Improvement of energy systems using the soft computing techniques

For complex energy systems, due to non-linear and usually non-explicit variable relationships on the one hand and incomplete mathematical model on the other, the term optimisation implies improvement rather than calculation of an overall optimum point. Therefore, the improvement procedure is performed based on the experiences of experts that can be translated into a class of soft computing technique so-called the fuzzy inference system (FIS). In this paper, a cogeneration power plant which generated the net electric power of 30.0 MW and could provide 14.0 kg s–1 of saturated steam at 2 MPa, namely as CGAM problem, was considered as a benchmark for exergoeconomic improvement using the FIS. The FIS system was designed to improve the overall system based on the improvement of each system component of the CGAM system. It was shown that the FIS could achieve a value for exergoeconomic objective function which was very close to the mathematical optimal solution