Maximum Power Point Tracking of Photovoltaic Renewable Energy System Using a New Method Based on Turbulent Flow of Water-Based Optimization (TFWO) Under Partial Shading Conditions

2021 ◽  
pp. 285-310
Author(s):  
Shohreh Nasri ◽  
Saber Arabi Nowdeh ◽  
Iraj Faraji Davoudkhani ◽  
Mohammad Jafar Hadidian Moghaddam ◽  
Akhtar Kalam ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Energy System ◽  
New Method ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Renewable Energy System ◽  
Water Based ◽  
Power Point

Maximum power point tracking and power flow management of hybrid renewable energy system with partial shading capability: A hybrid technique

2020 ◽  
Vol 42 (12) ◽  
pp. 2276-2296
Author(s):  
S Satheesh Kumar ◽  
A Immanuel Selvakumar
Keyword(s):  
Power Flow ◽  
Energy System ◽  
Grey Wolf Optimizer ◽  
Hybrid Technique ◽  
Grey Wolf ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Power Point

A grid connected hybrid energy system combining wind turbine (WT) and photovoltaic (PV) array generating system with energy storage system to supply continuous power to the load using hybrid technique is exhibited in this dissertation. The proposed hybrid technique is the joint execution of both the binary chaotic crow search optimizer (BCCSO) with grey wolf optimizer and random forest algorithm (GWORFA) and hence it is named as BCCSO-GWORFA technique. The main aim of the proposal is to optimally track the maximum power point tracking (MPPT) and to maintain the power flow of the grid connected HRES. Here, the BCCSO-based MPPT procedure optimizes the exact duty cycles required for the DC-DC converter of the PV under partial shading conditions and WT system under variable speed conditions based on the voltage and current parameters. On the other hand, the grey wolf optimizer (GWO) learning procedure-based random forest algorithm (RFA) predicts the control signals of the voltage source inverter (VSI) based on the active and reactive power variations available in the load side. To predict the control parameters, the proposed technique considers power balance constraints like RES accessibility, storage element state of charge, and load side power demand. The proposed strategy is implemented in MATLAB/Simulink working platform. The performance of the HRES is assessed by utilizing the comparison analysis with the existing techniques. The comparison results invariably prove the proposed hybrid technique effectiveness and confirm its potential to solve the related issues with efficiency of 99.5%.

scholarly journals A high performance hybrid MPPT control scheme for a grid connected PV system based three level NPCMLI

2018 ◽  
Vol 7 (2.20) ◽  
pp. 37 ◽  
Author(s):  
T Vijay Muni ◽  
K S. Srikanth ◽  
N Venkatesh ◽  
K L. Sumedha
Keyword(s):  
Renewable Energy ◽  
Characteristic Point ◽  
Energy System ◽  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Point Tracking ◽  
Power Point Tracking ◽  
Control Scheme ◽  
Power Point

This paper discusses about usage of novel control strategy to extract maximum power in case of solar energy conversion system for          renewable energy system applications with the power electronic technology based novel 3 level  neutral point clamped inverter.               Photovoltaic is one of the important renewable energy sources. Compared to other renewal energy sources photovoltaic energy is clean and abundantly available. Solar power is considered a very promising source for electric power generation. It is generally seen that the renewable energy system is highly stochastic in nature and does not guarantee continuous power throughout the period. The solar based renewable energy resource has to be coupled with the existing conventional gird which might overcome the stochastic behavior of the non conventional resources. To meet the demand of the various types of customers, the proposed combination or generation mix is highly desirable and ray of hope for future generation. The efficient usage of solar based power generation is certainly possible when interfaced with the existing gird and meet the load requirement of diversified customers who are dependent on electric power.Low efficiency of the solar PV module leads to research and improvement about control technology of different sub-modules of solar based renewable energy generation system interfaced with the existing grid. Generally, the photovoltaic system rating is constrained by the efficiency of percentage output power obtained from the PV panel. In order to achieve this objective , controller to extract the             maximum power from solar panel is designed and incorporated in the system known as Maximum power point tracking (MPPT). The return on investment is feasible with various constraints like environmental factors, other internal and external factors, only when the power output is optimum and maximum with the existing operating conditions.The maximum energy production that is power should be extracted from the solar panel in the given conditions. This process is called maximum powerpoint tracking. The point at each the proposed aim is reached, is called point of maximum power. The efficiency of the entire photovoltaic energy generation depends on the operating characteristic point. The load should ultimately get the optimum possible power obtained from the photovoltaic generation at the operating characteristic point [5]. Therefore, there should be some control logic or control technique in form of a suitable controller which is designated as maximum power point tracking (MPPT) controller. This            controller is designed in such a way that the maximum power is obtained from the photovoltaic module.In this work, Direct Prediction Method and P&O is implemented as a hybrid MPPT control scheme grid connected PV system based NPCMLI. MLI helpful in increasing dynamic performance of the PV system with the existing operating conditions. This MLI offers less harmonic disturbances and goes near to maximum possible power factor operation i.e. 1. The results are verified in Matlab /Simulink environment.   

scholarly journals Maximum Power Point Tracking of PV Systems under Partial Shading Conditions Based on Opposition-Based Learning Firefly Algorithm

2021 ◽  
Vol 13 (5) ◽  
pp. 2656
Author(s):  
Ahmed G. Abo-Khalil ◽  
Walied Alharbi ◽  
Abdel-Rahman Al-Qawasmi ◽  
Mohammad Alobaid ◽  
Ibrahim M. Alarifi
Keyword(s):  
Firefly Algorithm ◽  
Maximum Power ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Point Tracking ◽  
Opposition Based Learning ◽  
Power Point Tracking ◽  
Convergence Process ◽  
Power Point

This work presents an alternative to the conventional photovoltaic maximum power point tracking (MPPT) methods, by using an opposition-based learning firefly algorithm (OFA) that improves the performance of the Photovoltaic (PV) system both in the uniform irradiance changes and in partial shading conditions. The firefly algorithm is based on fireflies’ search for food, according to which individuals emit progressively more intense glows as they approach the objective, attracting the other fireflies. Therefore, the simulation of this behavior can be conducted by solving the objective function that is directly proportional to the distance from the desired result. To implement this algorithm in case of partial shading conditions, it was necessary to adjust the Firefly Algorithm (FA) parameters to fit the MPPT application. These parameters have been extensively tested, converging satisfactorily and guaranteeing to extract the global maximum power point (GMPP) in the cases of normal and partial shading conditions analyzed. The precise adjustment of the coefficients was made possible by visualizing the movement of the particles during the convergence process, while opposition-based learning (OBL) was used with FA to accelerate the convergence process by allowing the particle to move in the opposite direction. The proposed algorithm was simulated in the closest possible way to authentic operating conditions, and variable irradiance and partial shading conditions were implemented experimentally for a 60 [W] PV system. A two-stage PV grid-connected system was designed and deployed to validate the proposed algorithm. In addition, a comparison between the performance of the Perturbation and Observation (P&O) method and the proposed method was carried out to prove the effectiveness of this method over the conventional methods in tracking the GMPP.

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