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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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Multi-objective optimisation and sensitivity analysis of component influences on efficiency in air-based bifacial photovoltaic thermal systems (B-PVT) Rajani, Ahmad; Mat Said, Dalila; Noorden, Zulkarnain Ahmad; Ahmad, Nasarudin; Arifin, Muhammad Subhan; Komarudin, Udin; Atmaja, Tinton Dwi; Subagyo, Subagyo; Fudholi, Ahmad
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.2024.60212

Abstract

Bifacial Photovoltaic Thermal (B-PVT) technologies have seen significant advancements in sustainable energy production by converting solar energy into useful electric and thermal energies simultaneously. The present study explored the optimisation of these systems by first performing sensitivity analysis on design parameters to identify key variables affecting their performance efficiencies. The system design and performance were then studied simultaneously using a multi-objective optimisation algorithm NSGA-II. It was found that increasing packing factors from 0.4 to 0.8 leads to a 15% increase in both electrical and thermal efficiencies, while an asymmetry in channel depths could lead to an 8% increase in thermal efficiency.  Key design parameters such as transmissivity cover, mass flow rate, packing factors and channel depth ratios were found to have the most significant influence on overall system performance. Multi-objective optimisation of design variables results in a Pareto front describing trade-offs between solutions of conflicting objectives of performance. Optimisation with preferences towards overall efficiency over temperature differential produces solutions with a high overall efficiency yield of 70.79%, requiring specific values for mass flow rate (0.197 kg/s) and channel ratio (0.129), however at the expense of a reduced temperature differential of 5.12oC. Solutions with a balanced preference towards both objectives could produce a solution that is less biased in performance.
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.
Energy efficient design of rural prefabricated buildings based on ANN and NSGA-II Bai, Chaoqin; Xue, Xiaolin
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.2024.60153

Abstract

The growing concern about global climate change and the rapid development of rural areas highlight the need for energy efficient building design. This study aims to establish a multi-objective optimization model based on artificial neural network (ANN) and non-dominated sorting Genetic algorithm II (NSGA-II) to optimize the energy consumption of rural prefabricated buildings. Firstly, ANN and simulation technology are used to build building models and predict building energy consumption. Then, NSGA-II algorithm was used to optimize the energy consumption and material selection of the building, and the best prefabricated building scheme was obtained. The experimental results show that the optimization efficiency of the model is about 95%, which is better than the traditional method. Specifically, compared with the NSGA-II algorithm, the model reduces energy consumption by 16.7%, operating costs by 20.0%, and carbon emissions by 20.0%. When the cost optimization, energy consumption optimization and carbon emission optimization are difficult to balance, the average optimization efficiency of the research design method is about 90% when the cost optimization rate is low, and the other optimization rates are about 85% when the cost optimization rate rises to 50%. When the cost optimization reaches the maximum, the optimization rate remains at about 80%. These results show that the proposed model is robust and efficient. This study provides a comprehensive framework for designing sustainable and energy efficient rural prefabricated buildings that can help reduce energy consumption and environmental impact. It has positive significance in the sustainable development of rural economy and provides a new way of thinking for rural construction.
Orderly charging strategy for electric vehicles based on multi-level adjustability Teng, Changlong; Ji, Zhenya; Yan, Peng; Wang, Zheng; Ye, Xianglei
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.2024.60053

Abstract

The development of electric vehicles (EVs) is one of the essential ways to reduce environmental pollution. With the rapid growth in EVs, an orderly charging strategy based on multi-level adjustable charging power is proposed to address the problem of increasing peak-to-valley difference due to disorderly charging in different scenarios. Based on the information of multi-level adjustable charging power, information about staying in the residential area, and charging demands of EVs, this research designs a centralized charging mode with complete information under the centralized scenario and a decentralized charging mode with incomplete information under the decentralized scenario. This research takes the minimization of peak-to-valley difference in the residential area as the objective function and considers that the charging pile can have the function of multi-level adjustable charging power to support these two scenarios. Two charging modes of the charging pile are designed, and orderly charging model of EVs in the residential area is constructed. EVs can select charging time and charging power by using Bluetooth or code scanning in the charging pile. This research aims to design two orderly charging modes to effectively implement peak shaving and valley filling while ensuring the charging demand of EVs. This research uses the CPLEX solver in MATLAB to solve the objective. The simulation results show that EVs can reasonably select the multi-level adjustable charging power under different scenarios and provide a reference for engineering related to orderly charging. Strategy 4, proposed in this research, has the lowest peak-to-valley difference of the four strategies. The peak-to-valley difference is only 87 kW under the centralized scenario, and the peak-to-valley difference is 282 kW under the decentralized scenario.
Exploring the impact of financial development on renewable energy consumption within the renewable energy-environmental Kuznets curve framework in Sub-Saharan Africa Prempeh, Kwadwo Boateng; Kyeremeh, Christian; Danso, Felix Kwabena; Yeboah, Samuel Asuamah
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.2024.60339

Abstract

Renewable energy usage is deemed a feasible panacea to environmental degradation and energy poverty. In pursuit of carbon neutrality, nations are obligated to formulate strategies that bolster renewable energy initiatives following the Sustainable Development Goals of the United Nations. Given this, this article scrutinises the impact of financial development on the advancement of renewable energy consumption within the renewable energy- environmental Kuznets curve (REKC) framework while controlling for foreign direct investment (FDI), trade openness, governance and urbanisation using a panel of 38 Sub-Saharan African (SSA) nations from 2002-2019. The empirical findings based on the panel corrected standard error (PCSE) and the Feasible Generalized Least Squares (FGLS) models validated the REKC hypothesis for renewable energy consumption in the SSA region. Financial development, economic growth, trade openness, governance, and urbanisation have a substantial and detrimental impact on renewable energy consumption, whereas FDI has a neutral effect. The Dumitrescu-Hurlin causality tests demonstrate a bidirectional (feedback) causality between renewable energy consumption and all its determinants except for trade openness, where a unidirectional causality from renewable energy consumption to trade openness was established. Given these insights, our paper adds to empirical literature and provides incisive suggestions for policy formulation. 
Clustering-based assessment of solar irradiation and temperature attributes for PV power generation site selection: A case of Indonesia’s Java-Bali region Tanoto, Yusak; Budhi, Gregorius Satia; Mingardi, Sean Frederick
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.2024.59998

Abstract

This study presents clustering-based assessments of solar attributes for locating potential solar photovoltaic (PV) power plant sites using k-means and density-based spatial clustering of applications with noise (DBSCAN) by examining the yearly average single-attribute and three-attribute clustering on a dataset of long-term hourly-based direct and diffuse irradiation, ambient temperature, and solar PV power output from 2005 to 2022. Three-attribute clustering enables stakeholders to better understand the characteristics of a cluster by collectively identifying three solar attributes and the magnitude of each attribute in an area or cluster. The presence of this information, which constitutes the clusters, suggests that these attributes have different effects on solar PV output power in different clusters. Although k-means is an effective method for investigating potential locations for PV power plant placements, DBSCAN offers users an alternative method for accomplishing a similar goal. In the case of three-attribute clustering of direct irradiation with k-means and DBSCAN, the 18-year mean value of clusters with the highest yearly average value is achieved at very similar values of 0.305 kW/m2 and 0.310 kW/m2, respectively. It turns out that only six years of direct irradiation had an annual mean value of less than 0.305 kW/m2. This finding implies that in the long run, the solar resources in terms of direct irradiation will typically surpass 0.3 kW/m2/MW installed capacity over all areas suitable for PV power plants. While focusing on the Java-Bali region, Indonesia, the findings, and methods appear to be of broader interest to policymakers, particularly in developing countries where solar PV is considered an option for sustainable energy generation.
Electrical power output potential of different solar photovoltaic systems in Tanzania Warburg, Christopher Thomas; Pogrebnaya, Tatiana; Kivevele, Thomas
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.2024.58972

Abstract

This study examines the photovoltaic (PV) energy output and levelized cost of energy (LCOE) in seven regions of Tanzania across five different tilt adjustments of 1 MW PV systems. The one-diode model equations and the PVsyst 7.2 software were used in the simulation. The results reveal variations in energy output and LCOE among the regions and tilt adjustments indicating a strong correlation between PV energy output and solar irradiance incident on the PV panel. For horizontal mounting, the annual energy output ranges from 1229 MWh/year in Kilimanjaro to 1977 MWh/year in Iringa. Among the three optimal tilt adjustments, annually, monthly and seasonal, the last two are predicted to yield larger energy outputs, whereas the two axis tracking configuration consistently provides the maximal energy output in all regions, ranging from 1533 MWh/year in Kilimanjaro to 2762 MWh/year in Iringa. The LCOE analysis demonstrates the cost-effectiveness of solar PV systems compared to grid-connected and isolated mini-grid tariffs. The LCOE values across the regions and tilt adjustments range from $0.07/kWh to $0.16/kWh. In comparison, the tariff for grid-connected solar PV is $0.165/kWh, while for isolated mini-grids; it is $0.181/kWh. The monthly optimal tilt configuration proves to be the most cost-effective option for energy generation in multiple regions, as it consistently exhibits the lowest energy cost compared to the other four configurations. The results provide valuable insights into the performance and economic feasibility of various system setups. Through meticulous simulation and data analysis, we have gained a comprehensive understanding of the factors influencing energy generation and costs in the context of solar photovoltaic systems.
Effectiveness of building envelope parameters and adopting PV panels to reduce reliance on local generators in hot-dry climate Ibrahim, Ahmed Jabar; Zangana, Dnya Dlshad; Dehghanifarsani, Laleh
International Journal of Renewable Energy Development Vol 13, No 3 (2024): May 2024
Publisher : Center of Biomass & Renewable Energy (CBIORE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/ijred.2024.60111

Abstract

The growing energy demand, associated with the inability of the current infrastructure to satisfy this demand, has presented numerous challenges in Iraq's electricity sector. As a result, there has been an increased dependence on local diesel generators to mitigate power outages in homes. However, these generators raise environmental concerns and are associated with high operating CO₂  emissions. Here, using the DesignBuilder and EnergyPlus simulation software, the effectiveness of different building envelope modifications and photovoltaic panels as alternative energy sources was examined. Specifically, the impact of wall and roof insulation, window glazing, and shading devices on energy efficiency was analyzed. The results indicated that roof insulation is the most effective in reducing energy consumption by 28.8%, followed by wall insulation by 13.01%, while the effect of windows glazing and shading devices was insignificant. Furthermore, the installation of solar panels led to a significant reduction in energy demand by 53.6%, thereby decreasing operating carbon dioxide emissions and providing a practical alternative to the use of local generators. Our study offers valuable insights into the design of energy-efficient residential buildings in hot and dry climates. It highlights the importance of selecting appropriate building materials and integrating renewable energy sources, presenting a more environmentally effective solution to mitigate energy shortages.
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.

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