Optimal Distribution of Heat Transfer Areas in Feed Water Heaters in a 210 MW Thermal Power Plant

Abstract

Regenerative feed water heating has become a standard practice in steam power plants as it gives higher cycle efficiency because of minimization of irreversibility in the feed water heating process and increase in average temperature of heat addition to the cycle . An attempt has been made in this work to optimize the distribution of heat transfer areas of various heaters in the regenerative feed water heating cycle of one of the units of 2 x 210 MW coal fired steam power plant of BHEL design . The design of power plants has been carried out traditionally on the basis of experience , but the application of modern optimization techniques to design parameters could bring in large saving in materials or better utilization of given materials . The work aims at optimizing the feed water heater areas made available in the design of BHEL for 210 MW steam power plants. The work is based on theoretical formulations available in open literature for convection /condensation and it has been concluded that by using values of overall heat transfer coefficient calculated by these formulations for various heater conditions , better values of optimal areas for different heaters are achieved than in the case where a fixed value of heat transfer coefficient is used for all the heaters . The calculated values of overall heat transfer coefficient compare favourably with the data supplied by BHEL. There is a saving of about 5.6 extraction steam in the optimal design over that of actual design . In actual design the total quantity of steam extracted is 1,84,306 Kg/hr where as in the optimal design a the quantity of steam extracted is 1,74,038 Kg/hr . The steam thus saved can be utilized for producing more power. The calculations for overall heat transfer coefficient as well as optimal distribution of areas for feed water heaters have been done with the help of computer by writing two separate computer programs . The convergence for each step has been obtained in an iterative manner . Dynamic programming has been used for optimization. It is hoped that optimal studies can provide better design of power plants when applied to now systems , yet to be installed .