The growth of populations and economy in Northern Cyprus has led to continuing utilization of fossil fuels as the primary source of electricity, which will raise environmental pollution. Thus, utilizing renewable energy, particularly solar energy, might be a solution to minimize this issue. This paper presents the potential of grid-connected solar PV power generation at Near East University Hospital (NEU Hospital), one of the largest and leading medical facilities in Northern Cyprus, to meet the energy demand during the daytime to reduce energy bills. For this purpose, the first objective of the study is to evaluate the solar energy potential as a power source for the NEU Hospital based on four datasets (actual measurement, Satellite Application Facility on Climate Monitoring (CMSAF), Surface Radiation Data Set-Heliosat (SARAH), and ERA-5, produced by the European Centre for Medium-range Weather Forecast). The results showed that the solar resource of the selected location is categorized as excellent (class 5), that is, the global solar radiation is within the range of 1843.8–2035.9 kWH/m². The second objective is to investigate the impact of orientation angles on PV output, capacity factor, economic feasibility indicators, and CO₂ emissions by using different PV modules. The results are compared with optimum orientation angles found by Photovoltaic Geographical Information System (PVGIS) simulation software. This objective was achieved by using RETScreen Expert software. The results demonstrated that the highest performance of the proposed system was achieved for orientation angles of 180° (azimuth angle) and −35° (tilt angle). Consequently, it is recommended that orientation angles, PV modules, and market prices are considered to maximize energy production and reduce electricity production costs. Full article

The aim of the manuscript was to present the collective results of research on the profitability of using various renewable sources in Poland with the greatest development potential. In the paper, the economic parameters of various investment projects were determined and calculated, i.e., Net Capital Value (NPV), Internal Rate of Return (IRR) and the Period of Return on Invested Capital (PBT). The economic assessment of the use of RES technologies was supplemented with the assessment of environmental benefits. The ecological criterion adopted in the study was the assessment of the potential and costs of reducing greenhouse gas emissions as a result of replacing fossil fuels with renewable energy technologies. On the basis of the constructed economic model to assess the profitability of investments, it has been shown that the analyzed projects will start to bring, depending on their type and technical specification, measurable economic benefits in the form of a reduction in the amount of energy purchased on an annual basis and environmental benefits in the form of reduction of carbon dioxide emissions to the atmosphere. Moreover, the calculations show a high potential for the use of certain renewable sources in Poland, which contributes to the fulfillment of energy and emission obligations towards the EU. The analyzes and research of the Polish energy market with the use of the presented models have shown that the project is fully economically justified and will allow investors to make a rational decision on the appropriate selection of a specific renewable energy source for their investment. The presented economic models to assess the profitability of investments in renewable energy sources can be successfully used in other countries and can also be a starting point for a discussion about the direction of energy development. Due to the lack of collective, original and up-to-date research on the domestic market, the manuscript provides the reader with the necessary knowledge regarding the legitimacy of using renewable energy sources, investment and environmental profitability. Full article

Classic and intelligent techniques aim to locate and track the maximum power point of photovoltaic (PV) systems, such as perturb and observe (P&O), fuzzy logic (FL), artificial neural networks (ANNs), and adaptive neuro-fuzzy inference systems (ANFISs). This paper proposes and compares three intelligent algorithms for maximum power point tracking (MPPT) control, specifically fuzzy, ANN, and ANFIS. The modeling of a single-diode equivalent circuit-based 3 kWp PV plant was developed and validated to achieve this purpose. Then, the MPPT techniques were designed and applied to control the buck–boost converter’s switching device of the PV plant. All three methods use the ambient conditions as input variables: solar irradiance and ambient temperature. The proposed methodology comprises the study of the dynamic response for tracking the maximum power point and the power generated of the PV systems, and it was compared to the classic P&O technique under varying ambient conditions. We observed that the intelligent techniques outperformed the classic P&O method in tracking speed, tracking accuracy, and reducing oscillation around the maximum power point (MPP). The ANN technique was the better control algorithm in energy gain, managing to recover up to 9.9% power. Full article

This article presents laboratory and spatial numerical modeling of cemented paste backfill. The first part of the research concerned laboratory tests of a mixture of sand, water, and variable cement content (5%, 10%, and 15%). The density and curing time of the mixture were determined. Moreover, cylindrical samples with a diameter of 46 mm and a height of 92 mm were constructed, for which compressive and tensile strength were calculated after one, two, three, and four weeks. The second part of the research concerned 3D numerical modeling with the use of RS3 software. For the exploitation field with dimensions of 65 m × 65 m, a strip-mining method was designed. The main objective of the research was to determine the changes in displacements around the haulage room and transportation roadway located in the immediate vicinity of the exploitation field. For the first time in numerical modeling, a two-sided strip method was used for the four stages of mining the ore deposit where the post-mining space was filled with a cemented paste backfill. Based on this research, the compressibility coefficient was determined. Full article

The problem of energy poverty exists in practically every European country. Its size and scope are determined by a variety of factors, ranging from economic development to the direction of energy and climate policy implementation to cultural factors. Our aim in this paper was to carry out a comparative analysis of indicators related to energy poverty and sustainable development to identify correlations and links between the two issues and determine how they are related. The fact that the analysis was performed for most European countries is new and represents a broad spectrum of research; we were not limited to studies of countries bound by formal political-economic arrangements or by consideration of the degree of economic development. This approach enabled explication of how diverse the situation is in Europe. The research methods used included a critical analysis of the literature and the use of descriptive and mathematical-statistical tools. The main conclusions and findings of the analysis were that in some countries in economically developed Europe, energy poverty is a major problem, and that, in this respect, there are large differences between “old European Union” and “new European Union” countries, and in the countries that do not belong to political-economic structures in Europe. It is clear, from the research, which countries are rapidly and effectively reducing their energy poverty problems and which factors are the determinants of this. These results are linked to the new direction of energy policy and the shift towards more environmentally friendly energy use. In conclusion, it has been possible to identify the causes of energy poverty and how the energy poverty situation in Europe is changing. Full article

Low-emissivity (low-E) window films are designed to improve the thermal comfort and energy performance of buildings. These films can be applied to different glazing systems without having to change the whole window. This makes it possible to apply films to windows in old and historical buildings for which preservation regulations often require that windows should remain unchanged. This research aims to investigate the impacts of low-E window films on the energy performance and thermal comfort of a three-story historical stone building in the cold climate of Sweden using the simulation software “IDA ICE”. On-site measurements were taken to acquire thermal and optical properties of the windows. This research shows that the application of the low-emissivity window film on the outward-facing surface of the inner pane of the double-glazed windows helped to reduce heat loss through the windows in winter and unwanted heat gains in summer by almost 36% and 35%, respectively. This resulted in a 6% reduction in the building’s annual energy consumption for heating purposes and a reduction in the percentage of total occupant hours with thermal dissatisfaction from 14% (without the film) to 11% (with the film). However, the relatively high price of the films and low price of district heating results in a rather long payback period of around 30 years. Thus, the films seem scarcely attractive from a purely economic viewpoint, but may be warranted for energy/environmental and thermal comfort reasons. Full article

Considerable investment in India’s electricity system may be required in the coming decades in order to help accommodate the expected increase of renewables capacity as part of the country’s commitment to decarbonize its energy sector. In addition, electricity demand is geared to significantly increase due to the ongoing electrification of the transport sector, the growing population, and the improving economy. However, the multi-dimensional uncertainty surrounding these aspects gives rise to the prospect of stranded investments and underutilized network assets, rendering investment decision making challenging for network planners. In this work, a stochastic optimization model is applied to the transmission network in India to identify the optimal expansion strategy in the period from 2020 until 2060, considering conventional network reinforcements as well as energy storage investments. An advanced Nested Benders decomposition algorithm was used to overcome the complexity of the multistage stochastic optimization problem. The model additionally considers the uncertainty around the future investment cost of energy storage. The case study shows that deployment of energy storage is expected on a wide scale across India as it provides a range of benefits, including strategic investment flexibility and increased output from renewables, thereby reducing total expected system costs; this economic benefit of planning with energy storage under uncertainty is quantified as Option Value and is found to be in excess of GBP 12.9 bn. The key message of this work is that under potential high integration of wind and solar in India, there is significant economic benefit associated with the wide-scale deployment of storage in the system. Full article

Process integrity, insufficient data, and system complexity in the automotive manufacturing sector are the major uncertainty factors used to predict failure probability (FP), and which are very influential in achieving a reliable maintenance program. To deal with such uncertainties, this study proposes a fuzzy fault tree analysis (FFTA) approach as a proactive knowledge-based technique to estimate the FP towards a convenient maintenance plan in the automotive manufacturing industry. Furthermore, in order to enhance the accuracy of the FFTA model in predicting FP, the effective decision attributes, such as the experts’ trait impacts; scales variation; and assorted membership, and the defuzzification functions were investigated. Moreover, due to the undynamic relationship between the failures of complex systems in the current FFTA model, a Bayesian network (BN) theory was employed. The results of the FFTA model revealed that the changes in various decision attributes were not statistically significant for FP variation, while the BN model, that considered conditional rules to reflect the dynamic relationship between the failures, had a greater impact on predicting the FP. Additionally, the integrated FFTA–BN model was used in the optimization model to find the optimal maintenance intervals according to the estimated FP and total expected cost. As a case study, the proposed model was implemented in a fluid filling system in an automotive assembly line. The FPs of the entire system and its three critical subsystems, such as the filling headset, hydraulic–pneumatic circuit, and the electronic circuit, were estimated as 0.206, 0.057, 0.065, and 0.129, respectively. Moreover, the optimal maintenance interval for the whole filling system considering the total expected costs was determined as 7th with USD 3286 during 5000 h of the operation time. Full article

One way to reduce CO₂ emissions is to replace conventional energy sources with renewable ones. In order to encourage prosumers to invest in renewable energy, EU Member States are developing renewable energy subsidy programs. In Poland, in the years 2019–2020, the “My Electricity” program was implemented, co-financing was up to 50% of eligible costs (max PLN 5000, i.e., EUR 1111), and the total cost of the program was 251 million euro. During this period, around 400,000 prosumer installations were created in Poland, including over 220,000 prosumer PV Installations under the My Electricity program. The total power of the installation under the “My Electricity” program was 1.295 GWp with an average installation power of 5.72 kWp. It is estimated that the micro-installations will produce approx. 1.4 TWh of electricity annually. Depending on the replaced source of electricity (coal, gas, mix), in the next 30 years, it will help to avoid 26.2–42.7 million Mg of greenhouse gases calculated as carbon dioxide equivalents (CO_2eq). The coefficient of subsidy expenditure from the “My Electricity” program was 194 EUR/kWp, and in the next 30 years, it will be 6.52 EUR/MWh. The investment in PV will save EUR 1550 million, which would have to be incurred for the purchase of CO₂ emission permits. Full article

Variable speed wind turbines are commonly used as wind power generation systems because of their lower maintenance cost and flexible speed control. The optimum output power for a wind turbine can be extracted using maximum power point tracking (MPPT) strategies. However, unpredictable parameters, such as wind speed and air density could affect the accuracy of the MPPT methods, especially during the wind speed small oscillations. In this paper, in a permanent magnet synchronous generator (PMSG), the MPPT is implemented by determining the uncertainty of the unpredictable parameters using the extended Kalman filter (EKF). Also, the generator speed is controlled by employing a fuzzy logic control (FLC) system. This study aims at minimizing the effects of unpredictable parameters on the MPPT of the PMSG system. The simulation results represent an improvement in MPPT accuracy and output power efficiency. Full article

The paper presents the results and analysis of interdisciplinary research concerning electromagnetic field shielding, conductive polymers printed on textiles and numerical simulation using the finite element method (FEM). The use of conductive, layered textiles for shielding electromagnetic interference (EMI) has been proposed. After establishing the optimal conditions for deposition of polyaniline (PANI) and polypyrrole (PPy) on polyacrylonitrile (PAN) fabric, conductive composites were made by means of reactive inkjet printing. For this purpose, polyacrylonitrile (PAN) fabrics were coated with polyaniline or polypyrrole, obtained by chemical oxidation of aniline hydrochloride and pyrrole by ammonium peroxydisulfate. The morphology of the obtained coatings was observed using a scanning electron microscope (SEM). The conductive properties (surface resistance) of the fabrics were measured using the four-wire method, and the tests of the effectiveness of electromagnetic shielding were carried out using the waveguide method in the frequency range from 2.5 to 18 GHz. The results of experimental shielding effectiveness (SE) tests and numerical simulation showed that the composites of polyacrylonitrile with polyaniline PAN/PANI and polyacrylonitrile with polypyrrole PAN/PPy achieved very good and good EMI shielding efficiency, respectively. Moreover, the obtained measurement results were verified by numerical modeling with the use of FEM–ANSYS HFFS software. Full article

This paper describes the method developed using the Extreme Gradient Boosting (Xgboost) algorithm that allows high-resolution imaging using the ultrasound tomography (UST) signal. More precisely, we can locate, isolate, and use the reflective peaks from the UST signal to achieve high-resolution images with low noise, which are far more useful for the location of points where the reflection occurred inside the experimental tank. Each reconstruction is divided into two parts, estimation of starting points of wave packets of raw signal (SAT—starting arrival time) and image reconstruction via XGBoost algorithm based on SAT matrix. This technology is the basis of a project to design non-invasive monitoring and diagnostics of technological processes. In this paper, we present a method of the complete solution for monitoring industrial processes. The measurements used in the study were obtained with the author’s solution of ultrasound tomography. Full article

Recently, nanomaterial-based scintillators are newly emerging technologies for many research fields, including medical imaging, nuclear security, nuclear decommissioning, and astronomical applications, among others. To date, scintillators have played pivotal roles in the development of modern science and technology. Among them, plastic scintillators have a low atomic number and are mainly used for beta-ray measurements owing to their low density, but these types of scintillators can be manufactured not in large sizes but also in various forms with distinct properties and characteristics. However, the plastic scintillator is mainly composed of C, H, O and N, implying that the probability of a photoelectric effect is low. In a gamma-ray nuclide analysis, they are used for time-related measurements given their short luminescence decay times. Generally, inorganic scintillators have relatively good scintillation efficiency rates and resolutions. And there are thus widely used in gamma-ray spectroscopy. Therefore, developing a plastic scintillator with performance capabilities similar to those of an inorganic scintillator would mean that it could be used for detection and monitoring at radiological sites. Many studies have reported improved performance outcomes of plastic scintillators based on nanomaterials, exhibiting high-performance plastic scintillators or flexible film scintillators using graphene, perovskite, and 2D materials. Furthermore, numerous fabrication methods that improve the performance through the doping of nanomaterials on the surface have been introduced. Herein, we provide an in-depth review of the findings pertaining to nanomaterial-based scintillators to gain a better understanding of radiological detection technological applications. Full article

The higher share of renewable energy sources in the electrical grid and the electrification of significant sectors, such as transport and heating, are imposing a tremendous challenge on the operation of the energy system due to the increase in the complexity, variability and uncertainties associated with these changes. The recent advances of computational technologies and the ever-growing data availability allowed the development of sophisticated and efficient algorithms that can process information at a very fast pace. In this sense, the use of machine learning models has been gaining increased attention from the electricity sector as it can provide accurate forecasts of system behaviour from energy generation to consumption, helping all the stakeholders to optimize their activities. This work develops and proposes a methodology to enhance load demand forecasts using a machine learning model, namely a feed-forward neural network (FFNN), by incorporating an error correction step that involves the prediction of the initial forecast errors by another FFNN. The results showed that the proposed methodology was able to significantly improve the quality of load demand forecasts, demonstrating a better performance than the benchmark models. Full article

Discussions regarding the definition of Positive Energy Districts and the concept of a boundary are still being actively held. Even though there are certain initiatives working on the boundary limitations for PEDs, there is no methodology or tool developed for selecting peculiar spaces for future PED implementations. The paper focuses on a flexible GIS-based Multicriteria assessment method that identifies the most suitable areas to reach an annual positive non-renewable energy balance. For that purpose, a GIS-based tool is developed to indicate the boundary from an energy perspective harmonized with urban design and land-use planning. The method emphasizes evaluation through economic, social, political, legal, environmental, and technical criteria, and the results present the suitability of areas at macro and micro scales. The current study outlines macro-scale analyses in six European cities that represent Follower Cities under the MAKING-CITY H2020 project. Further research will be conducted for micro-scale analyses and the outcomes will pursue a technology selection process. Full article