Development of Maximum Power Extraction Algorithms for PV system With Non-Uniform Solar Irradiances

This thesis addresses the problem of extraction of maximum power from PV arrays subjected to non-uniform solar irradiances e.g partial shading. In the past, a number of maximum power point tracking algorithms (MPPTs) such as Perturb & Observe, Hill climbing, Incremental Conductance, etc. have been proposed. These are extensively used for obtaining maximum power from a PV module to maximize power yield from PV systems under uniform solar irradiance. However, these techniques have not considered partial shading conditions and the stochastic nature of solar insolation. In the event of non-uniform solar insolation, a number multiple maximum power points (MPPs) appear in the power-voltage characteristic of the PV module. In the present thesis, the stochastic nature of the solar insolation is considered to obtain the global MPP of a PV module with a focus on developing global optimization techniques for MPPT that would handle the multiple MPPs. Thus, the thesis will address the above problem by developing a number of global MPPT algorithms. In this thesis, an extensive review on MPPT algorithms for both uniform and non-uniform insolation levels is presented. Subsequently, an analysis with respect to their merits, demerits and applications have been provided in order to design new MPPTs to achieve higher MPPT efficiency under non-uniform solar irradiances. Firstly, PV modules are modelled with and without bypass diodes for handling Partial shading conditions (PSCs). Then, a new Ring pattern (RP) configuration has been proposed which is compared with different existing configurations such as Series parallel (SP), Total cross tied(TCT) and Bridge linked(BL) configurations on the basis of maximum power and fill factor. As described earlier, under non-uniform irradiances the MPPT problem boil down to determining the global MPP. Thus, the MPPT problem can be cast as a global optimization problem. It may be noted that evolutionary computing approaches are extensively used for obtaining global optimum solutions. One of the most recent evolutionary optimization techniques called grey wolf optimization technique has gained enormous popularity as an efficient global optimization approach. In view of this, Grey wolf optimization is employed to design a global MPPT such that maximum power from PV modules can be extracted which will work under partial shading conditions. Its performance has been compared with two existing MPPTs namely P&O and IPSO based MPPT methods. From the obtained simulation and experimental results, it was found that the GWO based MPPT exhibits superior MPPT performance as compared to both P&O and IPSO MPPTs on the basis of dynamic response, faster convergence to GP and higher tracking efficiency. Further, in order to scale down the search space of GWO which helps to speed up for achieving convergence towards the GP, a fusion of GWO-MPPT with P&O MPPT for obtaining maximum power from a PV system with different possible patterns is developed. An experimental setup of 600W solar simulator is used in the laboratory having characteristics of generating partial shading situation. Firstly, the developed algorithms were implemented for a PV system using MATLAB/SIMULINK. Subsequently, the aforesaid experimental setup is used to implement the proposed global MPPT algorithms. From the obtained simulation and experimental results it is observed that the Hybrid-MPPT converges to the GP with least time enabling highest possible maximum power from the solar PV system. In this thesis, analytical modeling of PV modules for handling non-uniform irradiances is pursued as well as a new RP configuration of PV modules is developed to achieve maximum power and fill factor. In order to extract maximum power from PV panels subjected to non-uniform solar irradiances, two new MPPT algorithms are developed namely Grey wolf optimization based MPPT (GWO-MPPT) and GWO assisted PO (GWO-PO)

Performance Analysis of Maximum Power Point Tracking Algorithms Under Varying Irradiation

Photovoltaic (PV) system is one of the reliable alternative sources of energy and its contribution in energy sector is growing rapidly. The performance of PV system depends upon the solar insolation, which will be varying throughout the day, season and year. The biggest challenge is to obtain the maximum power from PV array at varying insolation levels. The maximum power point tracking (MPPT) controller, in association with tracking algorithm will act as a principal element in driving the PV system at maximum power point (MPP). In this paper, the simulation model has been developed and the results were compared for perturb and observe, incremental conductance, extremum seeking control and fuzzy logic controller based MPPT algorithms at different irradiation levels on a 10 KW PV array. The results obtained were analysed in terms of convergence rate and their efficiency to track the MPP.Keywords: Photovoltaic system, MPPT algorithms, perturb and observe, incremental conductance, scalar gradient extremum seeking control, fuzzy logic controller.Article History: Received 3rd Oct 2016; Received in revised form 6th January 2017; Accepted 10th February 2017; Available onlineHow to Cite This Article: Naick, B. K., Chatterjee, T. K. & Chatterjee, K. (2017) Performance Analysis of Maximum Power Point Tracking Algorithms Under Varying Irradiation. Int Journal of Renewable Energy Development, 6(1), 65-74.http://dx.doi.org/10.14710/ijred.6.1.65-7

Simulation and Analysis of Photovoltaic Stand-Alone Systems

Energy saving is biggest issue now a days, renewable energy is playing a big role in producing electricity, among them wind and solar are popular renewable energy sources. Fast tracking of global maximum power point (MPP) is a challenge, many research is going on this direction. MPP highly depends on atmospheric conditions, so our maximum power point tracking (MPPT) technique should be good enough to track MPP in dynamic atmospheric conditions. Perturb and Observer (P & O) and Incremental conductance (INC) are widely used MPPT techniques, we used INC method and simulated solar photovoltaic system in dynamic atmospheric conditions. Partial shading gives local MPPs and one global MPP, power loss occur in a shaded module because of that efficiency reduces, most of the conventional MPPT are failed to track global MPP ,to deal with this problem two kind of control strategies found in literature first one modular MPPT and second one two controller structure. MPP also highly depends on the load, as the load changes MPP changes. Extra power need to store because sometimes load requirement is lesser than the generation, in this situation a battery is needed and in night time when PV module not able to generate, power can draw from the battery. In this thesis we have discussed about the INC MPPT method for different atmospheric conditions and partial shading

Comparative analysis of evolutionary-based maximum power point tracking for partial shaded photovoltaic

The characteristics of the photovoltaic module are affected by the level of solar irradiation and the ambient temperature. These characteristics are depicted in a V-P curve. In the V-P curve, a line is drawn that shows the response of changes in output power to the level of solar irradiation and the response to changes in voltage to ambient temperature. Under partial shading conditions, photovoltaic (PV) modules experience non-uniform irradiation. This causes the V-P curve to have more than one maximum power point (MPP). The MPP with the highest value is called the global MPP, while the other MPP is the local MPP. The conventional MPP tracking technique cannot overcome this partial shading condition because it will be trapped in the local MPP. This article discusses the MPP tracking technique using an evolutionary algorithm (EA). The EAs analyzed in this article are genetic algorithm (GA), firefly algorithm (FA), and fruit fly optimization (FFO). The performance of MPP tracking is shown by comparing the value of the output power, accuracy, time, and tracking effectiveness. The performance analysis for the partial shading case was carried out on various populations and generations

A Review on Photo Voltaic MPPT Algorithms

A photovoltaic generator exhibits nonlinear voltage-current characteristics and its maximum power point varies with solar radiation and cell temperature. A Dc/Dc power converter is used to match the photovoltaic system to the load and to operate the PV (photo voltaic) cell array at maximum power point. Maximum Power Point Tracking (MPPT) is a process which tracks one maximum power point from PV array input, varying the ratio between the voltage and current delivered to get the most power it can. There are different techniques proposed with lot of algorithms are being used in the MPPT controller to extract the maximum power. It is very difficult for the photo voltaic designers, researchers and academic experts to select a particular MPPT technique for a particular application which requires the background knowledge and comparative features of various MPPT algorithms. This paper will be avaluable source for those who work in the photo voltaic generation, so its objective is to review the main MPPT algorithms in practice and analyzes the merits and demerits with various factors

Robust Modified Flower Pollination Algorithm for Power Quality Enhancement in an Autonomous 31-Level Cascaded H-Bridge Photovoltaic Inverter with Partial Shading Conditions

The effect of global warming and the scarcity of fossil fuels has created an enormous problem in today’s era. To overcome such a problem, renewable energy sources, particularly solar energy, play a crucial role in meeting the developing need for power. However, the design of the Solar Photovoltaic (PV) system is interrupted by various factors such as the effect of temperature, isolation, aging, partial shading conditions, etc. Among all the factors mentioned, partial shading results in the significant diminution of power. To address this shading effect and enhance the flexibility of the PV system in terms of better utilization and energy extraction, a 31-Level Cascaded H-Bridge Multilevel Inverter (CHB-MLI) has been implemented to the autonomous PV system comprising of Maximum Power Point Tracking (MPPT) controller, boost converter and variable loads in MATLAB/Simulink architecture. To track maximum power from PV during varying irradiance and temperature and to further improve the system performance in terms of better convergence speed, an MPPT system with a Modified Flower Pollination Algorithm (MFPA) based PID controller has been proposed in this paper. To justify the suggested approach, the is-landed PV system is led to variation in irradiance and load. A detailed comparison of the proposed MFPA technique with classical control techniques has been meticulously discussed. The results obtained indicate that the suggested MFPA tuned PID with MLI outperforms the conventional methods in better system stability, reduced harmonics, and enhanced capacity to track maximum power from the PV system. In addition to this, the Total Harmonic Distortion (THD) using Fast Fourier Transform (FFT) has been found to verify IEEE-1547 power quality constraints. The values are found to be well within limits, thus justifying its real-time applications

Maximum Power Point Tracking Algorithm for Advanced Photovoltaic Systems

Photovoltaic (PV) systems are the major nonconventional sources for power generation for present power strategy. The power of PV system has rapid increase because of its unpolluted, less noise and limited maintenance. But whole PV system has two main disadvantages drawbacks, that is, the power generation of it is quite low and the output power is nonlinear, which is influenced by climatic conditions, namely environmental temperature and the solar irradiation. The natural limiting factor is that PV potential in respect of temperature and irradiation has nonlinear output behavior. An automated power tracking method, for example, maximum power point tracking (MPPT), is necessarily applied to improve the power generation of PV systems. The MPPT methods undergo serious challenges when the PV system is under partial shade condition because PV shows several peaks in power. Hence, the exploration method might easily be misguided and might trapped to the local maxima. Therefore, a reasonable exploratory method must be constructed, which has to determine the global maxima for PV of shaded partially. The traditional approaches namely constant voltage tracking (CVT), perturb and observe (P&O), hill climbing (HC), Incremental Conductance (INC), and fractional open circuit voltage (FOCV) methods, indeed some of their improved types, are quite incompetent in tracking the global MPP (GMPP). Traditional techniques and soft computing-based bio-inspired and nature-inspired algorithms applied to MPPT were reviewed to explore the possibility for research while optimizing the PV system with global maximum output power under partially shading conditions. This paper is aimed to review, compare, and analyze almost all the techniques that implemented so far. Further this paper provides adequate details about algorithms that focuses to derive improved MPPT under non-uniform irradiation. Each algorithm got merits and demerits of its own with respect to the converging speed, computing time, complexity of coding, hardware suitability, stability and so on