Analyzing the mechanisms behind temporal correlation between power sources using frequency separated time scales: A Swedish case study on PV and wind. (15th November 2022)

• Record Type: Journal Article
• Authors: Lindberg, O.; Lingfors, D.; Arnqvist, J.
• Is Part Of: Energy. Volume 259(2022)
• Publication Date: 2022-11-15
• Subjects: Hybrid power park -- Wind power -- PV power -- Temporal correlation -- Reanalysis product -- Site assessment; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2022.124817
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The temporal correlation between different power generation sources is important for quantifying the reduction in variability when constructing co-located hybrid power parks (HPPs) that combine multiple power sources. This study investigates the physical mechanisms behind correlation on time scales relevant for the power system using frequency separated time scales. The methodology is universally applicable to any data set consisting of at least two power sources and could be adjusted accordingly. The methodology is demonstrated and validated in a case study across Sweden for wind and PV power generation, using the meteorological reanalysis dataset CosmoREA-6. All studied time-scales (seasonal, mid-term, synoptic and diurnal) showed anti-correlated characteristics, although the magnitude of temporal correlation is highly dependent on the time-scale considered. The highest potential for useful anti-correlation is found on the seasonal cycle, followed by the diurnal cycle where existing wind turbine sites, on average, have stronger anti-correlation than the average site. The validation showed good correspondence with measurements for all time-scales. However, an underestimations of the results were found for the diurnal and seasonal cycle while this was shown to have a minor effect when analyzing the correlation on different time scales. The methodology of the case study should be generally valid for all similar climates. Highlights: A methodology to study correlation between co-located wind and solar is proposed. All studied time scales showed anti-correlated characteristics. The annual cycle followed by the diurnal cycle was found to be the most useful. Wind turbines sites show stronger anti-correlation. Validation of CosmoREA-6 revealed deficiencies in wind power modeling.