Norazlan Hashim
Universiti Teknologi MARA

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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.
Critical evaluation of soft computing methods for maximum power point tracking algorithms of photovoltaic systems Norazlan Hashim; Zainal Salam
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1451.682 KB) | DOI: 10.11591/ijpeds.v10.i1.pp548-561

Abstract

With the proliferation of numerous soft computing (SC)–based maximum power point tracking (MPPT) algorithms for photovoltaic (PV) systems, determining which algorithm performs better than others is becoming increasingly difficult. This is primarily due to the absence of standardized methods to benchmark their performances using consistent and systematic procedures. Moreover, the module technology, power ratings, and environmental conditions reported by numerous publications all differ. Based on these concerns, this paper presents a critical evaluation of the five most important and recent SC-based MPPTs, namely, genetic algorithm (GA), cuckoo search (CS), particle swarm optimization (PSO), differential evolution (DE), and evolutionary programming (EP). To perform a fair comparison, the initialization, selection, and stopping criteria for all methods are fixed in similar conditions. Thus, the performance is determined by its respective reproduction process. Simulation tests are performed using the MATLAB/SIMULINK environment. The performance of each algorithm is compared and evaluated based on its speed of convergence, accuracy, complexity, and success rate. The results indicate that EP appears to be the most promising and encouraging SC algorithm to be used in MPPT for a PV system under the multimodal partial shading condition.