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Abstract The combination of biomass gasification with fuel cells, especially high temperature Solid Oxide Fuel Cells (SOFCs) promises sustainable and highly efficient (decentralized and modular) energy conversion systems. This review encompasses the components of biomass integrated gasification–SOFC technology including biomass characteristics, the thermochemical conversion in gasifiers and the factors affecting the gasification process, the cleaning technologies for raw producer gas and its conditioning and finally the integration of gasifier with SOFCs. The influence of impurities present in biomass producer gas such as particulates, tar, H 2 S, HCl and alkali compounds based on recent experimental studies and their tolerance limits towards SOFCs are presented. Even though analysis based on the probable tolerance limits of impurities towards SOFCs and a comprehensive overview of the cleaning technologies for producer gas impurities indicate that producer gas cleaning at various temperatures using current technologies to meet SOFC requirements is possible, more experimental studies are still needed to acquire the detailed information on the tolerance limits of impurities for SOFCs. The recent theoretical modeling and experimental studies of biomass integrated gasification–SOFC systems are also presented.

Renewable energy has become more popular since it is cost-effective and more efficient than conventional energy sources. Biomass-based renewable energy is primarily used in emerging economies to ensure environmental sustainability. This study examines the asymmetric correlation between biomass energy consumption and CO2 emissions in the top-10 biomass energy consumer countries (Brazil, Canada, Thailand, China, Italy, India, Germany, USA, UK, and Japan). A new approach "Quantile-onQuantile (QQ)" is employed by utilizing the data from 1991 to 2018. Biomass energy consumption, with the exception of Thailand, significantly mitigates CO2 emissions at various quantiles in selected countries. As a robustness check, we used the quantile regression test, whose findings are consistent with the outcomes from the quantile-on-quantile method. However, the degree of asymmetry in the biomass energy-CO2 nexus varies by country, necessitating extra attention and government vigilance when developing biomass energy and environmental policies.

Abstract Hydrogen is considered a potential game changer for world energy systems and a solution to climate change concerns, as it generates zero waste and it is suited for power generation and transportation. Despite its several advantages, there are significant technical challenges in deploying a stable hydrogen economy including improving its process efficiencies, lowering production costs, maintaining cost-effective transmission and distribution, and exploiting inexpensive and sustainable feedstocks. In this context, a detailed study was conducted to analyze the production sources, technologies, storage and transport systems, and global potential exportable feedstocks to produce hydrogen. A comprehensive analysis of current hydrogen production technologies with their energy efficiencies and hydrogen selling prices was reported in this study. Various hydrogen production technologies with their capital investments and CO2 emissions were also presented. Potential feedstocks for hydrogen production were identified and analyzed through a product space model, which characterizes a network of global exportable products based on their similarities and productive knowledge. It was established that the hydrogen production feedstocks and sources currently used are primarily available in six countries: the United States of America, France, Russia, Sweden, the Netherlands, and Spain. Broadly, the results revealed that the United States of America and Russia shared the highest hydrogen feedstock exports, indicating a higher probability of hydrogen production in these countries. Except for Russia, all the studied countries fell in the most desired quadrant, indicating that they can move in all product space directions to exploit unexplored hydrogen feedstocks for better sustainable economic growth.

Abstract This paper presents a conceptual study of a solar PV integrated refrigeration system for a cold storage facility based on the conventional vapor compression system for banana fruit. In the first stage, the conventional system has been thoroughly analyzed. Mathematical modelling has shown that the condenser is oversized, while the evaporator was undersized. Furthermore, the air-conditioning compressor was also found to be oversized by approximately 12 kW after an evaluation at no-load and full-load conditions. In the second stage, the optimized system with reduced consumption was integrated to a solar PV field. The solar field sizing, and performance optimization of the proposed PV hybrid refrigeration system was accomplished in PV*SOL tool. The simulations demonstrated that with a 170 m2 solar field, an optimized PV hybrid refrigeration system can achieve 58.1% solar fraction at a performance ratio of 59.2%, under given climatic conditions. With net metering, the hybrid system shows a high economic feasibility with the payback period of 5.2 years. The comprehensive methodology and all-inclusive results are valuable to generate explicit recommendations for repowering along with renewable integration of cold storage facilities operating in the region.

SUMMARY This paper analyses the transportation and delivery features of hydrogen as energy market evolves and approaches a fully functional Hydrogen economy. Initially physical aspects have been assessed that affect the flow of hydrogen through the existing pipeline infrastructure. Line pack and compressors are the only identified problems that need to be addressed. This is followed by an investigation into the mixing of hydrogen with natural gas gradually. It was revealed that a mix of up to 17% by volume does not have any significant effect, however higher concentration of hydrogen leads to a changeover of high-pressure grid pipelines as well as the end-user applications. It is suggested that initially hydrogen can be introduced in the distribution system, while emphasizing towards developing means for high-pressure transportation of hydrogen fuel gas. Government policies towards encouraging use of hydrogen in an evolving market is important for widespread and early assimilation in energy mix. Renewable sources of energy are recommended for distributed generation of hydrogen along the pipeline network. Copyright © 2011 John Wiley & Sons, Ltd.

Abstract Theft of electricity is a problem in many developing countries. But AMI is paving the way for data-centric architecture to help in theft detection. However, a smart grid or even AMR is a long shot for many developing countries due to the costs involved in its large-scale deployment. This paper presents a technique to detect outliers among electricity users that further investigates electricity theft using data analytics on monthly usage data available to every utility company. Using this technique, we have reduced the search space for theft identification to as low as 3.4% of the total customer base.

Abstract In this paper, a hybrid features based support vector machine (SVM) model is proposed using infrared thermography technique for hotspots detection and classification of photovoltaic (PV) panels. A novel hybrid feature vector consisting of RGB, texture, the histogram of oriented gradient (HOG), and local binary pattern (LBP) as features is formed using a data fusion approach. A machine learning algorithm SVM is employed to classify the obtained thermal images of PV panels into three different classes (i.e., healthy, non-faulty hotspot, and faulty). The comparison of different machine learning algorithms and datasets is also carried out to validate the superiority of the proposed model and hybrid feature dataset. The experimental results reveal that the proposed hybrid features with SVM resulted in 96.8% training accuracy and 92% testing accuracy with lesser computational complexity and storage space than other machine learning algorithms. The proposed approach is easily implementable for efficient monitoring and fault diagnosis of PV panels.

Here we investigate the irreversibility aspects in magnetohydrodynamics flow of viscous nanofluid by a variable thicked surface. Viscous dissipation, Joule heating and heat generation/absorption in energy expression is considered. Behavior of Brownian diffusion and thermophoresis are also discussed. The nanoliquid is considered electrical conducting under the behavior of magnetic field exerted transverse to the sheet. Using similarity variables the nonlinear PDEs are altered to ordinary one. The obtained system are computed through Newton built in shooting method. Significant behavior of various involving parameters on entropy generation rate, velocity, concentration, Bejan number and temperature are examined. Gradient of velocity and heat transfer rate are numerically computed through tabulated form. Velocity field is augmented versus power index (n). Temperature and velocity profiles have opposite characteristics for larger approximation of Hartmann number. Concentration profile has similar impact against Brownian diffusion variable and Lewis number. Entropy optimization is boost up via rising values of Brinkman and Hartmann numbers. Bejan number is declined for increasing value of Hartmann number.