Du, XuXuDuEngelmann, AlexanderAlexanderEngelmannFaulwasser, TimmTimmFaulwasserHouska, BorisBorisHouska2024-03-042024-03-042021-05-25Proceedings of the American Control Conference 2021: 3126-3131 (2021)9781665441971https://hdl.handle.net/11420/46186The integration of renewables into electrical grids calls for novel control schemes, which usually are model based. Classically, for power systems parameter estimation and optimization-based control are often decoupled, which may lead to increased cost of system operation during the estimation procedures. The present work proposes a method for simultaneously minimizing grid operation cost and estimating line parameters. To this end, we rely on methods from optimal design of experiments. This approach leads to a substantial reduction in cost for optimal estimation and in higher accuracy in the parameters compared with standard combination of optimal power flow and maximum-likelihood estimation. We illustrate the performance of the proposed method on simple benchmark system.en0743-1619202131263131ACCAdmittance EstimationOptimal Experiment DesignOptimal Power FlowPower System Parameter EstimationNatural Resources, Energy and EnvironmentComputer SciencesConference Paper10.23919/ACC50511.2021.9482814Conference Paper