Online power system parameter estimation and optimal operation

The 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.