This paper presents the effect of the impact of moisture in paper insulation used as insulation of transformer windings on its thermal conductivity. Various types of paper (cellulose and aramid) and impregnated (mineral oil, synthetic ester, and natural ester) were tested. The impact of paper and impregnated types on the changes in thermal conductivity of paper insulation caused by an increase in moisture were analyzed. A linear equation, describing the changes in thermal conductivity due to moisture, for various types of paper and impregnated, was developed. The results of measuring the thermal conductivity of paper insulation depending on the temperature are presented. The aim of the study is to develop an experimental database to better understand the heat transport inside transformers to assess aging and optimize their performance.

One of the challenges which the electrical power industry has been facing nowadays is the adaptation of the power system to the energy transition which has been taking place before our very eyes. With the increasing share of Renewable Energy Sources (RES) in energy production, the development of electromobility and the increasing environmental awareness of the society, the power system must constantly evolve to meet its expectations regarding a reliable electricity supply. This paper presents the issue of deploying energy storage facilities in the meshed power distribution network in order to reduce transmission losses. The presented multi-objective approach provides an opportunity to solve this issue using multi-objective optimisation methods such as Non-dominated Sorting Genetic Algorithm II (NSGA-II), Multiobjective Particle Swarm Optimization (MPSO) and Biased Random Keys Genetic Algorithm (BRKGA). In order to increase the efficiency optimisation process, the Pareto Adaptive $ϵ$-dominance ($paϵ$-dominance) was used. It was demonstrated that the use of energy storages that cooperate with RES can significantly reduce transmission losses.

This paper concerns the application of the AHP (analytic hierarchy process) multi-criteria decision support method for the final selection of the structure of a hybrid power system with RESs (renewable energy sources) and EES (electrical energy storage) from a set of solutions obtained through multi-criteria optimization. These solutions, depending on their position within the Pareto front, may differ significantly in terms of the values of the criteria functions, or may be located very close to each other in the solution space. The role of the expert is to select the final solution, taking into account many additional criteria, often of a subjective nature. The article optimizes the structure of the proposed system using the multi-criteria NSGA-II (Non-dominated Sorting Genetic Algorithm) method, taking into account three technical criteria. The AHP method was used to select the final solution, which allows determination of the ranking of solution variants, taking into account selected additional criteria. In the analyzed case, these are primarily economic indicators, technical conditions, and preferences of the system recipients. In addition to determining the ranking of solutions, a sensitivity analysis was performed, which gives the expert extensive knowledge on the impact of individual criteria on the order of variants in the ranking. It was shown that in the case of selecting hybrid structures of generating systems with EES for a specific type of receiver, the use of the AHP method significantly facilitates making the final decision.

The paper presents the issues of a wind turbine-flywheel energy storage system (WT-FESS) operation under real conditions. Stochastic changes of wind energy in time cause significant fluctuations of the system output power and as a result have a negative impact on the quality of the generated electrical energy. In the author’s opinion it is possible to reduce the aforementioned effects by using an energy storage of an appropriate type and capacity. It was assumed that based on the technical parameters of a wind turbine-energy storage system and its geographical location one can determine the boundary capacity of the storage, which helps prevent power cuts to the grid at the assumed probability. Flywheel energy storage was selected due to its characteristics and technical parameters. The storage capacity was determined based on an empirical relationship using the results of the proposed statistical and energetic analysis of the measured wind velocity courses. A detailed algorithm of the WT-FESS with the power grid system was developed, eliminating short-term breaks in the turbine operation and periods when the wind turbine power was below the assumed level.

The development and advantages of renewable energy technologies mean that their areas of application are constantly expanding. The development of roads, transport systems, and electromobility also increases the demand for electricity. Roads occupy a certain area that could be used to install wind turbines or photovoltaic systems that could be used to power, among others, electric vehicle charging stations and road technical infrastructure facilities (travel service areas, tunnel lighting, road signs). There are many examples around the world where such solutions have been used. This critical review of existing solutions and the possibilities of their application in new places may contribute to further development and research in this area. Particular attention was paid to the possibility of using renewable energy systems in Poland, which can be successfully transferred to other countries with a similar climate.

An important aspect of the off-grid utilization of hybrid generation systems is the integration of energy storage facilities into their structures, which allows for improved power supply reliability. However, this results in a significant increase in the cost of such systems. Therefore, it is justified to use optimization resulting in the minimization of the selected economic indicator taking into account the most important technical constraints. For this reason, this work proposes an algorithm to optimize the structure of a hybrid off-grid power distribution system (with electrochemical energy storage), designed to supply a load with known daily energy demand. The authors recommend genetic algorithm utilization as well as a modified criterion for evaluating the quality of solutions based on the Levelized Cost of Energy (LCOE) index. Several technical and economic analyses were presented, including unit costs, power distribution of the wind and solar sections, nominal battery capacity, SSSI index (System Self-Sufficiency Index), etc. The model of the system includes durability of the elements which have a significant impact on the periodic battery replacement. The tests were carried out for two types of loads and two types of electrochemical batteries (NMC—Lithium Nickel Manganese Cobalt Oxide; and PbO₂—Lead-Acid Battery), taking into account the forecast of an increased lifetime of NMC type batteries and decreasing their price within five years. The proposed synthesis method of photovoltaic-wind (PV-wind) hybrid off-line systems leads to limiting the energy capacity of electrochemical storages. Based on the analyses, the authors proposed recommended methods to improve (reduce) the value of the criterion index (LCOE) for PV-wind off-grid systems while maintaining the assumed level of power supply reliability.