Experimental Validation of an Enhanced MPPT Algorithm and an Optimal DC–DC Converter Design Powered by Metaheuristic Optimization for PV Systems

Abstract

Nowadays, photovoltaic (PV) systems are responsible for over 994 TWH of the worldwide energy supply, which highlights their relevance and also explains why so much research has arisen to enhance their implementation; among this research, different optimization techniques have been widely studied to maximize the energy harvested under different environmental conditions (maximum power point tracking) and to optimize the efficiency of the required power electronics for the implementation of MPPT algorithms. On the one hand, an earthquake optimization algorithm (EA) was introduced as a multi-objective optimization tool for DC–DC converter design, mostly to overcome component shortages by optimal replacement, but it had never been tested (until now) for PV applications. On the other hand, the original EA was also taken as inspiration for a promising EA-based MPPT, which presumably enabled a solution with simple parametric calibration and improved dynamic behavior; yet prior to this research, the EA-MPPT had never been experimentally validated. Hence, this work fills the gap and provides the first implementation of the EA-based MPPT, validating its performance and suitability under real physical conditions, where the experimental testbed was optimized through the EA design methodology for DC–DC converters and implemented for the first time for PV applications. The results present energy waste reduction between 12 and 36% compared to MPPTs based on perturb and observe and particle swarm optimization; meanwhile, the designed converter achieved 7.3% current ripple, which is between 2.7 and 12.7% less than some industrial converters, and it had almost 90% efficiency at nominal operation. Finally, the EA-MPPT proved simple enough to be implemented even through an 8-bit MCU (ATmega328P from Arduino UNO).

Multiport Converter Utility Interface with a High-Frequency Link for Interfacing Clean Energy Sources (PV\Wind\Fuel Cell) and Battery to the Power System: Application of the HHA Algorithm

“…Constructed on the DC-DC converter's architecture and the corresponding circuit variables, different MPPT techniques have been used [44]. Entry capacitance (C PV ) is detected before the panel voltage (V PV ) and current (I PV ).…”

“…Observing the (V PV , I PV , and P PV ) will yield the I-V and P-V curves at various cell temperatures (CTs) and a constant irradiation level (CIL), as shown in Figure 5. Constructed on the DC-DC converter's architecture and the corresponding circuit variables, different MPPT techniques have been used [44]. Entry capacitance (𝐶 ) is detected before the panel voltage (𝑉 ) and current (𝐼 ).…”

“…As shown in Figure 5, the referring point for the panel data is determined and kept at the MPP value. Constructed on the DC-DC converter's architecture and the corresponding circuit variables, different MPPT techniques have been used [44]. Entry capacitance (𝐶 ) is detected before the panel voltage (𝑉 ) and current (𝐼 ).…”

Coordinated optimization model for solar PV systems integrated into DC distribution networks

“…Economic benefits of integrating the use of DC DERs into distribution systems [5][6][7][8][9][10][11] Optimal siting and design of grid-connected PV systems [12][13][14][15][16][22][23][24][25][26] PV output research [17][18][19][20][21] Techno-economic feasibility of an AC/DC hybrid distribution network [27][28][29][30][31][32][33] Optimal control of DC-DC, and AC-DC converters supporting DC distribution [8,[34][35][36][37][38][39] DC distribution-Analysis and optimization [40][41][42][43][44][45][46][47] To the best of the authors' knowledge, there are no existing works that present a coordinated optimization tool for the control of voltage controllers in DC distributed networks incorporating solar PV systems, such that solar power is maximized, and substation power is minimized.…”

“…The results indicate that the optimum tilt angle of solar panels stationed in the studied cities was close to the latitude of the aforementioned cities. Furthermore, multiple works aim to increase the output power of PV systems through effective maximum power point tracking (MPPT) methods and improved PV model designs [2,[18][19][20][21].…”