Abstract

AbstractElectricity from wind and, to a lesser extent, solar energy is intermittent and not controllable. Unlike conventional power generation, therefore, this electricity is not suitable to supply base-load electric power. In the future, with greater penetration of these renewable sources, intermittency and control problems will become critical. Here, the authors explore the use of canonical correlation analysis (CCA) for analyzing spatiotemporal balancing between regional solar and wind energy resources. The CCA allows optimal distribution of wind farms and solar energy plants across a territory to minimize the variability of total energy input into the power supply system. The method was tested in the southern half of the Iberian Peninsula, a region covering about 350 000 km2. The authors used daily-integrated wind and solar energy estimates in 2007 from the Weather Research and Forecasting (WRF) mesoscale model, at a spatial resolution of 9 km. Results showed valuable balancing patterns in the study region, but with a marked seasonality in strength, sign, and spatial coverage. The autumn season showed the most noteworthy results, with a balancing pattern extending almost over the entire study region. With location of reference wind farms and photovoltaic (PV) plants according to the balancing patterns, their combined power production shows substantially lower variability than production of the wind farms and PV plants separately and combined production obtained with any other locations. Atmospheric circulations associated with the balancing patterns were found to be significantly different between seasons. In this regard, synoptic-scale variability played an important role, but so did topographic conditions, especially near the Strait of Gibraltar.

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