Clean and environment-friendly energy harvesting are of prime interest today as it is one of the key enablers in achieving the Sustainable Development Goals (SDGs) as well as accelerates social progress and enhances living standards. India, the second-most populous nation with a population of 1.353 billion, is one of the largest consumers of fossil fuels in the world which is responsible for global warming. An everincreasing population is projected until 2050, and consequently, the energy demand in the upcoming decades will be co-accelerated by the rapid industrial growth. The Ministry of New and Renewable Energy (MNRE) with the support of National Institution for Transforming India (NITI) Aayog is working to achieve the Indian Government's target of attaining 175 GW through renewable energy resources. Many Indian states are currently increasing their renewable energy capacity in an objective to meet future energy demand. The review paper discusses in-depth about the three Indian states, namely Karnataka, Gujarat, Tamil Nadu, which pioneers the renewable energy production in India. The global energy scenario was discussed in detail with Indian contrast. Further, the barriers to the development of renewable energy generation and policies of the Indian government are discussed in detail to promote renewable energy generation throughout India as well as globally since the challenges are similar for other nations. This study analyzed various prospects of the country in renewable energy which has been done in a purpose to help the scholars, researchers, and policymakers of the nation, as it gives an insight into the present renewable energy scenario of the country. INDEX TERMS Renewable energy potential, global energy scenario, Energy policy in India, renewable energy barriers, prospects of renewables in India, renewable energy in India.

No abstract

epidemic outbreak has devastating effects on daily lives and healthcare systems worldwide. This newly recognized virus is highly transmissible, and no clinically approved vaccine or antiviral medicine is currently available. Early diagnosis of infected patients through effective screening is needed to control the rapid spread of this virus. Chest radiography imaging is an effective diagnosis tool for COVID-19 virus and followup. Here, a novel hybrid multimodal deep learning system for identifying COVID-19 virus in chest X-ray (CX-R) images is developed and termed as the COVID-DeepNet system to aid expert radiologists in rapid and accurate image interpretation. First, Contrast-Limited Adaptive Histogram Equalization (CLAHE) and Butterworth bandpass filter were applied to enhance the contrast and eliminate the noise in CX-R images, respectively. Results from two different deep learning approaches based on the incorporation of a deep belief network and a convolutional deep belief network trained from scratch using a large-scale dataset were then fused. Parallel architecture, which provides radiologists a high degree of confidence to distinguish healthy and COVID-19 infected people, was considered. The proposed COVID-DeepNet system can correctly and accurately diagnose patients with COVID-19 with a detection accuracy rate of 99.93%, sensitivity of 99.90%, specificity of 100%, precision of 100%, F1-score of 99.93%, MSE of 0.021%, and RMSE of 0.016% in a large-scale dataset. This system shows efficiency and accuracy and

Energy, being a prime enabler in achieving sustainable development goals (SDGs), should be affordable, reliable, sustainable, and modern. One of the SDGs (i.e., SDG7) suggests that it is necessary to ensure energy access for all. In developing countries like India, the progress toward SDG7 has somewhat stagnated. The aging conventional electric power system has its dominant share of energy from fossil fuels, plagued with frequent power outages, and leaves many un-electrified areas. These are not characteristics of a sustainable and modern system in the context of the SDG7. Promoting renewable-based energy systems, especially in the context of microgrids (MGs), is one of the promising advances needed to rejuvenate the progress toward the SDG7. In this context, a hybrid renewable energy microgrid (HREM) is proposed that gives assurance for energy access to all in an affordable, reliable, and sustainable way through modern energy systems. In this paper, a techno-economic and environmental modeling of the grid-independent HREM and its optimization for a remote community in South India are presented. A case of HREM with a proposed configuration of photovoltaic/wind turbine/diesel generator/battery energy storage system (PV/WT/DG/BESS) was modeled to meet the community residential electric load requirements. This investigation dealt with the optimum sizes of the different components used in the HREM. The results of this model presented numerous feasible solutions. Sensitivity analysis was conducted to identify the best solution from the four optimized results. From the results, it was established that a PV + DG + BESS based HREM was the most cost-effective configuration for the specific location. In addition, the obtained optimum solutions were mapped with the key criteria of the SDG7. This mapping also suggested that the PV + DG + BESS configuration falls within the context of the SDG7. Overall, it is understood that the proposed HREM would provide energy access to households that is affordable, reliable, sustainable, and modern.

No abstract

No abstract

No abstract

No abstract