As India's population grows and urbanization accelerates, energy demand is increasing sharply while conventional sources fall behind. To tackle energy shortages and climate change, India must prioritize renewable energy sources (RES), which offer sustainable solutions. The country is rich in RES, which can enhance fuel mix for electricity generation. This study analyzes various RES in India-solar, geothermal, hydro, biomass, wave, onshore, and offshore wind energy -using an integrated data envelopment analysis (DEA) and fuzzy analytic hierarchy process (Fuzzy AHP) methodology. Four main parameters-technical, economic, environmental, and socio-political -are identified and supported by 19 criteria, with environmental parameters including both desirable and undesirable criteria. In first phase, undesirable criteria are transformed into desirable criteria using Modified Ratio model. DEA is then applied to calculate initial efficiency score of RES under each parameter category. Fuzzy AHP determines weights for each parameter. The weights and initial efficiency scores are then combined to calculate overall efficiency score and ranking of RES. Sensitivity analysis shows that results obtained from proposed methodology are significant, and robust. Offshore wind ranks highest in efficiency, followed by hydro and onshore wind, while geothermal scores lowest. This methodology could benefit developing nations and guide policymakers in adopting RES.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1038/s41598-024-84891-2 | DOI Listing |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11700135 | PMC |
Environ Sci Pollut Res Int
January 2025
Department of Physics, Faculty of Science, King Abdulaziz University, 21589, Jeddah, Saudi Arabia.
A sustainable biosorbent, silver nanoparticles-decorated coffee-ground waste (CWAg), was synthesized through a simple in-situ reduction method. CWAg is extensively characterized via SEM-EDX, PZC, FTIR, XRD, HR-TEM, and XPS analyses. The biosorbent was tested to remove chromium (Cr(VI)) and methylene blue (MB) from wastewater, and its antibacterial properties was evaluated.
View Article and Find Full Text PDFNat Mater
January 2025
Department of Mechanical Engineering, The Pennsylvania State University, University Park, PA, USA.
Lithium-sulfur (Li-S) all-solid-state batteries (ASSBs) hold great promise for next-generation safe, durable and energy-dense battery technology. However, solid-state sulfur conversion reactions are kinetically sluggish and primarily constrained to the restricted three-phase boundary area of sulfur, carbon and solid electrolytes, making it challenging to achieve high sulfur utilization. Here we develop and implement mixed ionic-electronic conductors (MIECs) in sulfur cathodes to replace conventional solid electrolytes and invoke conversion reactions at sulfur-MIEC interfaces in addition to traditional three-phase boundaries.
View Article and Find Full Text PDFSci Rep
January 2025
Young Researchers and Elite Club, Omidiyeh Branch, Islamic Azad University, Omidiyeh, Iran.
Accurate estimation of interfacial tension (IFT) between nitrogen and crude oil during nitrogen-based gas injection into oil reservoirs is imperative. The previous research works dealing with prediction of IFT of oil and nitrogen systems consider synthetic oil samples such n-alkanes. In this work, we aim to utilize eight machine learning methods of Decision Tree (DT), AdaBoost (AB), Random Forest (RF), K-nearest Neighbors (KNN), Ensemble Learning (EL), Support Vector Machine (SVM), Convolutional Neural Network (CNN) and Multilayer Perceptron Artificial Neural Network (MLP-ANN) to construct data-driven intelligent models to predict crude oil - nitrogen IFT based upon experimental data of real crude oils samples encountered in underground oil reservoirs.
View Article and Find Full Text PDFSci Rep
January 2025
Electrical Power and Machines Engineering Department, Faculty of Engineering, Helwan University, Cairo, Egypt.
To improve the inadequate reliability of the grid that has led to a worsening energy crisis and environmental issues, comprehensive research on new clean renewable energy and efficient, cost-effective, and eco-friendly energy management technologies is essential. This requires the creation of advanced energy management systems to enhance system reliability and optimize efficiency. Demand-side energy management systems are a superior solution for multiple reasons.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Information Systems, College of Computing and Informatics, The University of Sharjah, Sharjah, UAE.
This study explores the integration of nanotechnology and Long Short-Term Memory (LSTM) machine learning algorithms to enhance the understanding and optimization of fuel spray dynamics in compression ignition (CI) engines with varying bowl geometries. The incorporation of nanotechnology, through the addition of nanoparticles to conventional fuels, improves fuel atomization, combustion efficiency, and emission control. Simultaneously, LSTM models are employed to analyze and predict the complex spray behavior under diverse operational and geometric conditions.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!