The IEA PVPS Task 13 group, experts who focus on photovoltaic performance, operation, and reliability from several leading R&D centers, universities, and industrial companies, is developing a framework for the calculation of performance loss rates of a large number of commercial and research photovoltaic (PV) power plants and their related weather data coming across various climatic zones. The general steps to calculate the performance loss rate are (i) input data cleaning and grading; (ii) data filtering; (iii) performance metric selection, corrections, and aggregation; and finally, (iv) application of a statistical modeling method to determine the performance loss rate value. In this study, several high‐quality power and irradiance datasets have been shared, and the participants of the study were asked to calculate the performance loss rate of each individual system using their preferred methodologies. The data are used for benchmarking activities and to define capabilities and uncertainties of all the various methods. The combination of data filtering, metrics (performance ratio or power based), and statistical modeling methods are benchmarked in terms of (i) their deviation from the average value and (ii) their uncertainty, standard error, and confidence intervals. It was observed that careful data filtering is an essential foundation for reliable performance loss rate calculations. Furthermore, the selection of the calculation steps filter/metric/statistical method is highly dependent on one another, and the steps should not be assessed individually.

The rising demand for high-density power storage systems such as hydrogen, combined with renewable power production systems, has led to the design of optimal power production and storage systems. In this study, a wind and photovoltaic (PV) hybrid electrolyzer system, which maximizes the hydrogen production for a diurnal operation of the system, is designed and simulated. The operation of the system is optimized using imperialist competitive algorithm (ICA). The objective of this optimization is to combine the PV array and wind turbine (WT) in a way that, for minimized average excess power generation, maximum hydrogen would be produced. Actual meteorological data of Miami is used for simulations. A framework of the advanced alkaline electrolyzer with the detailed electrochemical model is used. This optimal system comprises a PV module with a power of 7.9 kW and a WT module with a power of 11 kW. The rate of hydrogen production is 0.0192 mol/s; an average Faraday efficiency of 86.9 percent. The electrolyzer works with 53.7 percent of its nominal power. The availability of the wind for longer periods of time reflects the greater contribution of WT in comparison with PV towards the overall throughput of the system.