
@Article{ee.2026.083885,
AUTHOR = {Kai Xie, Dong Han, Genjun Chen, Dayun Zou, Jinran Wang, Ciwei Gao, Jingyi Li},
TITLE = {Research on Switching Criteria for Primary–Backup Systems in Electricity Markets under the Background of Renewable Energy Participation},
JOURNAL = {Energy Engineering},
VOLUME = {},
YEAR = {},
NUMBER = {},
PAGES = {{pages}},
URL = {http://www.techscience.com/energy/online/detail/27874},
ISSN = {1546-0118},
ABSTRACT = {With the continuous advancement of carbon peaking and carbon neutrality goals, the large-scale integration of renewable energy introduces significant uncertainty and operational risks to electricity market clearing systems. To address these challenges, this paper proposes a primary–backup dual-system parallel clearing framework based on differentiated solution strategies, where the primary system employs the interior-point method and the backup system adopts sequential quadratic programming. A data-driven switching criterion is developed by monitoring the variation rates of nodal prices, transmission line power flows, and generator ramping rates, and determining their critical thresholds through statistical analysis. Case studies conducted on a 5-bus system and a 15-bus system in the MATLAB R2022b environment demonstrate that the proposed method effectively improves system robustness under renewable energy uncertainty. Specifically, compared with the no-switching scenario, the proposed framework reduces constraint violation rates by 6.13% and mitigates fluctuations in nodal prices and generator outputs by approximately 7.52% and 10.0%, respectively, while maintaining comparable operational costs. In addition, the derived switching thresholds enable timely and reliable system transitions without introducing excessive switching frequency. These results confirm that the proposed dual-system clearing framework enhances the security, stability, and adaptability of electricity market operations, providing a practical and scalable solution for high-renewable power systems.},
DOI = {10.32604/ee.2026.083885}
}



