Saad Mekhilef
Swinburne University of Technology

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A Chameleon algorithm for solving economic dispatch problem in microgrid system Younes Zahraoui; Ibrahim Alhamrouni; Saad Mekhilef; Tarmo Korõtko; Awang Jusoh; Tole Sutikno
Bulletin of Electrical Engineering and Informatics Vol 12, No 4: August 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v12i4.4700

Abstract

The economic power dispatch (ED) is considered a critical optimization issue in the power system and microgrid. There are several objectives through the economic load dispatch issues such as reducing the operating cost, total emission, or start-up operations. This paper presents a Chameleon swarm algorithm (CSA) for determining the optimal ED of distributed energy resources (DER) in the microgrid. The proposed technique numerically mimics and executes chameleons' behavioral processes to their quest for food, such as their action for rotating their eyes to identify and grab prey using the speed of their sticky tongues. In this study, the CSA has been applied to obtain the optimal power dispatch from DER using the photovoltaic (PV) plants, combined heat power (CHP) systems, and traditional diesel generators. The obtained results from the simulation are compared with the conventional metaheuristic algorithms which have been used in previous studies, such as particle swarm optimization (PSO), genetic algorithm (GA), and artificial bee colony (ABC). Experimentally, the proposed algorithm for solving the ED problem determined the best value of the power dispatch and high performance compared to other metaheuristics methods.
Predictive-TOPSIS-based MPPT for PEMFC Featuring Switching Frequency Reduction Jye Yun Fam; Shen Yuong Wong; Mohammad Omar Abdullah; Kasumawati Lias; Saad Mekhilef; Hazrul Mohamed Basri
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 11, No 3: September 2023
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v11i3.4350

Abstract

A maximum power point tracking (MPPT) for a proton exchange membrane fuel cell (PEMFC) using a combination of conventional finite control set model predictive control (FCS-MPC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is proposed in this paper. The key idea is to maximize the power generation from a PEMFC while minimizing the switching frequency of the power converter. The FCS-MPC technique is formulated to track the maximum power of PEMFC highly affected by ever-changing internal parameters. Meanwhile, the TOPSIS algorithm is applied to overcome the potential weaknesses of insulated-gate bipolar transistor (IGBT), which can only withstand a lower switching frequency. In this project, all simulations were run using MATLAB software to display the output power of the PEMFC system. As a result, the proposed predictive-TOPSIS-based MPPT algorithm can track the MPP for various PEMFC parameters within 0.019 s with an excellent accuracy up to 99.11%. The proposed MPPT technique has fast-tracking of the MPP locus, excellent accuracy, and robustness to environmental changes.