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Biomass in its original form with low bulk density causes large transport and storage costs, and therefore, it cannot be used as an effective combustion fuel. Densification of biomass using briquetting technology can resolve the aforementioned issues and enhance the effectiveness of biomass as a combustible fuel. The relevance of using this fuel in thermal conversion processes is growing because it is abundant and under-explored. Hence, examining the fuel characteristics of these resource materials is imperative for their effective utilization in energy generation. The aim of the present work is to assess the suitability of various agricultural and aquatic residues as sources of briquette production by determining their fuel properties. Sixteen types of agricultural and aquatic residues which are abundantly available in Kerala (southwestern coastal state of India) were selected for this investigation. The fuel properties of the selected feedstock materials were determined using proximate analysis, elemental analysis, and heating value testing. The density, moisture content, volatile matter content, ash content percentage, and fixed carbon percentage of the feedstock material were carried out according to different ISO standards. Furthermore, the elemental analysis and the heating value of all the feedstock materials have been determined. Finally, the paper concludes by comprehensively listing all the fuel properties of the feedstock materials investigated in this study. The density of the feedstock materials ranged from 105.92 to 700.10 kg/m3. The fuel properties showed that Water hyacinth leaves, oil palm fruit bunch, saw dust; grass waste, dry leaves, vegetable market waste, and spent tea waste have significant potential for bio-briquette production. Also, from the characterization of the feedstock material, it is evident that rice husk and banana peel have higher ash content (above 20 %). Therefore, they are not appropriate for the production of biomass briquettes. The fuel properties of various agro aquatic residues for briquette production obtained from this study are expected to be of great use to the manufacturers in the briquetting of these feedstock materials. [ABSTRACT FROM AUTHOR]

With the increasing demand for energy worldwide, it has become imperative to explore and adopt sustainable energy practices. In this regard, predicting household electricity consumption accurately is essential, as it can help optimize energy usage and reduce waste. This paper focuses on using Long Short-Term Memory (LSTM) shows the neural networks to prevent household electricity consumption in India. The LSTM model was implemented using the Keras library in Python. The model was trained using the training set and tested using the testing set. The study demonstrated that LSTM neural networks are a promising approach to predicting household electricity consumption in India. Further research can be conducted to recover the accuracy of the perfect by including more variables such as household size, income, and appliance usage. [ABSTRACT FROM AUTHOR]

Due to the growth in gross domestic product (GDP) of the country, there is an improvement in the quality of life of an individual. And the economic status of a country also depends on the amount of electrical energy consumed. So, the requirement for energy sources is also increasing day to day to meet their high energy demand. The conventional sources of energy like coal, natural gas, petroleum products etc. are depleting and at the same time they are hazardous to environment. Hence renewable sources of energy are integrated into the grid on a large scale. For optimal utilization of resources and efficient operation of the system and also to provide end consumer reliably, smart grid has been proposed to be implemented. So, in this paper various initiatives take by the government in planning, implementing and monitoring the smart grids are presented. Different implementation challenges and their possible challenges are also proposed. So, the steps taken by the government of India and governing bodies established to monitor the smart grid initiatives are providing a favorable condition. But the identified challenges are also to be considered for its effective implementation. [ABSTRACT FROM AUTHOR]