Maximization of the Profit of a Complex Combined-Cycle Cogeneration Plant Using a Professional Process Simulator

The high cost of energy resources has driven a strong and continued quest for their optimal utilization. In this context, modern thermoeconomic optimization techniques have been developed to analyze and design improved energy systems, leading to a better compromise between energetic efficiency and cost. Thermoeconomic optimization can be parametric (plant configuration is fixed), applicable both at the design phase or operation phase of a system, or structural (plant configuration may vary). In practice, mathematical thermoeconomic optimization may be accomplished in two ways: (i) the conventional way, which manipulates all pertinent equations simultaneously or (ii) integrated with a professional process simulator, such that the equations are manipulated separately. In the latter case, the simulator deals with the thermodynamic property and balance equations, while an external optimization routine, linked to the simulator, deals with the economic equations and objective function. In this work, a previous implementation of an integrated approach for parametric mathematical thermoeconomic optimization of complex thermal systems is applied to an actual combined-cycle cogeneration plant located in the outskirts of the city of Rio de Janeiro in Brazil. The plant contains more than 60 thermal components, including two gas turbines, one steam turbine, and two heat recovery steam generators. Several hundred variables are required to simulate the plant at one operational steady-state. The plant produces 380 MW of power nominally, and exports a mass flow rate between 200 tons/h and 400 tons/h of superheated process steam, at 45 bars and $404°C$⁠, to a neighboring refinery. The simulator is the THERMOFLEX software, which interfaces with the Microsoft Excel program. The optimization routine is written in the Visual Basic for Applications language and is based on Powell’s method. The cogeneration plant operates subjected to time-changing economic scenarios, because of varying fuel, electricity, and steam prices. Thus, to manage the plant, it is necessary to vary the operational state appropriately as the economic parameters change. For a prescribed economic scenario, previous work determined the minimum operational cost, when a fixed contracted hourly-rate of process steam was to be exported, while a variable amount of electrical power was produced. In this paper, a broader optimization problem is formulated and solved, for which the objective is to maximize the plant profit under different economic scenarios. It is shown that the optimal operating conditions depend on the economic parameters, and do not necessarily imply maximum efficiency. The integrated optimization approach proves effective, robust, and helpful for optimal plant management.