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The united nations educational, scientific and cultural organization (UNESCO) considers the historic urban landscapes as the world heritages. Managing historic city centers and maintaining historic cores are the emerging challenges for sustainable urban planning. Today, the historic cores form an important part of the economic, social, environmental, and physical assets and capacities of contemporary cities, and play a strategic role in their development. One of the most important approaches to the development of central textures, especially in historical and cultural cities, is the sustainable urban regeneration approach, which encompasses all aspects of sustainability, such as the economic, social, cultural and environmental aspects. To maintain sustainability and regeneration of historic cores of cities, it is necessary to provide insight into the underlying characteristics of the local urbanization. Furthermore, the fundamental assets are to be investigated as indicators of sustainable regeneration and drivers of urban development. In the meantime, a variety of research and experience has taken place around the world, all of which has provided different criteria and indicators for the development of strategies for the historic cores of cities. The present study, through a meta-analytic and survey method, analyzing the experience and research reported in 139 theoretical and empirical papers in the last twenty years, seeks to provide a comprehensive conceptual model taking into account the criteria and indices of sustainable regeneration in historic cores of cities. The quality of the survey has been ensured using the preferred reporting items for systematic reviews and meta-analysis (PRISMA).

The main aim of this work is to propose a new algorithm of reliability assessment for steel civil engineering structures subjected to fire temperatures. This new algorithm is based upon the relative probabilistic entropy concept elaborated by Bhattacharyya, and this probabilistic distance is sought in-between extreme and admissible deformations of some structural beam subjected to higher temperatures. Similar to the First Order Reliability Method, this approach uses the first two probabilistic characteristics of the structural response, when structural output may be modelled with the use of Gaussian distribution. The probabilistic structural response is found here using hybrid computational technique–the Finite Element Method system ABAQUS with its fully coupled thermo-elastic analysis with 3D solid elements and probabilistic modules implemented in the computer algebra system MAPLE. The probabilistic response is determined via a triple stochastic analysis, which is based on the classical Monte-Carlo simulation, iterative generalized stochastic perturbation technique, and also using semi-analytical probabilistic calculus. Final determination of the relative entropy in the Serviceability Limit State of the given structure and its comparison with the results obtained using the FORM analysis enables to calibrate this new technique to numerical values proposed in the engineering designing codes. Hence, a more accurate probabilistic method may use some experimental-based admissible values included in the existing design of legal provisions.

This research investigates the relationships among renewable energy consumption, economic growth, and financial development in five sub-Saharan African nations utilizing panel data from 2000 to 2020. Econometric methods are used to ascertain the existence or absence of cross-sectional dependence and the short-run and long-run connections between the following factors: Pesaran cross-sectional dependence (CD) and cross-sectionally augmented IPS (CIPS) unit root tests, pooled mean group (PMG), and dynamic ordinary least squares (DOLS) estimations. The presence of cross-sectional dependence is found and represented with the CIPS unit root test. No significant short-run relationship is found between the variables of the study, yet a significant long-run relationship is present among them. A positive relationship exists between CO2 emissions and financial development, while financial development and renewable energy consumption are found to have negative relationships with CO2 emissions. The study also supports the scale effect of the environmental Kuznets curve hypothesis. Additionally, no causality is found among the variables, and impulse response and variance decomposition estimation are carried out to recommend future effects. Policy implications of findings are discussed, with accompanying suggestions.

Undoubtedly, the transition to electromobility with several million new, efficient charging points will have consequences for the energy industry, and in particular for network operators of the distribution infrastructure. At the same time, in the coming years the energy landscape will change into a system in which an increase in decentralized systems based on renewable energy sources will take over the leading function. This transformation process will further increase the complexity and overall pressure for change in energy systems over the next decade. In order to be able to ensure the energy supply and the reliable system operation of the grids in the future as well, communicative networking of generators, storage systems, electrical consumers and grid equipment is indispensable. This study aims to investigate the consequences of including electric vehicles in Istanbul’s power system using a unit commitment simulation model. The presented considerations analyze how uncertain and managed charging strategies affect the power system in terms of operating costs and renewable resources. The presented simulations indicate that, in economic terms, the use of a managed charging strategy saves 2.3%, reducing the total cost from USD 66.71 million to USD 65.18 million. The recipients of the presented research are both the demand and supply sides of the future energy transformation based on the idea of synergy of electromobility and renewable energy sources within the framework of the smart city idea.

Accurate dynamic models of supercapacitors (SCs) are a basis for the design, control and exploitation of the hybrid energy storage systems for electric vehicles. This paper concerns a fractional model of SC impedance, based on the Cole–Cole equation describing relaxation in electric double layer. This article provides a new method of identifying the parameters of fractional order model of SC impedance, performed without disconnecting the SC module from the energy storage system. The test drive for this purpose needs only the respect a few simple recommendations. The article presents the conditions of the mentioned test drive that will ensure the frequency spectra of the recorded signals lying in the bandwidth necessary for the correct identification of the model parameters. These parameters are determined by means of the Nelder–Mead simplex optimization method. The results of the identification described by the time method coincide with those obtained in the frequency domain. It has been shown in the last part of the article that the real energy losses in these systems significantly exceed the losses determined only on the basis of the nominal capacity and series equivalent resistance (ESR), to which the SC catalogue data are usually limited. This paper also provides an auxiliary frequency criterion for the selection of SCs intended for energy storage systems of electric vehicles.

With regard to underground mining, methane is a gas that, on the one hand, poses a threat to the exploitation process and, on the other hand, creates an opportunity for economic development. As a result of coal exploitation, large amounts of coal enter the natural environment mainly through ventilation systems. Since methane is a greenhouse gas, its emission has a significant impact on global warming. Nevertheless, methane is also a high-energy gas that can be utilized as a very valuable energy resource. These different properties of methane prompted an analysis of both the current and the future states of methane emissions from coal seams, taking into account the possibilities of its use. For this reason, the following article presents the results of the study of methane emissions from Polish hard coal mines between 1993–2018 and their forecast until 2025. In order to predict methane emissions, research methodology was developed based on artificial neural networks and selected statistical methods. The multi-layer perceptron (MLP) network was used to make a prognostic model. The aim of the study was to develop a method to predict methane emissions and determine trends in terms of the amount of methane that may enter the natural environment in the coming years and the amount that can be used as a result of the methane drainage process. The methodology developed with the use of neural networks, the conducted research, and the findings constitute a new approach in the scope of both analysis and prediction of methane emissions from hard coal mines. The results obtained confirm that this methodology works well in mining practice and can also be successfully used in other industries to forecast greenhouse gas and other substance emissions.

The main purpose of the paper was to identify the most frequently discussed directions of research on green transformation. In the article, both the significant similarities in the existing studies in this field, as well as the newly emerging topics of research, are presented. For this purpose, the authors used a systematic literature review with elements of statistical analyses. This kind of approach is not popularly used in literature review papers, as it differs from the research practices employed previously, which mostly concentrated on applying qualitative methods, alternatively supported by the analysis of the co-occurrence of keywords. In this paper, the authors decided to include selected methods of dimensional analysis in the systematic literature review, namely the log-linear and correspondence analyses. The main results of the presented analyses are a more detailed division of studies related to green transformations into groups focused on the areas more difficult to distinguish in terms of the traditionally conducted literature review.

This paper reports on the propagation of lightning overvoltage in a high-voltage direct current (HVDC) meshed grid. Since several topologies of meshed grids have been elaborated in the last decade, we used a common comprehensive reference test platform. The lightning impulse propagation was investigated with regard to the impact of surge arresters and the polarity of the lightning stroke concerning the DC line polarity (±500 kV). Various scenarios were considered, including a direct lightning strike to the DC+ conductor, to the tower, and to the shielding wire in the middle of the span, including backflash on the insulators. The influence of tower footing impedance on overvoltage levels at various nodes was assessed, depicting the critical value. A description of the models used in the simulations was provided. The main focus of the paper was on the wide-area propagation of the overvoltages in the meshed grid, at distant terminals and inside the feeders. An interesting observation was the effects of lightning at the far end of the analyzed grid, propagating through multiterminal and long-distance connections. The presented analysis, based on an exemplary meshed HVDC grid, underlines the importance of the insulation coordination studies and system security studies with respect to the localization of overvoltage protection systems.