In an era defined by the rapid evolution of energy technologies and the necessity of sustainable power generation, effective voltage control is a critical component in optimizing the performance of the power distribution grid and the seamless integration of renewable energy sourc
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In an era defined by the rapid evolution of energy technologies and the necessity of sustainable power generation, effective voltage control is a critical component in optimizing the performance of the power distribution grid and the seamless integration of renewable energy sources. This thesis presents the development and evaluation of an adaptive voltage control policy for high voltage to medium voltage transformers aimed at mitigating voltage limit violations in modern power distribution networks.
The motivation for this research arises from the increasing integration of distributed energy resources and the growing complexity of power grids, which require dynamic and robust voltage management strategies. The proposed policy utilizes a voltage control curve, optimized using a genetic algorithm, which systematically identifies the best parameters for the curve to ensure voltage stability and minimize violations across diverse grid configurations.
The methodology involves quasi-dynamic simulations performed on 30 real-world distribution grids, which test the effectiveness of the voltage control curves in maintaining grid stability under varying load and generation conditions. This was done by setting a stricter ±3% voltage limit for the medium voltage grid. Results show an average reduction of 88.54% in voltage limit violations and a 17.19% decrease in the maximum difference between the maximum and minimum voltage levels in the medium voltage grid throughout a complete year (2023). This study highlights the importance of a grid-specific voltage control curve, as every distribution grid exhibited unique voltage regulation needs.
Furthermore, the policy was evaluated under projected grid scenarios, demonstrating sustained effectiveness across two future timeframes: one set five years and the other ten years into the future. In the first scenario (2028), an 80.06% reduction in voltage limit violations was achieved, while the second scenario (2033) still showed a reduction of 62.25%.
Through the genetic algorithm optimization, the voltage control policy adapts to fluctuating grid dynamics, contributing to improved power quality and the successful integration of distributed energy resources. While effective in medium voltage grids, further research is needed to explore the policy’s applicability to low voltage networks and in environments with limited data availability.
The simplicity and universality of the proposed adaptive voltage control strategy make it a practical solution for real-world deployment, as it can be implemented on existing hardware. In contrast, the proposed strategy alone will not be enough to completely eliminate all the voltage stability problems in distribution grids and additional measures are necessary. However, by minimizing voltage violations and improving grid resilience, this work offers a robust framework for voltage management in modern, evolving power distribution networks, particularly in the context of the global energy transition towards sustainable energy sources.