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DOE OSTI2019

Continuum Modeling of Inductor Magnetic Hysteresis and Eddy Currents in Resonant Circuits

This paper presents a high-fidelity finite-element modeling technique for magnetic hysteresis and eddy current losses in toroid inductors. The method is based on the separation of ferromagnetic loss characteristics into two components: a quasi-static hysteresis component and a dynamic eddy current component. The Preisach model is used to describe the quasi-static magnetic hysteresis behavior of the core, providing strong guarantees on the reproducibility of the experimentally measured characteristics. This model is used to represent the magnetic field constitutive relationships within a finite-element framework combining the effects of hysteresis and eddy currents in a unified dynamic simulation. The finite-element model of the toroid is used as a high-order inductor model coupled to a resonant circuit simulation. The modeling technique is validated through experimental measurements on two different series RLC circuits. The first circuit is based on an M19 electrical steel toroid having resonant frequency near 200 Hz. The second circuit is based on a T38 ferrite toroid having a resonant frequency near 10 kHz. The models agree closely with the measured voltages, currents, and losses. The models also successfully predict discontinuities in the measured frequency responses due to the existence of bistable operating regimes.

42 ENGINEERING↗

DOE OSTI2018

Two-stage minimax stochastic unit commitment

The study proposes a stochastic optimisation approach based on discrete scenarios and the minimax criterion to deal with demand uncertainty in the two-stage unit commitment problem. To avoid making an over-conservative decision, the approach is designed to assign a probability-based weight to each demand scenario and provide a unit commitment schedule that minimises the maximum possible-weighted generation cost. Unit commitment is determined in the first stage and the economic dispatch under the scenario that corresponds to the maximum possible-weighted generation cost is determined in the second stage. The problem is formulated as a type of min-max-min mixed integer programming model. By introducing an auxiliary variable, the model is further transformed into a minimisation problem. A Benders decomposition algorithm is developed to solve the problem. The Benders master problem determines the unit commitment decision, while the Benders subproblem determines the dispatch decision. Multiple Benders feasibility cuts are constructed when the Benders subproblem is infeasible. Valid inequalities are derived to improve the lower bound provided by the Benders master problem. Numerical results show the performance of the algorithm.

Che, Ping↗