kalyan sen
Prof Emeritus, Bengal Engineering & Science University, Shibpur
Director, Central Coalfields Ltd
Former Director, Central Fuel Research Institute and Central Mining Research Institute, Dhanbad.
Former Chairman, Bureau of Indian Standard (Coal & Coke)
9th International Summit & Expo
POWER INDIA 2007, 25-27 October 2007, Mumbai, India.
Introduction
The production of coal production in India, the majority of which will be in the non coking coal category, is likely to triple in the next decade with the power utilities as the largest consumer followed by the steelmaking and cement industries. Most of the thermal power plants burn coal without any up gradation of the coal quality, neither by blending nor washing, in spite of the acknowledged fact that quality enhancement leads to significant improvement of the different sub-processes involved in the entire ‘mine-to-energy’ chain. Coal cleaning becomes one of the important action areas identified for conventional power generation for achieving reduction in CO2 emission/kWh of electricity produced.
One of the barriers that have constrained the desired expansion of the coal cleaning processes and their integration with the coal utilization industries is the uncertainty associated with the economic impact on the industrial processes. To transform from a qualitative understanding of the effect of the coal quality parameters to a quantitative domain an approach towards the development of an economic model considering the several factors involved throughout the mine-energy’ chain is a necessary prerequisite. Some of the relevant factors which need to be considered are cost of coal, logistics, beneficiation technology, efficiency improvement and environmental benefits. Coal producers, power plant operators and regulatory authorities should work together to justify the model.
Approach
What is Coal Preparation?
Raw coal is a heterogeneous substance. When we talk about a coal to have such and such property, we understand that it is its average property of all the discrete particles. In fact, the property of individual particles can vary widely e.g. ash content of individual particles can vary from 2 to 80% while the algebraic average may be 34%. It is known that any down stream chemical process like combustion or carbonization depends on the reactivity of individual particles, not mainly on its average value. In fact, preparation of coal endeavors to reduce the variability and thereby improving the homogeneity by discarding the stones and other obvious dirts.
Thus, it is the need for the consumer to know not only the average ash content and other average properties like V.M, F.C, etc. of the different particles but also to appreciate their permissible variability, so as to design the down stream processes more effectively and optimally. Even if two raw coals can have equal average ash content, the distribution of the individual ash content of different particles can vary widely depending upon the homogeneity of the systems.
I think the onus is both on the suppliers and utilizers of coal to understand the variability in the system and coal producers and washery operators should use well proven procedures to reduce the variability.
Coal beneficiation is definitely the preferred option over blending. Due to the wide heterogeneity of Indian non coking coals, there cannot be a single scheme for beneficiation of thermal coals having varying washability / heterogeneity characteristics. There are many technological options for thermal coal beneficiation depending on the quality requirement of the end users. The entire chain from raw material to value added product involves different activities and improvement of the overall efficiency of the process is critically dependent on the improved performance of the individual sub-processes.
For coal preparation, the different stages are generation of authentic washability data from a representative portion of sample, data validation, simulation, and identification of optimum parameters for plant run, implementation of optimum control strategy in actual plant run to meet the expected quantity and quality of the products.
Based on the washability data of the coals of different regions followed by computer simulation identification of the level of washing and development of proper flow sheet including dry and wet beneficiation scheme for coals of different regions /coalfields can be prepared. The level of washing has to be linked with some quantitative determinants of the benefits to the end users to arrive at the optimum cost of the clean coal. While arriving at the optimum cost the issue of reject utilization should come into play since depending on the level of cleaning , i.e., Ash content, the proportion of misplaced materials in the rejects is going to change due to the presence of high near gravity materials of the Indian coals. Beneficiation of coal will not only reduce the ash to required level but also enrich coal with reactive macerals for better thermal efficiency, plant availability and plant output and reduce operating/maintenance costs, reduce expenditure and decrease oil support to boiler and reduce pollution and GHG emissions per unit of electricity generated.
Methodology
Broadly, the economic model will constitute of several modules which can be used as standalone or in an integrated manner depending upon the objective. The modules can be categorized as following.
Module 1- Coal data base
Database of full scale size-wise washability data. Density wise chemical, heat value and ash composition is preferred. These data will help to know the quality parameters of the cleans at different ash level after any simulation run. The ash composition data is important because with cleaning, the reduction of ash content will lead to better combustion but the change in the ash composition with level of cleaning may lead to slagging /fouling problems.
Module 2 – Simulation of coal beneficiation Process.
Computer simulation program based on washability data (from module 1) and efficiency of washers to identify the optimum operation conditions for producing the maximum yield at desired quality. The program will have the flexibility to evaluate the different options of beneficiating a particular coal, such as,
The following beneficiation strategy can be tried while undertaking the simulation run.
Module 3 - Cost model
This is a global module which will evaluate the benefits to an end user for using washed coal at a particular level of cleaning for quick decision making The factors to be included are,
Conclusions