Abstract
This chapter reviews the application of multiobjective Gray Wolf Optimization in gasification-based problems. To fulfill this aim, designing a conventional waste-to-energy plant (WtEP) as well as simulating biomass gasification in a gasifier are considered. The redesigned system is evaluated and compared to the traditional WtEP and then, it is optimized to extract Pareto frontiers to provide a tradeoff among the objective functions. The optimization results indicate that the proposed WtEP has lower levels of CO2 emissions than the conventional system, while its net power output is higher. Also, total specific cost for the optimum solution improves as well, while the payback period of the proposed system is reduced. In addition, a parametric study is performed to investigate the effects of the main parameters on the performance criteria of the gasifier. Maximization of the cold gas and exergy efficiencies and minimizing CO2 emissions are the main purposes of this problem. The solutions are obtained for a wide range of feedstocks and gasification agents by employing the Linear Programming Technique for Multidimensional Analysis of Preference (LINMAP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. The exergy efficiency of biomass gasification using a suitable feedstock in the medium of steam and CO2 is presented.
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