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Abstract Solar photovoltaic energy is a vital renewable resource because it is clean, endless, and pollution‐free. Due to the fast growth of the semiconductor and power electronics sectors, photovoltaic (PV) technologies are climbing significant attention in modern electrical power applications. Operating PV energy conversion systems at the maximum power point is essential for getting the maximum power output and raising efficiency. This paper proposes a regression‐based Perturb and Observe method to quickly find a global maximum power point, avoiding being stuck in local maxima, likewise analytical and metaheuristic methods. The improved control focuses on the narrowed search areas by linear and non‐linear regression analyses using the generated PV model on a flexible Python environment. Furthermore, the method's accuracy is validated in real time under variable temperatures, irradiations, and loads. This method was proven with a hardware implementation. The proposed method is more than 98% accurate and can withstand long‐term modelling. The suggested regression‐based perturbation and observation method provided a short learning time and easy implementation. Additionally, the dynamic recorded results can be visualized for researchers to utilize efficiently.

This paper compares different maximum power point tracking (MPPT) control strategies in microgrid dynamics, focussing on perturb and observe (P&O), adaptive neuro-fuzzy inference system (ANFIS), particle swarm optimisation (PSO), and PSO sliding mode controller techniques. The study investigates their performance under varying microgrid conditions, considering factors like weather and load variations. The simulation results provide a detailed comparative analysis of the power at the point of common coupling (PCC) for MPPT techniques at different time intervals. Both the P&O and PSO sliding mode recorded a power output of 287 kW, while PSO-ANFIS achieved a slightly higher power output of 294 kW. At 2.5 seconds, the P&O method recorded a power output of 712 kW, while the PSO sliding mode and the PSO-ANFIS techniques achieved 717 kW and 738 kW, respectively. Overall, the PSO-ANFIS technique consistently outperformed the other methods in terms of power output, demonstrating its effectiveness in maximising energy extraction and adaptability to dynamic conditions. These findings provide valuable insights for designing and implementing MPPT controllers in microgrid systems, emphasising the efficiency of the hybrid PSO-ANFIS technique in enhancing the overall performance and stability of renewable energy systems.

In this research work, three maximum power point tracking (MPPT) control algorithms based on power feedback are applied to two types of converters, namely Zeta and buck-boost, in the photovoltaic (PV) system. The PV system is intended to guarantee the power supply to a remote smart greenhouse. The control algorithms investigated are perturb and observe (P&O), incremental conductance (IncCond), and fuzzy logic (FLC) methods. Their performance are investigated and compared for each converter. It is found that the maximum power is always achieved, even during abrupt changes in irradiation or/and in temperature. The three methods have shown to have good performance; fast response time and very low steady-state error, with minor preference of the P&O method where the output voltage followed the input with high efficiency. The comparative study revealed that the power response time of the PV generator under stable conditions (constant irradiance and constant temperature) for P&O and IncCond was longer in the buck-boost converter than in the Zeta. On the other hand, the ripple level was better for the buck-boost. For the FLC, the maximum power was reached in a shorter time (short response time) with the smallest ripple. As for operation under variable environmental conditions, the Zeta outperformed the buck-boost for each control technique.

Abstract The article introduces a new model of a Reference Signal Tracking (RST) controller for the fractional order quantities. The controller is applied to an indirect field‐oriented control (IFOC) system used for the speed control of an asynchronous motor powered by a photovoltaic (PV) generator with a maximum power point tracking (MPPT) algorithm. This model utilizes two fractional order controllers: the fractional order proportional‐integral (FOPI) regulator and the fractional‐order integral‐proportional (FOIP) regulator. These controllers are used with the generalized predictive control (GPC) technique. The first step in the approach is to derive the equivalent digital RST controller's model from the FOPI and FOIP controller's transfer functions. The GPC technique converts the continuous‐time FOPI (and FOIP) controller into a discrete‐time version. This conversion ensures a fast response and effective disturbance rejection. Simulation tests are conducted to analyze the rotor speed and stator current ripples to evaluate the performance of the proposed method. The results demonstrate the effectiveness of the introduced scheme in achieving improved control performance in terms of response speed and disturbance rejection. The article presents a modified RST controller model based on the fractional order approach applied to an IFOC system for motor speed control driven by a photovoltaic generator. Using FOPI, FOIP controllers, and GPC contributes to enhanced control performance, as evidenced by the simulation results.

Abstract This study elucidates the use of optimization algorithms to identify the controller parameters employed in adjusting the current and voltage values of loads powered by solar energy systems and battery groups. Parameters for these controllers were independently derived using a combination of ant colony optimization with Levy flight, hybrid firefly‐particle swarm optimization, hybrid gravitation search algorithm‐particle swarm optimization, alongside the implementation of Jaya and whale optimization algorithms. The results from each method were juxtaposed for thorough analysis. In addition, three distinct Maximum Power Point Tracker (MPPT) algorithms were employed in the system: perturbation and observation, open circuit voltage, and incremental conductance (IC). To assess the system’s adaptability to real‐world conditions, it was tested against varying temperatures and sunlight levels. Moreover, potential changes in the loads were considered by varying the load. The efficacy of the controllers was examined by altering both the environment and load. The effectiveness of the controllers was examined by referring to the integral of time‐weighted absolute error value. The system was simulated using MATLAB/Simulink software. This study demonstrates that the fractional‐order PID controller achieves the most effective results, the Jaya algorithm provides the best controller parameters, and the IC technique exhibits the highest performance in MPPT.

Introduction. In recent times, there has been a growing popularity of photovoltaic (PV) systems, primarily due to their numerous advantages in the field of renewable energy. One crucial and challenging task in PV systems is tracking the maximum power point (MPP), which is essential for enhancing their efficiency. Aim. PV systems face two main challenges. Firstly, they exhibit low efficiency in generating electric power, particularly in situations of low irradiation. Secondly, there is a strong connection between the power output of solar arrays and the constantly changing weather conditions. This interdependence can lead to load mismatch, where the maximum power is not effectively extracted and delivered to the load. This problem is commonly referred to as the maximum power point tracking (MPPT) problem various control methods for MPPT have been suggested to optimize the peak power output and overall generation efficiency of PV systems. Methodology. This article presents a novel approach to maximize the efficiency of solar PV systems by tracking the MPP and dynamic response of the system is investigated. Originality. The technique involves a multivariate linear regression (MLR) machine learning algorithm to predict the MPP for any value of irradiance level and temperature, based on data collected from the solar PV generator specifications. This information is then used to calculate the duty ratio for the boost converter. Results. MATLAB/Simulink simulations and experimental results demonstrate that this approach consistently achieves a mean efficiency of over 96 % in the steady-state operation of the PV system, even under variable irradiance level and temperature. Practical value. The improved efficiency of 96 % of the proposed MLR based MPP in the steady-state operation extracting maximum from PV system, adds more value. The same is evidently proved by the hardware results.

Abstract Flexible power point tracking (FPPT) is a common and significate photovoltaic control problem under partial shading conditions. Based on CPP and MPP distribution analysis, both constant power point tracking and maximum power point tracking could be mathematically described by a single objective optimization. As one of the recent meta‐heuristic algorithms, which avoid the limitations of conventional scanning methods, the carnivorous plant algorithm (CPA) solves non‐convex optimization problems with fast speed, high accuracy, and simple calculation. However, it exhibits several drawbacks such as inappropriate parameters, over‐searching, and feasible solution ignored issues. Therefore, a global FPPT strategy based on modified CPA (mCPA) is proposed, which includes a search objective integration, efficient non‐convex search space skipping strategy, and adaptive tuning parameters according to sensitivity analysis. By statistical experiments compared with eight popular meta‐heuristic algorithms, the mCPA can correctly converge to the global MPP under various scenarios with the highest accuracy of 99.0%. Meanwhile, the observations of dynamic experiments demonstrate the effectiveness of the proposed strategy in terms of fast time response (0.5–3 s) for global FPPT under various uniform and non‐uniform insolation conditions.

Grid-connected photovoltaic (PV) systems are commonly designed for maximum energy production. However, as their presence grows, revised grid regulations increasingly require these systems to partially adhere to the primary frequency regulation (PFR) by reducing their power production when the grid frequency exceeds the nominal value. Nevertheless, full participation in PFR of PV systems, without battery storage, would require operating with a dedicated active power reserve to be utilized in the event of underfrequency conditions. This paper presents a model-based (MB) flexible power point tracking (FPPT) algorithm for PV systems. Results of a microgrid simulation show that the proposed algorithm enables a PV system with a nominal power of 100 kW to maintain a 20 kW active power reserve under various irradiation and temperature conditions, with a relative error lower than 3%. Furthermore, a simulation of the PV system assisting in primary frequency regulation is presented. Thanks to the proposed strategy, when employing the algorithm, the frequency deviation is reduced both in the event of underfrequency and overfrequency conditions. By enabling operation with a constant active power reserve, as well as a quick adjustment of the produced active power, in the event of frequency imbalance, the proposed MB algorithm is an interesting candidate for achieving complete PFR capabilities of PV systems.

This paper presents studies of the four maximum power point tracking (MPPT) algorithms of a single-phase grid-connected photovoltaic (PV) inverter based on single loop voltage control (VC) and cascaded voltage and current control (CVCC). The purpose of this research was to evaluate four techniques for maximum power tracking control: (1) the Perturbation and Observation (P&O) MPPT&VC, (2) the Incremental Conductance (InC) MPPT&VC, (3) the P&O MPPT&CVCC and (4) the InC MPPT&CVCC. The MPPT efficiency values of each technique were affected by sudden changes in various irradiances. The CVCC was found to reduce the oscillating PV power and have a faster response time of MPPT from the PV array than the VC configuration. The InC MPPT&CVCC technique can track maximum power when irradiance changes rapidly. The simulation results showed that the InC MPPT&CVCC technique can decrease oscillation at a steady state around the set point and has a fast response time of MPPT, reduced electrical power ripple, and less power loss. The average efficiency of MPPT was 99.98%.

In this work PV fed Modified Resonant Voltage Multiplier Rectifier (RVMR) has been proposed for the hybrid renewable energy system. PV source energy is maximized in the modified RVMR scheme by applying the perturb and observe (P&O) based MPPT method. To incorporate modified RVMR for PV grid-connected systems and observe the improvement in dynamic response and voltage gain. In the proposed work, voltage gain and efficiency are analyzed and evaluated in the MATLAB/SIMULINK environment.

Abstract This paper presents a novel maximum‐power‐point tracking algorithm of a vertical‐axis wind‐turbine (VAWT) generation system using neural network compensator on the basis of a digital signal processing chip. First, the mechanical power versus rotation‐speed curve of a 3‐kW VAWT generator was constructed by means of the measurement data in various wind speeds. Because the slope of the wind‐turbine output power is a non‐linear function of the generator output current, air density, wind speed, and the characteristics of the wind‐turbine generator, the analytic solution for the maximum power is difficult to obtain due to its complexity, nonlinearity, and uncertainties of parameters. The innovation of this study is to obtain the maximum power of the wind‐turbine system using a recurrent neural network (RNN) by transferring the maximum‐power‐point tracking problem into a unit‐step‐command regulation problem despite the variation of the wind speed, ambient air density, and the load electrical characteristics. The uncertainties in the system are compensated by the RNN, which is composed of three‐layer networks with three neurons and feedback loops in the hidden layer for capturing the characteristics of the wind‐turbine generator system. Without the necessity of wind speed sensor, it only needs the generator output current and rotation speed as the inputs of the input layer. This structure containing only six neurons totally is simpler than the existing work. The duty cycle of the boost converter is determined by a proportional‐integral controller, the parameters of which are determined via a genetic algorithm by the minimisation of a performance index function with the help of MATLAB simulation tool. From the simulation and experimental results, the validity of the proposed control scheme was verified under various wind speed conditions. The performance efficiency and the tip speed ratio in each case of the experiment is near the optimal values of 0.28 and 4.3, respectively. The output power achieves 2048.4 W at the wind speed of 11 m/s in the steady state.

The major shortcoming in the extraction of electrical energy occurs due to partial shading over a limited area of vast spread solar panels underpinning reduction of efficiency. A number of panels are interconnected in series and parallel to form a photovoltaic (PV) array for large power plants and a shadow over a single cell deteriorates overall performance. As a consequence, several peaks are added to the P-V curve causing hotspots in PV panels, degradation of the PV system, and collapse of tracking algorithms. In order to minimize such issues in PV panels, an effective optimization technique is developed by reconfiguring the panels which are capable of reaching the full global power point in a PV system under partial shading conditions. The study proposes particle swarm optimization (PSO) using PV characteristics of Quaid-e-Azam Solar Plant (QASP) in Punjab, Pakistan1. In PSO, electrical connections of PV modules are changed keeping their physical locations unaltered aiming to improve the performance of the PV system. After reconfiguration, the algorithm finds the best combination of PV modules by equalizing the row currents followed by the comparison of row current, voltages, and power of panels. The proposed PSO is proved to be an efficient method for reconfiguring PV modules in very less computational time by increasing the output power of shaded modules.

This article addresses the Particle Swarm Optimization with Incremental Conductance algorithm (PSO-InC) performance as the maximum power point tracking algorithm (MPPT), when the photovoltaic system is under different partial shading patterns. The PSO-InC MPPT combines the global-searching capabilities of particle swarm optimization with the smoother search feature of the incremental conductance algorithm. The analysis proceeds from a systematic approach involving the system simulation for different Environmental conditions. Besides that, to accurately represent the effects of the inherent stochasticity of the PSO, diverse starting conditions were considered in each case. The main contribution, in this sense, consists of highlighting some PSC patterns that might compromise the effectiveness of the PSO, even though the average efficacy on searching the global MPP (GMPP) is over 89%. For instance, based on one of the exploited PSC patterns, one may note a decrement of the PSO effectiveness to a level as lower as 36%. This article also presents simulation results highlighting the PSO-InC MPPT dynamics under transient and steady-state conditions.

Abstract This work presents the operation and control of a pico‐hydro‐solar photovoltaic (PV)‐battery energy storage (BES)‐based isolated renewable energy system (RES) feeding 3‐phase 4‐wire loads. For voltage regulation, to maintain frequency, and power quality improvement in this system, a 4‐leg VSC is used. The BES is connected to the DC‐link of the voltage source converter (VSC) through a bidirectional converter (BDC), which regulates the DC‐link voltage and controls the charging and discharging current of the battery. An advanced perturb and observe (AP&O)‐based MPPT control technique with drift free operation and capability to operate in the derated mode is adapted in this work. The VSC connected to PCC, injects or absorbs power from this system based on the difference of power between generation and the load. The modified complex co‐efficient filter (MCCF)‐based control technique monitors the power quality of this RES system and 4 leg VSC provides the source neutral current compensation. This control algorithm is used to extract the amplitude of the fundamental load current component with improved dynamic response, DC offset elimination and higher order harmonics removal capability. The ability of the presented control strategy for power quality improvement, power management, load balancing and neutral current compensation is reported in this work.

To provide a stable operation of a standalone microgrid based on the photovoltaic system in the most efficient way, various mechanisms and control strategies need to be engaged simultaneously. Modeling, simulation, and analysis of the microgrid system composed of PV generator, battery energy storage system (BESS), and DC/AC converter are presented in the paper. The PV generator operates in maximum power point (MPP) mode, while the BESS is deployed to enable power flow between the storage and consumers using the charge/discharge cycle of the battery. The maximum power point tracking (MPPT) control at the PV side, combined with battery control, is obtained by Perturb and Observe (P&O) and Fuzzy Logic Control (FLC) algorithms. Simulation based voltage control strategy is performed by using both DC/DC buck-boost converter and DC/AC converter with aim to obtain stable voltage for different power inputs. Modeling and simulations are performed in MATLAB/Simulink software. It is demonstrated that proposed methods ensure a stable microgrid operation and PV system operation in MPP mode. Both MPPT algorithms, P&O and FLC, provided accurate responses with very high efficiency above 95%.

The power output of the solar panels follows a power-voltage (P-V) characteristic containing only one Global Maximum Point (GMP) in the normal conditions. However, under Partial Shading Conditions (PSC), the unbalanced irradiance in the panels creates Local Maximum Points (LMP) in the P-V curve. Standard control techniques for Maximum Power Point Tracking (MPPT) can not properly locate the GMP, stagnating in LMPs and generating losses in the energy harvesting. Specific techniques to locate the GMP are presented in the literature. However, the condition to restart the GMP is not widely discussed. The main challenges of global search algorithms are related to the restarting conditions. Avoiding unnecessary searching and providing an assertive GMP restarting condition is crucial for PV systems operation. In every GMP search, the solar inverters oscillate the power exchanged with the grid, causing frequency and voltage variations depending on the size of the PV plant. This paper proposes a novel technique that uses a centralized controller to identify the shaded inverters, creating flags that locally start the GMP searching. The solution minimizes the number of times the search is performed by providing an assertive GMP restarting condition, saving energy, and avoiding unnecessary output power oscillation. The proposed control technique was evaluated using the data of a real 150-kW solar farm containing five inverters with two MPPT trackers each.

The objective of this work is to design a Nonlinear Observer used in a Cascade Control scheme for Maximum Power Point Tracking goals of a grid-tied single-phase photovoltaic inverter. The main contribution of this work is to employ a nonlinear observer to reduce the number of sensors of an AC-grid-tied single-stage PV system. The nonlinear observer design was developed using the Takagi-Sugeno PV system model and Linear Matrix Inequalities based on Lyapunov stability criteria. To validate the performance of the nonlinear observer-based cascade control, the results of a comparison between the PV system with observer (without DC voltage sensor) and a PV system with DC voltage sensor (without observer) are presented. A suitable PV power estimation with the nonlinear observer-based cascade control is achieved, which allowing a good performance of the MPPT algorithms. Perturb & Observe and Incremental Conductance MPPT algorithms were used.

This research articles proposes a comparative symmetric examination of the four maximum-power point-tracking algorithms under partial shaded conditions, including Conservative MPPT, Grey Wolf Optimization, and Fast Terminal Sliding Mode MPPT. In addition, the genetic algorithm MPPT, particle-swarm optimization MPPT, Grey Wolf optimization MPPT, and perturb and observe MPPT are included in this study. A smart method was to use Fast Terminal Sliding Mode Grey Wolf Optimization algorithms under partly shadowed situations on a global MPPT. This study included a GWO methodology that successfully set the efficient FTSM controller parameters such that the global maximum-power photovoltaic (PV) device point-tracking was monitored under partial shading. In the MATLAB setting and test performance, it was programmed for the suggested methodology of changing the shade pattern status dynamically. The findings were assessed and compared with other symmetric algorithms. Unlike other algorithms, the methodology used herein wasa less accurate way to monitor a global MPP. These methods were also evaluated and contrasted with PV arrays under various partial shadowing circumstances. The experimental investigations were used to verify the control techniques and stability analysis based on the asymmetric nonlinear load method of analysis in a closed-loop design.

This paper presents an analytical solution to the maximum power point tracking (MPPT) problem for photovoltaic (PV) applications in the form of an improved fractional method. The proposal makes use of a mathematical function that describes the relationship between power and voltage in a PV module in a neighborhood including the maximum power point (MPP). The function is generated by using only three points of the P–V curve. Next, by using geometrical relationships, an analytical value for the MPP can be obtained. The advantage of the proposed technique is that it provides an explicit mathematical expression for calculation of the voltage at the maximum power point (vMPP) with high accuracy. Even more, complex calculations, manufacturer data, the measurements of short circuit current (iSC) and open-circuit voltage (vOC) are not required, making the proposal less invasive than other solutions. The proposed method is validated using the P–V curve of one PV module. Experimental work demonstrates the speed in the calculation of vMPP and the feasibility of the proposed solution. In addition, this MPPT proposal requires only the typical and available measurements, namely, PV voltage and current. Consequently, the proposed method could be implemented in most PV applications.

An improved performance of a photovoltaic (PV) pumping system employing a synchronous reluctance motor (SynRM) under partial shading conditions is proposed. The system does not include the dc-dc converter that is predominantly being utilized for maximizing the output power of the PV array. In addition, storage batteries are also not contained. A conventional inverter connected directly to the PV array is used to drive the SynRM. Further, a control strategy is proposed to drive the inverter so that the maximum output power of the PV array is achieved while the SynRM is working at the maximum torque per Ampère condition. Consequently, this results in an improved system efficiency and cost. Moreover, two maximum power point tracking (MPPT) techniques are compared under uniform and partial shadow irradiation conditions. The first MPPT algorithm is based on the conventional perturbation and observation (P&O) method and the second one uses a differential evolution (DE) optimization technique. It is found that the DE optimization method leads to a higher PV output power than using the P&O method under the partial shadow condition. Hence, the pump flow rate is much higher. However, under a uniform irradiation level, the PV system provides the available maximum power using both MPPT techniques. The experimental measurements are obtained to validate the theoretical work.

Generating electric power from solar energy is a vastly growing technology worldwide. This paper investigates and evaluates the performance of a solar power generation system utilizing variable structure control with sliding mode for maximum power point tracking (MPPT). This controller is implemented on a buck-boost dc-dc power converter to track the maximum power point (MPP). The suggested controlled solar energy system also includes a dc-link capacitance, a voltage-source inverter, and a grid filter. Energy-based control is performed for the voltage of the dc-link capacitor. Space vector pulsewidth modulation (SVPWM) with current control in dq rotating frame is utilized to govern the inverter. The suggested system is simulated and subjected to various operating conditions. The results demonstrate the power captured from photovoltaic (PV) panels and delivered to the grid while tracking the MPP. For more confidence on the MPPT controller, practical experimentation is introduced using a real PV panel and power circuit with interfacing to a personal computer (PC). The proposed design is subjected to various experimental tests to ensure its validity.

The power output of the solar-photovoltaic (SPV) array is affected significantly by non-uniformly incident solar radiation. Such non-uniform illumination (NUI) condition(s) occur due to shadows of terrestrial structures (like buildings, trees, etc.) or through the creation of hotspot(s) in the contribution of moisture-dust accumulation, bird droppings, etc. which are predictable in nature. Furthermore, projected images of cloud(s) also cause NUI impact which is unpredictable and is/are subject to variables such as 3-D cloud coverage, cloud density, wind speed, etc. Literature also affirms that SPV array architecture plays a critical role in NUI effect mitigation. The novelty of this paper is the introduction of switching network system with the flexibility in the arrangement of the SPV panel series–parallel connections as per solar light intensity, NUI pattern, and data obtained from panel's peripheral light sensors. The field programmable reconfiguration strategy proposed here will get the power vs voltage curve and current vs voltage curve to identify maximum power-point. Multiple NUI patterns are simulated in MATLAB with variance in SPV array matrix and peripheral sensor matrix. This proposed reconfiguration method is cost-effective and includes embedded devices that could be widely implemented for domestic as well as commercial applications with the nested sub-array scheme.

Switched-boost inverter (SBI) is a single-stage power converter suitable for interfacing between photovoltaic (PV) arrays and loads. Although, it has many advantages such as it's not requiring an expensive complex dead-time circuitry, yet its duty ratio is limited between 0 and 0.5. This means that it has some difficulties in increasing both the DC-link output voltage and its AC-output voltage. So, most researchers proposed it for low-voltage power applications or using with step-up transformers. Accordingly, this study contributes towards improving the performance of the SBI for being used in the modified nanogrid within an open energy system. It introduces a novel approach closed-loop control technique to overcome most of the inverter drawbacks. Also, it enhances both the DC-link and the transformer-less rated AC output voltages to a sufficient value suitable for feeding domestic loads. And in the same time, the proposed robust controller utilizes a hysteresis band for balancing between voltage stability and PV-maximum power achievement. This research also includes a more sophisticated fast-charging slow-discharging control strategy for the battery energy management system that depends on a bidirectional buck-boost converter. Test results ensure the robustness of the proposed controller against sensitivity, nonlinearity, and time-variant parameters of the overall system.

The goal of this paper is to present an implementation method for a Maximum Power Point Tracking (MPPT) algorithm using an electronic load and custom designed LabView software. The aim is to facilitate the testing of the algorithm in laboratory conditions, before it can be used in the real world, improving development time, facilitating cost reduction and offering confidence in the design. This paper analyses the most suitable MPPT algorithms for testing purposes and suggests a complete software and hardware implementation for hardware in the loop testing which can facilitate in-depth evaluation of different algorithms. In order to replicate realistic stimuli for the MPPT algorithm, a solar array simulator has been designed. Using the proposed method, the performance of various MPPT algorithms for different atmospheric conditions can be evaluated. The hardware and software setup have been tested and validated in laboratory conditions. The experimental results have validated the proposed evaluation method and the good dynamic response of the MPPT algorithm.

In the last two decades, the maximum power point tracking (MPPT) methods for PV system is becoming very interesting subject. Among these methods there is Fuzzy-MPPT, which is mainly based on two inputs and at least 25 rules. This structure need more calculation time and not easy to be implemented in hardware. For these reasons and in order to facilitate the MPPT synthesis, this paper proposes an intelligent MPPT controller based on a single-input Takagi–Sugeno fuzzy logic controller (SI-TS-FLC) with three linguistic variables and three rules. The proposed controller is simulated using MATLAB-SIMULINK for a PV system, which consists of a PV generator, DC-DC converter, and resistive load under varied temperature and irradiance levels. An experimental study is conducted using DSPACE 1104 card real-time board under partial shading condition. Simulation and experimental results show that the proposed controller exhibits less settling time and lower overshoot than the commonly used perturb and observe (P&O) algorithm in the transient state and minimum oscillation around the optimal operating point. DOI: http://dx.doi.org/10.5755/j01.eie.24.4.21476

This paper introduces a new fuzzy logic controller (FLC) based photovoltaic (PV) maximum power point tracking (MPPT) optimized with the genetic algorithm (GA). Four FLCs with five and seven numbers of triangular (tri) and generalized bell (g-bell) membership functions (MFs) are analyzed. The performances of the analyzed algorithms have been compared with the appropriate performances of the classical perturb and observe (P&O) algorithm by using the following criteria: the rise time (tr), the tracking accuracy of the output power, and the energy yield. The results showed that the FL-based PV MPPT controller with seven triangular (7-tri) MFs provides the best steady-state performances.

The conveyance of steel-plates is one of the potential uses of the magnetic levitation technology in industry. How¬ever, the electromagnetic levitation systems inherently show non¬linear feature and are unstable without an active control. Well-known U-shaped or E-shaped electromagnets cannot provide redundant levitation with multiple degrees of freedom. In this paper, to achieve the full redundant levitation of the steel plate, a quadruple configuration of U shaped electromagnets has been proposed. To resolve the issue of instability and attain more robust levitation, a centralized control algorithm based on a modified PID controller (I PD) is designed for each degree of freedom by using the Manabe canonical polynomial technique. The model of the system is carried out using electromechanical energy conversion princi¬ples and verified by 3-D FEM analysis. An experimental bench is built up to test the system performance under trajectory tracking and external disturbance excitation. The results confirm the effectiveness of the proposed system and the control approach to obtain a full redundant levitation even in case of disturbances. The paper demonstrates the feasibility of the con¬veyance of steel plates by using the quadruple configuration of U-shaped electromagnets and shows the merits of I-PD controller both in stabilization and increased robust levitation.

Photovoltaic (PV) system has a great potential and it is installed more when compared with other renewable energy sources nowadays. However, the PV system cannot perform optimally due to its solid reliance on climate conditions. Due to this dependency, PV system does not operate at its maximum power point (MPP). Many MPP tracking methods have been proposed for this purpose. One of these is the Perturb and Observe Method (P&O) which is the most famous due to its simplicity, less cost and fast track. But it deviates from MPP in continuously changing weather conditions, especially in rapidly changing irradiance conditions. A new Maximum Power Point Tracking (MPPT) method, Tetra Point Perturb and Observe (TPPO), has been proposed to improve PV system performance in changing irradiance conditions and the effects on characteristic curves of PV array module due to varying irradiance are delineated. The Proposed MPPT method has shown better results in increasing the efficiency of a PV system.

Advancements in wind energy technologies have led wind turbines from fixed speed to variable speed operation. This paper introduces an innovative version of a variable-speed wind turbine based on a model predictive control (MPC) approach. The proposed approach provides maximum power point tracking (MPPT), whose main objective is to capture the maximum wind energy in spite of the variable nature of the wind’s speed. The proposed MPC approach also reduces the constraints of the two main functional parts of the wind turbine: the full load and partial load segments. The pitch angle for full load and the rotating force for the partial load have been fixed concurrently in order to balance power generation as well as to reduce the operations of the pitch angle. A mathematical analysis of the proposed system using state-space approach is introduced. The simulation results using MATLAB/SIMULINK show that the performance of the wind turbine with the MPC approach is improved compared to the traditional PID controller in both low and high wind speeds.

The performance of a photovoltaic system is subject to varying environmental conditions, and it becomes more challenging to track the maximum power point (MPP) and maintain the optimal performance when partial shading occurs. In this study, an enhanced MPP tracking (MPPT) method is proposed utilising the state estimation by the sequential Monte–Carlo (SMC) filtering, which is assisted by the prediction of MPP via an artificial neural network (ANN). A state-space model for the sequential estimation of MPP is proposed in the framework of incremental conductance MPPT approach, and the ANN model based on the observed voltage and current or irradiance data predicts the global MPP to refine the estimation by SMC. Moreover, a quick irradiance change detection method is applied, such that the SMC-based MPPT method resorts to the assistance from ANN only when partial shading is detected. Simulation results show that the proposed enhanced MPPT method achieves high efficiency and is robust to rapid irradiance change.

Wind energy conversion systems (WECSs) require a suitable control to maximise the power generated by wind turbines independently on the wind conditions. Variable-speed fixed-pitch wind turbines with doubly-fed induction generators (DGIG) are used in WECSs for their higher reliability and efficiency compared to variable-pitch wind turbine systems. This study proposes an effective control algorithm to maximise the efficiency of fixed-pitch wind turbines with DFIGs using particle swarm optimisation control to compensate for the errors in the estimation of the circuit parameters of the generator. The proposed control algorithm generates an optimal speed reference to optimise the mechanical power extracted from the wind and the optimal d-axis rotor current through stator reactive power management to minimise the electrical losses of the doubly-fed generator. The optimal speed reference is provided by a maximum power point tracking control below the rated wind speed and a soft-stalling control above the rated wind speed, while the optimal d-axis rotor current is searched by a particle swarm optimisation algorithm. The proposed control system has been verified by numerical simulations and it has been demonstrated that the energy generated for typical wind speed profiles is greater than that of a traditional control based on a model-based loss minimisation.

Power quality and current limitation are the most important aspects of the grid-connected power converters under fault. Since the distributed energy resources are widely used, fault management strategy is important for micro-grids applications. This paper presents a new control strategy for low-voltage ride-through for 3-phase grid-connected photovoltaic systems. The proposed method, which is designed in a synchronous frame using positive and negative sequence components, can protect the inverter from overcurrent failure under both symmetrical and unsymmetrical faults and provides reactive power support. The method does not require a hard switch to switch from MPPT to a non-MPPT algorithm, which ensures a smooth transition.

This article proposes a new control paradigm for the seamless operation of a permanent magnet synchronous generator (PMSG) based wind energy conversion system (WECS) in both islanded and grid-connected modes. Conventionally, grid-connected WECS are controlled to extract the maximum power from the wind, known as maximum power point tracking (MPPT). However, in islanded operation, the objective is to control the power generated from the WECS to match the load demand, which here is called load following power generation (LFPG). This article proposes a power management system (PMS) which integrates the MPPT and LFPG capabilities of the WECS into a single-control paradigm. This enables the WECS to seamlessly achieve MPPT in grid operation, LFPG in islanded mode and low-voltage ride-through (LVRT) during fault. The proposed scheme is validated using MATLAB/SIMULINK simulations.

Linear alternators (LAs) are widely applied in many energy conversion systems based on pressure waves, to avoid linear to rotary conversion mechanisms. The control of the LA is the key element to maximise the system's electric power and efficiency. However, the LA resonant frequency cannot be accurately controlled by mechanical design due to parameter tolerance. Furthermore, the operating frequency is generally not strictly constant in real-time, making maximum power point tracking (MPPT) hard to achieve. Two MPPT strategies are proposed here to adjust the electronic stiffness amount in real time. They are hereafter referred to as symmetrical signal injection method and electronic stiffness perturbation method. The latter one is selected and validated via simulation studies.

Crack is one critical factor that degrades the performance of photovoltaic (PV) panels. To gain a better understanding of the impacts of cracks appeared on PVs and also to mitigate it, its failure mechanism, detrimental effects, criticality, and potential risks on independent PV panels are firstly reviewed in this study. An experimental study which investigates the degree of series connected and parallel connected PV strings which are affected by cracked cells are presented. A comparison of impacts of the partially shaded PV panel string and cracked cells happened to the PV panel string is given to evaluate their criticality levels. The experimental results show that the series connected PV panel string is strongly affected once the cell is seriously cracked, as the current generation capability is clamped. Partial shading, however, shows better performance. In addition, though the overall power the parallel connected PV string is reduced, it is less affected by the cracked cells compared to the series connected one. Lastly, a bypass diode is added to a series connected PV panel string with cracked cells, and the experimental results show that it can be an effective way to minimise the negative impacts of cracks.

Wind energy is an important renewable source with a stochastic nature. To capture this energy, variable speed generators are installed in wind towers and different maximum power point (MPP) tracking (MPPT) strategies have been developed in literature to maximise the output power. However, in gusty weather, wind turbines fail to track the optimum operating point due to their relatively high inertia. This paper proposes an innovative MPPT strategy to capture the energy of wind gusts. The developed controller consists of a conventional TSR control together with a bidirectional controller, which takes over the control of the rectifier under varying wind condition. The simulation results show an overall efficiency improvement and more stability for the proposed strategy.

Here, a novel photovoltaic power integration system based on LLC resonant converters is proposed for medium-voltage DC distribution network, which exhibits a feasible and efficient solution for large-scale solar energy integrating into DC grids. A control system with the voltage signal generation part and the frequency control part is designed to realise the current and voltage sharing of the sub-module, while achieving the maximum power point tracking (MPPT) of the PV arrays. To verify the practicability of the system with many switching devices, this paper proposes an optimisation model to accelerate the simulation speed of this system without losing accuracy. Finally, the feasibility of the proposed system is validated by the simulation based on PSCAD/EMTDC.

The maximum power point tracking (MPPT) mode is widely applied in photovoltaic (PV) power generation system. In this article, instead of MPPT, a novel control strategy of grid-connected PV power supply for frequency regulation is proposed. First, the static frequency characteristic curve of PV plant is proposed, and a method of synthesising the PV power output power–voltage characteristic curve and static frequency characteristic curve into frequency regulation curve of PV power supply is introduced. So the PV plant can participate in frequency regulation of the system. Through simulation analysis in power systems computer aided design (PSCAD)/electromagnetic transients including DC (EMTDC), PV plant realises the function of frequency regulation when load changes, so the variation of system frequency can be reduced and the frequency stability of power system can be improved, and the effectiveness of the strategy is verified.

Aiming at the voltage rise due to the photovoltaic generation system (PVGS) at the point of common coupling (PCC), the cause is analysed with power transmission theory. Here, the principle and strategies of voltage regulation based on active and reactive power in PVGS are proposed. In this control strategy, the voltage of PCC is tracked by PV system in real time. When the voltage of PCC is normal, inverter will output in the way of maximum power point tracking (MPPT).When the voltage of PCC exceeds the upper limit, the inverter will regulate the voltage using the remaining capacity preferentially. If the remaining capacity is insufficient, the inverter will adjust active output and dynamically calculate the active and reactive best out values. In this way, the voltage of PCC is adjusted in an appropriate range to achieve the active output minimisation and reactive output optimisation of inverter. The experimental results validate the effectiveness of the proposed control scheme for voltage regulation.

This paper presents the analysis of the DC-link voltage switching ripple in five-phase PWM voltage source inverters with balanced load. The analysis is particularly important for the design and selection of a DC-link capacitor making it possible to meet desired electrical performance of the inverter system. Simple and practical equation for designing the DC-link capacitor is proposed relating the value of capacitance to the maximum value (peak-to-peak) of the DC-link voltage ripple. The amplitude of the DC-link voltage switching ripple is analytically derived as a function of modulation index, and the amplitude of the output current and phase angle. In order to show peak-to-peak voltage ripple distribution, different diagrams are introduced. Reference is made to continuous symmetric centred PWM modulation (i.e., space vector modulation SVM). In order to verify proposed developments, simulations have been carried out by Matlab/Simulink considering full range of modulation index and output phase angle.

The photoelectric conversion efficiency of photovoltaic cells is mainly affected by temperature and irradiance. In order to promote the development of photovoltaic power generation, it is necessary to improve the photoelectric conversion efficiency of photovoltaic cells. This paper combines two major factors that affect photovoltaic cells, a maximum power point tracking scheme based on large variation GA-RBF network is proposed. The system used in this scheme is simulated through Matlab. The simulation results show that the new maximum power point tracking scheme has higher accuracy and rapidity, the photoelectric conversion efficiency of the photovoltaic cell is greatly improved.

The distribution network connected with photovoltaic (PV) power generation may show high voltage under strong light and low voltage under weak light. The influence of distributed PV generation on the grid voltage profile is analysed first, and then, the sensitivity of the grid voltage to the PV inverter output power is deduced. Aiming at overhead line distribution network, the local voltage regulation strategy based on the power control of the grid-connected PV inverter is proposed. The PV inverter works under the maximum power point tracking (MPPT) mode with unity power factor when the grid voltage is at the normal level. However, when the voltage is higher than its upper limit, the grid-connected PV inverter will be co-ordinately controlled to output limited active power and necessary reactive power to restrain the line voltage. Also, when the voltage is below than the lower limit, only the reactive power of the grid-connected PV inverter was controlled to sustain the line voltage, and the reactive power is no more than the residual capacity of the grid-connected PV inverter operated in the MPPT mode. Simulation and results show that the voltage quality of the distribution network with PV generation is improved by using the voltage regulation strategy presented in this study.

This paper proposes a maximum power point tracking (MPPT) method with partial shading (PS) detection based on modified PI incremental conductance (IC) for photovoltaic inverters. To accurately trigger the algorithm, a PS detecting approach based on voltage deviation is derived through the comparison of voltage and current characteristics under uniform and non-uniform insolation. To track the global maximum power point (GMPP) precisely and fast, a global search scheme considering appropriate voltage reference, search direction and termination criteria is presented. The modified PI-based IC method is implemented in the local search process. In order to verify the effectiveness of the algorithm, the proposed method is utilised in the two-stage grid-connected photovoltaic inverters built in MATLAB/Simulink. The performance of the scheme is compared with the traditional IC method under step-changing and gradual-changing insolation and various temperature. In all simulation cases, the proposed approach can identify the PS with multiple local maxima, accurately trigger the global search process and track the GMPP. The search periods are around 0.1–0.2 s, and the efficiencies of PV generation under steady state are normally above 99.5%. The presented method can improve the efficiency of distributed and centralised PV system.

Existence PV generation mostly operates under the Maximum Power Point Tracking (MPPT) mode and has no ability to increase or decrease active power, accordingly, PV generation does not participate in grid frequency regulation. Due to an increasing penetration of grid-connected PV generation, when a frequency contingency event occurs, grid may have neither enough inertia response nor governor support and frequency deviation may have a risk of exceeding the limit. Therefore, a novel adapted de-loading control strategy without MPPT for grid-connected inverters is proposed here. This control strategy provides a reserve power in PV system to meet the frequency control demand and an online output Active Power-Voltage Matching (APVM) technique, which is generated as a control flowchart, is implemented in this control strategy to make it possible to adjust PV output voltage performance matching different active power demand with different operation modes. The proposed control strategy of PVs is simulated using PSCAD/EMTDC Software. Results verify the correctness and effectiveness of the proposed adapted de-loading control strategy under several operating conditions.

The study on the stability of DC bus voltage is one of the key issues for researching independent DC microgrid. This paper has studied the independent DC microgrid with photovoltaic and energy-storage systems. The variable step incremental conductance method was taken to realise maximum power point tracking (MPPT). The self-adaptive Fuzzy-PI controller was designed to optimise the traditional double closed-loop control strategy. The energy management system was built to achieve coordinated control of the independent DC microgrid. The simulation results show that the improved strategy can get better robustness and system performance comparing with the traditional PI method.

In this study, a three-phase diode bridge rectifier and a single-phase voltage source inverter topology has been proposed for feeding single-phase utility grid employing a three-phase induction generator fed from wind energy. A self-excited induction generator configuration has been chosen for wide speed operation of wind turbine system, which gives the scope for extracting maximum power available in the wind. In addition to maximum power point tracking (MPPT), the generator can be loaded to its rated capacity for feeding single-phase utility grid using a three-phase induction machine, whereas it is not possible with existing configurations because of the absence of power converters. For the proposed system, MPPT algorithm has been devised by continuously monitoring the grid current and a proportional resonant controller has been employed for grid synchronisation of voltage source inverter with single-phase grid. A MATLAB/Simulink model of the proposed system has been developed to ascertain its successful working by predetermining the overall performance characteristics. The present proposal has also been tested with sag, swell and distortion in the grid voltage. The control strategy has been implemented using field programmable gate array (FPGA) controller with modularised programming approach. The efficacy of the system has been demonstrated with the results obtained from an experimental set-up in the laboratory.

Maximum power point trackers (MPPTs) play an essential role in extracting power from photovoltaic (PV) panels as they make the solar panels to operate at the maximum power point (MPP) whatever the changes of environmental conditions are. For this reason, they take an important place in the increase of PV system efficiency. MPPTs are driven by MPPT algorithms and a number of MPPT algorithms are proposed in the literature. The comparison of the MPPT algorithms in literature are made by a sun simulator based test system under laboratory conditions for short durations. However, in this study, the performances of four most commonly used MPPT algorithms are compared under real environmental conditions for longer periods. A dual identical experimental setup is designed to make a comparison between two the considered MPPT algorithms as synchronized. As a result of this study, the ranking among these algorithms are presented and the results show that Incremental Conductance (IC) algorithm gives the best performance.

This paper introduces a novel multiport power converter with modular architecture for photovoltaic (PV)-battery based power systems. Compared to conventional centralized multiport converters, the proposed converter significantly improves the utilization of PV available energy and battery capacity as it does not require a high number of series-connected PV and battery modules. The proposed converter also eliminates the need for additional battery cell/module equalizer circuitry by being able to implement directly energy management strategies that consider the different capabilities of battery modules to ensure charge/stress balancing. This makes it a promising solution for interfacing second-life batteries or for systems that utilize batteries with a high degree of mismatch. The modularity of the proposed converter enhances system reliability and fault tolerance and reduces the power/voltage ratings of the power electronic devices. The converter modes of operation, control strategy and design considerations are discussed. A 75 V/1 kW integrated PV-battery power system prototype is built and tested to validate the concept.

Maximum power point tracking is a mature control issue for wind, solar and other systems. On the other hand, being a relatively new technology, detailed discussion on power tracking of hydrokinetic energy conversion systems are generally not available. Prior to developing sophisticated control schemes for use in hydrokinetic systems, existing know-how in wind or solar technologies can be explored. In this study, a comparative evaluation of three generic classes of maximum power point scheme is carried out. These schemes are (a) tip speed ratio control, (b) power signal feedback control, and (c) hill climbing search control. In addition, a novel concept for maximum power point tracking: namely, extremum seeking control is introduced. Detailed and validated system models are used in a simulation environment. Potential advantages and drawbacks of each of these schemes are summarised.

This study proposed an adaptive double-integral-sliding-mode-controller-maximum-power-point tracker (DISMC-MPPT) for maximum-power-point (MPP) tracking of a photovoltaic (PV) system. The objective of this study is to design a DISMC-MPPT with a new adaptive double-integral-sliding surface in order that MPP tracking is achieved with reduced chattering and steady-state error in the output voltage or current. The proposed adaptive DISMC-MPPT possesses a very simple and efficient PWM-based control structure that keeps switching frequency constant. The controller is designed considering the reaching and stability conditions to provide robustness and stability. The performance of the proposed adaptive DISMC-MPPT is verified through both MATLAB/Simulink simulation and experiment using a 0.2 kW prototype PV system. From the obtained results, it is found out that this DISMC-MPPT is found to be more efficient compared with that of Tan's and Jiao's DISMC-MPPTs.