# The efficiency paradox of discharge masking head loss in run-of-river hydropower generation

## TL;DR

This study examines how water flow and operational choices affect the efficiency of a hydropower plant, revealing that efficiency gains are mostly due to high water flow, but long-term sustainability needs better management of head loss and optimized operations.

## Contribution

The study identifies the dominant role of discharge over head in plant efficiency and proposes an optimal operational range for improved performance.

## Key findings

- Plant efficiency increased by 3.6%-points per decade and is strongly correlated with discharge (r = 0.998).
- Efficiency remains stable during drought but increases by 17–18% during wet years due to buffering from Lake Kivu.
- An optimal load factor range (78–82%) could improve efficiency by ~4% points compared to historical operations.

## Abstract

While climate impacts on hydropower output are well-documented, plant efficiency, the critical ratio of electrical energy generated to hydraulic energy input, remains an underexplored metric, particularly in data-limited regions. This study analyzes the efficiency dynamics of the Ruzizi I plant (29.8 MW) from 2000 to 2023 to unravel the interplay between hydrological drivers and operational constraints. Building on the established context of a hydraulic trade-off between water volume and head, we employed machine learning (Multiple Linear Regression, Random Forest, Gradient Boosting) and operational analysis to diagnose efficiency drivers. Results reveal that plant efficiency increased significantly (+ 3.6%-points/decade) and is overwhelmingly governed by discharge (r = 0.998), with machine learning models confirming the negligible role of head and seasonality. This indicates that efficiency gains are almost entirely flow-dependent, masking the potential negative impact of head loss. The system exhibits strong buffering from Lake Kivu, with efficiency remaining stable during drought but surging by 17–18% during wet years. Crucially, operational analysis identified an optimal load factor range (78–82%) that could improve efficiency by ~ 4% points compared to historical operation. However, a concurrent decline in available capacity factor (− 5.5%/decade) signals emerging non-hydrological constraints. These findings underscore that while water volume currently dominates efficiency gains, long-term sustainability requires managing sediment-induced head loss and optimizing operations within the identified optimal range to mitigate the underlying vulnerabilities in the energy conversion process.