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Co-pyrolysis of lignocellulosic biomass and coal is considered as an effective way to reduce the carbon footprint. Bamboo is being a potential source of bioenergy particularly in the North East States of India; the thermal performance and synergetic behaviour of co-pyrolysis of bamboo with high ash Indian coal are investigated at various heating rates in a thermogravimetric analyser. Three different blend samples (25% bamboo with 75% coal, 50% bamboo with 50% coal and 75% bamboo with 25% coal) are used. The kinetic parameters are determined using three isoconversional methods: Friedman, Ozawa-Flynn-Wall and Kissinger–Akahira–Sunose. Average activation energy for all three blend samples is found in the range of 121–253 kJ/mol. Co-pyrolysis of all three blend samples have revealed some synergistic effect. However, the blend containing 25% of bamboo has shown the highest synergetic effect in terms of thermodynamic parameters. [ABSTRACT FROM AUTHOR]

In India's Northeast region, only 23.5% of rural households are connected with electricity. To date, only 3 kW comes from biomass gasification in this region. However, this region has plenty of biomass resources. Therefore, electricity generation from locally available biomass through the thermochemical gasification process may be viable in this region where grid-connectivity is not available. This paper presents a techno-economic analysis of biomass gasification for power generation in NE India. An attempt is made to find out the most economical process by comparing different systems, and it is observed that the downdraft gasifier connected with a 100% producer gas engine or dual-fuel engine could be the best option from the economic point of view. Downdraft gasifier connected with 100% producer gas engine with a capacity of 500 kW and 1000 kW can give the Levelized unit cost of electricity (LUCE) as low as $0.05/kWh, which is lower than the existing tariff in NE India comes from hydro- and gas power plants. [ABSTRACT FROM AUTHOR]

India is blessed with plenty of bamboo biomass resources. Particularly, in the north-east states of India, bamboo has the potential to supply the local energy need. In order to explore the feasibility of energy generation from these biomass materials, the first and the foremost thing is to know their higher heating values (HHVs). The artificial neural network (ANN) technique is used to predict the higher heating values of bamboo biomass. Three ANN models are developed based on input data from proximate analysis, ultimate analysis, and combined proximate-ultimate analysis. The prediction accuracies of these models are analyzed by comparing with the experimental data graphically and statistically. It is illustrated that ANN models could able to predict the HHV of biomass with reasonably high accuracy. Performance of the ANN models are also judge by comparing with the correlation-based models and found that all ANN models could able to predict the actual HHVs better than correlation-based models and the ANN model based on combined proximate-ultimate analysis gives the best accuracy with an average error of 2.49%. [ABSTRACT FROM AUTHOR]

Lignocellulosic biomass is carbon neutral and produces fuels and chemicals which are used for domestic, industrial, and transportation system. Thermochemical conversion processes (combustion, gasification, and pyrolysis) are emerging technologies which have great potential for industrial implementation. In this paper, the investigation has been done to select appropriate bamboo biomass suitable for thermochemical conversion process out of 21 biomass samples available in Mizoram, India. Various characteristics considered here for the selection of the appropriate bamboo biomass include proximate analysis, ultimate analysis, and their heating values. These characteristics are plotted in different diagrams and analysed in detail. It is observed after analysis that some bamboo biomasses are suitable combustion, some are suitable for pyrolysis and rest are suitable for gasification. [ABSTRACT FROM AUTHOR]