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International Journal of Renewable Energy Development
Published by Center of Biomass and Renewable Energy
ISSN : 22524940     EISSN : 27164519     DOI : https://doi.org/10.61435/ijred.xxx.xxx
Core Subject : Science, Engineering,
Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering
The International Journal of Renewable Energy Development - (Int. J. Renew. Energy Dev.; p-ISSN: 2252-4940; e-ISSN:2716-4519) is an open access and peer-reviewed journal co-published by Center of Biomass and Renewable Energy (CBIORE) that aims to promote renewable energy researches and developments, and it provides a link between scientists, engineers, economist, societies and other practitioners. International Journal of Renewable Energy Development is currently being indexed in Scopus database and has a listing and ranking in the SJR (SCImago Journal and Country Rank), ESCI (Clarivate Analytics), CNKI Scholar as well as accredited in SINTA 1 (First grade category journal) by The Directorate General of Higher Education, The Ministry of Education, Culture, Research and Technology, The Republic of Indonesia under a decree No 200/M/KPT/2020. The scope of journal encompasses: Photovoltaic technology, Solar thermal applications, Biomass and Bioenergy, Wind energy technology, Material science and technology, Low energy architecture, Geothermal energy, Wave and tidal energy, Hydro power, Hydrogen production technology, Energy policy, Socio-economic on energy, Energy efficiency, planning and management, Life cycle assessment. The journal also welcomes papers on other related topics provided that such topics are within the context of the broader multi-disciplinary scope of developments of renewable energy.
Arjuna Subject : Energi (semua kategori) - Energi Terbarukan, Keberlanjutan dan Lingkungan
Articles 18 Documents
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Search results for , issue "Vol 13, No 4 (2024): July 2024" : 18 Documents clear
Implementation of pumped hydro/photovoltaic systems in mining-degraded areas: a case study in Quadrilátero Ferrífero, Minas Gerais, Brazil Guimarães, Alberto de Almeida Bossi; Bastos, Adriano Silva; Viana, Edna Maria de Faria; Mendes, Victor Flores; Martinez, Carlos Barreira
International Journal of Renewable Energy Development Vol 13, No 4 (2024): July 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60005

Abstract

This work presents a proposal for the transformation of mining-degraded areas into renewable energy installations, converting deactivated mine pits, in the Quadrilátero Ferrífero (QF) region in state of Minas Gerais (MG), Brazil, into reservoirs for Pumped Storage Hydropower (PSH). Additionally, it proposes the alteration of adjacent areas impacted by mining extraction process, through their conversion into Photovoltaic Power Plants (PV). This measure has the potential to turn mining liabilities into sources of energy with lower environmental impact and sustainability for society. This process allows energy to be stored in the form of hydraulic batteries, which can mitigate the effects of intermittency of photovoltaic generation in the electrical grid. The presented methodology involves mapping deactivated mines, calculating the energy potential of the coupled PSH and PV systems, and conducting an economic feasibility study for PSH implementation. The work includes a case study discussing potential local environmental impacts and the energy potentials of this solution. The case study resulted in identifying a suitable pair of mine pits for a PSH in the QF, capable of supplying the electrical grid with approximately 234.3 MW, with the generated energy cost ranging between U$112.26/MWh to U$167.22/MWh. It is concluded that utilizing inactive mines as PSH reservoirs and installing PV in adjacent mining-degraded areas are innovative and technologically feasible strategies. Economically, their implementation will depend on the market price of energy.
Optimization of the PVT performance with various orientations of jets and MFFNN-RSA prediction model for smart buildings Al-Otaibi, Ali; Hatata, Ahmed Y.; Alruqi, Mansoor; Alabdullatief, Aasem; Essa, Mohamed A.
International Journal of Renewable Energy Development Vol 13, No 4 (2024): July 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60129

Abstract

The combined thermal and photovoltaic technology in PV/T systems is considered as a greatly promising technology for smart buildings. Thus, investigations for enhancing the PV/T performance are still proceeding. This research presents an investigation for novel configurations of cooling jets for the PVT system. The linear and circular distribution for the inlet jets considering regular and irregular positioning for all the jets as new cooling configurations are implemented. Moreover, the proposed geometrical configurations are optemized regarding the performance to identify the most suitable configuration that achieves the optimum efficiency and temperature. Furthermore, a novel hybrid ANN model is presented for predicting the performance of the PVT systems. This model combines the multi-feedforward neural network (MFFNN) with an optimization technique called reptile search algorithm (RSA). The proposed model can process the studied parameters to predict the PVT performance parameters (top surface temperature, temperature un-uniformity, outlet temperature, and efficiencies). The proposed MFFNN-RSA model minimized the mean square error to less than 0.4857×10-3. The maximum temperature decrease achieved by the presented configuration reached 60.62K compared to the uncooled case, while the minimum temperature un-uniformity reached 1K and 6K for 400 and 1000 W/m2, respectively. The increase of the ambient temperature found to decrease the temperature un-uniformity in all the cases. The irregular jet with the linear distribution was found to achieve the optimum performance of the overall, thermal, and electrical efficiencies of 63.5%, 49.6%, and 14.25%, respectively. Furthermore, the electricity production cost was reduced by 11.6%, and the yearly CO2 emissions were reduced by 215.3 kg/m2 compared to the normal PV system. The proposed irregular-line distribution of the jets is found to be the best configuration regarding the temperature of the PV model and the overall efficiency considering the pumping losses.
Effects of CaO addition into CuO/ZnO/Al2O3 catalyst on hydrogen production through water gas shift reaction Hastuti, Zulaicha Dwi; Rosyadi, Erlan; Anindita, Hana Nabila; Masfuri, Imron; Rahmawati, Nurdiah; Rini, Tyas Puspita; Anggoro, Trisno; Prabowo, Wargiantoro; Saputro, Frendy Rian; Syafrinaldy, Ade
International Journal of Renewable Energy Development Vol 13, No 4 (2024): July 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.59257

Abstract

Hydrogen is a promising renewable energy carrier and eco-friendly alternative to fossil fuels. Water-gas-shift reaction (WGSR) is commonly used to generate hydrogen from renewable biomass feedstocks. Enriching hydrogen content in synthesis gas (syngas) production can be made possible by applying the WGSR after gasification. WGSR can achieve a maximal carbon monoxide (CO) conversion using a commercially patented CZA (Cu/ZnO/Al2O3) catalyst. This study proposed three in-lab self-synthesized CZA catalysts to be evaluated and compared with the patented catalyst performance-wise. The three catalysts were prepared with co-precipitation of different Cu:Zn:Al molar ratios: CZA-431 (4:3:1), CZA-531 (5:3:1) and CZA-631 (6:3:1). The catalysts characteristics were determined through X-ray diffraction (XRD), Brunauer-Emmett-Teller (BET) analysis and Scanning Electron Microscopy (SEM) techniques. CO gas was mixed with steam in a catalytic reactor with a 3:1 molar ratio, running continuously through the catalyst at 250 °C for 30 mins. All three catalysts, however, performed below expectations, where CZA-431 had a CO conversion of 77.44%, CZA-531 48.75%, and CZA-631 71.67%. CaO, as a co-catalyst, improved the performance by stabilizing the gas composition faster. The CO conversion of each catalyst also improved: CZA-431 improved its CO conversion to 97.39%, CZA-531 to 96.71%, and CZA-631 to 95.41%. The downward trend of the CO conversion was deemed to be caused by copper content found in CZA-531 and CZA-631 but not in CZA-431, which tended to form a Cu-Zn metal complex, weakening the catalyst's activity.
Effects of carbon nanotubes and carbon fibers on the properties of ultra-high performance concrete for offshore wind power generation Chen, Jing
International Journal of Renewable Energy Development Vol 13, No 4 (2024): July 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60135

Abstract

Ultra-high performance concrete (UHPC), as one of the most eye-catching building materials, has been the subject of extensive research by scholars. On this basis, to expand the application of UHPC for offshore wind turbine towers in complex marine environments, three different fiber materials - copper-plated microfibre steel fibers, carbon fibers, and carbon nanotubes (CNTs) - have been selected for the study of the possibilities of further improving the mechanical properties of UHPC. This study focused on understanding the impact of various fiber combinations and dosages on the flowability, compressive strength, flexural strength, and tensile strength of UHPC. Our findings indicate that carbon fiber, when present at a concentration of up to 0.5%, the effect on the fluidity of UHPC is only about 1.05%. However, the addition of CNTs significantly diminishes the flowability of UHPC, with a consistent decrease observed as the CNT content increases. Notably, when carbon fiber and CNTs are used in combination, the maximum reduction in flowability reaches 7.8%. Furthermore, as the dosage of these fibers increases, the compressive strength, flexural strength, and tensile strength of UHPC all demonstrate a positive trend of improvement. It is observed that the optimal performance is achieved when both carbon fiber and CNTs are present. In particular, carbon fiber exhibits a more profound impact on enhancing compressive strength and flexural strength, when carbon fibers were doped by volume at 0.5%, the compressive and flexural strengths were increased by 6.7% and 11.7%, respectively, compared to the control group, while carbon nanotubes increased the tensile strength by 7.4% at lower dosage. These findings highlight the potential of fiber combinations to optimize UHPC’s mechanical properties for various engineering applications..
Biomass and organic waste conversion for sustainable bioenergy: A comprehensive bibliometric analysis of current research trends and future directions Alao, Kehinde Temitope; Gilani, Syed Ihtsham-ul-Haq; Sopian, Kamaruzzaman; Alao, Taiwo Onaopemipo; Oyebamiji, Damilare Samuel; Oladosu, Temidayo L
International Journal of Renewable Energy Development Vol 13, No 4 (2024): July 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60149

Abstract

The rising demand for renewable energy sources has fueled interest in converting biomass and organic waste into sustainable bioenergy. This study employs a bibliometric analysis (2013-2023) of publications to assess trends, advancements, and future prospects in this field. The analysis explores seven key research indicators, including publication trends, leading contributors, keyword analysis, and highly cited papers.  We begin with a comprehensive overview of biomass as a renewable energy source and various waste-to-energy technologies.  Employing Scopus and Web of Science databases alongside Biblioshiny and VOSviewer for analysis, the study investigates publication patterns, citation networks, and keyword usage. This systematic approach unveils significant trends in research focus and identifies prominent research actors (countries and institutions). Our findings reveal a significant increase in yearly publications, reflecting the growing global focus on biomass and organic waste conversion. Leading contributors include China, the United States, India, and Germany.  Analysis of keywords identifies commonly used terms like "biofuels," "pyrolysis," and "lignocellulosic biomass." The study concludes by proposing future research directions, emphasizing advanced conversion technologies, integration of renewable energy sources, and innovative modelling techniques.
Frequency control enhancement for hybrid microgrid using multi-terminal multi-function inverter Eid, Doaa; Elmasry, Said; El Samahy, Adel; Elnagahy, Farag; Youssef, Erhab
International Journal of Renewable Energy Development Vol 13, No 4 (2024): July 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60144

Abstract

Renewable energy sources (RESs) are considered a crucial energy transformation to reduce carbon emissions, so more RESs are being integrated into contemporary power systems. Power electronic converters are extensively utilized to connect power grids with renewable generators to manage the fluctuations and unpredictability of these renewable energy sources. This paper introduces a multi-terminal multi-function inverter (MT-MF) designed for a battery energy storage system (BESS) to maintain the frequency stability of a hybrid microgrid (MG). The MG comprises a photovoltaic generation system, a diesel generator, BESS, and two loads: one constant load and the other variable, fed through a medium-voltage radial feeding system. An introduced approach involves utilizing a model predictive control controlled virtual synchronous generator (MPC-VSG) for BESS. This method offers inertia support during transient states and improves the dynamic characteristics of system frequency. In addition, it enables the connection of multiple batteries, provides individualized control for each, and supports the injection of reactive power into the MG. The required power from the BESS is shared between the two batteries using the low pass filter technique. The simulation outcomes affirm the proposed control strategy’s effectiveness and underscore the MT-MF inverter approach’s potential in integrating extensive RESs. This paper also explores how the proposed technique outperforms other methods in improving frequency stability.
Effect of various silica-supported nickel catalyst on the production of bio-hydrocarbons from oleic acid Riyandi, Rafly; Rinaldi, Nino; Yunarti, Rika Tri; Dwiatmoko, Adid Adep; Simanjuntak, Fidelis Stefanus Hubertson
International Journal of Renewable Energy Development Vol 13, No 4 (2024): July 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60054

Abstract

The conversion of fatty acids into bio-hydrocarbons can be carried out through a deoxygenation (DO) reaction. Catalytic deoxygenation of fatty acids can occur through three reaction pathways: decarbonylation, decarboxylation, and hydrodeoxygenation. In this study, three kinds of silica were prepared: (i) silica obtained from the rice husk ash (RHA); (ii) synthetic mesoporous silica SBA-16; and (iii) commercial silica. All prepared silica was used as supported nickel (Ni) catalyst for bio-hydrocarbon production through DO reaction of oleic acid. The objective of this study was to investigate the effect of variations of silica on the reaction pathway and final products composition of DO reaction of oleic acid. The catalysts were characterized by X-ray fluorescence (XRF), X-ray diffraction (XRD), surface area analysis, and NH3-temperature-programme desorption. Based on XRF and XRD analysis results, it can be concluded that nickel was successfully impregnated into all silica. All samples of catalysts were used in a reaction carried out at temperature of 285 °C under a pressure of 40 bar H2 for 2h. The results showed that all catalysts were able to convert oleic acid to bio-hydrocarbon with differences in products composition. The highest oleic acid conversion of 98.25% was achieved with Ni/RHA catalyst but the obtained liquid products was the lowest among other catalysts. It is found that this phenomenon was closely related to the acidity properties of the catalyst.
Unlocking renewable energy potential: Harnessing machine learning and intelligent algorithms Le, Thanh Tuan; Paramasivam, Prabhu; Adril, Elvis; Nguyen, Van Quy; Le, Minh Xuan; Duong, Minh Thai; Le, Huu Cuong; Nguyen, Anh Quan
International Journal of Renewable Energy Development Vol 13, No 4 (2024): July 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60387

Abstract

This review article examines the revolutionary possibilities of machine learning (ML) and intelligent algorithms for enabling renewable energy, with an emphasis on the energy domains of solar, wind, biofuel, and biomass. Critical problems such as data variability, system inefficiencies, and predictive maintenance are addressed by the integration of ML in renewable energy systems. Machine learning improves solar irradiance prediction accuracy and maximizes photovoltaic system performance in the solar energy sector. ML algorithms help to generate electricity more reliably by enhancing wind speed forecasts and wind turbine efficiency. ML improves the efficiency of biofuel production by optimizing feedstock selection, process parameters, and yield forecasts. Similarly, ML models in biomass energy provide effective thermal conversion procedures and real-time process management, guaranteeing increased energy production and operational stability. Even with the enormous advantages, problems such as data quality, interpretability of the models, computing requirements, and integration with current systems still remain. Resolving these issues calls for interdisciplinary cooperation, developments in computer technology, and encouraging legislative frameworks. This study emphasizes the vital role of ML in promoting sustainable and efficient renewable energy systems by giving a thorough review of present ML applications in renewable energy, highlighting continuing problems, and outlining future prospects
Evaluating the performance of the Anwaralardh photovoltaic power generation plant in Jordan: Comparative analysis using artificial neural networks and multiple linear regression modeling Alma'asfa, Suhaib Ibrahim; Fraige, Feras Younes; Abdul Aziz, Mohd Sharizal; Khor, Chu Yee; Al-Khatib, Laila A
International Journal of Renewable Energy Development Vol 13, No 4 (2024): July 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60156

Abstract

The global energy demand is rising, driven by population growth, economic development, and industrialization. Shifting towards renewable energy, like solar energy, is gaining momentum worldwide because of ecological concerns and resource depletion. This paper aims to utilize Artificial Neural Networks (ANNs) and multiple linear regression (MLR) modeling techniques to evaluate the productivity of 11 MW photovoltaic (PV) solar power plant currently operational in Jordan. The case study reveals that both models can be used to predict the daily, monthly, and yearly average power produced and system efficiency with reasonable accuracy. The ANN model exhibited promising results, where the best value for the coefficient of determination (R2) and mean absolute percentage error (MAPE) for training were 95.85% and 0.59%, respectively. However, R2 was 93.7%, and MAPE was 1.27% for validation tests. All these results were achieved using a 7-6-1 model, with a sample ratio of 1:1 for the data allocated in training and validation. When using multiple linear regression, the R2 and standard error values were 93.42% and 0.17%. On the other hand, the results showed that the yearly output power for actual and predicted by both models over the year was 24,399 MWh, 24,538 MWh, and 24,401 MWh, respectively. This research showed valuable results in the monthly output power for solar cells at the Anwaralardh PV power system project, contributing to a better understanding of solar energy generation in arid desert climates and emphasizing the potential of solar power plants to play a crucial role in achieving SDG 7 objectives.
Automatic control of constant temperature and humidity in building air conditioning systems based on frequency domain analysis Wang, Lihui
International Journal of Renewable Energy Development Vol 13, No 4 (2024): July 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60102

Abstract

How to solve their automatic control of constant temperature and humidity gradually becomes a research hotspot as the continuous upgrading of air conditioning systems. This study aims to optimize the traditional proportional-integral-differential controller for improvement to solve the time-delay instability phenomenon in temperature and humidity control. The objective of this study is to optimize existing proportional-integral-differential controllers to improve the time-delay instability problem that is common in temperature and humidity control. Firstly, it treats the controlled object as a first-order and second-order system with time-delay characteristics. Next, the Smith predictor controller is generalized equivalent to ensure that the equivalent system does not contain time-delay. Finally, an analysis of the first-order and second-order closed-loop control system is conducted by combining Smith predictive controller and proportional-integral-differential controller. The system achieves the goal of automatic control of constant temperature and humidity by adjusting the control parameters. The experiment showcased that the temperature control time of the proposed control scheme under first-order and second-order time-delays was 16 s and 3 s, respectively. Meanwhile, the humidity control time was 14 s and 13 s, respectively. In practical applications, the proposed control scheme achieved good control effects in all four seasons. This indicates that the controller designed in this study possesses good control performance. It also can achieve the goal of constant temperature and humidity control. This can provide technical support for the automation control of air conditioning systems.

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