This paper provides a comprehensive review of the maximum power point tracking (MPPT) techniques applied to photovoltaic (PV) power system available until January, 2012. A good number of publications report on different MPPT techniques for a PV system together with implementation. But, confusion lies while selecting a MPPT as every technique has its own merits and demerits. Hence, a proper review of these techniques is essential. Unfortunately, very few attempts have been made in this regard, excepting two latest reviews on MPPT [Salas, 2006], [Esram and Chapman, 2007]. Since, MPPT is an essential part of a PV system, extensive research has been revealed in recent years in this field and many new techniques have been reported to the list since then. In this paper, a detailed description and then classification of the MPPT techniques have made based on features, such as number of control variables involved, types of control strategies employed, types of circuitry used suitably for PV system and practical/commercial applications. This paper is intended to serve as a convenient reference for future MPPT users in PV systems.

A Comparative Study on Maximum Power Point Tracking Techniques for Photovoltaic Power Systems

State-of-the-art in artificial neural network applications: A survey

A new fuzzy-logic controller for maximum power point tracking of photovoltaic (PV) systems is proposed. PV modeling is discussed. Conventional hill-climbing maximum power-point tracker structures and features are investigated. The new controller improves the hill-climbing search method by fuzzifying the rules of such techniques and eliminates their drawbacks. Fuzzy-logic-based hill climbing offers fast and accurate converging to the maximum operating point during steady-state and varying weather conditions compared to conventional hill climbing. Simulation and experimentation results are provided to demonstrate the validity of the proposed fuzzy-logic-based controller.

Fuzzy-Logic-Control Approach of a Modified Hill-Climbing Method for Maximum Power Point in Microgrid Standalone Photovoltaic System

Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices, and models that contrast the pervasive von Neumann computer architecture This biologically inspired approach has created highly connected synthetic neurons and synapses that can be used to model neuroscience theories as well as solve challenging machine learning problems The promise of the technology is to create a brain-like ability to learn and adapt, but the technical challenges are significant, starting with an accurate neuroscience model of how the brain works, to finding materials and engineering breakthroughs to build devices to support these models, to creating a programming framework so the systems can learn, to creating applications with brain-like capabilities In this work, we provide a comprehensive survey of the research and motivations for neuromorphic computing over its history We begin with a 35-year review of the motivations and drivers of neuromorphic computing, then look at the major research areas of the field, which we define as neuro-inspired models, algorithms and learning approaches, hardware and devices, supporting systems, and finally applications We conclude with a broad discussion on the major research topics that need to be addressed in the coming years to see the promise of neuromorphic computing fulfilled The goals of this work are to provide an exhaustive review of the research conducted in neuromorphic computing since the inception of the term, and to motivate further work by illuminating gaps in the field where new research is needed

A Survey of Neuromorphic Computing and Neural Networks in Hardware.

Cell modelling and model parameters estimation techniques for photovoltaic simulator application: A review

Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system

A new MPPT controller based on the Ant colony optimization algorithm for Photovoltaic systems under partial shading conditions

Modeling, analysis and comparison of solar photovoltaic array configurations under partial shading conditions

Maximum power point tracking (MPPT) control techniques play a vital role in efﬁciency improvement of photovoltaic (PV) systems. It is mainly used to extract maximum possible power of the PV modules under both variable climatic and partial shaded condition (PSC). From literature, various types of MPPT techniques have been developed to track the maximum power point efficiently, ranging from conventional methods to artificial intelligence and bio-inspired methods. Each technique has its own advantage and drawbacks. This paper focuses mainly on a review on advancements of global maximum power point tracking (GMPPT) techniques of photovoltaic (PV) system subjected to partial shading conditions (PSC) to help the users to make the right choice when designing their system. The most recent and selected MPPT methods are discussed and classified as optimization, hybrid, mathematical model based methods and other GMPPT methods. This study will serve as interesting guide for researchers working on PV system field.

A review of global maximum power point tracking techniques of photovoltaic system under partial shading conditions

This paper proposes an intelligent control method for the maximum power point tracking (MPPT) of a photovoltaic system under variable temperature and insolation conditions. This method uses a fuzzy logic controller applied to a DC-DC converter device. The different steps of the design of this controller are presented together with its simulation. Results of this simulation are compared to those obtained by the perturbation and observation controller. They show that the fuzzy logic (...)

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Cherif Larbes

Papers

Genetic algorithms optimized fuzzy logic control for the maximum power point tracking in photovoltaic system

A new MPPT controller based on the Ant colony optimization algorithm for Photovoltaic systems under partial shading conditions

Modeling, analysis and comparison of solar photovoltaic array configurations under partial shading conditions

A review of global maximum power point tracking techniques of photovoltaic system under partial shading conditions

Maximum power point tracking using a fuzzy logic control scheme