Key Performance Indicators of Wind Farm: Implications for Energy Storage Sizing

The increasing penetration of wind energy requires robust indicators to characterize variability and to guide the integration of storage technologies. This study presents a KPI-based comparative framework applied to measured hourly data from a 140 MW wind farm in Morocco over one full year. The framework quantifies energy yield, variability, and operational performance, linking these empirical indicators to optimal storage sizing. Results show an annual generation of 458 GWh, corresponding to an average output of 52.3 MW and a capacity factor of 37.4%. Availability reached 87.6%, excluding grid curtailments, and operation near nominal power occurred in less than 0.2% of the year. Monthly capacity factors varied between 24.5% and 49.7%, revealing strong seasonal fluctuations. Ramp analysis indicates that 95% of hourly ramps remain below ±21 MW/h, while extreme events reached ±139 MW/h. These dynamics were translated into storage requirements, showing that a battery of approximately 40 MW / 160 MWh can handle short-term and diurnal variability, whereas hydrogen storage with ≈120 MW electrolyzers and multi-day capacity is required for seasonal balancing. The hybrid configuration demonstrates superior performance, achieving renewable utilization above 95% and curtailment below 2%. This work introduces a novel, KPI-driven, data-validated methodology that links operational metrics with techno-economic design, offering a practical tool to optimize hybrid storage strategies and accelerate large-scale renewable integration in Morocco and comparable power systems.

Authors

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-12-19
DOI
https://doi.org/10.1051/e3sconf/202568000086/pdf
Primary Topic
Hybrid Renewable Energy Systems
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Key Performance Indicators of Wind Farm: Implications for Energy Storage Sizing

Karim Choukri, Mohamed El Khaïli, Mariem Bibih, Houssam Eddine Chakir
Springer Link (Chiba Institute of Technology)
Hybrid Renewable Energy Systems
article

Key Performance Indicators of Wind Farm: Implications for Energy Storage Sizing

Karim Choukri, Mohamed El Khaïli, Mariem Bibih, Houssam Eddine Chakir
article en

Abstract

The increasing penetration of wind energy requires robust indicators to characterize variability and to guide the integration of storage technologies. This study presents a KPI-based comparative framework applied to measured hourly data from a 140 MW wind farm in Morocco over one full year. The framework quantifies energy yield, variability, and operational performance, linking these empirical indicators to optimal storage sizing. Results show an annual generation of 458 GWh, corresponding to an average output of 52.3 MW and a capacity factor of 37.4%. Availability reached 87.6%, excluding grid curtailments, and operation near nominal power occurred in less than 0.2% of the year. Monthly capacity factors varied between 24.5% and 49.7%, revealing strong seasonal fluctuations. Ramp analysis indicates that 95% of hourly ramps remain below ±21 MW/h, while extreme events reached ±139 MW/h. These dynamics were translated into storage requirements, showing that a battery of approximately 40 MW / 160 MWh can handle short-term and diurnal variability, whereas hydrogen storage with ≈120 MW electrolyzers and multi-day capacity is required for seasonal balancing. The hybrid configuration demonstrates superior performance, achieving renewable utilization above 95% and curtailment below 2%. This work introduces a novel, KPI-driven, data-validated methodology that links operational metrics with techno-economic design, offering a practical tool to optimize hybrid storage strategies and accelerate large-scale renewable integration in Morocco and comparable power systems.

Springer Link (Chiba Institute of Technology)
Affordable and clean energy
Openalex Percentile: Top 45%
Hybrid Renewable Energy Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Key Performance Indicators of Wind Farm: Implications for Energy Storage Sizing — Karim Choukri, Mohamed El Khaïli, et al. · Springer Link (Chiba Institute of Technology) (2025) | TGRS Research Map | TGRS