Efficient integration of (n − 1)-security into probabilistic network expansion planning. (January 2018)

• Record Type: Journal Article
• Authors: Wiest, P.; Rudion, K.; Probst, A.
• Is Part Of: International journal of electrical power & energy systems. Volume 94(2018)
• Page Start: 151
• Page End: 159
• Publication Date: 2018-01
• Subjects: Branch outage -- Contingency analysis -- Monte Carlo method -- Power system planning -- Probabilistic load flow; 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.2017.07.002
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: Efficient linearized calculation method for contingency analysis. Formulation of Line Outage Distribution Factors for multiple segment lines. High Accuracy of Linearized Calculation Compared to Newton Raphson. Significant lower Computation Times for Linearized Calculation. Probabilistic Distribution Grid Planning for High Penetration of RES. Abstract: This paper presents a new efficient way to integrate the (n − 1)-security into modern probabilistic network expansion planning. Therefore, a method is presented for an (n − 1)-secure probabilistic load flow based on AC distribution factors. For the simulation of multiple segment outages, a new mathematical description is presented. The presented method is able to handle the islanding of single nodes within the calculation. Afterwards, a linearization is presented using the superposition theorem and Newton Raphson load flow calculations. A new linearization of the power flow is used to consider reactive power flows. Based on this, AC line outage distribution factors can be calculated using the normal operation state of the grid. The analyzed sensitivity of the distribution factors to the load and generation scenario is low. Therefore, the linearized method shows a good congruency. Additionally, the proposed method identifies correctly the worst case conditions in massively reduced computation time. A comparison between the (n − 1)-secure probabilistic method and today's deterministic planning methods show that the high penetration of renewable energy sources leads to an under dimensioning of the grid.