ISSN 2319-5347, ISI Impact Factor: 0.763

VOLUME 03 NO. 03 JULY 2015

Title:      Thermal efficiency improvement of Biomass for electricity generation by using Information Technology and Numerical methods
Authors:      Ranipet Hafeez BASHA, Shuichi TORII
Abstract:   Thermal energy based power generation is significant in most of the countries, but due to the depletion of fossil fuels there is a serious threat to its fuel supplies. Biomass has proved to be alternative fuel to coal with benefits of being renewable and sustainable source of energy. But the efficiency of such plants is significantly low because of lower thermal performance of biomass. Producing advanced material, increasing its calorie and reducing carbon emissions are the objectives of this research. Pre-treatment methods based on chemical, bio-chemical and thermo-chemical process can increase the performance of the fuel, but it requires initial supply of energy. The use of information technology and numerical methods in developing the renewable fuel by achieving the above objectives is the novelty of this study. Biomass is combination of multiple waste materials where alteration in its ratio can change its heat of combustion. The user interface based computer simulator with enhanced feature of predicting optimum composition of Biomass was developed in our laboratory using J2SE 5.0 program. Refuse Derived Fuel type biomass sample was simulated to get numerical results which were tested and validated with physical experiment where the values were equivalent. Combinatory optimization methods along with probability and permutations & combinations were used in the design of this software. Artificial Neural Networks and Genetic Algorithms based methods can be applied to reduce the computational time and increase the efficiency of simulator. Hence the use of information technology and numerical methods along with pre-processing methods of biomass together would improve the thermal efficiency of Biomass power plant to generate clean electricity.

Keywords:   Biomass, Combustion, Database, Computer Model, Numerical Simulation, Predictor
Pages:         205-208

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