Abstract
Due to global climate change as a result of pollution caused by the burning of fossil fuels, the world has changed its view when it comes to power generation. The focus is now more on natural and clean energy, such as solar PV systems. An effective solar PV system is not a simple system, as the sun is not a stationery object. The sun moves from east to west daily and that makes the design and installation of an effective solar PV system challenging for optimal power harvesting. The purpose of this paper is to compare two algorithms (linear regression and fuzzy logic) that are applied to a dual-axis tracker in order to maximize the output power yield that may be obtained from a fixed-axis system. One fixed-axis PV module serves as the baseline for comparing the results of the dual-axis trackers that are controlled by the two algorithms. A key recommendation is to align a PV module perpendicular to the sun from sunrise to sunset using a control algorithm based on fuzzy logic principles in order to extract the maximum amount of available energy.
Highlights
As a kind of clean and renewable energy source, solar photovoltaic (PV) systems have been drawing attention, especially in the field of electricity generation, due to the shortage and pollution effects of fossil fuels [1]
The purpose of this paper is to compare two algorithms that are applied to a dual-axis tracker in order to maximize the output power yield that may be obtained from a fixed-axis system
This paper compared two algorithms that were applied to a dual-axis PV module tracking system to maximize their output power
Summary
As a kind of clean and renewable energy source, solar photovoltaic (PV) systems have been drawing attention, especially in the field of electricity generation, due to the shortage and pollution effects of fossil fuels [1]. An important part of a solar PV system is the PV modules that produce maximum output power when direct solar radiation strikes its top surface at 90°angles. Aligning it perpendicular (90°) to the sun‟s rays results in more solar energy collection by the PV module [3]. The maximum output power of the PV module depends on atmospheric conditions (such as air pollution and cloud movements), the load profile, the tilt and orientation angles [4]. The purpose of this paper is to compare two algorithms (linear regression and fuzzy logic) that are applied to a dual-axis tracker in order to maximize the output power yield that may be obtained from a fixed-axis system
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