The power flow calculation considering uncertainty is common way of determining harmonic analysis of the system under uncertain conditions. Distributed generation and load are characterised by randomness. Hence, this study introduces uncertainty to the distribution network analysis. Three similar methodologies are proposed for distribution power flow, which calculate active power losses, voltage drops and voltage total harmonic distortion. The first methodology uses fuzzy logic in order to address uncertainties. Generation, active power loss variation and elasticity of power quality constraints are presented in a form of fuzzy numbers (FNs). The second methodology uses Monte Carlo simulation (MCS) to vary the values of the same variables, which are FN. The third methodology combines MCS and FN. The proposed methodologies are verified using case studies based on IEEE 33‐bus system. The results of all three methodologies are compared graphically and numerically. Analysing the distribution harmonic load‐flow results, one can find out the weak links of the network, which can provide references for making electrical accident premeditation and power quality problems.

A new concept of switches selection in the meta-heuristic optimization process of optimal distribution network reconfiguration has been proposed. Based on the adaptive set of selectable candidates, the proposed concept determines the switch status. This approach prevents the creation of unfeasible solutions (non-radial and unconnected configurations), and significantly reducing the number of searches and accelerating the optimization process. Unfeasible solutions, created by meta-heuristic optimization rules, can be corrected by means of the proposed adaptive loop concept. The correct parts of the unfeasible solution are retained, while only the defective parts are replaced by the adaptively formed loops from the currently available conditions that respect the correct switching operations. In this way, the basic characteristics of the optimization process have been retained to the greatest possible extent. Tests were performed on a two different size standard distribution networks.

With the increasing use of renewable energy sources and decentralized power systems, certain challenges have emerged in meeting consumers’ electrical energy demands. The intermittent nature of renewable energy generation means that it cannot always align with consumers’ needs, resulting in periods of excess energy production when it is not required. To bridge this gap between production and consumption, energy storage systems are necessary. This paper defines the work of an isolated microgrid, which consists of renewable sources (wind and PV) for energy production, households with electric vehicles as consumers, and a combined storage system. This storage system is made from batteries, hydrogen storage, and a control system that defines the best use of the storage. Stored energy is utilized through fuel cells to generate electricity for consumption when renewable sources cannot meet the demand. This paper presents the principles of electrolysis and models of individual elements within such a system, as well as the definition and principle of control of the system functionality based on rules and conditions. The proposed control system aims to increase the energy storage lifecycle by deciding when and how to utilize which type of storage and define a self-sufficient microgrid based on renewable sources of production. An economic analysis of the storage part of the system was carried out in which the levelized cost of energy stored and the NPC of the storage systems are calculated. A simulation of the system’s operation is conducted using one-hour measurements of wind turbines, solar panels, and household consumption in Serbia. To analyze the system’s behavior, a one-week time horizon is considered.

The paper presents an evolutionary algorithm for calculating available transfer capability (ATC). ATC is a measure of the transfer capability remaining in the physical transmission network for further commercial activity over and above already committed uses. In this paper, MATLAB software is used to determine the ATC between any bus in deregulated power systems without violating system constraints such as thermal, voltage, and stability constraints. The algorithm is applied on IEEE 5 bus system and on IEEE 30 bus system.

This paper presents a novel hybrid algorithm for determining the optimal Phasor Measurement Units (PMU) configuration in power networks to ensure full topological and numerical observability through a multi-phase process. In the first phase, a graph-theoretic Heuristic Node Selector (HNS) is developed to rapidly establish topological observability via Core-Tree construction and node dominance evaluation. Unlike most existing studies that implicitly assume topological observability implies numerical observability, the second phase applies a Genetic Algorithm to refine and extend the initial solution from HNS, ensuring complete numerical observability while minimizing number of PMUs. This hybrid method significantly reduces the search space and improves convergence. The HNS procedure is further extended in this work to explicitly handle Zero Injection Buses (ZIB) through rule-based topological modifications, enabling a modified version of the algorithm applicable to real networks with complex structures. Real-world implementation practices from European Transmission System Operators are considered through the adoption of a “one PMU per feeder” configuration. The proposed method is validated on standard IEEE test systems and Serbian transmission networks. Results demonstrate high scalability, adaptability to various network topologies (with and without ZIB nodes), and efficient PMU allocation. Notably, the method consistently achieves high values of the System Observability Redundancy Index, indicating strong robustness and redundancy in measurement placement.

Distribution utilities witness many changes nowadays. If the network voltages must be in 0.95-1.05 p.u. limits and grid input power factor greater than 0.85 all three modern strategies of smart distribution network as reconfiguration, capacitor switching and presence of distribution generation (DG) ought to be applied. Even in this case On Load Tap Changer (OLTC) in the supplying substation has to be used. In this paper, detailed technical analysis of eight realistic operation cases is presented by Simulated Annealing (SA) and by hybrid algorithm of Minimum spanning tree (MST) plus SA that works in shorter time. MST is used for tackling reconfiguration first and SA for capacitor switching afterwards that gives better results compared with SA alone. Implemented transparent graphical Monte Carlo method for locating of distributed generators and capacitor banks is unique and simple. Assumption is that DG is already present. Gauss and Weibull changing nodal loads and wind generators output, respectively as well as daily load curves for working and weekend day with insolation of solar panels are included in analysis. The objective function comprising of the cost of power losses, price of capacitors and undelivered energy is minimized. IEEE 69 bus network is analysed which has 69 nodes and 73 branches, all of which can commutate. The basic switching logic of uniform distribution of wind generators to the nodes and capacitors in accordance with objective function that changes every hour is unrealistic. More realistic one was issued with fixed nodes for allocation of DG and capacitors (the most frequently visited nodes). The programme final objective function indicates the price of peak power losses, losses of delivered electrical energy, of the banks, of undelivered electrical energy, OLTC and commutations for the period of month and a half.