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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 16 Documents
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Search results for , issue "Vol 13, No 6 (2024): November 2024" : 16 Documents clear
CFD analysis of key factors impacting the aerodynamic performance of the S830 wind turbine airfoil Nhung, Le Thi Tuyet; Van Y, Nguyen; Cong Truong, Dinh; Dinh Quy, Vu
International Journal of Renewable Energy Development Vol 13, No 6 (2024): November 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60249

Abstract

The Global Wind Energy Council (GWEC) reported that in 2021, global wind capacity increased by 93.6 GW (+12%), reaching a total of 837 GW, most of which was contributed by wind turbines. Improving wind turbine performance primarily hinges on advancements in blade technology and airfoil design. This study examines the effect of profile thickness on the aerodynamic performance of the S830 airfoil at a Reynolds number of 25,148, as part of the NREL airfoil's aerodynamic performance research. However, the impacts of additional variables—such as angle of attack, Reynolds number, speed range, and particularly ice accretion—have not been thoroughly investigated. This study utilized a 2D CFD model provided by the commercial software ANSYS Fluent and FENSAP-ICE. The lift-to-drag ratio of the S830 wind turbine airfoil was examined, considering the effects of angle of attack, wind speed, Reynolds number, airfoil thickness, and ice accretion. Additionally, design-related solutions will be suggested. The research indicates that the optimal angle of attack increases the lift-to-drag ratio by approximately 250% compared to a zero angle of attack.  An increase in wind speed causes this coefficient to rise nonlinearly within the studied velocity range. The Reynolds number directly influences the optimal angle of attack. According to CFD results, the lift-to-drag ratio can be increased by 50% if the airfoil's thickness is reduced by 20% compared to the original profile. For the ice accretion simulation model, a case test of the NACA 0012 airfoil was conducted to verify the model's parameters. Subsequently, a survey of this phenomenon on the S830 airfoil revealed that the lift coefficient decreased by 5.25% after 90 minutes of ice accretion.
Adaptive control of plug-in hybrid electric vehicles based on energy management strategy and dynamic programming algorithm Ge, Yuxin
International Journal of Renewable Energy Development Vol 13, No 6 (2024): November 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60463

Abstract

This study mainly analyses the fuel consumption of plug-in hybrid vehicles during operation. A new control method for automobiles based on energy management strategy and dynamic programming algorithm is proposed. The new method plans and analyses the minimum electricity consumption, and then uses dynamic programming algorithms to analyse this parameter. The research results indicated that the vehicle state was constantly changing with the variation of SOC value during driving. The energy mobilization of the vehicle was more obvious after adding dynamic programming strategy. The efficiency of the vehicle was relatively high in driving state 1, with a minimum value of 70%, which was about 20% higher than in driving state 4. The average fuel consumption in driving state 2 was 1.8L higher than in other driving states. The overall efficiency of automobiles after incorporating dynamic programming was improved, with a shorter time to reach the lowest efficiency point compared with not incorporating dynamic programming algorithms. The highest efficiency value was 7.86% higher than that of not incorporating dynamic programming models. The new control method can reduce energy consumption and improve the energy management and control effect. The study provides a better research direction for energy management and control of hybrid electric vehicles in the future.
Chemical characterization of activated carbon derived from Napier grass, rubber wood, bamboo, and hemp Khruengsai, Sarunpron; Pripdeevech, Patcharee; Pongnailert, Suwichien; Chanlek, Narong; Thumanu, Kanjana; Muangmora, Rattana; Rojviroon, Thammasak; Pongpiachan, Siwatt
International Journal of Renewable Energy Development Vol 13, No 6 (2024): November 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60502

Abstract

This study examines the process and analysis of activated carbons that use H2SO4, H2O2, and NaOH as activating agents. The distinct chemical methods employed by each activator impacted the ash and carbon content, surface properties, and functional groups of the activated carbons, exhibiting notable disparities. The ash level varied from 6.86% to 37.08%. H2SO4-activated carbons had the lowest ash content, suggesting better elimination of inorganic contaminants. The iodine number, which serves as a measure of adsorption capacity, was consistent among all samples, with values ranging from 800 to 950 mg g-1. This indicates that the three activating agents effectively increased the surface area and porosity. The BET surface areas varied between 9.14 and 167.42 m2 g-1, whereas the BJH adsorption surface areas ranged from 9.68 to 28.89 m2 g-1. The pore volumes ranged from 0.0071 to 0.0595 cm2 g-1, while the sizes ranged from 0.51 to 8.2 nm. These measurements suggest the presence of both micropores and mesopores. The FTIR spectra exhibited comparable functional groups among all samples, such as OH, CH, C=C, and C-O. The SEM-EDX and XPS tests showed that there was a lot of carbon. The carbon content was highest in H2O2-activated carbons because they were exposed to less severe oxidative conditions. These activated carbons comply with the requirements set by IUPAC and ASTM. They are suitable for catalytic processes and liquid adsorption, such as water and wastewater treatment. Subsequent research should aim to improve activation conditions to get the highest possible carbon content and optimise surface characteristics.
Production of biodiesel by using CaO nano-catalyst synthesis from mango leaves extraction Mahmood, Sarah Shakir; Al-Yaqoobi, Atheer Mohammed
International Journal of Renewable Energy Development Vol 13, No 6 (2024): November 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60469

Abstract

Development and population expansion have the lion's share of driving up the fuel cost. Biodiesel has considerable attention as a renewable, ecologically friendly and alternative fuel source. In this study, CaO nanocatalyst is produced from mango leaves as a catalysis for the transesterification of waste cooking oil (WCO) to biodiesel. The mango tree is a perennial plant, and its fruit holds significant economic worth due to its abundance of vitamins and minerals. This plant has a wide geographical range and its leaves can be utilized without any negative impact on its growth and yield. An analysis was conducted to determine the calcium content in the fallen leaves, revealing a significant quantity of calcium that holds potential for utilization. The catalyst was characterized by different analytic techniques such as XRD, SEM-EDS, FT-IR, and BET analyses. Several parameters impacted on the transesterification process were exploited by conventional transesterification (batch). The result revealed that the optimum reaction was reached at a methanol to oil ratio of 50% w/w, catalyst loading of 3%, temperature of 65℃ and reaction time of 1.5 h with a yield of 93.21%, and the activation energy of the transesterification reaction was found to be 38.906 KJ mol-1. The reaction was verified to be irreversible pseudo-first order based on a linear Arrhenius plot and a high R2 value. The catalyst shows good stability and catalytic activity when it is reused and the yield was found to be 80.293% in the 5th cycle.
Multi-objective decision optimization design for building energy-saving retrofitting design based on improved grasshopper optimization algorithm Bao, Xin; Zhang, Jinghui
International Journal of Renewable Energy Development Vol 13, No 6 (2024): November 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60483

Abstract

With the national emphasis on building energy efficiency planning, energy efficiency optimization in existing buildings requires renovation measures based on multi-objective factors. In order to get the optimal solution in the multi-objective decision-making of renovation, the study proposes a class of improved grasshopper optimization algorithms. The process employs a systematic methodology to identify an optimal energy renovation method, taking into account the specific characteristics of the building environment. It then classifies and formulates the energy reduction substitution items for building renovation, and finally, it synchronizes the cost of the renovation project as a measure for decision-making. The elite inverse strategy approach enhances the grasshopper optimization algorithm to facilitate the multi-objective decision-making process associated with building renovation measures. The results showed that the improved grasshopper optimization algorithm could achieve a decision accuracy of 98.8% for the test samples, which was 5.5% higher than the accuracy of the particle swarm optimization algorithm. Repeated run tests of the research algorithm for multi-objective decision making yielded a mean decision fitness value of 2.34×104 and a data extreme value of 0.38×104. Compared to other algorithms improved grasshopper optimization algorithm converged in a lower range of fitness values, which indicated that the algorithm worked well for multi-objective optimization and the model repeatability was good. The research algorithm was used to decide the energy efficient renovation planning of the building and the power consumption of the renovated power supply system was reduced by 23.7%-49.6%. This indicates that the renovated building has better energy efficiency and can provide a reliable technical direction for decision-making optimization of building energy efficiency renovation.
Performance analysis of a photovoltaic component integrated into a hybrid power plant in Southeast Mauritania Lemrabout, Ahmed; Kerboua, Abdelfettah; Mohamed, Regad; Bouaichi, Abdellatif; Ba, Abdellahi; Minehna, Sidi Med; Hacene, Fouad Boukli; Mahmoud, Abdel Kader
International Journal of Renewable Energy Development Vol 13, No 6 (2024): November 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60474

Abstract

This study investigated the performance of photovoltaic components of the 1.3MW KIFFA hybrid power plant in Mauritania. Data from the plant's monitoring system (January-December 2021) was used to assess various performance metrics. The analysis revealed a high daily reference yield (5.60 h/d), indicating good solar resource availability. However, final and array yields (4.78 h/d and 4.86 h/d, respectively) suggested potential for improvement. System component efficiencies were within acceptable ranges, with particularly high inverter efficiency (98.31%). Array capture losses were moderate (0.74 h/d), and system losses were minimal (0.08 h/d). The annual performance ratio (86.33%) and capacity factor (19.91%) indicated good overall plant performance. These findings were then compared with data from similar installations in various climate zones to understand the impact of climatic variations on photovoltaic performance. Compared to installations in temperate zones with lower irradiation levels, the KIFFA plant's reference yield was significantly higher. However, the final and array yields were closer due to potentially higher operating temperatures in Mauritania affecting module efficiency. Interestingly, comparisons with installations in other desert regions with similarly high irradiation levels revealed lower performance, particularly in terms of final yield, (4.71 h/d) in Algéria (Adrar) and (4.10 h/d) in Oman (Muscat). This suggests that climatic factors beyond just sunlight availability, such as dust accumulation, may have played a significant role in their performance compared to the KIFFA plant.
Impact of green trade on green growth in Malaysia: A dynamic ARDL simulation Razelan, Nor Dahlia; Hamidi, Hakimah Nur Ahmad; Zainuddin, Muhamad Rias K V; Khairuddin, Nurul Aishah; Zulkifli, Muhamad Solehuddin
International Journal of Renewable Energy Development Vol 13, No 6 (2024): November 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60413

Abstract

Green economic growth emphasizes developing an economy that safeguards natural resources, enhances resource capabilities, and promotes sustainable resource utilization. This approach is vital for balancing economic development with environmental preservation, highlighting the efficient and sustainable use of renewable and non-renewable resources to maintain a clean environment and societal well-being. It also stresses the long-term preservation of natural resources for green growth and prosperity. Environmental sustainability is key for economic growth, as poor sustainability can lead to economic decline due to inefficient resource use. The Eleventh Malaysia Plan highlights the importance of green economic growth, focusing on areas such as creating a supportive environment for green growth, adopting sustainable consumption and production practices, conserving natural resources, and strengthening resilience against climate change and natural disasters. This study examines the impact of natural resource use on the green economic growth in Malaysia from 1990 to 2021, with a focus on green trade as a key component. To achieve this objective, this study utlizies the Autoregressive Distributed Lag (ARDL) method and also its extension, the Dynamic ARDL (DYNARDL). Estimation results for both model indicate that green trade has a significant long run positive impact on green economic growth. While for short run, only DYNARDL method found evidence for positive impact of green trade. These findings suggest that policymakers should further promote green trade as a means to enhance sustainable and equitable resource use, thereby supporting the growth of the green economy in Malaysia.
AI-optimization operation of biomass-based distributed generator for efficient radial distribution system Ali, Muhammad Abid; Bhatti, Abdul Rauf; Farhan, Muhammad; Rasool, Akhtar; Ali, Ahmed
International Journal of Renewable Energy Development Vol 13, No 6 (2024): November 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60224

Abstract

This research aims to optimize the size and location of biomass-based distributed generator (BMDG) units to enhance the voltage profile, reduce electrical losses, maximize cost savings, and decrease emissions from power distribution systems. Biomass-based distributed generator (BMDG) systems offer numerous advantages to enhance the efficiency of power distribution systems. However, achieving these benefits relies on determining the optimal size and position of the BMDGs. To achieve these objectives, the metaheuristic technique called particle swarm optimization (PSO) is employed to find the optimal placement and size of BMDGs. The proposed model was validated on MATLAB's IEEE-33 bus radial distribution system (RDS), confirming the aforementioned benefits. Comparative analysis between the PSO-based technique and other algorithms from previous research revealed better results with the proposed method. The results indicate that optimal placement and sizing of BMDG units have led to a reduction of more than 67.68% in active power losses and 65.90% in reactive power losses compared to the base case. Additionally, the reduction in active power loss was 40.44%, 11.39%, 42.85%, 1.81%, 0.85%, 29.83%, 5.82% and 28.38% more than artificial bee colony, backtracking search optimization algorithm, moth-flame optimization, Coordinate control, artificial Hummingbird algorithm, variable constants PSO (VCPSO), artificial gorilla troops optimizer (AGTO), and a jellyfish search optimizer respectively. Furthermore, the reactive power losses were reduced by 38.33% and 15.68% compared to VCPSO and AGTO respectively. Furthermore, this study revealed a cost reduction of 6.38% when compared to the AGTO and 1.30% when compared to the AHA. Moreover, the voltage profile of the power distribution system was improved by 7.28%. The presented methodology has demonstrated promising results for BMDGs in RDS across various applications.
Design and evaluation of a standalone electric vehicles charging station for a university campus in Argentina Cecchini, Juan Pablo; Venghi, Luis Esteban; Dellasanta, Ezequiel Eugenio; Silva, Luis Ignacio
International Journal of Renewable Energy Development Vol 13, No 6 (2024): November 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60356

Abstract

The increasing popularity of electric vehicles in recent years has led to a growing demand for charging stations. In this context, universities are an ideal setting for their installation, as they have a large number of students, professors, and staff who could benefit from them and, at the same time, it serves as teaching material to raise awareness in the use of renewable energy. This work presents the design and proposal of an electric vehicle charging station for the campus of the Universidad Nacional de Rafaela (UNRaf). The station will be located in an area of the campus where the construction of more buildings and sport facilities is planned. This area will not be connected to the electrical grid and instead, will have an energy storage system to guarantee supply. The station will have the capacity to simultaneously charge 4 bicycles and 2 light electric vehicles, with an average energy demand of 0.786 kWh per hour. Homer Pro software was used for the calculations. The most economically viable option was a 100% renewable solution powered only by solar energy. It is expected to consist of a 15-kW solar system that will produce 22,922 kWh/year and a bank of 30 batteries of 3 kWh plus a single battery of 1 kWh. The installation of the electric vehicle charging station on the UNRaf campus will contribute to promoting the adoption of sustainable transportation, which will help reduce greenhouse gas emissions without using the public power grid.
Equation of motion of split conductor of anchor section at icing in wind flow Abitayeva, Rakhimash; Bekbayev, Amangeldy; Dzhamanbayev, Muratkali; Bayanbayev, Kairat; Aikimbayeva, Dina
International Journal of Renewable Energy Development Vol 13, No 6 (2024): November 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60369

Abstract

The relevance of the examined problem is connected with the necessity to develop measures to combat conductor galloping and the design of power transmission lines (ETL). The purpose of the research – to analyse statistical observation data on conductor galloping and apply a mathematical model to determine the parameters of galloping, to develop effective measures to combat conductor galloping and to improve the design of power lines. A sophisticated mathematical model was developed using Mathcad software to analyze conductor galloping in overhead power lines. This model, based on the equations of motion, predicts various galloping parameters under different conditions such as wind speed, span length, and initial mechanical stress. Time diagrams were constructed to represent linear and torsional motions, revealing correlations between amplitudes and frequencies. A comprehensive statistical analysis was performed on wire characteristics and split phase parameters to evaluate their impact on galloping patterns. Numerical methods, including the Runge-Kutta method, were employed to solve the equations and compute time-dependent behaviors. Results were visualized through graphs and diagrams to facilitate interpretation. The results revealed that conductor galloping occurs at wind speeds between 5 to 18 m/s, with significant occurrences at temperatures from 0°C to -10°C. The study identified that conductor galloping occurs within a wind velocity range of 5 to 13 m/s, predominantly with wind orientations between 30˚ and 90˚. The analysis showed that the frequency of galloping closely matches the natural oscillation frequency at low wind speeds but diverges with increasing wind speed and span length. These findings provide insights into the conditions under which conductor galloping is likely to occur and can inform design and operational strategies for overhead power lines.

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