Maximum power point tracking of partial shaded photovoltaic array using an evolutionary algorithm: a particle swarm optimization technique

 Partial shading is one of the unavoidable complications in the field of solar power generation. Although the most common approach in increasing a photovoltaic (PV) array’s efficiency has always been to introduce a bypass diode to the said array, this poses another problem in the form of multi-peaks curves whenever the modules are partially shaded. To further complicate matters, most conventional Maximum Power Point Tracking methods develop errors under certain circumstances (for example, they detect the local Maximum Power Point (MPP) instead of the global MPP) and reduce the efficiency of PV systems even further. Presently, much research has been undertaken to improve upon them. This study aims to employ an evolutionary algorithm technique, also known as particle swarm optimization, in MPP detection. VC 2014 Author(s).

Simulation and hardware implementation of new maximum power point tracking technique for partially shaded PV system using hybrid DEPSO method

In photovoltaic (PV) power generation, partial shading is an unavoidable complication that significantly reduces the efficiency of the overall system. Under this condition, the PV system produces a multiple-peak function in its output power characteristic. Thus, a reliable technique is required to track the global maximum power point (GMPP) within an appropriate time. This study aims to employ a hybrid evolutionary algorithm called the DEPSO technique, a combination of the differential evolutionary (DE) algorithm and particle swarm optimization (PSO), to detect the maximum power point under partial shading conditions. The paper starts with a brief description about the behavior of PV systems under partial shading conditions. Then, the DEPSO technique along with its implementation in maximum power point tracking (MPPT) is explained in detail. Finally, Simulation and experimental results are presented to verify the performance of the proposed technique under different partial shading conditions. Results prove the advantages of the proposed method, such as its reliability, system-independence, and accuracy in tracking the GMPP under partial shading conditions.

A comparative study on procedure and state of the art of conventional maximum power point tracking techniques for photovoltaic system

Due to the increasing world energy demand, renewable energy systems have been significantly applied in the power generation sector. Among the renewable energy options, photovoltaic system is one of the most popular resources which has been experiencing a huge attention during recent decades. The remarkable advantages, such as static and movement free characteristics, low maintenance costs, and longevity are the primary factors for the popularity of solar generation in the late years. Nevertheless, the low PV conversion efficiency in one side and high PV material cost in the other side have made PV generation comparably expensive system. Consequently, a capable maximum power point tracking (MPPT) is all important to elicit the maximum energy from the production of PV systems. Different researches have been conducted to design a fast, simple and robust MPPT technique under uniform conditions. However, due to the series and parallel connection of PV modules and according to the use of bypass diodes, in the structure of PV modules, a conventional techniques are unable to track a true MPP. Recently, several studies have been undertaken to modify these conventional methods and enable them to track the global MPP under rapidly changing environments and partial shading (PS) conditions. This report concentrates on the state of the art of these methods and their evolution to apply under PS conditions. The recent developments and modifications are analyzed through a comparison based on design complexity, cost, speed and the ability to track the MPP under rapid environmental variations and PS conditions.

Implementation of fuzzy logic maximum power point tracking controller for photovoltaic system

In this study, simulation and hardware implementation of Fuzzy Logic (FL) Maximum Power Point Tracking (MPPT) used in photovoltaic system with a direct control method are presented. In this control system, no proportional or integral control loop exists and an adaptive FL controller generates the control signals. The designed and integrated system is a contribution of different aspects which includes simulation, design and programming and experimental setup. The resultant system is capable and satisfactory in terms of fastness and dynamic performance. The results also indicate that the control system works without steady-state error and has the ability of tracking MPPs rapid and accurate which is useful for the sudden changes in the atmospheric condition. MATLAB/Simulink software is utilized for simulation and also programming the TMS320F2812 Digital Signal Processor (DSP). The whole system designed and implemented to hardware was tested successfully on a laboratory PV array. The obtained experimental results show the functionality and feasibility of the proposed controller.

A hybrid simulated annealing and perturb and observe method for maximum power point tracking in PV systems under partial shading conditions

This paper presents a hybrid method for Maximum Power Point Tracking (MPPT) of a Photovoltaic (PV) system which experiences non-uniform environmental conditions or partial shading conditions. The hybrid method combines two simple techniques with complementary strengths in achieving Global MPPT. Simulated Annealing (SA) has only recently been applied to PV MPPT and is very effective at locating global maxima with limited implementation complexity. Perturb and Observe (P&O) is a very common technique which provides continuous tracking of the MPP in a simple and easy to implement manner. The P&O method is generally incapable of locating global maxima, and the SA based method is unable to perform continuous searching. By merging these techniques in a hybrid MPPT method consisting of a global searching stage and a local searching stage, the tracking performance is improved compared to what each technique could achieve independently. Simulation results are presented to demonstrate the effectiveness of the proposed hybrid technique.

Maximum power point tracking techniques for photovoltaic systems: a comprehensive review and comparative analysis

Maximum Power Point Tracking (MPPT) is an important concern in Photovoltaic (PV) systems. As PV systems have a high cost of energy it is essential that they are operated to extract the maximum possible power at all times. However, under non-uniform environmental conditions, which frequently arise in the outdoor environment, many MPPT techniques will fail to track the global peak power. This review paper discusses conventional MPPT techniques designed to operate under uniform environmental conditions and highlights why these techniques fail under non-uniform conditions. Following this, techniques designed specifically to operate under non-uniform environmental conditions are analysed and compared. Simulation results which compare the performance of the common Perturb and Observe (P&O) method, the Particle Swarm Optimisation (PSO) and the Simulated Annealing (SA) MPPT approaches under non-uniform environmental conditions are also presented. The research presented in this review indicates that there is no single technique which can achieve reliable global MPPT with low cost and complexity and be easily adapted to different PV systems.

Efficient photovoltaic system maximum power point tracking using a new technique

Partial shading is an unavoidable condition which significantly reduces the efficiency and stability of a photovoltaic (PV) system. When partial shading occurs the system has multiple-peak output power characteristics. In order to track the global maximum power point (GMPP) within an appropriate period a reliable technique is required. Conventional techniques such as hill climbing and perturbation and observation (P&O) are inadequate in tracking the GMPP subject to this condition resulting in a dramatic reduction in the efficiency of the PV system. Recent artificial intelligence methods have been proposed, however they have a higher computational cost, slower processing time and increased oscillations which results in further instability at the output of the PV system. This paper proposes a fast and efficient technique based on Radial Movement Optimization (RMO) for detecting the GMPP under partial shading conditions. The paper begins with a brief description of the behavior of PV systems under partial shading conditions followed by the introduction of the new RMO-based technique for GMPP tracking. Finally, results are presented to demonstration the performance of the proposed technique under different partial shading conditions. The results are compared with those of the PSO method, one of the most widely used methods in the literature. Four factors, namely convergence speed, efficiency (power loss reduction), stability (oscillation reduction) and computational cost, are considered in the comparison with the PSO technique.

A simulated annealing global maximum power point tracking approach for PV modules under partial shading conditions

This paper proposes a simulated annealing (SA)-based global maximum power point tracking (GMPPT) technique designed for photovoltaic (PV) systems which experience partial shading conditions (PSC). The proposed technique is compared with the common perturb and observe MPPT technique and the particle swarm optimization method for GMPPT. The performance is assessed by considering the time taken to converge and the number of sample cases where the technique converges to the GMPP. Simulation results indicate the improved performance of the SA-based GMPPT algorithm, with arbitrarily selected parameters, in tracking to the global maxima in a multiple module PV system which experiences PSC. Experimental validation of the technique is presented based on PV modules that experience nonuniform environmental conditions. Additionally, studies regarding the influence of the key parameters of the SA-based algorithm are described. Simulation and experimental results verify the effectiveness of the proposed GMPPT method.

Maximum power point tracking methods for PV systems

Maximum power point tracking (MPPT) is an important consideration in photovoltaic (PV) systems. These systems exhibit variable nonlinear current–voltage (I–V) and power–voltage (P–V) characteristics which vary with environmental conditions. The optimum operation of a PV system occurs when the system operates at the unique maximum power point (MPP) for the given environmental conditions. Key environmental conditions include the irradiance on the cell, temperature of the cell and any shading phenomenon. Shading can occur due to objects, dust or dirt and module mismatch arising from damage or manufacturing tolerances. These shading effects introduce further nonlinearity into the I–V and P–V characteristics of the system. An extensive variety of MPPT techniques has been proposed which vary from simple estimation techniques to advanced tracking techniques. In this chapter, the criteria for assessing the performance of MPPT methods are defined followed by a complete description and discussion of both techniques designed for uniform environmental conditions and those designed for nonuniform environmental conditions.

A digital signal processor controlled smart battery charger for photovoltaic power systems

An off-grid photovoltaic power system requires an energy storage system, especially batteries, for mitigation of variability and intermittency problems, and for assured service reliability and availability. The longevity and reliability of such batteries depend on the effectiveness of the charging system. This paper presents the modelling, simulation and hardware implementation of a four-stage switch-mode charger based on the single-ended primary inductance converter. The digital signal processor based controller implements algorithms for the system's power balance control, maximum power point tracking to improve charging speed and efficiency, four-stage optimal charging, and system's protection. The protection algorithm provides over-charge, overdischarge, over-temperature and short circuit protection capabilities. The proposed system has the following advantages: ability to continuously charge the batteries even at reduced solar irradiation, higher efficiency, and use of adaptive thermally compensated set points for optimum performance. A prototype is built and experimental results are presented to validate the simulation results.

Low cost MPPT controller for a photovoltaic-based microgrid

 Photovoltaic based microgrid have been increasingly investigated in recent years, ascribable to their fundamental advantages such as the infinite energy source, environmentally friendly aspect and low upkeep cost. However, in practice, they are still considered as an expensive and low output option of renewable energy resources. To extract the maximum possible power from the output of the PV system, a reliable maximum power point tracker (MPPT) is required. Numerous studies have been conducted to introduce the best MPPT techniques suitable for different types of PV systems. However, they are mostly able to track the MPP from the PV system when the output signals (Voltage and Current) of individual array are available. In this study, a meta-heuristic method, based on particle swarm optimization theory, is used to determine the actual MPP of PV system, including several PV arrays, by only single current sensor at the output terminal. The results of the proposed PSO based technique, for tracking the global MPP in a multidimensional search space, have been presented at the end of this paper.

Analytical modeling of partially shaded photovoltaic systems

As of today, the considerable influence of select environmental variables, especially irradiance intensity, must still be accounted for whenever discussing the performance of a solar system. Therefore, an extensive, dependable modeling method is required in investigating the most suitable Maximum Power Point Tracking (MPPT) method under different conditions. Following these requirements, MATLAB-programmed modeling and simulation of photovoltaic systems is presented here, by focusing on the effects of partial shading on the output of the photovoltaic (PV) systems. End results prove the reliability of the proposed model in replicating the aforementioned output characteristics in the prescribed setting. The proposed model is chosen because it can, conveniently, simulate the behavior of different ranges of PV systems from a single PV module through the multidimensional PV structure.

Control and charge management of a grid-connected photovoltaic system with plug-in hybrid vehicle as energy storage

This paper presents the control and charge management strategy of a photovoltaic system (PV) with plug-in hybrid electric vehicle (PHEV) as energy storage. The hybrid energy storage system (HESS) of PHEV consists of battery and supercapacitor. A simulation model for the PV system with PHEV energy storage has been developed using Matlab/SimpowerSystems. The system consists of PV arrays, SEPIC dc-dc converter with maximum power point tracking (MPPT), hybrid battery-supercapacitor energy storage with bidirectional dc-dc converter and inverter for grid connection. A charge management algorithm for the hybrid energy storage system is proposed to control the power flows among the PV system, energy storage and the grid. Results show that the proposed power management algorithm can control the power flows in an efficient manner.

State of the art artificial intelligence-based MPPT techniques for mitigating partial shading effects on PV systems - a review

Given the considerable recent attention to distributed power generation and interest in sustainable energy, the integration of photovoltaic (PV) systems to grid-connected or isolated microgrids has become widespread. In order to maximize power output of PV system extensive research into control strategies for maximum power point tracking (MPPT) methods has been conducted. According to the robust, reliable, and fast performance of artificial intelligence-based MPPT methods, these approaches have been applied recently to various systems under different conditions. Given the diversity of recent advances to MPPT approaches a review focusing on the performance and reliability of these methods under diverse conditions is required. This paper reviews AI-based techniques proven to be effective and feasible to implement and very common in literature for MPPT, including their limitations and advantages. In order to support researchers in application of the reviewed techniques this study is not limited to reviewing the performance of recently adopted methods, rather discusses the background theory, application to MPPT systems, and important references relating to each method. It is envisioned that this review can be a valuable resource for researchers and engineers working with PV-based power systems to be able to access the basic theory behind each method, select the appropriate method according to project requirements, and implement MPPT systems to fulfill project objectives.

Robust nonlinear controller design for three-phase grid-connected photovoltaic systems under structured uncertainties

This paper presents a robust nonlinear controller design for a three-phase grid-connected photovoltaic (PV) system to control the current injected into the grid and the dc-link voltage for extracting maximum power from PV units. The controller is designed based on the partial feedback linearization approach, and the robustness of the proposed control scheme is ensured by considering structured uncertainties within the PV system model. An approach for modeling the uncertainties through the satisfaction of matching conditions is provided. The superiority of the proposed robust controller is demonstrated on a test system through simulation results under different system contingencies along with changes in atmospheric conditions. From the simulation results, it is evident that the robust controller provides excellent performance under various operating conditions. © 2014 IEEE.