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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 8 Documents
 1 
Search results for , issue "Vol 13, No 1 (2024): January 2024" : 8 Documents clear
Kinetic and thermodynamic study of composite with jute fiber as reinforcement Assanvo, Edja Florentin; Toure, Kicoun Jean-Yves N’Zi; N’Gatta, Kanga Marius; Boa, David
International Journal of Renewable Energy Development Vol 13, No 1 (2024): January 2024
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.54407

Abstract

In the present work, engineered by compression molding process via a hydraulic press, the A and B composite samples were carried out with 5% and 10% ratio respectively of Ricinodendron heudelotii oil-based alkyd resin in bio-based matrix made of unsaturated polyester using jute fibers as reinforcement material. The samples’ thermal decomposition was performed through thermogravimetry (TG) and derivative thermogravimetry (DTG) analyses. Both composite samples exhibit two stages of decomposition, where the main occurs at 200 - 550°C. Aiming to study and being able to model the thermal degradation of the elaborated composites, finding the kinetic triplets appears the best option to describe the kinetic process undergo by the composites in order to evaluate the performance application of the composites. Two non-isothermal techniques, Flynn-Wall-Ozawa (FWO) and Kissinger have been used to assess the activation energy Ea, and it is found that the apparent activation energy varies with the degree of conversion indicating that both composites decompose with a multiple step mechanism process. The appropriate reaction model for the second stage of decomposition was best suited with Johnson-Mel-Avrami (n<1) model and has been established, allowing us to model thermal degradation behavior of our elaborated composite material and set predictions. The estimated Arrhenius factor values were respectively about A and B composites, 4.12.1015 min-1 and 10.42.1015 min-1, allowing us to set the final equation characterizing the degradation process for the second and main decomposition stage. Finally, as a result of comparison between A and B composites, A appears to be the more thermally stable due to its lower values of Arrhenius pre-exponential factor over the main stage of decomposition and higher calculated the activation energy values.
Investigation of wind veer characteristics on complex terrain using ground-based lidar Tumenbayar, Undarmaa; Ko, Kyungnam
International Journal of Renewable Energy Development Vol 13, No 1 (2024): January 2024
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.56352

Abstract

The wind direction shift with height significantly influences wind turbine performance, particularly in relation to terrain conditions. In this work, wind conditions at 12 measurement heights ranging from 40 m to 200 m using a ground lidar, Windcube V2, installed on a 16 m tall building were analysed to examine the characteristics of wind veer angles in complex terrain. The measurement campaign was carried out from January 1st to December 31st, 2022, in the southeastern part of South Korea. The terrain complexity around the ground lidar system was evaluated using the ruggedness index (RIX), whose result was 14.06 percent corresponding to complex terrain. The ground lidar measurements were compared with mesoscale data, EMD-WRF South Korea, for the data accuracy check. Wind veer frequencies and wind roses were derived to identify directional shifts with height. Furthermore, diurnal, monthly, and seasonal variations of wind veer characteristics were analysed. Wind shear exponent factor (WSE) and turbulence kinetic energy (TKE) were calculated, and wind veer profiles were constructed based on these parameters. The relative errors of wind speeds were analysed for rotor equivalent wind speed (REWS) and hub height wind speed (HHWS), with REWS with wind veer correction, REWSveer, as a reference. Additionally, atmospheric stability conditions were classified using WSE and TKE, and the vertical changes in wind veering were analysed according to the stability conditions. The findings reveal lower wind speeds exhibited larger wind veer values and fluctuations. The relative errors for the REWS and the HHWS were 0.04 % and 0.20 % on average, respectively. The study demonstrates that terrain conditions significantly impacted wind veer angles at heights below 100 m, whereas the influence diminished with increasing height above 100 m. The results could be helpful for wind farm developers to make decisions on the siting as well as the hub height of wind turbines on complex terrain
Building energy consumption prediction method based on Bayesian regression and thermal inertia correction Su, Huiling; Duan, Meimei; Zhuang, Zhong; Bai, Yunlong
International Journal of Renewable Energy Development Vol 13, No 1 (2024): January 2024
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2024.58012

Abstract

The accurate prediction of building energy consumption is a crucial prerequisite for demand response (DR) and energy efficiency management of buildings. Nevertheless, the thermal inertia and probability distribution characteristics of energy consumption are frequently ignored by traditional prediction methods. This paper proposes a building energy consumption prediction method based on Bayesian regression and thermal inertia correction. The thermal inertia correction model is established by introducing an equivalent temperature variable to characterize the influence of thermal inertia on temperature. The equivalent temperature is described as a linear function of the actual temperature, and the key parameters of the function are optimized through genetic algorithm (GA). Using historical energy usage, temperature, and date type as inputs and future building energy comsuption as output, a Bayesian regression prediction model is established. Through Bayesian inference, combined with prior information on building energy usage data, the posterior probability distribution of building energy usage is inferred, thereby achieving accurate forecast of building energy consumption.  The case study is conducted using energy consumption data from a commercial building in Nanjing. The results of the case study indicate that the proposed thermal inertia correction method is effective in narrowing the distribution of temperature data from a range of 24.5°C to 36.5°C to a more concentrated range of 26.5°C to 34°C, thereby facilitating a more focused and advantageous data distribution for predictions. Upon applying the thermal inertia correction method, the relative errors of the Radial Basis Function (RBF) and Deep Belief Network (DBN) decreases by 2.0% and 3.1% respectively, reaching 10.9% and 7.0% correspondingly. Moreover, with the utilization of Bayesian regression, the relative error further decreases to 4.4%. Notably, the Bayesian regression method not only achieves reduced errors but also provides probability distribution, demonstrating superiority over traditional methods.
Enhancing microbial fuel cell performance with carbon powder electrode modifications for low-power sensors modules Al-badani, Mohammed Adel; Chong, Peng Lean; Lim, Heng Siong
International Journal of Renewable Energy Development Vol 13, No 1 (2024): January 2024
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2024.58977

Abstract

Microbial Fuel Cell (MFC) is a promising technology for harnessing energy from organic compounds. However, the low power generation of MFCs remains a significant challenge that hinders their commercial viability. In this study, we reported three distinct modifications to the stainless-steel mesh (SSM), carbon cloth, and carbon felt electrodes using carbon powder (CP), a mixture of CP and ferrum, and a blend of CP with sodium citrate and ethanol. The MFC equipped with an SSM and CP anode showed a notable power density of 1046.89 mW.m-2. In comparison, the bare SSM anode achieved a maximum power density of 145.8 mW m-2. Remarkably, the 3D-modified SSM with a CP anode (3D-SSM-CP) MFC exhibited a substantial breakthrough, attaining a maximum power density of 1417.07 mW m-2. This achievement signifies a significant advancement over the performance of the unaltered SSM anode, underscoring the effectiveness of our modification approach. Subsequently, the 3D-SSM-CP electrode was integrated into single-chamber MFCs, which were used to power a LoRaWAN IoT device through a power management system. The modification methods improved the MFC performance while involving low-cost and easy fabricating techniques. The results of this study are expected to contribute to improving MFC's performance, bringing them closer to becoming a practical source of renewable energy.
Grey wolf optimization and incremental conductance based hybrid MPPT technique for solar powered induction motor driven water pump Shetty, Divya; Sabhahit, Jayalakshmi Narayana
International Journal of Renewable Energy Development Vol 13, No 1 (2024): January 2024
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2024.57096

Abstract

The use of Solar Powered Water Pumps (SPWP) has emerged as a significant advancement in irrigation systems, offering a viable alternative to electricity and diesel-based pumping methods. The appeal of SPWPs to farmers lies in their low maintenance costs and the incentives provided by government agencies to support sustainable and cost-effective agricultural practices. However, a critical challenge faced by solar photovoltaic (PV) systems is their susceptibility to power loss under partial shading conditions, which can persist for extended periods, ultimately reducing system efficiency. To address this issue, this paper proposes the integration of Maximum Power Point Tracking (MPPT) controllers with efficient algorithms designed to identify the peak power during shading events. In this study, a hybrid approach combining Grey Wolf Optimization (GWO) and Incremental Conductance (INC) is employed to maximize the power output of SPWPs driven by an induction motor under partial shading conditions. In order to achieve faster convergence to the global peak, GWO handles the first stages of MPPT and then INC algorithm is employed at the end of the MPPT process.  This method reduces the computations of GWO and streamlines the search space. The paper evaluates the performance of the induction motor in terms of speed settling time and torque ripple. To validate the effectiveness of the GWO-INC hybrid approach, simulations are conducted using the MATLAB Simulink platform. The outcomes are then compared with results obtained from various well-known approaches, including Particle Swarm Optimization – Perturb and Observe (PSO-PO), PSO-INC, and GWO-PO, illustrating the superiority of the GWO-INC hybrid approach in enhancing the efficiency and performance of solar water pumps during shading. The GWO-INC excels with 99.6% accuracy in uniform shading and 99.8% in partial shading. It achieves convergence in a mere 0.55 seconds under uniform shading conditions and only 0.42 seconds when partial shading is present. Moreover, it significantly reduces torque oscillations, with a torque ripple of  8.26% in cases of uniform shading and 10.56% in partial shading.
Site suitability analysis of wind energy resources in different regions of Algeria’s southwestern highland Amrani, Fatima Zohra Bochra; Marih, Salah; Missoum, Ibrahim; Boutlilis, Fatima; Bekkouche, Benaissa
International Journal of Renewable Energy Development Vol 13, No 1 (2024): January 2024
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2024.56476

Abstract

This paper presents a site suitability analysis for a 20 MW wind farm project in western Algeria’s highlands. The aim is to improve the quality of the electricity grid’s service and increase Algeria’s renewable energy utilization. The wind potential of three regions, Mecheria, El Kheiter, and Naâma, was evaluated using the Weibull function and the wind atlas analysis and application program (WAsP) with a ten-year database (2011-2021) at 10 m hub height. The assessment encompassed a comprehensive analysis of various wind resource parameters, including mean wind speed, prevailing direction, and power densities. In comparison to other sites, the Mecheria region has the best wind potential, with a mean annual wind speed of 6.31 m/s, a power density of 283 W/m2, and Weibull parameters A = 7.1 m/s and k = 2.02. These promising results prompted us to design a wind farm in this region using Power Wind 90/2000 kW turbine technology facing the predominant wind directions of the site, producing 103.91 GWh of total annual gross energy produced (gross AEP) and 103.75 GWh of total annual net energy produced (net AEP). Finally, it appears that the wind resources in the selected region are well-suited for electricity generation, offering a promising opportunity to reduce the country's dependence on fossil fuels.
Screen printed carbon electrode from coconut shell char for lead ions detection Heliani, Kinkind Raras; Rahmawati, Fitria; Wijayanta, Agung Tri
International Journal of Renewable Energy Development Vol 13, No 1 (2024): January 2024
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2024.57679

Abstract

This research aimed to produce a screen-printed carbon electrode (SPCE) from an activated coconut shell carbon. As a raw material, coconut shell char provides renewability and is abundantly available in the market. Meanwhile, SPCE offers a simple electroanalytical electrode because the working, counter, and reference electrodes are in one piece. The coconut shell carbon was activated by steam at 700 oC for 1h, producing AC700 that was then characterized to ensure the result by following per under carbon as the main component, the phases, crystal structure, surface area, morphology, and elemental content. The result showed that the surface area of AC700 is 816 m2/g, and the surface structure is porous, as identified by SEM images. Impedance analysis followed by data fitting and conductivity calculation found a high conductivity of 8.68 x 10-2 Scm‑1. The produced-SPCE or SPAC700 was modified by ferrocene at various compositions of 10%; 20%; and 30% of mass. The SPAC700-Fc30 provided the best performance for lead analysis with a detection limit of 0.35 mM, a quantitation limit of 1.17 mM, and good reproducibility with a Repeatability Coefficient (RC) of 0.022. SPAC700-Fc30 showed good lead ions detection despite under 10% Cu2+ and 10% Co2+ interferences. The result confirmed the potential use of coconut shell char as the raw material for SPCE production.
Policies and measures for energy efficiency improvement at households: A bibliometric analysis Streimikiene, Dalia; Kyriakopoulos, Grigorios L.; Ślusarczyk, Beata; Stankuniene, Gintare
International Journal of Renewable Energy Development Vol 13, No 1 (2024): January 2024
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2024.57769

Abstract

Recently, governmental subsidies have led to increased renewable energy adoption and household CO2 emissions reduction. However, energy efficiency improvement and greenhouse gas emission reduction potential in households’ sector are not yet fully realized. Decision-making by individuals is also a crucial factor in adopting energy-efficient and renewable energy technologies, which is why this study analyses some important behavioral change-linked issues. This study also focuses on various policies and measures to achieve energy efficiency improvements in households, such as use of renewable energy sources, renovation of residential buildings, use of energy efficient appliances etc. The methodology of the study contains a bibliometric analysis in the field of energy efficiency at households, covering the years of publication 2010-2023 and organizing all documents into 9 classifications. Among them 6 classifications have been further considered:  Citation analysis; Authors’ networks; High impact journals of publishing; Knowledge mapping of co-authorship collaboration among institutions; Co-authorship among countries; Keywords concurrence analysis. Following a systematic literature review the bibliometric findings reveal the steady increase of literature production in the field of energy efficiency at households, showing also the pivotal role of institutions among developed and industrialized economies. Moreover, there is a densely and steadily growing network of keywords reported, implying the thematic expansion of this topic from the modelling-pilot scales towards the real world and in field applications. Finally, identified research constraints of energy efficiency improvement are that of: high costs, lack of information and knowledge, low priority to environmental and climate change mitigation concerns, and resistance to behavioral change.

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