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H Hadiyanto
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hadiyanto@che.undip.ac.id
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CBIORE office, Jl. Prof. Soedarto, SH-Tembalang Semarang
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INDONESIA
International Journal of Renewable Energy Development
ISSN : 22524940     EISSN : 27164519     DOI : https://doi.org/10.61435/ijred.xxx.xxx
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.
Articles 709 Documents
Optimum Sizing Algorithm for An Off Grid Plant Considering Renewable Potentials and Load Profile Nabiha Brahmi; Sana Charfi; Maher Chaabene
International Journal of Renewable Energy Development Vol 6, No 3 (2017): October 2017
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.6.3.213-224

Abstract

The energy demand in remote area cannot be satisfied unless renewable energy based plants are locally installed. In order to be efficient, such projects should be sized on the basis of maximizing the renewable energies exploitation and meeting the consumer needs. The aim of this work is to provide an algorithm-based calculation of the optimum sizing of a standalone hybrid plant composed of a wind generator, a photovoltaic panel, a lead acid-battery bank, and a water tank. The strategy consists of evaluating the renewable potentials (solar and wind). Obtained results are entered as inputs to established generators models in order to estimate the renewable generations. The developed optimal sizing algorithm which is based on iterative approach, computes plant components sizes for which load profile meet estimated renewable generations. The approach validation is conducted for A PV/Wind/Battery based farm located in Sfax, Tunisia. Obtained results proved that the energetic need is covered and only about 4% of the generated energy is not used. Also a cost investigation confirmed that the plant becomes profitable ten years after installation.Article History: Received June 24th 2017; Received in revised form September 26th 2017; Accepted Sept 30th 2017; Available onlineCitation: Brahmi, N., Charfi, S., and Chaabene, M. (2017) Optimum Sizing Algorithm for an off grid plant considering renewable potentials and load profile. Int. Journal of Renewable Energy Development, 6(3), 213-224.https://doi.org/10.14710/ijred.6.3.213-224
Two-Phase Expander Approach for Next Generation of Heat Recovery Systems Angad S Panesar; Marco Bernagozzi
International Journal of Renewable Energy Development Vol 8, No 3 (2019): October 2019
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.8.3.203-213

Abstract

This study presents the numerical adaptations to the semi-empirical expander model in order to examine the feasibility of piston expanders under off-design and two-phase scenarios. This expander model considers supply valve pressure drop, condensation phenomena, heat losses, leakage losses and friction losses. Using Aspen HYSYS©, the expander model is utilised in simulating the next generation of integrated engine cooling and exhaust heat recovery system for future heavy-duty engines. The heat recovery system utilises water-propanol working fluid mixture and consists of independent high pressure (HP) and low pressure (LP) expander. The results of off‑design and two-phase operation are presented in terms of expander efficiency and the different sources of loss, under two distinctive engine speed-load conditions. The heat recovery system, operating with the LP expander at two-phase and the HP expander at superheated condition, represented the design point condition. At the design point, the system provided 15.9 kW of net power, with an overall conversion efficiency of 11.4%, representing 10% of additional engine crankshaft power. At the extreme off-design condition, the two-phase expander operation improved the system performance as a result of the nullification of leakage losses due to the much denser working fluid. The optimised two-phase operation of the LP expander (x=0.55) and the HP expander (x=0.9) at the extreme-off design condition improved the system power by nearly 50% (17.4 vs. 11.7 kW) compared to the reference state. Finally, adapting piston air motors as two-phase expanders for experimental evaluation and reduction in frictional losses was a recommended research direction. ©2019. CBIORE-IJRED. All rights reserved
The feed-in tariff (FIT) policy to improve renewable energy utilization: An analysis of FIT implementation in ASEAN countries from renewable energy growth, decarbonization, and investment perspective Mujammil Asdhiyoga Rahmanta; Ari Permana; Wilson Susanto; Endiarjati Dewandaru Sadono; Irine Handika Ikasari; Muhammad Akhsin Muflikhun
International Journal of Renewable Energy Development Vol 12, No 5 (2023): September 2023
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2023.55929

Abstract

The FIT policy are widely adopted in the world to promote the utilization of renewable energy technology (RET). Tariff rates, tariff regression mechanisms, contract term, and quota constraints are all components of the FIT policy. This policy has also been adopted by Association of Southeast Asian Nations or ASEAN countries to optimize their renewable energy (RE) potential. This paper examines the utilization of RET in power generation under the FIT policy from the perspective of the growth of renewable energy, environment, and investment which applied in five major ASEAN countries in term of the biggest generation capacity, such as: Indonesia Vietnam, Malaysia, Thailand, and the Philippines. This study shows that the FIT has been successful in accelerating renewable energy growth compared to pre-FIT, where annual RE capacity growth was 7.52% in Thailand (2007-2021), 16.38% in Vietnam (2011-2021), 4.56% in Indonesia (2012-2021) 2021), 9.11% in Malaysia (2012-2021), and 5.21% in the Philippines (2012-2021). FIT also managed to keep CO2/kWh emissions production stable in Vietnam, Malaysia, and Thailand while increasing RE production in their power systems. Otherwise, due to the low utilization of RET in Indonesia and the Philippines, CO2 emissions in them has increased significantly, 6.67% per year at Indonesia, and 15.25% per year at the Philippines after the introduction of the FIT. Generally, FIT has succeeded in increasing the value of international funding investments in RE sector in Indonesia, Vietnam, Malaysia, Thailand, and the Philippines
Tin (II) Chloride Catalyzed Esterification of High FFA Jatropha Oil: Experimental and Kinetics Study Ratna Dewi Kusumaningtyas; Prima Astuti Handayani; Rochmadi Rochmadi; Suryo Purwono; Arief Budiman
International Journal of Renewable Energy Development Vol 3, No 2 (2014): July 2014
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.3.2.75-81

Abstract

Biodiesel is one of the promising energy source alternatives to fossil fuel. To produce biodiesel in a more economical way, the employment of the low-cost feed stocks, such as non-edible oils with high free fatty acid (FFA), is necessary. Accordingly, the esterification reaction of FFA in vegetable oils plays an important role in the biodiesel production. In this work, esterification of FFA contained in Crude Jatropha Oil (CJO) in the presence of tin (II) chloride catalyst in a batch reactor has been carried out. The esterification reaction was conducted using methanol at the temperature of 40-60 °C for 4 hours. The effect of molar ratio of methanol to oil was studied in the range 15:1 to 120:1. The influence of catalyst loading was investigated in the range of 2.5 to 15% w/w oil. The optimum reaction conversion was obtained at 60 °C with the catalyst loading of 10% w/w oil and molar ratio of methanol to oil of 120:1. A pseudo-homogeneous reversible second order kinetic model for describing the esterification of FFA contained in CJO with methanol over tin (II) chloride catalyst was developed based on the experimental data. The kinetic model can fit the data very well.
Numerical Analysis of Velocity Magnitude on Wave Energy Converter System in Perforated Breakwater Oki Setyandito; Nizam Nizam; Andrew John Pierre; Gede Dharma Suputra; Yureana Wijayanti; Martin Anda
International Journal of Renewable Energy Development Vol 11, No 1 (2022): February 2022
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2022.38535

Abstract

Waves are an alternative energy source that can be used for electricity generation. Wave Energy Converter (WEC) system in perforated breakwater is potentially applicable WEC system for coastal area. The magnitude of wave energy generated is determined by the volume of sea water inside the perforated breakwater. This volumetric flow rate is calculated using the flow velocity at perforated holes on the structure slope. Therefore, this research aims to study the velocity magnitude by analyzing the interrelation among wave steepness, wave run-up and relative velocity. The method used consists of applying numeric 3D flow model in the perforated structure of the breakwater with the variation of wave height, wave period and structure slope. The result shows that, the steeper the structure, the bigger is the relative run up (Ru/H). The higher the relative run up, the higher are the relative run-up velocities (V/Vru). As the velocity increase, the volumetric flow rate inside perforated breakwater will be higher, which leads to higher wave energy. Hence, it can be concluded that the higher the velocities (V/Vru), the higher is the wave energy generated.
Determination of Sliced Pineapple Drying Characteristics in A Closed Loop Heat Pump Assisted Drying System Cüneyt Tunçkal; Salih Coşkun; İbrahim Doymaz; Ernes Ergun
International Journal of Renewable Energy Development Vol 7, No 1 (2018): February 2018
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.7.1.35-41

Abstract

Pineapple (Ananascomosus) slices were dried with the aid of a heat pump assisted dryer (HPD). During this process, air velocity was kept constant at 1m/s, while air temperatures were changed as 37°C, 40°C and 43°C. The drying air was also circulated by using an axial fan in a closed cycle and fresh air was not allowed into the system. The drying rate and drying time were significantly influenced by drying temperature. It was observed that drying temperatures had significant effects on the drying rate and drying time. During the conduct of the study, pineapple slices were dried at 37, 40 and 43°C for 465, 360 and 290 min, respectively. The specific moisture extraction ratio (SMER) values were observed to change as drying temperatures were changed. The drying rate curves indicated that the whole drying process occurred in the falling rate period. Seven well-known thin-layer models (Lewis, Henderson &Pabis, Logarithmic, Page, Midilli & Kucuk, Weibull and Aghbashlo et al.) were employed to make a prediction about drying kinetics through nonlinear regression analysis. The Midilli & Kucuk and Aghbashlo et al. models were consistent with the experimental data. Fick’s second law of diffusion was used to determine the moisture diffusivity coefficient ranging from 3.78×10–9 to 6.57×10-9  m2/s the each of the above mentioned temperatures. The dependence of effective diffusivity coefficient on temperature was defined by means a fan Arrhenius type equation. The activation energy of moisture diffusion was found to be 75.24kJ/mol. Article History: Received: July 18th 2017; Received: October 27th 2017; Accepted: January 16th 2018; Available onlineHow to Cite This Article: Tunçkal, C., Coşkun, S., Doymaz, I. and Ergun, E. (2018) Determination of Sliced Pineapple Drying Characteristics in A Closed Loop Heat Pump Assisted Drying System. International Journal of Renewable Energy Development, 7(1), 35-41.https://doi.org/10.14710/ijred.7.1.35-41
Characterization of Lignocellulosic Biomass Samples in Omu-Aran Metropolis, Kwara State, Nigeria, as Potential Fuel for Pyrolysis Yields Anthony O Onokwai; Imhade P Okokpujie; Emmanuel S Ajisegiri; Makanjuola Oki; Adeyinka O Adeoyeb; Esther T Akinlabi
International Journal of Renewable Energy Development Vol 11, No 4 (2022): November 2022
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2022.45549

Abstract

This study deals with a preliminary investigation of biomass samples' physicochemical, structural composition, and thermal properties to aid the appropriate selection of biomass utilized for pyrolysis operation. The proximate, ultimate, structural composition and thermal analyses were conducted using seven lignocellulose biomass samples obtained in Ajase market, Ajasse Ipo, Kwara State, Nigeria, and Omu-Aran, Kwara State, Nigeria. Results showed that the average moisture contents (MC) ranged from 0.12 to 0.44%, and volatile matter (VM) ranged from 73.70 to 83.82%. Fixed carbon (FC) varied from 12.79 to 22.80%, and Ash contents varied between 01.20 to 5.52%. Similarly, the average carbon contents ranged from 45.11 to 50.00%. Hydrogen contents ranged from 5.38 to 6.15%, nitrogen contents varied between 0.20 to 1.24%, and oxygen contents from 43.79 to 48.51%. Also, sulphur contents varied between 0.01 to 0.19%, while the biomass species' average cellulose, hemicellulose, and lignin contents ranged from 28.34 to 45.80%, 25.83 to 34.01%, and 21.96 to 49.63% respectively. The high percentage of VM, C, H, HHV, ignitability index, cellulose, and hemicellulose content recorded in the biomass samples would enhance devolatilization reactivity, ignitability, and burn gases in the reactor, as well as a good production of hydrocarbons content during the pyrolysis process. Also, the low ash content would prevent harmful chemical deposits in the reactor during the pyrolysis process. It can be deduced that shea butter wood was best suited for biofuel generation, closely followed by sugarcane bagasse and palm kernel shell. At the same time, corn cobs possessed the least properties for the pyrolysis process.
Numerical and experimental investigations on a bladeless turbine: Tesla's cohesion-type innovation Malayathi Sivaramakrishnaiah; Dhanaraj Savary Nasan; Prabhakar Sharma; Thanh Tuan Le; Minh Ho Tran; Thi Bich Ngoc Nguyen; Phuoc Quy Phong Nguyen; Viet Dung Tran
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.2024.55455

Abstract

The design, numerical simulation, manufacturing, and physical experimentation of Tesla's bladeless centripetal turbine for electrical power production are the topics of this research project. The turbine generates rotational motion in the discs by directing pressurized air and water tangentially across parallel smooth disc surfaces. The fluid speed parameter at the nozzle inlet determines the power generated. To ensure optimal mechanical design parameters, SolidWorks design software, fluid dynamics concepts, and machine element design were employed. The numerical simulation software ANSYS CFX was used. The numerical and qualitative findings of the models and physical experiments coincided well. The study revealed that the power production and turbine efficiency were regulated by the input sources and blade size. Variations in the fluid composition between the discs may additionally have an impact on the outcomes. The researchers investigated the connection between input fluid pressure and turbine efficiency, as well as the number of discs and turbine power. The prototype could generate 76.52 W of electricity at 50 bar pressure and 1.01e+05 Reynolds number. The operation was efficiently simulated using CFD, with only a 9.3% difference between experimental and simulated results. Overall, this research provides an in-depth assessment of Tesla's bladeless centripetal turbine. It verifies the design and numerical simulation methodologies used, as well as identifies the essential aspects impacting turbine performance and efficiency. The findings contribute to a better understanding of the turbine's behavior and give ideas for improving its performance.
Biodiesel Production From the Microalgae Nannochloropsis by Microwave Using CaO and MgO Catalysts Herman Hindarso; Aylianawati Aylianawati; Martinus Edy Sianto
International Journal of Renewable Energy Development Vol 4, No 1 (2015): February 2015
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.4.1.72-76

Abstract

The needs of world petroleum are increased; in contrast, the fuel productions are getting decreased. Therefore, it has lead to the search for bio-fuel as an alternative energy. There are several different types of biofuel, such as biodiesel, ethanol, bioalcohol, and biogas. Biodiesel is typically made by chemically reacting lipids from a vegetable oil or animal fat with an alcohol producing fatty acid esters, such as methyl or ethyl ester. The present study aimed to study the effect of temperature (50, 60 and 65°C), reaction time (1 to 5 minutes) dan types of catalyst (CaO dan MgO of 1 and 3 %) in the production of biodiesel from microalgae by the transesterification process using microwave methods. It also studied the characteristics of biodiesel which had the greatest yield in the present study, i.e. flash point, cetane number, density, viscosity, and FAME. The greatest yield was 99.35% and obtained with combination of 3% MgO catalyst quantity at temperature of 60°C, in 3 minutes reaction time. At this process conditions, the biodiesel has a flash point of 122°C, cetane number of 55, density of  0.89, viscosity of 5 cP and FAME of 75.12 %.
Machine Learning Models Based on Random Forest Feature Selection and Bayesian Optimization for Predicting Daily Global Solar Radiation Mohamed Chaibi; El Mahjoub Benghoulam; Lhoussaine Tarik; Mohamed Berrada; Abdellah El Hmaidi
International Journal of Renewable Energy Development Vol 11, No 1 (2022): February 2022
Publisher : Center of Biomass & Renewable Energy, Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/ijred.2022.41451

Abstract

Prediction of daily global solar radiation  with simple and highly accurate models would be beneficial for solar energy conversion systems. In this paper, we proposed a hybrid machine learning methodology integrating two feature selection methods and a Bayesian optimization algorithm to predict H in the city of Fez, Morocco. First, we identified the most significant predictors using two Random Forest methods of feature importance: Mean Decrease in Impurity (MDI) and Mean Decrease in Accuracy (MDA). Then, based on the feature selection results, ten models were developed and compared: (1) five standalone machine learning (ML) models including Classification and Regression Trees (CART), Random Forests (RF), Bagged Trees Regression (BTR), Support Vector Regression (SVR), and Multi-Layer Perceptron (MLP); and (2) the same models tuned by the Bayesian optimization (BO) algorithm: CART-BO, RF-BO, BTR-BO, SVR-BO, and MLP-BO. Both MDI and MDA techniques revealed that extraterrestrial solar radiation and sunshine duration fraction were the most influential features. The BO approach improved the predictive accuracy of MLP, CART, SVR, and BTR models and prevented the CART model from overfitting. The best improvements were obtained using the MLP model, where RMSE and MAE were reduced by 17.6% and 17.2%, respectively. Among the studied models, the SVR-BO algorithm provided the best trade-off between prediction accuracy (RMSE=0.4473kWh/m²/day, MAE=0.3381kWh/m²/day, and R²=0.9465), stability (with a 0.0033kWh/m²/day increase in RMSE), and computational cost.

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