Showing papers on "Maximum power point tracking published in 2019"

An Overall Distribution Particle Swarm Optimization MPPT Algorithm for Photovoltaic System Under Partial Shading

Abstract: Solar photovoltaic (PV) systems under partial shading conditions (PSCs) have a nonmonotonic P – V characteristic with multiple local maximum power points, which makes the existing maximum power point tracking (MPPT) algorithms unsatisfactory performance for global MPPT, if not invalid. This paper proposes a novel overall distribution (OD) MPPT algorithm to rapidly search the area near the global maximum power points, which is further integrated with the particle swarm optimization (PSO) MPPT algorithm to improve the accuracy of MPPT. Through simulations and experimentations, the higher effectiveness and accuracy of the proposed OD-PSO MPPT algorithm in solar PV systems is demonstrated in comparison to two existing artificial intelligence MPPT algorithms.

A new prediction model of battery and wind-solar output in hybrid power system

Abstract: In this paper short term power forecast of wind and solar power is proposed to evaluate the available output power of each production component. In this model, lead acid batteries used in proposed hybrid power system based on wind-solar power system. So, before the predicting of power output, a simple mathematical approach to simulate the lead–acid battery behaviors in stand-alone hybrid wind-solar power generation systems will be introduced. Then, the proposed forecast problem will be evaluated which is taken as constraint status through state of charge (SOC) of the batteries. The proposed forecast model includes a feature selection filter and hybrid forecast engine based on neural network (NN) and an intelligent evolutionary algorithm. This method not only could maintain the SOC of batteries in suitable range, but also could decrease the on-or-off switching number of wind turbines and PV modules. Effectiveness of the proposed method has been applied over real world engineering data. Obtained numerical analysis, demonstrate the validity of proposed method.

MPPT methods for solar PV systems: a critical review based on tracking nature

Abstract: An efficient maximum power point tracking (MPPT) method plays an important role to improve the efficiency of a photovoltaic (PV) generation system. This study provides an extensive review of the current status of MPPT methods for PV systems which are classified into eight categories. The categorisation is based on the tracking characteristics of the discussed methods. The novelty of this study is that it focuses on the key characteristics and eleven selection parameters of the methods to make a comprehensive analysis, which is not considered together in any review works so far. Again, the pros and cons, classification and immense comparison among them described in this study can be used as a reference to address the gaps for further research in this field. A comparative review in tabular form is also presented at the end of the discussion of each category to evaluate the performance of these methods, which will help in selecting the appropriate technique for any specific application.

Power tracking techniques for efficient operation of photovoltaic array in solar applications – A review

Abstract: This paper presents a comprehensive overview on various maximum power point tracking (MPPT) techniques, which have been recently designed, simulated and/or experimentally validated in the PV literature. The primary goal of each MPPT technique is to optimize the output of shaded/unshaded photovoltaic (PV) array under static and dynamic weather conditions. Though each MPPT technique has its own pros and cons, an optimized MPPT technique is characterized in many aspects like hardware and software simplicity, implementation, cost effectiveness, sensors required, popularity, accuracy and convergence speed. In this paper the rating of various MPPT methods has been done based on the benchmark P&O method. The rating criteria is separately calculated for the techniques that are capable to work in full-sun and partial shading conditions. A rule based table is set to evaluate the MPPT against the algorithm's complexity, hardware implementation, tracking speed, and steady state accuracy or detection of global maximum. Moreover, special consideration has been given to bio-inspired MPPT algorithms. The bio-inspired algorithms are compared side by side with their specific application in PV system. A tree diagram is also designed to see the emergence of partial shading algorithms over a period of time. The traits presented in this paper are novel and provide bottom-line for the researchers to select and implement an appropriate MPPT technique.

Design and Hardware Implementation of New Adaptive Fuzzy Logic-Based MPPT Control Method for Photovoltaic Applications

Abstract: An adaptive fuzzy logic (FL)-based new maximum power point (MPP) tracking (MPPT) methodology for controlling photovoltaic (PV) systems is proposed, designed, and implemented in this paper. The existing methods for implementing FL-based MPPTs lack for adaptivity with the operating point, which varies in wide range in practical PV systems with operating irradiance and ambient temperature. The new proposed adaptive FL-based MPPT (AFL-MPPT) algorithm is simple, accurate, and provides faster convergence to optimal operating point. The effectiveness and feasibility verifications of the proposed AFL-MPPT methodology are validated with considering various operating conditions at slow and fast change of solar radiation. In addition, the simplified implementation of the proposed algorithm is carried out using C-block in PSIM software environment, wherein the proposed algorithm and system are simulated. Additionally, experimental results are performed using a floating-point digital signal processing (DSP) controller (TMS320F28335) for verifying the feasibility of the proposed AFL-MPPT methodology. The results of simulations and experimental prototypes show great consistency and prove the capability of the new AFL-MPPT methodology to extract MPPT rapidly and precisely. The new proposed AFL-MPPT method achieves accurate output power of the PV system with smooth and low ripple. In addition, the new proposed AFL-MPPT method benefits fast dynamics and it reaches steady state within 0.01 s.

An Extensive Practical Investigation of FPSO-Based MPPT for Grid Integrated PV System Under Variable Operating Conditions With Anti-Islanding Protection

Abstract: Maximum power point trackers (MPPT) are required in order to obtain optimal photovoltaic power. To achieve this task, an intelligent fuzzy particle swarm optimization (FPSO) MPPT algorithm has been proposed in this paper. Also an inverter control strategy has been gated with a ripple factor compensation-based modified space vector pulse width modulation (SVPWM) method. The proposed system performance is verified under varying sun irradiance, partial shadow, and loading conditions. For load bus voltage regulation, the buck-boost Zeta converter is selected due to least ripple voltage output. The experimental responses verify the efficiency and improved system performance, which is realized through a MATLAB/Simulink interfaced dSPACE DS1104 real-time board. The proposed MPPT and inverter current controller provides high tracking efficiency and anti-islanding protection with superior dynamic control of the system performance by injecting sinusoidal inverter current to the utility grid. The novelty of this paper is experimental implementation and verification of FPSO-based hybrid MPPT as well as modified SVPWM inverter control has neither been discussed nor implemented before using dSPACE platform by the author's best review.

A Decentralized Control Architecture Applied to DC Nanogrid Clusters for Rural Electrification in Developing Regions

Abstract: DC microgrids built through a bottom-up approach are becoming popular for swarm electrification due to their scalability and resource-sharing capabilities. However, they typically require sophisticated control techniques involving communication among the distributed resources for stable and coordinated operation. In this work, we present a communication-less strategy for the decentralized control of a photovoltaic (PV)/battery-based highly distributed dc microgrid. The architecture consists of clusters of nanogrids (households), where each nanogrid can work independently along with provisions of sharing resources with the community. An adaptive I–V droop method is used, which relies on local measurements of state of charge and dc bus voltage for the coordinated power sharing among the contributing nanogrids. PV generation capability of individual nanogrids is synchronized with the grid stability conditions through a local controller, which may shift its modes of operation between maximum power point tracking mode and current control mode. The distributed architecture with the proposed decentralized control scheme enables 1) scalability and modularity in the structure, 2) higher distribution efficiency, and 3) communication-less, yet coordinated resource sharing. The efficacy of the proposed control scheme is validated for various possible power-sharing scenarios using simulations on MATLAB/Simulink and hardware-in-the-loop facilities at the Microgrid Laboratory, Aalborg University.

An Effective Hybrid Maximum Power Point Tracker of Photovoltaic Arrays for Complex Partial Shading Conditions

Abstract: This paper proposes an improved maximum power point tracker (MPPT) for photovoltaic (PV) system. The scheme is a hybrid between the adaptive perturb and observe and particle swarm optimization (PSO). The algorithm incorporates the search-skip-judge (SSJ) mechanism to minimize the region within the P−V curve to be searched by the PSO. Furthermore, the PSO performance is enhanced by ensuring that the regions that have been previously explored (by other particle) will not be searched again by (another particle). Thus, the unnecessary movement of particles is minimized—leading to faster convergence. The proposed method is evaluated against four well-known MPPT techniques, namely the modified incremental conductance, the original version of SSJ, the modified cuckoo search, and the hybrid PSO. In addition, an experimental prototype, which is based on PV array simulator is used to verify the simulation. The competing algorithms are tested with a buck-boost converter, driven by the TMS320F240 DSP on the dSPACE DS1104 platform. It was found that the proposed scheme converges to the global maximum power point (GMPP) most rapidly and the GMPP tracking is guaranteed even under complex partial shading conditions.

A Comprehensive Review of DC–DC Converter Topologies and Modulation Strategies with Recent Advances in Solar Photovoltaic Systems

Abstract: Renewable Energy Sources (RES) showed enormous growth in the last few years. In comparison with the other RES, solar power has become the most feasible source because of its unique properties such as clean, noiseless, eco-friendly nature, etc. During the extraction of electric power, the DC–DC converters were given the prominent interest because of their extensive use in various applications. Photovoltaic (PV) systems generally suffer from less energy conversion efficiency along with improper stability and intermittent properties. Hence, there is a necessity of the Maximum power point tracking (MPPT) algorithm to ensure the maximum power available that can be harnessed from the solar PV. In this paper, the most important features of the DC/DC converters along with the MPPT techniques are reviewed and analyzed. A detailed comprehensive analysis is made on different converter topologies of both non-isolated and isolated DC/DC converters. Then, the modulation strategies, comparative performance evaluation are addressed systematically. At the end, recent advances and future trends are described briefly and considered for the next-generation converter’s design and applications. This review work will provide a useful structure and reference point on the DC/DC converters for researchers and designers working in the field of solar PV applications.

Review of Power Conversion and Energy Management for Low-Power, Low-Voltage Energy Harvesting Powered Wireless Sensors

Abstract: In this paper, state-of-the-art power electronics and energy management solutions utilized in low-power (less than 5 mW), low-voltage (less than 3 V) energy harvesting powered wireless sensors for Internet of things related applications are detailed. All aspects of an energy harvesting powered sensor system are examined, including the challenges of low-power energy harvesting sources, energy management circuits including power converters and energy storage elements, as well as the impact of wireless sensor pulsed power profiles. In particular, this paper focuses on existing voltage step-up energy management techniques, including the issues of cold-start and maximum power point tracking, as well as energy storage which is necessary for wireless sensor operation. Both academic and commercially available energy harvesting powered systems are examined to provide a comprehensive analysis of existing solutions. Issues that are limiting the current system performance are identified to help define future developments needed to enable efficient and effective energy harvesting powered wireless sensor operation.

An ant colony optimized mppt for standalone hybrid pv-wind power system with single cuk converter

Abstract: This research work explains the practical realization of hybrid solar wind-based standalone power system with maximum power point tracker (MPPT) to produce electrical power in rural places (residential applications). The wind inspired Ant Colony Optimization (ACO)-based MPPT algorithm is employed for the purpose of fast and accurate tracking power from wind energy system. Fuzzy Logic Control (FLC) inverter controlling strategy is adopted in this presented work compared to classical proportional-integral (PI) control. Moreover, single Cuk converter is operated as impedance power adapter to execute MPPT functioning. Here, ACO-based MPPT has been implemented with no voltage and current extra circuit requirement compared to existing evolutionary algorithms single cuk converter is employed to improve conversion efficiency of converter by maximizing power stages. DC-link voltage can be regulated by placing Cuk converter Permanent Magnet Synchronous Generator (PMSG) linked rectifier and inverter. The proposed MPPT method is responsible for rapid battery charging and gives power dispersion of battery for hybrid PV-Wind system. ACO-based MPPT provides seven times faster convergence compared to the particle swarm optimization (PSO) algorithm for achievement of maximum power point (MPP) and tracking efficiency. Satisfactory practical results have been realized using the dSPACE (DS1104) platform that justify the superiority of proposed algorithms designed under various operating situations.

A novel modified sine-cosine optimized MPPT algorithm for grid integrated PV system under real operating conditions

Abstract: This research work presents a modified sine-cosine optimized maximum power point tracking (MPPT) algorithm for grid integration. The developed algorithm provides the maximum power extraction from a photovoltaic (PV) panel and simplified implementation with a benefit of high convergence velocity. Moreover, the performance and ability of the modified sine-cosine optimized (MSCO) algorithm is equated with recent particle swarm optimization and artificial bee colony algorithms for comparative observation. Practical responses is analyzed under steady state, dynamic, and partial shading conditions by using dSPACE real controlling board laboratory scale hardware implementation. The MSCO-based MPPT algorithm always shows fast convergence rate, easy implementation, less computational burden and the accuracy to track the optimal PV power under varying weather conditions. The experimental results provided in this paper clearly show the validation of the proposed algorithm.

Adaptive Reactive Power Control of PV Power Plants for Improved Power Transfer Capability Under Ultra-Weak Grid Conditions

Abstract: This paper analyzes the power transfer limitation of the photovoltaic (PV) power plant under the ultra-weak grid condition, i.e., when the short-circuit ratio (SCR) is close to 1. It explicitly identifies that a minimum SCR of 2 is required for the PV power plant to deliver the rated active power when operating with the unity power factor. Then, considering the reactive power compensation from PV inverters, the minimum SCR in respect to power factor (PF) is derived, and the optimized coordination of the active and reactive power is exploited. It is revealed that the power transfer capability of PV power plant under the ultra-weak grid is significantly improved with the low PF operation. An adaptive reactive power droop control is next proposed to effectively distribute the reactive power demands to the individual inverters, and meanwhile, maximize the power transfer capacity of the PV power plant. Simulation results of a 200-MW PV power plant demonstrate that the proposed method can ensure the rated power transfer of PV power plant with the SCR of 1.25, provided that the PV inverters are operated with the minimal PF=0.9.

A Hybrid Photovoltaic-Fuel Cell for Grid Integration With Jaya-Based Maximum Power Point Tracking: Experimental Performance Evaluation

Abstract: This paper deals the grid integration of photovoltaic (PV), fuel cell, and ultra-capacitor with maximum power point tracking (MPPT). The voltage oriented control for the grid-integrated inverter is proposed to regulate dc link voltage. Here, the fuel cell is employed as the main renewable energy source and PV as an auxiliary source with ultra-capacitor, which compensates power variation. An integrated CUK converter is proposed for peak power extraction from PV modules. The Jaya-based MPPT method is employed to achieve fast PV tracking ability with zero deviation around maximum power point (MPP) and has accelerated searched performance in equated with particle swarm optimization (PSO) and artificial bee colony (ABC) techniques. The hybrid PV-fuel cell with ultra-capacitor as energy storage works effectively under varying operating conditions. Compared to other energy storing devices, ultra-capacitor provides a fast dynamic response by absorbing/delivering power fluctuations. The hybrid PV-fuel storage control methodologies are experimentally validated using dSPACE (DS1104) board that provides optimal power extraction with stable power affirmation for a standalone/grid-connected system.

Antlion optimizer-ANFIS load frequency control for multi-interconnected plants comprising photovoltaic and wind turbine.

Abstract: This paper proposes optimal load frequency control (LFC) designed by Adaptive Neuro Fuzzy Inference System (ANFIS) trained via antlion optimizer (ALO) for multi-interconnected system comprising renewable energy sources (RESs). Two systems are modeled and investigated; the first one has two plants of grid connected photovoltaic (PV) system with maximum power point tracker (MPPT) and thermal plant while the second comprises four plants of thermal, wind turbine and grid connected PV systems. ALO is employed to get the optimal gains of Proportional-Integral (PI) controller such that the integral time absolute error (ITAE) of frequency and tie line power deviations is minimized. The input and output of the optimized PI controller are used to train the ANFIS-LFC with Gaussian surface membership functions. Different load disturbances are studied and the results are compared with other reported approaches. The obtained results confirmed the accuracy and reliability of the proposed approach in designing LFC for multi-interconnected power systems.

An improved radial basis function neural network control strategy-based maximum power point tracking controller for wind power generation system:

Abstract: This literature presents an improved maximum power point tracking (MPPT) controller based on radial basis function neural network (RBFNN) control strategy to extract optimal power for wind power ge...

Mitigation of Interharmonics in PV Systems With Maximum Power Point Tracking Modification

Abstract: Interharmonics are emerging power quality challenges in grid-connected photovoltaic (PV) systems. Previous studies and field measurements have confirmed the evidence of interharmonic emission from PV inverters, where the maximum power point tracking (MPPT) is one of the main causes for interharmonics. In that regard, the MPPT parameters such as their sampling rate has a strong impact on the interharmonic characteristic of the PV system. In general, there is a trade-off between the interharmonic emission and the MPPT performance when selecting the sampling rate of the MPPT algorithm. More specifically, employing a faster MPPT sampling rate will improve the MPPT efficiency, but it will also increase the interharmonic emission level. To solve this issue, a new mitigating solution for interharmonics in PV systems is proposed in this paper. The proposed method modifies the MPPT algorithm in a way to randomly select the sampling rate between the fast and the slow value. By doing so, the interharmonics in the output current can be effectively reduced due to the distribution of the frequency spectrum. On the other hand, the MPPT performance of the proposed method can be maintained similar to the case when employing a fast MPPT sampling rate. The effectiveness of the proposed interharmonic mitigation has been validated experimentally on a single-phase grid-connected PV system.