Enhancing computational efforts with consideration of probabilistic available transfer capability using probabilistic collocation method
Most of Probabilistic Load Flow (PLF) studies with consideration of generation and load uncertainties concern with reducing efforts computational in addition high accuracy. One of the most famous expansion method used is Gram-Charlier and Comulants. This paper proposed a Probabilistic Collocation...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
Universiti Teknologi Malaysia
2016
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/52440/ http://irep.iium.edu.my/52440/ http://irep.iium.edu.my/52440/1/52440_Enhancing%20computational%20efforts%20with%20consideration.pdf |
| Summary: | Most of Probabilistic Load Flow (PLF) studies with consideration of generation and load uncertainties
concern with reducing efforts computational in addition high accuracy. One of the most famous
expansion method used is Gram-Charlier and Comulants. This paper proposed a Probabilistic Collocation
Method (PCM) to improve the common used PLF computation methods in order to model the network
topology uncertainties. This method uses Probabilistic Distribution Functions (PDF) concept to model the
impact of network uncertainties as a linear function of power injections. Maintaining the linear
relationship between line flows and power injections of transmission line flows. The proposed method is
examined using IEEE39-bus test system. Numerical comparison with Monte Carlo simulation method
was presented in this paper. Study results indicated that the proposed method has significantly reduced
the computational efforts while maintaining a high degree of accuracy. |
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