An integrated maximum power point tracker for photovoltaic panels

A hybrid maximum power point tracking for partially shaded photovoltaic systems in the tropics

Compared with typical current controlled PV inverters, voltage controlled PV inverters based on droop control are easier to achieve seamless transfer between the stand-alone mode and the grid-connected mode. This paper achieves both seamless transfer and the maximum power point (MPP) tracking (MPPT) by adjusting droop curves dynamically, combining MPPT and P-f droop control. The DC voltage is difficult to control during grid connecting which will affect both the stability of the system and the MPPT efficiency. To solve this problem, a control method is proposed which includes an active power inner loop and a DC voltage outer loop. At last simulation and experimental results validate the proposed control strategy and show that DC voltage response is fast and stable. Both seamless transfer and MPPT operation modes are realized.

This paper reviews the existing models, connection schemes and maximum power point tracking (MPPT) methods of PV arrays. The partial shading causes significant power losses. It is very difficult to maintain uniform irradiance over the entire PV array, especially for rooftop or building-integrated PV systems. The aspects such as connection scheme of PV array, shading pattern and maximum power point tracking (MPPT) techniques, etc., decide the power generated by the PV array. The conventional MPPT methods are only capable of reaching maximum power point (MPP) in identical insolation situations. Hence, conventional MPP tracking becomes inept due to the existence of several peaks in the P-V characteristics. There are different global maximum power point (GMPP) tracking techniques available in the literature that operate in partial shading scenarios. The reconfiguration of the PV array reduces the number of multiple peaks. This reduction in several peaks makes conventional MPP tracking techniques competent even under partial shading conditions with low implementation complexity and higher tracking speed. This paper can assist scientists in choosing a precise objective-based PV module model, connection schemes and MPP tracking methods out of numerous schemes available in the literature.

Photovoltaic (PV) modules subject to partial shading (PS) or inhomogeneous irradiation drastically decrease the PV string power output. An algorithm composed of maximum voltage point tracking (MVPT) and maximum power point (MPP) tracking (MPPT) is presented to restore part of the power loss caused by PS. The MVPT can simultaneously drive the operating point of series PV modules toward their respective MPPs and guarantee power peak uniqueness. The MVPT is performed by means of a controllable current transformer (CCT) disposed at the terminal of each PV module permitting a compatible current in the series path of a PV string. The CCT output current can be regulated using a dependent current source according to the MPPT algorithm. An appropriate CCT current determined by the MPPT algorithm can avert undue CCT activation and consequently reduces the switching and copper losses of the converter circuit. Experimental results validate that the proposed strategy can balance the PV modules' output current subject to PS and facilitate convergence to the theoretical global MPP.

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A multi-input single inductor dual-output boost converter for multi-junction photo-voltaic (MJ-PV) energy harvesting is presented. The fast maximum power point (MPP) tracking of each photo-voltaic (PV) sub-cell for irradiation change and the high MPP tracking (MPPT) efficiency are obtained using a dual-loop MPPT control. The implemented discontinuous conduction mode (DCM) of converter operation minimizes cross-regulation among MJ-PV sub-cells. A dual-output path provides regulation at load and stores the extra harvested energy to a battery. A prototype board with the proposed system is implemented. The achieved peak power efficiency is 83% and the MPPT efficiency is 95%. This system can also be used for cell-level parallel-connected PV solar system.

Due to the Randomness and fluctuation of the photovoltaic (PV) system, Maximum Power Point Tracking (MPPT) algorithm is employed to ensure the maximum power extraction from PV arrays, when it is connected to the grid. The previous studies have indicated that the MPPT algorithm is one of the main causes of interharmonics emission in PV systems. The MPPT algorithm parameters such as perturbation step size inevitably have a strong impact on the interharmonics in the current injected to the grid. In general, a smaller MPPT perturbation step size will reduce the interharmonics emission level, but it will result in poor tracking performance of the MPPT algorithm. Thus, there is a trade-off between the MPPT efficiency and the interharmonics emission in PV system. In this paper, an interharmonics suppression scheme with variable step size MPPT algorithm was proposed. In the suppression scheme, two voltage values near by the MPPT voltage and two tracking step size are preset. When the dc-link voltage of PV is between the two preset voltage values, it means that the PV power near its MPP and the smaller perturbation step size implemented in the MPPT algorithm. Otherwise, the bigger perturbation step size is employed. It can greatly reduce interharmonics emission level and maintain the MPPT efficiency. Simulations have been carried out to verify the effectiveness of the suppression scheme.

A novel population based maximum point tracking algorithm to overcome partial shading issues in solar photovoltaic technology

A novel Remote Area Power Supply (RAPS) system consisting of a Doubly Fed Induction Generator (DFIG) wind turbine generator, synchronous diesel generator system, battery storage system and a dump load is considered in this paper. A control coordination strategy is formulated with a view to regulate the system voltage and frequency within acceptable limits while extracting the maximum power available from the wind. The battery storage unit is used to provide a smooth state transition from Wind-Only (WO) to Wind-Diesel (WD) mode while enabling the DFIG to operate in its maximum power point tracking mode of operation. The dump load is used to absorb the excess energy which cannot be utilised through the battery storage system. The entire RAPS system has been modelled using SimPowerSystem toolbox in MATLAB.

Generally, perturb and observe (P&O) technique is widely adopted in photovoltaic (PV) system to maximize the output power. In flyback inverter, the modulation index needs to be adjusted based on the P&O algorithm. However if the changing step size of modulation index (Δma) is too large, the fast MPP (Maximum Power Point) tracking can be achieved but the power oscillation around the MPP will be large. In contrary, the small changing step size results in long tracking time and small oscillation. Consequently, this paper proposes a technique to adjust the changing step size (Δma) of Flyback inverter to achieve both acceptable tracking time and low power oscillation. In the proposed technique, irradiance is adopted as the input of a neural network which is used to estimate the appropriate modulation step size. Simulation results confirm that the proposed neural network based inverter can find the appropriate changing step size (Δma) which is adequate for any irradiance conditions.

A novel control strategy for mode seamless switching of PV converter in DC microgrid based on double integral sliding mode control

This paper presents a new maximum power point tracking (MPPT) method based on an incremental conductance (IC) algorithm, constant voltage, and look-up table approach. Convergence time, one of the indicators of MPPT quality, is considered for improving MPPT performance of photovoltaic (PV) modules. In this context, a novel hybrid MPPT approach has been proposed. This proposed method consists of three stages. In the first stage, the value of load resistance is calculated. Then the initial operation point of the PV module is determined by using the constant voltage method or look-up table approach. An IC algorithm is used in order to increase MPPT accuracy in the last stage. One of the novelties of this proposed approach is the determination criterion related to sample numbers of PV module current or solar irradiance. With the help of this approach, the initial operation point of the PV module is optimized before MPPT starts. Thus, convergence time is reduced. In this paper, a DC--DC boost converter has been designed to show the performance of the proposed approach. Then the proposed approach is compared with an IC algorithm. Experimental results show that the performance of the proposed approach is better than that of the IC algorithm in terms of convergence time. On the other hand, since the proposed approach is convenient for reducing convergence time, it can be used instead of variable step size algorithms. Furthermore, there are no topological constraints in the proposed approach. Therefore, this method can be easily applied to other converter topologies for low power or microconverter (module-based converter)-based applications.

When the battery or supercapacitor is connected to the output of a PV system, the conventional voltage equation expressing its mathematical model usually must be replaced by the current relationship to study the maximum power point tracking (MPPT) control theory. However, hitherto, there is a lack of an attempt to disclose the current constraint relationships at the maximum power point (MPP), which leads to the potential risk of MPPT failure. To solve this problem, in this paper, the MPPT constraint conditions on the basis of currents are built and then a new MPPT control strategy is proposed. In this strategy, a linearized model parameter of a PV cell is used as the bridge to find the current relationships. On the basis of them, some expressions involving the duty cycle are built to directly calculate the control signal of the MPPT controller. Meanwhile, an implementation method is designed to match this proposed MPPT strategy. Finally, some simulation experiments are conducted. The simulation results verify that the proposed MPPT constraint expressions are accurate and workable and that the proposed MPPT strategy and its implementation process are feasible and available. In addition, the simulation results also show that the proposed MPPT strategy has a better MPPT speed and the same MPPT accuracy when the P&O method and fuzzy algorithm are compared. By this work, the MPPT constraint conditions based on current relationships are first found, representing a breakthrough in disclosing the inherent relationships between different currents when the PV system is operating around the MPP.

This study presents a new adaptive predictive error filter-based maximum power point tracker (MPPT) for a photovoltaic (PV) system. This MPPT is developed using the concept of an adaptive predictive filter (APEF) that consists of a one-tap finite impulse response. The filter step-size of the APEF is adapted using a recursive least-square (RLS) algorithm with an adaptive forgetting factor. The specialty of this MPPT is that it performs MPP tracking operation in a single step. It performs two functions: namely, MPP estimation adjusting operating point of a boost converter at MPP and then filtering of the PV voltage fluctuation after MPPT action. Thus, the proposed MPPT is compact and efficient with less computational complexities than existing MPPTs such as perturb and observe (P&O) and incremental conductance. The filter part of the proposed RLS-APEF-MPPT is a discrete PID-controller, where PD-part is tuned using pole-placement strategy and integral-term is fixed. The performances of the proposed RLS-APEF-MPPT were verified using experimentation on a prototype PV system. Its performances were compared with that of P&O, adaptive-P&O-MPPTs. From the observed results, it is confirmed that the proposed MPPT exhibits superior performance.

As a sustainable energy source, the use of solar photovoltaic (PV) systems has significantly increased. Environmental elements, especially partial shadowing circumstances, have a considerable impact on how well solar PV systems function. In such cases, the various local maxima in the power-voltage curve make it difficult for conventional Maximum Power Point Tracking (MPPT) methods to maintain peak efficiency. Heuristic Maximum Power Point Tracking (MPPT) system for solar photovoltaic (PV) applications, employing the cuckoo search algorithm. The primary objective of the research is to enhance the efficiency and reliability of solar PV systems by optimizing the MPPT process, which is crucial for maximizing energy extraction under varying environmental conditions. The model is used to simulate the performance of the system under various environmental conditions, such as changes in temperature and irradiance levels. The simulation results are then statistically analyzed to evaluate the effectiveness of the cuckoo search algorithm in tracking the maximum power point accurately and rapidly. The algorithm demonstrates a robust ability to converge to the maximum power point efficiently, thereby enhancing the overall energy yield of the solar PV system.. The performance of the hybrid PSO-CSA MPPT algorithm in contrast to traditional MPPT techniques is assessed through simulations and tests under various shading circumstances. The findings show that the hybrid strategy regularly outperforms conventional methods by enhancing the total energy production of partially shadowed solar PV installations through faster convergence, less oscillations, and greater tracking accuracy. The proposed hybrid algorithm also demonstrates stability and flexibility in real-world settings, making it a potential option for boosting the dependability and efficiency of solar PV systems when shade is present. This study advances the field of renewable energy and prepares the path for the use of sophisticated optimization methods to the problems of solar PV power generation under changing environmental circumstances.