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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.
Conceptual study on Grid-to-Vehicle (G2V) wireless power transfer using single-phase matrix converter Muhammad Qusyairi Iqbal Mohd Zamani; Rahimi Baharom; Dalina Johari
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (413.143 KB) | DOI: 10.11591/ijpeds.v10.i3.pp1382-1388

Abstract

This paper presents the conceptual study on grid-to-electric vehicle (G2V) wireless power transfer (WPT) using Single Phase Matrix Converter (SPMC). In this work, the SPMC is used as a direct AC to AC converter to convert the input supply voltage at 50 Hz frequency to the output of 20 kHz to meet the WPT switching frequency operation of the transmitter and receiver coils. The high frequency AC voltage of the receiver coil is then rectified to a DC form by using SPMC. Through the proposed system, the battery of an electric car can be charged wirelessly, thus removing the annoying wires of the conventional electric vehicle charging system. The reduction in size of the charging system, power losses and optimum efficiency are among the advantages of the proposed system. MATLAB/Simulink (MLS) has been used to simulate the proposed model. Selected simulation result are presented to verify the proposed work.
Development of active power filter using rectifier boost technique Dygku Aniqnatasa Awg Osman; Rahimi Baharom; Dalina Johari; Muhamad Nabil Hidayat; Khairul Safuan Muhammad
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v10.i3.pp1446-1453

Abstract

The development of active power filter (APF) using rectifier boost technique has been identified to compensate for the pulsating nature of the distorted supply current waveform of non-linear load. In this work, investigation is carried out on the operation of rectifier without any filters function. This is then extended to operate the rectifier converter with an active power filter function. APF function is implemented by enabling the closed-loop control using standard proportional integral control to rectify the distorted supply current to become continuous, sinusoidal and in-phase with the supply voltage waveform. Consequently, the total harmonic distortion (THD) level was reduced to meet the acceptable limit defined in the standard of IEEE-519 1992. The selected simulation results obtained from MATLAB/Simulink are presented to justify the proposed filter structure.
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.