Spatio-Temporal Solar–Wind Complementarity Assessment in the Province of Kalinga-Apayao, Philippines Using Canonical Correlation Analysis

Karl Ezra S. Pilario, Jessa A. Ibañez, Xaviery N. Penisa, Johndel B. Obra, Carl Michael F. Odulio and Joey D. Ocon
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Karl Ezra S. Pilario: Process Systems Engineering Laboratory, Department of Chemical Engineering, College of Engineering, University of the Philippines Diliman, Quezon City 1101, Philippines
Jessa A. Ibañez: Power Electronics Laboratory, Electrical and Electronics Engineering Institute, University of the Philippines Diliman, Quezon City 1101, Philippines
Xaviery N. Penisa: Laboratory of Electrochemical Engineering (LEE), Department of Chemical Engineering, College of Engineering, University of the Philippines Diliman, Quezon City 1101, Philippines
Johndel B. Obra: Process Systems Engineering Laboratory, Department of Chemical Engineering, College of Engineering, University of the Philippines Diliman, Quezon City 1101, Philippines
Carl Michael F. Odulio: Power Electronics Laboratory, Electrical and Electronics Engineering Institute, University of the Philippines Diliman, Quezon City 1101, Philippines
Joey D. Ocon: Laboratory of Electrochemical Engineering (LEE), Department of Chemical Engineering, College of Engineering, University of the Philippines Diliman, Quezon City 1101, Philippines

Sustainability, 2022, vol. 14, issue 6, 1-12

Abstract: Increased utilization of renewable energy (RE) resources is critical in achieving key climate goals by 2050. The intermittent nature of RE, especially solar and wind, however, poses reliability concerns to the utility grid. One way to address this problem is to harmonize the RE resources using spatio-temporal complementarity analysis. Two RE resources are said to be complementary if the lack of one is balanced by the abundance of the other, and vice versa. In this work, solar–wind complementarity was analyzed across the provinces of Kalinga and Apayao, Philippines, which are potential locations for harvesting RE as suggested by the Philippine Department of Energy. Global horizontal irradiance (GHI) and wind speed data sets were obtained from the NASA POWER database and then studied using canonical correlation analysis (CCA), a multivariate statistical technique that finds maximum correlations between time series data. We modified the standard CCA to identify pairs of locations within the region of study with the highest solar–wind complementarity. Results show that the two RE resources exhibit balancing in the resulting locations. By identifying these locations, solar and wind resources in the Philippine islands can be integrated optimally and sustainably, leading to a more stable power and increased utility grid reliability.

Keywords: renewable energy; integration; correlation analysis; Pearson correlation; multivariate statistics; energy complementarity; solar; wind (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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