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All Journal EMITTER International Journal of Engineering Technology Prosiding SENTIKUIN (Seminar Nasional Teknologi Industri, Lingkungan dan Infrastruktur)
Erik Tridianto, Erik
Politeknik Elektonika Negeri Surabaya
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Energy Engineering Industrial & Manufacturing Engineering

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Power Generation Forecasting of Dual-Axis Solar Tracked PV System Based on Averaging and Simple Weighting Ensemble Neural Networks Rohman, Budiman Putra Asmaur; Hilman, Catur; Tridianto, Erik; Ariwibowo, Teguh Hady
EMITTER International Journal of Engineering Technology Vol 6, No 2 (2018)
Publisher : Politeknik Elektronika Negeri Surabaya (PENS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (12.589 KB) | DOI: 10.24003/emitter.v6i2.341

Abstract

Solar power is a renewable energy interest many researchers around the world to be explored for human life beneficial especially for electric power generation. Photovoltaic (PV) is one of technology developed massively to exploit the solar power for this purpose. However, its performance is very sensitive to environmental condition such as solar irradiance, weather, and climatic behavior. Thus, the hybrid power generation systems are developed to solve this output uncertainty problem. To support this such hybrid system, this paper proposes an ensemble neural network based forecaster of the power output of PV systems which will lead an efficient power management. The object of this research is the PV systems equipped with two axes automated solar tracking with peak power 10Wp. The proposed ensemble forecaster model employs four multi-layer perceptron neural networks with two hidden layers as base forecasters while the input number of historical data is varied in order to exploit the forecaster diversity. The final prediction is calculated both by conventional averaging and simple weighting optimized by the least square fitting technique. According to the research results, the both proposed approaches provide low error rate. Moreover, in term of comparison, the ensemble model with averaging combining technique gives the highest accuracy comparing to the other ensemble and conventional neural network structures.
Monitoring Renewable Energy Dengan Konsep Mini SCADA Menggunakan IoT Wahyu Pratama , Muhammad Syafii ; Tridianto, Erik; Permatasari, Prima Dewi
Prosiding SENTIKUIN (Seminar Nasional Teknologi Industri, Lingkungan dan Infrastruktur) Vol 2 (2019): PROSIDING SENTIKUIN
Publisher : Fakultas Teknik Universitas Tribhuwana Tunggadewi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (386.799 KB)

Abstract

The supply of electricity for the people of Indonesia is still dependent on PLN. PLN as a company that provides electrical energy often experiences problems that result in rotating blackouts due to peak load and theft which impact on consumers. In this research renewable energy monitoring has been designed using the mini scada concept which is integrated with IoT. The Miniscada concept has the advantage of being able to monitor the amount of electricity generated by renewable energy online, realtime and together wirelessly. By using the SCADA concept which has the function ckient and server. Client as a transmitter is used as a place to read data from the sensor before it is sent to the server. The server as a receiver is used as a place to store data sent by the transmitter and can be monitored online and in real time. The server receives all information on the amount of electricity emitted through the transmitter using a 2.4Ghz frequency radio and uploads the amount of electricity from the server to the cloud platform Blynk application. By utilizing IoT technology that makes it easy to monitor data in the form of voltage and current from solar panels, wind turbines and PLN with IoT via a smartphone. So that the data obtained in the form of AC voltage with 0.9% error DC voltage from Solar Panels with error 1.89% AC current from incandescent lamps 25 watts with error 0.7% DC current from batteries with an error of 3%.
Rancang Bangun Control Valve untuk Sistem Pengendalian pada Tangki Peyimpanan Azhim, Fadlul; Gayuh Prasetya, Hendrik Elvian; Tridianto, Erik
Prosiding SENTIKUIN (Seminar Nasional Teknologi Industri, Lingkungan dan Infrastruktur) Vol 2 (2019): PROSIDING SENTIKUIN
Publisher : Fakultas Teknik Universitas Tribhuwana Tunggadewi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (530.995 KB)

Abstract

The control system is an engineering discipline that involves mechanisms and algorithms to control the output of a process with the desired results. Modern industries and power plants use control valves as a control system in storage tanks. The control valve is a very important component in this regard as a final element. Therefore, we designed a control valve starting from the sizing control valve, mathematical modeling of the system to programming on Arduino and Visual Basic .NET so that it can be observed and understood directly. After sizing the control valve, it can be seen the type of valve that meets the valve opening standard is Globe valve at 46.8% and Ball valve at 33.0%. In this study, the commonly used PID tuning method is Ziegler Nichols tuning method to test the control system. The PID parameter is obtained through the tuning results in the Matlab simulation using mathematical modeling of the system. Control valve simulation with Matlab produces parameters Kp= 0.5625, Ti= 0.3, and Td= 0.7. While the control level produces a parameter Kp= 1.36, Ti= 3.33. The control level of the storage tank is better to use PI control compared to PID controls which continue to increase water levels. Changes in set point from 1 cm to 20 cm produce a 37-seconds settling time with a maximum overshoot value of 6 cm.
Co-Authors Azhim, Fadlul Budiman Putra Asmaur Rohman Hendrik Elvian Gayuh Prasetya, Hendrik Elvian Hilman, Catur Prima Dewi Permatasari Teguh Hady Ariwibowo Wahyu Pratama , Muhammad Syafii