Abstract This paper presents a detailed model of low-frequency oscillations and their damping within the Electric Power System (EPS) of Bosnia and Herzegovina (B&H). The system is modeled using MATLAB software, analysing the steady state and dynamic responses. This research highlights the challenges and impacts of integrating renewable energy sources, such as wind farms, on grid stability and oscillation damping. The paper utilizes eigenvalue analysis to investigate the dynamic characteristics of the system, emphasizing the need for efficient damping strategies to maintain system stability. The methodology includes a comprehensive review of existing literature, the creation of a detailed EPS model of B&H, and the application of eigenvalue and oscillation amplitude analysis to determine damping ratios. The dynamic responses of hydro power plants, HPP Mostar and HPP Jablanica, to transient disturbances are analysed to validate the model and refine damping strategies. The results indicate that the B&H EPS is well-damped, with all eigenvalues possessing negative real parts, and demonstrate the system’s resilience to small disturbances. The results are compared with the technical report on the integration of the wind power plant WPP Podveležje. This comparative analysis shows consistent patterns between the modeled calculations and empirical data, confirming the robustness of the EPS model. This alignment underscores the effectiveness of current damping mechanisms and provides a foundational strategy for enhancing system stability with increasing renewable energy penetration. The findings highlight the importance of developing advanced control strategies to sustain system stability as the integration of variable renewable energy sources continues to grow.

The decrease in overall inertia in power systems due to the shift from synchronous generator production to renewable energy sources (RESs) presents a significant challenge. This transition affects the system’s stable frequency response, making it highly sensitive to imbalances between production and consumption, particularly during large disturbances. To address this issue, this paper introduces a novel approach using Multivariate Empirical Mode Decomposition (MEMD) for the accurate estimation of power system inertia. This approach involves applying MEMD, a complex signal processing technique, to power system frequency signals. The study utilizes PMU (Phasor Measurement Unit) data and simulated disturbances in the IEEE 39 bus test system to conduct this analysis. MEMD offers substantial advantages in analyzing multivariate data and frequency signals during disturbances, providing accurate estimations of system inertia. This approach enhances the understanding of power system dynamics in the context of renewable energy integration. However, the complexity of this methodology and the requirement for precise data collection are challenges that need to be addressed. The results from this approach show high accuracy in estimating the rate of change of frequency (RoCoF) and system inertia, with minimal deviation from actual values. The findings highlight the significant impact of renewable energy integration on system inertia and emphasize the necessity of accurate inertia estimation in modern power systems.

This paper presents the use of the Hilbert-Huang Transform (HHT) to identify low-frequency electromechanical oscillatory modes, their characteristics, and damping. As these oscillations can have varying features, locations, and impacts on power systems, identifying and monitoring them is crucial for the monitoring, protection, and control of modern power systems. The Hilbert-Huang transform (HHT) is a technique used to analyze nonlinear and non-stationary time series data. It involves breaking down the data into components using Empirical Mode Decomposition (EMD), which generates components with varying amplitudes and frequencies. The EMD process includes an inner loop called sifting, which produces an Intrinsic Mode Function (IMF) until the signal reaches a mean value of zero or a maximum number of iterations. The obtained IMF is a characteristic function of a fundamental oscillation that is symmetrical around the abscissa. The dominant oscillatory mode's frequency can be determined by applying the Hilbert transformation to the first IMF, and the damping ratio and damping can be calculated by fitting a least square line to the logarithmic instantaneous amplitude of the first IMF. To demonstrate the efficacy of the methodology, three case studies are examined. The first case involves generating a synthetic signal to simulate a load angle change with a defined frequency and damping. In the second case, a small disturbance in mechanical power change in the Single Machine System is simulated. The third case simulates a three-phase short circuit on the transmission line using the IEEE 39 bus test system. The results are compared to modal analysis conducted in DigSilent PowerFactory software. The application of HHT yielded satisfactory and promising results in identifying the dominant mode's oscillation frequency and damping.

Abstract Generation of photovoltaic power plants is growing rapidly in the last ten years in the world. One of the key factors for the construction of floating photovoltaic power plants is to provide space for their construction. This paper presents statistical indicators of installed capacities of floating photovoltaic power plants, as well as a detailed description of the components of these power plants. Approaches to construction and maintenance recommendations are described in more detail. The basic results of simulations are presented on a concrete example of a floating photovoltaic 1 MW power plant on Lake Modrac. The available areas of artificial lakes in Bosnia and Herzegovina were analysed, and it was shown that the installation of floating photovoltaic power plants on 5% of the surface of artificial lakes would provide around 10% of the total electricity consumption in Bosnia and Herzegovina.

Background: Epilepsy is a brain disorder characterised by unpredictable and excessive nerve cell activity that causes epileptic seizures. Epileptic seizures are more common in children and adolescents than in elderly population. Electroencephalography (EEG) is a diagram of electrical activity of the brain and it is used as a method of choice for diagnosing epilepsy. Despite the accurate EEG tracing of electrical activity in the brain, the disadvantage of this type of analysing is the doctor’s skill to read the EEG correctly. Objective: The aim of this study was ro represents further research presented in our pevious works with wavelet based EEG analysis after masuring a multiresolution as relation between time and frequency resolution. Methods: Signal database set consist of 51 patients: a) healthy patient; b) 50 patients with a diagnosis of epilepsy. Additional characteristics of the analysed data: a) 19 signals-channels of EEG, b) Duration – 20 s or 2688 samples and. Nowadays, we can find dozens of EEG signal analysis papers using mathematical approach and with a focus on identification of epilepsy. Results: This paper represents some results relating to the analysis of EEG in children using Wavelet Transform (WT). The signals was collected and analysed at the Department of neuropediatrics, Pediatric Clinic at the University Clinical Center, University of Sarajevo. Conclusion: Using this approach it is possible to clearly differentiate patients with a diagnosis of epilepsy from healthy ones.

The use of renewable energy sources increases the energy self-sustainability of cities, enabling citizens to reduce energy costs, which results in an increase in their standard of living. However, solar energy penetration in Bosnia and Herzegovina, and its capital Sarajevo, is not in line with the possibilities. Furthermore, the Sarajevo Canton is extremely polluted during the winter months because of the use of unacceptable heating fuel. The aim of this paper is to introduce photovoltaic power systems use in heating electrification system. In this paper AQI is calculated based on historical data and the hybrid model EMD-SARIMA for air pollution and a solar production forecast is presented. The methodology was tested in the Sarajevo Canton, taking into account 35,000 households. In order to ensure clean air, renewable electric energy use for household heating should be implemented. The widespread use of inefficient individual heating systems characterized by inefficient and expensive use of firewood and the use of coal in individual furnaces in populated areas are the main problems of internal and urban air pollution in Sarajevo Canton. In order to reduce energy poverty in Sarajevo Canton, the use of a floating photovoltaic power plant located on Lake Jablanica with a capacity of 30 MW and the solar prosumers with capacity of 115 MW to provide the 196 GWh necessary for heating electrification of 35,000 households is implemented in this paper. Finally, based on correlation between AQI forecast and solar production it was calculated that the values of the AQI, considering the application of solar energy during 150 days (five months) in one heating season, have significantly decreased. Also renewable energy sources have a very important role in reducing carbon dioxide (CO2) emissions into the atmosphere and reducing urban pollution. With this approach, households would be heated by renewable electricity, which would make Sarajevo a cleaner, smarter city.

Electrical power systems throughout the world experience an unprecedented transformation. One of the main motivation for this is a transition from conventional power generation technologies towards renewable energy sources (RES). This transformation has numerous positive effects on power systems, environment and social engagements on a global level. However, poorly planned and allocated RES add complexity to power systems operations and can cause numerous challenges. This paper investigates some of the most common parameters used in the RES grid integration process. In particular, the impact of different PV penetration levels on energy losses and transformer current loading in a PV predominated power system are presented. The analysis is performed in DigSILENT® Powerfactory software using quasi-dynamic analysis on a modified IEEE 14 bus system. The results demonstrated that the energy losses could be reduced until the critical point of PV penetration. After the critical point is reached, the energy losses start to grow rapidly. The current loading of the transformers also tend to reduce with the increase in PV penetration until the critical point and rapidly grow after the critical point. In conclusion, results presented in this work demonstrate the importance of appropriate RES integration planning and analysis, which remains an important engineering task.