Reliability of power systems with climate change impacts on hierarchical levels of PV systems

• Published in: Electric power systems research 2021-01, Vol.190, p.106830, Article 106830
• Main Authors: Altamimi, Abdullah, Jayaweera, Dilan
• Format: Article
• Language: English
• Subjects: Climate change; Critical components; Index terms; Markov chain modelling; Markov chains; Monte Carlo simulation; Photovoltaic cells; PV systems; Reliability; Reliability analysis; Reliability assessment; Solar energy; Subsystems; Thermal stress; Wind speed
• ISSN: 0378-7796; 1873-2046
• DOI: 10.1016/j.epsr.2020.106830

•A novel reliability framework is proposed for integrated PV power system and climate impact.•Impact of climate changes varies up to 2.5% and planning assessment is required.•The proposed framework can be tailored to study other integrated renewable generation. The accelerating rate of climate changeis likely to impact the performance of photovoltaic (PV) power generating systemsover the long run. This paper proposes along-termreliability assessment approach for PV integrated power systems considering the climate change effects on hierarchical level of PV systems. Hierarchical levels in the PV systems were formed considering components in a PV system, subsystems in a PV system, whole PV system, and the power grid level. The paper also suggests a way of mitigating the impact of climate change on PV systems through proactive design and the application of maintenance strategies for averting progressive component failure initiated by the effects of climate change. The approach takes into account different climatic factors including temperature, solar irradiation and wind speed as well as performanceaffecting factors including thermal stress, aging and degradation due to internal faultswithin the reliability evaluation framework. The approach drives through Monte Carlo simulation and Markov chain. The ability of identifying the critical components and subsystems in a PV system that lead to climate associated failures is one of the key benefits of the approach. Two established climate modelsare incorporated to generate climate change factors for the years 2020, 2050 and 2080. A set of case studies were conducted, and the results suggest that the reliability performance decreases considerably with theeffects of climate change.These effects are inconsistent over time when aging is taken into consideration.