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International Journal of Renewable Energy Development
Published by Universitas Diponegoro
ISSN : 22524940     EISSN : 27164519     DOI : https://doi.org/10.14710/ijred
Core Subject : Science,
Chemistry Energy
The scope of journal encompasses: Photovoltaic technology, Solar thermal applications, Biomass, 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 and management The journal was first introduced in February 2012 and regularly published online three times a year (February, July, October).
Arjuna Subject : Kimia(semua kategori) - Kimia (Lain-Lain)
Articles 573 Documents
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Optimal power flow solutions to power systems with wind energy using a highly effective meta-heuristic algorithm Thi Minh Chau Le; Xuan Chau Le; Ngoc Nguyen Phuong Huynh; Anh Tuan Doan; Thanh Viet Dinh; Minh Quan Duong
International Journal of Renewable Energy Development Vol 12, No 3 (2023): May 2023
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.51375

Abstract

This paper implements two novel meta-heuristic algorithms, including the Coati optimization algorithm (COA) and War strategy optimization (WSO) for determining the optimal solutions to the optimal power flow problem incorporating the use of wind turbines (WTs). Two objective functions are considered in this study, including minimizing the entire electricity generation expenditure (EEGE) with the value point effect and minimizing the voltage fluctuation index (VFI). IEEE 30-bus system is chosen to conduct the whole study and validate the efficiency of the two applied methods. Furthermore, DFIG WTs are used in grids with varying power output and power factor ranges. The comparison of the results obtained from the two methods in all case studies reveals that WSO is vastly superior to COA in almost all aspects. In addition, the positive contributions of WTs to the EEGE and VFI while they are properly placed in the grid are also clarified by using WSO. As a result, WSO is acknowledged as a highly effective search method for dealing with such optimal power flow (OPF) problems considering the presence of renewable energy sources.
Agricultural waste-based magnetic biochar produced via hydrothermal route for petroleum spills adsorption Dessy Ariyanti; I Nyoman Widiasa; Marissa Widiyanti; Dina Lesdantina; Wei Gao
International Journal of Renewable Energy Development Vol 12, No 3 (2023): May 2023
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.52180

Abstract

Oil spills are one of the marine pollution events triggered by the results of tanker operations (air ballast), ship repairs and maintenance (docking), mid-ocean loading and unloading terminals, air bilge (drainage of water, oil, and engine-processed lubricants), ship scrapping, and the most common accidents/collisions of tankers. The impacts vary from the death of marine organisms, especially fish, changes in reproduction and behavior of organisms, plankton contamination, fish migration, as well as ecosystem damage, and economic loss. Bio-based absorbents such as biochar can be an environmentally friendly alternative to chemical sorbents that works to adsorb oil spills faster. In this study, the effectiveness of magnetic biochar in oil spill removal was investigated. It also includes the synthesisation of magnetic biochar from agricultural waste (bagasse, rice husks, and sawdust) using the hydrothermal method at a temperature of 200°C. Hydrothermal carbonization is considered a cost-effective method for biochar production because the process can be carried out at low temperatures around 180°- 250°C. Biochar characterization was carried out with a Scanning Electron Microscope and Energy Dispersive X-Ray (SEM-EDX), Fourier Transform Infrared Spectroscopy (FTIR), and X-Ray Diffraction (XRD). The Brunauer, Emmett, and Teller (BET) and Barrett–Joyner–Halenda (BJH) were used to analyse the surface area and pore size distribution. Based on the results of the SEM-EDX analysis, only biochar was made from rice husk and sugarcane bagasse which contained Fe elements, as a result of the FeCl3.6H2O reaction. This condition is also proven by the presence of the FeO on both samples based on FTIR. The three synthesized biochar are amorphous and categorized as mesopores due to pore size around 15 to 16 nm, which can absorb petroleum spills with a percentage of 81% for sugarcane bagasse-based biochar, 84% for rice husk-based biochar, and 70% for sawdust-based biochar. Biochar from rice husk has excellent adsorption effectiveness with an adsorption capacity of 0.21 g/g in 60 min due to its large functional group area and the excellent attachment of magnetic compound into the biochar surface to form magnetic biochar.
Three-dimensional CFD-solid mechanics analysis of the hydrogen internal combustion engine piston subjected to thermomechanical loads Maher A.R. Sadiq Al-Baghdadi; Sahib Shihab Ahmed; Nabeel Abdulhadi Ghyadh
International Journal of Renewable Energy Development Vol 12, No 3 (2023): May 2023
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.52496

Abstract

Fueling internal combustion engines with hydrogen is one of the most recommended alternative fuels today in order to combat the energy crisis, pollution problems, and climate change. Despite all the advantages of hydrogen fuel, it produces a higher combustion temperature than gasoline. In an internal combustion engine, the piston is among the numerous complex and highly loaded components. Piston surfaces are directly affected by combustion flames, making them critical components of engines. To examine the stress distribution and specify the critical fracture zones in the piston for hydrogen fuel engines, a three-dimensional CFD-solid-mechanics model of the internal combustion engine piston subjected to real thermomechanical loads was analyzed numerically to investigate the distribution of the temperature on the piston body, the interrelated thermomechanical deformations map, and the pattern of the stresses when fueling the engine with hydrogen fuel. With the aid of multiphysics COMSOL software, the CFD-solid-mechanics equations were solved with high accuracy. Despite the increase in pressure on the piston and its temperature when the engine is running on hydrogen fuel, the results show that the hydrogen fuel engine piston can withstand, safely, the thermomechanical loads. In comparison to gasoline fuel, hydrogen fuel caused a deformation of 0.34 mm, an increase of 17%. This deformation is within safe limits, with an average clearance of 0.867 mm between the cylinder liner and piston.
Willingness to pay for green energy sources in the United Arab Emirates (UAE) Haileslasie Tadele; Baliira Kalyebara
International Journal of Renewable Energy Development Vol 12, No 3 (2023): May 2023
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.50575

Abstract

This study investigates the willingness of customers in the UAE to pay a premium for green energy (GE) sources. Given the huge initial investment required for GE projects, raising capital is often achieved by increasing energy bills or taxes. To explore this issue, the study surveyed 192 small and medium-sized businesses using the contingent valuation method. The results indicate that while most businesses are aware of solar and wind energy sources and the importance of combating climate change, half of them are not willing to compromise their current energy use and do not support an increase in utility bills or taxes to finance GE projects. However, older businesses tend to be more willing to pay a premium for GE compared to younger businesses. Overall, majority of the businesses support a voluntary increase in electricity bills. The findings highlight the crucial role of current electricity bills and knowledge about GE sources in shaping customers' willingness to pay. This study contributes to the literature on energy finance and the contingent valuation method in the context of green energy in the UAE.
Response surface optimization and social impact evaluation of Houttuynia cordata Thunb solar drying technology for community enterprise in Chiangrai, Thailand Torpong Kreetachat; Saksit Imman; Kowit Suwannahong; Surachai Wongcharee; Nopparat Suriyachai
International Journal of Renewable Energy Development Vol 12, No 3 (2023): May 2023
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.52402

Abstract

Drying has emerged as one of the most important ways of preserving high-quality and quantity food goods. A force convection solar drying is considered an ecologically and environmentally friendly alternative. This research presents parameter optimization of greenhouse tunnel dryer  of  Houttuynia cordata Thunb (H. cordata) using response surface methodology with the assessment of economic feasibility and social return on invesment. The influence parameters of the drying process were evaluated to obtain maximum efficiency. The individual parameters were temperature (40 – 60 °C), material length (10 – 30 cm), and relative humidity (30 – 50%). The individual parameters of drying temperature showed an extreme effect on the response of moisture content and color value change, while the relative humidity had only an influence on moisture content. On the other hand, the parameter of material length was not significance in both responses. When compared to open-air drying, solar drying reduced the drying time of H. cordata by 57.14%. The payback period of the dryer was found to be 2.5 years. Furthermore, the results reveal that the social return on investment ratio in 2021 was 2.18, then increasing to 2.52 in 2022 and 2.91 in 2023. According to the findings, solar drying technology has the potential to be an adequate product quality improvement technology for H. cordata. It is a feasible drying technology in terms of economic evaluation.
Removal efficiency and reaction kinetics of phenolic compounds in refinery wastewater by nano catalytic wet oxidation Yousif S. Issa; Khaleel I. Hamad; Rafi J. Algawi; Jasim Humadi; Sara Al-Salihi; Mustafa A. Ahmed; Ahmed A. Hassan; Abdul-Kareem Abd Jasim
International Journal of Renewable Energy Development Vol 12, No 3 (2023): May 2023
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.52044

Abstract

A novel nano-catalyst based on iron oxide (MnO2/Fe2O3) was developed to promote wet oxidation of phenol. MnO2 was doped in Fe2O3 matrix to prepare composite nano-catalyst with different doping percentage (0, 2 and 5%). The catalytic phenol oxidation was conducted under different reaction temperatures and residence times. To evaluate the optimal kinetic parameters aiming to maximize phenol removal under the optimal conditions for the catalytic wet phenol oxidation process, modeling was applied on the batch reactor using the novel synthesis nano-catalyst (MnO2/Fe2O3) and the model developed was fed with the experimental data. gPROMS package was used to model the process of phenol oxidation and to optimize the experimental data. The error predicted between the simulated and experimental data was less than 5%. The optimal operating conditions were 294 min residence time, 70oC reaction temperature, and 764 ppm initial concentration of phenol over the prepared 5% MnO2/Fe2O3. Running of wet oxidation of phenol under the optimal operating conditions resulted in 98% removal of phenol from refinery wastewater.
Mediating role of stock market volatility to evaluate asymmetries in the growth-degradation nexus in Nigeria Abdullah AlGhazali; Nana Ize Musa; Saifullahi Sani Ibrahim; Ahmed Samour
International Journal of Renewable Energy Development Vol 12, No 3 (2023): May 2023
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.52322

Abstract

This study explores the mediating role of stock market volatility in the economic growth and environmental degradation nexus in Nigeria using data covering period from 1984 until 2020. The study uses Nonlinear Autoregressive Distributed Lag (NARDL) and a nonparametric asymmetric causality model. While the Wald test in model 1 reveals evidence of weak long-run asymmetric nexus between CO2 and economic growth however, findings in model 2 indicates that stock market volatility (SMV) exerts a strong asymmetric effect in growth-CO2 relation in the long-run. The result of nonlinear model validates the inverted U-shaped growth-degradation nexus consistent with EKC hypothesis. The finding in model 1 reveals that investment exerts a strong impact on CO2 in both the short-run and long-run. On the other hand, the results in model 2 show that the positive component of economic growth has a positive and significant impact on CO2 in Nigeria. However, the negative component of economic growth has a negative impact on CO2. Moreover, the dynamic causality model reveals: (i) a feedback causality between CO2 and the negative component of GDP; and (ii) a unidirectional causality flowing from CO2 to the positive component of GDP. Similarly, result of nonlinear causality test reveals a feedback causality between CO2 and GDP. The implication of the finding suggests that while asymmetric properties of economic growth must be controlled in efforts of promoting environmental sustainability, the stock market has a dedicated role to play in widening access to funds for green investment in Nigeria and other developing economies.
Experimental thermal and electrical performances of a PVT-air collector coupled to a humidification-dehumidification (HDH) cycle Ahmed Ghazy
International Journal of Renewable Energy Development Vol 12, No 3 (2023): May 2023
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.51808

Abstract

Despite their low electrical efficiencies, PVs are widely used to generate electricity from abundant solar energy. In order to maximize the utilization of incident solar energy, PVT collectors have been used to simultaneously generate electricity and thermal energy. Furthermore, combining PVTs with humidification-dehumidification (HDH) cycles can provide electricity and potable water in remote, arid rural areas that are not connected to the grid. In this paper, a PVT-air collector was coupled to an air-heated closed HDH cycle. Air was heated within the PVT collector and humidified by saline water spray inside the humidifier. Fresh water was produced by cooling humid air inside a dehumidifier that is cooled by saline water. The thermal and electrical performances of the PVT-HDH system were experimentally studied and compared to the electrical performance of a PV module with similar characteristics. The results demonstrated a significant decrease in PV temperature within the PVT-HDH system, which resulted in a 20% increase in the output power of the PVT-HDH system at midday compared to the identical PV module. In addition, the PVT-HDH system produced about 3.8 liters of water distillate for a PV module surface area of 1.48 m × 0.68 m, which contributed about 38% to the overall efficiency of the PVT-HDH system.
Prediction of the output power of photovoltaic module using artificial neural networks model with optimizing the neurons number Abdulrahman Th. Mohammad; Hasanen M. Hussen; Hussein J. Akeiber
International Journal of Renewable Energy Development Vol 12, No 3 (2023): May 2023
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.49972

Abstract

Artificial neural networks (ANNs) is an adaptive system that has the ability to predict the relationship between the input and output parameters without defining the physical and operation conditions. In this study, some queries about using ANN methodology are simply clarified especially about the neurons number and their relationship with input and output parameters. In addition, two ANN models are developed using MATLAB code to predict the power production of a polycrystalline PV module in the real weather conditions of Iraq. The ANN models are then used to optimize the neurons number in the hidden layers. The capability of ANN models has been tested under the impact of several weather and operational parameters. In this regard, six variables are used as input parameters including ambient temperature, solar irradiance and wind speed (the weather conditions), and module temperature, short circuit current and open circuit voltage (the characteristics of PV module). According to the performance analysis of ANN models, the optimal neurons number is 15 neurons in single hidden layer with minimum Root Mean Squared Error (RMSE) of 2.76% and 10 neurons in double hidden layers with RMSE of 1.97%.  Accordingly, it can be concluded that the double hidden layers introduce a higher accuracy than the single hidden layer. Moreover, the ANN model has proven its accuracy in predicting the current and voltage of PV module. 
The application of equilibrium optimizer for solving modern economic load dispatch problem considering renewable energies and multiple-fuel thermal units Hung Duc Nguyen; Khoa Hoang Truong; Nhuan An Le
International Journal of Renewable Energy Development Vol 12, No 3 (2023): May 2023
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.52835

Abstract

This study presents a modern version of the economic load dispatch (MELD) problem with the contribution of renewable energies and conventional energy, including wind, solar and thermal power plants. In the study, reduction of electricity generation cost is the first priority, while the use of multiple fuels in the thermal power plant is considered in addition to the consideration of all constraints of power plants. Two meta-heuristic algorithms, one conventional and one recently published, including Particle swarm optimization (PSO) and Equilibrium optimizer (EO), are applied to determine the optimal solutions for MELD. A power system with ten thermal power plants using multiple fossil fuels, one wind power plant, and three solar power plants is utilized to evaluate the performance of both PSO and EO. Unlike other previous studies, this paper considers the MELD problem with the change of load demands over one day with 24 periods as a real power system. In addition, the power generated by both wind and solar power plants varies at each period. The results obtained by applying the two algorithms indicate that EO is completely superior to PSO, and the solutions found by EO can satisfy all constraints. Particularly in Case 1 with different load demand values, EO achieves better total electricity production cost (TEGC) than PSO by 0.75%, 0.87%, 0.13%, and 0.45% for the loads of 2400 MW, 2500 MW, 2600 MW and 2700 MW. Moreover, EO also provides a faster response capability over PSO through the four subcases although EO and PSO are run by the same selection of control parameters. In Case 2, the high efficiency provided by EO is still maintained, though the scale of the considered problem has been substantially enlarged. Specifically, EO can save $51.2 compared to PSO for the minimum TEGC. The savings cost is equal to 0.33% for the whole schedule of 24 hours. With these results, EO is acknowledged as a favourable search method for dealing with the MELD problem. Besides, this study also points out the difference in performance between a modern meta-heuristic algorithm (EO) and the classical one (PSO). The modern metaheuristic algorithm with special structure is highly valuable for complicated problem as MELD.

Page 51 of 58 | Total Record : 573

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