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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 17 Documents
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Search results for , issue "Vol 12, No 3 (2023): May 2023" : 17 Documents clear
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.
Preparation of MgO-CaO/SiO2 catalyst from dolomite and geothermal solid waste for biodiesel production Widayat Widayat; Nadia Taradissa Maheswari; Wahyu Fitriani; Luqman Buchori; Hantoro Satriadi; K Kusmiyati; Norzita Ngadi
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.2023.51573

Abstract

Energy demand will increase along with the increase in population. The current energy demand is dominated by non-renewable energy as it could reduce dependence on fossil energy sources; hence, it is imperative to be developed. Biodiesel with waste cooking oil as its raw material is one of the renewable energies currently being developed. Catalyst can be utilized to improve the quality of biodiesel product and process. The major content in solid waste of geothermal power plant is silica oxide, while dolomite contains magnesium oxide and calcium oxide. This study aims to test the MgO-CaO/SiO2 catalyst performance from geothermal waste and dolomite in biodiesel production. The results of catalyst characterization based on FTIR, SEM, and BET tests indicates a successful impregnation method in MgO-CaO/SiO2 catalyst production. The result shows that the best variable to produce biodiesel is at the ratio of MgO-CaO: SiO2 is 15:85. The conversion of biodiesel using this variable is 92.63%. The overall results of biodiesel obtained in this study have a good quality and is in accordance with SNI 7182-2015.
An investigation of a 3D printed micro-wind turbine for residential power production Mohammad Shalby; Ahmad A Salah; Ghayda’ A Matarneh; Abdullah Marashli; Mohamed R. Gommaa
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.2023.52615

Abstract

The wind energy sector is rapidly growing and has become one of the most important sources of renewable power production. New technologies are being developed to increase energy production. This study focuses on developing and evaluating a 3-D printed micro-wind turbine system for residential electricity production. The effectiveness of using Poly Lactic Acid material for model production was assessed using the SolidWorks environment. Then, three–dimensional CFD model was developed to simulate a micro-wind turbine. The CFD model was validated in good agreement against scale physical model experiments performed in a wind tunnel. The results demonstrated that the 5-blade micro-wind turbine design was the most effective under the tested conditions, with a low cut-in speed and the ability to operate under torque up to 70 N.m. Finally, the currently available manufacturing processes for micro-wind turbines have been evaluated. Future work should evaluate the performance of the MWT system under realistic conditions in a site test to determine energy production and total efficiency
A four-line active shunt filter to enhance the power quality in a microgrid Abdelkader Mostefa; Karim Belalia; Tayeb Lantri; Houari Merabet Boulouiha; Ahmed Allali
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.2023.50270

Abstract

In recent years, power quality has become a major concern for electric network managers. Active filtering control schemes ensure improved power quality of the electric network and are able to maintain a desired voltage level at the point of connection, regardless of the current absorbed by nonlinear loads. Harmonics can cause vibrations, equipment distortion, losses and sweatiness in transformers. The main objective of this work is to enhance the quality of energy in a microgrid consisting of 100 kW photovoltaic (PV) system and a 50 kW battery storage connected to nonlinear and unbalanced loads. This paper proposes a the four-arm parallel active filter with a on Proportional-Integral (PI) controller to mitigate the harmonic problems in a microgrid. In addition, an algorithm has been designed to eliminate the neutral current. The identification function is one of the most particular approach for extracting harmonics, it involves providing a current reference imposed by the active filter in order to carry out the filtering operation. Both the performance and the quality of the current harmonic compensation's depend strongly on the strategy adopted for the generating the current reference. In this work, the instantaneous power strategy p-q is chosen outstanding the simplicity and effectiveness in implementation. The proposed control strategy has been tested under simulations and the results have shown good tracking of the references and a significant reduction in the Total Harmonic Distorsion (THD) level under highly unbalanced conditions of the nonlinear loads. The current THD is reduced from 43.64 before filtering to 3.74% after the application of the four-arm filter, following the recommendations of IEEE-519 standard (THD less than 5%).
Simulation and experimental study of refuse-derived fuel gasification in an updraft gasifier Thanh Xuan Nguyen-Thi; Thi Minh Tu Bui; Van Ga Bui
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.2023.53994

Abstract

Refuse-derived fuel (RDF) made from the mixture of wood and loose rice husk increases the porosity of the fuel in the furnace to facilitate the gasification process. Simulation results show that CO is concentrated in the incomplete combustion zone and CO2 forms mainly in the fully burned area; CH4 forms in the reduction region, while H2 forms in the region of high temperature of the furnace. When the mixture composition was f=0.3, the CO concentration in the syngas reached about 21%, the H2 concentration reached about 2% and the CH4 concentration was too low to be ignored. When the mixture composition increased to f = 0.5, the CO concentration reached about 26%, the H2 concentration remained almost unchanged and the CH4 content increased to 6%. The calorific value of the syngas reached a maximum when f = 0.5 and the temperature of the reduction zone is in the range of 900K to 1200K. Air humidity affects CO concentration but not much on CH4 and H2 concentration as well as the syngas calorific value. The difference between simulation and experimental results is not more than 10% for CH4 concentration and not more than 14% for CO2 concentration. The power of the spark ignition engine is reduced by 30% when running on syngas compared to when running on gasoline.

Page 2 of 2 | Total Record : 17

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