Reliability evaluation of bulk power systems with wind generation using small signal stability analysis. (July 2021)

• Record Type: Journal Article
• Authors: Amaral, Tiago S.; Gomes, Sergio; Borges, Carmen L.T.
• Is Part Of: International journal of electrical power & energy systems. Volume 129(2021)
• Publication Date: 2021-07
• Subjects: Modal analysis -- Monte Carlo simulation -- Power system dynamics -- Power system reliability -- Small-signal stability; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2021.106840
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Reliability evaluation of bulk power systems using small-signal stability analysis. Innovative addition of network failures to probabilistic small-signal analysis. Monte Carlo state sampling of wind variation and generation-transmission failures. Adequacy of system states evaluated by their small-signal stability condition. Partial eigenvalue solution focusing on a user-defined subset of poles of interest. Abstract: This paper presents a computationally efficient methodology for reliability evaluation of bulk power systems with wind power generation using small-signal stability analysis. The methodology is based on the application of Monte Carlo simulation to calculate reliability indices, where the sampled system states are evaluated by means of their small-signal stability condition. Therefore, the system small-signal stability is evaluated for scenarios that consider the failure of generation and transmission assets and the unavailability and power variations of wind farms. Unlike previous works, the proposed methodology does not consider the probability of small variations in system parameters, but instead the probability of occurrence of the scenarios themselves including the large and nonlinear variations resulting from network failures. This allows comparing different alternatives for the planning of large power systems, such as different PSS settings or system reinforcement solutions, in a more realistic approach. Additionally, the methodology uses a non-conventional partial eigenvalue solution focusing on a user-defined subset of poles of interest, efficient and practical for the small-signal analysis of large-scale power systems.