Showing papers on "Maximum power principle published in 2021"

DMPPT Control of Photovoltaic Microgrid Based on Improved Sparrow Search Algorithm

Abstract: There are some problems in the photovoltaic microgrid system due to the solar irradiance-change environment, such as power fluctuation, which leads to larger power imbalance and affects the stable operation of the microgrid. Aiming at the problems of power mismatch loss under partial shading in photovoltaic microgrid systems, this paper proposed a distributed maximum power point tracking (DMPPT) approach based on an improved sparrow search algorithm (ISSA). First, used the center of gravity reverse learning mechanism to initialize the population, so that the population has a better spatial solution distribution; Secondly, the learning coefficient was introduced in the location update part of the discoverer to improve the global search ability of the algorithm; Simultaneously used the mutation operator to improve the position update of the joiner and avoid the algorithm falling into the local extreme value. The results of the model in Matlab showed that the ISSA can track the maximum power point(MPP) more accurately and quickly than the perturbation observation method (P&O) and the particle swarm optimization (PSO) algorithm, and had good steady-state performance.

An Improved Adaptive Control Strategy in Grid-Tied PV System With Active Power Filter for Power Quality Enhancement

Abstract: This article investigates the power quality enhancement of a grid-tied photovoltaic (PV) distribution system by employing a fuzzy logic proportional–integrator–derivative multiple complex coefficient filter multiple second-order generalized integrator frequency-locked loop (FLPID-MCCF-MSOGI-FLL) hybrid control scheme based shunt active power filter. The MSOGI-FLL reference current generation strategy is implemented to mitigate the current harmonics by extracting the fundamental constituents (FCs) from the nonlinear load currents, whereas an MCCF is employed to separate the FC from the distorted grid voltages and eliminates the voltage harmonics during extremely polluted grid voltage condition. The main objective of using FLPID is to maintain the stable power between dc and ac sides by regulating the dc-link voltage constant under transient conditions. To track the maximum power from the PV panel under varying environmental condition, the particle swarm optimization based perturb and observe technique is used in this article. The comparative analysis is analyzed to check the effectiveness of the proposed hybrid control scheme with existing and adaptive control techniques in respect of power quality, better dc offset rejection, better FC and frequency extraction, and grid synchronization. The system with the proposed control scheme is simulated on MATLAB/Simulink and validated in a real-time field-programmable gate array platform under different test scenarios. In conclusion, the harmonic content of grid currents and voltages is found well within the IEEE-519 standard limits.

Improved Perturb and Observation Maximum Power Point Tracking Technique for Solar Photovoltaic Power Generation Systems

Abstract: The primary concerns in the practical photovoltaic (PV) system are the power reduction due to the change in operating conditions, such as the temperature or irradiance, the high computation burden due to the modern maximum power point tracking (MPPT) mechanisms, and to maximize the PV array output during the rapid change in weather conditions. The conventional perturb and observation (P&O) technique is preferred in most of the PV systems. Nevertheless, it undergoes false tracking of maximum power point (MPP) during the rapid change in solar insolation due to the wrong decision in the duty cycle. To avoid the computational burden and drift effect, this article presents a simple and enhanced P&O MPPT technique. The proposed technique is enhanced by including the change in current ( dI ), in addition to the changes in output voltage and output power of the PV module. The effect of including the dI profile with the traditional method is explained with the fixed and variable step-size methods. The mathematical expression for the drift-free condition is derived. The traditional boost converter is considered for validating the effectiveness of the proposed methods by employing the direct duty cycle technique. The proposed algorithm is simulated using MATLAB/Simulink and validated under various scenarios with the developed laboratory prototype in terms of drift-free characteristics and tracking efficiency. The result proves that the proposed technique can track the MPP accurately under various operating conditions.

Promising MPPT Methods Combining Metaheuristic, Fuzzy-Logic and ANN Techniques for Grid-Connected Photovoltaic.

Abstract: This paper addresses the improvement of tracking of the maximum power point upon the variations of the environmental conditions and hence improving photovoltaic efficiency Rather than the traditional methods of maximum power point tracking, artificial intelligence is utilized to design a high-performance maximum power point tracking control system In this paper, two artificial intelligence-based maximum power point tracking systems are proposed for grid-connected photovoltaic units The first design is based on an optimized fuzzy logic control using genetic algorithm and particle swarm optimization for the maximum power point tracking system In turn, the second design depends on the genetic algorithm-based artificial neural network Each of the two artificial intelligence-based systems has its privileged response according to the solar radiation and temperature levels Then, a novel combination of the two designs is introduced to maximize the efficiency of the maximum power point tracking system The novelty of this paper is to employ the metaheuristic optimization technique with the well-known artificial intelligence techniques to provide a better tracking system to be used to harvest the maximum possible power from photovoltaic (PV) arrays To affirm the efficiency of the proposed tracking systems, their simulation results are compared with some conventional tracking methods from the literature under different conditions The findings emphasize their superiority in terms of tracking speed and output DC power, which also improve photovoltaic system efficiency

Most Valuable Player Algorithm based Maximum Power Point Tracking for a Partially Shaded PV Generation System

Abstract: Inclusion of bypass diodes at the output terminal of the PV array mitigates the effect of partial shading (PS) but causes multiple peaks of power at the output. The conventional hill climbing and perturb and observe algorithms cannot track the optimal point during partial shading phenomena for multiple peaks corresponding to the different shading pattern on the Power-Voltage (P-V) curve. Fuzzy logic controller and artificial neural network-based methods for Maximum Power Point Tracking (MPPT) provide satisfactory results but at the cost of increased memory and computational burden. Recent work to incorporate exploration and exploitation phenomena of nature-inspired algorithms to track optimal power point have shown encouraging results by preventing convergence to local maxima and posing less burden on the processor. However, due to performance variation between different algorithms of this category newer algorithms with improved performances are still a requirement. In this paper, a novel most valuable player algorithm (MVPA) has been used to track the optimal operation point for extracting maximum power from a solar PV system. The algorithm's performance is compared with the commonly employed particle swarm optimization (PSO) and the recently proposed Jaya algorithm's modified form. It is observed that the proposed algorithm outperformed both the algorithms with a considerable improvement in terms of tracking speed, power tracking efficiency, robustness, faster decision for convergence after tracking the maximum power and lesser number of power fluctuations for different shading patterns.

Primary frequency control techniques for large-scale PV-integrated power systems: A review

Abstract: The increasing amount of solar photovoltaic (PV) penetration substitutes a large portion of conventional synchronous power plants. During the peak power production period, it may lead to reduced the rotational inertia and thereby deteriorate inherent inertial response of the power system. It is assumed that the conventional generators mainly provide the necessary frequency regulation service. Conversely most of the PV inverters are designed to operate in the maximum power point (MPP) to generate the maximum revenue. Due to the synchronization mechanism, an inherent close coupling exists between the speed of the conventional generator and the grid frequency. On the contrary, the inverter interface completely decouples PV from the grid. As a result, PV systems do not inherently contribute to the system inertia. Therefore, it is important to investigate the impact of reduced inertia on stability, control and operation of a power system. This paper presents an extensive review of research related to the main power system operational challenges with respect to the massive deployment of PV sources. Besides, this paper aims to provide a comprehensive review of various control approaches and applications of battery energy storage system (BESS) to improve the inertial response of a low-inertia power system.

Optimized Power Control Design for Over-the-Air Federated Edge Learning

Abstract: Over-the-air federated edge learning (Air-FEEL) has emerged as a communication-efficient solution to enable distributed machine learning over edge devices by using their data locally to preserve the privacy. By exploiting the waveform superposition property of wireless channels, Air-FEEL allows the “one-shot” over-the-air aggregation of gradient-updates to enhance the communication efficiency, but at the cost of a compromised learning performance due to the aggregation errors caused by channel fading and noise. This paper investigates the transmission power control to combat against such aggregation errors in Air-FEEL. Different from conventional power control designs (e.g., to minimize the individual mean squared error (MSE) of the over-the-air aggregation at each round), we consider a new power control design aiming at directly maximizing the convergence speed. Towards this end, we first analyze the convergence behavior of Air-FEEL (in terms of the optimality gap) subject to aggregation errors at different communication rounds. It is revealed that if the aggregation estimates are unbiased, then the training algorithm would converge exactly to the optimal point with mild conditions; while if they are biased, then the algorithm would converge with an error floor determined by the accumulated estimate bias over communication rounds. Next, building upon the convergence results, we optimize the power control to directly minimize the derived optimality gaps under the cases without and with unbiased aggregation constraints, subject to a set of average and maximum power constraints at individual edge devices. We transform both problems into convex forms, and obtain their structured optimal solutions, both appearing in a form of regularized channel inversion, by using the Lagrangian duality method. Finally, numerical results show that the proposed power control policies achieve significantly faster convergence for Air-FEEL, as compared with benchmark policies with fixed power transmission or conventional MSE minimization.

Analysis, Design, and Implementation of a Differential Power Processing DMPPT With Multiple Buck–Boost Choppers for Photovoltaic Module

Abstract: Submodule mismatch has become the major cause of losses in the photovoltaic (PV) power generation system, which has been an important factor restricting the development of PV technology. Differential power processing (DPP) architecture is increasingly employed in PV distributed MPPT (DMPPT) due to its low processed power. In order to improve the PV utilization efficiency, minimize the power loss and reduce the system cost, a novel scheme based on DPP is introduced in this article. The proposed DPP converter is composed of multiple buck–boost choppers, and a multidimensional perturb and observe (MPO) algorithm is proposed to achieve true DMPPT through correcting the voltage of each submodule to its voltage at the maximum power point by using a single current sensor. A prototype with multiple buck–boost choppers for 36 V/200 W PV module is designed and built to verify the operating principle and evaluate the performance of the proposed DPP converter and DMPPT strategy, and the experimental results show that the prototype is low-cost and effectively improves system efficiency.

Coordinated Power Management and Control of Standalone PV-Hybrid System With Modified IWO-Based MPPT

Abstract: To augment the photovoltaic (PV) power generation conversion, a maximum power point tracking (MPPT) technique plays a very significant role. This article introduces a hybrid MPPT algorithm integrating modified invasive weed optimization (MIWO) and perturb and observe (P&O) technique under the rapid weather change and partial shading scenarios for the efficient extraction of the maximum power from the standalone PV-based hybrid system. MIWO handles the initial stages of MPPT followed by the application of the P&O algorithm at the final stages in view of acquiring the rapid global peak and maximal PV power. The studied microgrid comprises of the PV system, battery, electrolyzer, fuel cell, and load. A coordinated dc-voltage regulation and power management strategy between each subsystem of the hybrid microgrid is implemented to save the battery from the undesirable charging/discharging operation. Additionally, with the monitoring of dc voltage, the dc/dc converter associated with the battery and dc link plays as an MPPT circuit of the PV without the requirement of an extra dedicated circuit. Takagi–Sugeno (TS) fuzzy controller is adopted for suppressing/mitigating the voltage oscillations of the microgrid during the variations in the solar irradiance/temperature and power demand. The results clearly exhibit the superior performance of the proposed methodology compared with some of the existing techniques.

An Energy Management System Design Using Fuzzy Logic Control: Smoothing the Grid Power Profile of a Residential Electro-Thermal Microgrid

Abstract: This work deals with the design of a Fuzzy Logic Control (FLC) based Energy Management System (EMS) for smoothing the grid power profile of a grid-connected electro-thermal microgrid. The case study aims to design an Energy Management System (EMS) to reduce the impact on the grid power when renewable energy sources are incorporated to pre-existing grid-connected household appliances. The scenario considers a residential microgrid comprising photovoltaic and wind generators, flat-plate collectors, electric and thermal loads and electrical and thermal energy storage systems and assumes that neither renewable generation nor the electrical and thermal load demands are controllable. The EMS is built through two low-complexity FLC blocks of only 25 rules each. The first one is in charge of smoothing the power profile exchanged with the grid, whereas the second FLC block drives the power of the Electrical Water Heater (EWH). The EMS uses the forecast of the electrical and thermal power balance between generation and consumption to predict the microgrid behavior, for each 15-minute interval, over the next 12 hours. Simulations results, using real one-year measured data show that the proposed EMS design achieves 11.4% reduction of the maximum power absorbed from the grid and an outstanding reduction of the grid power profile ramp-rates when compared with other state-of-the-art studies.

Novel Control Strategy for Enhancing Microgrid Operation Connected to Photovoltaic Generation and Energy Storage Systems

Abstract: Recently, the penetration of energy storage systems and photovoltaics has been significantly expanded worldwide. In this regard, this paper presents the enhanced operation and control of DC microgrid systems, which are based on photovoltaic modules, battery storage systems, and DC load. DC–DC and DC–AC converters are coordinated and controlled to achieve DC voltage stability in the microgrid. To achieve such an ambitious target, the system is widely operated in two different modes: stand-alone and grid-connected modes. The novel control strategy enables maximum power generation from the photovoltaic system across different techniques for operating the microgrid. Six different cases are simulated and analyzed using the MATLAB/Simulink platform while varying irradiance levels and consequently varying photovoltaic generation. The proposed system achieves voltage and power stability at different load demands. It is illustrated that the grid-tied mode of operation regulated by voltage source converter control offers more stability than the islanded mode. In general, the proposed battery converter control introduces a stable operation and regulated DC voltage but with few voltage spikes. The merit of the integrated DC microgrid with batteries is to attain further flexibility and reliability through balancing power demand and generation. The simulation results also show the system can operate properly in normal or abnormal cases, thanks to the proposed control strategy, which can regulate the voltage stability of the DC bus in the microgrid with energy storage systems and photovoltaics.

Optimized Fuzzy Controller for MPPT of Grid-connected PV Systems in Rapidly Changing Atmospheric Conditions

Abstract: Due to nonlinear behavior of power production of photovoltaic (PV) systems, it is necessary to apply the maximum power point tracking (MPPT) techniques to generate the maximum power. The conventional MPPT methods do not function properly in rapidly changing atmospheric conditions. In this study, a fuzzy logic controller (FLC) optimized by a combination of particle swarm optimization (PSO) and genetic algorithm (GA) is proposed to obtain the maximum power point (MPP). The proposed FLC uses the ratio of power variations to voltage variations and the derivative of power variations to voltage variations as inputs and uses the duty cycle as the output. The range of changes in fuzzy membership functions and fuzzy rules are proposed as an optimization problem optimized by the PSO-GA. The proposed design is validated for MPPT of a PV system using MATLAB/Simulink software. The results indicate a better performance of the proposed FLC compared to the common methods.

A High-Performance Global Maximum Power Point Tracker of PV System for Rapidly Changing Partial Shading Conditions

Abstract: This article proposes a fast and efficient maximum power point tracker (MPPT) for photovoltaic (PV) systems under rapidly changing partial shading conditions. An intelligent mechanism is adopted to systematically schedule the search for the global maximum power point (GMPP) on the P–V curve. As a result, the voltage track, i.e., the path length that the operating point traverses along the voltage axis of the curve (until it converges to GMPP), is reduced. The search region is further minimized using a novel skipping scheme, where the voltage section that does not contain GMPP is discarded. The superiority of the proposed scheme is evaluated against two recent algorithms, namely, the maximum power trapezium and the flower pollination MPPT. The performance is analyzed in terms of convergence time, voltage track, and transient efficiency. The MATLAB simulation is verified experimentally using a PV array simulator, in conjunction with a buck–boost converter. The competing MPPT algorithms are implemented using the TMS320F240 DSP on the dSPACE DS1104 platform. The results indicate that under the same operating and shading conditions, the proposed scheme is the fastest and most reliable and exhibits the highest overall transient efficiency.

Novel Spline-MPPT Technique for Photovoltaic Systems Under Uniform Irradiance and Partial Shading Conditions

Abstract: Different maximum power point tracking (MPPT) techniques used in photovoltaic (PV) systems are evaluated based on several criteria such as simplicity, speed, and accuracy. There are tradeoffs among these criteria, and generally higher accuracy is achieved at the expense of speed and simplicity. This article aims to introduce Spline-MPPT technique as a fast, accurate, and uncomplicated method to find the maximum power point of PV systems under uniform irradiance and partial shading condition (PSC) in which characteristics of the PV string are distorted. The proposed method is based on cubic spline interpolation that defines an approximate function for a few sample points. Several interpolation-based methods have been proposed in the literature to find MPP under uniform irradiance. They, however, are incapable of finding the global maximum power point (GMPP) under partial shading conditions. The Spline-MPPT technique only uses a small number of current and voltage samples to estimate the MPP of the system and maintain on this point as long as environmental conditions remain unchanged. Simulation results attest to the superiority of the proposed method.

Control for Power Converter of Small-Scale Switched Reluctance Wind Power Generator

Abstract: With the rapid development of wind power generation technology worldwide, the influence of intermittent and fluctuating characteristics of wind power generation on the microgrid and load is attracting a lot of attention along with its increasing penetration. Aimed at solving the problem that only wind speed variation is considered in the generation plan of traditional small-scale wind power generation applications, this article presents a set of control schemes for the switched-reluctance-generator-based small-scale wind power generation system with the integrated energy storage system. Considering the possibility of off-grid operation of small-scale wind power generation systems in the areas where the grid is weak or even uncovered, the proposed control scheme increases the consideration of dynamic changes in load and energy storage unit. To improve the utilization efficiency of small-scale wind power generation, a step control scheme is proposed combining maximum power tracking control with power balance control. The two-stage inverter is established to generate ac 110V/60Hz outputs by voltage closed-loop control in boost circuit of front stage and proportional integral (PI) control in the inverter circuit of the second stage. Finally, the effectiveness of the proposed control schemes is verified experimentally.

Maximum Power Point Tracking Injection Method for Islanding Detection of Grid-Connected Photovoltaic Systems in Microgrid

Abstract: This paper proposes a novel islanding detection method (IDM) for grid-connected photovoltaic systems (GCPVSs) through a disturbance injection in the maximum power point tracking (MPPT) algorithm. When an absolute deviation of the output voltage exceeds a threshold, the applied disturbance shifts system operating point from its maximum power point (MPP) condition. This leads to a sharp active power output reduction and consequently, a significant voltage drop in islanded mode beyond the standard voltage limit. The proposed algorithm is defined in a way that the distributed generator (DG) can be restored to MPP after islanding classification. It is thereby effective in microgrid in where the power injection at maximum level to cater the critical loads and maintain the stability of the isolated area are pursued. An intentional time delay has also been considered to avoid nuisance tripping in short-circuit faults which do not require tripping. The assessment of the proposed technique has been conducted for a sample network containing two GCPVSs in a real-time platform including actual relays in hardware-in-the-loop (HiL). The provided results under extensive islanding scenarios defined in islanding standards endorse timely and accurately detection with negligible non-detection zone (NDZ) as well as no false tripping in non-islanding disturbances. The comparative analysis of the presented scheme with a few recent IDMs for GCPVS highlights its overall superiorities, including very small NDZ, fast detection, thresholds self-standing determination, no adverse effect on power quality, and simple and inexpensive integration.

Optimal Energy Harvesting From a Multistrings PV Generator Based on Artificial Bee Colony Algorithm

Abstract: Photovoltaic (PV) systems based on multistring configuration are the best effective solution, given its advantages in terms of system availability, reliability, and energy efficiency. In this particular configuration each substring has its own dc–dc converter and a dedicated maximum power search algorithm which increase the cost and complexity. In this article, an efficient centralized global maximum power tracking (GMPPT) algorithm for multistring PV array subject to partial shading conditions is proposed. The algorithm is based on artificial bee colony (ABC) as an optimization approach to provide the optimal duty cycles allowing the extraction of the optimal global maximum power from each substring. In particular, the proposed approach allows significant reduction of the required sensors to only one pair of current and voltage sensors, at the common point of connection of the overall PV strings. The simulation study has been carried out under Cadence/Pspice and MATLAB/Simulink platforms on the I–V curves to confirm the effectiveness of the proposed algorithm when several shading patterns occur. In addition, complex shading pattern of a daily profile has been also carried out to demonstrate the GMPPT finding in dynamically variable conditions. Performance comparison against particle swarm optimization based maximum power point tracking algorithm and the traditional perturb and observe method has also been carried out. The obtained simulation and experimental results have shown the effectiveness and a good tracking capability of the proposed ABC algorithm in a multistring PV array configuration under uniform and nonuniform irradiance.

A Novel Fixed PV Array Configuration for Harvesting Maximum Power From Shaded Modules by Reducing the Number of Cross-Ties

Abstract: Partial shading is one of the main obstacle for constant power generation from solar photovoltaic (PV) systems. Partial shading conditions (PSCs) may be caused by passing of clouds, buildings, trees, bird litters, dust and etc. Due to PSCs, PV modules will experience the mismatching power losses which will lead to the loss of power generation capability and it also produces several peaks in the $P$ – $V$ curve. In order to avoid the problems associated with PSCs, the PV configuration is one of the best solution. The main objective of this research article is to model and simulate the proposed $7\times 7$ Tripe-Tied (TT) PV array configuration along with the Series (S), Series-Parallel (SP), Total-Cross-Tied (TCT), Bridge-Link (BL), Honey-Comb (HC) configurations under various shading scenarios. The performance above-mentioned PV array configurations are evaluated under uniform, corner, center, right side end, frame, random and diagonal shading scenarios. The comparative performance study of PV configurations is analyzed in terms of their mismatching power loss, fill factors, efficiency, global maximum power points (GMPPs), local maximum power points (LMPPs), voltages and currents at GMPPs, open-circuit voltage, and short-circuit current. KYOCERA-KC200GT PV module parameters are considered for simulating all PV configurations.

Temperature Coefficients of Perovskite Photovoltaics for Energy Yield Calculations

Abstract: Temperature coefficients for maximum power (TPCE), open circuit voltage (VOC), and short circuit current (JSC) are standard specifications included in data sheets for any commercially available pho...

Photovoltaic-Wind and Hybrid Energy Storage Integrated Multisource Converter Configuration-Based Grid-Interactive Microgrid

Abstract: In this article, a new dc–dc multisource converter configuration-based grid-interactive microgrid consisting of photovoltaic (PV), wind, and hybrid energy storage (HES) is proposed. Control structure along with power sharing scheme to operate the system under various operating modes, such as: 1) grid-connected mode; 2) islanded mode; 3) state of charge of battery ( $SoC_{b}$ ) less than or greater than specified limits; and 4) operating renewable sources (PV and wind) at maximum power point, is presented. The detailed analysis, modeling, and design of the proposed configuration and control structure are presented. The key highlights of the proposed configuration are: 1) low component count; 2) voltage boosting, voltage regulation of supercapacitor and power-sharing among the battery and supercapacitor are inherent; and 3) simple control structure with a reduced number of sensors. Supercapacitor-battery-based HES is interfaced which effectively handle the power fluctuations due to the wind, PV, and sudden load disturbances. Integration of supercapacitor to respond to high-frequency fluctuations increases the lifetime of battery storage and reduces the sizing of the storage unit. The proposed system is verified through digital simulation and experimental results.