Performance Enhancement of Static Transfer Switch Using Advanced State Estimation for Loss Minimization in Power Distribution Networks

Authors

  • Ashirwad Dubey
  • Sunil Kumar Singh

DOI:

https://doi.org/10.22399/ijcesen.3304

Keywords:

Power Distribution loss minimization, Advance State Estimation Technique, Power Quality, Sensitive Load, Static Transfer switch (STS), Switching Optimization

Abstract

In modern power distribution networks, ensuring uninterrupted power supply with minimal losses is critical, especially for sensitive and critical loads. Static Transfer Switches (STS) play a key role in maintaining continuity by rapidly switching between two independent power sources during disturbances. However, conventional STS control strategies often rely on predefined thresholds and do not consider the dynamic state of the network, leading to inefficient switching and increased power losses. This paper proposes a novel approach to enhance the performance of STS by integrating advanced state estimation techniques. Using real-time estimation of voltage magnitudes, phase angles, and system stability indicators is performed. These estimated parameters are then used to intelligently control the switching operation of the STS, selecting the optimal source based on system health and expected power loss. A simulation model is developed in MATLAB/Simulink to evaluate the proposed method under various fault and load conditions. The results acquired demonstrated the competency of the proposed approach to endow improved voltage stability, reduced switching time, and significant minimization of power distribution losses as compared to traditional switching approaches. This work highlights the potential of state-estimation-based control in making STS operations more adaptive, reliable, and energy-efficient in smart distribution networks. 

References

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Published

2025-07-06

How to Cite

Dubey, A., & Sunil Kumar Singh. (2025). Performance Enhancement of Static Transfer Switch Using Advanced State Estimation for Loss Minimization in Power Distribution Networks. International Journal of Computational and Experimental Science and Engineering, 11(3). https://doi.org/10.22399/ijcesen.3304

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Section

Research Article