In this article, a new maximum power point tracking algorithm based on a modified butterfly optimization algorithm has been proposed. The proposed method is capable of differentiating between ...different partial shading patterns, uniform shading, solar intensity, and load variation conditions with fast convergence speed (CS). Only one dynamic variable is used as a tuning parameter reducing the complexity of the algorithm. The search space skipping method has been proposed to improve the CS. The proposed method is hybridized with a constant impedance method to improve the response time of the system for fast varying load variations. The proposed method has been validated experimentally on the SEPIC converter topology with a sampling time of 0.05 s. The experimental validation proved the average tracking time for different shading patterns is less than 1 s with steady-state efficiency of 99.85% on average. The CS for uniform shading conditions is improved by 47.20%. The response to load variation is also improved by 86.15% and becomes eligible to be utilized for fast varying load variations. Finally, the comparison table based on the MPPT rating has been presented to determine the effectiveness of the proposed method among other popular metaheuristic approaches used for MPPT.
Solar energy exposed its prominence to diminish the growing energy demands. But the formation of multiple peaks under partial shading conditions causes the conventional maximum power point tracking ...controllers to fail to track the global maximum power point (GMPP). Scanning the whole power-voltage curve to locate the GMPP takes extreme time and reduces algorithm effectiveness. Thus, the proposed method devotes the skipping and scanning mechanism incorporated with the perturb and observe (P&O) algorithm to reduce the scanning area drastically. The skipping mechanism skips over the scanning areas between successive peaks based on a specific formula that narrows down the scanning zone. Along with a buck-boost converter, the system includes a voltage control loop controlled by a proportional-integral controller. The proposed algorithm's effectiveness is tested in both simulation and experimental environments on discretized partial shading patterns while GMPP is deployed at different locations. According to the experimental outcomes, the proposed algorithm outperforms the modified maximum power trapezium, skipping fast GMPP, modified cuckoo search, and the conventional P&O algorithm with an average convergence time of 1.02 sec and average efficiency of 99.44 percent.
An advanced power control strategy by limiting the maximum feed-in power of PV systems has been proposed, which can ensure a fast and smooth transition between maximum power point tracking and ...constant power generation (CPG). Regardless of the solar irradiance levels, high-performance and stable operation are always achieved by the proposed control strategy. It can regulate the PV output power according to any set point, and force the PV systems to operate at the left side of the maximum power point without stability problems. Experimental results have verified the effectiveness of the proposed CPG control in terms of high accuracy, fast dynamics, and stable transitions.
This paper proposes an improved maximum power point tracker (MPPT) for photovoltaic (PV) system. The scheme is a hybrid between the adaptive perturb and observe and particle swarm optimization (PSO). ...The algorithm incorporates the search-skip-judge (SSJ) mechanism to minimize the region within the P−V curve to be searched by the PSO. Furthermore, the PSO performance is enhanced by ensuring that the regions that have been previously explored (by other particle) will not be searched again by (another particle). Thus, the unnecessary movement of particles is minimized-leading to faster convergence. The proposed method is evaluated against four well-known MPPT techniques, namely the modified incremental conductance, the original version of SSJ, the modified cuckoo search, and the hybrid PSO. In addition, an experimental prototype, which is based on PV array simulator is used to verify the simulation. The competing algorithms are tested with a buck-boost converter, driven by the TMS320F240 DSP on the dSPACE DS1104 platform. It was found that the proposed scheme converges to the global maximum power point (GMPP) most rapidly and the GMPP tracking is guaranteed even under complex partial shading conditions.
The photovoltaic (PV) string under partially shaded conditions exhibits complex output characteristics, i.e., the current-voltage <inline-formula> <tex-math ...notation="LaTeX">(I\mbox{--}V)</tex-math></inline-formula> curve presents multiple current stairs, whereas the power-voltage <inline-formula> <tex-math notation="LaTeX">(P\mbox{--}V)</tex-math></inline-formula> curve shows multiple power peaks. Thus, the conventional maximum power point tracking (MPPT) method is not acceptable either on tracking accuracy or on tracking speed. In this paper, two global MPPT methods, namely, the search-skip-judge global MPPT (SSJ-GMPPT) and rapid global MPPT (R-GMPPT) methods are proposed in terms of reducing the searching voltage range based on comprehensive study of <inline-formula> <tex-math notation="LaTeX">I\mbox{--}V</tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">P\mbox{--}V</tex-math></inline-formula> characteristics of PV string. The SSJ-GMPPT method can track the real maximum power point under any shading conditions and achieve high accuracy and fast tracking speed without additional circuits and sensors. The R-GMPPT method aims to enhance the tracking speed of long string with vast PV modules and reduces more than 90% of the tracking time that is consumed by the conventional global searching method. The improved performance of the two proposed methods has been validated by experimental results on a PV string. The comparison with other methods highlights the two proposed methods more powerful.
This article proposes a fast and efficient maximum power point tracker (MPPT) for photovoltaic (PV) systems under rapidly changing partial shading conditions. An intelligent mechanism is adopted to ...systematically schedule the search for the global maximum power point (GMPP) on the P-V curve. As a result, the voltage track, i.e., the path length that the operating point traverses along the voltage axis of the curve (until it converges to GMPP), is reduced. The search region is further minimized using a novel skipping scheme, where the voltage section that does not contain GMPP is discarded. The superiority of the proposed scheme is evaluated against two recent algorithms, namely, the maximum power trapezium and the flower pollination MPPT. The performance is analyzed in terms of convergence time, voltage track, and transient efficiency. The MATLAB simulation is verified experimentally using a PV array simulator, in conjunction with a buck-boost converter. The competing MPPT algorithms are implemented using the TMS320F240 DSP on the dSPACE DS1104 platform. The results indicate that under the same operating and shading conditions, the proposed scheme is the fastest and most reliable and exhibits the highest overall transient efficiency.
Hot-spotting is a reliability problem influencing photovoltaic (PV) modules, where a mismatched solar cell/cells heat up significantly and reduce the output power of the affected PV module. ...Therefore, in this paper, a succinct comparison of seven different state-of-the-art maximum power point tracking (MPPT) techniques are demonstrated, doing useful comparisons with respect to amount of power extracted, and hence calculate their tracking accuracy. The MPPT techniques have been embedded into a commercial off-the-shelf MPPT unit, accordingly running different experiments on multiple hot-spotted PV modules. Furthermore, the comparison includes real-time long-term data measurements over several days and months of validation. Evidently, it was found that both fast changing MPPT and the modified beta techniques are best to use with PV modules affected by hot-spotted solar cells as well as during partial shading conditions, on average, their tracking accuracy ranging from 92% to 94%. Ultimately, the minimum tracking accuracy is below 93% obtained for direct pulsewwidth modulation voltage controller MPPT technique.
The perturb and observe (P&O) algorithm is a simple and efficient technique, and is one of the most commonly employed maximum power point (MPP) tracking (MPPT) schemes for photovoltaic (PV) ...power-generation systems. However, under partially shaded conditions (PSCs), P&O method miserably fails to recognize global MPP (GMPP) and gets trapped in one of the local MPPs (LMPPs). This paper proposes ant-colony-based search in the initial stages of tracking followed by P&O method. In such a hybrid approach, the global search ability of ant-colony optimization (ACO) and local search capability of P&O method are integrated to yield faster and efficient convergence. A theoretical analysis of the static and dynamic convergence behavior of the proposed algorithm is presented together with computed and measured results.
Optimizing the operational performance of maximum power point trackers during multiple peak partial shading conditions (PSCs) prevails as a major challenge in photovoltaic power generation. Though ...many of the newly evolved soft computing and heuristic methods are compatible during PSCs, the need for such techniques in uniform irradiation levels is uncertain because most of these algorithms produce extensive oscillations before converging to the global maximum power point (GMPP). On the other hand, adopting conventional perturb and observe (P&O) algorithm is meritorious to reduce the transient power and voltage oscillations. Therefore, this article presents a proficient hybrid tracking technology that provides an adequate tradeoff between conventional P&O and advanced soft computing techniques by accurately detecting shade occurrences. For which, the uniqueness in the operating point conductance of P&O at the leftmost power peak in the P-V curve is utilized. Subsequently, the proposed convention utilizes P&O for two major purposes: to track MPP in uniform irradiance, and to detect PSCs. More importantly, even during PSCs, the detection algorithm is well designed to operate at GMPP with the conventional P&O method itself, and, only for extreme shade cases, flower pollination algorithm is introduced to track GMPP. The pre-eminence of the proposed technology to track GMPP with reduced transient oscillations by discriminating shade occurrences is demonstrated via extensive experimental studies in this article.
Maximum power point tracking (MPPT) is one of the crucial components to ensure that the photovoltaic (PV) system operates optimally. The bypass diodes are added across series-connected PV modules to ...avoid the hotspot phenomenon, which resulted in multiple peaks on the power-voltage curve during partial-shading conditions. In this article, a new metaheuristic approach, namely improved team game optimization algorithm, has been proposed. Only one tuning parameter is required for the proposed algorithm, and a new approach has been introduced to increase the convergence speed. Apart from that, a constant current method has been proposed during load variation conditions, which improved the response of the system toward load changes by 78.26%. The experimental results showed that the convergence speed of the proposed method is 72.5% faster than the standard team game optimization algorithm. The proposed method is also validated under different shading conditions and proven to have an average MPPT efficiency of 99.78% and an average tracking time of 0.9 s. The comparison between the proposed method and different metaheuristic approaches was also carried out based on grade point average, and it showed the effectiveness of the proposed algorithm with a higher number of features.
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