SOFCs integrated with SMES under dynamic power control using Chernobyl disaster optimizer.

The current study uses the Chernobyl disaster optimizer (CDO), a new metaheuristic optimizer, to identify the seven unknown parameters of solid oxide fuel cells (SOFCs). The procedures of the CDO is based on physical behavior of the elaborated radiations from the well-known Chernobyl disaster according to their mass, speed, frequency, and degree of ionization. The sum of square errors (SMSE) among the estimated and the real measured output voltage datasets of SOFCs is minimized employing the CDO.

Estimation of electrical transformer parameters with reference to saturation behavior using artificial hummingbird optimizer.

This paper offers an efficient tool to define the unknown parameters of electrical transformers. The proposed methodology is developed based on artificial hummingbird optimizer (AHO) to generate the best values of the transformer's unknown parameters. At initial stage, the parameters' extraction of the transformer electrical equivalent is adapted as an optimization function along with the associated operating inequality constraints.