Future smart distribution grids will apart from a large number of measurement instruments, communication infrastructure, intelligent software etc., also require the appropriate techniques for analysis of the available signals. Various disturbances of different intensities constantly occur in real distribution systems. Many of them are just temporary while others cause the tripping of protection devices and the suspension of electricity supply. For distribution network operators, timely identification and adequate analysis of disturbances represent a very important segment of operation of electricity distribution networks. In this paper, the disturbance registered in the real distribution system of Bosnia and Herzegovina is analysed using four different time-frequency analysis techniques (Short-Time Fourier Transform (STFT), Continuous Wavelet Transform (CWT), Wigner-Ville Distribution (WVD) and Hilbert-Huang Transform (HHT)). The results show that all the applied techniques successfully identified the disturbance which is reflected in changes in frequency during the observed time period. These techniques could be suitable to be applied as a part of power quality monitoring systems, which provide the required measurement signals. The utilization of these techniques can provide distribution system operators with additional, a very important information about the distribution system.

Analysis of power consumption presents a very important issue for power distribution system operators. Some power system processes such as planning, demand forecasting, development, etc.., require a complete understanding of behaviour of power consumption for observed area , which requires appropriate techniques for analysis of available data. In this paper, two different time-frequency techniques are applied for analysis of hourly values of active an d reactive power consumption from one real power distribution transformer substation in urban part of Sarajevo city . Using the continuous wavelet transform (CWT) with wavelet power spectrum and global wavelet spectrum some properties of analysed time series are determined. Then, empirical mode decomposition (EMD) and Hilbert -Huang Transform (HHT) are applied for the analyses of the same time series and the results show ed that both applied approaches can provide very useful information about the behaviour of power consumption for observed time interval and different period (frequency) bands. Also it can be noticed that the results obtained by global wavelet spectrum and marginal Hilbert spectrum are very similar, thus confirming that both approaches could be used for identification of main properties of active and reactive power consumption time series .

In this paper, the impact of charging a large number of electric vehicles (EV) on the power system voltage stability is investigated on an example of a real power transmission system. First, the maximum load factors for different states in a selected part of the power system are determined using the continuation power flow (CPF) calculations and PV curves. The approach provides information about the active power limit value prior to the voltage collapse. Second, different daily load diagrams for the current load and the load expected in 2025 and 2030 together with the impact of charging 5 % and 10% of the electric vehicles in the analyzed region are constructed and voltage variations at 110 kV buses for different scenarios are analyzed. The results show that the foreseen future charging of a large number of EVs during the peak load intervals combined with the expected increase in power consumption can significantly affect the voltage profiles in the power transmission grid.

Because of the regulatory requirements for the quality of electricity supply being imposed in many countries, power quality is ought to be an important aspect of smart distribution grids. In this context, there is a need for the Integrated Power Quality Monitoring System, which would integrate all the power quality data available from various systems of smart distribution grid, such as Power Quality Monitoring System, Automated Meter Reading/Advanced Metering Infrastructure, Supervisory Control and Data Acquisition, Electric Vehicle Management System etc.

The smart distribution grids will have to supply the electricity according to power quality standards. Various measurement instruments, currently considered as cornerstones of smart grids (smart meters, protection relays, fault recorders etc.), do not measure all the power quality parameters specified in these standards. Some distribution system operators are already installing Power Quality Monitoring Systems (PQMS), based on fixed power quality monitors. The aim of this paper is to present the possibility of integrating power quality data from PQMS system, AMR/AMI (Automatic Meter Reading/Advanced Metering Infrastructure) system and all the other systems in the distribution network, into an Integrated Power Quality Monitoring System (IPQMS). The results of pilot projects conducted in the Public Electric Utility Elektroprivreda of Bosnia and Herzegovina, in order to test the three power quality monitoring systems, are also presented. The possibility of using data from smart meters in power quality monitoring was analysed.

This paper contains computing and measuring results of start-up, step load, braking and reversing performance of the induction motor. Computing of dynamic states was carried out using idealized mathematical model of the induction motor. The measuring of the dynamic characteristics of the induction motor was carried out with U/f power converter. The load of the induction motor is realized with eddy current brake. The results of computing and measuring are presented and compared.