Photovoltaic Maximum Power Point Tracking Research Articles

Optimal Design of Photovoltaic MPPT Disturbance Step Length in a Rapidly Changing Environment

The traditional maximum power point tracking (MPPT) algorithm can not track the maximum power point (MPP) quickly and accurately in the environment of rapidly changing illumination amplitude. In this paper, based on the basic circuit model of solar cell, the small signal model between the disturbance step size of MPPT algorithm near the maximum power point and the intensity of light irradiance, ambient temperature, working voltage and working current is used, and then the MPPT duty cycle disturbance is modelled and analysed. The simulation results show that the model proposed in this paper clarifies the mechanism of the disturbance step size of MPPT algorithm in the environment of rapidly changing illumination amplitude. It also provides a theoretical basis for the design of subsequent disturbance step size.

Current control of grid connected three phase current source inverter based on medium power renewable energy system

Current source inverter (CSI) features simple converter structure and inherent voltage boost capability. In addition, it provides low instantaneous rate of voltage change with respect to time in comparison to voltage source inverter (VSI) and multilevel inverter (MLI). Nonetheless, CSI does not outshine as grid interfacing unit in photovoltaic (PV) generation system. This is because of requirement of large sizing of dc-link inductor and sluggish performance during light load condition. Contemplating both advantages and disadvantages of CSI, this work is aimed to investigate and analyze the superiority of CSI in PV system. The proposed system employs direct regular-sampled pulse width modulation (DRSPWM) as modulator and multi-loop proportional-integral (PI) in synchronous frame as the controller. The grid-connected CSI system is further evaluated along with photovoltaic maximum power point tracking (PV-MPPT) control. Simulation verification highlighted that the option of using CSI as medium power PV grid integration unit in exchanging active-reactive power with grid network is very satisfactory. In addition, balanced sinusoidal output currents with acceptable harmonic limit are successfully achieved; like other topologies in PV grid integration. The proposed CSI system is proved to be able to track the references in event of varying input condition from PV array. The theoretical equations and modeling are described, and the simulation are conducted in MATLAB / Simulink platform.

Implementation of non-linear controller on photovoltaic maximum power point tracker for energy storage equipment charger

The portable energy storage system is an infrastructure for providing electrical energy needed to support the recovery process after a natural disaster. This system is a battery arrangement that can be recharged using locally available primary energy sources such as photovoltaic. The main problem in using photovoltaic as the power source for this equipment is to increase the efficiency of power extraction (energy harvesting) during the recharging process. Traditionally, to obtain maximum extraction conditions, conventional linear maximum power point tracker (MPPT) mechanisms such as PID-based MPPT and the like are used. However, if the PV and the storage system works at various locations with environmental conditions behave unusually, the conventional MPPT cannot work accurately and optimally. In this paper, the Fuzzy method for constructing a nonlinear controller-based MPPT was studied. The step size of the tracking process in the conventional MPPT P&O method is modified by involving the fuzzy algorithm. This algorithm then is applied to a DC-DC converter to test the performance criteria such as the response and efficiency of the resulting power extraction. The testing and computer simulations show that the conventional MPPT mechanism can provide prospective results through modification and application of a non-linear controller.

Efficient Power Utilization Control Scheme for Hybrid Distribution Generation Grid

Micro Grids (MGs) are well described as distribution systems with integrated distributed energy resources, i.e. photovoltaic (PV) and wind power generation systems. MGs can improve the quality of power by maintaining voltage levels and reducing the cost of energy supply. Despite the obvious advantages of distributed generation, technical operating and controlling challenges related to MGs are immense to maintain voltage and frequency stabilities during variable loading and emergency condition. This paper proposes an efficient an overhaul maximum power conditioning control system of micro grid feeds from PV modules and wind turbine. The PV power system utilizes two-stage energy conversion system topology, i.e. a DC/DC chopper circuit and voltage source inverter (VSI) that satisfies the MG technical requirements. For the proposed PV maximum power point tracking (MPPT), the boost chopper duty cycle is being adjusted to set the PV panel operating point to a maximum power point. Whereas for the proposed wind turbine, the pitch angle controller is developed to force the wind turbine to reaches its optimal operation at low and medium wind speeds. During high wind speeds, the pitch angle is changed to minimize the aerodynamic power. The dynamic model and control of the investigated MG for both transient and steady states operations are illustrated. Furthermore, the control strategies for maintaining the maximum energy conversion and to obtain voltage stability under multiple operating conditions are presented.

Partial Power Conversion and High Voltage Ride-Through Scheme for a PV-Battery Based Multiport Multi-Bus Power Router

With the development of renewable energy technology, distributed power supply mode with multi energy and multi-directional power flow including utility grid, renewable energy and energy storage unit has gradually become a research hotspot. An AC/DC hybrid multi-port power routing (MPPR) system which based on partial power conversion (PPC) of dual DC buses is proposed in this paper. The photovoltaic (PV) port, the battery port and two DC voltage buses form a power router. PV maximum power point tracking (MPPT) and high-voltage ride through (HVRT) of the grid-tied inverter are implemented by the same auxiliary port voltage modulation. The PPC based PV conversion features that only the power determined by voltage difference between PV panel and the series connected DC bus is dealt with, which significantly reduces the loss compared to the full power conversion (FPC) for PV. The detailed control schemes of all converters and energy transmit are given. The simulation and experimental results verify the effectiveness of the proposed scheme.

Design and Dynamic Modelling of PV-Battery Hybrid Systems for Custom Electromagnetic Transient Simulation

Battery energy storage systems (BESS) can alleviate the unstable effects of intermittent renewable energy systems, such as solar and wind power systems. In addition, a BESS can level the load of the existing utility grid. The penetration rate of this type of system is expected to increase in the future power grid, i.e., the microgrid. In this paper, a modeling technique is proposed that allows users to customize the photovoltaic (PV) battery hybrid systems. A dynamic power system computer-aided design/electromagnetic transients including DC system (PSCAD/EMTDC) model of a PV battery hybrid system is presented in this paper. Dynamic modeling of PV arrays, BESS, maximum power point tracking (MPPT) algorithms, and bidirectional converters are provided as well. The PV model, battery model, and MPPT control model are designed using a user-defined model (UDM) for custom electromagnetic transient simulation. A control method for stabilizing the output of the PV battery hybrid system is proposed. Finally, a PSCAD/EMTDC simulation is conducted to verify the effectiveness of the operating algorithm.

Optimization and Comparison of Photovoltaic MPPT

Maximum Power Point Tracking (MPPT), as the contral core of the output power of photovoltaic power generation system, is extremely crucial to the entire photovoltaic power generation system. In this paper, a number of common MPPT control methods are analyzed in comparison, and the traditional conductance increment method is improved as well. By means of comparative analysis in the simulation software MATLAB/Simulink, it turns out that the improved conductance increment method excels the traditional method with regards to optimization speed and stability.

A Fusion Firefly Algorithm With Simplified Propagation for Photovoltaic MPPT Under Partial Shading Conditions

An improved maximum power point tracking (MPPT) algorithm based on the fusion firefly algorithm (FFA) with a novel simplified propagation process (SPP) for photovoltaic (PV) systems under partial shading conditions (PSCs) is proposed in this study. By integrating the neighborhood attraction firefly algorithm (NaFA) and simplified firefly algorithm (SFA), the proposed FFA is capable of tracking the global maximum power points (GMPPs) with high accuracy. In addition, the proposed SPP process reduces the sampling events by omitting redundant propagations, thereby accelerating the tracking speed and reducing the energy loss and oscillations during the sampling process. The performance of the proposed FFA and the speed improvement using the SPP process were simulated using MATLAB software and verified with a hardware evaluation system. Experimental results confirmed that the proposed FFA algorithm offers high accuracy and efficiency with rapid tracking speed. In addition, the proposed SPP process is capable of significantly reducing the sampling events not only when integrating it with the FFA, but also with other conventional FA algorithms.

A novel PSO strategy for improving dynamic change partial shading photovoltaic maximum power point tracker

ABSTRACT Photovoltaic (PV) energy systems are very important electric generation sources in modern power systems. The generated power from the PV array is a function in its terminal voltage. Tracking the maximum power needs a DC/DC converter to control the PV array terminal voltage. The boost converter is used in this paper for this purpose. Due to the multiple peaks in the power versus voltage (P-V) characteristics of PV array a smart optimization technique is required to work as a maximum power point tracker (MPPT). The particle swarm optimization (PSO) is a superior technique to track the global peak (GP) and avoid getting trapped in one of the local peaks (LPs). Despite the superiority of PSO, it suffers from some shortcomings in the application of MPPT of PV systems such as its sluggishness convergence, its inability to catch the new GP in case of acute change in shading pattern, and the possibility of getting trapped in one of the LPs. All these shortcomings are solved in this paper using a new adaptive PSO (NA-PSO) strategy. This new strategy solved these problems by starting the duty ratio at an equal distance between each other and force the particles with lower generated power to work around the one with the highest generated power. This newly proposed technique reduced the convergence time by 50% and reduced the failure rate to zero. Also, the generated energy is increased by 10.4% compared to the conventional PSO. The results collected from the NA-PSO strategy show its superiority in reducing the convergence time and failure rate and increasing the generated power, and the system efficiency, especially in the dynamic variation of the shading pattern compared to the conventional PSO.

Maximum power exploitation for grid-connected PV system under fast-varying solar irradiation levels with modified salp swarm algorithm

With the rapid development of photovoltaic (PV) power generation technology, PV generation system has been applied into planes, cars, boats and trains. Solar irradiation levels will change rapidly in these PV systems. Fast-varying solar irradiation can invalidate the traditional configurations of PV system and maximum power point tracking (MPPT) control strategy, which will reduce the energy conversion efficiency. In order to extract maximum power exploitation, this paper proposes a novel maximum power exploitation configuration combined with the proposed control scheme for grid-connected PV system under fast-varying solar irradiation levels. In the proposed configuration, each PV panel cascades a step-up boost converter, hence allowing independent control corresponding to the irradiation levels, which generates multiple-levels of dc-voltage and may be converted to ac via an active neutral point clamped (ANPC) inverter. Meanwhile, a modified salp swarm algorithm with dynamic w factor (DWSSA) based MPPT method is proposed for each boost converter units, which can effectively accelerate convergence velocity and stability of iteration to make the searching process rapidly adapting to different fast-varying solar irradiation levels. In order to express the dynamic variation of the PV system, the mathematical model of the proposed configuration is established. Moreover, the performance of the proposed DWSSA algorithm is investigated by the stability analysis based Lyapunov theory and convergence analysis on 23 benchmark functions and CEC 2005 benchmark functions. Finally, the constructed simulation test platform is implemented and the results demonstrate that the configuration can exploit the variable converter ratios, and the proposed DWSSA method has faster tracking speed and higher energy extraction efficiency compared with the previous MPPT methods in most cases, especially, the power extraction percentage of 97.89% and the tracking time of 0.761s under the most severe uneven solar irradiation levels.

A novel photovoltaic maximum power point tracking technique based on grasshopper optimized fuzzy logic approach

The maximum power point tracking (MPPT) in the PV system has become complex due to the stochastic nature of the load, intermittency in solar irradiance and ambient temperature. To address this problem, a novel Grasshopper optimized fuzzy logic control (FLC) approach based MPPT technique is proposed in this paper. In this proposed MPPT, grasshopper optimization is used to tune the membership functions (MFs) of FLC to handle all uncertainties caused by variable irradiances and temperatures. The performance of the proposed grasshopper optimized FLC based MPPT is studied under rapidly changing irradiance and temperature. The proposed MPPT overcomes the limitations such as slow convergence speed, steady-state oscillations, lower tracking efficiency as encountered in conventional methods viz. perturb & observed (P&O) and FLC techniques. The feasibility of the proposed MPPT is validated through experimentation. The effectiveness of the proposed scheme is compared with P&O and also with FLC MPPT.

Interview

Shamsodin Taheri Shamsodin Taheri, from the University of Quebec Outaouais, Canada, talks to us about his group's submission “Analysis of electrical behaviour of PV arrays covered with nonuniform snow” page 192. I am an Associate Professor of Electrical Engineering in the Department of Computer Science and Engineering at the Université du Québec en Outaouais (UQO). The expertise of my research group in the field of power energy has advanced our understanding of the performance of photovoltaic (PV) sources in cold-climate conditions. This research was inspired by the issues that PV plants in Canada experience during cold months. In recent years, we have collaborated with several industry partners, who own utility-scale PV plants, to evaluate the performance of their facilities. This ongoing research helps mitigate the technical challenges facing the integration of renewable energy sources into power grids in cold regions. PV systems have found different applications in cold areas for a long time, such as remote research facilities in the South and North Poles and space travelling. The majority of PV energy plants are presently installed in geographical cold locations with a considerable amount of snowfall every year. Furthermore, the solar energy industry is expanding competitively in cold climate regions. For example, in Canada, the installed capacity of solar PV grew from 95 MW to more than 2500 MW during 2009–2016. PV panel efficiency is not only influenced by PV technology, but environmental conditions can also influence their energy production. Accumulation of snow/ice decreases solar radiation reaching the PV panels, which results in a significant loss of power generation. Non-uniform snow accretion on PV panels often occurs due to ambient conditions such as wind, temperature variation, partial snow shedding and ground interference. This leads to power loss that is dependent on the configuration of the PV system. Owing to the increasing deployment of PV systems, there is a significant interest in optimal utilisation of PV potential in cold climate regions. A fundamental need for knowledge of the impact of nonuniform snow accretion on PV systems is therefore essential. This research has shown that the snow-covered PV panels can still produce a significant amount of energy depending on the pattern and depth of the snow accumulation. The portion of this energy that could be collected is decided by configuration of the PV array as well as the maximum power point tracking (MPPT) technique. Investigations concerning the effect of bypass diodes have shown that the PV string without bypass diodes generally experiences more power loss. In addition, the vertical and horizontal PV array layouts were tested to determine power loss due to nonuniform snow accretion. The horizontal PV array layout would be more effective in snowy climates. This work is helpful for PV system performance assessment, MPPT development and testing, power generation prediction, and proper arrangement of panels in cold regions. The accumulation of snow on PV modules weakens the intensity of incoming solar radiation and hence limits their ability to generate electricity during cold months. However, the true extent of such impact on the energy production of PV modules cannot be specified in a straightforward way, since it is not proportional to the snow-covered area. In some instances, snow covering only one cell can reduce the efficiency of a whole module by a noticeable amount. Snow is a complex phenomenon, and a quantitative characterisation of radiation transmittance through snow coverage requires knowledge of the physical properties of snow. In fact, the interaction of sunlight with snow to determine the influence of snow coverage on the PV modules is a challenge. This leads to changing the electrical characteristics of the PV array and producing multiple, local peaks on PV characteristics. Accurate modelling of the electric behaviour of PV modules and systems is a key element in improving system operation and efficiency. Hence, proper modelling approaches of the operation of PV generators under varying environmental conditions that improve their performance control and assist the design of PV converters and their MPPT controller have been achieved. Moreover, an appropriate tool has been proposed to determine the efficiency of PV farms under cold conditions. Furthermore, a high performance MPPT technique has been proposed to harvest the maximum energy of a PV array with multipeak characteristic under partial shading condition. Major progress must be made on the proper design and arrangement of PV arrays and power electronic interfaces, minimising the effects of snow on large-scale PV farms and the increasing the use of bifacial PV modules as a candidate for cold regions over the next ten years.

Duty-Cycle Predictive Control of Quasi-Z-Source Modular Cascaded Converter Based Photovoltaic Power System

A duty-cycle predictive control is proposed for dc grid integration of front-end isolated quasi-Z-source modular cascaded converter (qZS-MCC) photovoltaic (PV) power system. The post-stage qZS half-bridge dc-dc converter deals with PV maximum power point tracking, dc grid integration, and dc-link voltage balance; whereas, the front-end isolation converters operate at a constant duty cycle of 50%. Thus, it saves control hardware resources while overcoming challenges from PV-panel voltage variations and dc-bus voltage limit. The proposed control uses the derived circuit model to predict the global active-state duty cycle for grid-connected current control and predict the shoot-through duty cycles for dc-link voltage balance, achieving a fast and accurate tracking target. The proposed control method has advantages of: i) eliminating weighting factors that exist in conventional model predictive control (MPC), ii) no sophisticated loop parameters design that exists in proportional-integral (PI) control, iii) operating at constant switching frequency that is different from the conventional MPC with variable switching frequency. Simulation and experimental tests are carried out to verify the effectiveness of the proposed control method and compare with the PI-based control system.

Hybrid, optimization, intelligent and classical PV MPPT techniques: Review

Renewable energy-based solar photovoltaic (PV) generation is the best alternative for conventional energy sources because of its natural abundance and environment friendly characteristics. Maximum power extraction from the PV system plays a critical role in increasing the efficiency of the solar power generation during partial shading conditions (PSCs). Therefore, a suitable maximum power point tracking (MPPT) technique to track the maximum power point (MPP) is of high need, even under PSCs. This paper presents an organized and concise review of MPPT techniques implemented for the PV systems in literature along with recent publications on various hardware design methodologies. Their classification is done into four categories, i.e. classical, intelligent, optimal, and hybrid depending on the tracking algorithm utilized to track MPP under PSCs. During uniform insolation, classical methods are highly preferred as there is only one peak in the P-V curve. However, under PSCs, the P-V curve exhibits multiple peaks, one global maximum power point (GMPP) and remaining are local maximum power points (LMPP's). Under the PSCs, classical methods fail to operate at GMPP and hence there is a need for more advanced MPPT techniques. Every MPPT technique has its advantages and limits, but a streamlined MPPT is drafted in numerous parameters like sensors required, hardware implementation, cost viability, tracking speed and tracking efficiency. This study provides the advancement in this area since some parameter comparison is made at the end of every classification, which might be a prominent base-rule for picking the most gainful sort of MPPT for further research.

An efficient fuzzy logic control algorithm for photovoltaic maximum power point tracking under partial shading condition

Under partially shaded conditions, solar photovoltaic (PV) array power–voltage (P–V) characteristic curve will show multiple peaks, and maximum power point tracking (MPPT) by using fuzzy control algorithm is easy to fall into the local optimal solution. In view of the above problems, an improved maximum power point tracking algorithm is proposed based on the fuzzy control method and the differential flatness control theory. Firstly, the output voltage of the PV array increases linearly by using the differential flatness control, and the maximum power point voltage is found. Then the fuzzy control algorithm is used to stabilize the output voltage of the photovoltaic array. The feasibility of the algorithm is verified by MATLAB simulation and hardware experiment.

Photovoltaic maximum power point tracking under dynamic partial shading changes by novel adaptive particle swarm optimization strategy

Maximum power point tracker (MPPT) is vital device in the Photovoltaic (PV) system because it can increase the generated power considerably. Partial shading conditions (PSCs) on the PV array generates many peaks in the P-V curve of PV array. Metaheuristic techniques like particle swarm optimization (PSO) have the ability to track the global peak (GP) at any operating conditions. PSO technique can track the GP but once the shading pattern (SP) changes, the value and location of the new GP will change and may PSO cannot catch the new GP because all particles are busy around the previous GP. This problem is classified into two conditions: the first condition if the GP change its location and value suddenly, the second condition occurs when the GP changes its value gradually and still in same place. The first problem is solved by reinitializing the particles. The second problem is solved using a new adaptive strategy that has not been treated or adopted in any literature before. The results obtained prove the superiority of the new proposed strategy in always catching GP in dynamic change PSCs.

Crowded plant height optimisation algorithm tuned maximum power point tracking for grid integrated solar power conditioning system

Solar energy is the base for both photovoltaic (PV) power generation and plant growth. Inspired by this biological phenomenon, a novel crowded plant height optimisation (CPHO) algorithm was developed for solar PV maximum power point tracking (MPPT). This CPHO-tuned MPPT algorithm was developed with the aim of obtaining the optimal duty cycle (d) for DC-DC boost converter for maximum solar power extraction from PV panels with the help of a proportional-integral controller. Crowded plants regulate the growth of their stem height in relation to neighbouring plants, also known as height convergence. Using this CPHO-algorithm, the stable height of the plant found in a numerical value is taken as the optimal height of the plant. This optimal numerical value was converted into (d) for the converter. Under dynamic weather conditions, the (d) was optimally adjusted by the proposed algorithm to regulate the DC output of the converter. On the utility side, d–q vector control-based voltage source inverter was used for PV power integration into the grid. The performance of the converter control strategy of the proposed CPHO algorithm was compared with perturb and observe algorithm-based MPPT control, which was analysed on MATLAB/Simulink platform.

Monitoring the performances of a maximum power point tracking photovoltaic (MPPT PV) pumping system driven by a brushless direct current (BLDC) motor

Nowadays, water pumping systems powered by solar-cell generators are one of the most important applications. It’s a promising alternative to conventional electricity and diesel based pumping systems, especially for applications like community water supplies and irrigation. This study presents a monitored standalone photovoltaic solar direct pumping system using the Maximum Power Point Tracking (MPPT) algorithm to optimize the solar photovoltaic conversion efficiency. It was done at ISET-Rosso in Mauritania. The experimental setup based on Lorentz PS1200C-SJ8-5 pumping system consists of four photovoltaic (PV) panels, inverter PS1200, BLDC motor, centrifugal pump and a storage tank. The system has been monitored, in order to determine the relationship between: the DC power produced by the PV generator and the solar radiation; the water flow and the DC power and by then the relationship between the water flow and the solar radiation. The effect of ambient temperature and solar radiation on the PV panels was also done under Matlab/Simulink environment and compared to the experimental results. ©2019. CBIORE-IJRED. All rights reserved

Modelling and analysis of an analogue MPPT‐based PV battery charging system utilising dc–dc boost converter

Nowadays, the research is being devoted to the development of rapid and precise maximum power point tracking (MPPT) for various photovoltaic (PV) applications. However, the constraints imposed by size, cost, efficiency, and tracking performances essentially limit the application of conventional MPPT techniques and their analysis methodologies. This study recommends a fast and robust analogue PV MPPT for the battery charging system using dc-dc boost converter. The fast dynamic performances with absolute robustness are ensured here by fast-scale stability analysis of actually switched boost converter using the concepts based on non-linear dynamics and bifurcation theory. Such concepts not only provide the information to design an efficient MPPT system under rapidly changing environmental conditions but also guarantee the system to operate either in period-1 or chaotic mode. The theoretical and mathematical analyses are experimentally verified using a prototype PV battery charging system utilising dc-dc boost converter. It is presented that operating the MPPT system in chaos not only yields the broader power spectrum with reduced spectral peaks at the multiples of converter's switching frequency but also exhibits high overall conversion efficiency.

Estimation-Based Maximum Power Point Tracking in a Self-Balancing Photovoltaic Battery Energy Storage System

This paper examines the problem of controlling the exchange of current in photovoltaic-plus-storage systems to achieve photovoltaic (PV) maximum power point tracking (MPPT). This work is motivated by the need for MPPT algorithms that are less costly and complex to implement in PV farms with integrated battery energy storage. We study the online optimal control of a “hybrid” PV/lithium (Li)-ion battery integration topology that is self-balancing in nature. The self-balancing behavior ensures that the state of charge (SOC) across different cells balances to the same stable equilibrium value without needing any balancing power electronics, thereby significantly reducing the integration cost. The DC–DC converters in this hybrid system are controlled to achieve PV MPPT that maximizes energy generation and storage. However, sensing needs for traditional MPPT controllers can render the hybrid system unnecessarily complex and costly. We surmount this problem by: (i) developing a novel model-based PV power estimation algorithm that only requires voltage measurement, and (ii) using this algorithm together with extremum-seeking (ES) control to achieve closed-loop, estimation-based PV MPPT. Simulation case studies show that this estimation-based MPPT controller is able to harness more than 99% of the maximum available solar energy under different irradiation profiles.