Overview of Black-Box Arc Models and Parameter Identification Techniques for Simulation of PV Systems

Abstract

Solar energy is widely regarded as an environmentally friendly and sustainable source of power. It reduces greenhouse gas emissions and dependency on fossil fuels, contributing to a cleaner environment. It also provides cost savings and enhances energy security. However, technical challenges persist. Poor installation, inadequate maintenance, and aging can degrade photovoltaic (PV) systems, leading to failures or faults. These issues increase the risk of power losses, electrical shocks, and fires. Direct Current (DC) arcs, in particular, pose a significant fire hazard in PV systems due to their unpredictability and high potential for damage. However, accurately defining parameters for real-world DC arc faults is difficult. Developing computational models of electric arcs is essential for simulating, analyzing, and detecting these faults. In that sense, this work provides a comprehensive overview of the prominent black-box arc models documented in the scientific literature, along with various methods for parameter identification, to facilitate the investigation of arc-related incidents within PV systems.

Keywords

• DC arcs
• metaheuristics
• parameters identification
• solar energy