In recent years, power-to-gas technologies have been gaining ground and are increasingly proving their reliability. The possibility of implementing long-term energy storage and that of being able to capture and utilize carbon dioxide are currently too important to be ignored. However, systems of this type are not yet experiencing extensive realization in practice. In this study, an overview of the experimental research projects and the research and development activities that are currently part of the power-to-gas research line is presented. By means of a bibliographical and sitographical analysis, it was possible to identify the characteristics of these projects and their distinctive points. In addition, the main research targets distinguishing these projects are presented. This provides an insight into the research direction in this regard, where a certain technological maturity has been achieved and where there is still work to be done. The projects found and analyzed amount to 87,... [more]

Corporate responsibility is an effective management strategy which, through conducting social dialogue at the local level, contributes to increasing the competitiveness of enterprises at a global level and simultaneously shaping favourable conditions for social and economic development. A review of the literature on the subject provided the theoretical motivation to undertake an emirical study of the implemented social innovations by the property manager and their reception by resource residents. The main aim of this study was to diagnose the attitudes of residents towards the implementation of social innovations by the municipal property manager. The research presented in the above article has been conducted in the first and second quarter of 2021 among residents of the Department of Housing “TBS” (ZGM TBS) in Częstochowa, Silesian voivoideship, Poland. The research was conducted using the survey method. The measurement instrument was a prepared questionnaire. The survey was completed... [more]

In industrial maintenance activity, very sophisticated technical and human factors are needed to achieve the great process or service that the company provides, with a large dose of knowledge based on the personal experience of maintenance technicians. However, the management and application of knowledge in this activity is often relegated to a third level (or simply forgotten). The aim of this study is to identify, classify and prioritize the different barriers and facilitators that can be found in maintenance organizations of the company in reference to knowledge management in strategic maintenance activities, and what competitive advantages could be used for their appropriate introduction in the company. For this, qualitative techniques have been used through a field study and observation, as well as semi-structured interviews between company directors and maintenance managers of first-level companies in various sectors (industrial or services), to draw conclusions on the applicatio... [more]

In this article, a description is presented of simulation investigations concerning the quality of regeneration effects of a technical object in an intelligent system with an artificial neural network. All repairable technical objects used are subject to a cyclic (random) process of damages and repairs in the time of their operation. A reduction of the parameters connected with the use of objects is the fundamental feature of this process. This results in the need of a regeneration (technical maintenance) of this object. Regeneration of an object in an intelligent system with an artificial neural network constitutes an effective approach to this problem. The problem of qualitative assessments of a maintenance process organized in this manner is the focus of this article. For this purpose, a program of simulation investigations is presented. The research program consists of a description of the models of the operation processes of technical objects, determination of the input data to th... [more]

Systematic failure analysis generally enhances the ability of engineering decision-makers to obtain a holistic view of the causal relationships that often exist within the systems they manage. Such analyses are made more difficult by uncertainties and organisational complexities associated with critical and inevitable industrial maintenance activities such as major overhauls, outages, shutdowns, and turnarounds (MoOSTs). This is perhaps due to the ratio of tasks-to-duration typically permitted. While core themes of MoOSTs including planning, contracts, costing, execution, etc., have been the focus of most research activities, it is worth noting that the ability to successfully transfer and retain MoOSTs knowledge is still under-investigated. Effectively implementing a case study-based approach for data collection, the current study explores the harmonisation of various risk assessments (i.e., fault tree analysis and reliability block diagrams) and multicriteria decision analysis (MCDA)... [more]

The concept of predictive and preventive maintenance and constant monitoring of the technical condition of industrial machinery is currently being greatly improved by the development of artificial intelligence and deep learning algorithms in particular. The advancement of such methods can vastly improve the overall effectiveness and efficiency of systems designed for wear analysis and detection of vibrations that can indicate changes in the physical structure of the industrial components such as bearings, motor shafts, and housing, as well as other parts involved in rotary movement. Recently this concept was also adapted to the field of renewable energy and the automotive industry. The core of the presented prototype is an innovative interface interconnected with augmented reality (AR). The proposed integration of AR goggles allowed for constructing a platform that could acquire data used in rotary components technical evaluation and that could enable direct interaction with the user.... [more]

The timeliness of the complex automated diagnostics of the metal condition for all characteristics has been substantiated. An algorithm for the automation of metallographic quality control of metals is proposed and described. It is based on the use of neural networks for recognizing images of metal microstructures and a precedent method for determining the metal grade. An approach to preliminarily process the images of metal microstructures is described. The structure of a neural network has been developed to determine the quantitative characteristics of metals. The results of the functioning of neural networks for determining the quantitative characteristics of metals are presented. The high accuracy of determining the characteristics of metals using neural networks is shown. Software has been developed for the automated recognition of images of metal microstructures, and for the determination of the metal grade. Comparative results of carrying out metallographic analysis with the dev... [more]

Fire protection is a basic safety issue for all categories of buildings. The criteria for effective fire suppression and the characteristics of extinguishing systems in insulated areas depend on a combination of factors. The main influences include the type of combustible material, ambient temperature, type of spray extinguisher, air inflow and outflow conditions, and space geometry. This article analyzes the most widely used fire-extinguishing technologies in different locations. The main aspects of using the pulsed delivery technology of extinguishing liquid are considered. Based on the analysis of publications from the last decade, it is possible to develop intelligent systems for recording fires and extinguishing fires in the premises.

This paper introduces the issue of reliability simulation studies of wind farm equipment in the process of an operation. By the improvement, retrofitting and insertion of new (optimal) solutions to change the quality and terms of the use of wind farm equipment, an evaluation of their impact on reliability under real conditions can be carried out over a long period of time. Over a brief period, testing the reliability of a technical facility is only possible in a simulation. The aspect of evaluating the reliability of wind farm equipment after the application of intelligent systems, including the Wind Power Plant Expert System (WPPES), can be tested in the manner of a simulation. It was accepted in this article that the operation of the wind farm equipment is detailed based on Markov processes. The results of such research activities are the development of reliable and appropriate strategies and an exploitation policy of PE facilities. The above-mentioned issues in such a comprehensive... [more]

This paper analyzes the challenges and requirements of establishing energy data ecosystems (EDEs) as data-driven infrastructures that overcome the limitations of currently fragmented energy applications. It proposes a new data- and knowledge-driven approach for management and processing. This approach aims to extend the analytics services portfolio of various energy stakeholders and achieve two-way flows of electricity and information for optimized generation, distribution, and electricity consumption. The approach is based on semantic technologies to create knowledge-based systems that will aid machines in integrating and processing resources contextually and intelligently. Thus, a paradigm shift in the energy data value chain is proposed towards transparency and the responsible management of data and knowledge exchanged by the various stakeholders of an energy data space. The approach can contribute to innovative energy management and the adoption of new business models in future ene... [more]

The article deals with simulation tests on the reliability of the equipment of the wind farm WF in the operation process. The improvement, modernization, and introduction of new solutions that change the reliability, as well as the quality and conditions of use and operation of wind farm equipment, require testing. Based on these tests, it is possible to continuously evaluate the reliability of the equipment of WF. The issue of reliability assessment of wind farm equipment, for which intelligent systems, diagnostic systems DIAG, and Wind Power Plant Expert System (WPPES) are used to modernize the operation process, can only be tested in a simulative way. The topic of testing the reliability of complex technical objects is constantly developing in the literature. In this paper, it is assumed that the operation of wind farm equipment is described and modeled based on Markov processes. The adoption of this assumption justified the use of the Kolmogorov−Chapman equations to describe the de... [more]

Among the most valuable types of renewable energy available today is wind energy. The reliability of WF systems must be regularly evaluated at every stage of their “life,” from design to operation, if a wind farm energy system is to be effective and function damage-free. Three key goals are presented in the article. The theory of fundamental quantities in reliability and maintenance analysis should be derived and explained first. Second, as a consequence of maintainability, theoretical correlations between reliability and mean time between failures (MTBF) are provided. The three-state theory of the WF procedure for operation presented in the research serves as the foundation for the analytical analysis of WF reliability. The time between failures is investigated as a function of maintainability, and the dependability of the WF under examination is assessed as a function of service life. The WF owner can make the best decisions to renew the WF and increase its reliability, energy, finan... [more]

Among the technological developments for complex technical objects such as civil aircraft, energy systems, medical devices, etc [...]

This article deals with the importance of simulation studies for the reliability of wind farm (WF) equipment during the operation process. Improvements, upgrades, and the introduction of new solutions that change the reliability, quality, and conditions of use and operation of wind farm equipment present a research problem during study. Based on this research, it is possible to continuously evaluate the reliability of WF equipment. The topic of reliability testing of complex technical facilities is constantly being developed in the literature. The article assumes that the operation of wind farm equipment is described and modeled based on Markov processes. This assumption justified the use of Kolmogorov−Chapman equations to describe the developed research model. Based on these equations, an analytical model of the wind farm operation process was created and described. As a result of the simulation analysis, the reliability of the wind farm was determined in the form of a probability fun... [more]

In this paper, the basic structure of an ICT platform of energy indicators, Openergy, is analytically presented, leveraging energy open data to help address the energy crisis more democratically. More specifically, its applicability as a dynamic tool for the management of climate, environmental, and socioeconomic information is described, and its efficiency in helping uncover insights for optimal data-driven decisions is depicted. Openergy uses data from the official portal for European data and the Eurostat site. Its database consists of data related to six energy categories, EU 2020 energy targets, energy balance, electricity production, transport fuels, heat production, and gas emissions, and each one includes its own indicators for EU countries. The platform includes visualizations of these data as well as time series modeling and forecasting, and the results are depicted at Openergy platform. The time series modeling provides forecasts with confidence intervals of each indicator u... [more]

The article considers the relevance and issues of wind turbine modeling, the principles of wind energy conversion (WEC) system operation, working areas and regulation. The influence of soft computing technologies on the different aspects of wind power systems, particularly in the fields of operation and maintenance, is considered. This article discusses the recent research, development and trends in soft computing techniques for wind-energy-conversion systems. For reliable analysis, the interaction of the wind-generator operation with the atmospheric boundary layer is considered. The authors give a detailed description of the approaches for the study and numerical modeling of the atmospheric boundary layer (ABL) in the vicinity of a wind farm. The study of the atmospheric boundary layer in the vicinity of the Ulyanovsk wind farm on the basis of cluster analysis of meteorological data is performed. Ten localizations of ABL homogeneous properties are identified. The subject of the study... [more]

The evaluation and analysis of the procedures for determining the dependability of WF wind farm equipment employed in a few publications are this article’s main problems. The publications chosen for review specifically mention investigations into the dependability of WF wind farm machinery. The following topics were the authors’ main areas of analysis: description and review of the techniques used to represent how technical items operate and the selection of the weight of the theoretical ideas of reliability that were used to gauge the dependability of the wind farm equipment under study. The authors of the studied works set out to address a number of significant problems pertaining to the modernization of the management of the WF equipment renewal process. The subjects of the studied works suggest that the established models of the technical object’s operational process are particularly significant in both the theory and practice of the reliability of technical objects. Using Kolmogor... [more]

The evolution and application of intelligence have been discussed from perspectives of life, control theory and artificial intelligence. However, there has been no consensus on understanding the evolution of intelligence. In this study, we propose a Tri-X Intelligence (TI) model, aimed at providing a comprehensive perspective to understand complex intelligence and the implementation of intelligent systems. In this work, the essence and evolution of intelligent systems (or system intelligentization) are analyzed and discussed from multiple perspectives and at different stages (Type I, Type II and Type III), based on a Tri-X Intelligence model. Elemental intelligence based on scientific effects (e.g., conscious humans, cyber entities and physical objects) is at the primitive level of intelligence (Type I). Integrated intelligence formed by two-element integration (e.g., human-cyber systems and cyber-physical systems) is at the normal level of intelligence (Type II). Complex intelligence... [more]

Deployment of photovoltaic (PV) systems has recently been encouraged for large-scale and small-scale businesses in order to meet the global green energy targets. However, one of the most significant hurdles that limits the spread of PV applications is the dust accumulated on the PV panels’ surfaces, especially in desert regions. Numerous studies sought the use of cameras, sensors, power datasets, and other detection elements to detect the dust on PV panels; however, these methods pose more maintenance, accuracy, and economic challenges. Therefore, this paper proposes an intelligent system to detect the dust level on the PV panels to optimally operate the attached dust cleaning units (DCUs). Unlike previous strategies, this study utilizes the expanded knowledge and collected data for solar irradiation and PV-generated power, along with the forecasted ambient temperature. An expert artificial intelligence (AI) computational system, adopted with the MATLAB platform, is utilized for a high... [more]

In practice, R&D in public organizations in developing countries is confronted with a variety of failures related to supporting management disciplines. The primary goal of this study is to address this issue through multiple-criteria decision making, which includes the DANP (DEMATEL-based ANP) approach. The DANP approach helps to resolve the classification issue that arises as a result of interdependence and feedback characteristics among the capabilities related to supporting management disciplines, allowing weak capabilities to be prioritized based on their interdependence. In the case of criteria weighting, the empirical result in terms of the degree of the net causal relationship had a greater influence on other criteria; however, in terms of dimensions, the technology management process capability had a greater significance on other dimensions, while the innovation management process capability had the least significance on other dimensions. The studies were based on relevant capa... [more]

Efficiently embedding and/or integrating mechanistic information within data-driven models is essentially the only approach to simultaneously take advantage of both engineering principles and data-science. The opportunity for hybridization occurs in many scenarios, such as the development of a faster model of an accurate high-fidelity computer model; the correction of a mechanistic model that does not fully-capture the physical phenomena of the system; or the integration of a data-driven component approximating an unknown correlation within a mechanistic model. At the same time, different techniques have been proposed and applied in different literatures to achieve this hybridization, such as hybrid modeling, physics-informed Machine Learning (ML) and model calibration. In this paper we review the methods, challenges, applications and algorithms of these three research areas and discuss them in the context of the different hybridization scenarios. Moreover, we provide a comprehensive c... [more]

In the biogas plants, organic material is converted to biogas under anaerobic conditions through physical and biochemical processes. From supply of the raw material to the arrival of the products to customers, there are serial processes which should be sufficiently monitored for optimizing the efficiency of the whole process. In particular, the anaerobic digestion process, which consists of sequential complex biological reactions, requires improved monitoring to prevent inhibition. Conventional implemented methods at the biogas plants are not adequate for monitoring the operational parameters and finding the correlation between them. As Artificial Intelligence has been integrated in different areas of life, the integration of it into the biogas production process will be inevitable for the future of the biogas plant operation. This review paper first examines the need for monitoring at the biogas plants with giving details about the process and process monitoring as well. In the follow... [more]

This work provides a manual design space exploration regarding the structure, type, and inputs of a multilayer neural network (NN) to obtain indirect information about the state variables in the alcoholic fermentation process. The main benefit of our application is to help experts reduce the time needed for making the relevant measurements and to increase the lifecycles of sensors in bioreactors. The novelty of this research is the flexibility of the developed application, the use of a great number of variables, and the comparative presentation of the results obtained with different NNs (feedback vs. feed-forward) and different learning algorithms (Back-Propagation vs. Levenberg−Marquardt). The simulation results show that the feedback neural network outperformed the feed-forward neural network. The NN configuration is relatively flexible (with hidden layers and a number of nodes on each of them), but the number of input and output nodes depends on the fermentation process parameters.... [more]

In addition to proper physicochemical properties, low toxicity is also desirable when seeking suitable ionic liquids (ILs) for specific applications. In this context, machine learning (ML) models were developed to predict the IL toxicity in leukemia rat cell line (IPC-81) based on an extended experimental dataset. Following a systematic procedure including framework construction, hyper-parameter optimization, model training, and evaluation, the feedforward neural network (FNN) and support vector machine (SVM) algorithms were adopted to predict the toxicity of ILs directly from their molecular structures. Based on the ML structures optimized by the five-fold cross validation, two ML models were established and evaluated using IL structural descriptors as inputs. It was observed that both models exhibited high predictive accuracy, with the SVM model observed to be slightly better than the FNN model. For the SVM model, the determination coefficients were 0.9289 and 0.9202 for the training... [more]

With the growing demand of supercritical carbon dioxide (SC-CO2) dyeing, it is important to precisely predict the dyeing effect of supercritical carbon dioxide. In this work, Generalized Regression Neural Network (GRNN) and Back Propagation Neural Network (BPNN) models have been employed to predict the dyeing effect of SC-CO2. These two models have been constructed based on published experimental data and calculated values. A total of 386 experimental data sets were used in the present work. In GRNN and BPNN models, two input parameters, such as temperature, pressure, dye stuff types, carrier types and dyeing time, were selected for the input layer and one variable, K/S value or dye-uptake, was used in the output layer. It was found that the values of mean-relative-error (MRE) for BPNN model and for GRNN model are 3.27−6.54% and 1.68−3.32%, respectively. The results demonstrate that both BPNN and GPNN models can accurately predict the effect of supercritical dyeing but the former is be... [more]