Štore Steel Ltd. makes more than 1400 steel grades. The highest costs in steel production from scrap stems from the electric arc furnace electric energy consumption. Electrical energy is used to produce heat energy generated by the burning arc between the graphite electrodes and steel scrap. In general, the balanced heat input of all electrodes is essential. Based on the input of thermal energy from all electrodes, also the possibility of occurrence of hot and cold spots in the electric arc furnace can be determined. Perception of and the elimination of the unequal heat load of electrodes have a major impact on reducing operating costs and increasing the efficiency of the electric arc furnace production. Most authors have modeled the arc furnace as an electrical equivalent circuit, where the electric arc is modeled using the macroscopic approach. In this paper, the microscopic approach to the electric arc model is described, where a set of equations (electrical neutrality, Dalton law, Saha–Eggert) was solved using differential evolution algorithm. The results of modeling were practically confirmed by measuring electric parameters (voltage, current, active power) during the electric arc furnace operation. In November 2016, the investment in a new electrode controller using implemented logic will be carried out.

The paper deals with the reliability-centered maintenance (RCM) of a transmission substation. The process of the planning and actual performance of maintenance was carried out using an optimization algorithm. This maintenance procedure represents the maintenance management and included reliability of the power system operation, maintenance costs, and associated risks. The originality of the paper lies in the integrated treatment of all maintenance processes that are included in the pre-processing and used in the optimization process for reliability-centered maintenance. The optimization algorithm of transmission substation maintenance was tested in practice on the equipment and components of an existing 400/110–220/110 kV substation in the Slovenian electricity transmission system. A comparison analysis was also carried out of the past time-based maintenance (TBM) and the new reliability-centered maintenance (RCM), on the basis of the optimization algorithm.

Lead-acid batteries are the most frequently used energy storage facilities for the provision of a backup supply of DC auxiliary systems in substations and power plants due to their long service life and high reliability. It is possible to define the load in these systems, therefore the IEEE 485 Standard can be used for the selection of batteries according to the conventional method of selection. Special attention is paid in the paper to the technical selection of a lead-acid battery, which depends on its operational reliability that decreases with battery aging. It is defined by the extent of maintenance during its service life. A cost analysis was also carried out, which took into consideration maintenance and procurement costs, as well as the costs of the related air conditioning that keeps the prescribed temperature and ventilates the battery room. The impact is shown of selecting a lead-acid battery on the battery room’s operating safety when charging. The final selection of lead-acid battery is performed using an optimization algorithm of differential evolution. Using the optimization process, the new battery selection method includes the technical sizing criteria of the lead-acid battery, reliability of operation with maintenance, operational safety, and cost analysis. Two cases of selection of lead-acid batteries for the backup supply of a DC auxiliary system in a transmission substation are presented in the paper, where the input data were determined based on measurements in an existing substation. A comparison is made between the existing conventional and new lead-acid battery selection method based on optimization.

This paper presents a method for determination of the finite-element method model electrothermal parameters in a medium-voltage switchgear cell. The research includes a thermal calculation that is considered as a consequence of the eddy currents phenomena, which is a coupled numerical problem. Calibration of the numerical model is based on the multiobjective optimization procedure, which is carried out with the differential evolution algorithm (DE). The DE provides the best possible agreement of the measured temperature values on the test model and calculated values with the equivalent numerical model. The presented results are obtained for the linear and nonlinear case of eddy currents phenomena. The goal of the calibration is to determine the correct electrothermal parameters.

This chapter deals with the influence of the electric field on a Medium Voltage Indoor Post Insulator (MVIPI) with standard and modified external shapes. The goal of this chapter is to show the electric field behavior of the MVIPI with different external shapes and to introduce a numerical model with a favorable distribution of the electric field that relieves the dielectric from stress. The chapter describes an MVIPI with nominal voltage 20 kV AC and shows an existing MVIPI, an MVIPI with a different number of ribs, and an MVIPI with exceptional external shape. The MVIPI’s new external shape does not have the typical shape of the ribs, but a new outline, using the Lagrange polynomial, that will acquire its optimal form through the optimization process. A Differential Evolution optimization algorithm is used for the optimal design of the insulator’s external shape. The value of the Electric Field Strength (EFS) will be minimized within the permissible bounds during the optimization process. The important parameters during the minimization of the objective function are the value of the EFS in the interior and exterior of the insulator. EFS values are shown for every MVIPI example and are compared with the existing MVIPI. The obtained results are analyzed and discussed.

This paper presents a method for optimizing the inertia constants and damping coefficients of interconnected virtual synchronous generators (VSGs) using a genetic algorithm. The goal of optimization is to find a balance between minimizing the rate of change of frequency (RoCoF) and enhancing controllability. Five controllability-based metrics are tested: the minimum eigenvalue, the sum of the two smallest eigenvalues, the maximum eigenvalue, the trace, and the determinant of the controllability Gramian matrix. The approach includes the oscillatory modes’ damping ratio constraints to ensure the small-signal stability of the entire system. The results of optimization on the IEEE 9-bus system with three VSGs show that the proposed method improves controllability, reduces RoCoF, and maintains the desired oscillation damping. The proposed approach was tested through time-domain simulations.