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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 709 Documents
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Optimization of sugarcane straw as a solid biofuel for thermochemical processes by water leaching pretreatment Assureira, Estela; Assureira, Marco
International Journal of Renewable Energy Development Vol 14, No 6 (2025): November 2025
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.61631

Abstract

Sugarcane straw, an abundant agricultural waste, has considerable potential as a renewable fuel due to its energy content, sustained generation, and CO2 neutrality but its direct utilization is limited by its high levels of ash, alkalis, S, Cl contents that cause severe slagging, fouling, and corrosion in boilers, as well as the harmful emissions released during combustion. To improve the fuel properties of sugarcane straw, a leaching pretreatment with distilled water was developed and applied to the residue under controlled conditions to evaluate the effects of water temperature, residence time and agitation of the leachate on the removal effectiveness of soluble ash-forming components. The leaching process was carried out in batches, maintaining a solid-to-liquid ratio of 1:30, and a feedstock size of 0.5–2 cm. Various combinations of temperature, residence time, and leachate agitation condition were tested to optimize the process. The optimal condition was established at 80 °C and 20 min with continuous agitation, which was applied to the residue, achieving reductions of 38.46% in ash, 78.26 in Cl, 57.14% in S, 9.09% in N, 54.61% in K2O, and 58.22% in Na2O, along with an increase in the high heating value, which reached 18.4 MJ/kg. These improvements reduce slagging, fouling and corrosion tendency, as indicated by lower predictive indices and higher ash fusion temperature reflected in the ternary phase diagram, and enhanced energy content. The improvements achieved make the washed sugarcane straw suitable for industrial biofuel applications, reducing issues associated with ash and emissions and providing higher energy content. The water leaching pretreatment also represents a valuable contribution since it can be easily replicated, and the upgraded residue has been valorized by being converted into a clean and sustainable fuel.
Design and control of a hybrid water pumping system using energy management for sustainable agricultural irrigation: A case study of the Sidi Bouzid region in Tunisia Amri, Akram; Moussa, Intissar; Khedher, Adel
International Journal of Renewable Energy Development Vol 14, No 6 (2025): November 2025
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.61626

Abstract

In this study, a renewable energy-powered Hybrid Water Pumping System (HWPS) is proposed for agricultural irrigation, designed to operate without reliance on battery storage. The system is adapted to the local climatic characteristics of the Sidi Bouzid region in Tunisia and is intended to regulate and coordinate water flow to effectively meet crop irrigation requirements. Hence, the system comprises three principal subsystems: A Wind Turbine (WT) driving a Doubly-Fed Induction Generator (DFIG) connected to the grid via rotor-side and grid-side converters; a Photovoltaic (PV) module integrated via a DC/DC boost converter; and a water pumping unit, consisting of an Induction Machine (IM) coupled to a centrifugal pump. The mathematical models of each subsystem were developed, and a control algorithms suite was implemented to enhance overall performance and energy efficiency. Maximum Power Point Tracking (MPPT) techniques were employed to optimize the energy harvested from renewable sources. A non-linear Sliding Mode Control (SMC) strategy was implemented to manage the DFIG power output, while Input-Output Feedback Linearization (IOFL) was applied to control the IM via a Voltage Source Inverter (VSI).Since the system operates without battery storage, a dynamic Energy Management System (EMS) is investigated to ensure optimal energy distribution, prioritizing solar energy during peak sunlight hours and transitioning to wind energy when solar availability declines. Simulation results validate the system’s effectiveness and demonstrate its potential for sustainable agricultural applications in rural areas. This approach offers a cost-effective and environmentally friendly sustainable solution for irrigation, contributing to improving water and energy security.
Thermal analysis of bifacial photovoltaic modules with single-axis trackers in a large power plant: Modeling by symbolic equations in tropical climates Vargas, Fabian Alonso Lara; Vargas Salgado, Carlos; Encalada, Alejandro Chacon; Alvarez, Jose Campos; Oviedo, Edison Ortega
International Journal of Renewable Energy Development Vol 14, No 6 (2025): November 2025
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.61489

Abstract

The thermal behavior of the single-axis tracked bifacial photovoltaic (PV) module is important for efficient energy extraction in large-scale power plants, especially in tropical regions under high irradiation and high ambient temperature. However, it is difficult to accurately predict their operating temperature due to the complex interaction between environmental variables and the characteristics of solar tracking. The available models, ranging from empirical correlations and computational fluid dynamics (CFD) simulations to machine learning methods, face challenges in terms of accuracy, interpretability, and computational load. This gap is addressed in this study, with the development of a modeling methodology based on symbolic regression (SR) utilizing genetic algorithms (GA) towards obtaining an explicit, interpretable Equation for the prediction of the PV module temperature in single-axis tracking systems. One year of data was collected at 5-minute intervals from a 19.9 MW PV plant located in San Marcos, Colombia, consisting of measurements for solar radiation, ambient temperature, wind speed, and module temperature. The constructed SR GA model achieved satisfactory prediction accuracy compared to classic models with the best root mean square error (RMSE = 4.14 °C) and R² (0.91) on the test data set. These results compare favorably with results from MLR (RMSE = 4.31 °C, R² = 0.90), the standard industry NOCT model (RMSE = 8.59 °C, R² = 0.60), and the empirical Skoplaki I model (RMSE = 5.92 °C, R² = 0.81). The resulting symbolic equation directly characterizes the effects of nonlinear solar radiation, ambient temperature, and wind speed, providing greater physical insight into the thermal dynamics of the system. An important finding is that the maximum temperature of the bifacial module is reached around 14:00h, probably due to the accumulation of temperature caused by solar tracking, which contrasts with what occurs in fixed-tilt monofacial technology. This study demonstrates that the symbolic regression technique with a genetic algorithm kernel can produce accurate, interpretable, and computationally economical models for advanced photovoltaic systems.
Multi-objective HVAC control using genetic programming for grid-responsive commercial buildings Waheed, Sibtain; Li, Shuhong
International Journal of Renewable Energy Development Vol 14, No 6 (2025): November 2025
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.61410

Abstract

Commercial buildings are significant energy consumers, with their heating, ventilation, and air conditioning (HVAC) systems being major contributors. Optimizing these systems is crucial for energy conservation, yet advanced artificial intelligence methods like Deep Reinforcement Learning (DRL) often produce opaque black-box solutions. While post-hoc explanation methods can offer some insight, they are often inexact and fail to render the core decision logic fully transparent, hindering trust and practical implementation. This paper presents a novel approach using Genetic Programming (GP) to automatically design HVAC control strategies that are both highly effective and inherently understandable. The novelty of our framework lies in its direct evolution of interpretable, multi-objective control policies that holistically co-optimize energy efficiency, occupant thermal comfort, and integrated Demand Response (DR) for a complex multi-zone system a combination not extensively explored in prior GP-HVAC research. We applied this framework to manage the central air handling unit of a simulated multi-zone office building, enabling it to dynamically adjust key settings like air temperature and fan pressure. Rigorous testing in a validated EnergyPlus simulation environment showed that the GP-designed control policies reduced annual HVAC energy use by 40.9% compared to standard ASHRAE A2006 guidelines, 28.4% against the advanced ASHRAE G36 standard, and a notable 9.3% more than a state-of-the-art DRL controller. These substantial energy savings were achieved while maintaining excellent occupant thermal comfort for 98.8% of occupied hours. Furthermore, the GP controller demonstrated robust performance during Demand Response scenarios, achieving a 72.1% reduction in peak power draw. A key outcome is that these high-performing strategies are expressed in a transparent format allowing direct inspection and understanding. This research establishes Genetic Programming as a compelling method for creating intelligent HVAC controls that are not only efficient and grid-responsive but also transparent, fostering greater confidence in advanced building automation.
Advanced composite adsorbent based on biochar, bentonite, and boric acid for sustainable removal of Pinoxaden Shakir, Safa Waleed; Al-Yaqoobi, Atheer Mohammad
International Journal of Renewable Energy Development Vol 14, No 6 (2025): November 2025
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.61503

Abstract

Pinoxaden is a post-emergence herbicide, which is widely applied for the control of wheat, barley, and other cereals. Its usage is increasing across the world, and there have been concerns regarding contamination of water bodies due to residues. In this research, we investigated the removal of Pinoxaden by a new boric-acid-activated biochar–bentonite composite. The composite was synthesized by pyrolyzing biomass with boric acid and bentonite clay. The composite was studied using XRD, SEM, FTIR, and BET analysis, which showed that it has a very porous structure and boron–oxygen features on its surface. Batch adsorption experiments (pH variation, time variation, and variation of initial concentration) demonstrated rapid uptake with high capacity. Kinetic analysis was pseudo-second-order, and equilibrium data obeyed the Langmuir isotherm, indicative of monolayer chemisorption. Researchers realized maximum adsorptive capacities of 150 mg/g, within the range of 5–100 mg/g. The removal efficiency was found, through a batch adsorption study, to be a maximum of more than 99.5% at optimum conditions. Increased Pinoxaden concentration and topped-up adsorbent loading reduced the adsorptive capacity but increased with maximum adsorbent loading. The data followed the Freundlich isotherm (R² > 0.999), which shows that the adsorption happens in multiple layers, and it matched the pseudo-second-order model, indicating that the process involves chemical bonding. Studies on how substances move within particles and how they come off showed that the surface features and the movement through pores were more important than the overall amount taken in. We found that adding boric acid significantly increased the polarity and reactivity by boosting the adsorptive capacity from raw biochar or bentonite. The research shows that the MC-Db composite could be a useful, eco-friendly material that effectively removes herbicides from contaminated water.
Economic activities and CO2 emissions: Evaluating the impacts of renewable energy, industrial growth, and financial development in CO2-intensive economies Dallali, Atef; Ben Jebli, Mehdi
International Journal of Renewable Energy Development Vol 14, No 6 (2025): November 2025
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.61779

Abstract

This study addresses the pressing challenge of mitigating carbon dioxide (CO2) emissions within the top ten emitting countries, which are critical to achieving global climate goals yet often analyzed separately. We investigate the intricate relationships between economic growth (GDP), renewable and non-renewable energy consumption (RE, NRE), financial development (FDI), industrial value-added (IVA), and CO2 emissions from 1990 to 2021, overcoming the limitations of single-country studies and mixed findings in existing literature. Employing a panel-based Pooled Mean Group-Autoregressive Distributed Lag (PMG-ARDL) model and Granger causality tests, we disentangle short-run and long-run dynamics, revealing that non-renewable energy significantly increases emissions while renewable energy, financial development, and industrial value-added offer mitigating effects. We provide nuanced evidence supporting the Environmental Kuznets Curve (EKC) hypothesis, suggesting a potential pathway toward sustainable growth. Furthermore, Granger causality analysis reveals significant bidirectional relationships, highlighting the interconnectedness of economic and environmental factors. We translate these findings into actionable policy recommendations, emphasizing targeted investments in clean technologies and financial strategies to foster industrial development while simultaneously curbing emissions. By providing a comprehensive analysis of these dynamics within a key group of countries, this research offers critical insights for overcoming the challenges of emissions reduction and achieving sustainable development.
Towards the Sustainability of an Oil Refinery: A Synergy between ISO 50001 and ISO 14001 Management Systems Chaves Almanza, Fabio Daniel
International Journal of Renewable Energy Development Accepted Articles
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.61162

Abstract

The most implemented standards worldwide for Energy Management Systems (EnMS) and Environmental Management Systems (EMS), ISO 50001 and ISO 14001 respectively, maintain a close correspondence due to the Harmonized Structure (HS) recently established by the International Organization for Standardization (ISO). However, achieving greater energy efficiency does not always align adequately with environmental issues, which is most evident in fossil fuel-based industries. Therefore, this work aims to explore a synergy between these standards and use it to evaluate a technological change in an oil refinery, for better energy performance and especially environmental sustainability. The results show that the change in technology increases electric efficiency from 14% to 45% and the rate of atmospheric emissions per unit of energy generated decreases by 15% on average. However, as fuel consumption doubles, the total emission rises by about 100%. This conflict between energy and environmental performance leads to an analysis of sustainable resource management to better understand the relevance of the change in technology as an appropriate solution for the refinery in the gradual transition to clean energy. The findings of this work shed light on how to deal with oil refineries in the global landscape of urgent sustainable development.
Influence of missing wind measurements on wind turbine power production using various measure-correlate-predict methods and reanalysis datasets Amarzaya, Buyankhishig; Ko, Kyungnam
International Journal of Renewable Energy Development Vol 14, No 6 (2025): November 2025
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.61557

Abstract

This study analyzes the impact of missing wind data points on the accuracy of Annual Energy Production (AEP) estimation in wind resource assessment (WRA). Evaluations were made under different scenarios using various Measure-Correlate-Predict (MCP) methods and reanalysis datasets. One year of wind measurements was collected from an inland met mast located in the Gashiri area of Jeju Island, South Korea. Three types of long-term reanalysis datasets- ERA-5, MERRA-2 and WRF (ERA-5)- were obtained, each exhibiting different levels of correlations with the met mast wind measurements. To simulate missing data points scenarios, a yearly percentage sampling method was applied to the one-year met mast wind data with sampling rates ranging from 10% to 90%. To ensure statistical reliability, random sampling was performed 12 times for each sampling rate. The MCP method was applied after pairing each sampled dataset with the reanalysis datasets. Long-term predictions were generated using four MCP approaches- two machine learning techniques (Random Forest and Gradient Boosting Regression) and two traditional methods (Regression and Matrix). AEP was calculted from these predictions and compared to the reference AEP derived from the complete dataset. Results show that accurate AEP estimation remained feasible even when using reanalysis datasets with low correlation to the measured data. Moreover, all four MCP methods demonstrated similar performance, with machine learning–based approaches producing results comparable to those of traditional methods. While conventional WRA practice recommends a data recovery rate above 90% for accurate AEP estimation, this study demonstrated reliable AEP estimates could be achieved with rates as low as 50%.
Optimization of Biodiesel Production from Candlenut Oil via Simultaneous Reaction Using a Bifunctional CeO2.CaO Catalyst Widayat, Widayat
International Journal of Renewable Energy Development Accepted Articles
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.61065

Abstract

The biodiesel synthesis process with a high free fatty acid content can be accomplished in a single stage using solid catalysts that function simultaneously as both base and acid catalysts. In this study, CeO₂.CaO was used as a bifunctional catalyst for biodiesel synthesis from candlenut seed oil. Catalyst characterization includes FTIR, BET, SEM-EDX, and TPD analysis. Process optimization was carried out using the central composite design method on Design Expert software. To determine the effect of each process variable on the simultaneous reaction, the effect of methanol-to-oil molar ratio, catalyst loading, and reaction temperature on FAME yield was also analyzed. The optimum operating conditions to achieve high FAME yield were found at methanol-to-oil molar ratio of 10.3:1, 5.39% w/w catalyst loading, and a reaction temperature of 60°C.
Structural, morphological and optical properties of ZnO thin films grown by time-dependent chemical bath deposition Gboglo, Alphonse Déssoudji; Baneto, Mazabalo; Ako, Ognanmi; Gadedjisso-Tossou, Komlan Segbéya; Grandidier, Bruno; Haris, Muthiah; Senthilkumar, Muthuswamy; N’Konou, Kekeli
International Journal of Renewable Energy Development Vol 15, No 1 (2026): January 2026
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2026.61665

Abstract

This study investigates the effect of deposition time on the structural, morphological, and optical properties of ZnO thin films synthesized by single-step chemical bath deposition (CBD) without the use of a seed layer. The films were systematically characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and UV-Visible spectroscopy in order to establish correlations between growth conditions and film properties. XRD analysis confirmed that all synthesized films are polycrystalline and crystallize in the hexagonal wurtzite structure, with average lattice parameters of a = 3.247 Å and c = 5.209 Å. The crystallite size increased slightly from 13.27 nm to 14.05 nm with increasing deposition time, indicating improved structural ordering and crystallinity. FTIR spectra verified the presence of characteristic Zn–O vibrational modes together with surface hydroxyl groups and other functional bonds related to the growth process. SEM images revealed a strong dependence of surface morphology on deposition time: ZnO microrods evolved from loosely distributed to more compact and densely packed assemblies as the deposition progressed, confirming enhanced film coverage. Optical measurements highlighted significant modifications in the transparency and band structure of the films. The average optical transmittance in the visible range decreased progressively from 68% to 52% when deposition time was extended from 30 to 120 minutes, reflecting increased film density. Concurrently, the optical band gap narrowed from 3.27 eV to 3.22 eV. These findings demonstrate that single-step CBD provides a reliable and controllable route for synthesizing ZnO thin films with tunable physical properties.

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