COMBINED CYCLE POWER PLANT THERMO-ECONOMIC MULTI-OBJECTIVE OPTIMIZATION USING EVOLUTIONARY ALGORITHM

In this paper, an integrated modeling framework consisting of GateCycle(R) power plant modeling commercial software, an evolutionary based optimization tool and an in-house developed computer code suitable for thermo-economic calculations, has been applied to the optimization of the bottoming steam cycle of an advanced combined cycle power plant. Out of the many economic performance evaluation parameters available, optimal performance have been obtained under both Net Present Value (NPV) maximization and Levelized Cost Of Electricity (LCOE) minimization. A basic superstructure, capable to handle multiple configurations such as HRSG arrangements, as well as pressure levels number, has been developed within the proposed modeling framework. The optimization tool handles simultaneously a large number of variables, both thermo-economic (for instance the suitable temperature differences and the pressure levels) and logical, defining the HRSG configuration. While many on-site (boundary) conditions affect optimal design, fuel gas cost is securely the most relevant parameter affecting thermo-economic performance during power plant lifetime. Therefore, optimal performance, that is maximum NPV and minimum LCOE, has been obtained assuming different values for this parameter. It has been proven how the framework is able to cope with varying on-site conditions and how, when these latter are carefully taken into account, optimal design is even significantly modified.