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Deriving Power Uncertainty Intervals for Low Voltage Grid State Estimation Using Affine Arithmetic

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Pseudo-measurements are usually applied as substitutes for measurement data to obtain observability even in case of sparse measurement configurations. The quality of pseudomeasurements strongly affects the accuracy of state estimation results. Generating pseudo-measurements is not a straightforward task in particular for customers with highly stochastic behavior. This paper proposes a novel approach to obtain verified boundaries of pseudo-measurements, which are consistent to currently available measurement information. These boundaries allow to verify generated pseudo-measurements, whether they are compliant to current system conditions. Additionally, tight boundaries are suitable to generate pseudo-measurements on-line regardless of the customer’s structure. The proposed algorithm applies Affine Arithmetic - a self-validated numerical model - to the state estimation problem and treats pseudo-measurements as main source of uncertainty. The key properties of the algorithm are rigorous, iterative, linearizing and large-scale. These properties are demonstrated by numerical simulation of two benchmark grid models of different complexity. Computational and implementation issues are addressed in detail.

Author(s):

Maximilian Schmidt    
Institute of Electrical Power Systems and High Voltage Engineering, University of Technology Dresden
Germany

Peter Schegner    
Institute of Electrical Power Systems and High Voltage Engineering, University of Technology Dresden
Germany

 

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