Optimization and evaluation gas sweetening unit using genetic algorithm with quadratic search

Associated Gas with crude oil containing hydrogen sulfide, and amine solutions should be used to sweeten it. The genetic/quadratic search algorithm )GQSA) is a hybrid genetic algorithm )GA) for optimizing plant economics when a process simulator models the plant. By coupling a regular GA with an algorithm based upon a quadratic search, the required number of objective function evaluations for obtaining an acceptable solution decreases significantly in most cases. The GQSA combines advantages of GA and quadratic search techniques, e.g. determining a global optimum for a problem with a high probability for discontinuous as well as non-convex optimization problems while at the same time providing faster convergence than conventional GA. The performance of both the GQSA and the GA was compared using four different test functions and an economic optimization problem for a turbo-expander process. Numerical test results indicate that the convergence of the GQSA is either better than or at least comparable to those of GA for all tests employing the same genetic parameters. Also, the results show that the high concentration of ethanol amine increase acid gas absorption, power, steam and water consumption and thus operating costs increase. Also, high temperature of the inlet amine decreases the H2S absorption. It also reduces power consumption and increases the amount of makeup water and ultimately reduces operating costs. Increase the amount of circulating amine and overhead stream from the tower increase the acid gas absorption, electricity consumption and the operational cost.