare the effectiveness of the observation method from three different axes at the same motor condition to be further helpful in repairing induction motor damage caused by the circuit. From the results of the study, it shows that the harmonic value of the stator current will be more effective than the Y axis with a harmonic amplitude value of -38.8 dB, higher than the harmonic value of the current on the X axis with a difference of 33.89 dB and a difference of 0.32 dB from the Z axis. Suppose the disturbance is measured from the stray harmonic value. In that case, the flux will be more effective than the X axis with a harmonic amplitude value - 25.27 dB, higher than the harmonic value of the flux on the Y axis with a difference of 6.425 and a difference of 4.85 dB from the Z axis.

Enhancement of frequency transient response using fuzzy-PID controller considering high penetration of doubly fed induction generators Abdillah, Muhammad; Solehan, Alfi; Pertiwi, Nita Indriani; Setiadi, Herlambang; Jasmine, Senit Araminta; Afif, Yusrizal; Delfianti, Rezi
Bulletin of Electrical Engineering and Informatics Vol 13, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v13i4.6481

In modern power systems, renewable-based power plant such as wind power system is integrated significantly. Among numerous types of wind power systems doubly fed induction generators (DFIG) is becoming favorable in the last few years. However, adding a wind power plant could give a new challenge to the power system, especially in frequency stability. Hence, it is important to control the frequency of the power system to be able to find its initial condition in every condition. Generally, the frequency of the power system can be controlled by using automatic generation control (AGC). AGC is used to maintain the balance between generating capacity and the load by adding integral control to the governor. However, with more and more wind power systems in the grid conventional AGC is unsuitable. Hence, it is important to have an advanced AGC based on the artificial intelligence method. This paper proposed the application of fuzzy-proportional integrator derivative (fuzzy-PID) for AGC in power systems considering the high penetration of wind power systems. From the simulation results, it is found that the proposed method can reduce the overshoot and accelerate the settling time of frequency better than using conventional AGC.

Internet of Things (IoT) Based Electrical Power Monitoring System for Solar Power Plants Using Telegram Application Delfianti, Rezi; Tazayul, Venny Aminda; Mustaqim, Bima; Nusyura, Fauzan; Harsito, Catur
Vokasi Unesa Bulletin of Engineering, Technology and Applied Science Vol. 2 No. 3 (2025)
Publisher : Universitas Negeri Surabaya or The State University of Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/vubeta.v2i3.39405

Indonesia, with its tropical climate, possesses substantial solar energy potential. However, traditional monitoring of solar power systems in Indonesia still relies on manual observation, making the process inefficient, time-consuming, and prone to error. To address these limitations, this study proposes the design and implementation of a real-time Internet of Things (IoT)-based monitoring system for solar power plants using the Telegram application as the user interface. The system integrates the ESP32 microcontroller and the Pzem-004 T sensor to measure AC electrical parameters, including voltage, current, power, energy, frequency, and power factor. Unlike previous studies that used platforms such as Blynk or ThingSpeak, this research introduces Telegram as an innovative messaging-based monitoring platform, offering greater accessibility, simplicity, and user familiarity. The monitoring system was tested on a single-phase off-grid solar power setup, utilizing five types of household electrical loads, to validate its accuracy and reliability. The ESP32 communicates with the Telegram bot through Wi-Fi, and users can retrieve real-time data via predefined commands. Experimental results demonstrate high measurement accuracy, with average errors of 0.07% for voltage, 0.1% for current, and 0.08% for power. These results confirm that the system provides reliable data transmission and sensor readings. This work contributes a low-cost, efficient, and user-friendly alternative to conventional monitoring systems, particularly for decentralized renewable energy systems in remote or off-grid areas. The integration of Telegram as a communication medium for energy monitoring adds a novel dimension to IoT-based power system applications.

Protection Coordination Analysis Study Considering The Arcflash In The Electrical System Of PLTU Paiton Unit III Using IEEE Standard 1584-2002 Prahesti, Fidya Eka; Indrawati, Elsanda Merita; Delfianti, Rezi; Ukhti, Vania Aprilia
Jurnal Edukasi Elektro Vol. 7 No. 2 (2023): Jurnal Edukasi Elektro, Volume 7, Nomor 2, 2023
Publisher : DPTE FT UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jee.v7i2.64647

Arch flash is a disorder that often occurs in the electrical system of an industry or factory. In this research focusing on the analysis of the protection system by considering arc flash, it will be discussed in detail at the existing factory in East Java, namely PLTU Paiton unit 3 which is developing a unit with a capacity of 1x815 MW. The electrical system at PLTU Paiton unit 3 discusses only high and medium voltage systems. In order to support the continuity of the plant, to connect the Java-Bali electricity system, it is necessary to have a good protection coordination system to avoid black out due to one of the impacts caused by the arc of fire. After coordination of protection in the Paiton PLTU unit 3 system, arc analysis will be simulated with IEEE 1584-2002 standard calculations to find the magnitude of energy incidents and determine the safety limits of workers and also personal protective equipment according to NFPA 70E standards. The results of the study after resetting the protection coordination of PLTU Paiton unit 3 using differential rele on the SWGR-3A bus incident value of arc energy and Flash Protection Boundary (FPB) value decreased which originally reached a level outside level 4 (>40cal / cm2) to level 3 (8.1-25cal / cm2), on the SWGR-3B bus the incidence energy value was at level 3 (8.1-25cal / / cm2) dropped to level 2 (4.1-8cal / cm2), for coal hand sys bus SWGR A the energy incident value from level 3 (8.1-25cal//cm2) drops to level 0 (0 -1.2cal/cm2), while for the coal hand sys SWGR B bus the energy incident value when existing conditions reach level 3 (8.1-25cal//cm2) drops to level 0 (0-1.2cal/cm2). After obtaining the energy level of the bus, then personal protective equipment can be determined.

Implementation of Neural Networks in Daily PV Power Output Prediction Using Bayesian Regularization Algorithms to Assist Energy Management Systems Mahmudah, Norma; Delfianti, Rezi; Sigit, Firman Matiinu; Putra, Dimas Panji Eka Jala; Nusyura, Fauzan
Jurnal Edukasi Elektro Vol. 9 No. 2 (2025): Jurnal Edukasi Elektro Volume 9, No. 2, November 2025
Publisher : DPTE FT UNY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jee.v9i2.91044

Solar power plants have several advantages, namely continuous energy production, reduced electricity demand, and low photovoltaic maintenance, so that PV power output can be optimized with reliable PV power output predictions. Implementation of Artificial Neural Network (ANN) to predict photovoltaic (PV) power output, using the Bayesian Regularization algorithm. Accurate PV power output prediction is very important in power systems. The data used are solar radiation, PV module temperature, ambient temperature, and actual PV power output, with the target being the PV power output for the next day with the PV power output output for the next day. The architecture used in this study is a Cascade Forward Neural Network (CFNN) and an Elman Neural Network (ENN). Both ANN models use daily data sets and performance evaluation using Mean Square Error (MSE). The results of the study show that ENN is more accurate than CFNN. ENN had the lowest MSE of 0.00664 at a configuration of N=8 and R of 0.9922 with a training time of 6.4 seconds, while CFNN recorded the lowest MSE of 0.024306 with N=25. ENN's ability to capture time series patterns in PV is more reliable and effective. Reliable predictions can assist in energy management systems because they help maintain supply balance, reduce the risk of failure, and improve system stability.

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