Surmount demand requirement in electrical energy has given a provision of integrating renewable energy to the three-phase grid-connected system. In particular, the penetration of distributed generation system has contributed more in electrical power generation. But the system connected produces adverse effects in grid due to the unpredictable atmospheric conditions. To handle such condition, in this research article, PV system is considered under study and a new two-stage CPG-P&amp;O MPPT method is used for interfacing PV with grid systems. In addition, a wide range of feed-in power to grid capacity at inverter level is briefly addressed. Further, the algorithm is designed to reduce the increased thermal stresses in switch and to get rid of the grid overshoot and power loss. The desired objective was acknowledged by the simulation results by ensuring delivery of optimal performance. © Springer Nature Singapore Pte Ltd. 2017.

Rajasekar N

Department of Energy and Power Electronics

School of Electrical Engineering

Vellore Campus

Kasthuri R

Bhageeratha Reddy K

Prasanth Ram J

Sudhakar Babu T

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Dynamic Performance Enhancement of Three-Phase PV Grid-Connected Systems Using Constant PowerGeneration (CPG)

Advances in Intelligent Systems and Computing Artificial Intelligence and Evolutionary Computations in Engineering Systems

A new method based on the concept of voltage band for efficient Distributed Maximum Power Point Tracking (DMPPT) of PV module is proposed. This novel formulation exhibits many advantages including faster convergence, improved tracking efficiency, zero steady state oscillations and simplicity in implementation. The paper unveils the possibility of utilizing a narrow voltage band for effective MPP tracking which has not been discussed so far in the literature. Extensive analysis is done and simulations are carried out in MATLAB/SIMULINK environment. To showcase the superiority of the proposed method, comparison is done with conventional methods for step change as well as gradual change in irradiation. © 2016 Elsevier Ltd.

Sustainable Energy Technologies and Assessments

Modeling, analysis and design of efficient maximum power extraction method for solar PV system

The extraction of maximum power from solar photovoltaic (PV) using Maximum Power Point Tracking (MPPT) methods is a promising research area in the recent past. Many methods including conventional methods, such as Hill Climbing and Incremental Conductance, and methods based on neural network, Fuzzy logic and bio-inspired algorithms, were proposed for MPPT application. However, all these methods suffer from drawbacks such as slower convergence, reduced power output, predominant steady state oscillations, larger memory requirement, and complex structure. Hence, in this paper an attempt is made to enhance existing Particle Swarm Optimization technique by emphasizing proper initial value selection. The key features of this method include the ability to track the global peak power accurately under partial shading conditions with almost zero steady state oscillations, faster dynamic response, and easy implementation. Simulations are carried out for different shading patterns and the results obtained are compared with existing methods. Further, simulation results are validated via experimental values. © 2016 AIP Publishing LLC.

Fulltext

Journal of Renewable and Sustainable Energy

Voltage band based improved particle swarm optimization technique for maximum power point tracking in solar photovoltaic system

Generation of electricity from solar energy has gained worldwide acceptance due to its abundant availability and eco-friendly nature. Even though the power generated from solar looks to be attractive; its availability is subjected to variation owing to many factors such as change in irradiation, temperature, shadow etc. Hence, extraction of maximum power from solar PV using Maximum Power Point Tracking (MPPT) method was the subject of study in the recent past. Among many methods proposed, Hill Climbing and Incremental Conductance MPPT methods were popular in reaching Maximum Power under constant irradiation. However, these methods show large steady state oscillations around MPP and poor dynamic performance when subjected to change in environmental conditions. On the other hand, bio-inspired algorithms showed excellent characteristics when dealing with non-linear, non-differentiable and stochastic optimization problems without involving excessive mathematical computations. Hence, in this paper an attempt is made by applying modifications to Particle Swarm Optimization technique, with emphasis on initial value selection, for Maximum Power Point Tracking. The key features of this method include ability to track the global peak power accurately under change in environmental condition with almost zero steady state oscillations, faster dynamic response and easy implementation. Systematic evaluation has been carried out for different partial shading conditions and finally the results obtained are compared with existing methods. In addition, simulations results are validated via built-in hardware prototype. © 2015 Elsevier B.V.

Applied Soft Computing

Modified Particle Swarm Optimization technique based Maximum Power Point Tracking for uniform and under partial shading condition

The contribution of renewable energy to the field of energy markets has been substantial over the last few years. A large number of PV array installations show the increasing contribution of solar energy to the renewable energy. Partial shading of the PV arrays is one of the most discussed and worked upon concept for the simple reasons that it decreases the power output of the PV array installations and exhibits multiple peaks in the I-V characteristics. As a result, the modules have to be reconfigured to get the maximum power output. This papers presents an optimization based approach for Total cross tied (TCT) connected modules in a PV array. The physical locations of the modules remain unchanged while the electrical connections are altered. The genetic algorithm (GA) as an optimization tool, gives the connection matrix for the new electrical interconnection which fetches the maximum power output from the PV array. This is done to obtain uniform dispersion of shadow throughout the panel. © 2014 Elsevier Ltd. All rights reserved.

Renewable and Sustainable Energy Reviews

Solar PV array reconfiguration under partial shading conditions for maximum power extraction using genetic algorithm

Solar PV cells usually operate at efficiency less than 20%, never generates maximum power due to change in environmental conditions such as irradiation, temperature, partial shading etc. Maximum power can be generated from PV cell with suitable tracking techniques. A modified Particle Swarm Optimization (MPSO) technique is proposed in this paper for tracking maximum power. This proposed evolutionary computation technique assures nearly zero steady state oscillation and faster convergence while tracking maximum power. The proposed PSO algorithm is tested on a CUK converter due to its higher efficiency and ripple free output. Simulations are carried out in MATLAB/SIMULINK and the computed results are validated in an experimental setup. © 2014 Published by Elsevier Ltd.

Journal	Data powered by TypesetAdvances in Intelligent Systems and Computing Artificial Intelligence and Evolutionary Computations in Engineering Systems
Publisher	Data powered by TypesetSpringer Singapore
ISSN	2194-5357
Open Access	0