A novel MPPT algorithm based on particle swarm optimization for photovoltaic systems
| Autor: | Adel El-Shahat, Ahmed F. Zobaa, Ramdan B. A. Koad |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Maximum power principle
020209 energy photovoltaic (PV) systems perturb and Observe (P&O) Method Stability (learning theory) 02 engineering and technology partial shading conditions (PSC) symbols.namesake Control theory maximum power point tracking (MPPT) 0202 electrical engineering electronic engineering information engineering Point (geometry) Multi-swarm optimization MATLAB Mathematics computer.programming_language particle swarm optimization (PSO) OPAL-RT Renewable Energy Sustainability and the Environment 020208 electrical & electronic engineering Photovoltaic system Lagrange polynomial Particle swarm optimization incremental conductance (IncCond) symbols computer |
| Popis: | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works In this paper a new maximum-power-point-tracking (MPPT) method for the photovoltaic (PV) system using an improved particle swarm optimization (PSO) algorithm is proposed. The proposed control scheme eliminates the problems in the conventional methods as it uses only a simple numerical calculation to initialize the particles around the global maximum power point (GMPP). Hence, the PSO will utilize less iteration to reach the MPP. The proposed algorithm is verified by using MATLAB SIMULINK tool, several simulations being carried out, and compared to Perturb and Observe (P&O) Method, Incremental Conductance (IncCond) Method, and conventional Practical Swarm Optimization based MPPT Algorithm. The simulation results indicate that the proposed algorithm can effectively enhance stability and fast tracking capability even under rapidly changing atmospheric conditions. |
| Databáze: | OpenAIRE |
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