Review of Maximum Power Point Tracking for Photovoltaic Systems
Keywords:
Photovoltaic (PV) System, Maximum Power Point Tracker (MPPT), Intelligent Optimization Technique, Particle Swarm Optimization (PSO), Fuzzy Logic Control (FLC), Artificial Neural Network (ANN), Artificial Bee Colony (ABC), Genetic Algorithm (GA), Ant Colony Optimization (ACO).Abstract
The demand of electrical energy is increasing with industrial development and the rate of
generation is unable to keep pace with increasing demand.The conventional energy sources
are limited so the obvious choice of clean, free source of energy whichprovidessafety for the
development is solar energy.But PV system has certain disadvantages like: low conversion
efficiency, high cost of installation hence we preferred MPPT for extracting the maximum
power output from Photovoltaic system. The output characteristic of photovoltaic array is
non-linear. The output power depends on temperature & irradiance. The common maximum
power point tracking (MPPT) techniques are Hill Climbing(HC), Incremental
Conductance(IC), Perturbation and Observation(P&O) butall these techniques have certain
drawbacks. So these drawbacks are minimized by usingintelligent optimization techniques
such as, Particle Swarm Optimization (PSO), Artificial Neural Network (ANN),Artificial Bee
Colony (ABC), Ant Colony Optimization(ACO),Genetic Algorithm(GA), and Fuzzy Logic
Control (FLC).All these techniques areused for extracting maximum power from
Photovoltaic(PV) System.
