OPTIMIZATION OF HEAT EXCHANGER NETWORK BASED ON EMISSION TARGETING

Abstract

In the present process industries, there is a need to reduce gaseous pollutants of all kinds because of heightening environmental concerns. This increases requirements for clean fuels and less polluting combustion systems. In the same context, energy management in process industries plays an important role and emerges as an effective solution to minimize pollutants emission to environment. Energy management also ensures denigration of total annual cost incurred to the process industry. The present investigation deals with the prediction of an optimum combination of model, fuel, utility system and process ΔTmin to manage energy requirements, which are constrained to CO2 emission. Hence, the total annual cost (TAC) of the process is optimized. Two models namely Model-1 and Model-2 have been developed in the present work. Model-1 and Model-2 are based on superstructure and Pinch technique, respectively. These are MINLP models. Model-1 and Model-2 deals with both binary and continuous variables takes into account both linear and non-linear equations. The objective function to be optimized is the plant TAC. Model-1 is a purely mathematical model based on superstructure technique of process integration. It accounts for network designing, based on best suitable match for the stage wise matching of hot and cold stream. The constrains such as heat duty, inlet & outlet temperatures, temperature of approach and emission limit imposed on superstructure model formation accordingly design and report the optimum network combination, which include least TAC and also obeys CO2 emission limits. Model-2 consists of combined approach for graphical using Pinch technology and mathematical modeling. In this model parameters obtained from pinch technology are incorporated in mathematical model, in order to obtain optimum TAC which satisfies CO2 emission limit. The Model-2 include constrains of Model-1 plus pinch temperature, ΔTmin, minimum utility consumption and fuel & utility consumption. The models developed are applied over two case studies, Case study-1 and Case study-2 based on aromatic plant stream data and ethylbenzene plant stream data, respectively. Case study-1 showed a decrement of 76.46% CO2 emission while using Model-2 in comparison to Model-1, and the TAC for Model-1 is 16 times that of Model-2. Case study-1 when compared with published literature showed a decrement of 70% emission. Similarly, Case study-2 observer a decline of 6.89% in CO2 emission, while using Model-2 over Model-1, and the TAC for Model-1was 2.8 times that obtained for Model-2. On comparing with published literatures, the number iv of heat exchanger units in the present model were found to be less in number. In both Cases study-1 & 2, Model-2 was found to be more effective over Model-1, while both the model used ΔTmin value to be 10 oC.