In the modern power system, Flexible Alternating Current Transmission System (FACTS) devices are widely used. An increased share of the distributed generation (DG) and the development of microgrids change the power flows in the existing distribution networks as well as a conventional power flow direction from the transmission to the distribution network level which may affect the overall stability aspects. The paper shows the FACTS devices’ implementation influence on the performance of the distribution network with integrated renewable energy sources (RES) observing the aspects of the oscillatory stability and the low-voltage motor starting. The FACTS devices, in particular the static var compensators (SVC), have been allocated according to a novel algorithm proposed in the paper. The algorithm uses an iterative process to determine an optimal location for implementation and rating power of SVC considering active power losses minimization, improvement of the voltage profile and maximizing return of investment (ROI) of FACTS devices. Novel constraints—transformer station construction constraint, SVC industrial nominal power value constraint and the constraint of distribution system operator (DSO) economic willingness to investment in the distribution network development are considered in the proposed algorithm. The analysis has been performed on 20 kV rural distribution network model in DIgSILENT PowerFactory software.

One of the main characteristics of power systems is keeping voltages within given limits, done by implementing fast automatic voltage regulators (AVR), which can raise generator voltage (i.e., excitation voltage) in a short time to ceiling voltage limits while simultaneously affecting the damping component of the synchronous generator electromagnetic torque. The efficient way to increase damping in the power system is to implement a power system stabilizer (PSS) in the excitation circuit of the synchronous generator. This paper proposes an enhanced algorithm for PSS tuning in the multimachine system. The algorithm is based on the analysis of system participation factors and the pole placement method while respecting the time domain behavior of the system after being subdued with a small disturbance. The observed time-domain outputs, namely active power, speed, and rotor angle of the synchronous generator, have been classified and validated with proposed weight functions based on the minimal square deviation between the initial values in a steady-state and all sampled values during the transitional process. The system weight function proposed in this algorithm comprises s-domain and time-domain indices and represents a novel approach for PSS tuning. The proposed algorithm performance is validated on IEEE 14-bus system with a detailed presentation of the results in a graphical and table form.

This paper aims to present carefully selected scientific papers that have pushed the boundaries in the application of advanced computational intelligence–based methods in power engineering, mainly in optimal power system management. Contemporary development of the Smart Grid and detailed framework for power grid digitalization enabled the real and efficient application of advanced optimization algorithms presented in this paper. Papers that are not directly related to Smart Grid management are also considered, since they solve the partial challenges of planning and development with metaheuristic procedures, and according to the authors, they are highly applicable and represent a fundamental starting point for wider application. This paper covers papers and research whose results are reproducible and can be realized in production-grade software. The emphasis of the paper is on the considerate and impartial way of providing a concise overview of the methods for solving technical challenges within the accepted Smart Grid architecture. The paper is the result of many years of research and commitment to this field and represents the foundation for present research and development.

Original scientific paper The paper analyzes the possibility of reducing active power losses in power system, constrained by regulated voltage levels, by implementing appropriate distributed generation capacity. The objectives of this paper were achieved by developing hybrid methods based on artificial neural network and genetic algorithm. Methods have been developed to determine the impact of different distributed generation power on all terminals in the observed system. The method that uses artificial neural network and genetic algorithm is applicable for radial distribution networks, and method using load flow and genetic algorithm is applicable to doubly-fed distribution network. For comparison purposes, additional method was developed that uses neural networks for the decision-making process. Data for training the neural network was obtained by power flow calculation in the DIgSILENT PowerFactory software on a part of Croatian distribution network. The same software was used as an analytical tool for checking the correctness of solutions obtained by optimization. Keywords: artificial neural networks; distributed generation; genetic algorithm Kontrola naponskih prilika i gubitaka snage korištenjem distribuirane proizvodnje i računalne inteligencijeIzvorni znanstveni članak U radu se analizira mogućnost smanjenja aktivnih gubitaka elektroenergetskog sustava, uz poštivanje propisanih naponskih razina, primjenom odgovarajućih kapaciteta distribuirane proizvodnje. Ciljevi ovog rada ostvareni su razvojem hibridnih metoda baziranih na umjetnim neuronskim mrežama i genetskom algoritmu. Razvijene su metode za određivanje utjecaja distribuirane proizvodnje različitih snaga na svim čvorovima u promatranom sustavu. Metoda koja koristi umjetnu neuronsku mrežu i genetski algoritam primjenjiva je za radijalne distributivne mreže, a metoda koja koristi proračun tokova snaga i genetski algoritam primjenjiva je za dvostruko napajane distributivne mreže. S ciljem usporedbe razvijena je i metoda koja koristi neuronske mreže za proces odlučivanja o najboljem rješenju. Podaci za učenje neuronske mreže dobiveni su proračunom tokova snaga u programskom alatu DIgSILENT PowerFactory i to na djelu hrvatske distributivne mreže. Isti programski alat se koristi analitički kao sredstvo provjere ispravnosti rješenja dobivenih optimizacijom.

This paper presents the integration of the solar power plant SE Gumiimpex, rated power of  1 MW in Croatian distribution network. Basic data of solar power plant are presented as well as the analysis of its impact on the distribution network. Power quality measurements, seven days before and seven days after the connection of PV plant to the grid are performed and obtained power quality indices are compared to those stated in the power quality standard HRN EN 50160/2012 and Croatian grid code. There are also presented results of the simulation of protection relays selection and coordination