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- W4386768252 abstract "The primary aim of electric power system design and operation is to ensure system security while adhering to system restrictions. As a security framework, it is vital to analyze the impact of probable failure situations on system performance. Despite the widespread use of performance indices (PI)-based approaches for contingency analysis, they cannot produce accurate rankings because of the masking effect. This paper introduces a fuzzy logic approach for ranking the network contingencies in severity order that reduces the masking effect. Following contingency ranking, the critical lines are modeled with fictional power injections at the relevant end points. Taking input uncertainties and network outages into account, the probability distribution of line power flows and state variables is then determined using a combined Cumulant and Gram-Charlier series expansion method. The dependency between the loads and wind power generations (WPGs) is modeled using Nataf transformation. A wind integrated 24-bus equivalent system encompassing Indian Southern region is tested with the proposed approach. Comparing with Monte-Carlo simulation, the proposed PLF yields precise and computationally efficient results." @default.
- W4386768252 created "2023-09-16" @default.
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- W4386768252 date "2023-01-01" @default.
- W4386768252 modified "2023-09-27" @default.
- W4386768252 title "Probabilistic Load Flow Study Considering Fuzzy Logic-Based Contingency Sequencing for Network Outages" @default.
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- W4386768252 doi "https://doi.org/10.1007/978-981-99-4175-9_6" @default.
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