A Case Study of Space-time Performance Comparison of Wind Turbines on a Wind Farm

TL;DR

This study compares multi-year power performance of turbines in a wind farm using a novel space-time analysis method that controls environmental variables, revealing differences and changes over time.

Contribution

Introduces a combined covariate matching and Gaussian process modeling approach for space-time performance comparison of wind turbines.

Findings

Identifies performance differences among turbines over four years.

Quantifies the impact of technical upgrades on turbine performance.

Provides a global view of turbine behavior over time.

Abstract

This paper presents an academia-industry joint case study, which was conducted to quantify and compare multi-year changes in power production performance of multiple turbines scattered over a mid-size wind farm. This analysis is referred to as a space-time performance comparison. One key aspect in power performance analysis is to have the wind and environmental inputs controlled for. This research employs, in a sequential fashion, two principal modeling components to exercise tight control of multiple input conditions -- a covariate matching method, followed by a Gaussian process model-based functional comparison. The analysis method is applied to a wind farm that houses 66 turbines on a moderately complex terrain. The power production and environmental data span nearly four years, during which period the turbines have gone through multiple technical upgrades. The space-time analysis presents a quantitative and global picture showing how turbines differ relative to each other as well as how each of them changes over time.