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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 15 Documents
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Search results for , issue "Vol 12, No 5 (2023): September 2023" : 15 Documents clear
Exploring the link between green energy, CO2 emissions, exchange rate and economic growth: Perspective from emerging South Asian countries Mohammad Rifat Rahman; Md. Mufidur Rahman; Roksana Akter
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.2023.53168

Abstract

This paper investigates the nexus between renewable energy use, CO2 emissions, exchange rate, and economic development within emerging South Asian nations, namely Bangladesh, India, Pakistan, and Sri Lanka, employing the Autoregressive Distributed Lag (ARDL) framework. It examines annual data spanning from 1990 to 2019, examining key indicators of renewable energy consumption, CO2 emissions, exchange rate, and economic development. The ARDL bounds test results demonstrate the existence of co-integration among the variables in the long run. The empirical result finds that the renewable energy consumption, CO2 emissions, and exchange rate have a significant impact on economic growth in Bangladesh, Pakistan, and Sri Lanka in the long run. In India no significant relationship found in the long run. In short run assessment, Bangladesh, India, and Sri Lanka also found same relationship with economic growth and renewable energy consumption, CO2 emissions, and exchange rate. Interestingly, In Pakistan no significant relationship has found in short run estimation analysis. Furthermore, study tried to determine the causality direction by using the Toda Yamamoto granger causality approach, which reveals bidirectional causation between exchange rate and CO2 emission in India. In Pakistan, study also found  bi-directional causality among the variables renewable energy consumption, CO2 emissions, and economic growth. Finally, this paper emphasizes developing the policy as well as making a concrete decision regarding the renewable energy consumption, CO2 emissions, exchange rate, and economic development for ensuring sustainable economic growth in South Asian region. Future research could extend this work by including different dimensional data, additional countries, or using alternative or supplementary modeling techniques.
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
Solid waste management by RDF production from landfilled waste to renewable fuel of Nonthaburi Udorn Rahotharn; Maneerat Khemkhao; Prangtip Rittichote Kaewpengkrow
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.2023.52956

Abstract

A worldwide increase in waste production and energy demand as the world's population grows and consumes more resources: therefore, sustainable waste management strategies are important. The goal of this work is to research the guidelines for the appropriate RDF production and landfill waste management of the Nonthaburi province, Thailand. Refuse Derived Fuel (RDF) produced from landfilled Waste (LW) in Nonthaburi was investigated the physicochemical. The following procedure has implemented for the production of LW to RDF of 25 tons/hr of LW; (i) the LW was placed in a pre-shredder, which was followed by a primary crusher; (ii) metals were removed from the waste stream using a magnetic separator; (iii) the LW was transferred using a conveyor belt to a dynamic disc screen, where recyclable waste was separated into smaller sizes less than 80 mm.; (iv) the waste passed through an air separator to reject high-density materials (soil and glass); (v) the undesired material were separated manually, and (vi) the desired material were baled. RDF composition consisted of 78.16-67.93% plastics, 2.29 -4.34% rubber, 1.27% wood, 1.53-2.19 % textile, and other (soil-like material) 12.19-26.72%. The proximate and elemental analysis of RDF was determined according to the ASTM method. The moisture content was reduced, and the heating value increased to 18.08-29.41 MJ/kg. The results suggested high carbon and low nitrogen content suitable for energy conversion. The separation can effectively convert LW to RDF, which can be applied as an alternative fuel. Therefore, RDF can contribute to a more sustainable and circular economy.
Performance characterization of a novel PV/T panel with nanofluids under the climatic conditions of Muscat, Oman Afzal Husain; Nabeel Z. Al-Rawahi; Nasser A. Al-Azri; Mohammed Al-Naabi; Musaab El-Tahir
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.2023.53287

Abstract

The study presents an experimental analysis of a novel mini channels-based Photovoltaic/Thermal (PV/T) panel with nanofluid flow. The design consists of a PV plate attached to an aluminum substrate absorber plate having minichannels grooved on it to act as a solar collector and cooling mechanism for PV. The proposed design was tested for thermal and electrical efficiencies under the working fluids of water, Al2O3, and SiO2 nanofluids at 0.1% and 0.2% concentrations in water and at a flow rate of 0.005 l/s to 0.045 l/s. The experiments were carried out outdoors in a real environment and the measurements were taken for PV surface and fluid temperatures, incidence solar flux, electrical voltage, and current produced. The PV and PV/T performance was compared, and a noticeable enhancement in electrical efficiency was observed with the proposed design as compared to the bare PV module, and an appreciable augmentation in thermal efficiency was noticed when nanofluids were applied. The maximum electrical and thermal efficiencies of PV/T with 0.2% Al2O3 nanofluid were 19.1% and 73.4%, respectively; whereas for bare PV panels, the electrical efficiency was 18.7%. The Al2O3 nanofluid at 0.2% exhibited more than a 10% increase in thermal efficiency compared to water as a working fluid in PV/T.
Evaluating the EEMD-LSTM model for short-term forecasting of industrial power load: A case study in Vietnam Nam Nguyen Vuu Nhat; Duc Nguyen Huu; Thu Nguyen Thi Hoai
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.2023.55078

Abstract

This paper presents the effectiveness of the ensemble empirical mode decomposition-long short-term memory (EEMD-LSTM) model for short term load prediction. The prediction performance of the proposed model is compared to that of three other models (LR, ANN, LSTM). The contribution of this research lay in developing a novel approach that combined the EEMD-LSTM model to enhance the capability of industrial load forecasting. This was a field where there had been limited proposals for improvement, as these hybrid models had primarily been developed for other industries such as solar power, wind power, CO2 emissions, and had not been widely applied in industrial load forecasting before. First, the raw data was preprocessed using the IQR method, serving as the input for all four models. Second, the processed data was then used to train the four models. The performance of each model was evaluated using regression-based metrics such as mean absolute error (MAE) and mean squared error (MSE) to assess their respective output. The effectiveness of the EEMD-LSTM model was evaluated using Seojin industrial load data in Vietnam, and the results showed that it outperformed other models in terms of RMSE, n-RMSE, and MAPE errors for both 1-step and 24-step forecasting. This highlighted the model's capability to capture intricate and nonlinear patterns in electricity load data. The study underscored the significance of selecting a suitable model for electricity load forecasting and concluded that the EEMD-LSTM model was a dependable and precise approach for predicting future electricity assets. The model's robust performance and accurate forecasts showcased its potential in assisting decision-making processes in the energy sector.

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