Abstract
In the entrained flow coal gasification process, the gas production is critically affected by the operating temperature (OT) and coal ash melting point (AMP), and the AMP is one of key factors for the determinations of OT. Considering the fact that coal is a typical nonhomogeneous substance and the coal ash composition varies from batch to batch, this paper proposes the application of the Markov Chain (MC) method in simulation of the random AMP series and the stochastic optimization of OT based on MC simulation for entrained flow coal gasification. The purpose of this paper is to provide a more accurate optimal OT decision method for entrained flow coal gasification practice. In this paper, the AMP was regarded as a random variable, and the random process method, Markov Chain, was used to describe the random AMP series of feed coal. Firstly, the MC simulation model about AMP was founded according to an actual sample data, 200 sets of AMP data from an industrial gasification plant under three simulation schemes (the sample data were individually divided into 16, eight and four state groups,). The comparisons between the simulation results and the actual values show that the founded MC simulation model descries the AMP series very well. Then, a stochastic programming model based on MC simulation for OT optimization was developed. Finally, this stochastic programming optimization model was optimized by genetic algorithm (GA). Comparing with the conventional OT optimization method, the proposed stochastic OT optimization model integrated MC simulation can ascertain a more accurate OT for guiding the coal gasification practice.
Highlights
Coal is the most wildly used natural energy resource with the largest reserves
The determined operating temperature (OT) with this method is usually inaccurate because the dynamic changes in ash melting point (AMP) series are neglected
Based on a stochastic process perspective, this paper focuses on the random simulation of AMP of feed coal for an entrained flow coal gasification process and the stochastic optimization of OT so as to provide more precise operational guidance for gasification operations
Summary
Coal is the most wildly used natural energy resource with the largest reserves. Compared with other energy sources, the utilization of coal has attracted wider attention in view of the advantages of wide distribution and easy exploitation of coal. The increasing environmental and health concerns in utilization of coal promote the emergence of clean coal technologies [1,2,3,4]. Among the clean coal technologies, coal gasification is regard as a promising utilization of coal because of its low technology cost and high conversion rate [5]. In the coal gasification practice, the basic equipment can be grouped into three main categories: fixed bed gasifiers, fluidized bed gasifiers and entrained flow gasifiers [6,7]. Differ from fixed bed and fluidized bed gasification, entrained flow gasification
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