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- W3173171618 abstract "Finding a trade-off between robustness and computational efficiency is one of the major challenges when deriving a state estimation algorithm. Conventional Least Absolute Value (LAV) algorithms are robust against outliers, but impose significant computational burden. In this paper, we propose two LAV-based state estimators that are capable of taking into account conventional and synchrophasor measurements simultaneously. Both algorithms utilize a linear modelling framework for all available measurements. The first algorithm is based on the linear LAV method and is formulated as a single Linear Program, while the second leverages an alternative LAV-based formulation that can be solved by gradient-based methods. As a result, both algorithms are computationally significantly more efficient than the conventional LAV method, while preserving the bad data rejection properties. The performance of the algorithms is evaluated on a range of test cases of various sizes." @default.
- W3173171618 created "2021-07-05" @default.
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- W3173171618 date "2021-04-11" @default.
- W3173171618 modified "2023-10-16" @default.
- W3173171618 title "Computationally Efficient Robust State Estimation for Power Transmission Systems with RTU and PMU Measurements" @default.
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- W3173171618 doi "https://doi.org/10.1109/naps50074.2021.9449765" @default.
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