article · Australian Journal of Electrical & Electronics Engineering
Managing voltage and power variability in automated intelligent photovoltaic systems remains a critical technical challenge. This research presents an automated control approach that combines Fractional Order Proportional Integral Derivative controllers with the Black Hole Optimisation algorithm to address these operational issues. The design incorporates thermal models for integrated batteries alongside solar panels to better regulate fluctuating power generation. By deploying the Black Hole Optimisation algorithm, fifteen separate operational parameters were fine-tuned across different system configurations. Objective validation identified a specific setup, designated as Instance 1, as the most effective arrangement because of its superior accuracy and scalability. Overall, the methodology provides a framework to enhance the automation, precision, and stability of photovoltaic power setups through algorithmic parameter optimisation.
Solar power generation often suffers from voltage fluctuations and inefficient power delivery. By automating the control of photovoltaic systems using specialised algorithms and controllers, solar installations can maintain steady voltage and power. Incorporating battery thermal behaviour helps ensure that energy storage works alongside solar generation predictably, making renewable power systems more reliable for everyday electricity needs.
This work could enable manufacturers and developers of photovoltaic control hardware to design more adaptable automated regulation systems. The research reflects early-stage computational modelling, as it focuses on parameter tuning and algorithmic validation across theoretical system instances rather than deployed field trials. Commercialisation would require testing on physical solar hardware and battery storage networks before integration into commercial energy management products.
AI-generated from the published abstract. Always read the original work before citing.
The article discusses the challenges related to voltage and power management in automated intelligent photovoltaic (PV) systems. It suggests that Fractional Order Proportional Integral Derivative (FOPID) controllers can help address these challenges effectively. The research aims to create a highly adaptable and precise automated intelligent PV system that focuses on managing voltage and power issues. It introduces a novel approach using the Black Hole Optimization (BHO) algorithm and leverages the advantages of FOPID controllers for automation. The study also considers thermal models for batteries within the automated intelligent PV system and explores different options to handle voltage and power issues stemming from PV panels. It involves fine-tuning 15 parameters using the BHO algorithm and concludes that one configuration (Instance 1) is preferable due to its superior accuracy and scalability. This choice is supported by objective validation. In essence, your abstract is about improving the performance and automation of PV systems, particularly in dealing with voltage and power challenges, through the application of FOPID controllers and the innovative BHO algorithm.
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DOI: 10.1080/1448837x.2024.2308415
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