Indonesian Journal of Electrical Engineering and Computer Science
Vol 14, No 1: April 2019

An artificial intelligent approach for the optimization of organic rankine cycle power generation systems

JianDing Tan (Universiti Tenaga Nasional)
ChinWai Lim (Universiti Tenaga Nasional)
SiawPaw Koh (Universiti Tenaga Nasional)
SiehKiong Tiong (Universiti Tenaga Nasional)
YingYing Koay (Universiti Tenaga Nasional)



Article Info

Publish Date
01 Apr 2019

Abstract

The study on Organic Rankine Cycle (ORC) power generation system has gained significant popularity among researchers over the past decade, mainly due to the financial and environmental benefits that the system provides. A good maximum power point tracking (MPPT) mechanism can push the efficiency of an ORC to a higher rate. In this research, a Self-Adjusted Peak Search algorithm (SAPS) is proposed as the MPPT scheme of an ORC system. The SAPS has the ability to perform a relatively detailed search when the convergence reaches the near-optima peak without jeopardizing the speed of the overall convergence process. The SAPS is tested in a simulation to track for a moving maximum power pint (MPP) of an ORC system. Experiment results show that the SAPS outperformed several other well-established optimization algorithm in tracking the moving MPP, especially in term of the solution accuracies. It can thus be concluded that the proposed SAPS performs well as a mean of an MPPT scheme in an ORC system

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