This article is organized into several parts to illustrate the application of the proposed optimization method using case studies. The case studies are related to the cold end system of a 300 MW TPP. The objective of the studies is to find an optimal design of the system that will perform its task at the lowest possible annual cost (capital and operating) while satisfying the specified input design conditions and operating conditions, as well as the imposed constraints.

In Part I of the article [1] , a detailed description of the methodology is included, and Case Study 1 is presented as the base case study. The decision variables are: cooling water approach to the ambient wet bulb temperature (ΔT_app), cooling water range (ΔT_cw), steam condenser terminal temperature difference (ΔT_TTD), cooling water velocity in the steam condenser tubes (v_SCt), hydraulic water load on the cooling tower fill (q_CTf), height of the cooling tower fill (H_CTf), and height of the cooling tower air inlet opening (H_CTi). The annual cost (capital and operating) of the cooling water system (AC_CWS) is chosen as the objective function. The optimal values of the decision variables and parameters of the cold end system equipment (SC, CT and CWPs and CWPLs) are determined on the basis that the AC_CWS is minimal. The exhaustive search algorithm [2] [3] is used to find the optimal values.

In this part (Part II) of the article, Case Study 2 is presented to investigate the effect of reducing the global optimization of the system to partial optimization by different combinations of the decision variables.

Case Study 2 is intended to demonstrate how different combinations of the decision variables affect the optimization results compared to the optimal base case OPT-0 when all decision variables are optimized.

Ten characteristic optimization cases, with different subsets of fixed and free decision variables, as shown in Table 1 , are compared at an assumed LCOE of 100 €/MWh. The various scenarios were selected on the following basis:

Note: The cooling water range (ΔT_cw) is a common decision variable for the design of the cooling tower and steam condenser.

All design/operating conditions and constraints for Case Study 2 are the same as for Case Study 1, except for the following:

Based on the input parameters, the optimal results for the decision variables and equipment sizes of the cold end system components are presented in Annex, Tables A1-A4 . The optimal results are shown as a function of the average annual ambient wet bulb temperature and the LCOE.

The decision variables that are not subject to optimization in the tables are marked in bold font.

Based on the optimization results given in the tables in Annex A, the following conclusions can be drawn: