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• W2786012603 abstract "This paper summarizes BC Hydro's experience in applying artificial neural networks (ANN) to on-line loading limit monitoring and Reliability Must-Run (RMR) development against voltage instability. Compared to previous loading limit and voltage stability margin evaluation methods based on ANN, the proposed strategy can be successfully employed in practical systems. Instead of relying on the ANN to learn directly from load-flow data, the proposed strategy uses operational experience and knowledge to define the feature selection and training data set generation. The proposed strategy was tested on the BC Hydro Vancouver Island system for operation against voltage instability. The results show that the method is accurate and reliable for practical system. The proposed technique can streamline the process of RMR development systems to secure reliable system operation." @default.
• W2786012603 created "2018-02-23" @default.
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• W2786012603 date "2017-07-01" @default.
• W2786012603 modified "2023-09-25" @default.
• W2786012603 title "On-line loading limit monitoring and reliability must-run development using artificial neural networks" @default.
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• W2786012603 doi "https://doi.org/10.1109/pesgm.2017.8274539" @default.
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