Operational Efficiency Clustering Analysis of Wind Farms in Peru Using Multidimensional Performance Metrics

Arellanos-Tafur E. · 2026 IEEE 15th International Conference on Communication Systems and Network Technologies, CSNT 2026 (2026) · DOI: 10.1109/csnt69054.2026.11502125

Resumen

This research presents a comprehensive analysis of wind energy generation efficiency clustering in Peru using multidimensional performance metrics. The research analyzes operational data from eight major wind energy companies spanning from May 2023 to April 2025, encompassing a total generation of 6,876.3 GWh. The methodology employs clustering algorithms based on four key performance indicators: total generation capacity, capacity factor, operational variability, and efficiency index. Results reveal three distinct operational clusters: high-efficiency operators (Parque Eólico Tres Hermanas and Parque Eólico Marcona) with capacity factors exceeding 55%; medium-efficiency operators (Enel Generación Peru, Energía Eólica, and Energía Renovable del Sur) with capacity factors between 25% and 32%; and high-volume operators (Engie, GR Taruca, and GR Paino) with lower efficiency but higher absolute generation. The clustering analysis demonstrates significant operational disparities, with variability coefficients ranging from 43.3% to 109.8%, while seasonal patterns show peak generation during autumn months (March-May) with average monthly outputs of 270 GWh. The research findings provide valuable insights for optimizing wind farm operations, strategic planning, and policy development in Peru's renewable energy sector, contributing to the understanding of regional wind energy performance patterns and establishing benchmarks for future wind farm developments in similar geographical and climatic conditions.

Instituciones: Universidad Continental