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All Journal Mechatronics, Electrical Power, and Vehicular Technology Jurnal Teknologi Elektro JMM (Jurnal Masyarakat Mandiri) Jurnal Otomasi Kontrol dan Instrumentasi Green Intelligent Systems and Applications eProceedings of Engineering Community Service Seminar and Community Engagement (COSECANT) Warta LPM
Irwan Purnama
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Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Social Sciences Other

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Journal : Mechatronics, Electrical Power, and Vehicular Technology

 1 
Increasing efficiency of a 33 MW OTEC in Indonesia using flat-plate solar collector for the seawater heater Setiawan, Iwan Rohman; Purnama, Irwan; Halim, Abdul
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 8, No 1 (2017)
Publisher : Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (6603.048 KB) | DOI: 10.14203/j.mev.2017.v8.33-39

Abstract

This paper presents a design concept of Ocean Thermal Energy Conversion (OTEC) plant built in Mamuju, West Sulawesi, with 33 MWe and 7.1% of the power capacity and efficiency, respectively. The generated electrical power and the efficiency of OTEC plant are enhanced by a simulation of a number of derived formulas. Enhancement of efficiency is performed by increasing the temperature of the warm seawater toward the evaporator from 26ËšC up to 33.5ËšC using a flat-plate solar collector. The simulation results show that by increasing these a water temperature up to 33.5ËšC, the generated power will increase up to 144.155 MWe with the OTEC efficiency up to 9.54%, respectively. The required area of flat-plate solar collector to achieve the results is around 6.023 x 106 m2.
Increasing efficiency of a 33 MW OTEC in Indonesia using flat-plate solar collector for the seawater heater Iwan Rohman Setiawan; Irwan Purnama; Abdul Halim
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 8, No 1 (2017)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2017.v8.33-39

Abstract

This paper presents a design concept of Ocean Thermal Energy Conversion (OTEC) plant built in Mamuju, West Sulawesi, with 33 MWe and 7.1% of the power capacity and efficiency, respectively. The generated electrical power and the efficiency of OTEC plant are enhanced by a simulation of a number of derived formulas. Enhancement of efficiency is performed by increasing the temperature of the warm seawater toward the evaporator from 26˚C up to 33.5˚C using a flat-plate solar collector. The simulation results show that by increasing these a water temperature up to 33.5˚C, the generated power will increase up to 144.155 MWe with the OTEC efficiency up to 9.54%, respectively. The required area of flat-plate solar collector to achieve the results is around 6.023 x 106 m2.
LSTM-based forecasting on electric vehicles battery swapping demand: Addressing infrastructure challenge in Indonesia Muhammad Zakiyullah Romdlony; Rashad Abul Khayr; Aam Muharam; Eka Rakhman Priandana; Sudarmono Sasmono; Muhammad Ridho Rosa; Irwan Purnama; Amin Amin; Ridlho Khoirul Fachri
Journal of Mechatronics, Electrical Power, and Vehicular Technology Vol 14, No 1 (2023)
Publisher : National Research and Innovation Agency

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.mev.2023.v14.72-79

Abstract

This article aims to design a model for forecasting the number of vehicles arriving at the battery swap station (BSS). In our case, we study the relevance of the proposed approach given the rapid increase in electric vehicle users in Indonesia. Due to the vehicle electrification program from the government of Indonesia and the lack of supporting infrastructure, forecasting battery swap demands is very important for charging schedules. Forecasting the number of vehicles is done using machine learning with the long short-term memory (LSTM) method. The method is used to predict sequential data because of its ability to review previous data in addition to the current input. The result of the forecasting using the LSTM method yields a prediction score using the root-mean-square error (RMSE) of 2.3079 x 10-6 . The forecasted data can be combined with the battery charging model to acquire predicted hourly battery availability that can be processed further for optimization and scheduling.
Co-Authors A Halim Aam Muharam Abdul Halim Amin Amin Angga Rusdinar Artha Ivonita Simbolon Augustina Asih Rumanti Bandiyah Sri Aprillia Carolus Kaswandi Desri Kristina Silalahi Eka Rakhman Priandana Galih Ryan Bagastama Ilma Mufidah Indra Sucipta Ismail Maulana Juned Iwan Rohman Setiawan Jangkung Raharjo Joni Welman Simatupang Kemal Muhammad Rais Kharisma Bani Adam Mohamad Ramdhani Muhammad Afan Aljafar MUHAMMAD ARIFIN Muhammad Ridho Rosa Muhammad Zakiyullah Romdlony Noval Hadriawan Novan Agung Mahardiono Novi Prihatiningrum Porman Pangaribuan Rahmat Ihsani Yuskar Rashad Abul Khayr Ridlho Khoirul Fachri Risna Septisari Rospawan, Ali Setiawan, Iwan Rohman Sudarmono Sasmono Ulfah Nadiya Yusuf Nur Wijayanto Yusuf Nur Wijayanto