Abstract
This paper presents an improved mathematical model for calculating the solar test factor (STF) and solar reliability factor (SRF) of a photovoltaic (PV) automated equipment. By employing a unified metrics system and a combined testing suite encompassing various energy-efficient testing techniques, the aim of this paper is to determine a general fault coverage and improve the global SRF of a closed-loop dual-axis solar tracking system. Accelerated testing coupled with reliability analysis are essential tools for assessing the performance of modern solar tracking devices since PV system malfunctioning is directly connected to economic loss, which is an important aspect for the solar energy domain. The experimental results show that the unified metrics system is potentially suitable for assessing the reliability evaluation of many types of solar tracking systems. Additionally, the proposed combined testing platform proves efficient regarding fault coverage (overall coverage of 66.35% for all test scenarios), test time (an average of 275 min for 2864 test cycles), and power consumption (zero costs regarding electricity consumption for all considered test cases) points of view.
Highlights
Solar energy is the cleanest and most accessible renewable energy source available, and it has been used in a variety of ways by people all over the world for thousands of years
This paper presents a novel unified metrics system based on a fault coverage-aware metrics set that calculates an solar test factor (STF) and solar reliability factor (SRF) parameter for assessing the reliability of a dual-axis solar tracking device
By using a combined testing suite composed of software, hardware, and in-circuit testing (ICT) methods, this paper aims to improve the SRF parameter and adapt the fault coverage-aware metrics for mixed test scenarios
Summary
Solar energy is the cleanest and most accessible renewable energy source available, and it has been used in a variety of ways by people all over the world for thousands of years. The first uses of solar energy were for heating, cooking, and drying. Because solar tracking systems make use of additional automated equipment that is usually deployed around domestic homes, electrical components such as microcontroller units (MCUs), integrated circuits (ICs), and motor drivers are directly exposed to environmental factors such as humidity, rain, and snow, to name only a few. These factors contribute to the occurrence of system errors and faults. One of the significant barriers that modern testing techniques pose in today’s reliability assessment standards is that each testing method can generate only one individual fault coverage for software, hardware, and in-circuit testing (ICT) errors
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