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All Journal Mechatronics, Electrical Power, and Vehicular Technology Jurnal Otomasi Kontrol dan Instrumentasi Journal of Engineering and Technological Sciences
Justin Pradipta
Laboratorium Manajemen Energi, Teknik Fisika – Institut Teknologi Bandung, Gedung TP Rahmat lt.3, Jl. Ganesha No. 10 Bandung, Jawa Barat 40132
Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering

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Modelling and Identification of Oxygen Excess Ratio of Self-Humidified PEM Fuel Cell System Leksono, Edi; Pradipta, Justin; Tamba, Tua Agustinus
Journal of Mechatronics, Electrical Power and Vehicular Technology Vol 3, No 1 (2012)
Publisher : Research Centre for Electrical Power and Mechatronics, Indonesian Istitutes of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (958.679 KB) | DOI: 10.14203/j.mev.2012.v3.39-48

Abstract

One essential parameter in fuel cell operation is oxygen excess ratio which describes comparison between reacted and supplied oxygen number in cathode. Oxygen excess ratio relates to fuel cell safety and lifetime. This paper explains development of air feed model and oxygen excess ratio calculation in commercial self-humidified PEM fuel cell system with 1 kW output power. This modelling was developed from measured data which was limited in open loop system. It was carried out to get relationship between oxygen excess ratio with stack output current and fan motor voltage. It generated fourth-order 56.26% best fit ARX linear polynomial model estimation (loss function = 0.0159, FPE = 0.0159) and second-order ARX nonlinear model estimation with 75 units of wavenet estimator with 84.95% best fit (loss function = 0.0139). The second-order ARX model linearization yielded 78.18% best fit (loss function = 0.0009, FPE = 0.0009).
Adaptive Ensemble Learning for Enhancing Building Energy Consumption Prediction: Insights from COVID-19 Pandemic Energy Consumption Dynamics Handre Kertha Utama, Putu; Leksono, Edi; Nashirul Haq, Irsyad; Indrapraja, Rachmadi; Mahesa Nanda, Rezky; Friansa, Koko; Fauzi Iskandar, Reza; Pradipta, Justin
Journal of Engineering and Technological Sciences Vol. 57 No. 2 (2025): Vol. 57 No. 2 (2025): April
Publisher : Directorate for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2025.57.2.2

Abstract

Buildings account for approximately 40% of the total global energy consumption. Therefore, accurate prediction of building energy consumption is necessary to optimize resource allocation and promote sustainable energy usage. A key challenge in developing building energy consumption models is their adaptability to abrupt changes in consumption patterns owing to extraordinary events, such as the COVID-19 pandemic. Therefore, a two-layer ensemble-learning (EL) model incorporating sliding windows as input features is proposed. The model is a two-layer stacking EL consisting of two base learning methods: (1) support vector regression (SVR), and (2) random forest (RF). Temperature and humidity are included to account for the influence of weather conditions on energy consumption. The proposed model is deployed to forecast building energy consumption both before (November 2019) and during (May – October 2020) the COVID-19 pandemic and is compared with a single machine learning model. The results demonstrate that the EL model outperforms the SVR and RF methods, providing excellent prediction accuracy even during the pandemic when significant changes in energy consumption patterns occurred. The findings also highlight the effectiveness of sliding windows as input features for improving model adaptability. Additionally, the analysis reveals that temperature is more prominent than humidity for improving prediction accuracy.
Sistem Arsitektur Manajemen Bangunan untuk Memaksimalkan Swakonsumsi pada Bangunan Universitas: Studi Kasus Puspita, Yumna; Nanda, Rezky Mahesa; Arif M. Natawidjaja, Reyza; Friansa, Koko; Pradipta, Justin; Armanto Mangkuto, Rizki; N. Haq, Irsyad; Leksono, Edi; Wasesa, Meditya
Jurnal Otomasi Kontrol dan Instrumentasi Vol 15 No 2 (2023): Jurnal Otomasi Kontrol dan Instrumentasi
Publisher : Pusat Teknologi Instrumentasi dan Otomasi (PTIO) - Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/joki.2023.15.2.5

Abstract

Due to its intermittent nature, significant adoption of solar PV into the grid can decrease grid reliability. One solution to increase it is to increase PV self-consumption with two methods: adding Energy Storage System (ESS) and conducting Demand Side Management (DSM). University building has a distinct characteristic in its complex dynamics. Therefore, there is a lack of research to control both methods of increasing self-consumption. This paper aimed to do an integrated literature review on increasing self-consumption and then propose a system architecture recommendation for university building management based on the review. The Smart Grid Architectural Model (SGAM) evaluated the case study object. The result showed that a data-driven controller has been chosen as the most suitable controller for the university building management system. The data needed to build a data-driven controller could be obtained through readily available sensors in the case study object, making it feasible for implementation.
Enhancing the Reliability of Photovoltaic Systems in Microgrid at Campus Area Hanadi; Christian, Hadi; Tomoyahu, Syafril; Faniama, Virara; Pradipta, Justin; Haq, Irsyad N. Haq; Leksono , Edi
Jurnal Otomasi Kontrol dan Instrumentasi Vol 16 No 1 (2024): Jurnal Otomasi Kontrol dan Instrumentasi
Publisher : Pusat Teknologi Instrumentasi dan Otomasi (PTIO) - Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/joki.2024.16.1.3

Abstract

This paper assesses the reliability of photovoltaic systems within a microgrid, considering the system's operational mode and monthly data on solar radiation and load demand. The evaluation encompasses various reliability metrics, including microgrid failure rate, interruption duration, system unavailability, EENS, EIR, LOLE, and LOLP, with the objective of minimizing these parameters. The methodologies applied involve the Markov model and artificial intelligence algorithms such as Naive Bayes and Support Vector Machine (SVM). Results indicate that the microgrid exhibits enhanced reliability in an on-grid mode configuration, with a LOLP value of 0.0008. Furthermore, employing machine learning, specifically SVM, for LOLP calculation based on solar radiation yields a more precise value of 0.7245. This study offers valuable insights for policymakers and system designers in determining the optimal configuration for microgrids.
Audit Energi Menggunakan Intensitas Konsumsi Energi untuk Konservasi Energi di Gedung Kampus Faniama, Virara; Hanadi; Christian, Hadi; Tomoyahu, Syafril; Pradipta, Justin; Nashirul Haq, Irsyad; Leksono, Edi
Jurnal Otomasi Kontrol dan Instrumentasi Vol 16 No 1 (2024): Jurnal Otomasi Kontrol dan Instrumentasi
Publisher : Pusat Teknologi Instrumentasi dan Otomasi (PTIO) - Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/joki.2024.16.1.6

Abstract

Energy auditing is an essential step in optimizing energy use in commercial buildings. This research explores the application of energy auditing with the Energy Consumption Intensity method to improve energy efficiency in campus buildings. Considering the changes in occupancy and activity patterns in the university environment can provide a comprehensive insight into the associated energy consumption patterns. The audit analyzed the building's energy consumption and identified potential energy savings to improve energy efficiency. Energy data was collected and analyzed to evaluate the building's energy performance. Recommended energy conservation measures include updating the lighting system, optimizing the cooling system, and improving the efficiency of equipment use. This research recommends that campus building managers adopt sustainable practices in energy management, which can lead to reduced operational costs and lower environmental impacts. Thus, the energy audit approach with the IKE method is a relevant and effective strategy for achieving energy conservation goals in the university environment. Based on the analysis, the latest IKE for Labtek V is 38.01 (2021), while the IKE for Labtek VI is 16.75 (2021), showing inefficiency of energy use in both buildings inefficient.
Analisis Pengaruh Variasi Laju Aliran Air pada Sistem Pendinginan Modul Fotovoltaik dengan Simulasi CFD (Computational Fluid Dynamics) Tomayahu, Syafril Agustion; Rozaq, M. Sya'banur; Romadhon, Rahmat; Pradipta, Justin; Haq , Irsyad N.; Leksono, Edi
Jurnal Otomasi Kontrol dan Instrumentasi Vol 16 No 2 (2024): Jurnal Otomasi Kontrol dan Instrumentasi
Publisher : Pusat Teknologi Instrumentasi dan Otomasi (PTIO) - Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/joki.2024.16.2.9

Abstract

Developing renewable energy is one of the main strategies to reduce greenhouse gas emissions and achieve global goals to limit global warming above pre-industrial temperatures. This study analyzes the effect of varying the cooling water flow rate on MS100-36 type polycrystalline photovoltaic modules through ANSYS Fluent 2024 R1 Student simulation. This simulation was conducted from 08:00 to 17:00, focusing on the influence of inlet water temperature on the temperature distribution of photovoltaic modules. The simulation results indicate thermal steady-state conditions at an irradiation of 463 W/m² with a natural coefficient of 5 W/m².There is a temperature distribution process occurring in the photovoltaic module under fluent conditions, where the effect of the inlet water temperature on the surface of the PV module is examined for a water temperature range of 20°C to 30°C in 5°C intervals, with water flow rates of 0.05, 0.1, and 0.2 kg/s. The contour images indicate that an increase in water flow rate can enhance the cooling effect of the photovoltaic module. Higher inlet water temperatures transfer less heat, producing higher temperatures for the photovoltaic modules. A water flow rate of 0.2 kg/s and an inlet water temperature of 20°C produce a lower and more uniform temperature distribution on the photovoltaic modules. Thus, increasing the water flow rate and decreasing the inlet water temperature have proven effective in enhancing the cooling performance of photovoltaic modules.
Co-Authors Arif M. Natawidjaja, Reyza Armanto Mangkuto, Rizki Christian, Hadi Edi Leksono Edi Leksono Faniama, Virara Friansa, Koko Hanadi Handre Kertha Utama, Putu Haq , Irsyad N. Haq, Irsyad N. Haq Indrapraja, Rachmadi Leksono , Edi Mahesa Nanda, Rezky N. Haq, Irsyad Nanda, Rezky Mahesa Nashirul Haq, Irsyad Puspita, Yumna Reza Fauzi Iskandar Romadhon, Rahmat Rozaq, M. Sya'banur Tomayahu, Syafril Agustion Tomoyahu, Syafril Tua Agustinus Tamba Wasesa, Meditya