Optimal power tracker for stand-alone photovoltaic system using Artificial Neural Network (ANN) and Particle Swarm Optimisation (PSO)

Kok, Boon Ching and Goh, Hui Hwang and Chua, H. G. (2012) Optimal power tracker for stand-alone photovoltaic system using Artificial Neural Network (ANN) and Particle Swarm Optimisation (PSO). In: International Conference on Renewable Energies and Power Quality (ICREPQ’12), 28-30 March 2012, Spain.

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Abstract

In recent years, many intelligent techniques and approaches have been introduced into photovoltaic (PV) system for the utilisation of free harvest renewable energy. Generally, the output power generation of the PV system rely on the intermittent solar insolation, cell temperature, efficiency of the PV panel and its output voltage level. Consequently, it is essential to track the generated power of the PV system and utilise the collected solar energy optimally. Artificial Neural Network (ANN) is initially used to forecast the solar insolation level and followed by the Particle Swarm Optimisation (PSO) to optimise the power generation of the PV system based on the solar insolation level, cell temperature, efficiency of PV panel and output voltage requirements. This paper proposes an integrated offline PSO and ANN algorithms to track the solar power optimally based on various operation conditions due to the uncertain climate change. The proposed approach has the capability to estimate the amount of generated PV power at a specific time. The ANN based solar insolation forecast has shown satisfactory results with minimal error and the generated PV power has been optimised significantly with the aids of the PSO algorithm.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:photovoltaic system; optimal power tracking; power generation; artificial neural network; particle swarm optimisation
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK1001-1841 Production of electric energy or power. Powerplants. Central stations
Divisions:Faculty of Electrical and Electronic Engineering > Department of Electrical Power Engineerings
ID Code:6110
Deposited By:Normajihan Abd. Rahman
Deposited On:16 Feb 2015 14:24
Last Modified:16 Feb 2015 14:24

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