Ying Ying Koay
Universiti Tenaga Nasional

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Optimization of wind energy conversion systems – an artificial intelligent approach Ying Ying Koay; Jian Ding Tan; Siaw Paw Koh; Kok Hen Chong; Sieh Kiong Tiong; Janaka Ekanayake
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 11, No 2: June 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (388.844 KB) | DOI: 10.11591/ijpeds.v11.i2.pp1040-1046

Abstract

The environmentally friendly wind energy conversion system has become one of the most studied branches of sustainable energy. Like many other power generator, maximum power point tracking is an easy yet effective way to boost the efficiency of the conversion system. In this research, a modified Electromagnetism-like Mechanism Algorithm (EM) is proposed for the maximum power point tracking (MPPT) scheme of a micro-wind energy conversion system (WECS). In contrast with the random search steps used in a conventional EM, modified EM is enhanced with a Split, Probe, and Compare (SPC-EM) feature which ensures solutions with higher accuracies quicker by not having to scrutinize the search in details at the beginning stages of the iterations. Experiments and simulations are carried to test the SPC-EM in tracking the maximum power point under different wind profiles. Results indicate that the performance of the modified EM showed significant improvement over the conventional EM in the benchmarking. It can thus be concluded that based on the simulations, the SPC-EM performs well as an MPPT scheme in a micro-WECS.
An Electromagnetism-like Mechanism Algorithm Approach for Photovoltaic System Optimization Jian Ding Tan; Siaw Paw Koh; Sieh Kiong Tiong; Kharudin Ali; Ying Ying Koay
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: October 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v12.i1.pp333-340

Abstract

Solar energy has become one of the most studied topic in the field of renewable energy. In this paper, an artificial intelligent approach is proposed for the optimization of a photovoltaic solar energy harvesting system. An Electromagnetism-Like Mechanism Algorithm (EM) has been developed to search for the hourly optimum tilt angles for photovoltaic panels. In order to investigate the effect of the search step size on the efficiency and overall accuracy of the algorithm, the EM has also been modified into several variants with different search step size settings. Experimental findings show that EM with bigger search lengths has the advantage of reaching a near optimum tilt angle in earlier iterations but less accurate. EM with smaller step lengths, on the other hand, can hit a relatively more optimum tilt angle in the process. During the peak of the power generation at noon, EM with smaller search stes found an optimum tilt angle which yielded additional 3.17W of power compared to a fixed panel. We thus conclude that the proposed EM performs well in optimizing the tilt angle of a photovoltaic solar energy harvesting system.