HYDROGEN MANAGEMENT IN REFINERY

Abstract

Increasingly advancement of the industry increases the risk of pollution of the environment thereby leads to the unhealthy environment for us to live. All the process industries namely refinery, thermal power plants, fertilizer industry etc. contributes to the majority of the industrial pollution, along with these process plants the mining industry namely viz. coal mining, mineral ore mining also plays a major role in increasing the pollution level of the atmosphere. In context of refinery, the main productions are petrol and diesel, which on burning as a fuel produces SOx & NOx thereby causing pollution in the environment. The major reason behind these SOx & NOx production is high level of Sulphur, as it is known to us that by 2020 Indian government is trying to replace BS-IV fuels with the BS-VI which reduces the sulphur level from 50 ppm to less than 10 ppm, thus reducing the significant amount of pollution load in the environment. Thus to carry out reduction in the sulphur level desulphurization units need more hydrogen than the present one, thus the growing demand of hydrogen compels many refinery to optimize their hydrogen network and uss hydrogen in an efficient manner so as to not effect their gross refinery margin (GRM). The present work deals with the optimization of hydrogen generation unit (HGU) of one of the Indian Refinery to manage hydrogen in refinery. A mathematical Model from Jhaveri et.al(2013) is taken and the real time data of the Refinery is used to show optimal network. The Model is optimized using a mathematical modeling tool, GAMS. The constraints of the model along with variable initializations are developed in the form of program in GAMS and the selected solver DICOPT solves the model and predicts the optimal network. The optimized Model is compared with existing network based on different parameters such as hydrogen consumption from hydrogen plant, fuel recovered, total operating cost and total annual cost. Consequently, it is found that the new network predicted is more profitable network based on the modified TAC which accounts export cost, payback period, etc. IV The present work also considers different capital cost functions for compressors taken from Dekker, 2003. On the basis of total annual cost (TAC), the screw compressor has been chosen as the most economical compressor. The present work also takes into account piping cost of the network. It is found that the optimal network consumes 5.11 % less hydrogen than the existing network amounting to 6.915 Knm3/hr of hydrogen saving in the network.