Energy saving algorithm for smart home energy consumption budget optimization under the SVM model using a simple particle swarm optimization algorithm to find the optimal value caused by the slow speed gradient value based on PSO algorithm is proposed to optimize the use of machine learning algorithm GDPSO algorithm (Gradient Descent based on down Particle Swarm Optimization Algorithm). First of all, the establishment of energy structure and energy consumption model of optimal hyperplane selection of penalty factor and Gauss the appropriate parameters; secondly, parameter selection and optimization of energy consumption model for smart home energy-saving emission reduction requirements using GDPSO algorithm, and improves the efficiency of the optimal SVM parameters to improve the accuracy of solution. A simulation example shows the effectiveness of the algorithm.

<span lang="EN-GB">This paper analyses the impact of asymmetry of over-head power line parameters on short circuit currents when three-phase fault and phase-to-ground fault occur. The calculation results with consideration of an asymmetry of the power line parameters are confronted with the calculation in accordance with the Slovak standard STN EN 60909 which does not consider asymmetry of equipment parameters in the power system. The calculation of short-circuit conditions was carried out for two types of 400 kV power line towers on which is a considerably different arrangement of phase conductors.</span>