TEMPORAL CHANGES in the POWER PRODUCTION of REAL-WORLD PHOTOVOLTAIC SYSTEMS UNDER DIVERSE CLIMATIC CONDITIONS

• Activity Number: 38 - Reliability Insights
• Type: Contributed
• Date/Time: Sunday, July 30, 2017 : 2:00 PM to 3:50 PM
• Sponsor: Section on Physical and Engineering Sciences
• Author(s): Rojiar Haddadian* and Yang Hu and Alan J. Curran and Ahmad M Karimi and Timothy J. Peshek and Roger H. French
• Companies: Case Western Reserve University and Case Western Reserve University and Case Western Reserve University and Case Western Reserve university and Case Western Reserve University and Case Western Reserve university
• Keywords: Degradation ; Durability of PV systems ; Linear regression model ; Piecewise linear regression model ; Reliability ; Stepwise Akaike information criterion

Abstract

The impact of external variables on the power production of over 1000 photovoltaic (PV) power plants under real-world operating conditions was studied. These PV systems are part of the SDLE Research Center's network, which includes 787 PV power plants in 13 climate zones.

The analysis of these 5 to 15 year-long PV power datasets was driven by a non-relational data warehouse of multiple heterogeneous energy data. We developed a stable, scalable, fast processing, and querying technology based on Hadoop and its NoSQL database tool, HBase.

The system's power output was predicted from a month-by-month fitted linear regression model. Furthermore, a piecewise linear regression model was fitted to the monthly predicted power output values, and the annual change rate was calculated. Finally, through a stepwise Akaike Information Criterion (AIC), the variables that had significant influence on the system change rate were selected and rank ordered.

The rank-ordered contributors from this analysis demonstrate that Koppen-Geiger Climate Zones is the largest factor determining the power change rate, a result not previously acknowledged in the PV research community.