Master's Degree in Water Management and Water Structures

2018–2020

Advanced studies in water management with focus on landscape water systems.

Brno University of Technology Supervisor: Ing. Pavel Menšík, Ph.D. Water Management General water management, focusing on landscape water systems.

Thesis

Title (EN)

The Design of Rules for the Hydropower Control of a Dam Reservoir

Title (CZ)

Návrh pravidel pro řízení hydroenergetické funkce vodní nádrže

Open thesis

Abstract

The master's thesis aimed to design an algorithm for optimizing the hydropower potential of a small run-of-river dam reservoir. By using electricity market price trends, the algorithm allows for efficient water resource management to maximize energy production and profit. The proposed rules were tested through simulation models under varying hydrological conditions to ensure robustness.

Achievements

Dean's commendation for excellent thesis

Other

Graduated with Honors

Main Research Goals

The thesis aimed to develop a simulation-based control strategy for optimizing dam hydropower operations.

The primary objectives included: developing an algorithm for adaptive control of dam releases based on electricity market prices, ensuring sustainable water management, and maximizing the profitability of small hydropower plants.

Simulation Model and Algorithms

The research employed simulation-based methods to evaluate different control strategies for hydropower production.

A simulation model was developed to test the effectiveness of the proposed control rules under various hydrological scenarios. The algorithm incorporates electricity market price data, flow data, and operational constraints to optimize water release schedules.

Performance of the Algorithm

The algorithm demonstrated significant improvement in energy production efficiency and profitability.

The results showed that the proposed control rules increased energy production during high electricity price periods while maintaining sustainable water levels. It also proved effective in different hydrological conditions, including dry and wet years.

Applications and Recommendations

The findings provide a foundation for real-world applications in dam management.

The developed approach can be adapted to other reservoirs and integrated into operational frameworks to enhance energy efficiency and water resource sustainability. Further development could incorporate real-time data and AI-driven decision-making tools.