Efficient water-based electricity strategies to reduce the number of switching operations in a smart grid

Akbarzadeh Niaki, Ali (2025) Efficient water-based electricity strategies to reduce the number of switching operations in a smart grid. Masters thesis, Memorial University of Newfoundland.

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Abstract

The increasing complexity of modern power systems, driven by the integration of renewable energy sources and the need for enhanced operational efficiency, has led to the widespread adoption of Transmission Switching (TS) as a cost-reduction strategy. TS optimizes the configuration of the transmission network by selectively switching transmission lines, thereby reducing the overall operational costs. However, this approach comes with significant drawbacks. The frequent switching operations required can degrade critical system components, particularly circuit breakers (CBs), leading to a shorter lifespan, higher maintenance and repair costs, increased likelihood of line outages, and a greater probability of load shedding. Moreover, these issues can collectively undermine the reliability of the entire power system. To address these challenges, this thesis presents a novel congestion management framework integrated within the Security-Constrained Unit Commitment (SCUC) problem. The primary objective of the proposed framework is to minimize the number of TS operations necessary to manage congestion, thereby mitigating the adverse effects on CBs and enhancing the overall reliability of the power grid. The framework introduces a grid-connected water-power system that leverages a fuel cell-based renewable energy source, coupled with a hydrogen storage tank, to provide additional flexibility in managing grid congestion. By utilizing this water-power system, the framework reduces the need for frequent TS operations, thus alleviating the associated strain on the transmission network. Additionally, the thesis addresses the inherent uncertainties in grid operations, particularly those related to fluctuating renewable energy output and unpredictable demand. To this end, an uncertainty-based Unscented Transform (UT) function is incorporated into the SCUC framework. This function enhances the robustness of the proposed methodology, ensuring that it remains effective under a wide range of operational scenarios and uncertainties. The proposed framework is validated through comprehensive simulations conducted on two standard test systems: a 6-bus and a 118-bus IEEE grid. These simulations are performed using Bender’s decomposition method in GAMS software, a widely recognized tool for large-scale optimization problems in power systems. The results from these simulations demonstrate that the proposed strategy significantly reduces line congestion and the number of TS operations required. Specifically, the framework achieves a 77% reduction in switching operations for the 6-bus system and a 45% reduction for the 118-bus system. These reductions not only extend the lifespan of CBs but also lead to substantial decreases in operational costs, thereby offering a more sustainable and cost-effective solution for modern power systems. The findings of this research contribute to the ongoing development of more resilient, efficient, and sustainable power systems, particularly in light of the increasing reliance on renewable energy sources. The proposed framework offers a viable path forward for grid operators seeking to balance cost efficiency with system reliability, all while integrating more renewable energy into the power grid.

Item Type: Thesis (Masters)
URI: http://research.library.mun.ca/id/eprint/16837
Item ID: 16837
Additional Information: Includes bibliographical references (pages 118-132)
Keywords: transmission switching, congestion management, Bender's decomposition, security constrained unit commitment (SCUC), uncertainty
Department(s): Engineering and Applied Science, Faculty of
Date: February 2025
Date Type: Submission
Digital Object Identifier (DOI): https://doi.org/10.48336/vkfq-bp51
Library of Congress Subject Heading: Electric power systems; Power transmission; Smart power grids; Mathematical optimization; Uncertainty (Information theory)

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