Volume 19, Issue 2 (June 2023)                   IJEEE 2023, 19(2): 2558-2558 | Back to browse issues page

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Ramezanzadeh S P, Mirzaie M, Shahabi M. Calculation and Forecasting of MTDC Grids' Reliability Indices Considering the Expansion of the Grid and Grid Components' Characteristics. IJEEE 2023; 19 (2) :2558-2558
URL: http://ijeee.iust.ac.ir/article-1-2558-en.html
Abstract:   (131 Views)
Due to the role of renewable energy sources in providing energy in future power systems, multi-terminal HVDC (MTDC) systems have attracted the attention of utilities and decision-makers. The reliability study of MTDC grids is critical for analyzing electrical power systems and providing a reliable power delivery system. Reliability modeling and study of six MTDC transmission networks containing hybrid DC circuit breakers for interrupting transmission line contingencies is presented in this paper. This study incorporates precise reliability models of MTDC grid configurations and describes a step-by-step grid expansion. Considering these reliability models, critical reliability indices of the demand bus of the grid have been obtained to calculate the amount of energy not supplied. Also, the influence of the tapping stations on the demand bus reliability features has been investigated. Since the components' characteristics significantly affect the system's reliability, the impact of the transformer and DC circuit breaker's failure rate and repair time on the reliability features of the demand bus of all MTDC grids have been assessed. The obtained results are employed to forecast the effect of simultaneous change of the repair time and failure rate of the transformer, the most influential component in determining the reliability indices, on the proposed configuration by incorporating multivariate linear regression.
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Type of Study: Research Paper | Subject: Artificial Intelligence Techniques
Received: 2022/06/11 | Revised: 2023/06/06 | Accepted: 2023/06/11

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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.