Anna Vitiuk, Leonid Polishchuk, Nataliia B. Savina, Oksana O. Adler, Gulzhan Kashaganova, Saule Kumargazhanova
The characteristic features of engineering products are revealed. Average industry performance indicators of mechanical engineering enterprises in Ukraine were formed. The competitiveness of mechanical engineering enterprises was studied. The integral indicator of the competitiveness of mechanical engineering enterprises in Ukraine was evaluated. It has been established that the competitiveness industry, despite certain profits received by enterprises, is in a systemic, predictable crisis and only individual enterprises that maintain their own line of economic behavior are successful, increase competitiveness and have prospects for further economic growth.
{"title":"ENGINEERING AND TECHNICAL ASSESSMENT OF THE COMPETITIVENESS OF UKRAINIAN MECHANICAL ENGINEERING ENTERPRISES BASED ON THE APPLICATION OF REGRESSION MODELS","authors":"Anna Vitiuk, Leonid Polishchuk, Nataliia B. Savina, Oksana O. Adler, Gulzhan Kashaganova, Saule Kumargazhanova","doi":"10.35784/iapgos.5351","DOIUrl":"https://doi.org/10.35784/iapgos.5351","url":null,"abstract":"The characteristic features of engineering products are revealed. Average industry performance indicators of mechanical engineering enterprises in Ukraine were formed. The competitiveness of mechanical engineering enterprises was studied. The integral indicator of the competitiveness of mechanical engineering enterprises in Ukraine was evaluated. It has been established that the competitiveness industry, despite certain profits received by enterprises, is in a systemic, predictable crisis and only individual enterprises that maintain their own line of economic behavior are successful, increase competitiveness and have prospects for further economic growth.","PeriodicalId":53131,"journal":{"name":"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136279778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper is devoted to questions of technological fatigue life assurance of parts working in conditions of cyclic loads by optimization their cutting conditions for finish turning process. In order to solve the task of optimizing the parts cutting conditions, the corresponding software, based on the previously created mathematical model of the finishing turning process, was developed in the C# programming language. With the purpose of technological providing the necessary fatigue life of the part, taking into account the real conditions of its operation for the maximum productivity of the finishing turning process, the methodical recommendations for determining the optimal parts cutting conditions at the phase of production technological preparation are given. An example application of the proposed solution is presented.
{"title":"OPTIMIZATION OF PARTS CUTTING PROCESS PARAMETERS WORKING IN CONDITIONS OF CYCLIC LOADS","authors":"Kateryna Barandych, Sergii Vysloukh, Grygoriy Tymchyk, Oleksandr Murashchenko, Saule Smailova, Saule Kumargazhanova","doi":"10.35784/iapgos.3650","DOIUrl":"https://doi.org/10.35784/iapgos.3650","url":null,"abstract":"The paper is devoted to questions of technological fatigue life assurance of parts working in conditions of cyclic loads by optimization their cutting conditions for finish turning process. In order to solve the task of optimizing the parts cutting conditions, the corresponding software, based on the previously created mathematical model of the finishing turning process, was developed in the C# programming language. With the purpose of technological providing the necessary fatigue life of the part, taking into account the real conditions of its operation for the maximum productivity of the finishing turning process, the methodical recommendations for determining the optimal parts cutting conditions at the phase of production technological preparation are given. An example application of the proposed solution is presented.","PeriodicalId":53131,"journal":{"name":"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136280122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Fatkhurokhman Fauzi, . Ismatullah, Indah Manfaati Nur
Opinions related to rising fuel prices need to be seen and analysed. Public opinion is closely related to public policy in Indonesia in the future. Twitter is one of the media that people use to convey their opinions. This study uses sentiment analysis to look at this phenomenon. Sentiment is divided into three categories: positive, neutral, and negative. The methods used in this research are Adaptive Synthetic Multinomial Naive Bayes, Adaptive Synthetic k-nearest neighbours, and Adaptive Synthetic Random Forest. The Adaptive Synthetic method is used to handle unbalanced data. The data used in this study are public arguments per province in Indonesia. The results obtained in this study are negative sentiments that dominate all provinces in Indonesia. There is a relationship between negative sentiment and the level of education, internet use, and the human development index. Adaptive Synthetic Multinomial Naive Bayes performed better than other methods, with an accuracy of 0.882. The highest accuracy of the Adaptive Synthetic Multinomial Naive Bayes method is 0.990 in Papua Barat Province.
{"title":"UNBALANCED MULTICLASS CLASSIFICATION WITH ADAPTIVE SYNTHETIC MULTINOMIAL NAIVE BAYES APPROACH","authors":"Fatkhurokhman Fauzi, . Ismatullah, Indah Manfaati Nur","doi":"10.35784/iapgos.3740","DOIUrl":"https://doi.org/10.35784/iapgos.3740","url":null,"abstract":"Opinions related to rising fuel prices need to be seen and analysed. Public opinion is closely related to public policy in Indonesia in the future. Twitter is one of the media that people use to convey their opinions. This study uses sentiment analysis to look at this phenomenon. Sentiment is divided into three categories: positive, neutral, and negative. The methods used in this research are Adaptive Synthetic Multinomial Naive Bayes, Adaptive Synthetic k-nearest neighbours, and Adaptive Synthetic Random Forest. The Adaptive Synthetic method is used to handle unbalanced data. The data used in this study are public arguments per province in Indonesia. The results obtained in this study are negative sentiments that dominate all provinces in Indonesia. There is a relationship between negative sentiment and the level of education, internet use, and the human development index. Adaptive Synthetic Multinomial Naive Bayes performed better than other methods, with an accuracy of 0.882. The highest accuracy of the Adaptive Synthetic Multinomial Naive Bayes method is 0.990 in Papua Barat Province.","PeriodicalId":53131,"journal":{"name":"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136280595","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In time series analysis, signal processing, and financial analysis, simple moving average (SMA), weighted moving average (WMA), exponential moving average (EMA), exponential weighted moving average (EWMA), and Kalman filter are widely used methods. Each method has its own strengths and weaknesses, and the choice of method depends on the specific application and data characteristics. It is important for researchers and practitioners to understand the properties and limitations of these methods in order to make informed decisions when analyzing time series data. This study investigates the effectiveness of time series analysis methods using data modeled with a known exponential function with overlaid random noise. This approach allows for control of the underlying trend in the data while introducing the variability characteristic of real-world data. The relationships were written using scripts for the construction of dependencies, and graphical interpretation of the results is provided.
{"title":"COMPARISON OF THE EFFECTIVENESS OF TIME SERIES ANALYSIS METHODS: SMA, WMA, EMA, EWMA, AND KALMAN FILTER FOR DATA ANALYSIS","authors":"Volodymyr Lotysh, Larysa Gumeniuk, Pavlo Humeniuk","doi":"10.35784/iapgos.3652","DOIUrl":"https://doi.org/10.35784/iapgos.3652","url":null,"abstract":"In time series analysis, signal processing, and financial analysis, simple moving average (SMA), weighted moving average (WMA), exponential moving average (EMA), exponential weighted moving average (EWMA), and Kalman filter are widely used methods. Each method has its own strengths and weaknesses, and the choice of method depends on the specific application and data characteristics. It is important for researchers and practitioners to understand the properties and limitations of these methods in order to make informed decisions when analyzing time series data. This study investigates the effectiveness of time series analysis methods using data modeled with a known exponential function with overlaid random noise. This approach allows for control of the underlying trend in the data while introducing the variability characteristic of real-world data. The relationships were written using scripts for the construction of dependencies, and graphical interpretation of the results is provided.","PeriodicalId":53131,"journal":{"name":"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136342191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Natali Fedotova, Maksim Procenko, Iryna Baranowa, Switłana Waszczenko, Yaroslava Dehtiarenko
In the field of computer game development, there are numerous optimization methods that help to significantly reduce the number of calculations that the game system performs while playing the game. In its turn, this allows to display increasingly realistic graphics. The paper presents the performed analysis of general optimization methods used in the game engine Unreal Engine, such as Distance Culling, Occlusion Culling, Frustum Culling, LODs, Level Streaming, and the Nanite System. The main factors such as resource intensity, visual quality, number of objects, and scale have been determined. The research results demonstrate that properly applied optimization methods can improve game performance and reduce the computational load on the system, which is crucial both functionally and aesthetically.
{"title":"RESEARCH ON CALCULATION OPTIMIZATION METHODS USED IN COMPUTER GAMES DEVELOPMENT","authors":"Natali Fedotova, Maksim Procenko, Iryna Baranowa, Switłana Waszczenko, Yaroslava Dehtiarenko","doi":"10.35784/iapgos.3828","DOIUrl":"https://doi.org/10.35784/iapgos.3828","url":null,"abstract":"In the field of computer game development, there are numerous optimization methods that help to significantly reduce the number of calculations that the game system performs while playing the game. In its turn, this allows to display increasingly realistic graphics. The paper presents the performed analysis of general optimization methods used in the game engine Unreal Engine, such as Distance Culling, Occlusion Culling, Frustum Culling, LODs, Level Streaming, and the Nanite System. The main factors such as resource intensity, visual quality, number of objects, and scale have been determined. The research results demonstrate that properly applied optimization methods can improve game performance and reduce the computational load on the system, which is crucial both functionally and aesthetically.","PeriodicalId":53131,"journal":{"name":"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136279463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The scheme of dynamic management of traffic and activity of message sources with different priority of service is considered. The scheme is built on the basis of the neuroprognostic analysis model and the gradient descent method. For prediction and early detection of overload, the apparatus of the general theory of sensitivity with indirect feedback and control of activity of message sources is used. The control algorithm is started at the bottleneck of the network node. It uses a recursive prediction approach where the neural network output is referred to as many steps as defined by a given prediction horizon. Traffic with a higher priority is served without delay using the entire available bandwidth. Low-priority traffic will use the remaining bandwidth not used by higher-priority traffic. An algorithm for estimating the maximum available bandwidth of a communication node for traffic with a low service priority has been developed. This approach makes it possible to improve the efficiency of channel use without affecting the quality of service for high-priority traffic.
{"title":"OVERLOAD AND TRAFFIC MANAGEMENT OF MESSAGE SOURCES WITH DIFFERENT PRIORITY OF SERVICE","authors":"Valerii Kozlovskyi, Valerii Kozlovskyi, Andrii Toroshanko, Oleksandr Toroshanko, Natalia Yakumchuk","doi":"10.35784/iapgos.3505","DOIUrl":"https://doi.org/10.35784/iapgos.3505","url":null,"abstract":"The scheme of dynamic management of traffic and activity of message sources with different priority of service is considered. The scheme is built on the basis of the neuroprognostic analysis model and the gradient descent method. For prediction and early detection of overload, the apparatus of the general theory of sensitivity with indirect feedback and control of activity of message sources is used. The control algorithm is started at the bottleneck of the network node. It uses a recursive prediction approach where the neural network output is referred to as many steps as defined by a given prediction horizon. Traffic with a higher priority is served without delay using the entire available bandwidth. Low-priority traffic will use the remaining bandwidth not used by higher-priority traffic. An algorithm for estimating the maximum available bandwidth of a communication node for traffic with a low service priority has been developed. This approach makes it possible to improve the efficiency of channel use without affecting the quality of service for high-priority traffic.","PeriodicalId":53131,"journal":{"name":"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136279617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Road accidents are concerningly increasing in Andhra Pradesh. In 2021, Andhra Pradesh experienced a 20 percent upsurge in road accidents. The state's unfortunate position of being ranked eighth in terms of fatalities, with 8,946 lives lost in 22,311 traffic accidents, underscores the urgent nature of the problem. The significant financial impact on the victims and their families stresses the necessity for effective actions to reduce road accidents. This study proposes a framework that collects accident data from regions, namely Patamata, Penamaluru, Mylavaram, Krishnalanka, Ibrahimpatnam, and Gandhinagar in Vijayawada (India) from 2019 to 2021. The dataset comprises over 12,000 records of accident data. Deep learning techniques are applied to classify the severity of road accidents into Fatal, Grievous, and Severe Injuries. The classification procedure leverages advanced neural network models, including the Multilayer Perceptron, Long-Short Term Memory, Recurrent Neural Network, and Gated Recurrent Unit. These models are trained on the collected data to accurately predict the severity of road accidents. The project study to make important contributions for suggesting proactive measures and policies to reduce the severity and frequency of road accidents in Andhra Pradesh.
{"title":"URBAN TRAFFIC CRASH ANALYSIS USING DEEP LEARNING TECHNIQUES","authors":"Mummaneni Sobhana, Nihitha Vemulapalli, Gnana Siva Sai Venkatesh Mendu, Naga Deepika Ginjupalli, Pragathi Dodda, Rayanoothala Bala Venkata Subramanyam","doi":"10.35784/iapgos.5350","DOIUrl":"https://doi.org/10.35784/iapgos.5350","url":null,"abstract":"Road accidents are concerningly increasing in Andhra Pradesh. In 2021, Andhra Pradesh experienced a 20 percent upsurge in road accidents. The state's unfortunate position of being ranked eighth in terms of fatalities, with 8,946 lives lost in 22,311 traffic accidents, underscores the urgent nature of the problem. The significant financial impact on the victims and their families stresses the necessity for effective actions to reduce road accidents. This study proposes a framework that collects accident data from regions, namely Patamata, Penamaluru, Mylavaram, Krishnalanka, Ibrahimpatnam, and Gandhinagar in Vijayawada (India) from 2019 to 2021. The dataset comprises over 12,000 records of accident data. Deep learning techniques are applied to classify the severity of road accidents into Fatal, Grievous, and Severe Injuries. The classification procedure leverages advanced neural network models, including the Multilayer Perceptron, Long-Short Term Memory, Recurrent Neural Network, and Gated Recurrent Unit. These models are trained on the collected data to accurately predict the severity of road accidents. The project study to make important contributions for suggesting proactive measures and policies to reduce the severity and frequency of road accidents in Andhra Pradesh.","PeriodicalId":53131,"journal":{"name":"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136280593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Unsatisfactory feat of the photo-voltaic cell is solitary in every of the foremost issues among the promotion of PV technology. A vital strand changing cell performance is operative temperature of the cell. The voltage of the cell, declines near directly with a rise in the operative temperature of the photo-voltaic cell. The temperature condition on the in-operative surface of a photo-voltaic panel remains usually 22–30°C beyond the normal temperature conditions. Upon the premise concerning those issues, the potency of the photo-voltaic cell will be refined by sustaining their operative temperatures as low as possible. This paper portrays a technique of PV/solar panel cooling using convection generated by the chimney effect. This paper considers the diminution of warmth from the Photo-voltaic panel for both active and inactive conditions.
{"title":"PV PANEL COOLING USING STACK EFFECT","authors":"Kudith Nageswara Rao, Ganesamoorthy Rajkuma","doi":"10.35784/iapgos.3756","DOIUrl":"https://doi.org/10.35784/iapgos.3756","url":null,"abstract":"Unsatisfactory feat of the photo-voltaic cell is solitary in every of the foremost issues among the promotion of PV technology. A vital strand changing cell performance is operative temperature of the cell. The voltage of the cell, declines near directly with a rise in the operative temperature of the photo-voltaic cell. The temperature condition on the in-operative surface of a photo-voltaic panel remains usually 22–30°C beyond the normal temperature conditions. Upon the premise concerning those issues, the potency of the photo-voltaic cell will be refined by sustaining their operative temperatures as low as possible. This paper portrays a technique of PV/solar panel cooling using convection generated by the chimney effect. This paper considers the diminution of warmth from the Photo-voltaic panel for both active and inactive conditions.","PeriodicalId":53131,"journal":{"name":"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136279605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article introduces an enhanced energy management strategy that employs the state of charge (SoC) of batteries in standalone DC microgrids with photovoltaic (PV) modules. Efficient energy management is crucial to ensure uninterrupted power supply to the load units in microgrids. To address the challenges posed by external factors such as temperature fluctuations and variations in solar irradiance, energy storage systems are deployed to compensate for the negative effects of the external factors on the output power of PV modules. The proposed approach takes into account various parameters of the microgrid elements, including the available power from the sources, demand power, and the SoC of batteries, in order to develop an efficient energy control mechanism with load-shedding capability. By considering these parameters, the strategy aims to optimize the utilization of available resources while ensuring a reliable power supply to the connected loads. The SoC of the batteries plays a critical role in determining optimal charging and discharging profiles, enabling effective energy management within the microgrid. To evaluate the effectiveness of the proposed approach, an algorithm is designed and simulations are conducted. The proposed algorithm utilizes a hybrid approach by combining power and SoC-based methods for efficient control. Through analysis of the simulation results, it is found that the presented approach is capable of delivering the intended load power while increasing the life cycle of the batteries with the pre-defined SoC levels.
{"title":"A STANDALONE DC MICROGRID ENERGY MANAGEMENT STRATEGY USING THE BATTERY STATE OF CHARGE","authors":"Elvin Yusubov, Lala Bekirova","doi":"10.35784/iapgos.5320","DOIUrl":"https://doi.org/10.35784/iapgos.5320","url":null,"abstract":"This article introduces an enhanced energy management strategy that employs the state of charge (SoC) of batteries in standalone DC microgrids with photovoltaic (PV) modules. Efficient energy management is crucial to ensure uninterrupted power supply to the load units in microgrids. To address the challenges posed by external factors such as temperature fluctuations and variations in solar irradiance, energy storage systems are deployed to compensate for the negative effects of the external factors on the output power of PV modules. The proposed approach takes into account various parameters of the microgrid elements, including the available power from the sources, demand power, and the SoC of batteries, in order to develop an efficient energy control mechanism with load-shedding capability. By considering these parameters, the strategy aims to optimize the utilization of available resources while ensuring a reliable power supply to the connected loads. The SoC of the batteries plays a critical role in determining optimal charging and discharging profiles, enabling effective energy management within the microgrid. To evaluate the effectiveness of the proposed approach, an algorithm is designed and simulations are conducted. The proposed algorithm utilizes a hybrid approach by combining power and SoC-based methods for efficient control. Through analysis of the simulation results, it is found that the presented approach is capable of delivering the intended load power while increasing the life cycle of the batteries with the pre-defined SoC levels.","PeriodicalId":53131,"journal":{"name":"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136279780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniyar Jarykbassov, Petr Lezhniuk, Iryna Hunko, Vladyslav Lysyi, Lyubov Dobrovolska
A method of forecasting the balance of electricity consumption of urban development objects, civil purposes using discrete macromodels is proposed. We consider the power supply system (PSS) of the district, which is characterised by power supply from general-purpose power grids, as well as having its own generation of electricity from renewable energy sources (RES). Such a local electric power system (LES) under certain conditions can be operated as an independent balanced electrical facility. For optimal operation of the LES under these conditions, it is necessary to predict its power consumption schedules. The proposed macromodelling method allows to develop deterministic models of power consumption with the required accuracy on the basis of retrospective information without the use of data preprocessing procedures. The solution to the problem of forecasting electricity consumption schedules is simplified by using only basic or deterministic characteristics in the construction of the model. These include fractal properties of PSS load schedules.
{"title":"MACROMODELING OF LOCAL POWER SUPPLY SYSTEM BALANCE FORECASTING USING FRACTAL PROPERTIES OF LOAD AND GENERATION SCHEDULES","authors":"Daniyar Jarykbassov, Petr Lezhniuk, Iryna Hunko, Vladyslav Lysyi, Lyubov Dobrovolska","doi":"10.35784/iapgos.4457","DOIUrl":"https://doi.org/10.35784/iapgos.4457","url":null,"abstract":"A method of forecasting the balance of electricity consumption of urban development objects, civil purposes using discrete macromodels is proposed. We consider the power supply system (PSS) of the district, which is characterised by power supply from general-purpose power grids, as well as having its own generation of electricity from renewable energy sources (RES). Such a local electric power system (LES) under certain conditions can be operated as an independent balanced electrical facility. For optimal operation of the LES under these conditions, it is necessary to predict its power consumption schedules. The proposed macromodelling method allows to develop deterministic models of power consumption with the required accuracy on the basis of retrospective information without the use of data preprocessing procedures. The solution to the problem of forecasting electricity consumption schedules is simplified by using only basic or deterministic characteristics in the construction of the model. These include fractal properties of PSS load schedules.","PeriodicalId":53131,"journal":{"name":"Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136280441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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