In the recent past, the solar photovoltaic (PV) system has emerged as the most promising source of alternative energy. This solar PV system suffers from an unavoidable phenomenon due to the fluctuating environmental conditions. It has nonlinearity in I-V curves, which reduces the output efficiency. Hence, the optimum maximum power point (MPP) extraction of the PV system is difficult to achieve. Therefore, for maximizing the power output of PV systems, a maximum power point tracking (MPPT) mechanism, which is a control algorithm that can constantly track the MPP during operation, is required. However, choosing a suitable MPPT technique might be confusing because each method has its own set of advantages and disadvantages. Hence, a proper review of these methods is essential. In this paper, a state-of-the-art review on various MPPT techniques based on their classifications, such as offline, online, and hybrid techniques under uniform and nonuniform irradiances, is presented. In comparison to offline and online MPPT methods, intelligent MPPT techniques have better tracking accuracy and tracking efficiency with less steady state oscillations. Unlike online and offline techniques, intelligent methods track the global MPP under partial shade conditions.
1. Motivation and Incitement
Solar energy has become the most popular renewable energy source, since it can be used in any location and is available every day. Because of its simple structure, low pollution, low or no carbon greenhouse emissions, and low maintenance costs, it has become a dominant renewable source [
1]. Solar power is currently the world’s preferred alternative energy source [
2]. Nonetheless, the solar PV system suffers from the unavoidable problem of current and voltage nonlinearity, which occurs primarily in partially shaded conditions (PSC). In general, PV systems have a unique operating point where the power is at its maximum. Hence, the PV system needs to operate at this point to harvest the maximum efficiency [
3]. For maximizing output power under all abnormal conditions, the PV system takes account of the MPPT mechanism.
2. Comparative Analysis
Many MPPT techniques can be found in the literature. This research conducted a comprehensive evaluation of the literature on MPPT approaches for both partial shade (non-uniform) and uniform irradiance. These techniques are divided into the following three categories: online, offline, and intelligent MPPT techniques. All the MPPT methods aim to optimize the output power of a PV system in an unrelated way. The following aspects are explored in this section: the GMPP tracking capability, convergence speed, complexity, and environmental change sensitivity.
2.1. Capability of Tracking GMPP
Due to the fact that the solar PV system does not receive uniform sun irradiance in very close sites in a short time, there is a possibility of partial shade due to unavoidable conditions. These conditions may be responsible for the formation of multiple peaks (LMPPs) on the I-V and P-V characteristics, which affects the MPPT’s tracking efficiency. The online and offline MPPT techniques are incapable of tracking the GMPP under partial shading conditions, whereas intelligent MPPT techniques are capable of tracking the GMPP under all abnormal conditions, such as uniform and nonuniform conditions.
2.2. Convergence Speed
An efficient MPPT technique must be able to converge to the required voltage and current with high speed and accuracy, regardless of whether the solar irradiance changes steadily or dramatically. When compared to intelligent MPPT techniques, the offline techniques convergence speed is fast but fails to track accurate MPP, whereas online techniques track MPP faster with constant oscillations, but converges to LMPP under partial shading conditions. The offline MPPT approaches never operate at accurate MPP, and hence are not suitable for efficient systems. The online MPPT techniques have high power losses under partial shading and accuracy is dependent on the size of perturbation. Furthermore, the intelligent techniques converge the GMPP under all abnormal conditions with negligible oscillation.
2.3. Complexity
The selection of an appropriate MPPT, keeping in mind its design complexity for a specific PV system, is regarded as one of the critical factors. The degree of accuracy with which the algorithm seeks for the real GMPP in the presence of several LMPPs determines the complexity of the MPPT approach. Otherwise, the PV system will not be able to capture the maximum solar energy. Moreover, the configuration and implementation of the MPPT are dependent on the user’s knowledge of the device, with one person being skilled in dealing with analog circuits, while the other prefers digital circuits. However, intelligent MPPT algorithms are implemented in digital form, which necessitates computer programming and software experts.
2.4. Sensitivity
A good MPPT technique must be sensitive enough to operate under all abnormal (uniform and nonuniform) conditions or atmospheric changes. It must be able to react quickly and track the GMPP of the specific PV system at the given condition. The comparative assessment of all the MPPT techniques is presented in Table 6.
Table 6. A comparative assessment of MPPT techniques.
| Type of MPPT Technique |
Offline
MPPT |
Online
MPPT |
Intelligent
MPPT |
| Tracking speed |
High |
High |
Medium |
| Tracking accuracy |
Less |
Moderate |
High |
| Tracking efficiency |
Poor |
Medium |
Very good |
| Steady-state Oscillations |
Less |
High |
Less |
| GMPPT tracking under PSC |
Yes |
No |
Yes |
| Suitability for high-efficiency operations |
No |
Yes |
Yes |
| Suitability for environmental changing conditions |
No |
No |
Yes |
The existing reviews provide the MPPT techniques based on uniform and partial shading conditions. They provided the details of a few conventional and swarm algorithm-based MPPT techniques. In addition, they performed a comparison of these techniques. The existing MPPT methods have drawbacks, such as being trapped at local MPP under PSCs, high initial oscillations, and slow tracking speed. Furthermore, to overcome these issues, hybrid intelligent MPPT techniques can be formed by combining the conventional and swarm algorithms or combining two heuristic methods.
Conclusion:
Solar PV is regarded as the most promising energy source in the renewable energy generation system due to its abundant availability of sunlight. However, it has some drawbacks, such as weather inconsistency, low efficiency, and high initial investment. As a result, MPPT is used as a power electronics interface to get the maximum power output of the PV system under both uniform and non-uniform shading conditions. So far, extensive research has been made on MPPT to improve the efficiency of PV systems under various weather conditions. However, selecting the appropriate MPPT for the specific PV system configurations and conditions has always been difficult. Therefore, this paper provides an accurate summary and a thorough review of various MPPT techniques. This research is based on the most commonly used techniques in recent years, which have been benchmarked in MPPT implementation. To summarise, a comparative study based on the sensor used, convergence speed, complexity, and application under dynamic weather conditions, are briefly examined. After a thorough examination of all offline, online, and intelligent MPPT methods, it has been determined that the offline MPPT techniques achieve faster MPP but fail to track the accurate MPP. The online MPPT techniques track the faster MPP with constant oscillations and fail to track GMPP under shading conditions. However, intelligent MPPT techniques track the GMPP quickly and accurately under partial shading and rapidly changing solar irradiance conditions. However, because they are complex algorithms, they are difficult to implement using embedded technologies.
This entry is adapted from the peer-reviewed paper 10.3390/a15100365
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