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- Uzunoglu, Bahri, et al.
(författare)
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Maximum Likelihood Ensemble Filter State Estimation for Power Systems
- 2018
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Ingår i: IEEE Transactions on Instrumentation and Measurement. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9456 .- 1557-9662. ; 67:9, s. 2097-2106
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Tidskriftsartikel (refereegranskat)abstract
- Maximum likelihood ensemble filter (MLEF) is an ensemble-based deterministic filtering method. It optimizes a nonlinear cost function through maximum likelihood and utilizes low-dimensional ensemble space on the calculation of Hessian preconditioning of the cost function. This paper implements the MLEF as a state estimation tool for the estimation of the states of a power system, and presents the first MLEF application study on a power system state estimation. The MLEF methodology is introduced into power systems and the simulations are implemented for a three-node benchmark power system and 68-bus test system which have been employed in several previous studies to address a discontinuous problem where derivative is not defined. This is in contrast to gradient-based methods in the literature that needs gradient and Hessian information which is not defined in jumps. The performance of the filter on the presented problem is analyzed and the results are presented. Results indicate that the estimation convergence is achieved with the MLEF method.
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