bluuebunny/crossref_metadata_2025 huggingface dataset:
ENHANCING DECISION-MAKING IN BUSINESS PROCESS MANAGEMENT WITH PREDICTIVE ANALYTICS BASED ON ARTIFICIAL INTELLIGENCE
Authors: Horchuk Yurii , Yukhimchuk Mariia , Dubovoy Volodymyr
Published: December 2024

This thesis examines the role of artificial intelligence (AI), specifically AI-based predictive analytics, in enhancing decision-making within the framework of Business Process Management (BPM). As organizations strive for increased efficiency and adaptability in their processes, predictive analytics has emerged as a key tool that empowers businesses to make more informed decisions. By leveraging AI models such as ChatGPT, Gemini AI, and others, companies can analyze vast amounts of historical and real-time data to forecast trends, optimize resource allocation, and mitigate risks in their operations. Predictive analytics, driven by AI, is revolutionizing how BPM is approached. The ability to anticipate potential future events based on data analysis allows businesses to proactively adjust workflows, schedules, and resource use. This shift leads to higher productivity, reduced operational costs, and more agile responses to market dynamics. AI models are particularly effective in analyzing large datasets that would be too complex or time-consuming for human analysts, thus enhancing the speed and accuracy of decision-making. This thesis also delves into the underlying algorithms and machine learning techniques used by AI models to generate predictive insights, including regression analysis, neural networks, and decision trees. It explores the integration of AI-based predictive analytics into existing BPM systems and examines its implications for both operational and strategic decision-making. Furthermore, the work addresses challenges such as data quality, integration complexity, and the need for continuous model training to maintain high prediction accuracy. The research underscores how predictive analytics powered by AI can transform business operations, especially in areas like supply chain management, customer relationship management, and financial forecasting. Additionally, the thesis considers the future potential of AI in BPM, particularly how predictive models might evolve to become more autonomous and adaptive over time, ultimately leading to smarter, self-optimizing business processes.
AUTOMATION OF THE PROCESS OF INTEGRATION OF 3D PRODUCT CONFIGURATORS IN ELECTRONIC COMMERCE SYSTEM
Authors: Puzhenko Vitalii , Kotsiubynskyi Volodymyr
Published: December 2024

This work is dedicated to studying the main challenges, advantages, disadvantages, and prospects for the development of automated integration of 3D configurators in e-commerce systems. In the modern world, where interactivity and personalization are key customer requirements, 3D configurators have become an essential tool that allows customers to customize products according to their needs, visualizing them in real-time. This significantly increases customer engagement, enhances satisfaction and loyalty, and opens up new opportunities for optimizing business processes. The study explores the features of a three-tier architecture, which ensures a structured and scalable integration of 3D configurators into e-commerce systems. This approach makes the system flexible, enabling quick and convenient product customization, order processing optimization, and seamless integration with other business processes such as CRM and ERP. The work focuses on the application of modern technologies that contribute to increasing the efficiency of 3D configurators and improving the user experience. The current market situation is analyzed, including examples of successful 3D configurator implementations by wellknown companies. The key challenges companies face during integration are identified, including high development costs, technological limitations for users, and system compatibility issues. Alongside this, the benefits of automation are highlighted, such as improved operational efficiency, cost reduction, and enhanced customer service. The research results show that 3D configurator automation is a promising direction for companies seeking to remain competitive and meet modern market demands. Recommendations for effective 3D configurator implementation are developed, considering new technologies and the specifics of a three-tier architecture, with a focus on security, flexibility, and system adaptability
COMPARATIVE ANALYSIS OF DECENTRALIZED LAST MILE DELIVERY SYSTEMS
Authors: Leshchenko Yulia , Moroz Ihor , Yukhymchuk Maria , Dubovoi Volodymyr
Published: December 2024

Decentralized last-mile delivery is a modern logistics approach that optimizes the delivery process by using local hubs or microhubs located near the final recipients. This reduces the distance between the hubs and the delivery location, which reduces transportation time and operating costs. At the same time, customers receive their orders faster, which increases their satisfaction with the service. This approach is extremely relevant amid the growing popularity of e-commerce, where speed and accuracy of delivery are crucial to maintaining customer loyalty. However, the successful operation of a decentralized delivery model requires a sophisticated logistics management system. Artificial intelligence technologies come to the rescue to solve a number of tasks, such as route optimization, inventory management, and demand forecasting. For example, machine learning algorithms are able to adapt courier routes in real time to changes in traffic, weather conditions, and road conditions, which reduces fuel costs and reduces the number of vehicles on the road. This is especially important in large urban areas with heavy traffic, where even small delays can significantly affect the overall delivery time. AI also plays an important role in inventory management, allowing for more accurate planning of replenishment of goods in individual local hubs, avoiding excessive accumulation of products or their shortage. By analyzing historical sales data and consumer behavioral patterns, AI systems can predict the demand for different categories of goods in certain areas. This helps minimize storage costs and ensure that products are available in the right place and at the right time, which in turn increases delivery efficiency. Thus, a decentralized last-mile delivery model involving artificial intelligence allows logistics companies to significantly improve the quality of service, increase the efficiency of all logistics processes, and reduce the negative impact on the environment.
TEST OBJECT MODEL: CONCEPT, APPLICATION, AND ROLE IN TEST AUTOMATION
Authors: Huralnyk Frederik , Kvyetnyy Roman
Published: December 2024

This research explores the concept of the Test Object Model and its role in software test automation. The This paper examines the concept of a test object model (TOM) and its key role in automating software testing processes. The test object model is one of the most effective methodologies that simplifies the development and maintenance of tests through modularity and code reuse. The paper provides a detailed analysis of the fundamental principles of TOM construction, focusing on the structuring of tests via abstraction of user interface elements. The advantages of using this model are highlighted, including improved code readability, the ability to quickly adapt to interface changes, and the minimization of manual work when test scenarios change. A separate section is dedicated to the practical aspects of implementing a test object model. In this context, methods for building a class catalog, creating class diagrams to describe test entities, and examples of deriving classes to ensure flexibility in testing are explored. The paper presents effective approaches to abstracting user interface elements, which help avoid code duplication and make tests more resistant to changes in the application interface. Additionally, the possibilities of reusing existing test classes to increase the efficiency of the development and testing teams are discussed. The study also investigates the impact of the test object model on the overall project structure and its ability to make the project more scalable and transparent for all team members. The use of TOM allows for the optimization of testing processes by reducing the time spent on developing and maintaining test scenarios. This is confirmed by the study results, which show an increase in the stability and quality of automated tests, ultimately leading to an overall improvement in software quality.
COMMUNICATION PROTOCOLS FOR SECURE DATA EXCHANGE BETWEEN UAVS IN A DISTRIBUTED SYSTEM
Authors: Protsenko Mykhailo , Maslii Roman
Published: December 2024

With the development of unmanned aerial vehicle (UAV) technologies and the increasing need to use them to collect and share data in real time, an important challenge arises to ensure reliable and secure communication between UAVs in distributed systems. With increasing demands on data security and the speed of information exchange, secure data exchange is becoming critical to the effective execution of various operations, such as joint reconnaissance, monitoring, or search missions. That is why communication protocols for such networks must ensure reliable data transmission, resistance to hacking and cyberattacks, and optimization of UAV resources to maximize efficiency and energy savings. The main aspects affecting the effectiveness of such systems are the reliability of data transmission, protection against hacking and attacks, and flexibility in the event of dynamic changes in operating conditions. This paper investigates the most advanced communication protocols for secure data exchange between UAVs, such as Ad-Hoc On-Demand Distance Vector (AODV), which allows dynamic routing in a changing network topology, and Secure Routing Protocol (SRP), which provides secure data transmission through authentication of network participants. In addition, the author discusses the Datagram Transport Layer Security (DTLS) protocol, which provides data encryption even in unreliable networks, and Optimized Link State Routing (OLSR), which optimizes routing in large networks and ensures reliable data transmission in complex environments. Security mechanisms, such as node authentication, which identifies each device in the network, and data encryption, which prevents intruders from accessing confidential information, are analyzed separately. Protection against DoS attacks ensures that the system is resistant to overload and loss of communication. This approach to building a communication system allows UAVs to be used efficiently and safely to carry out missions in difficult conditions, ensuring their reliability and durability even in the event of a failure of individual network components. The introduction of new technologies and approaches to organizing data transmission between drones can significantly expand the capabilities of UAVs, which is an important step in the development of this industry.
APPLICATION OF VISUAL INERTIAL SLAM ALGORITHM FOR AUTONOMOUS ROBOT NAVIGATION
Authors: Zharkov Anatoliy , Maslii Roman
Published: December 2024

This work investigates the application of the Visual-Inertial SLAM (Simultaneous Localization and Mapping) algorithm for the navigation of an autonomous robot. With the development of autonomous navigation technologies, there is a need for effective methods that allow robots to navigate in complex environments. Visual-Inertial SLAM combines data from cameras and inertial measurement devices, which ensures high accuracy of localization and map construction. Several SLAM approaches based on particle filter, extended Kalman filter, and neural networks have been investigated over the decades. These approaches are designed to construct maps in a variety of representations, including landmark, surface, polygon grid, and occupancy grid representations. They are now widely used for applications such as robot motion planning in unknown environments and are used in self-driving cars, unmanned aerial vehicles, and autonomous underwater vehicles. This work aims to simultaneously localize and map a robot in an unknown indoor environment using IMU odometry data and special points detected by a stereo camera. To achieve this goal, an extended approach based on the Kalman filter is implemented. The Kalman filter is an optimal linear estimator for linear system models with additive independent white noise in both forecasting and observational systems. The extended Kalman filter adapted computational methods, namely multivariate Taylor series expansions, to linearize the nonlinear model. The proposed solutions can be useful for the improvement of autonomous systems such as delivery robots, drones and mobile platforms, as well as for the development of new methods of integrating sensor data in modern navigation technologies.
COMPARATIVE ANALYSIS OF FORECASTING MODELS OF THE AIR CONDITION INDICATOR
Authors: Shmundiak Dmytro
Published: December 2024

Periodic time series have many applications in our lives. Examples of periodic time series are air quality indicators, financial market indicators, meteorological parameters, etc. Because of this, the analysis and forecasting of periodic time series is a widespread and interesting scientific topic. One of the main problems in the analysis of periodic time series is the determination of the parameters of the seasonality of this series and the identification and elimination of abnormal values that can significantly affect the accuracy of data forecasting. In this work, a comparative analysis of the previously developed models and approaches for air quality indicator forecasting is given. The research is based on real data from the EcoCity public air quality monitoring network. A brief description of the method of identifying the seasonality parameters of the time series based on the decomposition of this time series and an approach to finding local anomalies in a time series based on the results of series decomposition is given. The results of the described models were used to forecast the PM2.5 dust index of one of the air quality monitoring stations in the Vinnytsia region. The Python programming language was used to automate the forecasting process, and the program code itself was implemented in the Kaggle system, a web platform from Google for machine learning engineers. The Prophet time series model was used for forecasting. A comparison table of the forecast accuracy of the Prophet model with default settings and with custom configuration based on the data from developed models and approaches was provided. The study and analysis showed that using both developed methods helps to reduce the forecasting error for the air quality indicator. Compared to the accuracy of the Prophet model with the default parameters, it was possible to reduce the MAE error value by 30% and the RMSE by 21%. This proves that these methods are effective for the analysis and forecasting of time series, including time series of air quality indicators.
INTELLIGENT DECISION SUPPORT IN THE PRODUCTION OF ENTOMOPHAGES: AN ONTOLOGICAL APPROACH
Authors: Chernova Irina , Lysenko Vitaliy
Published: December 2024

In the production of entomophages of guaranteed quality for the biological protection of plants, as a complex biotechnical system of the ergic type, there are information flows that require there are, structuring and formalization. The application of the ontological approach, in particular, intelligent information technologies, allows to implement these functions. Currently, it is known that the ontological approach, as a generalization system, is actively used in the research of decision-making support processes, in particular, in the development of knowledge bases of intelligent information systems and the creation of automated knowledge management systems. The aim of the work was the development of a thesaurus of intellectual support for decision-making in the production of entomophages by managing the acquired knowledge using the results of own research, an ontological approach and the open source software environment Visual Understanding Environment. The thesaurus generalizes, structures and formalizes procedural knowledge in the form of the following components of the ontological approach: an expert system based on T. Saati's method of analyzing hierarchies, expert systems of fuzzy inference, fuzzy cognitive maps, Bayesian network, neural networks, frames, cognitive models. The thesaurus construction algorithm consists of the definition of concepts (knowledge regarding intellectual decision-making support in the production of entomophages), their decomposition into goals, means of automation (visualization) and efficiency. The specified approach allows to increase the level of informatization management processes of complex production due to the automation of knowledge acquisition, is useful in the processes of developing knowledge bases of intelligent systems. The research results are the basis for the development of a decision support system based on ontologies in the production of entomophages
VIBROMONITORING OF THE CENTRAL ASPIRATION INSTALLATION IN THE ASUTP OF THE CRUSHING FACTORY
Authors: Oselskyi Oleksand , Kukharchuk Vasyl
Published: December 2024

Mining and beneficiation production is quite famous for its scale and complexity of the technological process. For its maintenance, a large number of service personnel is involved, which contributes to the efficient operation of the enterprise around the clock. To facilitate the control and management of the technological process, local and global automation systems are implemented. In addition to monitoring the main indicators of production, great attention is paid to the organization of safe work of people and the environment. Since such production is accompanied by the formation of a large amount of dust and emissions of pollutants into the atmosphere or the working space of enterprises, air purification systems are used in enterprises to preserve the environment, safety and health of service personnel. Air aspiration systems at mining enterprises are mandatory for the operation of production as a whole. Therefore, the monitoring of the operation of the aspiration system should be carried out around the clock, and the exit from the working state of the main organs of the aspiration units should lead to a stoppage of the technological process. Since the main working body of the aspiration system is the smoke extractors, it is necessary to monitor their condition. One of the most effective methods of detecting malfunctions on heavy machinery is the vibration monitoring system. The automation control system was modernized and a vibration monitoring subsystem of the central aspiration unit of the crushing plant was created on the basis of VTV121 sensors of the ifm company, which allows for 24/7 monitoring of the state of smoke extractors for the early detection of mechanical, electrical and aerodynamic malfunctions and the prediction of emergency situations.
INFORMATION TECHNOLOGY FOR THE ADAPTATION OF WEB-RESOURCE "INSURANCE COMPANY" AS A MOBILE APPLICATION
Authors: Dubovyi Ruslan , Denysiuk Valerii
Published: December 2024

In the current state of society, where technology is rapidly developing, a web presence is becoming a necessary component of business success. Insurance companies are no exception, as they provide important financial services that require access and communication with customers. The introduction of a web resource for an insurance company is becoming an urgent task for improving communication with clients, ensuring the convenience and speed of access to information and services. The first thing to consider is the growing popularity of online shopping and online services. Customers are increasingly looking for an opportunity to obtain an insurance policy or to obtain information about the services of an insurance company directly on the Internet. A web resource for an insurance company creates an opportunity to attract new customers and retain the existing customer base, thanks to the convenience and speed of service. The second factor of relevance is competition in the market of insurance services. New insurance companies appear every year, which leads to increased competition. Creating a web resource for an insurance company allows you to stand out among competitors, emphasize your professionalism, high quality of services and ease of communication with clients. In addition, the web resource of the insurance company provides the possibility of effective management of client data and processes. This allows the insurance company to store and analyze customer data, identify their needs and offer appropriate insurance solutions. Analyzing the data obtained through the web resource helps insurance companies to understand their customers better, as well as to improve their services and adapt to the changing needs of the market. The topicality of the topic is due to the growing demands of users for the availability and convenience of obtaining insurance services through mobile devices. The article analyzes the main stages of adaptation, including interface design, functionality optimization and data security. Special attention is paid to methods of improving interaction with the user and integration of modern technologies. The advantages of the mobile application for users and the company, as well as potential challenges arising during the implementation of the project, are highlighted. The results of the study can serve as a basis for further developments in the field of digitalization of insurance services.
GROUND DRONE CONTROL THROUGH SIMULINK APPLICATION
Authors: Skoroid Maksym
Published: December 2024

The report presents the method of programming Arduino development boards through the Simulink tool of the Matlab software environment. The peculiarities of the application of computerized systems for remote control of various types of drives via Wi-Fi communication are considered. Advantages and disadvantages of programming Arduino Uno development boards using motor shield expansion modules and a Wi-Fi module in the Matlab programming environment at the time of its Simulink tool are analyzed. To implement the programming of Arduino development boards, the connection of third-party extensions was used, such as Simulink Support Package for Arduino Hardware and Image Acquisition Toolbox Support Package for OS Generic Video Interface, which add programming tools for Arduino development boards through the Simulink application and tools for working with video images and images from Web camer and create the possibility of integrating the Wi-fi Camer into the Matlab software environment in time for its Simulink tool for observing and recording the operation of a ground tracked drone for its further implementation in the military industry for use in demining the area. This method is preferred due to the fact that it does not require prior programming skills with writing code in the C/C++ language to perform complex programs and tasks. The created block 6 program for controlling a ground tracked drone via a Wi-Fi network and its modification with the addition of a Robotic Technical System (RTS) with four degrees of freedom are considered. A four-degree-of-freedom RTS control program is also considered to add new capabilities and improve the use of ground-tracked drones. The created model for visual display of the work of a ground tracked drone with the ability to save video images of its work is considered. It is expected that this method of controlling the operation of ground tracked drones through a Wi-Fi network with remote monitoring of its operation will be suitable for the implementation of tracked drones by the military to use ground drones for demining more dangerous areas.
BLOOD INSULIN LEVEL MONITORING SYSTEMS: ANALYSIS AND COMPARISON
Authors: Kruhlikov Oleksandr , Kozhemiako Andrii
Published: December 2024

The existing methods and systems of insulin level monitoring were reviewed and considered. A comparison table with key parameters for accuracy, comfort and availability of the systems is provided.
SOFTWARE AND TECHNICAL ENVIRONMENT FOR PRACTICAL STUDY BY STUDENTS OF THE BASICS OF THE INDUSTRIAL INTERNET OF THINGS
Authors: Papinov Volodymyr
Published: December 2024

The report proposed a new architecture of the software and technical environment for mastering by students of specialty 174 "Automation, computer-integrated technologies and robotics" of methods and means of practical application of the industrial Internet of Things in the automation of production based on the concept of "Industry 4.0". Unlike the existing ones, the new software and technical environment is built on the basis of online information services of Google, software tools of Microsoft "Office 365" and the information and educational environment "Virtual Chemical Production", which allows students to more effectively form modern professional competencies in in the form of professional knowledge that is not articulated (practical skills, experience, intuition).
AI-DRIVEN GREENHOUSE MANAGEMENT: OPPORTUNITIES AND CHALLENGES IN AUTOMATION
Authors: Suvorin Oleg , Kabachiy Vladyslav
Published: December 2024

The article discusses the opportunities and challenges associated with the automation of greenhouse management based on artificial intelligence (AI). Modern agriculture faces problems such as limited arable land, climate change and the need to ensure food security for a growing population. AI combined with computer vision and machine learning enables more precise management in greenhouses, which in turn contributes to higher yields and lower resource costs. However, automated systems face significant challenges, especially in the context of the war in Ukraine. These include dependence on internet connectivity, the risk of crop failure due to force majeure and the need for high resilience to external factors. The article includes an analysis of scientific research confirming the potential of AI in greenhouse management, as well as an examination of existing solutions such as LUNA by iUNU, AgroFlow and Heliospectra. The LUNA solution integrates computer vision for real-time monitoring of plant conditions, enabling precise management of climatic conditions. AgroFlow specializes in optimizing irrigation and monitoring soil conditions, while Heliospectra uses intelligent LED lighting systems to maximize photosynthesis. These technologies reduce the use of water, fertilizers and energy and increase yields by 15-30% under different conditions. The authors pay particular attention to the challenges associated with dependence on cloud services and internet connectivity, which can lead to interruptions in system operation. Proposed solutions include implementing local data processing systems, backup power sources, alternative connectivity technologies such as satellite internet and dividing the greenhouse power supply into zones with implemented queues. Overall, the authors conclude that the development of autonomous greenhouses with AI can significantly improve the yield performance and stability of agricultural production, reduce dependence on external resources and increase the resilience of greenhouse systems to external factors, which is particularly important in emergencies such as war and natural disasters.
APPLICATION OF BPMN FOR MANAGEMENT OF REMEDIATION PROCESSES IN WAR-AFFECTED TERRITORIES OF UKRAINE
Authors: Cherniavska Tetiana , Cherniavskyi Bohdan
Published: December 2024

The need for scientific developments in creating an effective management system for remediating war-affected territories is becoming an increasingly relevant and significant issue. The international community has recognized that the second most extensive and destructive war in Europe (after World War II, author's note) has inflicted substantial damage on Ukraine's ecosystems and natural resources. The restoration of territories contaminated with chemical substances, military debris, and other hazardous waste requires a systematic and comprehensive approach to coordinating the actions of all participants in the remediation process, as well as overseeing task fulfillment, with a focus on optimizing resource and time usage. Therefore, the authors explore the potential use of BPMN (Business Process Model and Notation) as a tool for enhancing the efficiency of remediation process management at all levels of hierarchy: the higher state level, the intermediate (regional) level, and the local management level. The article analyzes BPMN’s key advantages, notably its capacity to visualize, structure, and automate all stages of contaminated area remediation, from environmental condition analysis to monitoring restoration operations and evaluating results. What makes BPMN particularly valuable for management in the outlined application conditions is its ability to support rapid and effective decision-making through access to updated information. In the authors' study, BPMN is considered within the context of large-scale management of complex remediation processes, including the capability to model various scenarios, monitor task execution, and ensure the achievement of critical goals. Special attention is given to analyzing the possibilities of BPMN hybridization, proposing its integration with other technologies such as Geographic Information Systems (GIS). According to the authors, such a hybrid management system would become even more responsive and able to adapt swiftly to changing circumstances during remediation efforts.
SIMULATION OF THE REACTIVE POWER COMPENSATION PROCESS UNDER THE RANDOM CHARACTER OF LOADING
Authors: Burbelo Michailo , Kravets Oleksandr , Loboda Yurii , Slobodian Ruslan
Published: December 2024

The results of modeling the process of compensation of reactive power in distribution electric networks, which are equipped with devices for smooth regulation of reactive power, under the random nature of the load, are presented. The mode of compensation of reactive power based on the criterion of minimum loss of active power is considered.
VIBRATION CHARACTERISTICS ANALYSIS OF ELECTRICAL TRANSMISSION LINE WIRES DURING ICE MELTING
Authors: Kuchansky Vladyslav , Zaitsev Ievgen
Published: December 2024

The article analyzes the relationship between the ice melting current, the temperature distribution and the vibration of overhead power line wires, which is based on the use of the serial connection method to obtain the equation of the connection between electric and thermal energy, which is released in the process of melting the ice of the wires by a вшкусе current.
OPTIMIZATION OF HOURLY OUTAGE SCHEDULES AND MONITORING OF THEIR IMPLEMENTATION BY THE ELECTRICITY DISTRIBUTION SYSTEM OPERATOR
Authors: Kulyk Volodymyr
Published: December 2024

An integrated approach is proposed for the formation and implementation of measures to limit power supply in the conditions of a shortage of generated power in the power system of Ukraine caused by military operations. The software implementation of modules for planning schedules of hourly customer outages (SHO), registration of actions of dispatchers of the distribution system operator (DSO) on the implementation of SHO, graphical display of SHO for informing the population, internal control over the implementation of SHO based on data from the automated system of commercial electricity metering (ASCEM) is proposed. A method and program for optimizing the SHO was developed to ensure uniformity of power supply restrictions to consumers. The volume of the limitation was determined by the ratio of the projected electricity consumption and the maximum load, as determined by the National Energy Company. To find the optimal solution, the following criteria were used: the accuracy of compliance with the maximum load should be maximized, the duration of outages for individual customers should be minimal, and the uniformity of outages for individual customers should be maximized. To enable the practical implementation of optimal solutions, a number of constraints were taken into account, including the presence of critical infrastructure consumers and the need to maintain their backup power supply, a given frequency of outages for household consumers, different levels of economic consequences of power outages for different regions, the current state (gradual decrease in resource) of switching equipment at distribution power substations, etc. The ensemble Random Forest method was used to forecast consumer load. To determine the weighting coefficients of the components of the objective function, the methods of expert evaluation and sensitivity analysis were used. To find the optimum, the method of optimized search of options with weighting is used. The effectiveness of the proposed methods and algorithms has been confirmed during the industrial operation of the complex of programs.
IMPROVING THE ACCURACY OF THE FORECAST OF ELECTRICITY PRODUCTION BY PHOTOELECTRIC PLANTS BASED ON THE RANDOM FOREST METHOD
Authors: Kulyk Volodymyr , Zatkhei Maksym
Published: December 2024

The paper considered the Random Forest method as a tool for forecasting the generation of photovoltaic plants, which is a key element for optimizing the structure of the electricity balance in the power system. Photoelectric stations are characterized by significant dependence on meteorological conditions, which creates difficulties in accurately forecasting their generation. The use of the Random Forest method allows taking into account numerous variables and complex interrelationships between them, which increases the accuracy of the forecast in conditions of significant uncertainty inherent in renewable energy. On the basis of the conducted research, an effective Random Forest application algorithm was proposed, which allows to reduce forecast errors. Particular attention is paid to how the model can adapt to changes in weather conditions and seasonal variations, which are important factors in maintaining the stable operation of the power system. The results of the study demonstrate that the application of the Random Forest method for forecasting the generation of photovoltaic plants provides an acceptable level of accuracy for planning power reserves in the power system. In particular, it allows power system operators to more effectively manage the balance of electricity, planning in advance the necessary power reserves depending on the forecasted volumes of renewable energy generation. This is especially important to ensure the stability of the power system during peak loads and in conditions of a growing share of renewable energy sources in the overall generation structure.
DETERMINING FOR CONSUMERS THE ORIGIN OF ELECTRICITY FROM LOW-CARBON ENERGY SOURCES
Authors: Hunko Iryna , Lysyi Vladyslav , Sytnyk Artur
Published: December 2024

The research focuses on determining the share of electricity that a consumer receives from low-carbon sources, such as renewable energy sources and nuclear power. Confirmation of the origin of the consumed electricity helps to improve the company's image in the eyes of customers, partners and investors and to label products accordingly. Also, in the context of the introduction of the EU's carbon adjustment mechanism for imports (CBAM), determining the origin of electricity is becoming relevant for companies in such industries as metallurgy, construction, energy and agriculture. CBAM will create additional barriers to trade by increasing costs due to carbon emissions, making it more difficult for Ukrainian goods to export to the EU. The use of clean energy can reduce the cost of carbon certificates under the CBAM. Companies sourcing energy from lowcarbon sources will have fewer CO2 emissions, which will reduce their import costs to the EU. For companies and entrepreneurs engaged in foreign trade, this can be an important strategy for adapting to new requirements and remaining competitive. In order to confirm the origin of electricity from LCES, the article investigates the possibility of applying a method for calculating individual components of electricity flows in the branches of the power grid circuit caused by generation and consumption in the nodes. The method is based on the methods and algorithms for calculating steady-state modes of power grids. As a result, a matrix of power distribution coefficients is formed, which allows determining the component of power flows in the branches of the circuit caused by the generation of LCES. As an example, a calculation was performed for an IEEE circuit of 14 nodes, including various energy sources, using the Power Factory software package. The analysis of the calculation results is confirmed by the results of computer modelling.
INCREASING THE EFFICIENCY OF THE USE OF MEASURING TRANSFORMERS DURING ELECTRICITY METERING
Authors: Babenko Oleksii , Goloborodko Oleksandr , Zakharov Vasyl
Published: December 2024

Error limits of current and voltage measuring transformers are given and analyzed. The influence of factors on the accuracy of current and voltage measurement, as well as accounting of active and reactive electricity using current and voltage measuring transformers, was analyzed. In particular, for a measuring current transformer, such factors are the load schedule of the consumer, individual metrological characteristics of the transformer itself, as well as the load of its secondary winding (load). As for measuring voltage transformers, the accuracy of their operation is affected by the value of the load and individual metrological characteristics. It is emphasized that for the effective use of current and voltage measuring transformers at specific objects, it is necessary to conduct research in order to obtain initial information that will help to substantiate the specified efficiency: graphs of consumer loads, loads of secondary circuits, metrological characteristics. The analysis of the received information makes it possible to outline the most appropriate measures to increase the specified efficiency: optimization of the loading of the secondary circuits of the measuring transformers by, for example, choosing the optimal switching scheme, applying additional loads, as well as using measuring transformers of a higher accuracy class. An analysis of the results of the verification of voltage measuring transformers is given, which showed that the accuracy class of the indicated transformers corresponds to the values standardized by the state standard for loads from 25 to 100%, and in the case of a smaller or larger load, their error increases. In particular, with a smaller load, the error increases in the positive direction and reaches up to +0.5% per phase. The latter, in turn, leads to an increase in the measurement error of active or reactive energy in a threephase network of consumers up to +1.5%.
REACTIVE POWER COMPENSATION OF MAIN ELECTRICAL NETWORKS IN ACCORDANCE WITH THE REQUIREMENTS OF MODERN INTERNATIONAL STANDARDS
Authors: Kuchansky Vladyslav , Tugai Yuriy , Tugai Irina
Published: December 2024

The main requirements for compensation of reactive power in ultra-high voltage alternating current power transmission systems are outlined. A block diagram of reactive power compensation planning by controlled shunt reactors and static synchronous compensators is given
DAMAGE AND DIAGNOSIS OF POWER TRANSFORMERS OF PHOTOVOLTAIC PLANTS
Authors: Rubanenko Oleksandr , Smaglo Ivan
Published: December 2024

The damage to the equipment of photovoltaic plants (PHS) was studied. The main attention is paid to oil-filled transformers with a voltage of 10/.0.4 kV, 35/.0.4 kV, 35/10/.0.4 kV with a capacity of up to 5 MVA and the development of an algorithm for determining probable places of damage to photovoltaic modules, which allows you to choose diagnostic equipment. The use of such equipment will ensure the detection of damage to power transformers and photovoltaic modules at an early stage of their development, as well as timely measures aimed at preventive repairs, reduce the number of transformer damages, downtime and repair of damaged power transformers that were damaged during their operation on FES. Operation of power transformers at photovoltaic plants involves their frequent switching on and off. High-voltage vacuum switches designed for a voltage of 10 kV or 35 kV are used as high-voltage switching devices. The capacity of inverters, the inductance of the windings of power transformers, the inductance of the windings of measuring voltage transformers, the capacity of cable lines and inserts under the conditions of using vacuum switches create prerequisites for the occurrence of commutation overvoltages, the occurrence of resonances in circuits (power transformer, cable insert or cable line, measuring voltage transformer). Increased thunderstorm activity is observed in the places of operation of some photovoltaic plants. The electrical equipment of these stations is affected not only by switching (internal overvoltages), but also by atmospheric overvoltages. To protect against overvoltages, arresters (type RVO, RVS, etc.) and overvoltage limiters are used. The damage of these surge arresters and limiters indicates the existence and intensity of overvoltages. Damage to cable inserts and cable couplings, voltage measuring transformers at photovoltaic stations and in electrical networks near these stations also testify to the negative impact of overvoltages on the FES equipment, including power transformers of these stations.
AUTOMATION OF CONTROL OF DISTRIBUTED GENERATION AND LOAD OF THE DISTRIBUTION NETWORK IN CASE OF SEPARATION FROM THE POWER SYSTEM
Authors: Andrushko Stanislav , Kulyk Volodymyr
Published: December 2024

This report discusses the current issues of distributed energy systems, in particular in the context of Ukraine, which is facing challenges in maintaining reliable electricity supply due to the war. Particular attention is paid to the use of the ‘energy island’ concept to ensure the autonomy of energy supply in the face of possible emergencies or attacks on infrastructure. The term ‘energy island’ covers self-sufficient systems that can operate autonomously from the main power grid, combining distributed energy sources (RES), including renewable energy sources, and consumers within microgrids. The text provides examples of countries that have already successfully implemented such an isolated power system and analyses the potential benefits of introducing similar technologies in Ukraine. The report emphasises the strategic importance of distributed generation (DG), which can operate independently of the centralised power system in crisis conditions. Based on a literature review and international experience, a structured concept of a microgrid based on distributed generators with autonomous control systems is proposed. The article describes the technical features of automation systems that ensure stable functioning of the microgrid in the conditions of disconnection from the main grid. In particular, it describes the requirements for automatic frequency and voltage regulators, reclosers that ensure safe transition to the island mode, as well as generator monitoring and synchronisation systems. The study is aimed at improving the reliability of the Ukrainian power system through the introduction of distributed energy sources and energy storage systems (ESS), which will increase the resilience of distribution networks to external influences. An important element of the study is the emphasis on the advantages of hydroelectric power plants, which can be easily started without an external power source, as they require minimal energy for auxiliary systems, so the report uses a hydroelectric power plant as an example, although the principles are generally relevant to other DGS
ANALYSIS OF THE USE OF DECENTRALIZED ELECTRIC GRIDS WITH SMALL MODULAR REACTORS
Authors: Yukhymchuk Maria , Lesko Vladyslav
Published: December 2024

In the article "Analysis of the Use of Decentralized Electric Grids with Small Modular Reactors," the latest approaches to energy security and the resilience of electrical systems through the integration of small modular reactors (SMRs) into decentralized electric grids are examined. In the context of global challenges such as climate change, rising demand for electricity, and the need to reduce greenhouse gas emissions, decentralized energy supply systems are becoming increasingly relevant. The article begins with an overview of the technological aspects of small modular reactors, including their design and operating principles. The authors emphasize the advantages of SMRs, such as compactness, high safety, the possibility of modular manufacturing, and flexibility in placement. They also discuss the potential of SMRs to ensure energy independence for regions and to mitigate risks associated with centralized electricity generation. Subsequently, the article analyzes the economic and environmental benefits of decentralized electric grids. In particular, it highlights the reduction in electricity transportation costs and the opportunities for integrating renewable energy sources alongside SMRs. The authors explore existing models for integrating SMRs into decentralized systems, analyzing their functioning in various countries and regions. A separate section of the article addresses the challenges that arise from implementing decentralized electric grids with SMRs. These include regulatory barriers, technological risks, and safety concerns. The authors propose possible solutions and strategies for overcoming these obstacles, emphasizing the importance of international cooperation and knowledge sharing. The concluding part of the article contains recommendations for further research in this field, particularly in the direction of developing new technologies and regulatory frameworks that will facilitate the effective integration of small modular reactors into decentralized electric grids. This article will serve as a valuable resource for energy professionals, researchers, and policymakers seeking to implement innovative solutions for a sustainable energy future.
RESEARCH ON MODERN METHODS AND TOOLS FOR DIAGNOSING HIGH-VOLTAGE EQUIPMENT
Authors: Yukhymchuk Maria , Lesko Vladyslav , Klymchuk Oleksandr
Published: December 2024

The article "Research on Modern Methods and Tools for Diagnosing High-Voltage Equipment" examines key aspects of diagnosing and monitoring high-voltage systems used in energy and industry. High-voltage equipment, such as transformers, switching devices, and cable lines, is critical for ensuring the reliability of electrical networks. Failures in these systems can lead to significant economic losses, interruptions in electricity supply, and even emergency situations. The article focuses on modern diagnostic methods, including non-invasive technologies such as thermography, acoustic emission, and ultrasound testing. These methods allow for the early detection of defects, reducing the risks of serious issues arising. Special attention is given to technologies for measuring and analyzing electrical parameters, which ensure timely detection of deviations in equipment performance. The authors also analyze innovative monitoring tools, including systems based on the Internet of Things (IoT). These systems can provide round-the-clock monitoring of the condition of high-voltage equipment, allowing for prompt responses to changes in its operation. The prospects of using artificial intelligence and machine learning to improve diagnostic accuracy and predict potential failures are also discussed. The article presents the results of practical studies that confirm the effectiveness of modern diagnostic methods in real operational environments. It highlights the role of diagnostics in maintenance planning and asset management, which helps reduce costs and enhance the reliability of energy systems. Thus, the article emphasizes the importance of implementing modern diagnostic technologies in the field of high-voltage equipment, outlining the main advantages, challenges, and prospects for their application. This makes it a valuable resource for professionals, engineers, and researchers working in this field.