Single-phase grid-connected PV system with golden section search-based MPPT algorithm

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 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.

An off-grid photovoltaic (PV) system's PV array is connected with a charge controller as the first power conversion stage. The average efficiency of the power stage of charge controllers is around 90%. Supercapacitor (SC) battery hybrid PV system is a novel PV system that utilizes some of the wasted energy of a typical system and enhances the system's efficiency up to 98%. However, the feasibility of maximum power point tracking (MPPT) for this system is yet to be validated. This paper presents a comparative study to adapt MPPT for the proposed system consisting of a series-connected SC bank with PV array and step-down DC-DC converter. The step-down converter is used as the impedance matching network. Different solar irradiance profiles were emulated to check the feasibility and efficiency of MPPT. Experimentally, it was shown that the typical MPPT could be adapted to the proposed PV system with very high MPPT efficiency.

In this paper, a complete simulation model of a single phase grid-connected photovoltaic (PV) system with associated controllers is presented. The simulation model is developed in MATLAB/SIMULINK tool. The main component of the single phase grid-connected PV system are, a PV array, a dc-dc boost converter, a PWM based voltage source inverter and filter. For high efficiency of the PV system used maximum power point tracking (MPPT) algorithm. Simulation studies shows that the sun irradiance are increase so increase the PV array output power and also increase the PQ. PV energy is large than load demand; the excess energy is will exported to the utility.

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.

Photovoltaic (PV) systems are increasingly used as a sustainable energy source, but their efficiency is significantly affected by environmental factors such as shading and temperature variations. This study proposes a novel Maximum Power Point Tracking (MPPT) algorithm based on the fusion of Support Vector Regression (SVR) and Incremental Conductance (INC) techniques, designed to enhance the performance of PV systems under partial shading conditions. The SVR model is employed to predict the power output of the PV system based on voltage and current measurements, leveraging its capability to handle non-linear relationships with high accuracy. The INC method is then integrated with the SVR predictions to dynamically adjust the operating point of the PV array, ensuring rapid and precise tracking of the maximum power point (MPP). The algorithm was implemented in MATLAB, and comprehensive simulations were conducted to evaluate its performance. Simulation results demonstrate that the SVR-INC fusion algorithm significantly improves the accuracy and stability of MPPT under varying shading conditions. The algorithm effectively reduces the tracking time to the MPP and minimizes power losses caused by partial shading. Compared to traditional MPPT methods, the proposed algorithm shows enhanced robustness and faster convergence, making it highly suitable for practical applications in real-world PV systems. Furthermore, the integration of SVR with INC provides a robust framework for dealing with the complexities of $P V$ power generation. The algorithm’s ability to adapt to changing environmental conditions ensures that the PV system operates at its maximum efficiency. The study also discusses the optimization of SVR parameters and the importance of datadriven approaches in enhancing MPPT performance. In conclusion, the proposed SVR-INC fusion MPPT algorithm offers a promising solution for improving the efficiency and reliability of PV systems under partial shading. The findings highlight the potential of this approach for future advancements in PV technology, contributing to the development of more efficient and resilient solar energy systems..

In photovoltaic (PV) systems, maximum power point tracking (MPPT) techniques are used in order to extract the maximum power from PV panels. So far, different MPPT methods have been presented. In all of these methods, two MPPT parameters, perturbation amplitude $(\Delta \mathbf{D})$ and perturbation period $(T_{p})$, have a great effect on the MPPT efficiency. In this paper, first, the dynamic behavior of PV systems are assessed in both steady and transient states with the use of the small signal model and the simulation. The PV operating point has different behavior in the steady and transient states; therefore, in the proposed method, first, a state of the system is identified. Afterwards based on characteristics of each state which are assessed in the dynamic behavior of the PV system, the MPPT parameters are optimized. $\Delta \mathbf{D}$ is variable and based on the slope of the P-V curve with two different scaling factors; furthermore, the linear and exponential functions are used to determine the variable $T_{p}$ based on an operating state. In order to prove the superiority of the proposed method over the existing methods, the simulations are done in MATLAB/Simulink and PSIM software, and also comparison is conducted between the proposed method and the previous works.

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.

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.

Efficient Maximum Power Point Tracking (MPPT) techniques play a vital role in optimizing energy extraction from photovoltaic (PV) systems, primarily due to the high sensitivity of photovoltaic panel (PVP) characteristics to varying environmental parameters, including ambient temperature and solar irradiance. Conventional MPPT methods generally depend on identifying and following reference points, which are extracted from variables closely related to the Maximum Power Point (MPP) on the external current-voltage characteristics of PVP. In response to the limitations inherent to traditional approaches, this study proposes an advanced lookup table strategy to generate highly accurate reference values explicitly as functions of measured ambient temperature and solar irradiance. Initially, this research employs the two-diodes electrical circuit model to rigorously define the foundational relationships between ambient temperature, irradiance, and photovoltaic panel performance. Subsequently, contemporary advanced extraction methods based on recent academic literature were applied, enabling accurate identification of the MPP coordinates. Creating an effective lookup table requires comprehensive and detailed experimental datasets, which are often insufficient or unevenly distributed in practical scenarios. To address this challenge, the Shepard global interpolation method was integrated into the model development process, effectively mitigating datasets limitations through accurate interpolation of missing data points. This approach significantly elevates the precision and robustness of MPPT models. A comprehensive case study, conducted with real-world experimental datasets, rigorously validated the accuracy and reliability of the proposed interpolation-based lookup table. The results confirm substantial enhancements in MPPT accuracy, facilitating greater energy extraction efficiency and improved overall performance in practical photovoltaic applications. DOI: 10.61416/ceai.v27i4.9541

In renewable system control engineering, Maximum Power Point Tracking (MPPT) techniques are considered as one of the key steps in photovoltaic (PV) system development. Indeed, some MPPT techniques provide high performance under uniform irradiation and temperature conditions. However, their performance significantly degrades when the two preceding climatic conditions suddenly change. Therefore, this paper proposes a new voltage regulation based on Fuzzy Logic Control (FLC) strategy and small-signal model of DC–DC booster converter. The proposed control scheme is mainly based on the indirect incremental conductance (Inc) technique, equipped with an optimal integrator controller (OIC). It is implemented in a PV system, consisting of a DC–DC boost converter connected to a resistive load, with the main objective of ensuring a good MPP tracking behavior for variable operating conditions. To achieve this objective, the proposed MPPT strategy is designed around two stages. First, the smooth reference voltage is ensured by a Single-Input Single-Output (SISO) fuzzy logic controller using the Inc technique based on the MPPT approach. Then, the optimal integrator controller stabilizing the closed-loop system is integrated with optimization of its parameter according to Routh’s criterion for resistive load variations. Simulation results confirm the effectiveness of the proposed MPPT technique compared to some commonly used MPPT approaches. The superiority of the proposal is proven by using efficiency ratio, which rises more than 98% in all case studies. These objectives are ensured for both uniform and critical sudden change in weather conditions, regardless of resistive load variations.

Today, Photovoltaic (PV) systems are very popular for power generation because they enjoy the advantage of being pollution free abundant natural resource, low maintenance cost and noiseless operation. Photovoltaic (PV) systems needs maximum power point tracking (MPPT) to maximize the PV array power output which is independent of the temperature, irradiation coPIC18F452nditions and electrical characteristics of the load. The Research Work introduces photovoltaic MPPT system based on PIC18F452 to achieve maximum power tracking. Moreover, the combination of boost circuit and PIC18F452 microcontroller is used for tracking of the maximum power generation from PV system. Moreover, Research presents a practical implementation of Perturbation and Observation (P&O), Incremental Conductance (IncCon) and Fuzzy Logic algorithms to achieve MPPT control. These algorithms are widely used because of its low-cost and ease of realization. Proposed P&O, Incremental Conductance and Fuzzy Logic algorithms are implemented and tested under different loads, and the test results are analyzed and compared. The results show the performance of the Fuzzy Logic and Incremental Conductance algorithm in tracking MPP is better than the P&O algorithm and the experimental results of Fuzzy Logic and Incremental Conductance algorithm indicate the feasibility and improved system functionality with high-efficiency. Also, results concludes that the design can effectively accomplish the purpose of the maximum power tracking.

ABSTRACTPhotovoltaic systems require efficient maximum power point tracking (MPPT) controllers to optimize energy extraction under varying conditions. This paper presents an enhanced nonlinear MPPT controller for stand‐alone photovoltaic systems based on a Cascaded Dual Loop of Synergetic Control. The proposed method addresses key limitations of conventional approaches, such as Incremental Conductance and Synergetic Control, by reducing ripple and chattering phenomena. The Cascaded Dual Loop Control dynamically adjusts the boost converter's duty cycle to maximize power extraction while ensuring stable energy delivery. Simulations conducted in MATLAB Simulink under varying irradiance and temperature conditions demonstrate the controller's high performance. It achieves a tracking efficiency between 97.2% and 99.15%, outperforming traditional methods. Additionally, it minimizes ripple and chattering to very low levels, enhancing system stability and reliability during transients. A comparison with state‐of‐the‐art MPPT techniques highlights the proposed method's advantages, including scalability for systems with power ratings up to 850 W. It excels in dynamic performance and power output stability, making it suitable for practical applications. In summary, the Cascaded Dual Loop Control represents a significant advancement in MPPT for photovoltaic systems. By combining high efficiency with robust stability, it offers an innovative solution for enhancing the reliability and performance of renewable energy systems in real‐world scenarios.

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

To mitigate problems like energy shortage and environmental degradation caused by conventional energy sources, it needs to shift from conventional energy to non-conventional energy sources. The solar photovoltaic (PV) technology emerges as one of the leading non-conventional energy sources. To operate a PV system at its maximum efficiency, it requires the operating module at maximum power output point (MPP). There are many conventional as well as advanced maximum power point tracking (MPPT) techniques developed and implemented for a solar PV system. This work provides a comparative analysis of the conventional and fuzzy logic controller (FLC)-based MPPT techniques for a solar PV system. In this study, performance of two conventional techniques is considered, i.e., perturb and observe (P & O) and incremental conductance (IC) MPPT technique. The analysis of the PV system is performed for different solar irradiance levels. The comparative study is evaluated for complexity, tracking time, efficiency, range of power, voltage, and current oscillations. The DC-DC boost converter is used for operation of the proposed PV system at MPP. The implementation of the entire system and control algorithms has been modeled in MATLAB Simulink.