Fuzzy thermoeconomic optimization of energy-transforming systems

We have developed a new approach for thermoeconomic analysis of energy-transforming systems based on the sequential uncertainty account to make decisions that simultaneously meet thermodynamic and economic goals. Thermoeconomic optimization has been considered as a fuzzy non-linear programming problem in which local criteria: maximum energy (exergy) efficiency and minimum total cost rate as well as different constraints in an ill-structured situation can be represented by fuzzy sets. The trade-off or the Pareto domain, where the value of a thermodynamic criterion cannot be improved without the value of economic criterion being worsened, has been considered as a first step of optimization strategy. The Bellman–Zadeh model, as the intersection of all fuzzy criteria and constraints, has been used for a final decision-making. Case studies of fuzzy thermoeconomic analysis application have been presented.