A probabilistic security assessment approach to power systems with integrated wind resources. (January 2016)

• Record Type: Journal Article
• Authors: Le, D.D.; Berizzi, A.; Bovo, C.
• Is Part Of: Renewable energy. Volume 85(2016)
• Page Start: 114
• Page End: 123
• Publication Date: 2016-01
• Subjects: Probabilistic power flow -- Cumulant -- Security assessment -- Correlation -- Frequency control -- Wind power; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.renene.2015.06.035
• Languages: English
• ISSNs: 0960-1481

Abstract

Abstract: Renewable energy sources, such as wind and photovoltaic solar, have added additional uncertainty to power systems. These sources, further to the conventional sources of uncertainty due to stochastic nature of both the load and the availability of generation resources and transmission assets, make clear the limitations of the conventional deterministic power flow in power system analysis and security assessment applications. In order to manage uncertainties, probabilistic approaches can provide a valuable contribution. In this paper, we propose a new scheme for probabilistic security assessment. The model can deal with various types of probability distributions modeling power injections and can explicitly represent the effects on system security of correlation among nodal power injections (such as wind power) and of contingencies due to branch and generating unit outages. In addition, the steady-state behavior of the frequency regulation is explicitly included in the model. A new approach to deal with current limits is also proposed. Extensive testing on both the modified IEEE-14 bus test system and the Sicilian power system indicates good performance of the proposed approach in comparison with the result obtained by the computationally more demanding Monte Carlo approach. Highlights: A new scheme for probabilistic security assessment is proposed. A technique to account for various types of probability distributions is developed. Probabilistic evaluation of currents can be performed. Impacts of contingencies and correlations on security are explicitly assessed. The proposed model is suitable for large-scale power systems.