Кафедра електричної інженерії
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Item type:Наукова стаття, Efficient Energy Management for the Smart Sustainable City Multifloor Manufacturing Clusters: A Formalization of the Water Supply System Operation Conditions Based on Monitoring Water Consumption Profiles(Basel, Switzerland: MDPI AG, 2023) Davydenko, LiudmylaThis study is devoted to improving the energy efficiency of urban infrastructure systems (UISs), in particular, the centralized water supply of a city multifloor manufacturing cluster (CMFMC), by developing the principles of effective energy consumption management. The CMFMCs are located in the residential area of a megapolis and include manufacturing and service enterprises, residential and non-residential buildings, and a city logistics node. Demand monitoring and identification of the influence of seasonal and social environmental factors on its fluctuations is considered as a tool for identifying changes in the operating conditions of the water supply system (WSS) for the CMFMC facilities. To identify the typical operating conditions of water supply facilities, an approach is proposed that involves the analysis of daily water consumption profiles (WCPs). The formation of a database, the formation of groups of the same type of daily WCPs, and the construction of typical daily WCPs for typical groups and their description are the main stages of the proposed approach. The database contains a set of classification characteristics that describe the daily water consumption and its unevenness, as well as the shape of the daily WCP. The principal component analysis was applied to determine the dominant components of daily water consumption. A set of morphometric parameters was used to describe the shape of the daily WCPs. The methods of cluster and discriminant analysis were used to identify the influence of seasonality and social factors on water consumption and to form groups of the same type of daily WCPs. The analysis of sets of similar type of daily WCPs for typical days of typical seasons was carried out for a formalized description of the typical operating conditions of water supply facilities. The results of the analysis are the clarification of the equations of the dominant components of daily water consumption, the determination of the average values of the characteristics of daily water consumption, and the construction and description of typical daily WCPs for typical operating conditions of water supply facilities. The research results were obtained on the basis of the data of the monitoring systems for water supply enterprises in Ukraine and Poland in 2021–2022. The obtained results are the basis for planning the water supply process and adjusting the operation modes of WSS pumping stations for the CMFMC, as well as planning power consumption for typical operating conditions, which will contribute to increasing the efficiency of water and electricity use.Item type:Наукова стаття, A Decision Support Model for Lean Supply Chain Management in City Multifloor Manufacturing Clusters(Basel, Switzerland: MDPI AG, 2024) Davydenko, LiudmylaCity manufacturing has once again become one of the priority areas for the sustainable development of smart cities thanks to the use of a wide range of green technologies and, first of all, additive technologies. Shortening the supply chain between producers and consumers has significant effects on economic, social, and environmental dimensions. Zoning of city multifloor manufacturing (CMFM) in areas with a compact population in large cities in the form of clusters with their own city logistics nodes (CLNs) creates favorable conditions for promptly meeting the needs of citizens for goods of everyday demand and for passenger and freight transportation. City multifloor manufacturing clusters (CMFMCs) have been already studied quite a lot for their possible uses; nevertheless, an identified research gap is related to supply chain design efficiency concerning CMFMCs. Thus, the main objective of this study was to explore the possibilities of lean supply chain management (LSCM) as the integrated application of lean manufacturing (LM) approaches and I4.0 technologies for customer-centric value stream management based on eliminating all types of waste, reducing the use of natural and energy resources, and continuous improvement of processes related to logistics activities. This paper presents a decision support model for LSCM in CMFMCs, which is a mathematical deterministic model. This model justifies the minimization of the number of road transport transfers within the urban area and the amount of stock that is stored in CMFMC buildings and in CLNs, and also regulating supplier lead time. The model was verified and validated using appropriately selected test data based on the case study, which was designed as a typical CMFM manufacturing system with various parameters of CMFMCs and urban freight transport frameworks. The feasibility of using the proposed model for value stream mapping (VSM) and managing logistics processes and inventories in clusters is discussed. The findings can help decisionmakers and researchers improve the planning and management of logistics processes and inventory in clusters, even in the face of unexpected disruptions.Item type:Наукова стаття, Monitoring of Energy Efficiency of District Heating System Facilities: Methodology for Determining the Energy Baseline(Kishinau: Institute of Power Engineering of the Academy of Sciences of Moldova, 2022) Davydenko, LiudmylaDetermining the energy consumption level is one of the stages of energy efficiency monitor-ing facilities. The aim of the article is to adapt the energy baseline to the operating conditions of the facility in accordance with the ISO 50000 Standards requirements. The methodology for determining the energy baseline was proposed to achieve the goal. The three-stage procedure for forming a set of relevant variables of the energy baseline, which allows taking into account the significance of varia-bles, the possibility of their measurement, controllability and control, and the procedure for construct-ing a multifactorial model of the optimal structure for determining the energy baseline are the main scientific results. This methodology was applied to a boiler house of a district heating system. Rele-vant variables were formed using a three-stage selection of factors that influence the gas consumption efficiency of the boiler house. Combinatorial algorithm of the group method of data handling was used for gas consumption simulation. The search for models of optimal complexity was performed in six classes of basic functions. The selection of better structures of the mathematical model was realized based on the criteria for its appropriateness (regularity, unbiasedness criterion, Schwartz, determina-tion coefficient) and accuracy of the forecast using the morphological criterion. As a result, a multifac-tor mathematical model of optimal structure was obtained. The percent forecasting error did not ex-ceed 1%. The significance of the results lies in the fact that the proposed methodology can be applied to any facility.Item type:Наукова стаття, Short-Term Forecasting of Photovoltaic Solar Power Generation Based on Time Series: Application for Ensure the Efficient Operation of the Integrated Energy System of Ukraine(Kyiv, 2023) Davydenko, LiudmylaOver the last decade, there has been a growing in the dependence of electricity production by solar power plants (SPPs) in Ukraine. Therefore, there is a need to optimize the structure of the energy balance of the state, based on the requirements of energy security and ensure the share of renewable energy at 25%. However, with the development of renewable energy sources (RESs) there is a problem of ensuring the appropriate maneuverability of the power system. This is due to the fact that the structure of generating capacity of the United Power System of Ukraine in terms of effective regulation of frequency and power in the power system is suboptimal. Among the reasons for this, the main ones are unregulated and variable operation of a SPP, which is exacerbated by the lack of tools and approaches for the power generation modes forecasting. That is why the issue of accurate forecasting of the possible electricity generation volume has become acute. However, solar energy forecasting is a rather difficult task, as it largely depends on climatic conditions that change over time. This study presents an analysis and application of the seasonal autoregressive integrated moving average (SARIMA) method to develop a model that can support and provide forecasting the amount of power produced by SPP. Data for the development of the model were obtained from the time series of electricity generation on the example of the SPP in the village of Velyka Dymerka, Kyiv re-gion. The data consisted of more than 26 thousand samples collected from July 1, 2020, to December 31, 2020, which characterize the operating conditions of solar panels with a capacity of 9 MW. This led to the choice of the SARIMA model. The coefficient of determination (R2) for the obtained model was 92%. This indicates the ability of the final model to accurately represent and give forecast based on data set of the SPP power generation.Item type:Наукова стаття, Smart Sustainable Freight Transport for a City Multi-Floor Manufacturing Cluster: A Framework of the Energy Efficiency Monitoring of Electric Vehicle Fleet Charging(Basel, Switzerland: MDPI AG, 2022) Davydenko, LiudmylaThis study focuses on the problem of the efficient energy management of an independent fleet of freight electric vehicles (EVs) providing service to a city multi-floor manufacturing cluster (CMFMC) within a metropolis while considering the requirements of smart sustainable electromobility and the limitations of the power system. The energy efficiency monitoring system is considered an information support tool for the management process. An object-oriented formalization of monitoring information technology is proposed which has a block structure and contains three categories of classes (information acquisition, calculation algorithms, and control procedures). An example of the implementation of the class “Operation with the electrical grid” of information technology is presented. The planning of the freight EVs charging under power limits of the charging station (CS) was carried out using a situational algorithm based on a Fuzzy expert system. The situational algorithm provides for monitoring the charging of a freight EV at a charging station, taking into account the charge weight index (CWI) assigned to it. The optimization of the CS electrical load is carried out from the standpoint of minimizing electricity costs and ensuring the demand for EV charging without going beyond its limits. A computer simulation of the EV charging mode and the CS load was performed. The results of modeling the electrical grid and CS load using the proposed algorithm were compared with the results of modeling using a controlled charging algorithm with electrical grid limitations and an uncontrolled charging algorithm. The proposed approach provides a reduction in power consumption during peak hours of the electrical grid and charging of connected EVs for an on-demand state of charge (SOC).