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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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Performance and carbon emissions of a diesel/oxy-hydrogen dual-fuel engine with oxy-hydrogen injection variation under low and medium load conditions Felayati, Frengki Mohamad; Prasutiyon, Hadi; Janah, Sholikhatul; Wijaya, Dimas Hadi; Saputra, Mukhammat Bayu; Semin, Semin
International Journal of Renewable Energy Development Vol 13, No 2 (2024): March 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.57983

Abstract

Reducing carbon emissions such as carbon dioxide (CO2) and carbon monoxide (CO) from diesel engines struggled with engine performance challenges and fossil fuel limitations. Besides, huge transportation such as ships hardly replaced diesel engines due to the higher thermal efficiency and low operation cost. Oxy-hydrogen gas, as a carbon-free gas, could potentially improve diesel engine performance and carbon emissions. Most of the studies tried to identify the effect of oxy-hydrogen induction into diesel engine combustion on performance and emissions. However, this study evaluated oxy-hydrogen injector sizes to the diesel engine performance and carbon emissions at several loads and several engine speed conditions. Overall, the result showed that the oxy-hydrogen gas injection into the diesel engine’s intake port improved the performance and carbon emissions compared to the single diesel fuel as a baseline. High engine performance with low carbon emissions could be achieved at low and medium engine load conditions with high engine speeds. Moreover, smaller oxy-hydrogen injector sizes were suitable for the medium engine load and vice versa, to improve the performance and carbon emissions. At low load, the engine performance improvement of engine torque, specific fuel consumption, and thermal efficiency were 1800 to 2200 rpm. Moreover, the CO2 and CO emissions reductions were also suitable with 2200 rpm with a bigger oxy-hydrogen gas injector (6 mm). Furthermore, at medium load, the engine performance improved at 1400 rpm but the CO2 and CO emissions were lower at 2200 rpm with a small oxy-hydrogen gas injector (4 mm). The engine operation at 2200 rpm with a 4 mm injector also improved the engine performance regarding carbon emissions reduction. However, injecting oxy-hydrogen gas into diesel engines had the potential to enhance the engine performance and reduce carbon emissions, moving closer to achieving zero emissions
Financial viability analysis for green hydrogen production opportunity from hydropower plant’s excess power in Indonesia Hardana, Hendy Eka; Adiwibowo, Pupung; Sunitiyoso, Yos; Kurniawan, Tri Edi Kusuma
International Journal of Renewable Energy Development Vol 13, No 5 (2024): September 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60304

Abstract

The research presents a comprehensive analysis of the financial viability of producing green hydrogen from excess power generated by small hydropower plants in Indonesia. It highlights Indonesia’s commitment to increasing renewable energy sources to achieve net zero emissions by 2060 and the role of Perusahaan Listrik Negara (PLN) in this transition. The study examines the potential of utilizing dormant excess power from retroactive small hydropower plants to produce green hydrogen, which could significantly decarbonize hard-to-abate sectors and enhance energy security. The authors conducted a financial analysis using the NREL H2A Production Model to determine the optimal technical arrangement and financial simulation for green hydrogen production. The paper discusses various electrolyzer technologies, with a focus on alkaline water electrolyzers due to their high technology readiness level and low capital expenditure. It also explores the sensitivity of the levelized cost of hydrogen to different factors, particularly the cost of utilities. The findings suggest that green hydrogen production from small hydropower plants is economically feasible in Indonesia, with the potential to contribute to the global hydrogen market and support the country’s green circular economy. The study concludes that green hydrogen production using excess electricity from small hydropower plants is a viable method for decarbonization and offers scalability for future energy production in Indonesia, with the first initial step being as a green hydrogen and natural gas co-firing fuel mixing in gas turbines.
An integrated framework for techno-enviro-economic assessment in nanogrids El Sayed, Ahmad; Poyrazoglu, Gokturk; E. E. Ahmed, Eihab
International Journal of Renewable Energy Development Vol 13, No 2 (2024): March 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60001

Abstract

This paper presents an integrated framework designed for capacity planning of grid-connected nanogrid, a small solar and energy storage system that can provide kilowatt-level services to individual buildings. This framework comprehensively evaluates nanogrid cost-effectiveness, sustainability, and reliability, employing a multi-faceted techno-enviro-economic assessment approach. Traditional nanogrid capacity planning often prioritizes peak load requirements, which may lack optimality owing to occasional peak load occurrences. Conversely, optimizing solely for base load requirements might also fall short of effectiveness, compromising reliability and sustainability objectives. The proposed framework employs a three-step, integrated process for nanogrid (NG) capacity planning. Firstly, the Planner module identifies optimal asset sizing considering a two-day look-ahead logic. Then, the Operator module serves as a digital twin for the system, conducting hourly calculations over a short-term horizon. Lastly, the Evaluator module evaluates technical, environmental, and economic metrics for each solution, assessing the effectiveness of asset-sizing decisions. A simulated case study has demonstrated the effectiveness of the proposed framework. The technical assessment revealed that a PV size of 24 kW and a storage capacity of 91 kWh led to the most reliable solution, with a probability of local sufficiency of 95 percent. Furthermore, the environmental assessment showcased a renewable fraction of 94% with a PV size of 26 kW and a storage of 85 kWh. Economically, the analysis identified that a PV size of 12 kW and a storage size of 24 kWh led to the minimum total cost. In contrast, a PV size of 26 kW and a storage size of 85 kWh yielded a total operating savings of $4,801.
The contribution of green technological innovation, clean energy, and oil rents in improving the load capacity factor and achieving SDG13 in Saudi Arabia Ragmoun, Wided; Ben-Salha, Ousama
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.2024.60683

Abstract

This research aims to assess the effects of green technological innovation, renewable energy sources, and oil rents on the load capacity factor in Saudi Arabia from 1988 to 2021. The primary conclusions can be outlined as follows. The combined cointegration and Saikkonen-Lütkepohl cointegration tests reveal long-run relationships between the load capacity factor and the explanatory variables at the 1% significance level. In comparison, the Phillips-Ouliaris test shows evidence of cointegration only at 10%. Moreover, the quantile regression indicates that oil rents adversely impact environmental quality; however, they remain contingent upon environmental conditions. A 1% increase in oil rents results in a decline in environmental quality by 0.025% under poor conditions, 0.036% under moderate/normal conditions, and 0.108% under good conditions. On the contrary, renewable energy consumption and green technological innovation improve environmental quality, irrespective of the prevailing environmental conditions. However, the environmental impacts of renewable energy consumption exceed those of green technological innovation. Results show that a 1% increase in renewable energy consumption leads to a 0.052-0.253% improvement in environmental quality, whereas a 1% increase in green technological innovation results only in a 0.017-0.047% improvement. Finally, population and GDP per capita exert negative and positive implications on the load capacity factor, respectively, while energy intensity has no significant environmental effects. The research findings provide significant insights and suggest policy recommendations to address climate change and meet the targets set out in SDG13.
Low-carbon dispatch optimization of wind-solar-thermal-storage multi-energy system based on stochastic chance constraints and carbon trading mechanism Liu, Hong; Su, Yongwei; Cai, Kaijing; Mo, Yingkang
International Journal of Renewable Energy Development Vol 14, No 2 (2025): March 2025
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.60669

Abstract

To improve the low-carbon economic performance of renewable energy-dominated power systems, a multi-energy coordinated optimization dispatch model for wind, solar, thermal, and storage systems considering uncertainties on both the supply and demand sides is proposed. This paper comprehensively considers the economic costs of thermal power unit operation, wind and solar power curtailment, energy storage operation, carbon trading and spinning reserve. The model incorporates a penalizing carbon trading mechanism and uses a stochastic chance-constrained approach to handle fluctuations in wind and solar power generation as well as uncertainties in load forecasting. The study, based on the IEEE 30-bus system, is solved using a stochastic simulation particle swarm optimization algorithm. Results show that after introducing the carbon trading mechanism, the system's carbon emissions were reduced by 8.35%, wind and solar curtailment penalties were reduced by 65.48%, and overall costs decreased by 14.94%. Additionally, the chance-constrained model effectively reduced the system's reserve capacity requirements, with reserve capacity decreasing by 31.84%, leading to a further reduction of 26.83% in overall costs. In the scenario of combined wind-solar-thermal-storage output, the wind and solar curtailment rate dropped to 7.37%, and carbon emissions decreased to 6474.69 tons. Through the "energy shifting" function, the energy storage system provided effective support during peak loads, further optimizing the dispatch outcomes.
Analytical computation of arm inductor for minimizing MMC circulating current using passive method Aslam, Amna; Raza, Muhammad
International Journal of Renewable Energy Development Vol 14, No 1 (2025): January 2025
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.60466

Abstract

The study of circulating currents in modular multilevel converters is vital for improving their efficiency and reliability. The circulating current may arise from capacitor voltage unbalancing, modulation imperfections, load variations, and transient conditions. Such currents typically induce distortions in arm currents, exhibiting second-order harmonics that lead to power losses and negatively impact the ratings of converter components as well as the amplitudes of capacitor voltage ripples. Despite ongoing research, effective strategies to mitigate circulating currents are limited. This paper aims to systematically address this issue by selecting key design parameters specifically arm inductance and capacitor values, to suppress circulating currents. The methodology incorporates harmonic analysis and instantaneous power theory to derive expressions for arm inductance. Initial modelling includes common mode and differential mode analyses, leading to an examination of harmonic content. Analysis reveals that the selection of the arm inductor value is mainly influenced by the second-order harmonic component, whereas the capacitor value is determined by the fundamental harmonic component. By adopting this methodology, the boundary limit for arm inductor selection can be determined. This article proposes a novel expression for arm inductor selection. The proposed expression mainly depends on factors such as load, submodule capacitor voltages, submodule capacitor, and differential current. By selecting an appropriate inductor value based on converter-rated parameters, circulating current within the system can be effectively suppressed. The methodology offers a practical framework for arm inductor selection. Simulation results validation shows strong alignment with analytical results with the error margin of less than 1%, hereby the MMC parameter can be determined with better accuracy through analytic method.
Building energy management model integrating rule-based control algorithm and genetic algorithm Gong, Jie
International Journal of Renewable Energy Development Vol 14, No 1 (2025): January 2025
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.60628

Abstract

Energy is a crucial material foundation for the development of human society. Building energy consumption accounts for a significant proportion of global energy consumption. Optimizing building energy management is of great significance for achieving sustainable development. A building energy management model that integrates rule-based control algorithm and genetic algorithm is proposed, aiming to optimize building energy utilization and reduce operating costs. Mathematical models for different devices in the building energy system are established, and the rule-based control algorithm is used to provide system decision support. Then, the genetic algorithm is integrated to address the complexity and uncertainty of energy optimization problems. The comparative test results showed that the proposed fusion algorithm had higher fitness values and faster convergence speed. The root mean square errors of the algorithm in the training and testing sets were 43.6544 and 43.6844, with the lowest error and highest accuracy among the four algorithms. The simulation experiment results showed that the building energy management model integrating rule-based control algorithm and genetic algorithm had energy expenditures of 788.3 yuan and 967.6 yuan for two types of buildings, respectively. Taking Building 1 as an example, compared with Supervisory Control and Data Acquisition (SCADA), Beetle Antennae Search and Particle Swarm Optimization (BAS-PSO) algorithm, and Long Short-Term Memory-Convolutional Neural Network (LSTM-CNN) algorithm, the proposed model reduced the cost of energy consumption optimization by 39.30%, 28.32%, and 20.20%, respectively. Overall, the proposed building energy management model effectively reduces operating costs, utilizes building energy, and contributes to daily building energy management and decision support.
A double-Gaussian wake model considering yaw misalignment Soesanto, Qidun Maulana Binu; Soesanto, Qidir Maulana Binu; Widiyanto, Puji
International Journal of Renewable Energy Development Vol 14, No 1 (2025): January 2025
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.60690

Abstract

A wake steering has been known to effectively increase wind farm production by deflecting the upstream turbines’ wakes via yaw misalignment, thus minimizing their negative impacts on the downstream turbines' performances. This study presents analytical modeling of horizontal-axis wind turbine (HAWT) wake using low-cost analytical modeling as an alternative to expensive numerical and experimental trials. The existing double-Gaussian (DG) analytical wake model was modified to include the yaw misalignment effect, allowing its usability for the yawed HAWT wake modeling. The benchmark dataset produced by high-fidelity large eddy simulation (LES) of wake flowfields behind the turbine with yaw angles of 0º, 10º, 20º, and 30º were used to validate the accuracy of the DG yaw wake model. Overall, the DG yaw wake model predictions showed good agreement with the benchmark dataset under varying HAWT rotor yaw configurations. The analytical results verified by the LES dataset confirm the effectiveness of yaw misalignment in deflecting the wake trajectory, expediting the wake recovery downstream of the HAWT. In addition, a higher rotor yaw angle improves the wake recovery rate in the prevailing wind direction. Notable deviations against the benchmark dataset were found mainly within the near-wake region owing to flow acceleration arising from turbine-induced turbulence. As a result, the model’s predictions were slightly lower than the benchmark dataset, most likely due to neglecting the acceleration term in the analytical model derivation. Otherwise, the analytical model could accurately predict the mean wake velocity within the far-wake region for all evaluated cases, demonstrating its reliability in estimating wind speed potential within a practical distance for micrositing. These results were also proved quantitatively by statistical evaluations utilizing root mean square error (RMSE) and Pearson correlation coefficient R. The present study points out the importance of the upstream HAWTs’ rotor yaw controls to properly deflect their wakes away from their mainstream trajectories, thus effectively maximizing the wind speed potentials extracted by the downstream HAWTs and improving the overall wind farm production.
Unveiling the interactive effect of green technology innovation, employment of disabilities and sustainable energy: A new insight into inclusive sustainability Ragmoun, Wided; Alfalih, Abdulaziz
International Journal of Renewable Energy Development Vol 14, No 1 (2025): January 2025
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2025.60767

Abstract

The interaction between green technology innovation, employment of disabilities, and sustainable energy is a critical area of research that addresses the emergent need for inclusive sustainability. Nowadays, the interaction between sustainable energy and green technology innovation is considered an essential field of research that has been widely discussed in previous studies. However, the role of employment, especially of people with disabilities, on this effect is still inexistent despite its relative importance for the achievement of sustainable development goals. By unveiling the interactive effect between these factors, strategies can be defined to reduce and limit the negative impact on the environment while promoting employment.  This study aims to fill this research gap by investigating the impact of green technology innovation and employment of disability on sustainable energy in 25 OECD countries from 1994 to 2020 using a dual methodological approach that integrates a parametric analysis: the panel vector autoregression (PVAR) model and a nonparametric assessment: the local linear dummy variable method (LLDV). The findings reveal (i) a significant positive correlation between the enforcement of green technology innovation and the increase in the employment rate of people with disabilities, (ii) a limited direct effect of green technology innovation on green energy consumption, and (iii) a positive impact of the interactive effect of employment of disabilities and green technology innovation, with a higher elasticity than that recorded by a separated effect. The outcomes address environmental challenges and promote social equity in the green economy. They also offer some critical recommendations for policymakers and researchers on sustainable energy.
Renewable energy in sustainable cities: Challenges and opportunities by the case study of Nusantara Capital City (IKN) Yudiartono, Yudiartono; Santosa, Joko; Fitriana, Ira; Wijaya, Prima Trie; Rahardjo, Irawan; Abdul Wahid, La Ode Muhammad; Siregar, Erwin; Hesty, Nurry Widya; Fithri, Silvy Rahmah; Sugiyono, Agus
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.2024.60390

Abstract

This study explores strategies for optimizing energy consumption in Indonesia's New Capital City (IKN) to achieve net zero emissions by 2045, focusing on energy efficiency, sustainable mobility, and renewable energy through the Low Emissions Analysis Platform (LEAP) model. Sustainable cars, such as renewable-energy-powered electric and green hydrogen-powered vehicles, can reduce energy consumption by 43% in 2045 and 33% in 2060, respectively, compared to BAU. GHG emissions per capita will drop 70% in 2045 and 63% in 2060. In NZE scenario, IKN can reach 100% green energy by 2045 with a 4.4 GW solar power plant, a 0.92 GWh BESS, and a full load hour capability of 4 hours. By 2045, 1.1 GW of hydropower and 143 MW of wind power are expected to be utilized. In 2060, hydropower will be 2.8 GW, wind power will be 184 MW, and solar power will be 8 GW with 1.6 GWh of BESS. Lack of legislation, technical expertise, high prices, inadequate grid infrastructure, and renewables shortfalls restrict Indonesia's BESS. Solar installation criteria, subsidies, and off-grid project incentives can all help ease BESS use. Forecasts predict 0.53 GW of rooftop solar PV capacity by 2045 and 3.35 GW by 2060. Net metering and solar tariffs boost rooftop solar system profitability. One ton of green hydrogen production requires 55.7 MWh from a solar power plant. Solar power plant capacity will rise to 0.49 GW by 2045, producing 19,359 tons of green hydrogen, and almost quintuple to 89,594 tons by 2060. Hydrogen generation, storage, transit, and distribution require specific infrastructure due to high capital costs and a lack of networks, yet interest in them is growing.

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