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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS)
Nik Fasdi Nik Ismail
Universiti Teknologi MARA
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

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DC-DC Boost Converter Design for Fast and Accurate MPPT Algorithms in Stand-Alone Photovoltaic System Norazlan Hashim; Zainal Salam; Dalina Johari; Nik Fasdi Nik Ismail
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 9, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (2855.607 KB) | DOI: 10.11591/ijpeds.v9.i3.pp1038-1050

Abstract

The main components of a Stand-Alone Photovoltaic (SAPV) system consists of PV array, DC-DC converter, load and the maximum power point tracking (MPPT) control algorithm. MPPT algorithm was used for extracting maximum available power from PV module under a particular environmental condition by controlling the duty ratio of DC-DC converter. Based on maximum power transfer theorem, by changing the duty cycle, the load resistance as seen by the source is varied and matched with the internal resistance of PV module at maximum power point (MPP) so as to transfer the maximum power. Under sudden changes in solar irradiance, the selection of MPPT algorithm’s sampling time (TS_MPPT) is very much depends on two main components of the converter circuit namely; inductor and capacitor. As the value of these components increases, the settling time of the transient response for PV voltage and current will also increase linearly. Consequently, TS_MPPT needs to be increased for accurate MPPT and therefore reduce the tracking speed. This work presents a design considerations of DC-DC Boost Converter used in SAPV system for fast and accurate MPPT algorithm. The conventional Hill Climbing (HC) algorithm has been applied to track the MPP when subjected to sudden changes in solar irradiance. By selecting the optimum value of the converter circuit components, a fast and accurate MPPT especially during sudden changes in irradiance has been realized.
Optimal population size of particle swarm optimization for photovoltaic systems under partial shading condition Norazlan Hashim; Nik Fasdi Nik Ismail; Dalina Johari; Ismail Musirin; Azhan Ab. Rahman
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp4599-4613

Abstract

Particle swarm optimization (PSO) is the most widely used soft computing algorithm in photovoltaic systems to address partial shading conditions (PSC). The success of the PSO run heavily depends on the initial population size (NP). A higher NP increases the probability of a global peak (GP) solution, but at the expense of a longer convergence time. To find the optimal value of NP, a trade-off is typically made between a high success rate and a reasonable convergence time. The most used trade-off method is a trial-and-error approach that lacks explicit guidelines and empirical evidence from detailed analysis, which can affect data reproducibility when different systems are used. Hence, this study proposes an empirical trade-off method based on the performance index (PI) indicator, which takes into account the weighted importance of success rate and convergence time. Furthermore, the impact of NP on achieving a successful PSO was empirically investigated, with the PSO tested with 16 different NPs ranging from 3 to 50, and 10,000 independent runs on various PSC problems. Overall, this study found that the best NP to use was 25, which had the best average PI value of 0.9373 for solving all PSC problems under consideration.
Co-Authors Azhan Ab. Rahman Dalina Johari Ismail Musirin Norazlan Hashim Zainal Salam